Sergey Brin, Google’s co-founder, admitted that Google “for sure messed up” by underinvesting in AI and failing to seriously pursue the opportunity after releasing the research that led to today’s generative AI era.
Google was scared. Google didn’t take it seriously enough and failed to scale fast enough after the Transformer paper, Brin said. Also:
Google was “too scared to bring it to people” because chatbots can “say dumb things.”
“OpenAI ran with it,” which was “a super smart insight.”
The full quote. Brin said:
“I guess I would say in some ways we for sure messed up in that we underinvested and sort of didn’t take it as seriously as we should have, say eight years ago when we published the transformer paper. We actually didn’t take it all that seriously and didn’t necessarily invest in scaling the compute. And also we were too scared to bring it to people because chatbots say dumb things. And you know, OpenAI ran with it, which good for them. It was a super smart insight and it was also our people like Ilya [Sutskever] who went there to do that. But I do think we still have benefited from that long history.”
Yes, but. Google still benefits from years of AI research and control over much of the technology that powers it, Brin said. That includes deep learning algorithms, years of neural network research and development, data-center capacity, and semiconductors.
Why we care. Brin’s comments help explain why Google’s AI-driven search changes have felt abrupt and inconsistent. After years of hesitation about shipping imperfect AI, Google is now moving fast (perhaps too fast?). The volatility we see in Google Search is collateral damage from that catch-up mode.
Where is AI going? Brin framed today’s AI race as hyper-competitive and fast-moving: “If you skip AI news for a month, you’re way behind.” When asked where AI is going, he said:
“I think we just don’t know. Is there a ceiling to intelligence? I guess in addition to the question that you raised, can it do anything a person can do? There’s the question, what things can it do that a person cannot do? That’s sort of a super intelligence question. And I think that’s just not known, how smart can a thing be?”
One more thing. Brin said he often uses Gemini Live in the car for back-and-forth conversations. The public version runs on an “ancient model,” Brin said, adding that a “way better version” is coming in a few weeks.
The video. Brin’s remarks came at a Stanford event marking the School of Engineering’s 100th anniversary. He discussed Google’s origins, its innovation culture, and the current AI landscape. Here’s the full video.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/12/0nlnx94fcue-CrSf2v.jpg?fit=1280%2C720&ssl=17201280http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-15 17:15:162025-12-15 17:15:16Sergey Brin: Google ‘messed up’ by underinvesting in AI
Reddit is an online forum that’s part search engine, part social network.
Millions of people use it to swap advice, review products, and argue about virtually every topic under the sun. It all happens inside niche communities called subreddits.
All this makes it a powerful place for Reddit marketing. As long as you know how to play by its rules, that is.
The No. 1 rule? You can’t treat Reddit like another broadcast channel. Users hate obvious self-promotion and call out spam instantly. They reward brands that show up to add value, so just popping in and dropping links won’t cut it.
The upside? If you’re useful and authentic, the reward is real trust and traffic you won’t get anywhere else.
In this guide, we’ll walk you through how to market on Reddit the right way, including both organic and paid strategies. We’ll also toss in some tips on etiquette to keep you from getting buried (or banned).
Key Takeaways
Reddit is a network of niche communities. Winning here means respecting each sub’s rules and culture.
Organic comes first. Use a Crawl-Walk-Run approach in your Reddit marketing strategy: Listen and comment, then start useful threads, then scale into branded subs, SEO plays, and selective paid campaigns.
Self-promotion is allowed but heavily policed. Contribute more than you pitch and follow Reddiquette and subreddit rules to avoid bans and backlash.
Reddit ads run on an auction model and work best when they feel native to the feed.
Reddit threads influence Google results, “Discussions and forums” boxes, and even AI answers.
Why Is Reddit Important as a Marketing Platform?
Reddit is massive and growing fast. Recent estimates put it at around 100 million daily active users and hundreds of millions of monthly users, spread across more than 100,000 active subreddits.
It’s basically a giant ecosystem of niche communities where people compare products, troubleshoot problems, and share unfiltered opinions.
What makes Reddit especially relevant today is how often its content shows up outside Reddit. Google’s “Discussions and forums” search feature appears on millions of queries and is heavily dominated by Reddit threads, especially for product reviews and how-to topics.
Check out the “Discussions and forums” results for “best VPN for travel.” Reddit grabs the top spot above Facebook groups, which tells you two things: Google trusts Reddit threads for experience-based queries, and real travelers would rather hear from other travelers than from brand pages.
When someone searches “running shoes for bad knees,” for example, a Reddit discussion appears on page one.
“Google, specifically, is prioritizing the platform because it highlights true first-hand experiences,” says Becky McManus, senior SEO strategist at NP Digital.
Reddit’s also a growing force in AI search. It has data-licensing deals with Google and OpenAI, which use Reddit posts to train and power their large language models. In some analyses, Reddit is one of the most commonly cited domains in AI-generated answers.
So, when you show up on Reddit, you’re not just reaching users on one platform. You’re influencing search results, AI-generated summaries, and the conversations that shape buyer decisions.
Fundamentals to Know About Reddit
Maybe the most fundamental thing to know about Reddit is that it isn’t one big audience. It’s a web of niche communities (subreddits). Each has its own rules and culture. And not all of them have a high tolerance for brands.
“Reddit is a different kind of digital marketing space,” McManus says. “It’s all about being real and adding value to the conversation, not just pushing promotions, which you can do more of on standard social media platforms.”
That’s what makes Reddit marketing powerful. It’s also what makes it easy to screw up.
Start with the basics by reading Reddit’s page about self-promotion and what’s allowed and what isn’t. Once you’ve read that, look at the “Reddiquette” page so you can see Reddit’s main rules.
