Citations in AI search assistants reveal how authority is evolving online.
Analyzing results across 11 major sectors shows which domains are most often referenced and what that says about credibility in an AI-driven landscape.
As assistants condense answers and surface fewer links, being cited has become a powerful signal of trust and influence.
Based on Semrush data from more than 800 websites, the findings highlight how AI reshapes visibility across industries.
AI citation trends across industries
The analysis surfaced several clear patterns in how authority is distributed across industries.
Universal authorities
Some domains appeared in the top 50 cited URLs across nearly all 11 sectors, with four domains appearing in every one:
reddit.com (~66,000 AI mentions across 11 sectors)
en.wikipedia.org (~25,000, 11 sectors)
youtube.com (~19,000, 11 sectors)
forbes.com (~10,000, 11 sectors)
linkedin.com (~9,000, 10 sectors)
quora.com (~8,000, 10 sectors)
Other domains are sector-strong but globally influential:
amazon.com (ecommerce and five other sectors).
nerdwallet.com (finance-focused).
pmc.ncbi.nlm.nih.gov (health and academic citations).
Concentration and diversity by sector
Citation concentration varies by sector.
Most concentrated: Computers and electronics, entertainment, education.
Most diverse: Telecom, food and beverage, healthcare, finance, travel and tourism.
This means some sectors rely on a handful of go-to sources, while others distribute authority across a broader field.
Relationships between visibility and SEO metrics
AI visibility and AI mentions are strongly correlated (0.87).
Organic keywords correlate more strongly with AI visibility (0.41) than backlinks (0.37).
Keywords and backlinks themselves correlate at 0.79.
By sector, the coupling between AI visibility and backlinks is strongest in computers and electronics, automotive, entertainment, finance, and education.
In these sectors, the scale of authority clearly helps drive AI references.
Sector breakdowns
Finance
Media brands such as Forbes and Business Insider dominate citations, reflecting the importance of timely commentary and market analysis.
However, NerdWallet shows that specialized finance experts can achieve high AI visibility by building deep evergreen guides and comparison content.
This sector also shows one of the strongest correlations between AI visibility and backlink scale, suggesting that authority signals remain highly influential.
Healthcare
Academic and government domains are heavily cited.
The dominance of PubMed Central (PMC), CDC, and national health portals underlines the central role of trusted peer-reviewed or official information.
Wikipedia also appears consistently, often serving as a layperson-friendly entry point.
Diversity is lower here compared with consumer-facing sectors, reflecting the need for evidence-based references.
Travel and tourism
Citations are spread across government advisories (for example, gov.uk travel advice), booking platforms, forums, and user-generated communities.
This diversity reflects the mix of practical (visa, safety), inspirational (guides, blogs), and transactional (booking) content users need.
The sector’s Herfindahl-Hirschman Index (HHI) score is low, suggesting no single authority dominates, and visibility is earned by serving very specific user needs.
Entertainment
User-generated platforms dominate.
Reddit, YouTube, and Quora all appear near the top of cited domains, alongside reference sources such as Wikipedia and IMDb.
This highlights how conversational, community-driven content is central to how AI assistants explain and contextualize entertainment.
In this space, backlink counts are less predictive than breadth of coverage.
Education
Citations concentrate around reference authorities including Wikipedia, university portals, and open-courseware providers.
Specialist learning platforms and forums also feature, but the dominance of well-known academic sources creates a more concentrated citation environment.
Here, AI assistants lean heavily on authoritative, structured content.
Computers and electronics
Technology news and review sites dominate, with CNET, The Verge, and Tom’s Guide appearing prominently.
Wikipedia is again present, but the sector is notable for its concentration, with citations clustering around a few highly recognizable review hubs.
This sector also shows one of the highest correlations between AI visibility and backlink scale, underlining the competitive role of authority signals.
Automotive
A mix of consumer guides (for example, Autotrader, AutoZone) and publisher content.
Insurance and financing providers also receive citations, reflecting user queries that span from buying cars to managing ownership.
Citations are somewhat more evenly distributed, but AI assistants lean on a balance of transactional and informational sources.
Beauty and cosmetics
Influencer-led platforms and community discussion spaces are frequently cited alongside brand websites and review hubs.
The combination of user-generated content and brand authority makes this sector more diverse than average.
Here, social-driven citations compete with established publishing brands.
Food and beverage
Recipe hubs, nutrition authorities, and community cooking sites dominate.
Wikipedia also features, especially for ingredient-level explanations.
The sector has one of the lowest HHI values, meaning a wide diversity of domains are being cited.
Backlink totals are less correlated with visibility here. Instead, topical coverage breadth seems to matter more.
Telecoms
Citations are relatively diverse, ranging from provider help portals to tech media and consumer advocacy sites.
Forums like Reddit often feature in troubleshooting contexts.
The sector’s low HHI suggests no single authority dominates, but users’ practical questions drive AI systems to reference customer-support-style material.
Real estate
Cited domains include large listing platforms (for example, Zillow-type sites), financial services tied to mortgages, and government portals for regulation and housing data.
While concentrated, the sector also pulls from news sources when market conditions are being explained.
The patterns in AI citations carry direct lessons for brands and SEOs, highlighting:
How authority is built.
What types of assets AI prefers to reference.
Why traditional SEO levers now interact differently with visibility.
Reference assets matter
Evergreen guides, standards, and explainers attract citations from both search engines and AI models.
To compete with Wikipedia or government sites, brands need to publish authoritative, fact-checked material that others can comfortably reference.
Breadth of coverage drives visibility
Domains with a wide organic keyword footprint consistently show stronger AI visibility.
This means that covering an entire topic area comprehensively – not just optimizing for a handful of high-volume keywords – positions a brand as a reliable reference source.
Sector rules differ
Each sector rewards different authority signals. In healthcare, peer-reviewed or government-backed resources dominate.
In entertainment, community-driven and UGC platforms rise to the top. In finance, explainers and calculators from expert brands are frequently cited.
Brands need to adapt their content strategy to the trust model of their sector.
Fewer links, higher stakes
AI assistants often cite only a handful of sources per response.
Being included delivers disproportionate visibility.
Conversely, being absent means competitors capture nearly all of the exposure.
This concentration raises the bar for what counts as a reference-worthy asset.
Backlinks still matter, but less directly
While backlink scale correlates with AI visibility, the correlation is weaker than for organic keyword breadth.
This suggests backlinks remain an authority signal, but the breadth and relevance of content may be more critical in an AI-driven environment.
User intent alignment
AI assistants pull from sources that best align with the specific intent behind a query.
Brands that anticipate user needs – whether transactional, informational, or troubleshooting – stand a better chance of being cited.
Creating layered content (guides, FAQs, tools) that matches different intents strengthens visibility.
Becoming a referenced brand
Citations in AI search results reveal the trust networks that underpin the next wave of search.
Wikipedia, Reddit, and YouTube are universal reference points, but sector-specific authorities also matter.
For brands, the lesson is clear: to win visibility in AI-driven search, you need to be the page that others cite.
That means authoritative content, breadth of coverage, and assets designed to be referenced.
Analysis methodology
The analysis drew from AI citation data spanning 11 sectors and more than 800 domains, using responses from Google AI Mode, Perplexity, and ChatGPT search.
Two primary metrics were calculated:
AI visibility score: The average share of responses in which a domain was cited across Google AI Mode, Perplexity, and ChatGPT search.
AI mentions: The total number of times a domain was cited across those engines in a given sector.
These metrics were then enriched with:
Organic keywords (Semrush): The number of keywords for which a domain ranks in organic search.
Backlinks (Semrush): The total backlinks pointing to a domain.
Spearman correlation
To measure the degree of correlation between metrics, I used the Spearman correlation coefficient.
Unlike Pearson correlation, which assumes linear relationships, Spearman looks at whether the ranking of one metric moves in step with another.
In simple terms, if domains with higher keyword counts also tend to rank higher for AI visibility, the Spearman value will be high even if the relationship is not a perfectly straight line.
A value near +1 means the two rise together consistently, near -1 means one rises as the other falls, and near 0 means no clear pattern.
Concentration of the HHI
I then measured citation concentration using the Herfindahl-Hirschman Index, a metric borrowed from economics.
It is calculated by summing the squares of market shares, in this case, each domain’s share of AI mentions in a sector.
An HHI closer to 1 means a sector is dominated by just a few domains, while values closer to 0 indicate citations are spread more evenly.
For example, an HHI of 0.05 suggests a concentrated landscape, whereas 0.02 points to greater diversity.
By combining AI visibility, citation counts, SEO scale (keywords and backlinks from Semrush), Spearman correlations, and HHI concentration, I built a cross-sector picture of who holds authority in AI-driven search.
Let’s get one thing straight before the industry turns “GEO” into yet another three-letter source of confusion.
Generative engine optimization isn’t SEO with a new hat and a LinkedIn carousel. It’s a fundamentally different game.
If you’re still debating whether to swap the “S” for a “G,” you’ve already missed the point.
At its core, GEO is brand marketing expressed through generative interfaces.
Treat it like a technical tweak, and you’ll get technical-tweak results: plenty of noise, very little growth.
CMOs, this is where you step in.
SEOs, this is where you either evolve or get automated into irrelevance.
The question isn’t what GEO is – that’s been done to death.
It’s how to tell if your GEO is actually working.
The North Star: Share of search (not ‘share of voice,’ not ‘topical authority’)
The primary metric for GEO is the same one that should already anchor any brand-led growth program: share of search.
Les Binet didn’t coin a vanity metric for dashboards.
Share of search is a leading indicator of future market share because it reflects relative demand – your brand versus competitors.
If your share is rising, someone else’s is falling, and the future tilts your way.
If it’s declining, you’re mortgaging tomorrow’s revenue. That’s the unglamorous magic of it.
It isn’t perfect. But across category after category, share of search predicts brand outcomes with a level of accuracy that should make “awards case studies” blush.
And yes, GEO affects it, often through PR.
When an LLM recommends your brand (linked or not), some users still open a new tab and Google you.
Recommendation sparks curiosity. Curiosity drives search. Search is the signal.
Expect branded search volume to rise as generative usage grows, because people back-check what they see in AI results.
It’s messy human behavior, but it’s consistent.
Your first diagnostic: plot your brand’s share of search against your closest competitors.
Use Google Trends or My Telescope for branded demand, and triangulate with Semrush.
Watch the trend, not the weekly wobbles.
And do not confuse share of search with share of voice.
Different metric. Different lineage. Different purpose.
The two halves of the signal: Brand demand and buyer intent
Share of search has two practical layers for GEO diagnostics:
Brand search: The purest signal of salience. Are more people looking for you than last quarter, relative to the category? That’s how you know your brand availability is increasing inside generative engines and the culture around them.
Buyer-intent traffic: The money end. Of your non-branded search clicks, how much is clearly commercial or buyer-intent versus informational fluff? And how does your share of that buyer-intent traffic compare to competitors?
You won’t know a rival’s exact click-through rates – and you don’t need to.
Use Semrush to estimate non-branded commercial demand at the topic level for you and them, then compare proportions.
Export everything and segment aggressively by intent.
Where tool estimates diverge from your actuals, you’ll learn something about the noise in third-party data and the real shape of your market.
If your brand search is flat but buyer-intent share is rising, congratulations – you’re harvesting demand but not creating enough of it.
If brand search is rising but buyer-intent share isn’t, you have a conversion or content problem – your GEO is sparking curiosity, but your site and assets aren’t turning that into qualified traffic.
If both are up, pour fuel.
If both are down, stop fiddling with prompts and fix your positioning, advertising, and PR.
Competitors are winning in AI answers. Take back share of voice.
Benchmark your presence across LLMs, spot gaps, and get prioritized actions.
Compare share of voice and sentiment in seconds.
Category entry points: The prompts behind the prompts
GEO lives or dies on category entry points (CEPs) – Ehrenberg-Bass’ useful term for the situations, needs, and triggers that put buyers into the category.
CEPs are how real people think.
“I just left the gym and I’m thirsty.” That’s why there’s a Coke fridge by the exit.
“I’ve just come out of a show near Covent Garden and need food now.” That’s why certain restaurants cluster and advertise there.
These are not keywords. They’re human contexts that later materialize as words.
Translating that to GEO: your customers’ prompts in ChatGPT, Gemini, Perplexity, and AI Mode reflect their CEPs.
Newly appointed marketing manager under pressure to fix organic? That’s a CEP.
Fed up with a current tool because the price doubled and support disappeared? Another CEP.
Map the CEPs first, then outline the prompt families that those CEPs produce.
The wording will vary, but the thematic spine stays consistent: a role, a pain, a job to be done, a timeframe.
Once you’ve mapped CEPs to prompt families, you can evaluate your prompt visibility – how often and in what context generative engines surface you as a credible option.
This is a brand job as much as a content job.
LLMs don’t “decide” like humans. They triangulate across signals and citations to reduce uncertainty.
Distinctive brand assets, third-party coverage (PR), credible reviews, and consistent evidence of capability all raise your odds of being recommended.
Notice I didn’t say “more blog posts.” We’ll come back to that.
Once you’ve outlined your prompt families, test visibility systematically.
Run qualitative checks in the major models. Log the sources they cite and the types of evidence they appear to weight.
Are you visible when the CEP is “newly promoted CMO, six-month plan to grow organic pipeline”?
Are you visible when it’s “VP of ecommerce losing non-brand traffic to marketplace competitors, needs an alternative”?
If you’re absent, don’t complain about model bias – earn your spot with PR, credible case studies, and assets that reinforce what the engines are trying to prove about you.
Next, switch to the quantitative side.
In GSC, build regex filters for conversational queries – the long, natural-language strings (4 to 10 words, often more) that resemble prompts with the serial numbers filed off.
We don’t yet know how much of this traffic comes from bots, LLM scaffolding, or humans typing into AI-powered SERPs, but we do know it’s there.
Track impressions, clicks, and the proportion that are clearly buyer-intent versus informational.
If your conversational query clicks are growing and skewing commercial, that’s a strong signal your GEO is turning curiosity into consideration.
The two-second rule: Why informational content won’t save you
Here’s a hard truth for the SEO content mills: informational traffic is about to become even less valuable.
Most AI citations offer only fleeting exposure.
Brand recall takes more than a glance – in both lab and field data, you get roughly two seconds of attention to make anything stick.
Most sidebar mentions and AI Overview snippets don’t deliver that, and the memory fades fast anyway.
If your GSC export shows that 70% or more of your clicks come from “how-to” mush with no buyer intent, your GEO isn’t working.
It’s subsidizing the LLMs that will summarize you out of existence.
Fix the mix – shift your asset portfolio toward category entry points that actually precede purchase.
Here’s your weekly CMO/SEO standup. Four lines, no fluff.
1. Share of search (brand)
Your brand’s share versus your top three competitors, trended over 13 weeks.
Up is good. Flat is a warning. Down means it’s time to get comms and PR moving.
2. Share of buyer-intent traffic
Your estimated share of non-brand commercial clicks versus competitors (from tool triangulation), plus your actual buyer-intent clicks from GSC.
