SEO in 2026 is expanding, not changing. Traditional search still matters, but now SEO also includes AI-driven discovery, social platforms, and chatbots. The principles are the same, like clarity, structure, authority, and relevance, but the platforms are multiplying. We surveyed 59 SEOs to see how they’re handling these changes.
Some have less than a year of experience. Others have been in the field for over a decade. Their answers show an industry figuring things out. A few are ahead of the curve, but most are still catching up.
The best SEOs aren’t just reacting to AI. They’re using it to strengthen what already works: technical foundations, high-quality content, and real authority. Others are stuck debating whether SEO should even keep its name.
Here’s what stood out, and where Yoast fits into the conversation of what SEO means in 2026.
You can find the full results, with more questions and deeper insights from Yoast’s principal SEOs, Carolyn Shelby and Alex Moss, in a downloadable PDF. Sign up below!
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51% of respondents consider SEO to be “evolving”. 33% say it’s “thriving”. Only 10% think it’s “declining”.
This is an interesting divide, but it’s not random. In the results, those with 10+ years of experience say SEO is thriving, while newcomers say it is not. It might be that experts know the landscape better and see change as a constant.
Alex Moss’s take:“SEO has always adapted to changes in the SERP, and now it’s adapting again. The traditional SERP is gone, but SEO isn’t.”
Carolyn Shelby’s take:“SEO is evolving, but not because its fundamentals are breaking. The interfaces between users and information are changing. Search is no longer confined to ten blue links, but the need for structured, relevant, trustworthy content hasn’t diminished.”
The Yoast Perspective: We think SEO isn’t going anywhere, but there are changes happening. Traditional search from Google and Bing still drives traffic, but AI-driven discovery from LLM-powered assistants shapes perception and discovery. Therefore, the best SEOs don’t choose sides in this fight; they are mastering both directions.
2. Keep the name Search Engine Optimization
39% say SEO should be relabeled “Search Everywhere Optimization”. Only 32% want to keep “Search Engine Optimization”.
Big support for relabeling SEO, and even among veterans, 41% prefer Search Everywhere Optimization. Of course, this doesn’t mean that we should do this.
Alex Moss’s take:“The term ‘SEO’ will stay. The role will widen to include AI and other disciplines, but the name doesn’t need to change.”
Carolyn Shelby’s take:“The term ‘SEO’ still holds shared meaning, credibility, and market recognition. There’s no strong evidence that rebranding the discipline itself is necessary or beneficial. Responses favoring ‘Search Everywhere Optimization’ reflect where SEO outcomes now surface, not a fundamentally different practice.”
The Yoast Perspective: We at Yoast don’t think the term SEO is broken. Yes, there is a lot of change happening, especially in search, with AI overviews, chatbots, and social media platforms, but what about the core SEO work? You still have to focus on technical foundations, content quality, brand building, and authority.
‘Search Everywhere Optimization’ might describe where SEO happens, but it doesn’t change what SEO is. The name ‘SEO’ still works, but we just need to explain how it applies to AI and social platforms.
3. Good SEO is LLM optimization
64% agree LLM optimization is essentially the same as traditional SEO. 59% aren’t even actively optimizing for LLMs.
You might call this laziness, but you could also call it efficiency. It oftentimes comes down to the same thing.
There’s also the 9% who strongly disagree with this statement. These respondents say LLMs prioritize synthesis over rankings, so focusing on structured data and brand mentions makes more sense for them. Of course, they are not wrong, but they don’t contradict what others have said. LLMs don’t require new tactics; they just reward the same SEO principles more strictly.
Alex Moss’s take:“If you’re undertaking good SEO, you’re already optimizing well for LLMs. The tactics don’t change—just the audience.”
Carolyn Shelby’s take:“The same practices that make content discoverable and trustworthy for search engines also make it usable for LLMs. The confusion arises when people treat LLMs as a completely separate system. In reality, LLM visibility rewards clarity, relevance, and authority—all long-standing SEO principles.”
LLM optimization isn’t a separate discipline because it’s SEO for AI. The same principles apply: clarity, structure, and authority. The difference? AI systems are less forgiving of mediocre content, so the bar for quality is higher.
4. Rankings still matter, but not like they used to
52% say rankings are “equally important” as before. 30% say they’re “less important”.
This is a sensible shift. Google’s AI overviews and other zero-click results mean visibility does not equal traffic. For AI systems, rankings are still an authority signal.
Alex Moss’s take:“Traditional rankings are still important because agents still search the web to ingest information. If you aren’t visible there, it’s less likely an agent will identify and select you into their responses.”
Carolyn Shelby’s take:“Rankings still matter, but they are no longer the end goal. They are a proxy for visibility, not a guarantee of impact.”
The Yoast Perspective: We need to stop obsessing over ranking number one, so start tracking visibility and presence. Check whether you are cited in AI-driven answers, and try to be mentioned in industry discussions. AI visibility and citations are the new rankings.
5. Organic traffic is still king, but for how long?
55% say “organic traffic” is their top metric. Yet 49% cite “reducing organic clicks” as their biggest challenge.
We see this as the great paradox of 2026. Traffic is down, but the value of that traffic could be up. You might get less traffic, but the clicks that do happen have a better intent.
Carolyn Shelby’s take: “As AI reduces the need for some visits, success looks like being represented correctly rather than merely visited. Visibility in AI overviews doesn’t always drive clicks, but it builds legitimacy. Being included signals that you’re a credible source, even when users don’t click.”
Our advice:
Work on AI visibility, as this is the new SEO metric. Just as rankings show your visibility in traditional search, citations in AI overviews show your authority in AI-driven discovery. Track it alongside rankings and traffic
Keep an eye on branded search volume to learn whether people are looking for you by name
Monitor citations to see if others are referencing your content online
6. Content saturation is a big threat
39% say “competing with AI-generated content” is their top challenge. Only 4% cite a “talent gap.”
We know AI can write bad content. But it’s a bigger challenge when AI writes good enough content at scale. This will flood the web with noise, making it hard to penetrate.
Alex Moss’s take:“AI-generated content is artificial. Humans connect with stories, not regurgitated lists.”
Carolyn Shelby’s take:“AI doesn’t change what good content is, but just raises the bar. Mediocrity doesn’t just rank lower; it disappears.”
Our advice:
Focus on building your EEAT, because AI can’t fake real-world expertise and authority
Prioritize quality over quantity, as a single great piece of content can beat ten average ones
Use AI, but be careful and always use it as a tool, not as a replacement
7. Most SEOs are ignoring a fast-growing search channel
Traditional search (Google/Bing) is still #1. But TikTok search ranks #5, lower than Amazon.
This might be something of a blind spot for many. Younger generations use TikTok and other video platforms for entertainment, recommendations, tutorials, and even B2B advice.
Alex Moss’s take:“Social platforms influence how LLMs perceive freshness and authority. Ignoring them means missing out on signals that AI systems value.”
Carolyn Shelby’s take:“You don’t need to rank on TikTok, but you do need to be discoverable there. LLMs scrape social platforms for real-world signals.”
The Yoast Perspective: SEO now includes social platforms like TikTok. You don’t need to rank there, but you do need to be discoverable, because LLMs scrape these platforms for fresh, authoritative content. A great video channel can boost your authority in AI responses.
Our advice:
Repurpose content for video platforms like TikTok and YouTube
Check brand mentions in these platforms
Improve your video SEO in general
What Yoast’s experts really think
The data shows trends, but the real wisdom comes from Yoast’s SEO leaders, Carolyn Shelby and Alex Moss. Here is a small peek at the insights they share about the various debates:
On “Search Everywhere Optimization”:
Alex: “The term ‘SEO’ will stay. The role will widen, but the name doesn’t need to change.”
Carolyn: “Rebranding risks fragmenting understanding. ‘SEO’ is already well-established outside the industry.”
On the future of SEO metrics:
Alex: “As we move from being seen to being selected, visits don’t hold the same value they used to. The business goal should be the most important metric.”
Carolyn: “Visibility in AI overviews doesn’t always drive clicks, but it builds legitimacy. Being included signals that you’re a credible source.”
On rankings vs. influence:
Alex: “Rankings still matter because agents search the web to ingest information.”
Carolyn: “Rankings are a proxy for visibility, not a guarantee of impact. Focus on presence.”
On the role of SEOs in 2026:
Alex: “100% all three: marketers, brand builders, and SEO specialists. Brand and marketing have become intertwined with SEO as our role expands.”
Carolyn: “A blended mindset is essential. SEO can’t operate in isolation from brand, product, or communications.”
Do you want to read the full story?
These insights are just a small taster for you. In the full Yoast SEO report, you’ll find much more:
Includes the full answers to all 25 questions
In-depth commentary from Yoast’s SEO experts, Carolyn Shelby and Alex Moss
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00Dubado Solutionshttp://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.pngDubado Solutions2026-04-21 10:29:142026-04-21 10:29:14The Yoast Perspective 2026: 7 things we learned from the SEO industry
The Ubersuggest Chrome Extension surfaces keyword data like volume, CPC, and competition scores directly on Google, YouTube, and Amazon search results pages without leaving your browser.
The extension works on both Windows and Mac, and activates automatically once installed.
YouTube and Amazon support expands your keyword research beyond Google, covering video and ecommerce search behavior in one tool.
The extension connects to the full Ubersuggest platform, where AI visibility features help you track how your brand and content appear in AI-generated search results.
Traditional organic rankings are no longer the whole picture. Ubersuggest helps you monitor visibility across both classic search and the AI-powered results shaping where traffic goes next.
The Ubersuggest Chrome Extension has seen some significant updates over the years, and the latest version is the most useful one yet.
The improvements go well beyond a simple refresh. Keyword research is faster, more intuitive, and built around how SEO professionals actually work. This post breaks down what the extension does, what’s changed, and how to get the most out of it.
Here’s what Ubersuggest Chrome can do for you…
The Ubersuggest Chrome Extension brings SEO data directly into your browser, so you’re not jumping between tabs or tools to get the numbers you need.
Once installed, the extension activates automatically whenever you run a Google search. Right there on the results page, you’ll see keyword data layered in: monthly search volume, cost-per-click (CPC), and competition scores for your search term. No extra steps required.
Here’s how to put it to work across a few common use cases:
Researching keywords: Search any term on Google and the extension surfaces volume and difficulty data instantly. Use that to qualify whether a keyword is worth targeting before you invest time in content.
Scoping out the competition: Click into any organic result directly from the SERP and the extension pulls up domain-level authority data. It’s a fast way to size up who you’re up against. For a deeper look, pair it with a full competitor analysis to understand where gaps exist.
Finding related keywords: The extension also surfaces keyword suggestions tied to your search. These are useful for building out topic clusters or identifying secondary terms to work into existing content.
It works the same way whether you’re on Windows or Mac, as long as you’re running Chrome. The experience is consistent across both operating systems, so the workflow above applies regardless of your setup.
Keyword research beyond Google
Google isn’t the only place people search. YouTube is the second-largest search engine in the world, and Amazon drives more product searches than Google does in the ecommerce space. The Ubersuggest Chrome Extension works across both platforms, giving you keyword data wherever your audience is actually searching.
On YouTube, the extension surfaces keyword data directly as you type. Search any term and you’ll see volume and competition data on suggested keywords in real time.
Click “view all” next to the search bar for a deeper breakdown. You’ll see monthly search volume trends over the past 12 months, seasonal patterns, competition scores, CPC data, click rates, and audience age ranges. The extension also shows whether a keyword skews toward mobile or desktop searches, which matters for conversion strategy. Desktop searches tend to convert at higher rates, so prioritizing those terms can sharpen your targeting.
The right-hand side of any YouTube results page also surfaces related keyword suggestions, giving you additional terms to evaluate without leaving the page.
Amazon works a little differently. Rather than overlaying data on the results page, the extension surfaces keyword information directly on search suggestions, keeping the shopping experience intact while still giving you the data you need for ecommerce keyword research.
Think of the extension as your on-ramp to smarter research across the open web. The data it surfaces on Google, YouTube, and Amazon is just the starting point. The full Ubersuggest platform goes deeper, with features like AI visibility tracking and AI-powered keyword overviews that help you understand not just where you rank, but how AI search surfaces your brand. Those capabilities live in the platform, and the extension is the fastest way to get there.
What does that mean for you?
Search has changed. Google’s AI Overviews now answer questions directly on the results page, and platforms like TikTok, YouTube, and Amazon have become legitimate search destinations in their own right. Ranking on Google alone no longer guarantees visibility.
That’s where Ubersuggest’s newer AI-focused features become relevant. The platform can show you how your brand and content are surfacing across AI-generated results, not just traditional organic rankings. That kind of insight is hard to get anywhere else, and it’s increasingly necessary for staying competitive.
The Chrome Extension is your entry point into all of it. It gives you real-time keyword data as you browse, and connects directly to the Ubersuggest platform where the deeper AI visibility analysis lives. Together, they give you a clearer picture of where you stand across both traditional and AI-powered search.
In short: the extension makes everyday research faster, and the platform helps you think bigger about where search is headed.
But wait, There’s more…
There is also one other important change made to the extension that you may have already noticed if you use Google on a regular basis.
When you search on Google, there is now traffic estimations under each URL.
This traffic estimation is for organic search traffic and it is done on a domain level. Eventually, we will tweak it to be page-based and even show you the other keywords each page ranks for… but for now, we are providing you with organic traffic estimates for each domain.
And if you are more of a visual person, in the right-hand sidebar you can also see the traffic estimation for any result in the top 10.
FAQs
How do I use the Ubersuggest Chrome extension?
Once you download and install the Ubersuggest Chrome Extension, it runs automatically in the background. Go to Google and run any search, you’ll see keyword data including monthly search volume, CPC, and competition scores layered directly onto the results page. The same applies on YouTube and Amazon. Search a term and the extension surfaces keyword suggestions with supporting data as you type. No setup or configuration is needed beyond the initial install.
Conclusion
Already using the Ubersuggest Chrome extension? It’s still a great way to get quick insights as you browse.
But here’s the real play: use it as your entry point into the full platform.
When you click through, you’ll unlock deeper keyword data, competitor insights, and our newer AI features that help you generate content ideas, analyze pages, and move faster without guessing.
Don’t have the extension yet? Install it here and start turning everyday browsing into real SEO opportunities.
New privacy laws will require marketers to think carefully about how they collect and manage data.
While many marketers aren’t overly concerned about the depreciation of third-party cookies, it’s recommended to explore cookieless solutions like Enhanced Conversions.
Several emerging platforms are on the rise, including gaming networks, digital out-of-home (DOOH) ads, connected TV (CTV) ads, and Brave Ads.
Paid social is as popular as ever thanks to the evolution of social media platforms as search engines and e-commerce hubs.
Want to mix up your paid ads strategy in 2026? Try user-generated content (UGC) or conversational advertising.
Short-form videos on TikTok or YouTube Shorts grab attention fast—just make sure your first five seconds are strong to hook viewers.
Premium placements like TikTok Pulse and YouTube Select allow advertisers to position their brands alongside trending, top-performing content for added credibility.
AI tools like Performance Max or Jasper can optimize bidding, generate creative, and streamline campaigns, helping marketers save time and improve ROI.
Want to upgrade your paid media strategy for the rest of 2026 and beyond? Whether you want to take advantage of AI, discover new platforms, or prepare to advertise in a world without third-party cookies, this guide is here to help.
Just as our Search Engine Rewind did for SEO trends, this guide combines expert insights from the paid media team at NP Digital and other paid marketers in the field.
You’ll learn which new paid media platforms you should be taking advantage of, how the paid social landscape is shifting, and the best practices you should focus on.
So, if you’re ready to discover the biggest paid media trends of 2026, read on.
Methodology
The insights in this guide come from two super knowledgeable resources.
The first is the team at NP Digital, which includes industry experts with decades of experience in paid search, social, and programmatic advertising.
The second is a group of 309 paid marketers who work at companies with over 250 employees. We surveyed marketers from across the U.S. to understand how they see the paid search landscape changing.
We asked this group about a range of paid search topics, such as emerging platforms, new targeting strategies, and the impact of artificial intelligence.
Privacy Concerns and Expanded Privacy Regulations
New privacy laws are changing how platforms and advertisers collect and use consumer data. A slew of U.S. states have recently enacted data privacy laws, including California (which amended and expanded the California Consumer Privacy Act to the California Privacy Rights Act), Colorado, Florida, Montana, Oregon, and Texas.
Google has reacted by adjusting its data collection practices. It has enabled Restricted Data Processing (RDP), which means the search platform shows only non-personalized ads to users in these states.
In Europe, the Digital Markets Act (DMA), which became applicable halfway through 2023, means major platforms like Google and Meta need explicit consent to collect and use personal data from consumers in the European Economic Area (EEA). That’s unlike most state-based privacy laws in the U.S., which let users opt out of personalized ads, but still displays them by default.
Data protection laws are also being introduced across Africa, the Middle East, and Asia. In most cases, businesses will need to introduce a cookie banner that lets users choose their preferences. You can also implement Google’s consent mode v2, which enables you to collect conversion data through a tag-based system and comply with regulations.
While platforms like Google generally help companies comply with privacy laws, you may find it easier to use a compliance management platform (CMP) that streamlines your paid media compliance efforts.
One privacy-related issue marketers don’t have to worry about just yet is the deprecation of third-party cookies in Chrome. Google has reversed its decision to remove cookies from its browser in response to concerns from the U.K.’s Competition and Markets Authority, along with demand from advertisers. Instead, it will continue to work on its Privacy Sandbox.