The list includes:
Contributing more than you promote and avoiding spammy, link-only posts
Being transparent about who you are and any affiliations you have
Speaking to other users respectfully, even when you disagree
Following each subreddit’s specific rules instead of assuming they’re all the same
Next, zoom in on each subreddit.
Read the sidebar and pinned posts. Some communities allow links only on certain days. Others ban surveys, coupon codes, or branded content of any kind. Moderators (mods) enforce those rules, and they won’t hesitate to remove posts or ban accounts.
Take a look at how the r/digitalmarketing subreddit clearly spells out its rules.
Your job is to show up as a helpful user first and a marketer second. Answer questions, share experiences, post useful resources, and only occasionally mention your product when it genuinely fits the thread.
If you’re unsure whether something crosses the line, message the mods and ask.
Organic Reddit Strategies
Organic participation is the name of the game withReddit marketing.
Ads can help, but many brands win by showing up as real users first. That means answering questions and sharing useful resources, which helps build karma over time.
Done right, this also feeds into your Reddit SEO strategy before you ever touch paid campaigns.
Use a Business Account
If you’re going to do anything promotional on Reddit, start with a branded account. Redditors care a lot about transparency, and a handle that clearly represents your company or team builds more trust than a random personal username that secretly belongs to “Marketing.”
Create an account that signals who you are (for example, BrandName_Official or FirstNameAtBrand). Add a short bio that explains your role and what people can expect from you, such as support or product questions.
Here’s an example profile from Cleveland.com, whose parent company, Advance Local, has had success with organic Reddit marketing strategies.
From there, resist the urge to start dropping links. Instead, comment, answer questions, and join existing threads. That way, your profile doesn’t look like it was created only to push content. If teammates also use personal accounts, have them be open about their affiliation when it’s relevant.
An honest business presence boosts the credibility of every future promo. It also looks less like spam.
Provide Value to Communities
Reddit rewards accounts that make threads better. If your first instinct is “Where can I post my link?”, you’re already in trouble.
Focus on being useful long before you mention your brand.
Look for questions you can answer in detail. Share things like:
How-tos
Real examples
What actually worked for you, even when the answer doesn’t involve your product.
Summarize complex topics in plain language.
Drop frameworks, checklists, or quick diagnostics people can try on their own.
You can also add value by recapping good resources, explaining trade-offs between options, or sharing honest pros and cons from your experience. Link sparingly and only when it clearly adds context.
Over time, that kind of participation builds karma, name recognition, and trust. Then, when you occasionally share something from your own site, it feels like a contribution, not an intrusion.
Ask Me Anything (AMA)
AMAs can be useful, even if you’re not a household name. The key is to find a clear, interesting angle that fits the subreddit.
Instead of “I’m a founder; ask me anything,” pitch something specific to the mods first:
“I run growth for a bootstrapped SaaS that just hit $1M ARR. Ask me anything about what actually moved the needle.”
“I’ve moderated a 200K-member fitness community for five years. Ask me anything about what keeps people engaged.”
For example, this AMA works because it leads with a high-stakes, personal hook: someone risking their life savings on a mobile game. People want to hear the story and ask what happened next.
Most subreddits require proof and mod approval, so follow their instructions closely. During the AMA, focus on being candid and helpful. Share stories, mistakes, and lessons. Avoid turning every answer into a soft pitch.
If people like you, they’ll click through to your profile and brand on their own. The AMA’s job is to build credibility, not to read like a live ad.
Start a Subreddit
Starting your own subreddit is more of a “phase two or three” move than a starting point. If you don’t already have people talking about you on Reddit, a brand-new sub will sit empty and make you look inactive.
Once there’s clear interest—mentions in other subs, recurring questions, or an existing community elsewhere—you can launch a subreddit as a hub. Think of it as a place for support, feature requests, user wins, and deeper discussions around your niche, not just announcements.
Set clear rules, pin a simple “Start here” post, and seed the sub with genuinely useful threads: FAQs, guides, templates, product walkthroughs, or office-hours posts. Commit to moderating and replying.
When you promote the subreddit, invite people in for the value (“Come ask questions and see real use cases”), not just to “follow” your brand.
Reddit Paid Advertising
Organic participation is the foundation of your Reddit marketing efforts, but paid ads are how you scale once you know what resonates.
Reddit now reaches a massive, mostly younger audience across thousands of active communities, and a lot of those users are actively researching products (not just scrolling).
The big advantage for marketers is context.
You can target by subreddit, interest, keyword, location, and device, so your ads show up inside conversations that already match your offer. Formats range from promoted posts and video ads to conversation placements and takeovers, with newer options like dynamic product ads for e-commerce.
If your creative matches the culture of the communities you’re in, Reddit ads can drive serious awareness and consideration.
Reddit Advertising Policies
Reddit’s ad policies are strict because ads sit right next to user posts. If your campaigns feel spammy or misleading, you’d better believe they’ll get rejected fast. Even when they’re approved, users will downvote them into oblivion.
Creative and Video Quality
Ads should look and sound professional. Make sure your audio and visuals are clear and text is readable.
Also be sure your video is relevant to the audience you’re targeting and correctly labeled if it includes mature themes. Anything graphic or heavily profane needs the proper rating and warnings, and strobing or flashing effects are off limits.
Style and Copy Standards
Reddit expects clean, honest copy. So, check your spelling and grammar, keep emojis and symbols to a minimum, avoid shouty all-caps, and don’t stuff personal data into your ad unless regulations require it. And be sure that your images are high quality and match what you’re promoting.
Accuracy and Transparency
Your ad has to reflect the real product or service. That means no clickbait headlines or no bait-and-switch offers. And don’t promote specific Reddit comments or posts unless you’re using approved formats.