The gap between the two is your reality check.
3. Prompt visibility index
For each priority CEP, how often are you recommended by major models, and with what supporting evidence?
Track monthly.
Celebrate gains.
Fix absences with PR and proof.
4. Conversational query conversion
Impressions and clicks on 4–10+ word natural-language queries, segmented by intent.
Are the commercial ones rising as a share of total? If not, your GEO is a content cost center, not a growth driver.
How to read the scoreboard
If those four lines are improving together, your GEO is working.
If only one is improving, you’re playing tactics without strategy.
If none are improving, stop thinking you can “Wikipedia” your way to growth with topical-authority fluff.
The levers that actually move GEO
What moves the dial? Not more “SEO content.” GEO responds to the levers of brand availability:
PR that builds credible third-party evidence: Reviews, analyst notes, earned features, and founder or expert commentary with substance. LLMs love corroboration.
Customer-centered case studies: Framed around CEPs, not your product roadmap. “Marketing manager replaces X to cut acquisition costs in 90 days” beats “New feature launch.”
Tighter copy: Precise, functional language matched to CEPs and prompt families. Kill the poetry.
Experience signals: Your site must resolve buyer intent fast. The conversation from AI should land on pages that continue – not restart – the dialogue.
Content still matters, but only as support for these levers.
Most of your old blog inventory was never going to build memory or distinctiveness, and in an AI-summarized world, it certainly won’t.
Scrap the vanity spreadsheets. Build assets that make both engines and humans more certain you’re the right choice in buying situations.
Yes, content marketing is back in a big way – but that’s another article.
GEO isn’t just SEO
When AI modes become the default interaction layer, and they will – whether through chat, answers, or blended SERPs – the game rewards brands that are easy for machines to recommend in buying moments.
That is GEO’s beating heart: increasing AI availability.
Think of it like free paid search.
If you’re still obsessing over informational traffic and topical hamster wheels, you’ll be caught with the lights on and no clothes. Some of you already are.
SEOs who make the leap become organic-search strategists.
You’ll speak CEPs, buyer intent, and brand effects.
You’ll partner with PR, product marketing, and sales enablement.
You’ll still use the tools – Semrush and GSC – but you’ll use them to evidence strategy, not to justify content churn.
The rest of you? You’ll be replaced by an agentic workflow that writes better filler faster than you ever could.
The humbling truth about GEO
Marketing rewards humility.
You are not the consumer, and you are certainly not the model.
Stop guessing. Measure the four lines.
Map the category entry points.
Build the assets that make you easy to recommend.
Cross-reference tool estimates with your own data and let the differences teach you.
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Yoast SEO is a free WordPress SEO plugin that helps your site perform better in search engines like Google. It also gives you the tools to bring your content to the highest SEO and overall readability standards. Here, we’ll explain how our plugin helps you build the best website possible!
Yoast SEO offers many tools and features to boost your SEO. Some of these features influence the SEO of your whole site, while others help you optimize individual posts and pages for search engines.
At Yoast, we believe in our mission, “SEO for everyone,” so you can access all the essential WordPress SEO tools in our free Yoast SEO plugin. But if you really want to boost your SEO, upgrade to Yoast SEO Premium. This upgrade gives you even more amazing SEO features, including great AI features like Yoast AI Optimize and AI Summarize! Keep reading to find out what Yoast SEO can do for your SEO!
SEO for your posts and pages
If you want your posts and pages to appear in the search results, you need to optimize them! So, when you use WordPress to create/edit posts, you’ll find a lot of Yoast SEO tools to help you draft and optimize great content. And if you think SEO optimization is all about keywords, think again. The tools and tips in our Yoast SEO plugins also focus on quality content and user experience. Trust us, because it will all help your rankings, directly or indirectly.
Here’s how the plugins will help you optimize your posts and pages:
Make sure you’re optimizing correctly (we’ll tell you if you aren’t)
After you’ve done your keyword research, you’ll have to start optimizing the pages and posts on your sites for the keywords and keyphrases you want to rank for. To do that, you can set a focus keyphrase for an article in Yoast SEO. Then, the plugin uses our content SEO analyses to determine how your content scores on different factors. It checks how many times you use your keyphrase, the length of your text, or whether you used any internal links.
The results of these analyses guide you in optimizing your post or page to rank with your chosen keyphrase. You’ll see red, orange, and green traffic lights to indicate how every factor scores. This gives you an overview of the overall score and what you can still tackle to increase your rankings!
We also give you tools to find out which keywords you can target successfully, and track how successful your content really is. For the keyword research part, we integrate with the leading online marketing platform, Semrush. For tracking the performance of your content in search, we integrate with the rank tracking platform Wincher.
The content SEO analysis tells you how to optimize your text for a certain keyword with the use of red, orange, and green traffic lights.
Guidance for writing high-quality content — in many languages!
Optimizing your content to rank with the right keyphrase is important, but don’t forget your reader! Even if you write amazing content for search engines, your audience won’t benefit from it if they don’t understand it. When a person doesn’t understand your content, the chance of them buying something from you is close to zero. The same is true for the odds of them sharing one of your articles with their friends. So, you must ensure your content is also easy to understand. And that’s where the readability features come in.
Our readability checks let you adopt the feedback in a way that suits you, without losing your personal touch. If you’re interested in all the factors that increase readability, you can read more about the Yoast SEO readability features. What’s more, you can optionally enable the inclusive language analysis alongside readability and SEO checks
The readability analysis tells you how to optimize your text to make it read easily using red, orange, and green traffic lights
All or most features are available in the following languages: English, German, Dutch, French, Spanish, Italian, Portuguese, Czech, Russian, Polish, Swedish, Hungarian, Indonesian, Arabic, Hebrew, Turkish, Norwegian, Japanese, Slovak, and Greek.* We support more languages at various levels. Check the overview for other languages.
* Unfortunately, it’s not possible to calculate the Flesch reading ease score for some of these languages. Check the overview below to see which languages.
Based on years of research
Yoast SEO’s readability features are well-researched analyses that give you feedback on how to optimize your writing. Now, this may sound strange, because the way you write can be very personal. Let us explain how it works.
The plugin uses an algorithm to check your content for factors that are proven to increase readability. We look at the use of transition words, the use of passive voice, sentence and paragraph lengths, word complexity, and more. However, we carefully crafted this algorithm to be as accurate as possible without being too strict.
Influence what Google shows in search results
Of course, you don’t just want your pages to appear in Google’s search results. You want your search results to look amazing, too! That’s why Yoast SEO has tools to let you plan and preview how each page will (probably) look when it appears on Google. This is probably something we can’t avoid here, as Google will occasionally decide it knows better and show something else instead. But by optimizing certain outputs on your page, you can indicate how Google should present your content to users. And that’s still something worth doing.
Titles and meta descriptions
With our plugin, you can specify an SEO title (the ‘headline’ of your search result) and a meta description (a short piece of text underneath your search headline, describing what users can find on your page) for each new page you publish. We’ll let you know if these are too long or if your keyword is missing. If you want to, you can also set defaults for all your pages.
The search appearance section of Yoast SEO shows how your content will look in the SERPs
You might have seen search results that contain extra parts beyond the usual headline-and-description format before. The example below contains recipes with extra information like reviews, cooking time, ingredients, and images, for instance. And that’s just one example. Extra information can be added for all kinds of results, including products!
A structured data-powered search result in Google for recipes
The way to get results like this is by using Schema structured data. We won’t lie: it’s complex, technical stuff. Luckily for you, you won’t need to know a thing about the tech wizardry behind it. Just having Yoast SEO installed means you’ll automatically have structured data output for your pages. All you need to do is select a few options to make sure it suits your needs.
Manage social outputs
Now, social media isn’t strictly a part of SEO. But when you make great content, you often want to share that content on your social feeds, too. That’s why Yoast SEO also comes with Facebook and X previews that you can adjust to make sure your content is always looking great, whoever is sharing it. You can set a specific title, description and OpenGraph image for each post. Again, if you prefer to set one standard structure for all posts, there’s an option to do that.
Technical SEO for your website
We’ve taken a look at what Yoast SEO can do for your posts and pages. But what can it do for your site overall? If technical SEO isn’t your strong suit, much of the following may not make sense to you. But don’t worry! Yoast SEOexists to make sure you don’t have to know all of these things.
Set up your site for SEO
The plugin settings are very sensible by default, and our first-time configuration also guides you through the steps to get your technical SEO settings right. Behind the scenes, our hidden features will also gear you up with an XML sitemap, a robots.txt file, site-level Schema structured data, and more.
The free version of Yoast SEO automatically generates XML sitemaps for your website, making it easier for search engines like Google to find and index your content. These sitemaps update on their own whenever you add or remove pages, so you don’t have to do any manual work. In addition, Yoast SEO gives you easy access to your site’s robots.txt file. From the plugin, you can view or edit this file to control which parts of your site search engines are allowed to crawl. Both features help search engines discover your content while giving you more control over your site’s visibility.
Thanks to Yoast SEO, you can now quickly and without additional cost add an llms.txt file to your site to guide AI systems toward your most valuable content. This simple text file helps AI tools identify and prioritize key pages efficiently, ensuring they focus on what matters most to your site.
Manage your content
As you write more and more content for your site, you’ll be looking for easy ways to manage it! The Yoast SEO plugin comes with a few features to help you manage your content well and avoid common SEO issues. For instance, when you make changes like deleting a page or changing a URL, if you don’t know what you’re doing, then things can get messy. And if you make a lot of similar pages, that can be a problem too, as Google doesn’t know which one it should direct users towards. To help you deal with SEO issues like these, Yoast SEO comes with two unmissable tools: canonical URL tags and the Redirects tool.
Canonical URLs
Canonical URLs are really helpful if you have a lot of similar content, such as a webshop with multiple variants of the same product, each having its own page. To make life easy for you, Yoast SEO automatically adds canonical tags to all content marked for indexing. All of the canonical tags will be taken care of in the background; in most cases, you won’t need to change a thing. If you do need to adjust your canonical URL tags, it’s easy to do so.
Managing redirects
Redirects are essential if you’re moving or removing content. The fact is, users will probably still find their way to the old URL, but the content they’re expecting won’t be there. That’s not only disappointing and frustrating for users, but it can also make it harder for Google to find and index your content, too. While advanced redirect management is part of Yoast SEO Premium, you can still handle basic changes using WordPress settings or other free plugins.
Managing redirects is easy with Yoast SEO Premium
Build your site structure and internal links
If you want findable content that really ranks, you need to take care of your site structure and internal linking. The Yoast SEO plugin comes with a few tools to help you manage how your content links together: there’s a text link counter, which will tell you how many incoming and outgoing internal links there are on a page, as well as an internal linking suggestions tool in Yoast SEO Premium (in the editor view), which can help you add more if necessary. These features help you build a strong site structure and make sure your important content is easy for visitors and search engines to find.
Even more technical features of Yoast SEO
By simply installing the plugin and following the steps in our configuration workout, you’re already fixing a lot of important technical SEO things for your site! We do these steps for you, so you don’t have to know about every little technical detail.
If you really want to know everything Yoast SEO can do for you, then take a look at the complete list of features. Additionally, if you are (a bit more) familiar with technical SEO, you might enjoy reading more about Yoast SEO’s hidden features that secretly level up your SEO!
Still need to learn about SEO? One of the biggest benefits of using the Yoast plugins is that they make it really easy to get started and learn as you go along! We’ll give you pointers to help you get everything right, as well as links to read more about how SEO works and how to do it.
If you want to keep learning about SEO, we also offer free training courses and resources in our Yoast SEO Academy and on our SEO blog. You can start with these basics to understand how SEO works and get more out of your website as you go.
A quick recap
In this article, we’ve shown you what Yoast SEO can do for your site. Our plugin helps you improve your content SEO by helping you set a keyphrase and telling you exactly how you can optimize your content to rank with this keyphrase. The plugin also helps you improve the readability of your content by providing feedback that you can easily incorporate into your own writing style. And last but not least, the Yoast plugin improves your technical SEO by taking care of a lot of technical things in the background.
Everything above is available in Yoast SEO’s free plugin, making it a great starting point for most WordPress users. If you ever want more advanced tools, you can always explore Yoast SEO Premium and its extra features.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-10 12:00:002025-10-10 12:00:00What does Yoast SEO do?
If you have ever run your writing through a readability checker like Yoast SEO, you have probably come across the Flesch reading score. This metric was developed more than 70 years ago and is still one of the most widely used ways to measure how easy your text is to read. But what does it actually mean, and how does it affect your writing for the web?
In this guide, we will explain how the Flesch reading score works, why it became so prominent in publishing and SEO, and how you can use it effectively today. We will also show you where it fits into the Yoast SEO plugin and why we have introduced new readability checks alongside it.
Reminder: We made changes to our readability analysis in Yoast SEO 19.3. We replaced the Flesch Reading Ease Score with the word complexity and sentence length assessments. You can find the Flesch reading ease score in the Insight tab, but we won’t use this assessment in our readability analysis anymore.
What is the Flesch reading score?
The Flesch reading score, also called the Flesch reading ease test, was created by Rudolf Flesch in the 1940s. His goal was simple: to give writers a quick way of checking whether their text was easy to understand. The formula combines three basic elements: sentence length, word length, and syllable count. When these figures are combined into the formula, which I’ll explain in just a moment, they generate a score between 0 and 100.
The highest scores are reserved for the easiest text. For example, a score in the 90s suggests that a typical 11-year-old child should be able to read it without any difficulty. A score of around 60 is closer to plain English that a high school student would be expected to understand. Scores under 30 are considered very difficult and are only really found in academic or legal writing.
Here’s a quick overview of the ranges and what they mean:
Score range
Readability level
Who can understand it
90–100
Very easy
An average 11-year-old student
80–89
Easy
Middle school students
70–79
Fairly easy
Teenagers aged 13–15
60–69
Standard
High school students
50–59
Fairly difficult
College students
30–49
Difficult
University graduates
0–29
Very confusing
Specialists, academics, or experts
Just for fun: this article itself scores around 63 on the Flesch reading score, which puts it in the “standard” range.
How the Flesch reading score is calculated
The formula behind the score looks intimidating, but don’t worry, it is surprisingly straightforward. In fact, it’s only based on two things. The total number of words divided by the total number of sentences, which gives us the ASL or Average Sentence Length, and the total number of syllables divided by the total number of words to get the ASW or Average Syllables per Word. Once we have these figures, we enter them into this formula:
206.835 – (1.015 × ASL) – (84.6 × ASW)
This will give us a score between 0 and 100. The longer your sentences and the more complex your words, the lower your score will be.
Let’s take a quick example by looking at this short text below:
“The cat sat on the mat. The dog barked.”
This has very short words and sentences, so it would score in the 90s, which means it is very easy to read.
Now compare it with:
“The domesticated feline reclined languidly upon the woven floor covering, while the canine produced a resonant vocalization.”