Even so, the majority (57.9 percent) of our survey respondents felt that the deprecation of cookies wouldn’t impact their paid marketing plans much.
That might be because they’ve already switched to less cookie-focused tracking methods like Google Ads’ enhanced conversion tracking. This method works in addition to your existing conversion tags, sending hashed first-party data from your website to Google in a privacy-focused manner.
The most popular paid marketing channels can be expensive. Four in 10 of our respondents said their pay-per-click (PPC) costs had increased over the past year, yet almost half (49.6 percent) of that group planned to double down on spending.
Cost per click (CPC) may become even more expensive due to the upcoming U.S. presidential election. The majority (70 percent) of marketers in our survey think the presidential election will impact paid advertising. This may stem from the fact that the results of presidential elections tend to have ripple effects in the business world as companies react to the potential economic policies of the incoming administration.
Those who say they are seeing higher PPC costs are more likely to seek out new forms of paid marketing—and there are plenty of up-and-coming paid media platforms and channels to choose from.
We’ve highlighted five of these new frontiers below.
Gaming
Gaming is a $350 billion industry with a highly engaged audience, so it’s no surprise that gaming ads are becoming more popular.
Our survey found that 57.3% percent of marketers were advertising there, with Twitch, Discord, and in-game ads as the most popular channels.
If you want to get started on Twitch, there are eight formats to choose from:
Headliner
Homepage Carousel
Medium Rectangle
Stream Display Ads
Streamable Ads
Super Leaderboard Ads
Twitch Premium Video Ads
First Impression Takeover
Of these formats, brands will be most interested in:
Headliner ads, which appear behind the paid-for carousel ads used by streamers
Stream display ads, which appear during live streams
Super leaderboard ads, which appear at the top of the page
Twitch premium video ads, short pre-roll, and mid-roll unskippable video ads
Note that you have the option to run self-service ads on Twitch through Amazon’s DSP, similar to the self-serve platforms of Meta and Google.
If you’d rather target gamers mid-game, a solution like Activision Blizzard’s Rewarded Video may do the trick.
These user-initiated in-game ads (like the Ben & Jerry’s ad above) let you connect with highly engaged gamers at key moments in combination with desirable player rewards they can use to advance through their game of choice. Brands can also use interactive end cards to increase audience engagement and drive higher click-through rates.
In-App Ads
In-app advertising is a win-win for brands and developers. It gives developers a source of additional revenue while letting brands reach targeted and engaged audiences.
Spending on this form of paid media is forecast to reach $352.7 billion in 2024 and $534.1 billion by 2029.
In-app advertising comes in various forms, including:
Interstitial ads
Video ads
Banner ads
Native ads
Here’s an example of an interstitial ad from Google’s AdMob network:
Advertisers can choose from a range of pricing models, too:
Cost per mille (CPM): Pay for every thousand views.
Cost per click (CPC): Only pay when your ad is clicked.
Cost per view (CPV): Only pay when users watch your video ad.
Cost per install (CPI): An app-specific pricing model through which you only pay when users install your app.
Cost per action (CPA): Only pay when users complete a predefined action.
In-app ads are an ideal and effective way for brands to target smartphone users. Research shows 42.6 percent of consumers have bought something after clicking on an in-app ad, and 56.5 percent of consumers have downloaded an app after an in-app ad recommended it.
The other great thing about in-app ads is that you aren’t just limited to using a single advertising platform. There are several to choose from, including Google’s AdMob, AppLovin, Publift, PropellerAds, and RevX.
Digital Out-Of-Home (DOOH)
Digital out-of-home media (DOOH) is one of the fastest-growing paid media sectors. Used by over 43 percent of respondents, it was the second most popular trending paid media option in our survey.
DOOH is a form of dynamic and data-driven outdoor advertising. Brands can tailor ads based on things like the time of day, the location of the signage, and even the weather. DOOH includes digital billboards and outdoor signage—as large as the billboards in Times Square or as small as the sign at your local bus stop.
DOOH offers several benefits over both online ads and traditional outdoor media:
There are no online ad blockers, meaning consumers will always be exposed to your ad.
You can engage consumers close to the point of sales with geofenced advertising.
Signage is dynamic, allowing brands to only pay for their ads to be shown at specific times of the day.
DOOH advertising isn’t perfect. It’s much harder to measure than online advertising since there’s no way of knowing for sure how many people walked past your ad or saw it. Inventory is also spread between multiple platforms, which can make campaigns hard to manage.
Connected TV (CTV) and Over-the-Top (OTT) Advertising
Want to reach consumers while they are watching TV? Connected TV ads and over-the-top advertising are two emerging channels to try.
Some use these two terms interchangeably, but they are slightly different.
Connected TV (CTV) advertising delivers targeted ads through internet-connected smart TVs. Over-the-top (OTT) advertising delivers ads through video streaming services like Hulu and Paramount+.
Regardless of which paid media format you use, both types of advertising have advantages over traditional TV ads.
Unlike traditional TV ads, which have to appeal to a broad audience, CTV ads can be hyperpersonalized and targeted. Brands can target audiences based on their viewing interests, for example, as well as their location and the time of day.
These ads are also much more measurable than traditional TV ads. Brands can track viewing, engagement, and conversion metrics like return on ad spend (ROAS), cost per completed view (CPCV), and gross rating points (GRPs) to optimize campaigns in real time.
CTV also has integrated ad buying options at your fingertips through Microsoft Advertising. Advertisers can manage CTV campaigns alongside search and display ads, simplifying ad management and removing the need for separate DSPs. Other benefits include:
Easy setup
No onboarding fees
Budget flexibility
Impression-based remarketing
Cohesive messaging across CTV and other formats
Leverages Microsoft’s vast first-party data to enhance personalization and performance.
CTV ads and over-the-top advertising were used by 40.8 percent and 43.3 percent of respondents in our survey, respectively.
But these ads are only going to become more popular. Connected TV ad spending is expected to reach $21.45 billion by the end of the year and grow by 13.9 percent year on year. OTT, on the other hand, projects to reach $11.14 billion and account for 3.7% of all digital ad spend.
Brave Ads
One emerging ad format used by only 29.1 percent of respondents in our survey (although 17.27 percent said they soon would) was Brave Ads.
If you don’t know much about Brave, it’s a free, open-source, Chromium-based browser that puts a premium on speed and privacy. It boasts over 78 million monthly active users and is popular with those who like Chrome but want a more private browsing experience. The browser has built-in ad blockers, its own crypto wallet, and even a search engine.
Brave Ads are ideal for reaching a unique audience of tech-savvy, privacy-first individuals who are harder to reach on other platforms. There are several ad formats you can choose from that cover both the platform’s browser and search engine:
Search ads:
A privacy-preserving text-based ad that appears at the top of the Brave search results page.
Tab takeover ads:
High-quality full-page images that feature in Brave’s new tab rotation.
Newsfeed ads:
Display ads that show in the private and customizable news feed that appears every time someone opens a new tab
Notifications ads:
Text-based ads with a call-to-action that appear during user browsing sessions.
One of the biggest benefits of Brave Ads is the ability to reach a unique target audience. Brave’s userbase spreads across over 200 countries. These users tend to be younger and privacy-conscious individuals—the kind of people who would have ad blockers on another browser like Chrome or Safari. Because these users have more trust in the Brave platform, ads on the platform don’t have the same perception of “spammy” or “intrusive” conventional paid ads might.
Perplexity Ads
Another emerging platform for advertisers is the AI generative search engine Perplexity, which boasts around 100 million search queries per week. In November, the platform announced that it would start launching ads in the form of sponsored follow-up questions. Note that these follow-ups would be generated by Perplexity, not your brand.
Some of the initial brands taking part include Indeed, Whole Foods Market, Universal McCann, PMG, and others. But what does an ad on a generative search engine look like?
Here’s an example: First, here’s a typical Perplexity question and response:
Now, here’s an example of a sponsored followup question.
Perplexity has the potential to open up a new potential audience for advertisers, even though the concept is in its relative infancy. The platform has shared that:
80% of its users have undergraduate degrees.
30% have what they call a “senior leadership position.”
65% are considered to work in “high-income white-collar professions.” Examples include law, medicine, and software engineering.
If you’re targeting that high-earning, well-educated audience, or want the lower competition of an emerging platform, Perplexity could be a good way to get started on the ground floor.
Social Media Landscape Shifts
Over 5 billion people around the world use social media, and 259 million new users have come online in the past year.
These networks are becoming much more than a way to connect with friends. Modern social platforms are news outlets, search engines, and storefronts.
The popularity of social media advertising isn’t in doubt—it was the most popular paid media campaign style among our respondents. But how marketers think about the network is changing.
Below, we look at four of the biggest paid social trends this year so far.
Expansion of Social Commerce
Social commerce is the fusion of social media and e-commerce. It’s a powerful combination that enables users to make purchases directly from their favorite social platform. U.S. social commerce was valued at $89.11 billion in 2022 and is expected to grow at a compound annual growth rate of 29.2 percent.
Facebook is the most popular social commerce platform overall, although platforms like Instagram, YouTube, and TikTok are leading the charge in social commerce, especially among Gen Z, who favor seamless in-app shopping experiences.
The great thing about social commerce from an advertiser’s point of view is they no longer have to convince users to leave the platform to make a purchase. Shoppable ads on platforms like Instagram, TikTok, and Facebook mean users can click a link in the post’s description, see the price, and make a purchase.
So, how can you get started?
Having your product feed in order is essential. These are the cornerstones of shoppable ads on most social media platforms, such as Facebook and TikTok.
These feeds let you take advantage of each platform’s unique shopping ad formats. On Facebook, that includes carousel collections, photo ads, and video ads.
Ad-Free Experiences
Social media platforms have always relied on ads to generate revenue. But that may not be the case for much longer since several social media platforms are trialing ad-free subscription models.
This includes X, with a Premium+ tier that costs $16 per month, Meta (which announced it will offer ad-free subscriptions to European users for €9.99—just under $11 in U.S. currency), and TikTok, which is piloting an ad-free subscription priced at $4.99.
While it remains to be seen just how many users will pay a subscription to use social media, advertisers should consider how to navigate ad-free social media networks in the future.
One obvious option is to invest more in influencer marketing. Paid users will still follow their favorite influencers, making this an easy way for brands to reach these consumers. Investing in nano- and micro-influencers, specifically, could help brands maintain reach in ad-free environments while keeping campaigns cost-effective.
The other solution is to grow organic followings using a paid ad strategy while you can. An ad-free social media experience doesn’t mean people won’t follow their favorite brands. So, community building may be the order of the day before consumers choose to forgo ads for good.
Social Media Is Becoming Its Own Search Platform
Social media platforms have become search engines for millions across the globe. Research by Adobe finds that two in five Americans use TikTok as a search engine, and 10 percent of Gen Z users are more likely to turn to TikTok than Google.
Platforms like YouTube and Instagram are also popular among people of all ages looking for information fast.
Speed is one reason consumers turn to social media instead of search engines. But so are trust and convenience. When people are on social media a lot more than Google, it’s much easier to turn to trusted sources like your favorite influencer or the app’s discovery section for advice.
Some social platforms are embracing this phenomenon, and advertisers would do well to follow. TikTok, for example, is launching Search Ads Toggle in Beta—a feature that allows brands to advertise in search results.
TikTok automatically creates ads using the advertiser’s existing content and serves them alongside organic results, as you can see above.
Nano- and Micro-Influencers Take Center Stage
Move aside, celebrities and social media mega influencers. The time of the micro- and nano-influencers has arrived.
Micro-influencers (people with 10,000 to 50,000 followers) and nano-influencers (people with 1,000 to 10,000 followers) may not have the follower counts of people like Jake Paul. But they have a lot of other characteristics that appeal to brand advertisers.
This includes:
Highly engaged audiences
Authenticity and relatability
Cost-effectiveness
While macro-influencers were the most popular with marketers in our survey, that’s primarily because they fit their business audience. Of the marketers who preferred nano-influencers, one-third said it was because they are more cost-effective.
Even the biggest brands work with micro-influencers.
Take Melizza Black, for example, a fangirl fashionista who partners with the likes of Disney, Pixar, and Universal Studios to promote new films, product ranges, and clothing merchandise.
In fact, survey respondents with budgets topping $200,000 were more likely to work with micro-influencers because of better campaign performance.
Linkedin Influencers For B2B Campaigns
Targeted B2B audiences with paid media campaigns has always had its unique challenges due to the longer buying cycles and more discerning preferences compared to B2B. Bringing Linkedin influencers into your paid campaigns can be a difference-maker in terms of providing that credibility and reach you need.
LinkedIn influencers bring a unique advantage to paid media campaigns due to their highly professional and engaged audiences. Since they are often focused on professional growth and industry-specific insights, they make a perfect fit for B2B campaigns.
Collaborating with Linkedin influencers allows brands to target a niche audience with tailored messaging, increasing conversion rates and ROI.
With that in mind, how do you fully harness the power of this growing option for paid media? Start by identifying individuals whose audience aligns with your target demographics.
For example, NP Digital co-founder Neil Patel is a successful Linkedin influencer, buiilding an audience of over 680k followers on the platform.
This would make him an ideal fit for any paid campaign related to digital marketing services or tools due to his established success in the space.
Use tools like LinkedIn’s Creator Mode analytics or platforms like BuzzSumo to evaluate influencer performance metrics such as engagement rates and follower authenticity.
Once you start your Linkedin partnership, prioritize authenticity in your paid campaigns. LinkedIn audiences are particularly sensitive to overtly promotional content, so it’s essential to frame your message as an industry-relevant insight or case study. Personal anecdotes or professional experiences tied to your product can boost credibility and audience trust as well.
Developing Practices for Paid Media
The strategies advertisers use to craft the best paid ads are constantly changing. Whether it’s the format, platform, or bidding strategy, it’s important to stay ahead of the curve and use the latest techniques to create ads that resonate with audiences and drive return on investment (ROI).
Short-Form Video
Want to seize a user’s attention? Short-form videos are the way to go.
A short-form video is between three and 90 seconds long. Most commonly found on TikTok, this video format has quickly spread to YouTube, Instagram, and Facebook.
Short-form videos are popular for both organic and paid marketing efforts thanks to high engagement rates, lower costs, and simple messaging.
You can create short-form video ads on any of these platforms, but TikTok and YouTube Shorts are the most popular and effective. YouTube Shorts boasts more than 2.3 billion monthly users, and 70 billion daily views, for example, while TikTok has over 1 billion global monthly active users.
Google’s making several new initiatives for YouTube Shorts advertising to take advantage of this newfound popularity, including:
The introduction of the YouTube Select Shorts lineup, where advertisers can place ads next to curated popular Shorts content.
Tailoring its ABCD framework for short-form content, which emphasizes strategies like capturing attention quickly and integrating branding early. Additionally,
Three things are critical to succeed with short-form video ads. The first is to make the first five seconds of your video as captivating as possible. The better your hook, the fewer users will click skip.
Second, ensure you have a single, clear message. Don’t try to highlight multiple unique selling propositions (USPs) or target different audiences in a 30-second short. Short, sweet, and to the point is the order of the day.
Lastly, Google reports that creator-led ads on YouTube Shorts can achieve up to 20% higher conversions than traditional branded ads. You can apply this lesson to any short-video platform, and work with relevant influencers on the platform to increase your reach and credibility.
Immersive and Interactive Experiences (AR and VR)
You probably can’t remember the last ad you saw. But it’s more likely you can remember the last time you experienced augmented reality (AR) or virtual reality (VR).
That’s why AR and VR ad experiences are becoming increasingly popular with major brands. The AR market alone is expected to hit $5.2 billion by the end of the year.
While traditional ads are passive affairs that struggle to capture our attention, augmented and virtual reality ads create an interactive and memorable experience.
Take Coca-Cola Zero Sugar’s #TakeATasteNow out-of-home augmented reality campaign that launched at the end of 2023. Rolled out across 13 U.K. locations, the AR ad experience enabled customers to interact with digital billboards in real time by scanning a QR code to redeem a Coca-Cola in a nearby store.
AR and VR ads don’t have to be high-budget guerilla advertising campaigns, however. IKEA has seen success with IKEA Place, an app that launched in 2017 and lets customers use AR to place IKEA products around their homes.
User-Generated Content (UGC)
User-generated content (UGC) is a popular organic social media strategy, but you can also use it in paid campaigns.
In fact, it can go a long way toward improving your ad conversion rates, given that visitors who interact with UGC convert 102.4 percent higher than average.
UGC also improves the authenticity of your ads. It’s hard to make a paid ad truly authentic, but reviews and recommendations from real customers help humanize your campaigns.
Integrating UGC into your paid ads campaign can be as simple as dropping a testimonial into your next creative, as Peet’s Coffee does here:
Or you can use video reviews as your ad’s main creative, as the beauty brand Prose does below:
Conversational advertising uses personalized and automated conversations to encourage users to take action.
Rather than a static image or scripted video, conversational ads use a chat interface to mimic a real-life conversation. Users can select predefined messages that can change the nature of the conversation and lead to different outcomes.
Facebook and LinkedIn are the two social platforms that work best for this paid media strategy. LinkedIn Message Ads lets you send sponsored direct messages to a specific set of users on the platform, for example. Facebook Messenger Ads are conversational ads that appear in the Messenger app.
But social media isn’t the only place you’ll find these ads. You can also re-create a chatbot interface using banner ads. Here’s an example from Emirates Vacations:
Contextual Targeting
Contextual advertising is a type of targeted digital advertising where ads change depending on the content of the webpage.