URLs and Landing Pages
Your landing page should clearly feature the product you advertised. You’ll also want it to load reliably and stick to Reddit’s content rules. Keep the language consistent with your ad and avoid aggressive pop-ups or spammy tactics.
When in doubt, review Reddit’s full advertising policy before you launch. It’s easier to fix issues in draft than after a denial.
What Are the Different Types of Reddit Ads?
Reddit’s ad formats are designed to feel like part of the feed, not banner clutter. Here’s how the main options break down in Reddit’s own language:
Free-form ads: Reddit-native units that can mix text, images, video, and GIFs in one post. Great for storytelling or more complex messages.
Image ads: Single-image promoted posts that look like standard Reddit posts with a “Promoted” label. Solid for simple offers and clear CTAs.
Video ads: Autoplay video in the feed, built to grab attention and work across awareness, consideration, and conversion.
Carousel ads: Swipeable units that showcase multiple images or videos in one ad—perfect for product lines, before/after stories, or feature highlights.
Conversation ads: Let you join or spark discussions directly in conversation spaces, so your brand shows up where people are already talking.
Product ads: Shopping-focused units that pull from your product catalog and recommend items to redditors who are ready to buy.
AMA ads: Sponsored “ask me anything” experiences that put a subject-matter expert or brand rep at the center of a Q&A thread.
Most of these are available in the self-serve ads manager, so you can test formats quickly and double down on what your audience actually engages with.
Examples of Great Reddit Ads
Before diving and creating your own Reddit ad, let’s look at a few examples.
ChatGPT
This ad works because it feels like a Reddit post, not a banner. The headline clearly promises the benefit (“transform your words into works of art”), and the creative shows the product in action—a funny, hyper-specific dog portrait that fits Reddit’s meme-y culture.
The user interface screenshot makes it obvious how ChatGPT is used, so there’s no learning curve. The copy is light, the visual does the selling, and the single “Sign Up” call to action (CTA) keeps the next step simple.
All in all, it’s fun, clear, and native to the feed.
The Coupon Nerd
This ad works because it leans into Reddit’s strengths: story and specificity.
The headline (“I’m a massive savings nerd… stupidest money mistakes…”) sounds like a real thread you’d click, not brand copy. The post leads with concrete value—numbers, personal savings, and clear next steps—before it ever feels promotional.
It’s written in plain language, framed as advice from a fellow user, and backed by strong engagement (upvotes, comments), which signals social proof right in the feed.
How to Build Your Reddit Marketing Campaigns
Reddit doesn’t reward brands that rush in with a big ad budget. It rewards the ones that show up and learn the culture first.
That’s why it helps to think about Reddit marketing in stages instead of “launching a campaign” overnight.
Start with low-risk actions that teach you how each community works. Then layer on more visible content and light promotion. Once you know what lands, you can treat Reddit like a full channel.
In the sections below, we’ll walk through a practical Crawl → Walk → Run model you can use to move from basic participation to a scalable Reddit program that drives traffic and revenue (and not just karma).
Crawl
In the Crawl stage, your main job is to learn the ropes of Reddit and show up like a real user. You’ve set up a branded account, know the Reddiquette, and have your eyes on the subreddits where your audience already hangs out.
From here, keep it simple:
Read top and “hot” posts to get a feel for tone and what flies.
Comment on existing threads where you have real experience to share.
Answer questions in detail without instantly pushing your product.
Use Reddit search and “site:reddit.com” Google searches around your main topics to find the discussions that matter most to your buyers.
This screenshot shows the Crawl stage in action using a site search to see which subreddits and threads already rank for “gravel bikes.” It includes threads on clarifying the definition of a gravel bike and calls for product recommendations.
As you explore, pay attention to the phrases people use and the problems they describe. Also take note of the kind of answers they upvote.
Crawl is about listening and learning. You’re gathering intel on which communities are worth investing in. That way, you don’t sound like a marketer who just discovered Reddit yesterday.
Walk
In the Walk phase, you’re moving beyond “lurking” and turning your Reddit presence into a repeatable habit. Now, you’re showing up in a handful of high-value subreddits on purpose. You’re not just scrolling anymore.
Start by narrowing your focus. Pick three to five communities where your audience already hangs out and where you can add real expertise. Look for threads that match your core topics and keywords.
Your job at this stage is to:
Comment thoughtfully on existing threads, especially questions you can answer from experience.
Share occasional links to genuinely useful resources (yours or others), but always wrapped in context.
Track what gets upvotes, saves, and replies so you can see which angles resonate.
Think of Walk as your calibration stage. You’re learning the language and formats that work in each subreddit. You’re also starting to spot patterns you can later turn into content pillars, SEO topics, and even product ideas.
You’re not trying to dominate Reddit yet. You’re trying to become a familiar, helpful name in the spaces that matter.
“It’s all about trust,” says Becky McManus, the senior SEO strategist at NP Digital.
“Teams should expect to earn trust gradually by engaging authentically and consistently within the communities that genuinely care about what they offer.”
Run
Run is where Reddit becomes a proper channel, not just a side experiment.
By this point, you know:
Which subreddits respond best.
Which topics reliably spark quality discussion.
Which profiles (brand and team) have real credibility.
Now you can scale intentionally. This may include launching and actively moderating a branded subreddit as a hub for FAQs, feedback, updates, and success stories. You might also keep a presence in adjacent communities and jump into high-impact threads quickly.
From there, you can coordinate with your SEO and content teams to help keep responses and resources consistent.
Reddit becomes:
A content engine: Your best threads turn into blog posts, landing pages, videos, and email content.
An SEO asset: More of your conversations show up in SERPs and “Discussions and forums” modules.
A live focus group: You see unfiltered reactions to ideas, messaging, and features in real time.
At this stage, you can also layer in paid campaigns, but be sure to promote angles you already know resonate organically. That way, you’re not just guessing with ad dollars.