This is essentially the same meaning, but longer words and clauses drop the score dramatically, likely into the 30s.
This example shows why the Flesch reading score works well as a proxy for readability. It rewards writing that is concise and simple with a high score and wags a finger at writing that is dense and complex, ultimately giving it a low score.
Why the Flesch reading score became important
The Flesch reading score spread beyond classrooms into business and publishing because it answered a universal question: Is my writing easy to understand?
By the 1970s, the U.S. Navy was using it to ensure that training manuals were clear for recruits. Later, several U.S. states made it part of their official requirements for insurance documents and consumer contracts. Healthcare organizations also began using it to ensure that patient information was accessible.
When personal computers became common, Microsoft Word added the Flesch reading ease test to its spelling and grammar tools. Suddenly, anyone writing a school essay or business report could get instant feedback on readability. That mainstreamed the score and kept it relevant well into the digital age.
In the world of web writing, readability became even more critical. Online readers scan rather than study text. Research shows they decide within seconds whether a page is worth their time or not. That makes clarity a competitive advantage. Tools that included the Flesch reading score gave web writers a way to benchmark themselves and improve user experience.
The Flesch reading score in Yoast SEO
When Yoast introduced readability checks to the plugin, the Flesch reading score was one of the first tools we built in. We popularized the use of tools to score your content. It gave writers using WordPress an instant way to measure whether their content was accessible to a broad audience. You can still find the Flesch reading ease score inside the plugin today, in the insights tab.
This has helped thousands of users discover that shorter sentences and simpler words often improve how people engage with their content. While the score does not guarantee better rankings, it does contribute to a positive reading experience, which in turn can influence user behavior and SEO outcomes.
The Insights tab contains a lot of information, including your Flesch reading ease score
Why Yoast moved beyond Flesch
The Flesch reading ease score is a useful tool, but it has its limitations. For one, it only looks at sentence and word length, ignoring context, tone, and audience. A medical blog, for example, might score poorly even if it’s perfectly suited to its readers.
There’s another issue: the Flesch score combines two factors, sentence length and word length, into one number. If your score is low, you won’t know which part needs fixing. That’s why we added separate checks for sentence length and word complexity. Word complexity doesn’t just measure length; it also takes into account a few other elements, like how common a word is. Based on all these factors, it assesses the difficulty of your vocabulary, giving you clearer feedback.
This way, you can still use the Flesch score as a quick guide, but with sharper insights to refine your writing.
Should you still care about the Flesch reading score?
The Flesch reading score remains a valuable guide for writers who want to make their content more approachable. If your text scores very low, it may be worth shortening sentences or replacing long words with simpler alternatives. But you do not need to obsess over getting a perfect score.
Readability is about more than numbers. Think about your audience, their expectations, and the purpose of your content. Combine the Flesch reading score with other readability signals to create a text that is clear, engaging, and optimized for both humans and search engines.
How to use the Flesch reading ease score to improve your writing
We’ve come to the essential question. How can you use the Flesch score to improve your writing? Well, you write for an audience and know your audience the best. Before writing or editing, consider what kind of texts fit your readers. Do you sell clothes or organize photography workshops? Or do you write for a mom blog or make step-by-step DIYs? Your content should be relatively easy to read in all these cases since you are targeting a broad audience.
However, remember that you do not have to chase a high Flesch reading score at all costs. For example, you may write about complex, specialist topics for a specific, more knowledgeable audience. Or, perhaps you are an academic blogging about your research? It makes sense if the Flesch test produces a lower score in those cases.
Still, whatever your situation is, your text always benefits from concise language. So, if you want to benefit from the feedback the Flesch reading ease score gives you, focus on two things:
1. Shorten your sentences
Too many long sentences make your text difficult to read, while short sentences keep the subject clear. When the sentences in your text are short, you allow your readers to absorb the information in your text. As a result, they don’t need to use all their attention to decipher what you want to say. That is why we advise you to break down long sentences; your text will be much easier to read.
And please, don’t think that by using short sentences, you will oversimplify your text. Let’s compare two short texts to show you what we mean. First, we have this sentence:
My favorite place to visit during weekends is my grandparents’ house near the lake, where we love to fish and swim, and we often take the boat out on the lake.
Did you find this sentence easy to read? Wasn’t it too lengthy, confusing, and difficult to process? Breaking it into two or more sentences can make it much clearer:
My favorite place to visit during weekends is my grandparents’ house. It’s near the lake, where we love to fish and swim. We also often take the boat out on the lake.
These few short sentences are much easier to read. Yet, you give the same information as in the long sentence, so there is no oversimplifying. Using short sentences keeps the subject clear and lets your readers absorb the information you’re presenting.
Shorten your sentences with Yoast SEO
The Yoast SEO Readability analysis helps identify long sentences with its sentence length assessment. You can also use Yoast AI Optimize for sentence length for quick, automated improvements.
2. Limit your use of difficult words
Words with four or more syllables are considered difficult to read, so try to avoid them where possible. Or try not to use them too much. For example, try words like small instead of minuscule, about instead of approximately, and use instead of utilize. We have the word complexity assessment in Yoast SEO Premium to help you with that.
If you want to reach a broad audience, you should also try to avoid using jargon. If you’re a medical expert, you’re probably familiar with terms like analgesic, intravenous, and oophorectomy. However, keep in mind that most people aren’t. When you can’t find a better alternative, make sure to explain it for users who might not know the word.
Conclusion
The Flesch reading score has been around for decades, and it is not going anywhere. It still offers a quick way to test whether your writing is easy to follow, and it continues to play a role in Yoast SEO. At the same time, readability isn’t just about scores. Readability is about meeting your goals. By breaking down the Flesch reading ease score into clearer checks (like sentence length and word complexity), you get actionable feedback to refine your writing. That way, your content stays readable and effective.
So next time you write a blog post, take a look at your Flesch reading score. Use it as a guide, not a rule. The result will be content that your readers and search engines will thank you for.
TLDR
You should care about your score, but do not chase perfection. Balance readability with your audience’s needs
The Flesch Reading Score measures how easy a text is to read, using sentence length and word length
Scores range from 0 to 100: higher is easier. For example, 90–100 is very easy, 60–69 is standard, and 0–29 is very confusing
It became popular in education, government, and publishing before being integrated into tools like Microsoft Word and SEO platforms
In Yoast SEO, the Flesch reading score still exists in the Insights tab, but we now also use word complexity to provide more accurate feedback
Go Premium and get free access to our SEO courses!
Learn how to write great content for SEO and unlock lots of features with Yoast SEO Premium:
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-06 09:21:252025-10-06 09:21:25The Flesch reading ease score: Why & how to use it
Omnichannel marketing is a way to make your brand feel the same everywhere: website, email, ads, social, SMS, app, and in-store. People can start on their phone, switch to a laptop, and buy later without friction.
Why is this important?
Your customer doesn’t think in channels. They see one brand. If your ads, emails, site, app, and store don’t match, money slips through the cracks. Omnichannel marketing closes those gaps and moves more people to buy.
But how many more people are buying from omnichannel campaigns versus single-channel campaigns?
A lot, actually.
An Omnisend study found the purchase rate of omnichannel marketing campaigns to be 287% higher than single-channel campaigns.
Creating a seamless experience for your customers means better brand perception and higher revenue. It’s a real win-win.
This guide walks you through omnichannel marketing strategy benefits, best practices, and examples. By the end of it, you’ll understand what goes into creating an omnichannel campaign that drives results.
Key Takeaways
Omnichannel marketing creates a seamless customer experience across every touchpoint, including website, email, ads, SMS, social, app, and in-store.
Brands using an omnichannel strategy saw purchase rates 287 percent higher than single-channel campaigns in one study.
Unlike multichannel marketing, omnichannel connects your data and messaging across platforms so everything works together, not in silos.
Benefits include better customer experiences, stronger brand recognition, more personalization, higher loyalty, and increased revenue.
To get started, map your customer journey, centralize data, integrate your channels, and follow clear brand guidelines for a consistent feel.
What Is Omnichannel Marketing?
Omnichannel marketing is a marketing strategy that seamlessly integrates all of a business’s marketing channels to create a cohesive shopping experience for each customer.
As customers move through the sales funnel, an omnichannel strategy ensures all touchpoints seamlessly speak to each other so that no matter where a potential customer makes contact with your business, it feels like the same channel.
Here’s how it looks in practice.
A customer might check out a product on a brand’s website. They decide they’re not yet ready to make a purchase, but then they’re met with ads for that product across different social media channels. They can easily click through and buy the product, even though it’s not the same channel they initially used to shop.
This is what omnichannel looks like on a small scale. At enterprise scale, the same idea gets bigger. Your teams share a single customer profile, so service reps, store staff, and ads all see the same context. POS and ecommerce pull from the same inventory. Loyalty rewards apply online and in-store. Buy online, pick up in store just works.
That’s an omnichannel marketing strategy: connect data and creative across channels so customers move forward, and your revenue does too.
Omnichannel Marketing vs. Multichannel Marketing
Before we dive deeper into what omnichannel looks like, let’s talk about how it differs from a similar tactic called multichannel marketing. Both obviously occur across different channels. But they work slightly differently.
Omnichannel marketing uses multiple channels, but it ensures that all channels are integrated seamlessly, creating a connected experience. Meanwhile, multichannel marketing just occurs across different channels, treating them more as separate entities than trying to build an interconnected ecosystem.
Multichannel is useful for quick reach and simple campaigns. Think one-off promos, early tests, short cycles, or when tools and data are basic.
Omnichannel is best for cross-device shoppers, syncing online and in-store experiences, and longer, more complex customer journeys.
Bottom line: start with multichannel, then shift to an omnichannel marketing strategy when you’re ready to connect data and deliver one continuous experience.
Why Omnichannel Marketing Is Important
Your buyers don’t stick to one platform. They search on Google, watch a review on YouTube, see a Reel, ask ChatGPT for a product comparison, click an email, price-check on Amazon, and walk into a store. If you only optimize for organic search, you miss the moments that push customers to act.
Omnichannel marketing lets you show up at key points in the customer journey and connects those touchpoints so the experience feels cohesive. Your ad matches the email. The site matches the app. The cart follows the customer across devices. Service and store teams see the same history. That consistency builds trust and cuts friction, which leads to more sales.
An omnichannel marketing strategy also spreads risk. If one channel slows down, you still have paid social, SMS, marketplaces, and retail working together.
It improves measurement, too. Shared data tells you which mix drives first purchases, repeat orders, and higher order values.
People discover, compare, and buy across many platforms. Brands that coordinate messages and data across those platforms win more often. If you’re serious about growth in today’s digital world, build an omnichannel marketing strategy so your brand is clear, consistent, and present at every step.
Benefits of Omnichannel Marketing
Omnichannel marketing has a number of benefits. These advantages can provide your business with better results and happier customers.
Think of omnichannel marketing as the glue that holds your entire shopping experience together.
Improved Customer Experience
Omnichannel marketing focuses on creating an interconnected experience no matter where your customers are interacting with your business. Because of this, it creates a seamless customer experience that’s vastly better than if the different channels couldn’t speak to each other.
Here’s what that means for customers: progress carries over (carts, wish lists, support tickets), and context follows them from device to device. If they ask a question on chat, your email workflow resurfaces it. If they browse a size in the app, your site remembers.
Abandon cart emails are great examples of omnichannel marketing in action. A customer visits your website and adds an item to their cart. They leave your site without completing the purchase. That action is sent to and triggers an ‘Abandon cart’ workflow in your email marketing platform.
They receive an automated email with the item in their cart and some encouraging words and/or a discount to get them to complete the purchase.
An omnichannel marketing strategy reduces repeats, dead ends, and mixed messages so buyers feel understood and move forward faster.
Better Brand Awareness
Creating a consistent experience across platforms (including in-store) makes it easier for customers to recognize your brand. Plus, as more people have positive omnichannel experiences with your brand, they’re more likely to share it with their friends and family, boosting word-of-mouth referrals and awareness.
Consistency is a key component of a strong brand strategy. When people see the same appearance, messaging, and offers across channels, recall and trust in your brand grows. Pair that with targeted campaigns across search, social, and marketplaces, and your brand shows up more often for relevant terms with the same look and promise.
Personalization
When your marketing channels speak to each other, you’re presented with even more opportunities for gathering customer data that can be used to personalize experiences across all channels, and not just the ones they’ve used before. This personalization is just another way to improve the overall experience with your business, making it easier for customers to work with you.
Use customer actions, like product views, cart adds, and website searches to customize messaging. Recommend items that fit past behavior, pause promos after a purchase, and nudge at the right time (not just more often). Keep consent and preferences front and center.
Done well, omnichannel personalization feels like help, not hype.
Customer Loyalty
As customers discover how easy it is to work with your business, they’re more likely to stick around and continue to buy from you again and again. Why bother finding a competitor if your business has created such a seamless shopping experience?
Loyalty grows when every interaction feels smooth and familiar. Connect rewards across store and online, recognize returning customers, and close the loop on issues fast.
Use lifecycle triggers, like welcome, re-engagement, and win-back, to stay relevant without spamming. The easier you make repeat buying, the less tempted people are to price-shop elsewhere.
Competitive Advantage
Just like we mentioned, there’s no need for customers to shop around and test out your competitors if you’ve provided such a great shopping experience. Omnichannel marketing gives you a major competitive advantage, fueling more of your target audience to head straight to you rather than others in your industry.
Most teams still run channels in silos. You’ll move faster because your data, inventory, and messaging are already in sync. Creative can be reused, offers are consistent, and measurement is clearer. That speed compounds into lower costs and better customer outcomes, an edge that’s hard to copy without a true omnichannel strategy.
Higher Revenue and Conversion Rates
Naturally, if people are sharing their positive experiences, sticking around longer, and ultimately having a great relationship with your brand, you’re going to reap those benefits in the form of higher revenue and conversion rates. Which is the ultimate goal, right?
More relevance and less friction mean more adds to cart, more checkouts, and bigger orders. Omnichannel marketing also improves attribution, so you can double down on the mix that actually drives purchases and repeat business.
Over time, the flywheel kicks in: Better data leads to sharper targeting, which leads to stronger retention, which leads to higher revenue.
Best Practices for an Effective Omnichannel Marketing Strategy
Your goal is simple: build an omnichannel marketing strategy that feels consistent everywhere and moves people forward. Start with what customers do today, not what you wish they did. Then connect the channels and tools you already use, fill the gaps, and measure what actually changes behavior.
Follow along with these steps to learn more about creating an effective omnichannel marketing strategy that will boost your customer satisfaction.
Collect & Analyze Customer Data
Start by centralizing truth. Pull website analytics, email metrics, ad performance, POS data, support logs, and audience sentiment into one view so you can spot insights like:
The channels your customers prefer to use when interacting with businesses
Which devices your customers spend the most time on
The types of messaging that seem to resonate most with them
How your customers feel about your current shopping experience
Then, pick an attribution model that fits your business. Each model is tailored to different types of customer journeys and campaign goals.