Contextual targeting can either be keyword-based or semantic:
Keywords: Platforms use on-page keywords to serve targeted ads.
Semantic: Platforms use AI to understand the meaning of the page rather than just identifying keywords.
Contextual targeting is an excellent way to serve relevant ads to an engaged audience without relying on third-party cookies. If someone is reading a page about tourist destinations in Bali, you can be pretty sure they’ll be interested in a hotel or flight to the region.
Contextual targeting can also be quite cost-effective, especially compared with behavioral marketing campaigns that require massive amounts of user data. This makes it easier to implement, too.
There are plenty of platforms you can use to get started with contextual ads, including Google AdSense, DV360, the Yahoo! Bing Network, and Media.net.
Premium Inventory Opportunities
Want to give your ads the best chance of success in 2026 and beyond? Consider leveraging the premium inventory opportunities available on several social media platforms.
Premium ad inventories are the most expensive and exclusive ad spaces on these platforms. They typically appear under or alongside the most on-trend and relevant content.
TikTok Pulse suite, for example, places your ads immediately after the best in-feed content. There are several options, including:
Max Pulse: Ads placed next to the top 4 percent of content on the platform, according to the Pulse Score.
Category Lineups: Ads inside TikTok’s Pulse Lineups, a collection of top-performing content across a dozen categories.
Seasonal Lineups: The seasonal equivalent of category lineups, where ads are placed alongside top-performing content from holiday events like Thanksgiving and the Fourth of July.
Pulse Premiere: Ads placed after top-performing content in the lifestyle & education, sports, and entertainment categories.
YouTube Select is a similar program that shows ads alongside the top 5 percent of the platform’s most viewed content.
Premium inventory opportunities are a fantastic way to associate your business with the biggest brands and content creators. This network effect can be a great way to increase brand awareness. Thirty-four percent of survey respondents said they are already using opportunities like this, with another 20 percent planning to start using them in the next year.
Gen Z And Social Responsibility
Want to attract younger consumers with paid media? Then you better be a socially responsible corporation.
Gen Z has strong values and expects brands to share them. McKinsey research finds that almost three-quarters (73 percent) of Gen Z try to purchase from ethical companies. Nine in 10 believe companies have a responsibility to address social and environmental issues.
As “digital natives”—the first generation to grow up surrounded by technology—your best bet for reaching Gen Z is through digital channels. But not just any ad will do. Sprout Social found that 73 percent of Gen Z consumers think brands should raise awareness and take a stand on sensitive issues.
By taking a stand against fast fashion and partnering with well-known social activists, including Xiye Bastida, Emma Chamberlain, and Marcus Rashford, the brand raised awareness of our shared environmental responsibility while promoting the quality of its products and attracting a new, younger generation of customers.
AI’s Impact on Advertising
It wouldn’t be a 2026 trends article if we didn’t end with a section about AI, would it? The truth is there’s a lot to cover. AI has become so pervasive that it’s impacting almost every part of the paid media world—and the majority of our survey respondents are already using it in their campaigns.
Ad creation is one common use case. Google’s Dynamic Search Ads feature uses AI algorithms and content on your existing website to automatically create relevant ads and show them to customers searching for the exact product or service you offer.
Meta also has a Dynamic Ads offering, which can automatically promote all your products across Facebook and Instagram.
Then there are generative AI tools like ChatGPT or Jasper, which you can use to create ad copy in seconds.
Soon enough, though, you won’t even need to leave your native ad platform of choice for generative AI support. Many of the major players, like Google, Meta, and TikTok are all building native creative solutions that can auto-generate copy and creative.
Google, in particular, is taking this capability to the next level, using AI to assist advertisers with video and voice-over capabilities, enhancing the efficiency and quality of ad creation. The platform includes features such as AI-powered video editing and text-to-speech functionality for YouTube ads.
Imagine being able to input a script, choose a variety of voices, and create natural-sounding audio overlays, This allows for flexible and quick adjustments to match your brand voice, making video content production more efficient and accessible than ever.
AI can run your campaign for you, too. Over one-third of our respondents used AI-powered paid bidding strategies, for example, which was the top use case in our survey. In addition, when it comes to taking advantage of Google’s capabilities to generate creative using AI, our survey respondents were very intrigued.
Speaking of Google’s AI improvements, Performance Max (PMax) campaigns are a great example of this technology. Performance Max campaigns deliver broad, conversion-focused coverage with the use of AI. The results are impressive, with Google claiming marketers are seeing 27 percent more conversions.
Not that Google is resting on its laurels. The search giant is making a series of improvements to PMax by:
Optimizing broad matches by 10% for advertisers using smart bidding
Adding the ability to see ad performance by creative and placement details
Implementing YouTube exclusions
Introducing a profit optimization goal in Smart Bidding, which optimizes for profit using data from cart-level conversions and your Merchant Center account
If you already have paid media campaigns set up, there are several third-party platforms that let you leverage AI to improve campaign performance. These include Trapica and Adsmurai.
What do all the AI leaps mean for paid media marketers? Well, the role is evolving. The advent of AI simplifying tasks like content generation, bidding, and more means that there is less time spent on tedium and more time on higher-level tasks, with supervision for that AI output. Paid media professionals are becoming more a hybrid campaign/creative/strategy manager role.
FAQs
How have paid media trends shifted for healthcare recently?
Healthcare paid media has shifted from aggressive targeting and quick conversions to privacy-first, trust-driven marketing.
You can’t rely on hyper-targeting like before. Privacy rules and platform changes have limited how precisely you can track and target users. So the focus has moved to intent and context—think search queries, location, and content people are actively engaging with.
At the same time, the strategy has expanded beyond just paid search. Search still captures demand, but channels like YouTube, social, and even connected TV are now critical for building trust before someone ever clicks.
Content plays a bigger role too. Educational ads, doctor-led videos, and patient stories outperform hard “book now” pushes because healthcare decisions take time.
Bottom line: healthcare paid media isn’t just about driving clicks anymore. It’s about showing up early, building credibility, and staying visible until the patient is ready to act.
Conclusion
Paid media is one of the most dynamic and fast-paced marketing environments. Things can change significantly from month to month, and there are always new trends and platforms you can use to drive more revenue and generate higher returns on your investment.
New trends may not last, but that doesn’t mean you shouldn’t be experimenting. You never know: Contextual advertising, short-form video, or in-app ads may be your new highest-converting channel.
Then it’s all about executing. And remember, the faster you execute, the better positioned you’ll be to take advantage of new paid marketing trends and digital marketing predictions in 2026 and beyond.
If you want even more insights on these upcoming trends, check out our full report on the NP Digital website.
AI is changing search and rewriting the rules. If your brand isn’t visible in AI-generated answers, you have a bigger problem than just traffic. You’re missing out on trust, credibility, and customers who now expect AI to recommend the best options everywhere.
We see that traditional SEO isn’t enough anymore. Today, it’s possible to rank #1 on Google and still be invisible in the AI responses people now often turn to for recommendations.
Yoast AI Brand Insights is a great tool that shows you exactly how your brand appears in AI-generated answers from ChatGPT, Perplexity, or Google Gemini. It tracks sentiments and benchmarks against competitors. What’s more, it doesn’t just help build your AI visibility, but also helps control your brand’s narrative.
Key takeaways
AI visibility matters; brands absent in AI responses lose trust and customers.
Yoast AI Brand Insights helps track brand mentions, sentiment, and credibility across AI platforms.
Modern SEO now focuses on AI visibility, moving beyond traditional search engines.
To improve AI brand visibility, brands should publish authoritative content and optimize for AI citations.
Active participation in online communities enhances brand visibility on AI platforms.
Why modern SEO is about AI visibility
People are no longer just searching on Google. Every day, more people are asking AI tools and Large Language Models (LLMs) like ChatGPT, Gemini, and Perplexity for recommendations. Unlike classic search engines, these tools don’t just list links; they curate answers by combining trained knowledge with information they’ve learned from the web.
AI platforms combine information from multiple sources to provide a single, context-aware, and custom answer. People even start treating these AI answers as personal advice, not just generic search results. This will happen more and more as search engines like Google increasingly integrate AI into their search results. As a result, the boundaries between traditional search and AI-generated answers are blurring.
AI search is a blind spot for most
Classic SEO tools track rankings, but they don’t track how your brand appears in AI answers. This leads to blind spots where your competitors might be all over the AI recommendations in your market without you realizing it.
What’s more, you might rank well on Google, but you could be invisible to a growing audience if AI systems ignore your brand. Your competitors can appear more often or more positively in AI recommendations. Or there’s negative sentiment in AI responses that can harm your reputation without you even knowing.
Controlling the narrative of your brand
AI platforms like ChatGPT, Perplexity, and Gemini piece together your brand’s story from scattered sources, like reviews, news articles, social media, and your own content. If these send mixed signals, the answers an AI gives will too. That’s why you need to send a unified, consistent message. This is one of the most effective ways to reinforce your narrative across every platform.
Repeat your main message, whether that’s “affordable luxury” or “sustainable innovation,” everywhere, from your site content to press releases and from social media to external interviews.
Quickly address misinformation and respond to inaccurate reviews by publishing clarifications online. By doing this, you prevent the AI from amplifying outdated or incorrect details.
Support your brand’s most important attributes with structured data. Add the awards your brand won, or its unique selling points, so you can give the AI platform an all-encompassing framework to reference.
Remember, consistency is about repeating your most important brand aspects everywhere. Shape the narrative in such a way that the AI has no choice but to reflect the brand the way you want it to project.
Yoast AI Brand Insights is here to help
Yoast AI Brand Insights is a helpful tool that tracks how your brand appears in AI answers. It provides a clear, actionable view of your brand’s visibility, sentiment, and credibility across major AI platforms.
Yoast AI Brand Insights helps you:
Understand if and how your brand is mentioned in AI responses
Track sentiment and see if AI platforms describe your brand positively or negatively
Identify the sources to see what AI references when mentioning your brand
Benchmark against competitors to see how you stack up
We didn’t build this to get you some data, but to turn that AI black box into actionable insights.
The main page of the Yoast AI Brand Insights shows your main metrics, and you can delve deeper into your analysis by going to Analysis details
Understanding the AI visibility metrics
Using the Yoast AI Brand Insights metrics helps you measure and improve your brand’s visibility in AI platforms. To make the most of it, you have to understand what metrics mean and why they matter.
AI Visibility Index (AIVI)
The AI Visibility Index (AIVI) scores (on a scale of 100) how visible your brand is on AI platforms such as ChatGPT, Perplexity, and Gemini. It consists of the following metrics:
Mentions, or how often your brand is cited in AI answers
Citations, or the number of authoritative sources referencing your brand
Sentiment, or the rate of positive vs. negative keywords associated with your brand
Rankings, or the relative position of your brand mentions compared to your competitors
The higher the AIVI score (on a scale of 0-100), the more visible your brand is in AI search results for the tracked terms. If you find that your score is low, you should focus on getting more mentions and citations. You should also work on positive sentiment around your business.
You build your relevance by publishing authoritative content. Try to get featured on relevant sites and monitor and improve negative sentiment around your brand. Learn more about how AI shapes brand perception.
The higher the AIVI score (on a scale of 0-100), the more visible your brand is in AI search results for the tracked terms
Mentions
The Mentions section tracks the specific queries for which your brand appears in AI responses. So, if someone asks, “What is the best low-cost CRM system for small businesses?” and your brand is in the results, that is a mention.
It’s not hard to understand why this is important. More mentions generally lead to greater visibility. If you don’t show up for the terms and queries relevant to your brand, you need to start improving your content.
Use the built-in AI-generated brand queries to find high-intent questions and write content that answers those questions thoroughly. These could be blog posts or FAQ pages, or whatever makes sense. Also optimize for conversational queries, such as “Is brand X good for startups?”
The mentions section tracks the specific queries for which your brand appears in AI responses
Sentiment
Sentiment measures the percentage of negative vs. positive words in the query results associated with your brand. So, if the AI describes your brand as “innovative” or “reliable”, that counts as positive sentiment. However, if they use terms like “overpriced” or “unreliable”, that’s negative sentiment.
Positive sentiment helps build trust, while negative sentiment can drive potential customers away. That’s why you should always actively address negative sentiments online. Don’t leave those bad online reviews unresponded to. You can also publish testimonials on your site to amplify positive voices, and you can do the same in your marketing messaging by talking about “a brand loved by thousands” or “award-winning” products.
Keep an eye on trends in your online sentiment and catch and fix issues early.
Sentiment measures the percentage of negative vs. positive words in the query results associated with your brand
Citations
Citations refer to the sources that AI platforms explicitly reference when generating an answer, not the brands mentioned within those sources. For example, if Gemini answers a query about “the best credit cards” and cites a New York Times article about best credit cards, that New York Times page is the citation. Even if the article includes brands like American Express or Chase, the citation is attributed to the publisher, not to the individual brands.
That said, appearing in those cited sources still matters a great deal. If your brand is consistently featured in relevant, high-authority publications like The New York Times, it increases the likelihood that AI systems will surface your brand in their responses over time. In other words, you may not receive a direct citation, but you benefit from being part of the content that AI platforms trust and rely on.
Over time, your brand (say, American Express or Chase) becomes more likely to be included in AI responses to queries like “best credit cards,” especially if it consistently appears in trusted sources.
AI platforms use citations to validate their answers. Citations from top sources, such as industry publications, enhance credibility. Find where there’s a natural match between your customers and their audience, and publish the type of content people will want to link to.
Citations refer to the sources that AI platforms explicitly reference when generating an answer
5 Ways to improve your AI brand visibility
Now that you understand the metrics, here’s how to use insights from Yoast AI Brand Insights to improve your AI visibility.
Optimize for AI citations
AI platforms like Gemini, Perplexity, and ChatGPT use citations to validate their responses. So, citations increase the likelihood of your brand being included and trusted in AI-generated answers
Try to get featured on relevant, authoritative sites and publish guest posts on industry sites, news sites, or educational domains. Get mentioned in roundup articles, like “Top 10 tools for doing X”. Ask customers to write reviews on platforms like Capterra, G2, and Trustpilot. All of these tactics can act as proof that your brand is a well-trusted source. Remember, it must be relevant citations.
Make sure your content is structured so the AI can read it easily. Use clear, hierarchical headings and bullet points to make the content easy to scan. Add FAQs and publish direct answers to common questions. It is also a good idea to add schema markup to help the AI crawlers understand your content.
Don’t forget to update old content regularly. The AI platforms prioritize fresh, up-to-date information when retrieving sources, so refresh your content regularly to stay relevant.
Monitor and improve brand sentiment
By mentioning your brand, the AI platforms also shape how people see it. If those sentiments in the AI’s answers are negative, it can hurt your trustworthiness and cost conversions. This could signal the need for a broader reconsideration of business strategy priorities.
Once you find AI platforms associate your brand with negative terms (like “slow customer service”), respond to this issue publicly. For instance, you could contact customers on review sites to resolve complaints. You can also publish case studies and testimonials to steer the AI towards positive perceptions.
In your monitoring, you’ll also find the positive terms AI platforms associate with your brand, such as “trusted” or “innovative”. Use these terms in your marketing, in your site content, and on social media.
The weekly scans in Yoast AI Brand Insights track sentiment shifts for your queries over time. If sentiment drops, investigate the cause, like a recent PR issue or a product recall.
Benchmark against competitors
AI visibility is also about how you compare to the competition. If they are mentioned more often or in a better light than you, they will appear more often in recommendations made by AI platforms.
See how your brand stacks up against competitors. Use Yoast’s Competitor ranking tab to see which brands show up a lot in AI answers. Analyze their content strategy. Do they publish more case studies? Are they active on review sites?
This tool shows how AI describes your brand compared to others in your market. For example, if you’re a coffee company like Taylor’s of Harrogate, you might find that Lavazza is consistently labeled as “the Italian espresso expert.” Now you know exactly what to highlight, whether it’s your heritage, roasting process, or sustainability, to stand out. Use these insights to sharpen your messaging and compete more effectively.
Don’t forget to check your weekly competitor analyses to see if your AI visibility is improving. Double down on the strategy that works for you. The tool also includes an historical view. This lets you look back at earlier analyses by selecting a past date, helping you compare visibility and sentiment across different points in time.
For each tracked query, Yoast AI Brand Insights gives specific insights into how your brand performs versus the competition
Answer brand-specific questions
AI platforms are very good at answering specific questions, such as “Is brand X reliable?” or “What’s the best tool to do Y?” You’re missing out on a lot of potential customers when your brand isn’t in these answers.
Yoast AI Brand Insights suggests queries you should monitor based on your input, such as “Is [Your Brand] good for small businesses?” In addition, do deep research into the common questions asked in your industry using tools like AnswerThePublic, AlsoAsked, or simply by checking Google’s People Also Ask section.
With the insights gathered, publish blog posts, FAQs, or landing pages and directly answer those brand-related queries. Support the content with properly structured data, such as FAQ and how-to schema, to give AI platforms more tools to understand your content.
In Yoast AI Brand Insights, track which questions get the most mentions from AI platforms. Don’t forget to keep your content up to date to keep it accurate and relevant.
During the setup, Yoast AI Brand Insights generates five highly relevant queries based on your input. You can change them if you like
Track progress with the AI Visibility Index
Improving the AI visibility of your brand isn’t a one-time task, but a recurring effort. Luckily, Yoast’s AI Visibility Index gives you an easy-to-understand metric that you can use to track your progress over time.
Run your first scan to establish the starting point for your AI Visibility Index. Note which areas, like citations or sentiment, are strongest and weakest.