What Reddit Marketing Success Looks Like
A good example of Reddit done right is NP Digital’s work with TurboTax.
From January to April 2025, TurboTax-branded profiles joined relevant tax and personal finance threads, adding 159 thoughtful comments and starting targeted conversations during filing season.
The impact showed up well beyond Reddit. Several of those threads were pulled into Google’s “What people are saying” for searches like “quarterly tax deadlines” and “turbotax early refund,” and one comment was cited in AI-generated Reddit answers within days.
Brand mentions hit 5,404 (up 10 percent year over year), and positive mentions nudged up even in the middle of tough conversations about pricing and early refunds.
We also paired that Reddit work with SEO. A refreshed “Ways to File for Free” guide captured the featured snippet for “is turbotax free,” helping outrank older negative Reddit threads and giving TurboTax more control over how the brand shows up in search.
FAQs
How do you do marketing on Reddit?
Act like a helpful user, not a billboard: join relevant subreddits, add value in threads, then layer in carefully targeted information that can be tied back to your brand.
Can you self-promote on Reddit?
Yes, but only within strict limits. Reddit and most subreddits take a hard line on spammy self-promotion. If most of your activity is just dropping your own links, you’ll get downvoted or banned. Read Reddit’s self-promotion and Reddiquette guidelines and participate in conversations, but make sure any link you share is genuinely helpful and clearly relevant to the thread.
How do I create a Reddit marketing strategy?
Start with your goal (awareness, traffic, leads, or support), then map the subreddits your audience already uses. Create a branded account, learn each community’s rules, and spend time commenting before you post anything promotional. From there, plan a mix of organic participation (answers, explainers, AMAs, resource threads) and small paid tests once you know what resonates.
How do I market on Reddit without getting banned?
Read the FAQs, Reddiquette, and each subreddit’s rules before you start posting anything. And be sure to contribute more than you promote: answer questions, share experiences, and only link to your own content when it clearly adds value.
How much do Reddit ads cost?
Reddit ads run on an auction model, so prices vary widely. It sets its rates at $5 a day minimum, and costs vary from $1.50 to $10 per 1,000 impressions (or more for premium placements).
Conclusion
Reddit is a unique platform with millions of active users. It might seem like the ideal place to promote your business, but you could get banned (or ridiculed) if you aren’t careful.
Although Reddit is tougher on self-promotion on other platforms, that doesn’t mean marketers should steer clear of it altogether. Provided you stick to the rules and don’t stray into spamming or being “salesy,” you have the opportunity to grow a keen, engaged following.
Reddit can become one of your most valuable channels if you do it right. You can build trust inside niche communities, earn traffic from threads that rank in search, and even shape how your brand shows up in AI summaries.
With thousands of subreddits, there’s almost always a corner of Reddit where your audience is already talking. Show up to listen and answer questions as you learn the ropes.
Promotion comes later, after you’ve proven you’re there to add value, not just to cash in.
New technologies like AI have drastically changed search engine architecture. Gaining visibility online requires more advanced tactics than traditional SEO. One of these secret weapons to give your pages more real estate in search results is called FAQ schema.
It’s simple to implement using basic structured data (if you’re new to that, here’s a primer on schema). But here’s the real kicker: Google’s AI Overviews and other AI-driven platforms are now pulling content directly from FAQ schema.
In the past, marketers have implemented FAQ schema to gain visibility in Google features, such as featured snippets and Answer Cards. Other features are more prevalent now, but FAQ schema is still an important part of modern search.
Today, using FAQ to structure your data can help you appear in AI-driven results. If your content is optimized, that gives your content the best shot of being read and cited by LLMs, not just by the regular search engines.
Most site owners still aren’t taking full advantage of this. So if you jump in now, you’re ahead of the curve.
This guide will walk you through setup, placement, and results.
Key Takeaways
FAQ schema increases your visibility in Google by making your content more visible to Google features like People Also Ask, as well as the LLMs that power AI search results—even if your ranking doesn’t change.
Use schema on FAQ hubs, knowledge bases, and any other priority content. Structuring this data can help answer common questions and reduce friction.
Google’s AI Overviews and other LLM-driven features are now pulling answers directly from FAQ schema, making it critical for future visibility.
JSON-LD is the recommended format, and you can implement it in under 30 minutes using simple tools or plugins.
Schema works best when your questions are specific, helpful, and tied to real customer concerns.
What is FAQ Schema?
FAQ schema is a type of structured data you add to your page’s html code to help search engines understand your frequently asked questions and display them directly in results.
It’s based on Schema.org markup, which Google and other search engines use to parse and categorize content. When implemented correctly, FAQ schema turns your standard list of questions and answers into rich results.
That added visibility means users can find the info they need faster, making your website stand out from the rest. You might not jump in rankings, but you’ll earn higher visibility just by taking up more space.
Today, that structured content can also be pulled into generative AI responses like Google’s AI Overviews, which are becoming more prominent in search. That gives you another opportunity to show up, even if you’re not ranking #1.
You don’t need to be a developer to use schema, either. Tools and plugins can handle the heavy lifting, and you can gain a solid understanding of how schema works behind the scenes just by reading this breakdown of structured data.
Not only does Google change its algorithm regularly, but it also often tests new design elements.
For example, if you search for “food near me”, you see a list of local restaurants along with their ratings.
When you search for a person, Google may display a picture of that person along with a brief overview.
Over the years, Google has refined its search results to provide you with the best experience.
For example, if you search for “2+2,” Google shows you “4,” so you don’t have to click through and visit a webpage.
However, FAQ schema markup may be flying under the radar, by comparison.
Here’s what I mean: if you search “digital marketing,” you see a bank of questions in the People Also Ask section:
This snippet holds some of the most coveted real estate on Google’s SERPs. It’s the third thing you see below sponsored results and images for our “digital marketing” search.