For example, position-based tracking is better for businesses with longer sales cycles, like B2B and lead gen. And data-based attribution is great for omnichannel e–commerce strategies, marketplaces, subscription apps, and retailers with steady traffic.
Check out the graphic below for a full breakdown of attribution models you can use to measure the success of your omnichannel marketing efforts.
Map Out the Customer Journey
Your next step is to map out your current customer journey. Outline each step that a Your next step is to map out your current customer journey. Outline each step that a customer would have to take from first discovering your business all the way to becoming a repeat customer.
As Matthew Santos, SVP of Products and Strategy at NP Accel, explains, “Customer journey mapping involves visualizing a customer’s various touchpoints with your brand, from initial awareness to purchase and beyond. By understanding these touchpoints, you can identify which channels are most important at different stages of the journey.”
To create your map:
Identify your customers: Identify your customers’ names, addresses, and other demographic information. Look in your CRM or use a current buyer persona.
Understand their pain points: What drives your customers to make a purchase? What challenges do they want to solve?
Find out where they hang out: What platforms do your customers use during the purchase process?
Track the conversion path: How do most of your customers convert? Their path is unlikely to be straight. They might visit your website, view your Instagram reels, and then purchase in-person, in your store. Aim to define the most common paths.
In the end, your customer journey map might look something like this:
Now it’s time to identify and integrate your different sales and marketing channels, which could include:
Social media
SMS marketing
Email marketing
Your website and online store
A physical store
A mobile app
Make sure to include all channels that you’re currently using to reach your target audience plus any channels you’ve discovered your customers prefer.
For example, you might not have previously incorporated SMS messaging into your overarching marketing strategy, but your customer data analysis showed you that your target audience prefers that method of communication.
Once you’ve selected the different channels you’ll use to communicate, market, and sell to your customers, it’s time to get them to work together.
To properly integrate your marketing avenues and create a successful omnichannel strategy, you’ll need the right technology. Some tools to consider include:
CRM: A CRM can help you store customer information so that it’s accessible across channels. It can also help you segment out your audience to create even more tailored and personalized experiences. Omnisend is a great option for building out specific segmentations.
Marketing Automation Software: To build an effective omnichannel marketing strategy, you need marketing automation tools to engage more on social media, send scheduled emails, or move users through the conversion process. Many tools you already use, like email marketing, CRMs, and social media management, have built-in automation features. You can also use a tool like Zapier to build custom triggers.
Social Media Management Tools: This type of tool can make it easy to communicate with your audience across various platforms. Get access to a social inbox that puts all conversations across all platforms in one single messaging dashboard. Use auto-replies or canned responses that ensure communication is consistent across the board. Hootsuite and Sprout Social are both great options to consider for your social media management.
Customer Data Platforms (CDPs): A CDP pulls data from all your touchpoints—site, app, ads, email, POS—into a single customer profile. That unified view makes it easier to segment audiences, personalize campaigns, and keep experiences consistent across channels. Tools like Segment or mParticle help you clean, connect, and activate data without needing a dev team for every change.
Once you’ve set up the right tools and integrated all your channels, it’s time to make sure your teams are all on the same page. If your customer support team is using different messaging than your social media team, your overall strategy is going to feel disjointed.
By creating documented brand guidelines that cover how your customer-facing teams should be communicating with customers and talking about your products, you can ensure your channels feel connected.
Your brand guidelines should include things like:
Guidance for brand visuals, like logos, imagery, colors, and graphics
How to handle customer support issues or questions to create positive and consistent experiences
Tone and voice guidelines with “do’s and don’t’s” examples
Copy guidance with channel-specific examples (e.g. email subject lines vs. educational blog content)
Legal guidelines on what you can and cannot discuss, if applicable
Share your brand guidelines with your entire team and make sure everyone is familiar with them. Give constructive feedback when you see people straying.
Brand consistency is the glue that holds an omnichannel marketing strategy together.
Test & Measure Your Efforts
After sharing your brand guidelines across your company and implementing your omnichannel approach, it’s time to test everything out. Run through each of your marketing channels the way you might if you were a new customer to make sure the experience feels seamless from discovery to purchase.
Then, think about how you’ll measure success.
In omnichannel marketing, you need to consider metrics that touch every part of the funnel. For example:
Discovery: Impressions, educational blog traffic, mentions in the media
Consideration: Engagement on social media, product views, visits to company pages
Conversion: Orders, checkout rate, CPA
Loyalty: Repeat rate, time between orders, customer reviews
Use clean UTM rules, consistent naming, and dashboards that show both channel and journey views. Review the data weekly for anomalies, monthly for trends, and quarterly for bigger bets.
3 Examples of Omnichannel Marketing
Let’s look at a few examples of omnichannel marketing in practice so you can get an idea of what this could look like for your own business.
1. Sephora
Sephora offers an amazing omnichannel experience for its customers. First-time customers are able to sign up for a Sephora account using their phone number, and then keep track of all purchases there.
Customers can figure out what they’ve purchased before and when, which makes it easier for them to restock on the products they love. It also makes it easier for the marketing team to tailor messaging and special offers to each customer’s unique shopping preferences.
Sephora accounts also track customer rewards points, as well as when their birthday month is. Whether they make a purchase online or in the store, Sephora sends the customer a little sample-size product as a birthday gift.
This omnichannel strategy makes shopping with Sephora feel easy and personal, no matter where someone is making a purchase.
2. Starbucks
The Starbucks app makes for an amazing omnichannel experience that the coffee brand’s customers love. Not only can customers order through the app then pick up in a nearby store, they can also reload gift cards, pay in-store, earn and redeem rewards, and more.
The app also makes it extremely easy to find stores near you and personalizes its offerings based on the local weather. Starbucks is already a wildly popular coffee chain, but their omnichannel marketing strategy helps boost sales even more.
3. Target
Target is another great example of what omnichannel should look like. Again, customers can create an account and easily track past purchases so they can reorder products again and again with ease.
Target also has its own rewards program called Target Circle that allows users to rack up rewards they can put towards future purchases.
But one of the best things about Target’s omnichannel strategy is that customers can check online if a product is in stock at stores near them. And it’s wildly accurate, even during huge sales events like Black Friday.
The Future of Omnichannel
Omnichannel isn’t standing still. AI, automation, and privacy changes are reshaping how brands connect with customers. Search engines and social platforms now answer questions directly, sometimes before a click. In fact, nearly 60% of searches result in zero clicks.
So how does this apply to an omnichannel marketing strategy?
For marketers, it means two things.
First, you’ll need stronger first-party data—think email lists, purchase history, loyalty programs—to fuel your targeting as third-party cookies fade. Second, you’ll need systems that can use that data in real time, adjusting offers and content across every channel without manual work.
Expect channels themselves to keep expanding. Voice assistants, connected TV, chat apps, and even in-car systems are becoming part of the customer journey. The brands that win will be the ones that stay consistent across all of them.
The future of omnichannel marketing is smarter, faster, and more connected. Get your data house in order now so you can adapt as AI and new platforms evolve.
FAQs
What is omnichannel marketing?
Omnichannel marketing is the practice of connecting all your marketing and sales channels so customers get one seamless experience. Instead of each channel running in isolation, they work together. For example, a shopper might browse on mobile, add to cart on desktop, and finish in-store, with their data and offers synced across all steps. This consistency builds trust, reduces friction, and increases conversions by making every touchpoint feel like part of the same journey.
What is the difference between multichannel and omnichannel marketing?
Multichannel means using multiple platforms, but each runs separately. Omnichannel connects those platforms so the experience is unified, not siloed.
How to implement omnichannel marketing?
Start by collecting customer data, mapping the journey, and picking channels your audience uses most. Then integrate tools like CRM, automation, and analytics to sync messaging and measure results.
Create Your Omnichannel Marketing Strategy Today
Your customers want an omnichannel experience, so it’s your job to give it to them. Figure out how to make your channels work together so your customers get a personalized, consistent, and seamless experience every time they shop with your business.
Sounds like a lot, but if you follow the steps above, you can start to build a more cohesive journey for your customers. And if you’re looking for additional help, an omnichannel marketing agency like NP Digital can bring your strategy to life.
AI has infinitely sped up the hype cycle in marketing.
So when the term “vibe marketing” came onto the scene, you may have rolled your eyes for a moment before you said, “I have to try this.”
In basic terms, vibe marketing means using AI to run entire marketing workflows. Usually, this involves a combination of:
Vibe coding: No-code AI tools where you type what you want (e.g., “Build me a landing page”), and the tool spins it up
AI agents: Always-on assistants that handle background tasks, like checking your inbox for leads or updating your CRM
And whether or not they consider themselves “vibe marketers,” many teams are already doing this.
In a survey of marketing teams doing $100m+ in revenue, GrowthLoop found that more than a third of those teams use AI to optimize campaigns or predict customer behavior.
And those embedding AI into their processes report more effective strategies.
So, is vibe marketing the next wave of marketing methodology? Or just more AI hype?
In this guide, we’re diving into real-world case studies that show how marketers are using AI in their daily workflows.
Plus, we’ll test the hype against reality based on my own experiments and the perspective of industry experts.
Vibe Marketing vs. Traditional Marketing
With vibe marketing, things like campaigns, segmentation, and competitor analysis can happen in the background. So you can focus more on creative work and strategy.
Here’s how it stacks up against traditional marketing:
Task
Traditional Marketing
Vibe Marketing
Campaign creation
Weeks of strategy, briefs, handoffs, and approvals
Concepts, landing pages, and emails drafted in hours
Audience segmentation
Manual data exports and persona-building
AI builds real-time dynamic segments
Competitive analysis
Manual research on competitor websites, social feeds, reports
Automated data scraping and AI summaries
Performance reporting
Hours compiling data into slides
Real-time dashboards + plain-English insights
This all sounds incredible, and it’s all technically possible for marketing teams today.
But here’s the catch: AI workflows are still clunky and experimental.
Hootsuite reports that while 83% of marketers say their AI budgets have increased, 4 in 10 companies waste at least
10% of their AI budget on tools that didn’t deliver.
Bottom line: Don’t expect AI workflows to run your marketing overnight. Sometimes building them takes longer than doing the task manually (I learned that firsthand — more on that later).
So, what does vibe marketing look like when it does work?
6 Examples of Vibe Marketing in the Wild
Vibe marketing can seem like a vague concept.
But when we talk about using AI to automate social listening workflows, follow up with inbound leads, or run competitive analysis, all of a sudden this ambiguous concept takes on real-world meaning.
We’ll see six examples of brands using vibe marketing in their daily workflows.
Plus, how you can copy these ideas into your own strategy.
1. Build Enterprise-Level Campaigns Without Reliance on Technical Teams
The biggest slowdown in most campaigns isn’t the marketing work itself. It’s the wait for other teams to deliver what you need.
At the job site, Indeed, those delays stretched to an average of 3.5 months per campaign.
Even simple requests — like defining an audience segment — meant analysts had to pull data from their warehouse. Then, engineers had to reformat it before marketing could use it.
With vibe marketing, the team broke that bottleneck.
They used the AI platform GrowthLoop to turn raw customer data into ready-to-use segments.
Now, their team can type a plain-English prompt (e.g. “nurses in the U.S. who searched jobs in the last 30 days but haven’t applied”) and instantly generate that segment.
Instead of waiting a whole quarter to get in front of job seekers, the team can now react to hiring needs in almost real time.
Try It Yourself:
If you’re on an enterprise team already using a data warehouse tool, GrowthLoop’s makes it easy to type a goal, generate audiences, and send them directly into campaigns.
On the other hand, let’s say you keep customer data in a CRM or spreadsheet — names, emails, recent purchases.
With a tool like Clay, you can import those leads and use the built-in AI to enrich them with more data.
Then, you can create campaigns that automatically go out based on that enrichment.
For example, when a company has received funding in the last three months, they can be automatically added to a campaign.
In seconds, you’ve got a list ready to target.
What makes this powerful isn’t just faster data access.
It’s the AI layer that turns raw information into something marketing can actually act on, without waiting on anyone else.
2. Automate Social Listening Workflows
Getting a lot of mentions on social media is great — until it isn’t. Some social media managers can spend hours every day sifting through comments and posts that tag the brand.
More than just being a tedious task, this is completely unsustainable.
Which is exactly what Webflow’s two-person social team realized.
Between Reddit, X, YouTube, and forums, they faced 500+ daily mentions. But only a handful actually needed a human reply.
Finding those few was like looking for needles in a haystack.
So, they built an AI workflow to do the sorting for them.
The system scans every mention, tags it by sentiment and urgency, and pushes the important ones straight into Slack.
Out of 500+ daily posts, the team now sees just 10–15 that matter most — and responds within the hour.
Pick one high-volume channel — maybe Reddit, X, or even a busy community forum.
Use a tool like Gumloop or Apify to pull in mentions of your brand. Then, run them through an AI categorizer to flag sentiment and urgency.
Start small, check the tags for accuracy, and only then scale to other platforms.
Note: To take this workflow a step further, add a tool like ManyChat or Yuma.ai to generate automated responses to posts and DMs. Entrepreneur Candace Junée did this and saw a 118% increase in leads while saving 15 hours per month answering Instagram DMs.
3. Create On-Brand Content Assets
Ever tried to turn a 40-page technical document into a blog post or campaign copy?
The content is there, but shaping it into something clear — and in your brand’s voice and style — takes time.
At Pilot Company, with multiple sub-brands and channels to manage, that challenge multiplied.
Writers spent hours summarizing technical docs into usable briefs. Designers waited for copy that matched the right tone before prototypes could move forward.
And inconsistencies crept in across brands.
So, the team used Jasper to help build consistency in style and tone.
They used the tool’s summarizer to condense long technical documents into actionable outlines, and the brand-voice model to keep messaging aligned across sub-brands.
Designers could even pull realistic placeholder text without waiting on writers.
The result: Each team member saved 3–5 hours a week, freeing them up for strategy and storytelling instead of slogging through documents.
Try It Yourself:
With a tool like Jasper, you can add specific instructions about your brand voice, audience, and even include source material to show what great content looks like for your brand.
Then, you can use it to create copy and content for entire campaigns.
You can also use tools like Notion AI, Claude, or ChatGPT to turn long documentation into campaign content.
Start by inputting your brand voice, style, target audience, and any other details that might be useful. Then, upload documentation and ask the AI to turn it into specific pieces of content.
Test the tools to find your favorite. Make sure to give specific instructions on what kind of output you’re looking for.
Use AI to generate briefs, draft first passes, or speed up design prototypes — and reserve human time for the creative polish.
On paper, 500+ inbound marketing leads a day looks like a dream for a small agency.
But for Tiddle, a six-person influencer agency, it was a nightmare.
They were buried in the flood of messages, with only a few that were worth pursuing. Sorting through the noise ate up 6–8 hours a day — time that should’ve gone into client campaigns and outreach.
Instead of hiring more staff, they brought in AI.
Using Lindy, every inbound email was screened automatically.
Low-quality offers were politely declined, while promising ones were flagged and routed to the right person.