Yoast AI Brand Insights runs weekly scans. Please review them to track progress. Check the historical view, but remember these cannot be viewed together. Select the week before and then reselect this week to spot changes. Look for trends, such as improvements in sentiment or a sudden increase in citations.
If your score doesn’t improve, revisit the strategies above, such as optimizing for citations and improving sentiment. Be sure to experiment with new tactics and publish original research to secure more earned media.
How to influence LLMs to mention your brand
Imagine this: A potential customer asks ChatGPT, “What’s the best CRM for small businesses?” If your brand isn’t mentioned in the answer, you’ve lost a customer before they even knew you existed.
LLMs like ChatGPT, Gemini, and Perplexity don’t just pull answers out of thin air. They rely on data, citations, and patterns to generate responses. If your brand isn’t part of those patterns, it’s far less likely to be mentioned, no matter how well you rank on Google.
Publish authoritative content
LLMs are looking for well-structured, factually accurate content. These AI platforms love sources that provide unique insights or expert opinions, so be sure to focus on that.
Start with original research. Publish surveys, case studies, or industry reports with unique data. For example, “2026 State of [Your Industry] Report: Key Trends and Insights” positions your brand as an authority and gives AI platforms a reason to cite you.
Use the proven inverted pyramid structure in your content. Start with the most important information, like key findings and conclusions, follow with supporting details, and end with background information. This makes it easier for AI to extract, digest, and use your content.
Don’t forget to optimize for facts. Include statistics, quotes from experts, and actionable insights. For example, instead of “Our tool is great for marketers,” say “Our tool increased conversion rates by 30% for 500+ marketers in 2025, according to our latest case study.”
For example, HubSpot built its authority by publishing ultimate guides, like “The Ultimate Guide to Inbound Marketing.” These guides became go-to resources for marketers, earning backlinks from industry blogs, news sites, and even competitors. As a result, HubSpot is now frequently cited in AI responses about marketing tools.
Get mentioned on relevant, high-authority sites
LLMs trust reputable sources like industry publications, news sites, and review platforms. The more your brand is mentioned on these sites, the more likely it is to appear in AI responses. Please keep in mind that relevance is key here. For instance, if Yoast gets mentioned in Gardeners’ World or Home and Garden, it will do little to nothing for our brand. Find the most important and relevant sources and focus on those.
Pitch stories to journalists or industry blogs. For example, try to get featured in “Top 10 [Your Industry] Tools in 2026” lists.
Encourage customers to leave reviews on G2, Capterra, Trustpilot, or Google Reviews. Don’t forget to respond to (negative) reviews to show engagement and transparency.
If possible, try to reach out to sites like HubSpot, Search Engine Journal, or industry-specific blogs and ask to write for them. Be sure to include a bio with your brand name to reinforce recognition.
Optimize for conversational queries
LLMs are designed to answer natural language questions. This means you have to optimize your content for conversational queries. Conversational queries are things like “What’s the best CRM for startups?” rather than “best CRM”.
In your content, you should use question-focused headings. For example, answer the question “Is [Your Brand] good for small businesses?” directly in the first paragraph to make it clear and easy to understand.
LLMs often answer long-tail questions, so you should target long-tail keywords. For example, instead of “project management tool,” target “best project management tool for remote teams in 2026.”
In support of all of this, create FAQ pages with schema markup to help AI better understand your content.
Build citations
Build up a network of high-quality mentions that reinforce your brand’s authority. The more high-quality, relevant citations you have, the more likely LLMs are to mention your brand.
Publish assets like ultimate guides, templates, or tools that others want to reference and link to. For example, “The Ultimate Guide to [Your Industry] in 2026.”
Reach out to bloggers, journalists, and influencers to reference your content. For example, “We noticed you mentioned [Competitor] in your article. Here’s why [Your Brand] might be a better fit.”
Get featured in press releases, podcasts, or webinars. For example, “[Your Brand] Announces Groundbreaking Feature for [Industry].”
Make sure AI crawlers can reach your site
It’s important to ensure that AI crawlers can discover and index your content. If your site is invisible to them for whatever reason, your brand won’t appear in AI responses.
Your site should be technically sound, but you can also help LLMs in other ways. Make sure your site loads fast and is mobile-friendly. Use clean URLs, good meta tags and descriptions, and alt text for images. Also, use schema on your site to help AI crawlers understand what your site is about and how it all ties together.
In Yoast SEO, you can activate an llms.txt file. This proposed standard helps point AI crawlers to your most important content. Also, check whether your robots.txt file inadvertently blocks AI crawlers from accessing your content.
The llms.txt file in Yoast SEO helps point AI crawlers to your most important content
Be active in online communities
LLMs are trained on and can retrieve information from forums, social media, and community platforms such as Reddit, Quora, and LinkedIn. It can improve your brand’s visibility on AI platforms if you participate there.
Answer questions on Quora and Reddit. Provide valuable, non-promotional answers that naturally mention your brand. For example, “As a [Your Industry] expert, I recommend [Your Brand] because…”
Join discussions on Slack, Discord, or niche forums. Share insights and link to your content when relevant. Post thought leadership content on LinkedIn, Twitter, or Facebook. For example, “Here’s why [Your Industry] is changing in 2026, and how [Your Brand] is leading the way.”
The future of brand visibility is AI-driven
We’ve seen that AI is changing how people discover brands. There’s a simple rule: if your brand isn’t visible in AI responses, you are missing out on an ever-growing audience.
Luckily, Yoast AI Brand Insights gives you the tools to:
Track mentions, sentiment, and citations across AI platforms
Benchmark against competitors to identify gaps
Optimize for high-intent queries to capture more attention
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00Dubado Solutionshttp://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.pngDubado Solutions2026-04-16 14:45:232026-04-16 14:45:235 ways to improve your AI brand visibility (Using Yoast AI Brand Insights)
Knowing how to measure marketing ROI requires moving beyond credit assignment toward causal proof. Attribution shows what happened; incrementality shows what marketing actually caused.
Marketing leaders face structural visibility gaps from walled gardens, cross-device behavior, offline conversions, and AI-mediated discovery that no single tool can fully account for.
Marketing investment ROI looks different at different funnel stages. Lower-funnel channels support high statistical confidence. Upper-funnel activity requires directional signals and longer evaluation windows.
The payback curve problem means short reporting cycles systematically under-value brand and upper-funnel investment, even when those channels drive the most long-term growth.
Learning velocity matters as much as measurement precision. A confident direction pursued quickly outperforms a perfect answer that arrives too late.
The Real Measurement Challenge CMOs Face
The core challenge in figuring out how to measure marketing ROI is not a lack of data. Most marketing teams have more data than they can act on. The challenge is that the data they have mostly reflects activity, not impact. And the visibility gaps that matter most are structural, not fixable with a better dashboard or a new marketing measurement plan.
Consider what falls outside standard analytics. Walled garden platforms like Google, Meta, and Amazon run their own measurement systems optimized to report performance favorably within their ecosystems. Cross-device behavior means a buyer who saw an ad on mobile and converted on desktop may never be connected in a single attribution path. Offline conversions, from phone calls to in-store visits to deals closed in a CRM, are underrepresented or missing entirely. Private sharing channels, where recommendations travel through direct messages and group chats, show up as direct traffic if they register at all. And AI-mediated discovery, where a buyer forms a view of a brand through an AI-generated answer before ever visiting a website, leaves no footprint in standard reporting.
NP Digital research found that the average customer journey grew from 8.5 touchpoints in 2021 to 11.1 touchpoints in 2025. The interactions most likely to have shaped a purchase decision are the ones least likely to appear in a marketing report.
Marketing leaders who understand this stop expecting their measurement stack to show a complete picture. Instead they ask which signals are reliable enough to act on, which decisions require stronger proof, and where directional confidence is sufficient to move forward.
Attribution modeling remains one of the most widely used marketing measurement tools available, and it has a genuine role to play in day-to-day campaign management. The problem is that when it gets used to answer questions it was not built to answer.
Attribution shows which touchpoints preceded a conversion. It does not show whether those touchpoints caused the conversion. That distinction sounds subtle, but it has significant implications for budget decisions. When Airbnb paused its performance marketing budget, bookings did not drop. When Uber cut spend in certain channels, rider acquisition was largely unaffected. In both cases, the attribution system had been crediting spend for outcomes that would have occurred regardless. The marketing was capturing demand, not creating it.
The questions leadership most often asks are precisely the ones attribution cannot answer reliably. Did this campaign generate new demand, or intercept demand that already existed? Would revenue have changed if this activity had not run? Which channels are actually changing the economics of the business? These are questions about causality. Attribution is built around correlation.
According to NP Digital research, nearly 47 percent of marketers lack confidence in their current attribution model. Yet most organizations still use attribution reports as the primary input for strategic budget decisions. Understanding where attribution blind spots appear is the first step toward building a marketing measurement plan that can support those decisions more reliably.
The Four Questions Modern Marketing Measurement Must Answer
Rather than starting with a dashboard, high-growth marketing organizations start with a set of diagnostic questions. These questions function as decision filters, helping leaders separate marketing activity from actual business impact. They come directly from how to measure marketing ROI in a way that connects to causal outcomes rather than credited touchpoints.
What is the incremental conversion lift? This asks not how many conversions occurred, but how many would not have occurred without the marketing spend. The gap between attributed conversions and incremental ones reveals how much of reported performance reflects demand capture rather than demand creation.
What is the incremental search impact? If branded search volume rises following a campaign, what created that lift? Upstream video, social, or content investment often generates the demand that search later captures. Understanding this connection changes how upper-funnel spend gets evaluated.
What attribution redistribution is occurring? Referral traffic spikes or conversion rate improvements in one channel sometimes reflect credit shifting between paths rather than genuine growth. Identifying redistribution separates real gains from accounting changes.
Where is attributed alienation occurring? At what point does frequency, promotional dependency, or margin compression start producing negative incremental lift? Channels that look efficient in aggregate can be actively eroding value at the margin.
These questions are not new KPIs to add to a dashboard. They are the lens through which marketing investment ROI gets evaluated honestly. For teams building this capability from scratch, tracking content marketing ROI using incremental rather than attributed signals is a practical place to start, since content often influences conversions across multiple subsequent touchpoints.
Matching Measurement Standards to Funnel Position
One of the most common errors in building a marketing measurement plan is applying the same standards of statistical rigor to every channel, regardless of where it sits in the funnel. Lower-funnel and upper-funnel activity operate on fundamentally different timescales and produce fundamentally different signal quality.
Lower-funnel channels, including branded search, retargeting, and conversion-focused paid campaigns, generate fast, measurable feedback. Requiring 95 percent statistical confidence before acting on their results is appropriate. The signal is clear, the data is abundant, and underperformance should be addressed quickly.
Upper-funnel channels work differently. Video, brand campaigns, content, and influencer partnerships create future demand. Their effects develop gradually, often appearing as increased branded search volume, improved conversion rates, or lower customer acquisition costs weeks or months later. Requiring the same level of statistical certainty from channels with 8- to 12-week lag times means cutting potentially effective strategies before they can prove themselves.
This creates a pattern NP Digital research consistently surfaces: teams reduce upper-funnel investment because it lacks immediate proof, then experience declining lower-funnel efficiency as the demand pipeline weakens. SEO ROI follows a similar curve. Organic search investment can take months to produce measurable returns, but teams that cut it during that window often see compounding downstream effects on paid efficiency.
The practical approach is tiered standards matched to funnel position. Lower-funnel channels require high confidence before spending continues or scales. Upper-funnel channels can be evaluated at 50 to 60 percent directional confidence, supported by leading indicators like branded search lift, engagement rate trends, and downstream conversion rate improvements.
The Payback Curve Problem
A related challenge in knowing how to measure marketing ROI is what happens when budgets shift toward channels with longer payback periods. Most organizations evaluate all marketing activity on the same weekly or monthly reporting cadence, regardless of how long each channel takes to deliver its full value. This creates a systematic bias against the investments that often produce the most long-term growth.
Direct-response channels like paid search and retargeting deliver 80 to 90 percent of their value within the first week. Email and owned media deliver 60 to 70 percent within the first two weeks. Paid social and display activity produces 50 to 60 percent of its value in the first three weeks, with a long tail extending to 8 to 12 weeks. Video and brand investment delivers only 30 to 40 percent of its value in the first month, with the majority accruing over three to six months.
When marketing spend shifts toward longer-payback channels, weekly performance declines by design. The scrutiny does not. Teams that understand their channel-level payback curves can model expected performance rather than reacting to short-term dips. Teams that do not understand them tend to cut upper-funnel investment at exactly the point where it would have begun producing downstream returns.
Building a dual-view reporting approach helps address this directly. Reporting what happened this week alongside what the model projects based on payback curves gives leadership the context to evaluate performance honestly. This is a core component of unified marketing measurement, where multiple methods and timeframes are combined into a single coherent view of marketing performance rather than a collection of disconnected channel reports.
Why Directional Confidence Often Beats Perfect Precision
Waiting for certainty before acting is one of the most reliable ways to lose ground in modern marketing. How to measure marketing ROI is partly a question of marketing investment ROI, but it is equally a question of decision speed. A model with 60 percent directional confidence, acted on quickly and iterated frequently, consistently outperforms a perfect answer that arrives a quarter too late.
Incrementality testing and geo experiments are the most reliable ways to build directional confidence without waiting for statistical perfection. A well-designed geo holdout can validate whether a channel is generating causal lift within a matter of weeks. The result may not be 95 percent certain, but it is far more useful for a budget decision than months of attribution reporting that cannot establish causality at all.
Rapid iteration compounds this advantage. Organizations that run frequent, smaller experiments build measurement capability faster than those waiting to design the perfect study. Each test produces a documented methodology that makes the next one cheaper and faster. Over 12 to 18 months, this creates a meaningful gap in decision quality between organizations that have built this muscle and those still relying primarily on attribution.
Learning velocity, the rate at which an organization converts experiments into better decisions, matters as much as the precision of any individual measurement. The teams gaining ground are the ones that have made experimentation a routine part of how they allocate budget, not a special project triggered by a performance crisis.
What This Means for Modern Marketing Leaders
The shift in how to measure marketing ROI comes down to three practical changes in how marketing leaders operate. Each one moves measurement closer to the capital allocation decisions that actually matter.
First, prioritize causal insight over attribution reports for strategic decisions. Attribution has a role in day-to-day optimization, but it should not be the primary input when deciding where to increase or decrease investment at a channel level. Incrementality testing and marketing measurement tools that surface marginal returns give a more reliable picture of where the next dollar will produce incremental growth.
Second, allocate budget based on marginal impact rather than blended performance. A channel running at strong average ROAS may be saturated at the margin. A channel with weaker blended numbers may have significant headroom. Understanding where diminishing returns begin is what separates organizations optimizing toward real growth from those optimizing toward the appearance of it. This is the core of unified marketing measurement: combining MMM, incrementality, and attribution signals to see the full picture rather than any single view in isolation.
Third, build experimentation into the operating rhythm rather than treating it as a special project. Weekly budget decisions based on directional evidence outperform quarterly reallocations based on attribution. Organizations that run incrementality tests regularly, document the results, and apply those learnings to subsequent decisions accumulate a structural advantage that compounds over time.
FAQs
What Is ROI in Marketing?
Marketing ROI, or return on investment, measures the revenue generated relative to what was spent on marketing. The basic formula is (revenue attributed to marketing minus marketing cost) divided by marketing cost. In practice, meaningful marketing investment ROI analysis goes beyond this formula to account for which revenue was incremental, what the margin on that revenue was, and how long it took to recover the initial spend.
How Do You Measure Marketing Success?
Measuring marketing success depends on which question you need to answer. For operational performance, platform metrics and attribution data provide fast feedback. For strategic decisions about where to invest, incrementality testing and marketing mix modeling give more reliable signals. A complete marketing measurement plan uses both, matched to the type of decision being made.
What Is a Good Marketing ROI?
There is no universal benchmark for good marketing ROI because it depends heavily on margins, customer lifetime value, and payback period. A channel delivering 3x ROAS with strong retention and high margins may outperform a channel at 6x ROAS where customers churn quickly and margins are thin. Evaluating ROI in the context of customer value and payback period gives a more accurate picture than any single ratio.
How Do You Improve Marketing ROI?
Improving marketing investment ROI typically comes from three places: identifying and cutting spend in channels that are capturing existing demand rather than creating new demand; reallocating toward channels with demonstrated incremental lift; and building upper-funnel investment that reduces customer acquisition costs downstream. Incrementality testing is the most reliable tool for identifying which of these opportunities exists in your specific channel mix.
Conclusion
Knowing how to measure marketing ROI has always required judgment alongside data. What has changed is that the data itself has become less reliable as a standalone guide. Attribution models over-credit demand capture. Platform dashboards optimize within closed ecosystems. Blended ROAS hides where spending stops working. And the channels doing the most to build future demand are often the ones that look weakest in a standard report.
The organizations closing this gap are building unified marketing measurement approaches that combine causal proof with directional confidence, match standards to funnel position, and make budget decisions at a cadence that reflects how fast markets actually move.
If you are building this capability, start with the questions before the tools. Identifying which decisions your current stack cannot support is more valuable than adopting new marketing measurement tools before you know what gaps they need to fill. And for teams beginning with organic and content investment, this breakdown of content marketing ROI applies the same incremental thinking to channels that are often the hardest to measure and the most underfunded as a result.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00Dubado Solutionshttp://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.pngDubado Solutions2026-04-15 07:00:002026-04-15 07:00:00How Smart CMOs Decide Where the Next Marketing Dollar Goes
Google’s Ask Maps feature does more than help users find nearby businesses.