Getting included in a Google feature like this requires structured data. That’s why FAQ schema is such a powerful optimization.
To take things further, mastering markup and data structuring can also position your pages to appear in Google’s AI Overviews. The large language models (LLMs) that power your favorite AI assistant need a way to process the information on the internet. They rely on schema and data structure to understand what they’re reading. Here’s an example:
So, where should you begin with FAQ schema and data structuring? Keep reading while I talk you through it.
Picking The Right FAQ Schema Markup: QA vs. FAQ Schema
Before you introduce schema to your site, you have a markup decision to make. There are different types of markup, but one of the most popular is FAQ schema.
This kind of FAQ schema markup tells search engines your website is a Frequently Asked Questions (FAQ) page. If you have a FAQ page on your website, using the FAQ schema can help you improve your ranking in the SERPs.
As an example of what FAQs can do, in some cases, you can get a collapsible menu under your SERP results that reveals the answer when a user clicks on it:
If you use Google’s voice search, structured data can help you rank here. And, with Google’s current layout, you actually get double the payoff. The AI overview will pull from your structured data, and you’ll also appear as a source tile, directly to the right of it:
In contrast, you use a Q&A schema where users contribute different types of answers and vote for the best one. This provides rich result cards under your SERP, showing all the answers with the top answer highlighted.
After Google’s implementation of its FAQ schema rich results, website owners could have two URLs showing in search. Typically, they look like this:
Now you understand the purposes of these different schemas, let’s move on to Google’s guidelines on using FAQ schema.
Google’s FAQ Schema Markup Guidelines
As detailed below, Google has a comprehensive list of FAQ schema guidelines:
Use FAQPage only if your page contains a list of questions and answers. Use QAPage instead if you have a single question, and users can submit alternative answers. Here are some examples:
Valid use cases:
The health site created an FAQ page without any option for users to answer alternative questions.
A government agency support page that lists FAQs without a way to submit alternative answers.
Invalid use cases:
Forum pages reserved for posting a single answer to a particular question.
A product support page where users can submit answers to a single question.
A product page to which users can submit multiple questions and answers on a single page.
Using FAQPage for advertising purposes.
The entire question text should be included in each question, and the entire answer text should be included in each answer. The entire question text and answer text may be displayed.
Content that includes obscene, profane, sexually explicit, graphically violent, promotion of dangerous or illegal activities, or hateful or harassing language may not appear as a rich result.
All FAQ content must be visible to the user on the source page.
As set out below, Google also has extensive guidelines for Q&A schema:
Only use the QAPage markup if your page has information in a question-and-answer format, which is one question followed by its answers.
Users must be able to submit answers to the question. Don’t use QAPage markup for content that has only one answer for a given question with no way for users to add alternative answers; instead, use FAQPage. Here are some examples:
Valid use cases:
Forum pages that allow users to submit answers to individual questions.
Product support pages that enable users to submit answers to singular questions.
Invalid use cases:
FAQ pages written by the site itself that don’t let users provide alternative answers.
Product pages allowing users to give multiple questions/answers on an individual page.
How-to guides, blog posts, and essays that answer a specific question.
You must not add QAPagemarkup to an entire site or forum if some of the content isn’t eligible, or apply QAPage markup to FAQ pages with numerous questions on a single page.
Don’t use QAPagemarkup in your advertising.
Each question must include the full text of each question and answer.
Only use Answermarkup for answers to the questions. Not for comments on the questions or answers.
If your question and content include prohibited content such as hateful language, sexually explicit content, or promote dangerous or illegal activities, Google may not display it as a rich result.
If your content meets these guidelines, the next step is to implement the schema on your website and decide which type to use.
How Do I Implement QA and FAQ Schema?
You can implement schema either through JSON-LD or Microdata, but first, let me explain some more about them.
JSON-LD is a schema definition language; it describes the structure and meaning of JSON data. JSON-LD is easy to use, lightweight, and extensible, allowing you to define your own custom schemas or utilize existing schemas from other sources.
In contrast, microdata uses a subset of the JSON format to add extra information to HTML tags. The role of this information is to identify the type of data and how to handle it. For example, you can use microdata to mark up a person’s name and email address:
I recommend choosing one style and sticking to it throughout your webpage; for consistency, I’d suggest not using both types on the same page. Let’s walk through a quick process on how to create and test each type of schema on your site.
Create Your Schema
If you’re unsure which one is best to use, Google recommends JSON-LD, and Google has been in the process of adding support for markup-powered features. You can implement JSON-LD in the header of your content, and it’s quick to add.
JSON-LD
If you’re wondering what this looks like in practice, here are some examples:
For ease of implementation, you can create your own schema by using the Technical SEO FAQ schema markup tool. It gave me the following result:
The Technical SEO tool is easy to use. Just select the type of page you want to create, add in your questions and answers, and watch the schema appear!
Microdata
Now on to microdata.
Creating microdata code, like the example below, may appear complicated, but it doesn’t have to be. You can use one of the many free tools to create your own code, like I did here:
<p itemprop=”text” class=”faq-a”>Digital marketing is the process of creating, managing, and executing a marketing plan that uses digital technologies to reach and engage customers. Digital marketing includes email marketing, search engine optimization (SEO), social media marketing, and display advertising.</p>
When implementing schema on your website, feel free to use the templates above and modify them with your own text, or keep it simple by using the tools I linked to.
Consider questions that prompt your reader to take the next step. That could be clarifying a product feature, explaining your pricing model, addressing objections, or even tackling basic industry terms. If users are asking about it in a search—or in your support inbox—it’s probably a good fit. You don’t need a lot of questions either. Three to five well-structured FAQs can be enough to add value and get picked up by search engines.