If terms weren’t a fit, the AI could even suggest counteroffers.
The team went from slogging through hundreds of emails to focusing only on the 10–15 real opportunities that mattered.
As Tiddle’s CEO, Mike Hahn, says, “Every deal we’ve closed in the last few months came from Lindy surfacing the right conversations.”
Try It Yourself:
Pick one channel where inbound volume is overwhelming (email, DMs, LinkedIn).
Define the “must-haves” for a qualified lead (budget, offer type, brand fit), then use a tool like Lindy or Clay to screen and tag incoming requests.
You can even set up conditional logic so the tool can change how it responds based on specific conditions.
Note: Small companies aren’t the only ones making use of AI for inbound leads. Ariel Kelmen, president and CMO of Salesforce, recently said that they use AI agents to handle interactive follow-ups with leads. And those agents manage the first 80% of the conversation.
5. Build Hyper-Personalization for Your Ideal Customer Profiles
“Hi [first name]…” personalization doesn’t cut it anymore. But manually tailoring every message to your ideal customer profiles (ICPs) is impossible to scale.
Oren Greenberg, a solo marketing consultant, faced this problem.
And since there was no system that fit his ideals of hyperpersonalization, Oren built his own.
He coded a workflow in Replit that filtered a 50,000-company dataset, excluded existing contacts, and generated outreach tailored to each company’s stage and challenges.
The result: outreach so specific it only makes sense for the intended recipient.
Pro tip: Hyper-personalization works only if you deeply understand your ICP — AI can’t do that thinking for you. But once you know who you’re selling to, it can scale bespoke messaging in ways you couldn’t manually.
Try It Yourself
If you’re a highly technical person with the skills and know-how to recreate something like this in a vibe-coding tool, then by all means have at it.
For the rest of us, using a tool like Clay is a fast path to get 80% of the way there.
Start by defining your ICP.
Then use Clay to pull in business data, filter it against your ICP criteria, and enrich it with extra context.
With that data in place, you can add an AI-powered column that drafts personalized outreach for each prospect.
Run a pilot batch of 50–100 and iterate until the system feels like true one-to-one messaging.
6. Run Competitive Analysis
New marketing roles often start with 30-60 days of slow discovery.
Who are the real competitors? What do customers actually care about? What language do they use?
Semrush’s former VP of Brand Marketing Olga Andrienko found a way to shortcut that process.
Before Day 1 at a new job, she suggests running an AI-powered competitive analysis.
Pull your site and the top competitors’ pages, transcribe the most-viewed YouTube reviews, and mine Reddit and forums for repeated complaints.
Then, feed that into an AI summarizer to surface frequent feature praise or criticism and real customer phrasing. Tools like Google Opal or Gemini help cross-link those insights into a positioning map.
Whether you’re stepping into a new role, launching a campaign, or scoping out a new market, the same workflow applies.
First, pick your brand and three competitors. With a scraper tool like Apify, get your website copy and grab a handful of top YouTube reviews and forum threads.
Then, feed those into a tool like Claude, Gemini, or ChatGPT to summarize and analyze the data.
Extract the top five pains and language customers use, and sketch a one-page positioning map you can bring to meetings.
That way, you start your campaign with clarity — not uncertainty.
My Disastrous Vibe Marketing Experiment (What I Learned the Hard Way So You Don’t Have To)
Giving you examples is great, but I wanted to put all this to the test and see if I could build a usable AI workflow for myself. (Spoiler: It did not go well.)
Goal: Save time replying to LinkedIn comments without losing my voice.
Constraints: Something I could test immediately, for free, and that would actually be useful.
Method: Build a workflow that scrapes comments, learns my style, and drafts replies I could approve before posting.
Time spent: 4+ hours
1st Attempt
First, I created an account in PhantomBuster, a tool that automates actions on social platforms like LinkedIn.
Then, I connected my LinkedIn account and set up the “LinkedIn Post Commenter and Liker Scraper” tool.
I asked it to retrieve only comments from my LinkedIn posts from recent days, which it did successfully.
Next, I created a new “Scenario” in Make, a no-code automation and AI agent tool, and added PhantomBuster as the start of that workflow.
Then, I built a Make AI Agent that would draw from my previous posts to learn my voice..
I added that Make AI Agent into the workflow, giving it instructions to analyze the comments scraped by PhantomBuster and produce a reply.
And finally, I added Google Docs as the final output. The idea was to create a document where I could see both the original comment and the AI-generated reply.
The whole workflow ran successfully, which I took as a win and closed up shop for the night.
But when I opened my laptop the next day to check all the wonderful replies my new AI buddy had written for me, all I found was this lovely Google Doc:
Still undeterred, I decided to try something different.
2nd Attempt
Along the same lines, I wanted to build an automated AI workflow that would scrape content from LinkedIn that I’m interested in. Then, write comments in my voice and style using my existing content as a foundation.
I used a similar workflow: PhantomBuster to scrape the content, Make AI Agents to analyze and write comments, and getting the final output in a Google Sheet.
Unfortunately, that gave me the exact same result (only this time in spreadsheet format, woohoo!):
What especially irked me was that the automations themselves were running successfully. But I still had no output.
So after more than four hours of work (and a lot of back-and-forth with ChatGPT), I finally gave up.
Could I have figured out this AI workflow eventually? Yes, I have no doubt.
But at that point, how much time would I be saving?
Does a little time saved on writing comments justify spending hours building an AI workflow (and what should’ve been a relatively simple one, at that)?
Here’s what I learned from this experiment:
If you’ve been secretly feeling a little skeptical about vibe marketing, you were right
The folks building vibe-coded apps and AI workflows in five minutes have years of practice. The rest of us can’t expect the same speed.
The tools that are currently available for vibe coding and AI automations aren’t ready yet for the average user to just jump in and build
If someone with a background in tech (me) struggled so much with a simple workflow, imagine the challenge of something more complex
And while it’s true that others are seeing success with vibe marketing (like the examples that we saw above), there are also clear downsides.
It’s Not All a Bed of Roses: The Caveats of Vibe Marketing
Vibe marketing is like any new marketing buzzword: We all love to join in the hype, even if we don’t quite get it.
The problem is, the hype can obscure reality.
After running my own experiments, I also talked with other experts in the field. What emerged was a clear pattern — vibe marketing is powerful, but the gaps between promise and practice are real.
It’s Harder Than It Looks
The idea that you can tinker around with AI for five minutes and produce a usable workflow just isn’t feasible for the majority of us.
And yet, that’s the promise we’re seeing over and over again:
This all sounds great, but we’re marketers: We know better.
Simple automations? Sure.
But robust, real-world systems usually need engineering support or serious AI chops.
Without that, you risk fragile prototypes that break the first time they’re stress-tested.
Oren Greenberg, the AI marketing consultant we talked about earlier, told me:
“The level of hype is out of this world. Vibe coding is cool, and there are a few people who’ve built a nice small business out of it. But it’s mostly the vendors who are minting cash.”
Here’s the point: Don’t get swept up in the hype. Check the source.
The Infrastructure Is Messy
AI workflows look slick in a demo. But in practice, you have to plug into your marketing stack.
And that’s where things get complicated.
For example, you might build the perfect AI agent to score inbound leads, only to realize that your CRM can’t accept the data the way you need.
As Austin Hay, Co-Founder of Clarity and MarTech teacher at Reforge, noted in a recent interview:
“Everyone’s excited about unstructured data, but unstructured data is useless when it needs to play nice with structured systems.”
For traditional marketing teams, this means your AI workflows may not play well with your company’s established martech systems.
And if your tech’s API documentation is outdated (or worse, nonexistent), it will be nearly impossible to vibe code your way to integrations between existing tools.
AI Can’t Invent Outside its Datasets
Another misconception around vibe marketing is that you can throw any messy, undefined problem at an AI agent and it will figure it out.
The reality is less glamorous.
AI thrives on patterns it’s seen before. Point it at a well-scoped, repeatable task, and it shines.
But ask it to invent outside of its training data — or solve a fuzzy, novel problem — and you’ll end up with loops, errors, and wasted hours.
Speed Only Works When You Know Where You’re Going
AI can help you move fast. But if you don’t know what metrics matter and where you want your workflows to lead, faster will just mean getting lost sooner.
Marketers who succeed with vibe coding are the ones who define the finish line first. AI then becomes a vehicle to reach those goals faster, not a substitute for setting them.
Kevin White, Head of Marketing at Scrunch AI, put it this way in a recent interview:
“AI multiplies the abilities of people who already know their craft. Treat it as a force multiplier for your expertise rather than a substitute for it.”
Vibe Marketing Tools Free Up Time…But for What?
As more marketers build AI workflows and vibe code their way to productivity, a philosophical question arises: why?
AI workflows and automations free up time (when they work). But, what are we freeing up time for?
By eliminating the busywork, we’ve saved only the most demanding tasks for ourselves. And while creating and strategizing may be what we enjoy most, it’s impossible for most people to do that kind of mentally-taxing work for eight hours straight.
“In conversations with CMOs, it’s clear that GenAI has become a core part of how modern marketing teams operate. What separates the winners is a commitment not just to scaling the technology, but to empowering the people who use it. Those CMOs investing in tools and talent are the ones rewriting the playbook.”
Ready to Try Your Own Vibe Marketing Experiment?
Vibe marketing isn’t snake oil. But it’s not a silver bullet, either.
The hype can make it feel like anyone can vibe code and automate their way to a marketing edge. But the reality is far more nuanced.
The marketers getting real value from vibe marketing are the ones with strong fundamentals, clear goals, and often a layer of engineering support behind them.
For the rest of us, the takeaway is simple:
Vibe marketing is worth experimenting with, but it won’t replace strategy, judgment, or hard-won expertise.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-03 14:08:552025-10-03 14:08:55Vibe Marketing: Hype, Reality, and Real Case Studies
ChatGPT recommends products — complete with photos, pricing, and purchase links — to its 700 million weekly users.
And now customers can complete purchases without leaving the chat.
BIG deal.
But will ChatGPT recommend your products?
That’s not automatic. And you can’t pay for placement.
What you can do is optimize your site so ChatGPT understands what you sell, trusts your brand, and surfaces your products when buyers search. This guide shows you how.
You’ll learn the eight-step framework for getting featured in ChatGPT Shopping.
I also spoke with Leigh McKenzie, Backlinko’s Head of Growth and founder of the ecommerce brand UnderFit, to get his insights on what’s actually working.
First, let’s look at how ChatGPT decides which products make the cut.
How ChatGPT Shopping Works
ChatGPT Shopping kicks in automatically for some shopping intent prompts.
While it doesn’t fire every time, I found it appears more often than not after testing 100+ prompts.
The key? Typing a prompt with clear buying intent.
Like “e-bikes that can handle potholes.”
Instead of just explaining things or offering advice, ChatGPT Shopping recommends specific products.
This includes product images, pricing, and links to online stores and websites where users can make a purchase.
Side note: The ChatGPT Shopping experience isn’t consistent. Even with the same prompt, the carousel may (or may not) show. It can also appear at the top, middle, or bottom of the chat. This variability suggests the feature is still evolving.
If your store gets recommended, countless high-intent shoppers will see your products.
For example, when I tested the e-bike query, ChatGPT gave me a brief explanation of what features to prioritize.
But it also provided a visual product carousel with eight products, each in its own card with key details.
(It looks similar to Google Shopping ads, except you don’t have to pay for them.)
Clicking on any card opens a side panel with:
Additional product photos
A list of stores, prices, and direct links
A short “why you might like this” summary
Sentiment pulled from reviews and forums
From there, users simply click “Visit” to reach the merchant’s product page.
But this experience is changing.
As of September 2025, OpenAI is rolling out Instant Checkout — a feature that lets shoppers buy directly inside ChatGPT.
This is a huge shift.
ChatGPT is no longer just a product discovery tool. It’s a full shopping destination.
Right now, Instant Checkout is only available to Etsy sellers in the United States.
But OpenAI plans to expand this feature to Shopify merchants and other countries soon.
Not on either platform?
They’re also accepting applications for merchants to build their own integrations. (More on this in Step #7.)
How ChatGPT Selects Products to Recommend
A shopper describes what they’re looking for (“running shoes with arch support under $150”), and ChatGPT’s AI goes to work.
It scans the web for the most relevant products based on that request.
And weighs details like product names, descriptions, features, reviews, brand authority, and other signals to find the best matches.
If your product checks the right boxes — and the information on your site is clear and crawlable — it has a chance to be recommended.
ChatGPT may also consider the user’s location and preferences when making recommendations.
Ultimately, all product recommendations must also pass through OpenAI’s safety systems.
This filters out low-quality, misleading, or unsafe products.
So, what does all of this mean for you?
ChatGPT Shopping is evolving fast — and the brands that keep up will win the most visibility.
Here’s how to ensure ChatGPT can understand, trust, and recommend your products.
1. Add Structured Schema Markup to Your Site
ChatGPT needs structured data to understand what you sell.
Schema markup is code that labels key details on your product pages (and website as a whole): name, price, description, availability, reviews, and more.
It turns raw HTML into data AI tools can parse instantly.
Without it, ChatGPT (and other AI systems) have to guess what’s on your page.
With it, they see clean, structured information they can confidently include in product recommendations.
At a minimum, your product schema should include:
Product: Name, description, brand, image, and identifiers (GTIN, SKU, MPN)
Offer: Price, currency, availability, and URL
Review: Individual reviews with reviewer names and ratings
It may look intimidating, but many content management systems — like WordPress, Shopify, and Wix — offer plugins or built-in tools that generate the markup for you automatically.
Once your markup is in place, test that it’s working correctly using Google’s Rich Results Test or Schema.org’s validator.
These tools make it easy to check that your structured data is valid, visible, and error-free.
Pro tip: Go beyond the schema basics. Add AggregateRating for average review scores or FAQPage markup to answer common buyer questions. The more context you provide, the easier it is for AI to surface your product in response to specific prompts.
2. Create and Maintain a High-Quality Product Feed
A product feed is a structured file that packages up your product details and sends them to platforms like Google Merchant Center, Shopify, and Etsy.
It includes details like titles, prices, availability, images, links, and more.
ChatGPT may use data from major platforms like Google to decide which products to recommend.
Pro tip: Want to add your product feed directly to ChatGPT? OpenAI will notify interested merchants when this feature is available. Fill out the Merchant Application form for consideration.
For example, if your Google Shopping feed is outdated, incomplete, or inaccurate, ChatGPT may return bad information about your products.
Or skip recommending them entirely.
That’s why a high-quality, up-to-date product feed is critical.
Side note: If you’re on an ecommerce platform like WooCommerce or Shopify, feeds are usually created automatically.
But keeping feeds accurate is easier said than done.
There are a lot of moving parts, like site updates, refresh schedules, and third-party tools.
And it only takes one slip for mismatches to creep in.
Here are a few common product feed issues — and how to fix them:
Product Feed Problem
Why It Happens
Fix
Price Mismatch
Feed not refreshed, sync delay
Enable daily/real-time feed updates. Use one consistent pricing source.