Based on hands-on testing of local service queries for plumbers, electricians, and HVAC companies, Ask Maps often narrows the field, interprets user intent, and frames businesses around qualities such as responsiveness, specialization, honesty, and repair-first thinking.
In more complex prompts, it sometimes provides guidance before recommending businesses. This shows Google Maps moving beyond simple local retrieval and toward a more recommendation-driven experience.
To evaluate that shift, we tested Ask Maps across five levels of local intent — starting with simple category searches and progressing toward conversational prompts involving uncertainty, trust, and decision-making.
A clear pattern emerged. As query nuance increased, Ask Maps shifted from listing businesses to interpreting which businesses fit and why.
This article draws from hands-on testing across a limited set of local service queries in one geographic area. Treat these findings as an early directional view, not a comprehensive representation across all markets or query types.
The testing framework
To evaluate progression, we built a five-level intent model based on how homeowners and local service customers actually search. Instead of organizing around traditional keyword categories, we structured the framework from simple retrieval toward conversational decision-making.
Level 1 focused on basic requests with minimal context.
Example: “Looking for an HVAC company near me.”
Level 2 introduced more service specificity.
Example: “I need an electrician to upgrade my panel in an older home.”
Level 3 moved into situational queries, where the user described a problem.
Example: “My furnace is making a loud banging noise and I’m not sure if it needs to be replaced or repaired.”
Level 4 introduced trust and decision concerns.
Example: “I think my furnace might need to be replaced, but I don’t want to get overcharged. Who is honest about that?”
Level 5 combined those elements into fully conversational prompts asking for guidance, validation, and recommendations in the same search.
Example: “I was told I need a full furnace replacement, but it feels expensive. How do I know if that’s actually necessary, and who should I call for a second opinion in my area?”
This framework allowed us to evaluate:
Which businesses appeared.
How Ask Maps interpreted prompts.
What attributes it emphasized.
When results started to resemble guided recommendations rather than search results.
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Ask Maps narrows the field and adds interpretation
One of the clearest patterns across the testing was that Ask Maps consistently returned a relatively small set of businesses while increasing the amount of interpretation as the user’s search intent became more complex.
At Level 1, the average number of businesses shown was 3.6. Level 2 rose to 4.3. Level 3 dropped slightly to 3.3. Level 4 averaged 5, and Level 5 averaged 4.6. Across the full set, the range remained fairly tight, generally between three and eight businesses.
That’s a different experience from traditional Maps, where a user can scroll through a much broader set of options and do more of the evaluation work themselves.
Ask Maps narrows choices early and spends more effort explaining why those businesses fit the prompt, but stops short of being fully action-oriented. Even when a phone number is shown, there’s no clickable call button directly in the Ask Maps response.
To call or access the full set of contact options, the user still has to click into the business’s Google Business Profile. That matters because while Ask Maps is becoming more interpretive, the underlying GBP is still where action happens.
As prompts become more nuanced, uncertain, or trust-sensitive, Ask Maps draws on a broader range of sources. It shows fewer businesses, replacing breadth with interpretation.
Even the simplest queries don’t behave like a traditional Maps result.
At the baseline level, Ask Maps still relies heavily on Google Business Profile data, including:
Business descriptions.
Review content.
Ratings.
Hours.
In some cases, posts.
Website influence is minimal here, and there’s little evidence of outside sourcing. But even within that mostly closed ecosystem, it goes beyond listing nearby businesses.
Instead of just showing names, ratings, and locations, Ask Maps:
Generates narrative summaries based on information in the Google Business Profile.
Describes businesses in terms of responsiveness, experience, specialization, or the kinds of situations they seem well-suited for.
Draws on reviews when framing businesses.
Even at the most basic level, Ask Maps isn’t neutral. It’s beginning to interpret businesses for the user.
As queries become more specific, Ask Maps starts matching capability
Once the prompt shifts from a general service search to a specific type of job, Ask Maps becomes more selective in how it matches businesses to the request.
A query about an electrical panel upgrade doesn’t behave the same way as a query about urgent AC repair.
Replacement-oriented prompts emphasize installation and system expertise.
Repair-oriented prompts emphasize speed, availability, and responsiveness.
Queries tied to older homes or higher-risk work call for more evidence of specialization.
At this level, Google Business Profile and reviews still carry much of the weight, but websites matter more when the job is more complex or costly. A panel upgrade query produces stronger external link usage than a more straightforward AC repair prompt.
That doesn’t mean websites are always heavily used. It shows more selectivity. As decisions become more complex, Google looks for more supporting evidence before recommending businesses.
The more noticeable shift begins once the prompts move from service categories to real-world scenarios.
At Level 3, the user is no longer looking for a plumber, electrician, or HVAC company. Instead, they’re describing a problem, such as a loud banging furnace, outdated electrical in an older home, or an AC unit that has stopped working during extreme heat. In those cases, Ask Maps increasingly interprets the problem before introducing businesses.
Some responses provide guidance or context first. Others identify the provider and clarify the work before making recommendations. The businesses that follow aren’t framed as generic providers. They’re framed as possible solutions to the situation.
Review content becomes important here. Rather than simply supporting a business’s credibility, reviews act as evidence that the company has handled similar situations before. Fast arrival times, experience with older homes, communication during stressful repairs, and problem-solving ability all become more meaningful when describing businesses.
This is the point where Ask Maps moves more clearly from retrieval to interpretation.
Trust-oriented queries change what gets emphasized
When the prompts introduce fear, skepticism, or concern about making the wrong decision, Ask Maps changes again.
At Level 4, the focus is less on the service need itself and more on the emotional context around it. The user is worried about being overcharged, being pushed into unnecessary replacement, or hiring someone who would cut corners.
Ask Maps doesn’t just return businesses capable of doing the work. It organizes businesses around trust-related qualities such as honesty, transparency, careful workmanship, fairness, and second-opinion value.
This is one of the strongest patterns in the research. At this stage, review language is the primary signal shaping how businesses are framed. Specific phrases and anecdotes matter, elevating businesses that explain options clearly, don’t upsell, offer honest assessments, or deliver careful, professional work.
External sources become more relevant here. In addition to GBP information and reviews, Ask Maps shows more willingness to pull from company websites, testimonials, third-party platforms, and educational resources when the user’s concern involves decision risk rather than just service need.
Once the query becomes trust-driven, the recommendation no longer appears to be based only on who can do the job. It reflects who is most likely to handle the situation in a way that the user feels good about.
The strongest example of this progression came at Level 5. These are prompts where the user combines a problem, uncertainty, and a request for recommendations in a single query.
For example, someone might say they were told they needed a full furnace replacement but were unsure whether that was really necessary and wanted to know who to call for a second opinion. In these cases, Ask Maps moves most clearly into a decision-support role.
Instead of leading with local businesses, it often starts with an explanation, introducing frameworks, safety context, or ways to think about the decision.
Only after that does it recommend businesses, and those businesses are often grouped not just by rating or proximity, but by approach. Some are framed as repair-first options. Others are framed as second-opinion experts or safety-focused specialists.
This is where Ask Maps feels least like a directory and most like an advisor. The structure of the response looks more like a guided decision process than a traditional local search result.
That doesn’t mean the system is flawless or that every answer is equally strong. But it does suggest that when a prompt includes uncertainty and a need for validation, Ask Maps is trying to do more than match a category. It’s trying to help the user think through what to do next.
Across the testing, several source patterns appear repeatedly, and the mix appears to shift depending on the type of query.
At the foundation, Google Business Profile does much of the early work. Business categories, service descriptions, hours, ratings, and review counts help determine which businesses are eligible to appear and how they are initially framed. In some cases, Ask Maps also pulls from GBP services and products, business descriptions, and occasionally posts when those help reinforce what the business does.
Reviews seem to be one of the most important inputs across nearly every query type. Not just in ratings, but in how review language shapes the summary.
Ask Maps often draws on review themes tied to:
Responsiveness.
Honesty.
Professionalism.
Fast arrival times.
Work on older homes.
Repair-versus-replace situations.
Whether customers feel the company explains options clearly or avoids unnecessary upselling.
In other words, reviews support reputation and help define how a business is positioned in the response.
Business websites matter more once the query becomes more specific, higher-stakes, or more tied to decision-making. In those cases, Ask Maps seems more likely to pull in service pages, testimonial pages, or other on-site business information that helps reinforce specialization, repair-first positioning, second-opinion value, or experience with a particular type of job.
That’s more noticeable in queries tied to things like panel upgrades, replacement decisions, or older-home electrical concerns than in simpler “near me” searches.
External sources are the most selective layer, but they become more visible when the query involves safety, diagnosis, pricing uncertainty, or broader decision support.
In those cases, Ask Maps pulls in:
Educational content around issues like repair-versus-replace decisions, quote validation, and electrical safety.
Third-party review and directory platforms such as Angi, HomeAdvisor, YouTube, and Facebook.
Other publicly available business information, when it helps reinforce trust, workmanship, or reputation.
In some of the trust-oriented electrician queries in particular, this outside sourcing is more prominent than in simpler local lookups, suggesting Google may broaden its evidence base when evaluating how a business is likely to operate, not just what services it offers.
Ask Maps isn’t relying on a single source of truth. It appears to be constructing an answer from a mix of Google Business Profile data, review language, business website content, and selectively chosen outside sources, with the balance shifting based on what the user is actually asking.
What this may mean for local visibility
If Ask Maps continues to develop in this direction, it could have meaningful implications for local visibility in Google Maps.
Inclusion alone may matter less than interpretation. If Ask Maps is consistently showing a smaller set of businesses and adding more explanation around them, the question is no longer just whether a business appears. It’s also how that business is framed and whether Google has enough confidence to position it as a good fit for the situation.
Review content is becoming more important than many businesses realize. The language within reviews appears to influence not just credibility, but the actual way a business is described and recommended.
Website content plays a more targeted role than many local businesses assume. It may not be equally important for every prompt, but it matters more when the service is complex, expensive, or tied to greater uncertainty.
More broadly, Ask Maps points toward a version of local search in which retrieval, evaluation, and decision support occur much more closely together. Instead of searching, comparing, researching, and then deciding across several steps, the user may increasingly be guided through much of that process within a single AI-mediated Maps experience.
What businesses and SEOs should tighten up now
If Ask Maps continues moving in this direction, the practical response isn’t to chase a new tactic or treat it like a separate channel. It’s to make the business easier for Google to understand and easier for customers to trust.
Keep the Google Business Profile current and specific
A Google Business Profile may play a bigger role when Ask Maps is trying to decide what a business does, what kinds of jobs it handles, and whether it fits a more nuanced prompt.
Review primary and secondary categories to make sure they reflect the core work accurately.
Tighten the business description so it clearly explains the services offered, the types of jobs handled, and any specialties or areas of focus.
Make sure hours, service areas, and contact details are complete and current.
Add photos that reinforce the kinds of jobs the business wants to be associated with.
Treat posts and profile updates as another way to reinforce services and activity, not just as optional extras.
Use the Services and Products sections fully, adding clear descriptions that reflect the specific jobs, specialties, and situations the business wants to be known for.
Pay closer attention to review language
If Ask Maps uses review language to shape how businesses are positioned, then the wording in reviews may matter more than many businesses realize.
Look beyond review volume and average rating.
Pay attention to whether reviews naturally mention specific jobs, customer concerns, and outcomes.
Watch for language around responsiveness, honesty, professionalism, repair-first thinking, and clear communication.
Encourage reviews that reflect real experiences rather than generic praise.
Use review trends to understand how the business is likely being framed by Google.
Revisit website content for higher-consideration services
Website content appears more likely to matter when the query is more complex, more expensive, or tied to more uncertainty.
Strengthen service pages for the higher-value or higher-risk work the business wants to be known for.
Add FAQs that address real decision points, not just basic definitions.
Include examples of the kinds of jobs handled, especially where context matters.
Reinforce trust signals such as experience, process, reviews, and proof of work.
Use language that helps explain situations like repair versus replace, older-home work, or second-opinion scenarios.
Think beyond ranking for a phrase
There’s a broader strategic shift here for local SEO. The question may no longer be only whether a business can rank for a phrase. It may also be whether Google has enough evidence to recommend that business in response to a real-world question.
Evaluate whether the business is easy to understand across GBP, reviews, website content, and broader digital mentions.
Look at whether the business is clearly associated with the jobs and situations it wants to win.
Think about trust and decision support, not just service relevance.
Focus on making the business more legible to both Google and potential customers.
Treat local optimization less like keyword matching alone and more like building a clear, consistent business profile across sources.
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The direction of Ask Maps is becoming clearer
The main question behind this research was when Ask Maps stops behaving like a directory and starts behaving more like a recommendation engine. Based on this testing, that shift starts earlier than many might expect.
Even at the most basic level, Ask Maps narrows, summarizes, and interprets. As prompts become more specific, situational, and trust-driven, they move further toward guided recommendations. At the highest level of complexity, it begins to look less like traditional local search and more like a system designed to help users make decisions.
That doesn’t mean Google Maps has fully changed into something else. But it does suggest the direction is becoming clearer. For local businesses and the people who support them, that makes this worth watching closely. Visibility inside Maps may increasingly depend not just on being present, but on being understood well enough for Google to explain why the business fits the user’s needs.
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At midnight on Jan. 5, hackers took over our Google Ads Manager Account (MCC). We weren’t alone. While it’s hard to get an exact count, hundreds, if not thousands, of agencies have been affected by the hacks, in turn affecting tens of thousands of accounts.
While I wouldn’t wish this experience on our worst enemy, having been through it, I have some insights that I hope can help you prevent the same experience from happening to your MCC account.
How we were hacked
Despite having two-factor authentication (2FA) and allowed domains enabled, the hackers were able to get into our account via an employee’s email address. It was clearly a targeted hack: the night of the hack, the hackers tried to get in via two other email accounts at our company before they succeeded with the third.
While phishing or compromised passwords may have originally gotten them into the system — we still don’t know which — we later learned that the account the hackers used had been compromised for months and that they had created their own 2FA that they had been using all along.
Once they gained access to our account, the hackers removed everyone else’s access to the MCC. They then changed the allowed domain to Gmail and granted access to over a dozen people. The hackers then created a new MCC in our company’s name and invited most of our clients. Luckily, none of them accepted.
In the few hours they were in the MCC, the hackers proceeded to create chaos. They removed all the users from some accounts and changed the payment method in others. They launched new campaigns on only a few accounts, yet somehow also attempted half-million-dollar credit card charges on two others (despite not running any ads in those accounts).
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What happened after the hack
We were very lucky. The hackers were locked out within eight hours, and we regained access in just over a week. They spent only about $100 across the MCC. Neither crazy credit card charge went through. We were fully recovered from the hack within two weeks. How did we do this? Let’s take a look at the steps we took.
Step 1: We contacted Google
When we were hacked, we immediately contacted our reps at Google. We’re incredibly lucky to have wonderful Google reps with whom we’ve built longstanding relationships, including one we’ve worked with for over three years.
These long-term relationships helped, and our reps went to bat for us. They continued to put pressure on the support cases until they were resolved and helped connect us to the resources we needed. Not everyone has their own reps, but you can also take these steps on your own.
Step 2: Fill out the forms
Our Google reps immediately directed us to their “What to do if your account is compromised” resource. From there, we filed Account Takeover Forms, alerting Google to the hack. We were directed to file a form for each of our accounts that had been hacked.
We first filed one for our MCC, even though the form, at the time, said not to use it for MCCs. It looks like that language has since been changed, which is great — don’t skip this step. Getting back into the MCC makes it easier to resolve all issues, rather than having to file tickets and coordinate access for each account.
Step 3: Contact clients
At the same time, we directed any clients who still had access to their accounts to disconnect them from our MCC, and to grant access to a non-compromised email account. That way we were able to secure the accounts, work on them, and mitigate any damages immediately. We were also able to triage our accounts to figure out which we were still able to access, and which had no admins left with access.
Step 4: Reset billing
Disconnecting from our MCC wound up being a very important step. That’s because when our accounts were disconnected from the MCC, we were easily able to reset the billing by editing the payment manager and undoing all of the payment chaos that the hackers had created. We were then able to reconnect them without issue.
Step 5: Check change history
When we eventually did get back into the accounts, we immediately checked the change history, which we were able to do at the MCC level for additional speed. All the changes the hackers made during that time were there with time stamps, allowing us to put together a timeline of the hack and remediate any remaining issues.
During all this activity, a few things were especially critical to our success in recovering the account and mitigating damage. Here’s a quick rundown of best practices to keep in mind.
Make sure clients have access
This isn’t just a best practice, but something we believe should always be the case for ethical reasons. Having additional admins in the account let us regain access immediately, despite being locked out of the MCC, and remediate issues without losing time or momentum.
Google also pushed back on any access or billing changes that didn’t have approval from an existing admin, so having people still in the accounts was critical.
Keep your MCC clean
Remove old clients, and any other MCCs for tools you’re no longer using. We didn’t do this, and wish we had. We’ve made it a best practice for our accounts moving forward.
Limit team access
Make sure your team only has the minimum access they need. Standard access is great. Admin access should be reserved for as few people as possible. The compromised account belonged to a junior team member who didn’t need admin-level access.
This isn’t to say they wouldn’t have gotten in through a more senior team member’s account — as mentioned, they did try to get in through several before succeeding — but it would have mitigated risk.