Testing Your New Schema
Once you’ve finished, you can use Google’s Structured Data Testing Tool to test your rich results or structured data. The tool tests schema markup and rich results, and gives you feedback on any errors or issues with your code. Google’s Rich Result Tester also gives you an idea of what your structured data looks like in the results.
Getting Results With FAQ Schema
Log in to Google Search Console and enter the URL of any page you’ve modified in the top search bar.
After that, you want Google to crawl the page so it can index the results. The only thing you need to do is click “request indexing”.
After your URL is reindexed, it’s more likely to show up in relevant search results.
The key to making this work is to do this with pages and terms that already rank on page 1. That’s where I’ve seen the biggest improvement.
Where to Use FAQ Schema
FAQ schema isn’t just for blog posts. You can use it across dedicated FAQ pages, knowledge bases, and any pages that give users helpful answers.
Think of FAQ schema as a way to move users closer to a decision. If a potential customer might hesitate, an FAQ can help them keep going. When those answers show up in search, you’re making it even easier for them to find and trust you.
Wherever you decide to use it, be sure to add FAQs that handle objections, explain your process, or outline what’s included. The goal is to clearly address any concerns your customers may have. This might mean breaking down what makes your product or offering unique or helping customers choose between different options in your industry.
Does FAQ Schema Help Me Rank For People Also Ask and Featured Snippets?
Here’s a question: Does the FAQ schema help with ‘People Also Ask’ and Featured Snippets?
Yes. Properly structuring your data using FAQ schema markup can significantly increase your chances of appearing in People Also Ask or AI-driven searches. Structuring your data shows Google that your FAQs are providing direct answers to users questions, creating a much better chance of increasing your visibility.
Maximizing your efforts here may require some research. Dig into what customers are asking routinely on your own pages, as well as competitors and industry leaders. From there, you can frame those user queries as FAQs on your pages.
With the right questions in hand, your job now becomes answering them as directly as possible. Write a quick, direct answer that takes no more than two to three sentences. Also, don’t “bury the lead.” Make sure you include the important information as close to the beginning of your answer as possible.
Does FAQ Schema Help Me Rank For Voice Search?
Short answer: absolutely!
For a start, FAQ schema can help Alexa users find you. According to recent stats, there are about 77.6 million Alexa users in the U.S. alone, and you want these people to discover your site!
It’s not just Amazon, though.
Apple and Google are also using voice search, and there’s a good reason why: in recent years, voice search use is up among online users. Recent data shows there are over 100 million U.S. consumers using smart speakers.
Additionally, voice search enhances accessibility and enables mobile users to find you when they’re on the go, providing two more reasons to consider using FAQ schema markup.
Questions from voice search get most of their answers from featured snippets, and adding structured data on your website increases the chances of getting you into these high-visibility snippets.
I also suggest checking out these tips on voice search SEO for more strategies for ranking for voice search.
Does FAQ Schema Help Me Rank In LLMs?
Yes, and it’s becoming a bigger deal by the day.
As generative AI continues to shape search, large language models (LLMs) like Google’s Gemini and Bing Copilot are pulling more answers directly from structured content. That includes FAQ schema.
If your content is clearly marked up and answers a question well, it has a higher chance of being pulled into AI Overviews and other rich AI snippets, even if your page isn’t ranking #1 organically.
This is especially true for concise, factual Q&A content. LLMs look for clarity, context, and credibility. Well-written FAQ schema checks all three boxes and gives search engines a clean structure to work with.
While there’s no guaranteed way to rank in AI-generated results, schema gives your content a technical advantage. It tells the model: “Here’s a clear, trustworthy answer.”
And with less real estate available in AI-driven SERPs, every edge counts.
If future visibility is your goal, FAQ schema should be part of your strategy. It’s one of the simplest ways to increase your chances of being surfaced by generative AI.
FAQs
What is FAQ schema?
FAQ schema is a type of structured data that helps search engines understand and display your frequently asked questions in the search results. It can turn your standard FAQs into rich results, giving your listing more space and improving click-through rates.
How do you create FAQ schema?
You can create FAQ schema manually using JSON-LD code or use a tool or plugin that generates it for you. Many platforms like WordPress have SEO plugins that make this simple—just input your questions and answers, and the markup is handled for you.
How do we implement FAQ schema?
Once you’ve created your FAQ schema, you can add it to the HTML of your page—usually in the header or just before the closing body tag. Be sure to test your code using Google’s Rich Results Test to make sure it’s valid and error-free.
Does FAQ schema still work?
Yes, FAQ schema still works—and it’s more relevant than ever. It not only boosts your visibility in the SERPs but also increases your chances of being included in AI Overviews and other generative search features.
Conclusion
The simple hack of adding FAQ schema potentially increases the visibility of your brand and helps improve the authority of your website. It’s a simple solution that can take a single day to implement across your main question, product, or FAQ page.
I’ve used it heavily in the past, and as long as I pick keywords that I already rank on page 1 for, I get great results.
Although FAQ schema markup looks complicated, there are plenty of free tools to help you create it, and taking this extra step may give you an SEO advantage that other sites may lack.
B2B marketing often gets treated like a second-class citizen compared to B2C. But here’s the truth: business-to-business marketing is growing fast and generating real results across industries.
Eighty percent of B2B buyers expect a B2C-like experience when interacting with brands. That means the old-school, relationship-only playbook won’t cut it anymore. You need a digital-first strategy that attracts high-quality leads, builds trust at scale, and drives measurable revenue.
In this guide, we’ll walk through proven B2B marketing strategies that actually work in 2026 and how to build your own roadmap from scratch.
Key Takeaways
B2B buyers are research-driven, digital-first, and selective.
Content marketing, SEO, and email are foundational for long-term growth.