Inaccurate availability
Inventory updates on site, but feed refresh lags
Sync stock levels in real-time whenever possible. Double-check before campaigns.
Wrong or Truncated Title
Feed title auto-truncated or different from H1/meta
Align feed titles with on-page H1/meta. Keep product names consistent.
Incorrect image
Feed defaults to first gallery image
Set hero/product image as primary in CMS and feed
Missing reviews
Reviews hidden in JS or not in schema
Add Review and AggregateRating schema in HTML
Conflicting schema
Multiple apps/plugins overwrite each other
Use one schema source. Validate with Schema.org or Google’s Rich Results test
Automation keeps most updates in sync. And manual checks before major launches or sales help catch anything that may slip through.
Here’s how Leigh maintains a balance of the two for his ecommerce store:
“I keep all my product data in a spreadsheet. Whenever I change a product detail, I update it there first. WooCommerce uses that data to update my site’s pages and schema automatically. Then, Channable takes the same spreadsheet and syncs those updates into my product feeds. That way, my site and my feeds are always pulling from the same source, so everything stays consistent.”
3. Make Sure AI Bots Can Read Your Site
If ChatGPT can’t read your site, it can’t recommend your products.
Two simple technical issues block many ecommerce sites from showing up: hidden content and restricted crawlers.
Check for JavaScript
Many AI bots — including ChatGPT — still struggle with content that only loads via JavaScript.
If key details aren’t in the page’s raw HTML, the bot might never see them.
This includes your product descriptions, prices, and images.
Eek.
Here’s how to check if that’s happening:
Pull up a product page on your website or online store
In Google Chrome, go to “Settings” > “Privacy and security” > Site Settings
Under “Content,” click “JavaScript” and toggle “Don’t allow sites to use JavaScript”
Reload the product page you’re testing
If your product details disappear, it means they’re only loading through JavaScript.
To fix this, work with a developer to ensure all essential information is in your site’s raw HTML.
They’re onboarding merchants on a rolling basis and will reach out when you’re accepted.
Once you’re in the pipeline, you’ll need to:
Provide a structured product feed that meets OpenAI’s product feed specs. Leigh recommends starting with your existing Google feed and updating it as needed to meet OpenAI’s requirements.
Enable ACP checkout. ACP lets ChatGPT place and complete orders in your system. If you’re on Stripe, setup can be as simple as one line of code. If not, you can still integrate using Stripe’s Shared Payment Token API or the Delegated Payments Spec — no provider switch required.
Connect your payment provider. You’ll still process transactions and remain the merchant of record.
Pass certification requirements. OpenAI requires sandbox testing and end-to-end checks before you go live.
Pro tip: Even if ChatGPT Instant Checkout isn’t available for your store yet, preparing your product data, feeds, and backend now will help you move faster when it is. This should give you a head start as this feature gains popularity.
8. Track Your ChatGPT Visibility
It’s not enough to show up in ChatGPT Shopping.
You also need to measure how well you’re performing.
Start with tracking traffic.
The easiest way is through OpenAI’s built-in UTM tag.
utm_source=chatgpt.com
This is code that OpenAI automatically adds to all outbound links. And looks like this:
Set up a custom segment in Google Analytics to track and analyze ChatGPT traffic to your site.
Once that’s done, look for patterns:
Is ChatGPT traffic increasing month over month — or slowing down?
How does the conversion rate compare to other channels?
Do visitors stick around or bounce right away?
Side note: Not every ChatGPT mention will be traceable. Some users see your product in a chat and search your brand directly on Google instead of clicking. Look for spikes in branded search traffic or direct visits to gauge the broader impact of LLMs.
But traffic only tells you what happens after people click.
You also need to measure what happens before — specifically, which prompts surface your products.
To do this, it helps to understand the kinds of prompts shoppers type.
Most fall into four buckets.
Price-based: “Best dog food bowl under $20,” “luxury ceramic dog bowl”
Use-case: “Dog bowl for messy eaters,” “raised bowls for large breeds”
Feature-based: “Non-slip stainless steel dog bowl,” “slow feeder BPA-free”
Problem-solution: “Dog bowl that keeps ants out,” “dog bowl that doesn’t slide on tile”
Think of these buckets as templates.
Test prompts in each category and ask yourself:
Does your product show up? If so, are the details accurate?
If not, who does — and why? (Are their reviews fresher, their authority stronger, or their copy closer to buyer language?)
Repeatedly run these checks to gather more data.
You’ll learn which prompts lead to product mentions, how your LLM visibility changes, and how buyers talk about your brand.
Rather automate this process?
Tools like Semrush’s AI SEO Toolkit let you:
Track which prompts surface your products
Monitor brand sentiment
Compare visibility in different platforms
Beyond ChatGPT Shopping: Your AI Visibility Playbook
There isn’t a magic formula for getting ChatGPT to recommend your products.
But the brands that consistently get recommended all have three things in common:
A rock-solid technical foundation
Clear, buyer-focused product copy
Strong trust signals across the web
Get these right, and you’re not just optimizing for ChatGPT Shopping.
You’re setting yourself up to be discovered across EVERY AI platform out there.
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Turning paid ads into profit is a proven path to scalable, predictable growth.
When you nail it, paid media gives you a steady stream of customers, without depending on Google’s latest update or social media’s shifting algorithms. In fact, digital ad spend hit $259B in 2024 and is expected to keep growing.
But which channels are right for you? How can you weave them together into an effective strategy? And what’s the best way to measure your performance?
Here’s what you need to know.
Key Takeaways
Paid media is any form of advertising you pay to place on platforms you don’t own, like Google ads, Facebook posts, banner placements, or influencer partnerships.
The big three categories are display ads (banners and videos that stand out), native ads (sponsored posts that blend in), and traditional media (billboards, TV, radio).
Search ads and influencer partnerships are the most trusted paid channels because they catch people with intent or leverage existing relationships.
A winning campaign has seven steps: get your team aligned, set specific goals, budget for real costs (not just ad spend), know your audience, pick the right channels, create compelling ads, and optimize relentlessly.
Track five key metrics: return on ad spend (ROAS), overall return on investment (ROI), cost per click (CPC), impressions, and click-through rate (CTR). These tell you whether you’re making money or just spending it.
Paid Media Basics
Paid media is any kind of promotion that meets two criteria: it happens on a platform you don’t own, and you pay for it.
Banner ads are everywhere, like the ones shown in the Wired article below.
Paid media drives real revenue, whether you’re running a startup or managing a global brand.
In research from my team at NP Digital, we found that paid ads make up a meaningful chunk of revenue across businesses of all sizes.
Paid Media vs. Earned Media vs. Owned Media
Think of marketing like a three-legged stool. The three legs here are paid, earned, and owned media.
Understanding how they work and how they work together can help you build a strategy that covers your blind spots and scales over time.
As mentioned earlier, paid media is any promotional placement you pay for. Think search ads, social ads, banner placements, influencer partnerships, and more.
Earned media is unpaid publicity that your business receives from other people and websites. It’s what others say about your brand mentions in news articles, influencer shoutouts, customer reviews, backlinks, or viral social shares.
Owned media is the stuff you fully control. Your website, blogs, social media accounts, newsletters, and email list, fall into this category. You manage the content, the experience, and the message.
Here’s how they fit together:
Paid media helps you get visibility fast, especially when you’re just starting out or entering new markets
Owned media builds trust, it’s where your brand message lives
Earned media amplifies both. It kicks in when people start talking about what you’re already doing well
The best campaigns use all three. Paid gets attention. Owned keeps it. Earned multiplies it.
Categories and Examples: Paid Media in the Wild
Paid media is evolving fast. Search, social, video, and display are table stakes, but newer formats are gaining traction too, including ads inside large language models (LLMs) like ChatGPT and Gemini.
Even with all this growth, most formats fall into three core categories: display, native, and traditional. There’s often overlap between them, but these labels help keep things simple.
Display ads: These are visually distinct image, video, and text ads that appear alongside content on the web. Website banners, YouTube ads, and interstitial pop-ups are all examples.
Native ads: These are ads that fit within the flow of content and are often indistinguishable from it at first glance. Influencer recommendations, advertorials, and sponsorships are well-known forms of native advertising.
Traditional media: Commercials, billboards, and direct mail are examples of traditional media. You don’t get the same tracking or targeting you’d see with digital, but these channels still play a role in large-scale brand awareness.
Now that we’ve covered the broad categories, let’s break down some of the most common paid media channels, and where each one fits.
While Google Ads dominates the space, Bing Ads (now part of Microsoft Advertising) can offer lower CPCs (cost per click) and a different audience, especially for B2B brands. Amazon Ads also work well for product-heavy businesses.
We foundthat search ads across platforms drive some of the highest conversion rates in paid media, second only to channels like LinkedIn and influencer marketing.
Here’s what the advertising process looks like:
Open an account with the ad network (like Google or Bing)
Choose the keywords you want to appear for, such as “gardener in Arizona”
Set your maximum bid for those keywords (top bidders appear first)
Create your advertisement, which will be text-based
Launch your campaign and let Google serve your ad on relevant SERPs
The benefit of SEM is intent. You’re targeting users who are already searching for what you offer, which puts them closer to a buying decision.
And if you’re willing to bid competitively, your ad can appear above the organic result, even above your competitors.
Here’s an example of search engine ads for the keyword “paid media consultant.” Note the “Sponsored” label, which helps users distinguish paid ads from organic results.
Third-Party Banner Ads
Banner display ads are shown on a third-party online property, usually a website or app.
Most people think banner ads only appear at the top of pages. Not true. Inline banner ads also show in the flow of content. A banner ad is simply a square or rectangular display ad (an ad that is distinct from surrounding content).
NP Digital research shows that banner ads are the least trusted of all paid media formats, underperforming search and influencer ads significantly.
That said, banner ads are good at raising brand awareness. As customers see the same ad repeated across different websites, “brand memory” strengthens. The average person needs to see a brand at least seven times before they make a purchase.
Here’s an example of a fairly conspicuous banner ad on UK news site the Daily Mail:
The Google Display Network, the world’s biggest display network, consists of over two million websites and mobile apps that businesses can display their ads on—reaching 90 percent of web users worldwide. When someone clicks on an ad, Google Ads and whoever hosted it share the spoils.
Paid Social Media Advertising
Social media advertising is big business. The global market was worth an impressive $252.95 billion at the end of 2024, and this is set to grow in the future.
According to NP Digital research, Facebook generated over $100 billion in ad revenue last year, making it the top-performing social ad platform. Instagram followed at $70.9 billion.
Here’s an example of paid media advertising on Facebook. This sponsored post is by McDonald’s and appears in relevant customers’ newsfeeds, enticing them to try their $8 Chicken McNugget Meal. These ads blend into the feed but still offer clear calls to action.
And it’s not just for B2C. In the LinkedIn ad below,Microsoft targets professionals in banking with an ebook download offer.
Social ads work because they meet people where they’re already scrolling. Nearly 60 percent of the world’s population has at least one social media account.
Even better, social platforms give you advanced targeting tools. Most platforms let you target people by age, gender, and location, as well as their hobbies and other social media accounts they follow.
Video Advertising
Video content gets more engagement than static text or images. In fact, one NP Digital study found that short-form and long-form videos accounted for 31.38% and 15.51% of all engagement, respectively.
That kind of engagement makes video a powerful paid media tool, especially on platforms like YouTube, Facebook, TikTok, and Instagram.
Video ads show up before or during content users are already watching.
What makes video ads effective is how they combine storytelling with visual cues. Create a stylish, funny, or cool video, and people will naturally want to discover your brand. Like display ads, videos are great for capturing people’s attention on mobile as well.
In-App Ads
In-app ads are paid placements that show up inside mobile apps while someone is using them. These can be banner ads, video ads, interstitials (full-screen takeovers), or rewarded ads where users watch a video in exchange for in-app perks.
You’ve probably seen these in gaming apps, news apps, or streaming services. They appear between levels, in feed scrolls, or before content loads.
These ads work well if your audience spends a lot of time on mobile, and even better if you’re targeting users by behavior, interest, or location. App data gives you targeting options you won’t always get on the open web.
Performance varies by industry, but in-app ads tend to perform best for consumer apps, entertainment, retail, and local services.
Digital Out of Home (DOOH) Ads
DOOH ads are digital billboards, transit screens, and signage in public spaces. You’ve seen them in malls, airports, gas stations, elevators, and even gym treadmills.
Unlike traditional out-of-home ads, these use screens and software, which means you can update them in real time and target by location, time of day, or audience segment.
They’re a great fit for local campaigns, brand awareness pushes, or national advertisers who want visibility in high-traffic areas. You won’t get click data, but they can be effective for driving searches, visits, and offline conversions.
DOOH is especially useful when paired with mobile or geotargeted campaigns. Seeing a screen ad in a gym, then getting a related offer on your phone, is the kind of multi-touch experience that performs well.
Connected TV (CTV) and Over-the-Top (OTT) Advertising
Connected TV (CTV) and Over-the-Top (OTT) ads show up inside streaming content, on platforms like Hulu, Roku, YouTube TV, and Peacock. These are the ads you see while watching shows or movies on smart TVs, streaming boxes, or even mobile apps.
The big difference? CTV runs on television screens. OTT can run on any device.
These ad formats are great for reaching cord-cutters who’ve moved away from traditional cable. They’re also more trackable than old-school TV ads, with options for targeting by location, device, behavior, and even interests.
CTV and OTT ads are especially useful for brand awareness, product launches, and retargeting. You can run short video ads in high-attention environments—and often get better completion rates than on social.
Large Language Model (LLM) Ads
LLM ads are an emerging format of paid placements that appear in large language model tools like ChatGPT, Google Gemini, and Perplexity. These ad types are still in the early stages, but they’re gaining momentum as AI assistants become part of everyday search behavior.
Right now, some platforms are testing sponsored response blocks or product carousels within AI-generated answers. These typically appear when users ask for recommendations, product ideas, or service comparisons.
For marketers, LLM ads offer a new way to show up during early-stage research, especially in verticals like travel, consumer products, software, and education.
Unlike traditional search ads, these placements are more dependent on content quality and relevance than keyword bidding. That gives brands with helpful, trustworthy content an advantage.
This space is still evolving, but it’s one marketers should keep a close eye on. Testing early gives you a head start as AI search platforms build out their ad offerings.
Sponsorships and Advertorials
Sponsorships, advertorials (paid articles), and influencer marketing are the most prominent examples of paid native advertising.
These ads blend in with regular content.
Here’s an example: an article written by a company executive who’s part of Forbes Council, a paid program that entitles members to publish a set number of articles every year. It looks like editorial content, but it’s paid for, and the author gets guaranteed publishing rights.
Sponsored posts are everywhere, especially on social. The Instagram post below is clearly labeled as a “Paid partnership with Gymshark.” This post feels authentic because it comes from a trusted influencer, not a brand’s ad account.