Use credit cards or invoices
Neverconnect your bank accounts to your MCC. We’ve heard of companies that have lost hundreds of thousands of dollars with this same kind of hack. Because our clients were all either on invoice or credit cards, the hackers couldn’t quickly spend money in a way that hit their accounts.
As noted earlier, the credit card companies rejected the very suspicious half-million-dollar charges the hackers attempted to make, and notified the credit card holders. The clients we were invoicing were never charged, and everything was captured on the invoices before billing.
Invest in relationships
It’s important to invest in your relationships with your Google reps, and fellow agency owners. We remain incredibly grateful to all of the people who helped us, or even just commiserated with us along the way. This experience would’ve been even more painful if we’d had to go through it alone.
How to prevent being hacked
For those who have yet to be hacked, congratulations! Let’s try to keep it that way. Here are some things you can do to make it much less likely that this will ever happen to your accounts.
Start with a clean reset
Begin by kicking every single user out of your account, and have everybody on the accounts reset their passwords. Make sure you log everyone out of every session they were in on every device.
Our hackers were sitting around auto-logging in and keeping their sessions open for over two months prior to the night they took over the MCC. If we’d forced a reset and logged everyone off, we would’ve removed their access without even realizing it.
Enable 2FA and allowed domains
Make sure there’s only one 2FA per person. 2FAs that use authenticators or physical keys are better than pinging a device. The hackers had created their own 2FA to get into our employees’ accounts, and we never even had an idea that it was happening.
Audit and limit access
Make sure the minimum number of people have the minimum access they need to the MCC. This reduces your risk.
Enable multi-party approval
Google rolled out this new feature quite recently to help prevent account takeovers. Essentially, the feature requires that a second admin verifies any big changes before they happen. If you’d like to read up on this feature, here’s a great guide introducing multi-party approval.
Back up your accounts
You can copy and paste your accounts into your preferred spreadsheet app via Google Ads Editor. Make a habit of doing this periodically so that you’ll always have a copy of how things were in case of a hack. With the backups, you can easily revert back if you need to.
Use strong passwords
It’s important to use unique passwords that aren’t being used anywhere else. That way, if one site gets hacked, your MCC is still not at risk. We’re still not sure how the hackers passed the initial password stage to be able to create their own 2FA.
Invest in security monitoring
If you want to be extra careful, invest in security software and/or a cybersecurity expert to monitor your system. We have now done this, and it’s been amazing (and scary) to see how many phishing attempts have already been caught in the six weeks since we did it.
A note for clients: If you’re a client and another team is managing your Google Ads, do not accept any Google Ads MCC access requests that you aren’t expecting. Please make sure you always know who and what you’re giving access to. When in doubt, double-check with the team that is managing your account. A little caution can go a long way.
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Stay safe out there
The good news is that Google knows about these issues, and is actively finding ways to tighten their systems to prevent hacks. In the meantime, I hope this article has helped make our loss your gain. With an ounce of prevention, you’re likely to prevent a pound of pain.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500Dubado Solutionshttp://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.pngDubado Solutions2026-04-14 12:00:002026-04-14 12:00:00Google Ads MCC hacked? Here’s what to do immediately
Copywriting is persuasive writing designed to drive a specific action. It differs from content writing, which builds awareness over time.
Good copy starts with a deep understanding of your audience’s pain points. It goes deeper than just listing your product’s features.
AI can assist with drafting and scaling copy, but human strategy and judgment are what make it convert.
Craft fundamentals like tone and storytelling remain the backbone of effective copy.
Copy that demonstrates genuine expertise and cites original data is more likely to show up in AI visibility.
AI can write copy in seconds. So why does human-generated content still pull in 5.44 times more traffic than AI-generated content?
Copywriting is about getting people to act. That’s a skill that still demands a human touch.
Copywriting is different from content writing. Whereas content writing builds awareness over time, copywriting is built for one thing: conversions. Every word is focused on driving visitors to sign up or buy.
That distinction matters more than ever as AI floods the internet with generic output every day. The brands that cut through the noise are the ones treating AI like a tool, using it strategically to craft copy that speaks to real human motivations.
This guide covers what copywriting is, why it still matters in 2026, and which strategies work.
What Is Copywriting?
Copywriting is the practice of writing persuasive text to get readers to take a specific action, such as signing up for a newsletter or making a purchase. It includes everything from ads and landing pages to emails and product descriptions.
Good copy communicates your value clearly and motivates the reader to act. Features, benefits, pricing, and social proof all serve the message, but copy is what determines how those elements land with the reader.
In other words, your product or service is the offer, and your copywriting is the pitch. No matter how strong the offer is, a weak pitch won’t convert your target audience.
How Does Copywriting Differ from Content Marketing?
Content writing is the craft behind content marketing. It focuses on indirect goals, such as educating your audience or building brand awareness. Assets like blog posts and webinars fall into this category. Their aim is to bring readers in and keep them coming back.
Copywriting is more direct. Its job is to get the reader to take a specific action, right now. You see it in ads, calls to action (CTAs), and product descriptions, but it shows up everywhere decisions get made.
My own blog is a good example of both working together. The article you’re reading right now is content marketing. Its goal is to inform you about copywriting.
However, the page also contains distinct copy elements, each doing a specific job:
The headline, “Comprehensive Guide to Copywriting: 2026 Update,” gets you to click.
The banner ad above drives traffic to our Ads Grader.
The CTA below, which also shows up in the sidebar of my site, nudges you to get a free SEO analysis and potentially work with our agency.
All appear on the same page, but each has a different objective.
Is Copywriting Still Important?
AI can generate copy at scale. So, the question many marketers are asking right now is: Do you even need a human copywriter anymore?
The short answer is yes. Here’s why.
Copywriting has always been about more than stringing words together. It’s about understanding what motivates your audience and building a message that moves them to act. AI can draft and iterate quickly, but it can’t replace the strategic thinking that makes copy convert.
There’s also a trust problem. According to Accenture’s Life Trends report, 62 percent of consumers say trust is an important factor when choosing to engage with a brand.
At the same time, AI-generated content is flooding every channel. Audiences are getting better at spotting generic copy and tuning it out, and their eyes are sharpening quickly. Data from CivicScience shows 36 percent of consumers can spot AI in a brand’s marketing and won’t do business with them when they do. That number has gone up 4 percent in less than six months.
This data illustrates exactly why copywriting is so important. A well-crafted headline or an email that sounds human still requires a writer who understands the nuance behind the words.
AI is a powerful tool in the writing process, but the judgment and the strategy behind effective copy still require a person. Neglecting that human element means you could be missing out on over five times as much traffic, as we mentioned in the intro to this guide.
Types of Copywriting
Copywriting strategies vary depending on your goals. Here’s a look at how brands can apply each of the types of copywriting.
Brand Copywriting
Brand copywriting defines how a brand displays its values and personality, creating an emotional connection with its customers. It shows up in landing pages and anywhere else a brand needs to interact with its audience.
Many people picture brand copywriting as the big, flashy stuff, like what you see in Pepsi commercials and on Nike billboards. Those are some of the most visible examples, but the goal is the same no matter the scale: to create an emotional connection with your audience.
That connection drives real business results. Analysis of over 1,400 advertising case studies in the Institute of Practitioners in Advertising (IPA) dataBANK finds that purely emotional campaigns outperform those using rational content alone, generating almost double the profitability.
Take the ad below from Apple as an example. It doesn’t mention product specs or features. It’s designed to make the viewer feel they’re getting the coolest products with the best technology when they buy from Apple.
Brand copywriting is about making people emotionally connected to your brand. Done well, it turns a transaction into a lasting relationship.
Social Media Copywriting
Social media copywriting is about grabbing users’ attention as they scroll and then converting it. Every platform has its own rules, so your approach needs to adapt accordingly. Copy that works on LinkedIn, for example, won’t land the same way on X or TikTok.
That said, the goal’s the same across platforms: to get people to act. Recent data shows 89 percent of consumers say a brand’s social media impacts their purchasing decisions. That kind of conversion requires copy that’s platform-native and strongly guides viewers to a clear CTA.
While there are some nuances to creating native copy, here are a few principles that apply across channels:
Use strong, active verbs and keep sentences short.
Write in a tone that feels human, not corporate.
Lead with your hook and always include a clear CTA.
Mix it up. Rotate between educational, entertaining, and conversational content.
Use hashtags strategically to extend your reach
SEO Copywriting
SEO copywriting is the practice of writing content that ranks well in search engines and provides value to the reader. It’s about creating copy that satisfies search intent and compels the right audience to take action.
For years, the formula was straightforward: Research keywords and build high-quality content around them. That formula still holds, but the game has changed.
AI is now answering questions directly on the search engine results page (SERP), which means traffic that once flowed to well-ranked content is shrinking.
Recent data shows that the organic click-through rate (CTR) for queries featuring Google AI Overviews has dropped 61 percent (as seen in the graph below). Users are getting the information they need quickly and moving on without clicking through to your site.
The right response is to make your SEO copywriting better.
Copy that answers questions with depth and specificity, earning citations in AI Overviews, will outperform generic, keyword-stuffed content. According to the same study, websites cited in AI Overviews are seeing a 35 percent higher organic CTR than those without citations.
Thought Leadership Copywriting
Thought leadership copywriting positions your brand as a trusted authority in your industry. The goal is to deliver expert perspectives and original thinking that earns credibility with the people who matter most.
My team and I already implement this strategy through thought leadership pieces like this one on social ranking strategies from our Digital PR Director, Kimberly Deese:
This approach works well with experienced, senior audiences.
According to the recent Edelman-LinkedIn B2B Thought Leadership Impact Report, the majority of decision-makers and C-suite executives spend an hour or more each week consuming thought leadership content. And 73 percent say an organization’s thought leadership is one of the best ways to evaluate the caliber of work it’s likely to deliver to clients.
Thought leadership content takes many forms: expert interviews, research reports, essays, podcasts, and branded publications.
Nutanix is a strong example. Its online magazine, The Forecast, takes a broad look at enterprise cloud computing through expert content, and builds authority without ever leading with a product pitch.
Email Copywriting
Email copywriting is one of the most direct forms of copy you’ll write. You’re landing in someone’s personal inbox, and you have seconds to make an impression before they scroll past or hit delete.
The opportunity is worth the effort. Email marketing generates a higher return on investment (ROI) than virtually any other marketing channel, averaging $10 to $36 for every $1 spent.
What makes email copywriting distinct is the relationship it assumes. Unlike a social ad or a search result, an email speaks directly to someone who has already opted in. That trust needs to be respected.
Strong email copy starts with a subject line that earns opens and delivers value quickly, then asks the reader to take action with your CTA. Personalization and relevance are the baseline.
Tools for Copywriters
AI writing tools aren’t going away, and that’s a good thing for copywriters. They can sharpen your output when you use them strategically. Without applying your own judgment along the way, though, they can flatten it.
Here are four tools that can make your writing more efficient and impactful if you use them right.
1. Anyword
Anyword is a data-driven AI copywriting platform built specifically for marketers. Its standout feature is a predictive performance score that forecasts how well your copy will convert before you publish, based on a dataset of millions of real-world A/B-tested ad campaigns.
Anyword gives you multiple variations ranked by predicted performance. You pick the winner before spending a dollar on distribution.
It works best for performance-driven copy like paid ads. If you’re running campaigns where conversion rates directly impact revenue, Anyword’s ability to cut the guesswork makes it worth the investment.
2. Grammarly
Grammarly has been a popular copywriting tool for years. It integrates directly into the apps you already use, catching spelling and grammar mistakes and flagging tone mismatches.
In late 2025, Grammarly’s parent company rebranded to Superhuman, uniting Grammarly with productivity tools Coda and Superhuman Mail under one platform. The Grammarly writing tool itself remains unchanged. It’s just now part of a broader AI productivity suite that includes a new AI assistant called Superhuman Go.
For copywriters, the core value proposition hasn’t shifted. Grammarly is still one of the most reliable tools for catching errors and refining tone before your copy goes live.
3. Wordtune
Wordtune is an AI-powered rewriting tool built around one core idea: Your meaning is there, but the words aren’t landing yet. Paste in your copy, and Wordtune suggests alternative phrasings that preserve your meaning while improving clarity and flow.
Unlike tools focused on grammar correction, Wordtune is about expression. You can toggle between formal and casual tones and choose from multiple rewrite options for the same passage. It integrates directly into most major platforms, working wherever you write.
For copywriters, it’s most useful during the editing phase when you need to sharpen individual sentences without losing your voice. Think of it as a sounding board for your ideas.
4. Writesonic
Writesonic is a full-scale AI content platform built for marketers and content teams that need to produce high volumes of quality copy across multiple formats. Where tools like Wordtune focus on refining what you’ve already written, Writesonic is built for content generation.
Recently, the platform has grown beyond its content-generation engine roots to include SEO tools and AI visibility tracking, showing brands how they appear on platforms like ChatGPT and Perplexity. For copywriters working on search-driven content, that’s an advantage over tools that rely solely on static training data.
Writesonic is best suited for small or large teams that need to produce high-quality content and track its performance in today’s search everywhere environment.
As with any AI writing tool, of course, the output still requires human editing and strategic oversight, but it significantly reduces the time from a blank page to a working draft.
How to Copywrite: Copywriting Strategies
Tools can make you faster. Strategy is what makes you effective. Here are 10 basics of copywriting that turn good writing into copy that drives action.
1. Before You Start, Get to Know Your Audience
Great copy speaks directly to your reader. Before you write a word, you need a clear picture of who that person is.
According to Attentive’s Consumer Trends Report, 81 percent of consumers ignore irrelevant marketing messages. The fix is knowing your audience well enough that your copy never feels generic to them.
Start by building a buyer persona: a detailed profile of your ideal customer, like the one below. Pull from your actual customer data rather than assumptions. Look at who your highest-value customers are and what they have in common.
Once you have that profile, let it shape every copy decision. How does this person speak? What objections do they have to your brand? The more specifically you can answer those questions, the more directly your copy will speak to them.
Another simple tactic that works every time is writing to “you,” not “them.” Copy that addresses the reader directly, and not your audience as a group, converts better because it feels personal.
HubSpot proved this with a study of 330,000 CTAs over a six-month period. The resulting data showed that personalized CTAs performed 202 percent better than more generic CTA copy.
2. Use the Right Tone
Tone is what makes copy feel right or wrong for a given audience. It’s the attitude behind your words that signals whether your brand is playful, authoritative, empathetic, or direct. Get it wrong, and even accurate, well-written copy can push people away.
Consider two versions of copy for a fictional sales software company:
“Understand your customers better using state-of-the-art software designed to take your business from zero to hero.”
“Gain a deeper understanding of your customers using our AI-powered sales software. SellingPlus helps streamline your sales funnel and drive revenue.”
The first is approachable and slightly playful, a good fit for a scrappy startup audience. The second is polished and precise, better suited for a C-suite buyer evaluating enterprise solutions.
Using the right tone will resonate more with the person you identified in your buyer persona. When tone matches the audience, readers feel like the copy was written specifically for them.
3. Stress Your Unique Value Proposition (UVP)
U.S. e-commerce sales exceeded $1.5 trillion in 2025, according to Digital Commerce 360’s data analysis.
In a market of that size, the brands that win are the ones that are crystal clear about what they offer that their competitors don’t.
That clarity is your unique value proposition (UVP): a concise statement of what you do and why you’re the right choice over the competition.
Strong UVP copy is specific. “We help small businesses manage their finances” is a generic example.
On the other hand, “Cloud accounting software built for small business owners who hate spreadsheets” tells someone exactly whether they’re in the right place.
Brands shouldn’t try to be perfect for everyone.
A small business owner shopping on a tight budget has different needs than an enterprise CFO. A free-range egg farmer needs different tools than a factory operation.
The more precisely your copy speaks to your actual audience, the more effectively it’ll convert. Stop trying to appeal to everyone and own your unique niche clearly.
4. Use Storytelling
“Facts tell, stories sell,” is one of the oldest sayings in sales and marketing, proving that storytelling is one of the most powerful tools in a copywriter’s toolkit.
A good story is more entertaining than a list of features and far more likely to be passed along. Most importantly, it puts the reader inside an experience rather than outside looking at a product.
Allbirds does storytelling well. The footwear brand leads with a story about why its shoes exist, giving customers a sense of pride when buying from them. By the time you get to a product page, you’re already invested.
You can see from the above example that you don’t need a lengthy origin story to use this approach. Even a single sentence of narrative context can shift how copy lands. In this case, the copy tells you that the brand is about “creating better things in a better way.”
That’s a strong ethos statement that people will feel compelled to support with their wallets.
5. Solve Pain Points
Copy that leads with features tells people what you built. Copy that leads with pain points tells people you understand their problem.
The second approach tends to convert at a higher rate because it meets the reader where they actually are. And that’s a big deal given that more than 80 percent of customers ignore irrelevant marketing messages.
Take Ubersuggest. When someone considers using my keyword research tool, they’re not thinking about features. They want to outrank their competitors and show up where it counts: on Google and in AI search results. The Ubersuggest landing page copy speaks directly to that ambition.
There’s no feature list or product description. Just the outcome the audience cares about.
That focus is intentional. Your copy can’t solve every problem, and it shouldn’t try to.
Identify the most common pain points your audience faces and build your message around the one you solve best. Customer interviews and support ticket trends are all reliable ways to surface what really matters to your audience.
6. Leverage Social Proof
Consumers do their homework before they buy.
According to recent data from BrightLocal, 41 percent of consumers “always” read reviews when browsing for businesses, a significant jump from 29 percent the year before (2025).