LinkedIn and Google Ads are ideal for paid B2B campaigns.
You need a strategy built on your ideal customer profile, clear goals, and constant testing.
Trends like AI-generated content, video, and ABM are shaping the future of B2B digital marketing.
What is B2B Marketing?
B2B marketing stands for business-to-business marketing. Instead of selling directly to consumers (like B2C), you’re selling to other businesses.
That means longer sales cycles, more stakeholders, and a bigger focus on ROI. B2B decisions are driven by logic, not emotion. Buyers want to solve a pain point, improve operations, or generate a clear return.
In B2C, you might sell running shoes to a single customer. In B2B, you could be selling supply chain software to a procurement team of 12. That’s a very different game.
But even though you’re selling to companies, it’s still humans making the call. So your B2B strategy still needs to connect on a personal level.
How B2B Marketing Works Today
The modern B2B buyer looks a lot like a B2C consumer:
They start online.
They do extensive research.
They talk to peers.
They want to be educated before they talk to sales.
According to Gartner, 83% of a typical B2B purchasing decision happens before a buyer speaks with a sales rep. That means your marketing needs to do the heavy lifting.
The journey isn’t linear either. One stakeholder might download an e-book. Another might follow your brand on LinkedIn. A third might attend your webinar two months later. You need to stay visible and valuable at every stage.
Digital-first, multi-touch, always-on marketing wins in B2B today. It’s about building trust long before the sales team gets involved.
Core B2B Marketing Strategies That Work
There isn’t one silver bullet for B2B growth, but there are a handful of tried-and-true strategies that consistently deliver results. From attracting leads to nurturing them into customers, each of these plays a key role in your overall marketing mix.
Content Marketing
Content marketing is at the heart of every successful B2B strategy. It’s how you build authority, answer buyer questions, and stay visible throughout long sales cycles. Whether it’s blog posts, whitepapers, or customer success stories, great content gives prospects a reason to trust you before they buy.
Create a content calendar that includes top-of-funnel topics (like how-to posts or industry trends), mid-funnel pieces (case studies and solution guides), and bottom-funnel assets (ROI calculators, product comparisons). Use SEO research to guide your topics, and always write with your ICP’s pain points in mind. Update old content regularly to stay relevant, and use internal linking to guide users deeper into your funnel.
Blogs, whitepapers, guides, and case studies all play a role in educating and nurturing your audience. For example, security software provider Entrust does an annual report on fraud, relevant to their audience of enterprise, finance, and government professionals.
Long-form SEO-driven content builds authority and captures top-of-funnel traffic. Tie your strategy to the funnel. For example, TOFU is best suited for blogs, MOFU for case studies, and BOFU landing pages.
SEO
Search is where most B2B buyers begin. If you’re not showing up for high-intent keywords, you’re missing out on warm leads who are actively looking for a solution like yours. That’s why SEO is a non-negotiable for any serious B2B strategy.
Start by identifying search terms your audience uses throughout their buying journey through tools like Ubersuggest. Prioritize informational and commercial keywords, not just branded terms. Sometimes a low MSV may be okay if it’s relevant to your core audience, like the example below:
Optimize your site structure, title tags, meta descriptions and content. Build backlinks through guest posts and digital PR. Use schema markup to help search engines understand your pages. B2B SEO takes time, but it compounds, make it part of your long game.
Email Marketing
Email marketing continues to be the highest-performing B2B channel when it’s done right. It’s personal, direct, and measurable. But today’s buyers won’t tolerate one-size-fits-all blasts. You need segmentation, automation, and value in every send.
Use gated content and lead magnets to build your list, then segment it based on industry, buyer stage, or behavior. Set up automated drip campaigns that educate and nurture. Include useful resources, not just sales CTAs. Monitor open and click rates, and A/B test everything from subject lines to CTA placement. Good email marketing feels like a helpful nudge, not a pushy pitch.
Segment your lists by persona, behavior, and funnel stage. Use lead magnets like checklists or templates to grow your list. Automate nurture flows, and track opens, clicks, and replies.
Paid Ads
Organic takes time. Paid gives you speed and scale, especially when targeting high-value buyers. The key is precision. B2B paid ads work best when you combine targeting capabilities with smart messaging.
LinkedIn ads let you reach decision-makers by job title, industry, and company size. Google Search ads help you show up when someone searches for your product or service. Retarget website visitors with display or video ads to stay top of mind. Use UTM tracking to measure effectiveness, and continuously refine your copy and creatives. Paid ads work best when they amplify a strong organic strategy.
Webinars and Events
Webinars and virtual events are lead generation machines when done well. They give you the chance to educate prospects, show off your expertise, and interact with potential buyers in real time.
Pick topics that align with pain points your audience is actively researching. Bring in subject matter experts, use polls to engage viewers, and offer the replay as a gated asset post-event. Promote your webinar via email, social, and paid channels, especially after the initial release where it will show the most impact:
Events are also a content goldmine—turn recordings into short video clips, blog recaps, and nurture emails to extend their value.
They let you demonstrate expertise, answer objections, and collect leads. Keep topics specific. Invite prospects already in your pipeline. Repurpose the content as video clips, blog posts, or gated downloads.
B2B Vs B2C Marketing: How Do They Compare?
The biggest difference between B2B and B2C marketing comes down to the buyer’s mindset and how they make decisions.
Here’s a breakdown of how each approach typically differs:
B2B Marketing
Driven by ROI, efficiency, and logical outcomes
Longer sales cycles with multiple stakeholders
Higher-value deals and more complex products or services
Content is educational, technical, and data-backed
Messaging targets decision-makers and buying committees
B2C Marketing
Driven by emotion, desire, and personal benefit
Shorter sales cycles with individual decision-makers
Lower price points and more impulse-driven purchases
Content is entertaining, persuasive, and brand-oriented
Messaging targets individuals based on lifestyle or interests
These differences also extend to the type of content that performs well for each segment based on these needs.