Along with that, since the influencer has a loyal, engaged following—the post has over 140,000 likes—the ROI will likely be positive for the advertiser.
What makes these work? Trust. When the message comes from someone users already trust, it tends to land better, and perform better.
Benefits of Paid Media as a Marketing Channel
Here are some key benefits of paid media for marketers:
You have more control. As you pay to advertise, you get more say over your ad’s appearance. Conversely, if you submit a press release to a publication, they may edit it to suit their in-house tone of voice.
You get immediate visibility. Search engine optimization (SEO) costs less than paid media, but it can take three to 12 months to see optimal results. With paid media, if you’re happy to pay, you can appear in front of prospective customers immediately.
You can measure results. Paid ads platforms offer detailed analytics so you can see how your ads are doing. Some even provide a quality score so you know which campaigns you need to optimize.
You can tailor your ads. You can target your ads to specific groups of customers and even tailor content toward a location. This increases the chances of people responding positively to your advertisements. Similarly, you can advise who you don’t want your ad to show to.
You can implement automation. You can be as hands-on or hands-off with your advertising as you want. For example, Google Ads offers automated bidding where it automatically optimizes your bids to appeal to people more likely to help you achieve your goals.
Top 5 Paid Media Metrics for Paid Media
You could track dozens of metrics, but these five matter most.
There are lots of metrics you can use to track the success of your paid media campaigns. The risk is that you get lost in a sea of data.
I recommend a simplified approach. One that lets you hone in on channels with potential, drop those that aren’t working, and demonstrate a clear ROI throughout.
Here are my top five metrics for paid media:
These give you a clear picture of performance and help you decide where to optimize or pull back.
Return on ad spend (ROAS): ROAS tells you how much revenue you’re generating for every dollar spent on ads. It’s important to measure this separately because it’s the first thing you need to remedy if you’re not achieving a positive ROI overall. If your ROAS drops, you may need to adjust your targeting, creative, or offers.
Return on investment (ROI): This is the big one. If you’re generating more from your paid media campaigns than it costs to run them, you’re on the right track. Account for everything—creative costs, time managing ad accounts, A/B testing, etc.—and not just the ad platform fees. Paid media without ROI is just spend. Use this number to decide whether to scale or pause.
Cost per click (CPC): This is the average amount you pay whenever someone clicks on your ad. Ideally, this should be as low as possible. It’s a ripe area for optimization. CPC is most useful when viewed alongside CTR and conversion rate. A low CPC doesn’t help if nobody converts.
Impressions: This is the total number of times users see your ads. A high reach shows that you’ve chosen a channel that gives you exposure to a large audience, which is important for brand building. Low impression count? It might be time to evaluate the reach of your chosen channel. Impressions alone won’t drive results but they show whether your ads are getting visibility in the first place.
Click-through rate (CTR): This is the percentage of people who see and click on your ad. A high CTR shows that people find your ad interesting and valuable.
How to Create a High-ROI Paid Media Campaign: 7 Steps
Paid media can generate traffic, leads, and revenue, but only if you approach it with a clear plan. Skipping strategy and jumping into ad spend is one of the fastest ways to burn through your budget.
Because large amounts of money are involved, caution is your ally. Many businesses burn through cash before giving up on paid media, wondering what went wrong.
Your paid media strategy should clearly cover the following:
Which internal stakeholders you need to include
Goals you want to achieve
Characteristics of your audience
Platform-specific budgets
Viable paid media channels
Products and services you want to promote
Metrics for gauging success
The process doesn’t need to be complicated. These seven steps will help you build a campaign that’s focused, efficient, and ready to scale.
1. Obtain Internal Stakeholder Buy-In
Getting buy-in goes beyond simple approval. Your team needs to fully understand what’s happening, why it matters, and what role they play.
Start by identifying who needs to be involved. At a minimum, that usually includes:
Sales (if the campaign impacts lead gen or pipeline)
Don’t wait until after launch to bring these teams in. Paid media works best when everyone is aligned from day one.
Set up a short kickoff meeting to walk through the campaign plan. Cover what you’re promoting, who you’re targeting, what platforms you’re using, and how results will be reported.
It doesn’t have to be a big formal process. A shared doc, quick sync, or even a Slack thread can go a long way.
The goal is to eliminate surprises and make it easy for other teams to support the strategy.
2. Set clear goals and KPIs
You need to know exactly what you’re trying to accomplish. Metrics are important (we’ll come to those later), but goals lay the foundation.
If you don’t know what success looks like, it’s easy to waste money. That’s why clear goals are the first thing to lock in, before budgets, platforms, or creatives.
Start by asking one question: What do you need this campaign to accomplish?
This could include:
Lead generation
Product sales
Free trial signups
App installs
Event registrations
Traffic to a specific landing page
Brand awareness in a new market
Be specific, not general. “More leads” isn’t a goal. “Generate 250 demo requests this quarter at a CPL (cost per lead) under $80” is. Pass your goals through the SMART test: are they Specific, Measurable, Attainable, Relevant, and Timely? The more detailed you make the goals, the easier they will be to achieve.
After that, you can pick KPIs and metrics that match your objective, which we will be talking about in a little bit.
3. Determine budget
With paid media campaigns, it’s essential to set a budget and stick to it. Many paid media platforms let you set a definite upper limit for your ad campaigns. If you exceed this budget, the platform stops showing your ads.
Your budget isn’t just ad spend, but it fuels the entire campaign. Along with the baseline budget for your paid media ads, you must also consider additional costs. These include ad copywriting, graphic design, and videography. If you use an agency, you’ll have to cover ongoing account management fees.
Start by figuring out what success looks like. If your goal is to get 100 leads at $50 each, you’ll need to spend at least $5,000 in ad budget alone. That’s your baseline.
Then add in the supporting costs:
Ad creative (copy, graphics, video, landing pages)
Tracking and analytics setup
A/B testing budget to compare variants
Management costs if you’re outsourcing or using tools
Different platforms also have different minimums and cost expectations. Running paid social on Facebook or Instagram can be more flexible for smaller budgets. Search ads on Google or Bing often require more competitive bidding to see traction.
Don’t spread your budget too thin. It’s better to run fewer campaigns with enough spend to test and optimize properly, instead of trying to be everywhere with limited reach.
And whatever number you start with, keep a reserve. Paid campaigns almost always need tweaking in the first few weeks.
4. Know Your Audience
The more specific you get with your targeting, the less you waste on clicks that go nowhere. If you’re paying for media on a publication or newsletter, you can compare your ideal customer profile (ICP) to the audience specs.
Research all the following points for your ICP:
Industry or niche
Company size or household income
Job titles or demographics
Location
Pain points and goals
What platforms they use most
What influences their buying decisions
Here’s how your audience research translates into paid media results:
Ad platforms: Choose based on where your audience actually spends time
Creative: Match tone, visuals, and messaging to their mindset
Offers: Promote what solves their problem, not what you want to sell
Targeting settings: Use demographics, behaviors, and interests to narrow reach
Retargeting: Build separate campaigns for cold traffic vs. returning visitors
The goal is to reach the right people at the right stage and give them a reason to click.
5. Choose Channels
Not every platform fits every goal. The right channel depends on who you’re targeting, what you’re promoting, and how fast you need results.
Take the following into consideration when choosing where to advertise:
Use search ads (like Google or Bing) if you’re targeting high-intent keywords. People searching are already looking for solutions.
Use social ads (Facebook, Instagram, TikTok, LinkedIn) to create demand or raise awareness. These platforms are great for targeting by interest, behavior, or job title—even if people aren’t actively searching yet.
Use display or retargeting to stay in front of people after they’ve engaged. These can bring users back to your site to finish what they started.
You can also learn a lot by seeing where your competitors are advertising. Tools like Meta Ad Library, Google Ads Transparency Center, and manual Google searches will show you what channels they’re using and how often they show up. Look at their messaging, creative, and landing pages. If it’s working for them, it might work for you.
Budget matters, too. Some platforms are better suited to lower ad spend. Facebook, Instagram, and TikTok can give you meaningful reach on a modest budget. Search or YouTube may require more competitive bidding to see real traction.
For smaller budgets, focus on one or two channels where your audience is most active. Don’t try to be everywhere if you can’t afford to run meaningful tests.
And don’t lock yourself into one format. The best campaigns evolve. Start with the highest-potential channel, then expand once you’re confident in performance.
Don’t be afraid of being “loud”—you want an ad that customers stop and look at.
Keep your ad copy clear and concise.
User-generated content and testimonials show prospects why existing customers love your brand.
If you’re using search advertising like Google Ads, take advantage of assets that tell customers more about your business for no additional cost.
Run multiple variants of your ads from the get-go for some quick A/B test wins.
But good creative is more than just how your ad looks, it also covers what you say and how fast you get to the point. Lead with the benefit, keep the message tight, and match your CTA to the user’s intent.
Make sure your offer matches the awareness stage also. A discount works well for bottom-of-funnel buyers. But for top-of-funnel, try a quiz, guide, or video to build interest first.
Finally, try to avoid launching with just one ad. Rotate in multiple headlines, formats, and visuals early so you can learn what actually converts before you scale spend.
In addition, some paid media platforms have ad libraries where you can see examples of paid media ads from your competitors. Meta (Facebook and Instagram), TikTok, LinkedIn, and Google Ads all have libraries. They’re fantastic sources of inspiration.
7. Optimize Your Campaigns
Like all digital marketing campaigns, paid media is not something you can set and forget. When it comes to optimization, little and often wins the race.
I recommend checking your paid media accounts at least once a week, even once a day if you’re running a short-term campaign.
Paid media is excellent for running multivariate and A/B testing. You can create multiple ad versions with small differences—such as CTA texts or color schemes—and test them against statistically significant sample sizes.
But don’t stop at testing creative. Optimization includes your audiences, bidding strategy, landing pages, placements, and even campaign structure.
Here’s what to review regularly:
Which ads are getting clicks but not conversions? Pause or adjust those.
Which campaigns are spending without results? Reallocate that budget.
Are certain audiences or geos outperforming others? Double down where it counts.
Is your cost per result trending up or down? That’s your early warning system.
Document what you’re testing and why. Optimization doesn’t mean quickly reacting without thinking. Your team needs to learn over time and building a smarter strategy with every round.
Paid Media and AI: Trends You Need to Know
AI is already shaping how campaigns are built, optimized, and scaled. My team and I ran research looking at AI vs. human-generated ads, for example, and found that AI ads converted at 1.28%, less than half a percentage point below human ads, which converted at 1.54%. Yes, human ads performed better. But not by a huge margin.
I would urge digital marketers to keep the following four points in mind when it comes There are already a growing amount of applications for AI in the world of paid media:
Marketers are using AI to:
Write ad copy faster (especially for high-volume campaigns)
Build and test ad creative using AI image and video tools
Generate audiences automatically based on existing customer data
Optimize budgets in real time across channels
Predict what offers or creatives will perform best, before spending anything
These aren’t experimental use cases anymore. They’re being built directly into the tools marketers already use.But things are changing fast. Here’s some key points to keep in mind:
Paid media isn’t going anywhere: Most paid media channels will remain viable. People will continue to read their favorite publications, open newsletters, follow influencers on social media, listen to podcasts, and so on. Even if traditional SEO and search ads vanish, LLMs like ChatGPT will need to monetize at some point.
Revenue from ads provides stability: As AI changes the way people consume content online, revenue from ads can actually provide more stability. Unlike organic traffic, they’re not dependent on algorithms over which you have no control.
Paid media helps you build brand citations: Branding will be more important than ever in the age of AI. Citations around the web are one of the ways LLMs identify and measure the relevance of your business to a particular query. For example, if “NP Digital” appears often in AI training materials next to “advertising agency,” my brand is more likely to be referenced in response to related questions.
Now is the time to start experimenting with AI: As was shown in the research by me and my team, AI can perform nearly as well as humans. For a head start when AI is truly ready to assist with paid media campaigns, you should start experimenting and learning now.
That said, AI is a tool, not a strategy. You still need strong positioning, good creative, and clear goals. But if you’re not testing AI workflows now, you’re going to fall behind the brands that are.
Should You Focus on One or All Channels?
Most marketers think they need to be everywhere. That’s usually wrong.
To be clear, I’m a big proponent of omnichannel digital marketing.
When you’re everywhere, you reach more of your prospects. Yet you would be amazed at how many businesses fail to grasp this simple fact.
With that said, for paid, omnichannel may sound great, but isn’t always the right move.
With large amounts of money at risk, you need to do two things: research and test.
If you’re just getting started with paid media, stick to one or two platforms where your audience is most active. That gives you enough budget and data to learn what works without spreading yourself too thin.
Once you’ve found a winning message and offer, then it makes sense to expand. You can start repurposing creative, retargeting across platforms, and building a true full-funnel system.
Here’s the truth: omnichannel paid marketing only works when you have the team, budget, and systems to support it. Otherwise, it turns into a mess of disconnected campaigns.
Ask yourself:
Do you have the creative capacity to build for multiple formats?
Do you have enough budget to collect meaningful data across platforms?
Can you track performance in a way that ties everything together?
If the answer is yes, go for it. If not, focus and scale intentionally. The best paid media campaigns start small, then scale up.
FAQs
What is paid media?
Paid media refers to any marketing or advertising content a brand pays to place on a third-party platform. Common examples include search engine ads, social media ads, display banners, video ads, influencer sponsorships, and traditional placements like radio, print, or TV.
The key benefit of paid media is the ability to generate visibility and traffic quickly, often with precise targeting and measurable results. Brands typically use paid media to reach new audiences, promote offers, or support other marketing efforts. It works best when paired with earned and owned media in a broader strategy.
How often should you evaluate your paid media budget?
Most brands should evaluate their paid media budget weekly. This allows time to monitor spend, performance, and early signals on what’s working.
For short-term or high-investment campaigns, daily budget checks are recommended to catch issues before they impact results.
Monthly or quarterly reviews are useful for larger budget adjustments, channel planning, or reallocation based on return.
Consistent monitoring ensures your budget is supporting your goals and allows for real-time optimizations, rather than reactive fixes after performance dips.
How do you build a paid media strategy?
A strong paid media strategy starts with setting a clear objective, such as lead generation, product sales, or brand awareness.
From there, define your target audience and select platforms that align with where they spend time. Creative should match the platform and campaign goal, while KPIs like ROAS, CPC, or conversion rate help track progress.
Budget should be allocated based on priorities and expected return, with room for testing.
Successful strategies are built on iteration—launching, analyzing, and optimizing based on what the data shows.
What’s the difference between earned media and paid media?
Paid media includes advertising you pay for, such as social ads, search ads, sponsored content, and display banners. It gives you control over placement, timing, and messaging.
Earned media refers to organic exposure you don’t pay for—such as press coverage, backlinks, user reviews, or social shares.
While paid media drives immediate visibility, earned media builds trust and long-term authority. Most marketing strategies benefit from a mix of both, with paid media often used to accelerate early reach.
Conclusion
Most marketers treat paid media like throwing money at a wall and hoping something sticks. That’s expensive and frustrating.