If your copy doesn’t include social proof, then you could be leaving customers on the table.
The reason it works is that people trust other people more than they trust brands. A stranger’s review carries more weight than your best marketing copy, because it comes without a motive to sell.
There are two smart ways to use social proof in your copywriting.
First, let it inform your messaging. Reviews and customer surveys reveal exactly what language your audience uses to describe the problems and benefits they care about most.
Second, place it strategically on landing pages and homepages where buying decisions are made.
Social proof can apply to B2B brands, too. For example, Slack lets other businesses know they’ll be joining “the most innovative companies” by using their service:
That single phrase tells a prospective customer that the decision has already been made by people like them.
Case studies, testimonials, star ratings, and media mentions all establish trust before your copy even has to ask for the sale.
7. Avoid Fluff and AI Tells
In the age of AI-generated content, copy that reads like it came off an assembly line can erode trust in your brand.
AI tools can be incredibly useful, but you still need to edit like a human. That means cutting the filler phrases that weaken your message and replacing predictability with personality.
Here are some of the most common AI tells to eliminate from your copy. The fix is often as simple as deleting or reordering a few words.
“When it comes to…”
The tell:When it comes to marketing, copywriting is a must-have skill.
The fix:Copywriting is a must-have marketing skill.
“It’s important to know/remember…”
The tell:It’s important to remember to track your marketing campaign metrics.
The fix:Remember to track your marketing campaign.
“By doing X, you can do Y”
The tell:By tracking campaign metrics, you can optimize the success of your marketing.
The fix: Tracking campaign metrics helps you optimize the success of your marketing.
“Ever-evolving landscape of…”
The tell:AI tools are essential to survival in the ever-evolving landscape of copywriting.
The fix:AI tools are essential to your survival as a copywriter.
“Whether you do X or Y…”
The tell:Whether you post blogs or record videos, your storytelling skills are important.
The fix:Strong storytelling resonates regardless of the format you choose.
“ABC isn’t X—it’s Y”
The tell:Marketing isn’t about listing features, it’s about telling stories.
The fix:Marketing is about telling stories that move people to act.
“ABC does more than X — they Y”
The tell:Marketers do more than advertise products, they provide solutions.
The fix:Marketers connect people with solutions to real problems.
Predictable lists of three (“X, Y, and Z”)
The tell:Strong copy requires clarity, brevity, and a compelling call to action.
The fix:Strong copy is clear and concise, with every word earning its place, including the CTA.
If a phrase delays you getting to your point or creates a robotic cadence, cut it.
A good rule of thumb is to read your copy out loud. If it sounds like something a machine would write, it needs another pass.
8. Test Your Copywriting
What resonates with your audience today might fall flat in six months. The only way to know what’s actually working is to test it.
A/B testing web copy means running two versions of the same element against each other to see which drives more action. According to a recent benchmark report from Unbounce, the median landing page conversion rate across 41,000 pages is just 6.6 percent.
That number leaves a lot of room for improvement, and systematic testing is how you close the gap.
The key is to test one variable at a time. If you change too many things at once, you won’t know what actually moved the needle.
Focus your tests on:
Headlines: Test different angles, benefit statements, or emotional hooks.
CTAs: Try variations in wording and placement to find what drives the most clicks.
Point of view: Compare second-person options like “you can save” against direct imperatives like “save now.”
Button copy: Make small wording shifts and measure the impact on conversions.
Testing is how you stay current with what the market wants. Audience expectations shift over time, and copy that converts well in January may need to be adjusted by Q4 as seasonal priorities change.
Building testing into your process as a habit is the best way to stay ahead of the curve.
9. Use Engaging Data and SME Proof
With AI becoming widely adopted, it’s easy for just about anyone to produce content at scale. However, the question becomes: Is it effective, high-quality content?
Today, facts and data backed by subject matter expert (SME) proof are essential for your copy’s credibility and visibility.
According to the Content Marketing Institute’s B2B Content Marketing Report, only 4 percent of B2B marketers report a high level of trust in generative AI content output.
Audiences are skeptical of AI-generated copy for good reason, but one of its biggest crimes is that it often makes assertions without evidence. The way for copywriters to stand out is to be someone who actually backs their claims.
Content that demonstrates genuine expertise through proprietary data and named expert quotes is significantly more likely to earn citations in both traditional and AI-powered search.
For copywriters, the practical takeaway is to replace vague assertions with specific figures whenever possible. Swap anonymous claims for named expert quotes. Commission original research so your brand owns the data, as my team did with our AI hallucinations study:
If you can’t do that, the next best option is to source data from original, credible sources. Track data all the way back to the original organization or company that researched it.
Another best practice is to use only data points from highly credible sites. Publications such as peer-reviewed academic journals and case studies are great places to look.
Implementing these copy improvements will result in strong copy that signals to both readers and AI systems that your content is worth citing.
10. Build Your Call to Action
Potential customers who visit your website need a clear path to follow. A CTA gives them that, telling them exactly what to do next. The goal is to remove any hesitation about taking that step.
Specific language like “Get your free report” outperforms generic phrasing like “Submit.” Specificity reduces friction and makes the value clear to the customer before they click.
CTAs are even more important on landing and product pages built around a single conversion goal.
A few principles worth keeping in mind for CTA success:
Use action-oriented verbs.
Keep CTA language short.
Align the CTA messaging with the copy above it.
You can take things a step further by A/B testing your CTAs. It should be a regular part of your process, since even the smallest wording changes can drive meaningful lifts in conversion.
Copywriting for AI Visibility: What to Do
AI visibility is whether your brand gets cited or recommended by large language models (LLMs). It’s becoming as important to track as your search rankings. If your brand isn’t showing up as the answer to your audience’s queries on AI platforms, you risk being left out of the conversation entirely.
McKinsey’s AI Discovery Survey says half of consumers now intentionally seek out AI-powered search engines, and a majority say AI is the top digital source they use to make buying decisions. The good news is that many of the principles that make copy effective for humans also make it more likely to be cited by AI.
A few strategies that can help:
Lead with clear, direct answers. AI systems favor content that gets to the point.
Use specific data and named sources. Vague claims get skipped, while cited stats get repeated.
Structure content with descriptive headers. Well-organized copy is easier for AI systems to parse and extract answers from.
Include expert quotes with credentials. Named authority signals are weighted heavily as they establish credibility.
Keep your copy current. AI systems favor recently published, frequently updated content.
How to Use AI for Copywriting (the Right Way)
AI writing tools are most useful when you treat them as a first-draft engine. Editing is important, but the output is only as good as the direction and input you give it up front.
The way you design your prompts is critical in making the most out of AI-generated content. Vague requests produce vague copy. The more context you give the tool, the more useful the output will be.
Compare these two prompts:
Weak: “Write a headline for my email marketing tool.”
Strong: “Write five headline options for a landing page promoting an email marketing tool for e-commerce brands. The tone should be direct and confident. The main benefit is saving time through automation. The CTA is ‘Start your free trial.’”
The second prompt gives the AI something to work with. The first gives it practically nothing.
A strong copywriting prompt includes:
Your target audience
The goal of the piece
The tone you want
Any key points to hit
Once you have a draft, that’s where your work begins. Read it aloud and ask whether the cadence sounds or feels robotic. Does it sound like your brand? Does it lead with the right pain point and have a strong CTA?
AI can draft, but only you can judge whether it converts. Think of it as a collaboration where AI gives you the basic building blocks, and you turn it into something worthwhile.
FAQs
What is copywriting?
Copywriting is the practice of writing persuasive text designed to get the reader to take a specific action, like a sign-up or a purchase. It appears across ads, emails, landing pages, and websites. Unlike content writing, which builds awareness over time, copywriting is conversion-focused. Every word serves a purpose, and even small copy changes can produce significant lifts in revenue.
What does a copywriter do?
A copywriter specializes in creating ad copy and other marketing materials. They are also responsible for writing persuasive sales copy, such as catchy slogans and attention-grabbing headlines.
How do you become a copywriter?
You don’t need any specific qualifications to become a copywriter. What you need are strong writing skills and an ability to understand how to inspire your target audience into taking action.
Conclusion
AI can generate copy at scale, but scale without strategy produces noise. The brands that stand out are the ones investing in copy that’s human and built around a real understanding of their audience. That’s a skill no tool can fully replicate.
The strategies in this guide give you a framework to start with. As you put them into practice, dig into the psychology behind why copy converts. Understanding what motivates your reader at a deeper level is what separates good copy from great copy.
Google is changing how Google Analytics and Google Ads share consent signals — a shift that could have major implications for marketers’ tracking setups starting this summer.
What’s happening. Beginning June 15th, Google Ads data collection will rely solely on the ad_storage consent setting, removing a layer of complexity that previously came from linked Google Analytics configurations.
Until now, ad data flows between Analytics and Ads were influenced by both Consent Mode and Google Signals settings inside GA. That created confusion for marketers, especially because some of the controls were buried in Analytics settings rather than clearly surfaced in ad consent banners or tag implementations.
Starting in June, Google is simplifying that structure. Google Analytics data collection will still be governed by Google Signals, but Google Ads will look only at whether users have granted ad_storage consent.
That means a linked Google Analytics tag will no longer affect whether Google Ads can collect or use advertising identifiers.
What changes. For many advertisers, the update will effectively create a cleaner — but more rigid — consent framework.
If ad_storage is granted, Google Ads may use all available advertising signals, including linking activity to a user’s signed-in Google account when possible. If ad_storage is denied, Google will be limited to less persistent signals, such as URL parameters like gclid.
There appears to be little middle ground. Marketers will have less ambiguity about what drives ads data collection, but they will also have fewer ways to fine-tune what gets shared.
Why we care. This change makes consent settings much more consequential for measurement, attribution and audience targeting. From June, whether Google Ads can use identifiers will depend almost entirely on the ad_storage signal, so any gaps or errors in consent mode setup could directly affect campaign performance data.
It also removes some hidden complexity from linked Google Analytics settings, giving advertisers clearer rules — but less flexibility.
Between the lines. The move reflects Google’s broader push to make consent systems easier to understand for advertisers and regulators.
A single source of truth for ad consent could reduce implementation errors and make compliance easier to explain. But it also puts more pressure on brands to ensure their Consent Mode setup is working properly.
If consent updates are delayed, misconfigured or incomplete, marketers could see gaps in measurement, attribution and audience targeting.
What marketers should do now. Audit your consent implementation before the June deadline.
Teams should confirm that Consent Mode update calls are firing correctly and that ad_storage settings accurately reflect user choices. Brands with Google Signals turned off should pay particular attention: under the new setup, they could see more Ads-linked data than before if users grant ad consent.
For marketers, the takeaway is simple: cleaner rules are coming, but getting consent right will matter more than ever.
Keyword research is the process of finding and analyzing the search terms your audience uses to determine which ones are worth targeting and why.
Search intent, keyword difficulty, search volume, and topical authority are the core variables that determine whether a keyword is a viable target for your site.
AI Overviews now appear in a significant share of searches and measurably reduce click-through rates.
Long-tail keywords carry more weight than ever. They convey highly specific intent and mirror the natural language patterns behind voice and LLM queries.
Prompt research is a discipline that sits alongside traditional keyword research. It accounts for how people interact with AI tools, where query structure and user intent differ meaningfully from traditional search.
Have you been tracking your target keywords, only to watch rankings hold steady while organic traffic falls?
You’re not imagining it.
According to SEOClarity, AI Overviews (AIOs) appear for 30 percent of U.S. desktop searches, and according to Ahrefs, that presence alone reduces organic click-through rate (CTR) for position-one results by 58 percent.
You might think that makes keyword research for SEO less important now, but that couldn’t be further from the truth.
Your research still matters. What’s changed is the goal. High-volume terms alone won’t cut it anymore.
You need to identify which keywords still drive clicks and understand how large language models (LLM) prompts are reshaping the demand signals you rely on.
This guide covers the full research process, updated for how search works today.
What Is Keyword Research?
Keyword research is the process of identifying and analyzing the search terms your target audience types into search engines and LLMs. The goal is to determine which terms are worth targeting based on factors like the intent behind a user’s query.
Intent is the why behind what people search, and it’s an area many teams underinvest in.
Finding a high-volume keyword is easy enough. The harder part is understanding the true intent behind the keyword. That’s the key to making sure your content satisfies that intent better than what’s already ranking.
Why Is Keyword Research Important for SEO?
Creating content without keyword research is a gamble.
Sure, you might produce something useful. However, without confirming what people are actually searching for and that you have a realistic shot at ranking, you’re spending resources on content that may never be found.
Keyword research solves for three variables that determine whether a keyword is worth pursuing:
Search volume tells you how many people are looking for a term each month. A keyword with zero volume isn’t worth a dedicated page. Search volume alone doesn’t close the case, though. The vast majority (94.74 percent) of keywords receive 10 or fewer monthly searches, proving low-volume, high-relevance terms can still drive traffic that converts.
Keyword difficulty tells you how competitive a keyword is based on the authority of the pages currently ranking for it. This is where many teams misjudge their opportunities. A keyword with a high difficulty score might be within reach for a high-authority domain but completely out of scope for a site with limited backlink equity. Targeting beyond your domain’s current authority just adds to your backlog.
Topical authority has become increasingly important over the past two years. Google has gotten a lot better at evaluating whether a domain demonstrates depth and consistency within a topic area. Keyword research should inform a content strategy that builds clusters of related content rather than targeting disconnected terms.
There’s also the AI layer.
AIOs now appear in a significant share of searches and reshape the value of a keyword depending on whether one shows up.
Research from Seer Interactive tracking 3,119 informational queries finds that organic CTR dropped 61 percent for queries with AIOs compared to queries without them.
Notice how a more semantic long-tail keyword for the same subject produces a Google AIO versus a product-based search:
Source: Google.com
Source: Google.com
See how small differences in keywords can drastically change your results? This is why doing proper keyword research is important.
Long-tail keywords are more likely to trigger AIOs, which means users get their answer without clicking through.
That’s worth knowing, but it’s not a reason to abandon those keywords. Flag them during analysis and see where they fit in your broader strategy.
Why Search Intent Is Important for Keyword Research
Search intent is the underlying goal behind a query.
Google organizes intent into four broad categories:
Informational (users want to learn something)
Navigational (users are looking for a specific site or brand)
Commercial (users are comparing options before a purchase)
Transactional (users are ready to buy or act)
Intent type is a big deal because Google matches results to intent.
An e-commerce product page won’t rank for a query that Google interprets as informational. A how-to article won’t win for a transactional query where users want a product listing.
No amount of optimization compensates for a content-to-intent mismatch.
Use keyword research for SEO to verify intent before you commit to a content format. The fastest way to do this is to run the keyword in Google and see what’s ranking.
If listicles dominate page one, that’s what Google thinks the searcher wants. If product pages own the top positions, a blog post isn’t going to break through.
“What sort of things do they search for during the awareness, research, and transaction phases of their buying journey? Target each of these clearly in different areas of the website by bucketing groups of terms into these different intent groups,” explains William Kammer, Vice President of SEO at NP Accel.
Bucketing your keyword list by intent before mapping keywords to pages is one of the most practical things you can do to make sure your SEO efforts match how your audience actually moves through the funnel.
Prompt Research and AI Visibility
Traditional keyword research focuses on what people type into Google.
Prompt research focuses on how people interact with AI tools like ChatGPT, Perplexity, and Gemini. The patterns across them are quite different.
When someone searches Google for “email marketing tools,” they enter that short phrase (or a close variant) and scan a list of results.
When someone asks ChatGPT the same question, the query looks more like this: “I run a small e-commerce business, and I’m looking for an email marketing tool that integrates with Shopify and has automation features. What would you recommend?”
The intent might be the same, but the structure and the specificity are completely different.
LLMs take these longer queries and break them down into three key components:
Persona: Defines who the user is and helps the LLM tailor the response to them
Context: Identifies the user’s specific needs and narrows the scope of the answer
Question: The actual “ask” contained within the query defines the LLM’s output
Source: Claude.ai
This structural difference affects your content strategy.
LLMs synthesize information from multiple sources to generate a response. They evaluate content for credibility and depth.
A page optimized around a head keyword might rank well in Google but never appear in an LLM response if it doesn’t fully answer the underlying question a user would actually ask.
Prompt research is the practice of identifying the underlying questions within the full, natural-language queries people use when interacting with AI tools and the keyword-related topic clusters those queries reveal.
Think of it as keyword research for a different interface. LLMs use a process called query fan-out, breaking out a single user prompt into multiple sub-queries to retrieve information. That means your content needs to answer not just the surface question but the related ones surrounding it.
A quarter of search volume has already shifted toward AI-driven chatbots and answer engines, according to Gartner.
That shift is gradual, but it’s not stopping. Get ahead of it now by building prompt research into your workflow alongside traditional keyword research.
How to Do Keyword Research
Good keyword research starts with the same core process regardless of where you’re starting. Here’s how to work through it, whether you’re building a content strategy from scratch or auditing an existing one.
1. Revisit Your SEO Goals
Before you open a keyword tool, get clear on what you’re trying to accomplish. Your keyword strategy should follow from your business goals, not the other way around.
A site prioritizing revenue will have a different keyword mix than one focused on growing organic traffic volume. A brand building topical authority in a new vertical needs different content targets than one trying to hang on to existing rankings.
Your objectives will dictate the metrics you optimize for and which parts of the keyword funnel you invest in first.