The brands winning with paid media treat it like a system. They start with one platform, nail their message and targeting, then scale what works. They track the right metrics, test relentlessly, and aren’t afraid to kill campaigns that aren’t delivering.
If you’re just getting started, pick Google Ads or Facebook—whichever platform your audience uses most. Set a budget you can afford to lose while you learn. Create multiple ad variants from day one so you can see what resonates.
We’re excited to announce the beta release of Yoast AI Brand Insights, available as part of the Yoast SEO AI+ package. This new tool helps you understand how your brand appears in AI-powered answers, and where you can improve your visibility. Ideal for bloggers, marketers, and brand managers, Yoast AI Brand Insights gives you an overview of your brand presence across tools like ChatGPT, Perplexity, and Gemini.
For years, Yoast has helped you get found in search engines. Recently though, search is changing. People aren’t just using Google anymore, they’re turning to AI tools like ChatGPT for answers. Those answers often mention brand names as recommendations. So here’s the big question: when AI tools answer questions in your niche, does your brand show up? Our new tool, Yoast AI Brand Insights (beta), helps you find out.
Yoast AI Brand Insights lets you see when and how your brand appears in AI-generated answers and helps you understand where you need to focus your effort to improve your visibility.
Why Yoast AI Brand Insights matters, now
AI-powered answers are shaping customer decisions faster than ever. Visitors from AI search are often more likely to convert than those from regular search. It’s no surprise, because asking an AI-powered chatbot can feel like getting a personal recommendation. Afterall, word of mouth remains one of the most powerful ways to build trust and spark interest.
Most analytics tools can’t tell you how your brand appears in AI answers, or if it’s mentioned at all. With more people turning to tools like ChatGPT, Perplexity, and Gemini for advice, that’s a big blind spot if you are trying to get your name out there.
Yoast AI Brand Insights aims to close that gap. You’ll see when and how your brand appears, what’s being said, and where the information comes from, so you can take action to ensure your brand is part of the conversation.
See how you stack up against other brands mentioned in your prompts
With just a few clicks, you can:
Check if your brand is mentioned in AI-generated answers for relevant search queries
Benchmark against competitors: see how often your brand comes up
Understand the sentiment connected to your brand: positive, neutral, or negative
Find the sources AI tools use when they mention you
Track your progress over time so you can respond to changes quickly
Pricing & getting started
Yoast SEO AI+ is priced at $29.90/month, billed annually ($358.80 plus VAT). The plan includes one automated brand analysis per week per brand, so you can track and compare how your brand is showing up in AI-powered search over time. With each purchase of Yoast SEO AI+ you recieve one extra brand.
With this package you also get the full value of Yoast WooCommerce SEO, which includes everything from Yoast SEO Premium, News SEO, Local SEO, and Video SEO, in addition to one free seat of the Yoast SEO Google Docs add-on.
For marketers, this means you no longer need to patch together separate solutions for on-page SEO, ecommerce optimization, content creation, or LLM visibility. Everything you need to analyze, optimize, and grow your brand presence is included in one complete package.
How to get started
Login with MyYoast: secure, single sign-on for all your Yoast tools and products.
Open Yoast AI Brand Insights: You can find it near the Yoast SEO Academy
Set up your brand: add your brand’s name and a short introduction to your business
Run your scan: we’ll find relevant AI search queries for you, you can use them or tweak them to your liking.
Review your results: see relevant mentions and their sources, your brand sentiment, and the AI Visibility Index in an easy-to-read dashboard
Yoast AI Brand Insights is now available in beta as part of Yoast SEO AI+. This is your chance to be among the first to explore how your brand shows up in AI-powered search. We’d love your thoughts as we refine the tool, your thoughts here.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-01 10:07:322025-10-01 10:07:32Introducing a new AI-powered package: Track your brand in AI search
Content summarization isn’t a new idea. It goes back to the 1950s when Hans Peter Luhn at IBM introduced one of the first algorithms to summarize text. Back then, the goal was straightforward: identify the most important words in a piece of writing and create a shorter version. What began as a technical experiment has now evolved into a fundamental aspect of how we read, learn, and share information. Summarization allows us to cut through overwhelming amounts of text and focus on what really matters, shaping everything from research and education to marketing and SEO.
In this article, we’ll explore why summarizing is essential for modern content and how both humans and AI-driven tools are making information more accessible, trustworthy, and impactful.
What is content summarization?
Content summarization is the process of condensing a large piece of high-quality content into a shorter version while keeping the essential points intact. The aim is straightforward: to produce a clear and concise summary that accurately represents the meaning of the original text without overwhelming the reader.
Summarization makes information easier to process. Imagine reading a lengthy report or book but only needing the key takeaways for a meeting. It also helps individuals and businesses grasp the core message quickly, saving time and effort.
There are two main approaches to summarize moder content:
Manual or human-driven content summarization
Think back to the last time you turned a long article into a short brief for a colleague; that’s a perfect example and explanation of manual content summarization. In this approach, a human reads, weighs what matters, and rewrites the core points for easy digestion of information.
Manual content summarization requires critical thinking to spot what matters and language skills to explain important information clearly and concisely.
Clear advantages of human-driven content summarization are:
The ability to notice nuance and implied meaning
Flexibility to shape tone and level of detail for a specific audience
The creativity to link ideas or highlight unexpected relevance
Judgment to keep or discard details based on purpose
This human-led method complements content summarization AI, giving summaries a thoughtful, audience-aware edge.
AI-driven content summarization
The other approach is powered by technology. AI-driven content summarization utilizes natural language processing and machine learning to rapidly scan through text and generate summaries in seconds. It typically works in two ways:
Extractive summarization, where the AI selects the most important sentences directly from the content
Abstractive summarization, where the AI generates new sentences that capture the main ideas in a more natural way
The benefits are clear: speed, consistency, and scalability. AI can summarize website content, reports, or articles far faster than a human team. However, it has limits. Context can be missed, and nuances like sarcasm or cultural references may be overlooked. The quality also depends on the AI model and the original text.
Both manual and AI-driven summarization play a crucial role today. Humans bring nuance and creativity, while AI delivers efficiency and scale. Together, they make summarization an essential tool for modern communication.
What are some of the core benefits of content summarization?
Turning lengthy information into clear takeaways is more than convenient. It makes content meaningful, easier to use, and far more effective in learning and communication. Whether done manually or supported by AI tools, summarization offers key benefits:
Enhances learning and study preparation
Summarizing strengthens comprehension and critical thinking by distilling main ideas and separating them from supporting details. Students and professionals can also rely on concise notes that save time when revising or preparing presentations.
Improves focus and communication
Condensing text sharpens concentration on what matters most. It also trains you to express ideas in a precise and structured way, which enhances both writing and verbal skills.
Saves time and scales with AI tools
Summaries allow readers to absorb essential points without having to read hours of content. With AI tools, this process scales further, reducing large volumes of text into clear insights within minutes.
Boosts accessibility and approachability
Summarization makes complex or lengthy content approachable and accessible for diverse audiences. Multilingual AI tools extend this further, breaking down language barriers and ensuring knowledge reaches a global audience.
Why summarization matters in the modern content landscape?
We live in an age of too much information and too little time. Every day, there is more content than anyone can read, which means people make split-second choices about what to open, skim, or ignore. This makes it more important that your content presents clear takeaways upfront before readers move on. Content summarization is how you win that first, critical moment of attention.
Information overload
Digital work and life produce an enormous flood of text, messages, reports, and notifications. This makes it challenging for readers to find the right signal in the noise. Therefore, text summaries act as a filter, surfacing the most relevant facts so readers and teams can act faster and with less cognitive friction.
People scan and skim, so clarity wins
Web reading behavior has been stable for years: most users scan pages rather than read every word. Good summaries present the core idea in a scannable form, increasing the chance your content is understood and used. That scannability also improves the odds of search engines and AI LLM comprehension surfacing your content as a quick response to user queries.
Trust and clarity for readers and systems
A clear and crisp text summary signals that the author understands their topic and values the reader’s time. That builds trust. On the search side, concise and well-structured summaries are what engines and AI systems prefer when generating featured snippets or AI overviews. Being chosen for a snippet or overview can boost visibility and credibility in search results.
Faster decision-making
When stakeholders, readers, or customers need to act quickly, summaries provide the necessary context to make informed decisions. Whether it is an executive skimming a report or a user checking if an article answers their question, summaries reduce the time to relevance and accelerate outcomes. This is also why structured summaries can increase the chance of being surfaced by search features that prioritize immediate answers.
Prominent use cases of content summarization
Content summarization is not a nice-to-have. It is one of the main reasons modern content continues to work for busy humans and businesses. Below are the most practical and high-impact ways in which the summarization of modern content is currently being used.
Business reports
Executives and teams rely on concise summaries to make informed decisions quickly and effectively. Executive summaries and one-page briefs transform dense reports into actionable insights, enabling stakeholders to determine what requires attention and what can be deferred. Effective summaries reduce meeting time, expedite approvals, and enhance alignment across teams.
Educational content
Students and educators use summaries to focus on core concepts and to prepare study notes. AI-driven summarization tools can generate revision guides, extract exam-relevant points, and turn long lectures or papers into study-friendly formats. These tools can support personalized learning and speed up content creation for instructors.
Marketing strategies and reporting
Marketers rely on summaries to present campaign performance, highlight key KPIs, and share learnings without overwhelming stakeholders. Condensed campaign briefs and executive summaries enable teams to iterate faster, align on priorities, and uncover insights for strategic changes. Summaries also make it easier to compare campaigns and track trends over time.
Readers and listeners increasingly prefer bite-sized overviews. Newsrooms use short summaries and AI-powered digests to connect busy audiences with high-quality reporting. Podcasts and newsletters pair episode or article summaries with timestamps and highlights to improve discoverability and retention. Summaries help users decide what to read, listen to, or save for later.
Content Summarization & SEO: Does it Benefit in Boosting Organic Visibility?
Did you know that content summarization can help your SEO strategy? Search engines prioritize clarity, relevance, and user engagement, and concise summaries play a role in meeting those criteria. They not only shape a smoother user experience but also help search engines quickly grasp the core themes of your content.
Boosting click-through rates
Summaries also support higher CTRs in search results. A clear and compelling meta description written as a summary can serve as a strong preview of the page. For example, a blog on “10 Healthy Recipes” with a summary that highlights “quick breakfasts, vegetarian lunches, and easy weeknight dinners” is more likely to attract clicks than a generic description.
Improving indexing and relevance
From a technical standpoint, summarization helps search engines with indexing and relevance. Algorithms rely on context and keywords, and well-written summaries bring focus to the essence of your content. This is especially important for long-form blogs, case studies, or reports where the main ideas may otherwise get buried.
Winning featured snippets
Another growing benefit is visibility in featured snippets and People Also Ask sections. Summaries that clearly answer a query or highlight structured takeaways increase the chances of being pulled into these high-visibility SERP features, directly boosting organic reach.
Extending multi-channel visibility
Content summarization also creates multi-channel opportunities. The same summaries can be repurposed as social media captions, newsletter highlights, or even adapted for voice search, where users want concise and direct answers.
Supporting AI and LLMs
Lastly, in the age of AI, summaries provide context for LLMs (large language models). Clean, structured summaries make it easier for AI to process and reference your content, which extends your reach beyond search engines into how content is surfaced across AI-powered tools.
How to write SEO-friendly content summaries with Yoast?
The basics of an effective summary are simple: keep it clear, concise, and focused on the main points while signalling relevance to both readers and search engines.
This is exactly where Yoast can make your life easier. With AI Summarize, you can generate instant, editable bullet-point takeaways that boost scannability for readers and improve how search engines interpret your content.
Want to take it further? Yoast SEO Premium unlocks extended AI features, smarter keyword optimization, and advanced SEO tools that save you time while improving your visibility in search.
A smarter analysis in Yoast SEO Premium
Yoast SEO Premium has a smart content analysis that helps you take your content to the next level!
AI text summarization uses artificial intelligence to condense text, audio, or video content into shorter, more digestible content. Rather than just cutting words, it preserves key ideas and context, making information easier to absorb.
Today, summarization relies on large language models (LLMs), which not only extract sentences but also interpret nuance and generate concise, natural-sounding summaries.
How does AI text summarization work?
AI text summarization relies on a combination of sophisticated systems that help a large-language model deeply understand the content, decipher patterns, and generate content summaries without losing any important facts.
Here’s a brief overview of the process of AI-powered content summarization:
Understanding context: AI models analyze entire documents, identifying relationships, sentiment, and flow rather than just looking at keywords, allowing the AI models to understand at a deeper level
Generating abstractive summaries: Unlike extractive methods, which simply copy existing sentences, abstractive summarization paraphrases or rephrases content to convey the essence in fresh, coherent language
Fine-tuning for accuracy: LLMs can be trained on specific domains such as news, legal, or scientific content, so the summaries reflect the right tone, terminology, and level of detail
Benefits of AI text summarization
The true power of AI summarization lies in the value it creates. By blending scale with accuracy, it turns information overload into actionable knowledge.
Scales content summarization: Handles hundreds of pages or documents in minutes, which would otherwise require hours of manual effort
Ensures consistency: Produces summaries in a uniform style and structure, making information easier to compare and use
Saves time and costs: Frees up teams, researchers, and analysts to focus on insights instead of spending time reading
Improves accessibility: Makes complex content digestible for wider audiences, including those unfamiliar with technical details
Supports accuracy with human oversight: Editors can refine summaries quickly while still benefiting from automation
Practical use cases of AI summarization
AI summarization is not just theoretical. It has already become part of how businesses, teams, and individuals manage daily information flow. Here are some of the common applications of AI summarization which have become a part of our live:
Meetings: Automatically captures key points, decisions, and action items in real time
Onboarding: Condenses company or project documentation so new team members can understand essentials quickly
Daily recaps: Summarizes Slack, Teams, or email threads into clear, concise updates
Surfacing information: Extracts relevant context from long reports, technical documents, or customer feedback, ensuring that critical insights are never overlooked
In fact, AI agents are already being used in professional settings to summarize key provisions in documents, with 38% of professionals relying on these tools to expedite the review process. This demonstrates that AI summarization is not just a future possibility, but an integral part of how modern teams manage complex information.
In summary, don’t skip the summary!
Summarization is no longer a sidekick in your content strategy; it is the main character. It fuels faster human learning, strengthens SEO by making your pages clearer to search engines, and ensures AI systems don’t misrepresent your brand. When your content is easy to scan, you reduce bounce rates, improve trust, and increase visibility across platforms where attention spans are short.
This is exactly where a tool like Yoast SEO Premium becomes invaluable. With features like AI Summarize, you can instantly generate key takeaways that work for readers, search engines, and AI overviews alike. Instead of manually condensing every piece of content, you achieve clarity at scale while maintaining editorial control. Summarization is not just about making content shorter; it is about making it smarter, and Yoast helps you do it with ease.
So, to summarize the summary: invest in doing this right, because the future of content depends on it.
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