Three common goal types shape keyword priorities:
Conversion-focused goals call for commercial and transactional keywords. These terms sit at the bottom of the funnel and carry strong purchase or sign-up intent. They also tend to have higher keyword difficulty. That means traffic volumes are often lower, but the quality is high.
Traffic-growth goals point toward informational keywords with higher search volumes. These terms attract users earlier in the funnel and are generally easier to rank for, though they convert at lower rates.
Topical authority goals are where keyword clusters shine. These are groups of semantically related terms that together signal depth of expertise to Google. The cluster approach is a longer-term play, but it’s often the only sustainable way to rank for the high-difficulty terms in competitive verticals.
Keep your competition in mind as you match keywords to goals, too.
If a transactional keyword is out of reach for your domain right now, targeting it could hurt your conversion goals and waste resources. A smarter move is finding long-tail keywords around the same seed and intent as a backdoor into that topic.
2. Keyword Discovery
Keyword discovery is where you build a broad list of potential targets before narrowing it down during analysis. A lot of teams spend too much time here without a clear method. Here’s one that works.
Start by mapping your core topic areas from your audience’s perspective. Consider their pain points and the industry terminology they naturally use. These become your seed keywords, the starting points you’ll expand through tools.
From there, enter your seed keywords into a keyword tool.
My SEO tool, Ubersuggest, has a Keyword Ideas feature that gives you dozens of variations to shape the focal point of your content.
Here’s what it delivers for the seed keyword “hiking boots”:
Run enough seed keywords through the tool to build a list of hundreds of candidates before you start cutting.
Your competitors are a valuable third-party source, too. Pull competitor domains into Ubersuggest’s Keywords by Traffic feature to see which keywords are driving traffic to their pages. This surfaces real gaps in your strategy rather than theoretical ones.
Here’s what you get when you search my domain, neilpatel.com.
One caveat to note is that tools may not yet have reliable volume data for trending or emerging topics.
Jonathan Hoffer, SEO Manager at NP Digital, notes that “in the case of new trends, they might not appear in a tool, so you’ll have to check social media or forums to see if something is trending.”
Long-Tail Keywords
Long-tail keywords are search phrases of three or more words. They carry lower search volumes than head terms, but they’re more specific. That means they face less competition and tend to attract users with clearer intent, which often translates to higher conversion rates.
“Hiking boots skechers” illustrates the point well. The difficulty score is lower than our seed keyword phrase, meaning it’s easier to rank for.
As you can see below, Ubersuggest rates “hiking boots” 39 in SEO difficulty vs. 27 for “hiking boots skechers.”
That keyword is still valuable, though, because someone typing “hiking boots skechers” probably knows exactly what they want to buy. That means the odds are good that they’re close to a purchasing decision.
A page that directly addresses that particular brand is far more likely to rank and convert than a generic “hiking boots” page ever would for that searcher.
The value of long-tail keywords goes beyond traditional SEO.
For starters, voice search queries are naturally long-tail. They’re phrased the way people speak in real life rather than in typed shorthand.
Someone typing might enter “hiking boots waterproof.” The same person using voice search asks, “What are the best waterproof hiking boots for wide feet?”
LLM prompts follow the same conversational pattern. A user asking an AI assistant a question phrases it the way they’d phrase it to a knowledgeable colleague.
Targeting long-tail keywords in these cases gives you the best shot at matching how your audience searches.
Local Keywords
Local keyword research follows the same core process as broader keyword research. There’s one important distinction, though: Potential competitors and search intent are filtered through geography.
Someone searching “pizza delivery” in Santa Monica isn’t looking for the same results as someone searching the same term in Chicago. Both are looking to get pizza delivered, yes, but the keyword effectively becomes a different target once location comes into play.
Don’t limit yourself to a single location modifier.
A pizzeria in Santa Monica can target “pizza delivery Santa Monica” and neighborhood-level variants like “pizza near the pier.” Service-specific combinations like “late night pizza delivery Santa Monica” work, too.
Each geographic variation is a keyword opportunity in its own right.
Local keywords tend to have lower difficulty than non-local ones, but that doesn’t make them uniformly easy.
Local rankings don’t run on content alone. Your Google Business Profile and the consistency of your name, address, and phone number (NAP) across the web factor in, too.
3. Keyword Analysis
By the end of discovery, you’ll have a long list of potential keywords. Keyword analysis is how you cut it down to a working set.
The primary metrics to evaluate are search volume, keyword difficulty, and search intent alignment.
A tool like Ubersuggest lets you organize all your candidates in a Keywords List and sort by these variables simultaneously, which is faster than evaluating them one at a time.
The right search volume floor depends on your goals. Don’t automatically filter out low-volume keywords. A term with 50 monthly searches and clear commercial intent can be worth more than a 5,000-volume informational keyword with no realistic conversion path.
For keyword difficulty, calibrate your threshold to your domain authority.
Sites with limited backlink equity are usually better off focusing on terms with difficulty scores under 40. Higher-authority domains have more room to compete for scores of 50 and above. What counts as realistic is site-specific.
After sorting by the numbers, run a Google search on each shortlisted keyword and analyze the search engine results page (SERP) directly. Your goal is to answer two questions:
Does the content format match what you can produce? If every top-ranking result is a detailed comparison guide and you’re planning a product page, that’s an intent mismatch.
Does your domain belong in this conversation? Look at who’s ranking. If the top results are all major publications with significantly more backlink equity than your site has, be realistic about your timeline and consider adjusting your target keyword.
You should also consider whether your target keyword generates an AIO. A keyword where an AIO is present doesn’t make it a bad target, but it does change how you measure success. For those terms, landing an AIO citation matters as much as ranking position.
Nikki Brandemarte, Sr. SEO Strategist and Local SEO Team Lead at NP Digital, offers this guidance: “Pay attention to content coverage for specific topic areas. For example, are your SERP competitors publishing multiple blogs that explain the basics of a topic, or a single comprehensive guide? This can help pinpoint gaps in topical authority.”
By the end of analysis, every keyword on your shortlist should clear these bars:
Measurable search volume
Relevant to your brand or industry
A difficulty score your domain can realistically compete for
Clear search intent alignment
A content format your site can actually produce
4. Keyword Targeting
Once you have a refined keyword list, you need to decide which keywords to pursue first and which URLs to target them with.
For prioritization, start with keywords that combine low difficulty with reasonable volume. These are your highest-probability wins. They won’t always be the most valuable keywords on your list, but early traction validates the strategy and gives you ranking data to learn from.
From there, move to high-intent commercial keywords. These carry more difficulty but have the most direct line to revenue. A few hundred visitors from a well-targeted commercial keyword can generate more return than thousands of visits from an informational term.
Finally, layer in top-of-funnel, high-volume informational terms. These are the awareness plays. They’re hard to rank for and have longer time horizons, but they’re important for building topical authority over time.
Cannibalization happens when two or more pages on your site target the same or nearly identical keywords. This splits ranking signals, creating competition between your own content.
It’s one of the more common structural problems in mature content programs. Audit for it before you start mapping new keywords to existing pages. If you find two pages competing for the same term, consolidate, redirect, or clearly differentiate the content before adding more.
5. Keyword Optimization
With your keyword targets set, optimization is how you signal relevance to search engines without sacrificing content quality. Here’s a rundown of what current best practices look like.
Title tag and H1: Your primary keyword belongs in both. This remains one of the most consistent on-page ranking signals. According to Rankability, 93.5 percent of page-one results use their target keyword in the title or H1.
URL slug: Use a clean, keyword-inclusive URL. Research shows that URLs that include the target keyword see up to 45 percent higher click-through rates than those without.
Meta description: Your meta descriptions don’t directly influence rankings, but they do influence clicks. The goal is to include the keyword naturally and give searchers a clear reason to click.
Body copy: Use your keyword and related semantic terms throughout, but write it for the reader first. Resist the urge to stuff keywords. Density has declined as a ranking factor. Pages in the top 10 today have significantly lower keyword density than those that ranked well even a few years ago.
Image alt text: Include your keyword in at least one image’s alt attribute on the page. Alt text serves accessibility and SEO purposes.
Structured data:Schema markup helps search engines and AI systems understand the content type and context of your page. For competitive keywords, structured data improves your eligibility for featured snippets and AIO citations.
Content completeness: For any keyword you’re seriously targeting, your content needs to address the topic more thoroughly than what’s currently ranking. That doesn’t mean longer for its own sake. Your piece can be shorter and still outrank what’s currently there if yours is more helpful.
For highly competitive keywords, link building to the specific page will almost certainly be part of the equation. Rankings alone won’t hold in a tough vertical without external authority pointing at the page.
6. Keyword Tracking
Systematically tracking your keyword research is what separates good SEO results from great SEO.
Rankings change, and competitor or algorithm adjustments can swiftly change the playing field. A tracking system catches those changes before they become problems.
Typically, keyword research tools include a rank-tracking feature that monitors your keyword positions daily and displays ranking distribution or visibility trends across your tracked keyword set.
Here’s what Ubersuggest’s Rank Tracking feature looks like:
You can track performance separately by desktop and mobile, which is a big plus given how differently Google’s SERPs behave across devices.
The core metrics to monitor are:
Ranking position
Organic impressions via Google Search Console
CTR
CTR is especially worth watching for any keywords where AIOs are present.
A stable ranking alongside a declining CTR is a signal that an AIO has entered the picture, but don’t panic. This is less a traffic problem and more an opportunity for content optimization. You may be able to go back and refresh that page with long-tail keywords that more properly align with AI search.
For broader keyword programs, tracking AI citation frequency is increasingly worth adding to your reporting stack. Brands cited in AIOs earn 35 percent more organic clicks and 91 percent more paid clicks than brands that aren’t cited on the same queries, according to Seer Interactive.
Citation is now a meaningful key performance indicator (KPI) alongside position.
The Prompt Research Process: Is It Any Different?
The short answer is yes. Prompt research differs somewhat from traditional keyword research, but the fundamentals overlap.
Prompt and keyword research share the same goal, though: to understand what your audience is looking for and create content that satisfies that need.
The difference is the interface.
LLM users don’t type compressed keyword strings. They ask full questions and often include specific constraints.
The prompt below breaks down how each component works together. Notice how far it goes beyond a simple keyword search:
These added layers change what a good target keyword looks like.
Here’s a practical approach to building prompt research into your workflow:
Start with your existing keyword list. Take your top commercial and informational keywords and expand them into full-sentence questions. “Email marketing tools” becomes “What’s the best email marketing tool for a small business that already uses Shopify?”
Mine community forums and Q&A platforms. Reddit threads and Quora discussions show you the actual language your audience uses when asking for help. These tend to be longer and more detailed than keyword tool data, and that specificity is precisely what LLM prompts look like.
Use your keywords in LLMs directly. Type your target topics into ChatGPT or Perplexity and observe their results and how they phrase follow-up questions. Those follow-up questions represent the sub-queries the model identified as relevant, which are also the content gaps your pages can fill.
Monitor brand mention prompts. Tools like Profound track which prompts lead AI engines to mention your brand or your competitors, and how those mentions change over time. This is the closest thing to rank tracking for LLM visibility.
The content strategy implication is to prioritize completeness.
Content scoring highly on semantic completeness appears in AI-generated answers at a rate 340 percent higher than content that scores lower, according to recent AIO research data.
LLMs reward content that fully addresses a topic, which is the same thing Google has been rewarding since the Helpful Content updates. The convergence is not coincidental.
Bonus: More Ways to Find Keywords
As your skills grow or you take on more competitive keywords, the tools below are worth adding to your stack to spot opportunities you might otherwise miss. You’ve already seen a little of what Ubersuggest can do, so let’s start there.
Ubersuggest
One sometimes-overlooked part of Ubersuggest is the Keyword Ideas feature’s ability to filter keyword results by suggestions, related terms, questions, prepositions, and comparisons.
Each filter uncovers a different angle on how people search for your topic (as shown in our hiking boots example).
The Questions modifier is particularly useful for content planning.
The Questions filter alone gives you 120 variations for “hiking boots.” They range from informational queries like “how long do hiking boots last” to commercial ones like “where to buy hiking boots near me.”
Each has a potential content angle with its own intent and difficulty profile.
It shows you exactly what people are asking about a keyword, giving you ready-made content angles and FAQ targets.
Ahrefs and Semrush
Ahrefs’ Keywords Explorer provides full SERP analysis in one dashboard.
One feature worth highlighting is the AI visibility filter in Ahrefs’ Site Explorer, which shows exactly which of your ranking keywords are currently triggering AIOs. That filter turns AIO exposure into a specific, actionable list of keywords you can monitor more closely.
Semrush has integrated AI-specific research tools into its platform, too.
Its tracking functionality enables you to monitor your brand’s performance across ChatGPT, Perplexity, and Google’s search generative experience (SGE) simultaneously. Plus, its AI sentiment feature tells whether AI-generated responses mention your brand positively or negatively.
For teams building out an AEO strategy alongside traditional SEO, that cross-platform visibility is difficult to replicate manually.
Many experienced SEOs use multiple tools in parallel, cross-referencing data from Ubersuggest, Ahrefs, and Semrush to build a more complete picture. Because volume figures are estimates and can vary by platform, using multiple tools reduces the risk of making targeting decisions based solely on a single platform’s data.
AnswerThePublic
AnswerThePublic generates question-based keyword ideas from a seed keyword. Enter a topic, and the tool maps the questions people are asking about it, organized by preposition and question type.
The output is useful for building FAQ sections and identifying informational content angles that pure volume-based tools can’t see.
For example, if you search for “social media marketing,” AnswerThePublic returns questions like “what are the best social media marketing strategies?” and “how to measure ROI in social media marketing?”
Both are strong long-tail targets with real search demand.
LLMs and AI Tools
AI tools have become genuinely useful for scaling keyword research, particularly in the brainstorming and clustering phases.
Take Claude or ChatGPT. You can rapidly expand a seed keyword into related angles and intent clusters. Use the persona component of your prompt to make them think like your target audience.
For example, you might ask an LLM to generate the questions a small business owner would ask before buying a product. Or you might dig into the objections they’d have at each stage of the purchase process.
LLM output isn’t a replacement for tool-based volume data, but it’s a fast way to surface angles you wouldn’t have thought to search for.
Here’s a sample query I ran in Claude: “What questions would someone ask before buying email marketing software?”
Source: Claude.ai
This is just a small snippet of what it returned. The LLM returned questions across a variety of categories, covering the entire buying journey someone might go through when purchasing email marketing software.
Doing the same could provide you with long-tail keyword opportunities to reach every segment of your target audience exactly where they are.
Semrush’s AI-powered keyword clustering tools take this further by grouping related keywords by semantic meaning and search intent. Running your keyword list through clustering before mapping keywords to pages can reveal topical gaps and consolidation opportunities that spreadsheet-based sorting misses.
Of course, you need to keep these tools’ limitations in mind. They’re strong at synthesis and pattern recognition but weaker at providing reliable volume and difficulty data. Use them alongside your keyword tools, not instead of them.
Search Suggestions
Search engines themselves are a free, always-up-to-date resource for keyword research. Google autocomplete, the People Also Ask box, and the related searches section at the bottom of the SERP all surface real query patterns from real users.
Google autocomplete is particularly useful for long-tail discovery. Enter your seed keyword and add a letter:
Source: Google.com
Google will suggest several popular phrases, each of which is a data point about what people search with that keyword as a root.
People Also Ask (People also search for) displays related questions that Google considers topically connected to your query, often revealing adjacent content opportunities worth targeting independently.
Source: Google.com
FAQs
What is keyword research?
Keyword research is the practice of finding and analyzing search queries to identify which ones are worth targeting with your content. It involves evaluating search volume, keyword difficulty, and the intent behind each query to build a targeted list of terms that align with your site’s goals and domain authority.
How do I do keyword research?
Start by defining your goals, then build a list of seed keywords based on your audience’s pain points and your core topic areas. Use a tool like Ubersuggest to expand that list and analyze candidates by search volume, difficulty, and intent. Audit the SERP directly for your top candidates before finalizing your targets. Then map keywords to specific pages, create or optimize content, and track performance over time.
Can I do keyword research for free?
Yes. Ubersuggest and AnswerThePublic both offer free keyword data. Google Search Console is also free. If you’re not ready to pay for a tool yet, you can use Google’s built-in search features like autocomplete and People Also Ask (People also search for). Free tools may have volume and feature limitations, but they’re more than sufficient for early-stage research or smaller sites. Paid plans unlock more comprehensive data that you may want to view as you progress.
What do I do after keyword research?
After completing keyword research, map your keywords to specific URLs, either existing pages you’ll optimize or new content you’ll create. Prioritize by intent and difficulty, then write or update content to match the search intent behind each keyword. Publish, build links where needed, and track performance in a rank tracker. Keyword research isn’t a one-time task. Revisit it regularly as your domain authority grows and as search behavior evolves.
Conclusion
Keyword research has always been the foundation of SEO.
What’s changed is the complexity of the environment you’re researching. AIOs have changed how clicks are distributed. LLMs have introduced a layer of search behavior that operates under different rules entirely. And topical authority now matters as much as optimizing individual keywords.
The teams navigating this well aren’t researching keywords in isolation anymore.
They’re combining traditional keyword analysis with prompt research and monitoring AI citation alongside ranking position. They then use that research to build content strategies around topic clusters rather than individual terms.
The process I’ve outlined here covers all that. If you want to go deeper on implementation, my complete SEO checklist walks through how keyword research connects to the rest of your optimization program.
If you’d rather have an expert team handle the execution, NP Digital’s SEO consulting services are built for exactly this kind of work and dive into keyword research for your site using the process above.
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