How To Build a B2B Marketing Strategy From Scratch
You don’t need a huge team or budget to build a powerful B2B strategy. What you do need is clarity: on who you’re targeting, what you want to achieve, and how you’ll measure success. These are the building blocks every marketing plan should be built on.
Know Your Ideal Customer (ICP)
Everything starts with knowing who you’re selling to. Your ideal customer profile (ICP) should be specific and rooted in data—not assumptions. Outline key characteristics like industry, company size, annual revenue, and tech stack. Then go deeper: what roles make the buying decisions? What keeps them up at night? What objections do they raise in the sales process?
Use interviews, win/loss analysis, and CRM insights to map these out. A strong ICP informs your messaging, targeting, offers, and even product positioning. Without it, your marketing will feel generic—and miss the mark.
Who do you want to reach? What are their roles, pain points, objections, and decision criteria? Use interviews, surveys, and CRM data to build accurate personas.
Set Goals and KPIs
A marketing plan without measurable goals is just guesswork. Define success using metrics that align with business outcomes. Think beyond vanity metrics like impressions or traffic. Focus on KPIs such as MQLs, SQLs, CAC, CLV, and pipeline velocity.
Set benchmarks based on past performance or industry standards. Make sure sales and marketing agree on definitions and expectations. Use dashboards and regular reporting to track progress. When your team knows what “good” looks like, they’re more likely to hit it.
Track MQLs (marketing qualified leads), SQLs (sales qualified leads), CAC (customer acquisition cost), and CLV (customer lifetime value). Tie your KPIs to revenue.
Choose Your Channels
Don’t spread yourself thin trying to be everywhere. Choose marketing channels based on where your ICP actually spends time and how they make decisions.
LinkedIn is a powerhouse for targeting professionals. Email is ideal for nurturing. SEO brings long-term compounding returns. Paid ads provide immediate visibility. Webinars and events build authority. Select a mix of 2–4 core channels and go deep before you go wide.
Document how each channel maps to your funnel. Assign ownership and set clear goals for each.
Use a blend of organic and paid. For example: content + SEO + LinkedIn Ads.
Create a Content Plan
A content plan connects your ideas to outcomes. Start by mapping topics to each stage of the funnel: awareness, consideration, and decision. Awareness content (like blog posts) attracts traffic. Consideration content (like case studies or webinars) builds trust. Decision content (like pricing pages) removes friction.
Balance evergreen content that compounds over time with campaign-specific pieces tied to launches or seasonal priorities. Repurpose content across formats, turn webinars into blog posts, or blogs into LinkedIn posts. Make distribution part of the plan, not an afterthought.
Test and Optimize
No B2B strategy is perfect out of the gate. The best teams test constantly. Start with A/B tests on subject lines, CTAs, landing pages, and ad copy. Measure what actually moves the needle, not just what looks good.
Review performance weekly or monthly, depending on volume. Use heatmaps, CRM data, and attribution tools to identify where leads drop off. Small improvements add up fast, especially in long sales cycles. Optimization is where great marketing gets better.
A/B test CTAs, landing pages, ad creatives, subject lines. Run monthly reviews and adapt based on performance.
B2B Marketing Trends To Watch
Staying ahead in B2B marketing means paying attention to what’s gaining traction across digital channels.
AI Content Creation: Tools like ChatGPT, Jasper, and Writer.com are speeding up workflows and lowering content costs. That said, AI is best used for drafts, outlines, or ideation. Final outputs should still go through human editing to preserve quality, tone, and brand voice.
Video for Trust: Short-form video continues to dominate attention spans. Think beyond YouTube. Platforms like LinkedIn and TikTok now prioritize native video. B2B brands are using testimonial videos, product explainers, and founder messages to build credibility fast.
Account-Based Marketing (ABM): ABM is moving from enterprise-only to mid-market and even SMBs. With more tools available, it’s easier than ever to target specific accounts with personalized content, ads, and outreach. Align sales and marketing to increase close rates and shorten cycles.
First-Party Data Focus: With the decline of third-party cookies, companies are investing more in building their own data. Expect more gated content, newsletter offers, and community-building plays to capture emails and preferences directly from users.
Sales and Marketing Alignment: Marketing can no longer just focus on lead gen. It’s also about sales enablement, creating assets that help close deals. Look for tighter integration between CRM systems, shared KPIs, and ongoing collaboration between both teams.
Conversational Marketing: Chatbots and live chat are becoming standard on B2B websites. Instant answers and qualifications can speed up pipeline velocity. Use tools like Drift or Intercom to build conversational flows that feel personal, not robotic.
FAQs
What is B2B marketing?
B2B marketing stands for business-to-business marketing,strategies used to sell products or services to other businesses. B2B marketers use a mix of digital channels, from content, SEO, social media, email, PPC, and webinars to gain authority and interest from customers.
How do you do B2B marketing?
Build a strategy based on your ideal customer, set measurable goals, pick the right channels, and consistently test and improve.
How does content marketing help B2B?
Content builds trust and educates potential buyers before they talk to sales. It drives organic traffic and supports every stage of the funnel.
Conclusion
If you’re serious about growing in B2B, you need a digital strategy that reflects how modern buyers behave. They expect value at every interaction. They need proof that your solution works.
Focus on building trust through content, SEO, email, and targeted campaigns. Measure what matters. Optimize relentlessly.
And if you need help building a scalable, high-converting B2B strategy, NP Digital is here for you.
But AI search adds a new layer your team needs to master.
Here’s what I mean:
Traditional SEO gets your pages ranking in top search positions.
AI SEO gets your brand visible in AI-generated answers — through brand mentions, citations, or both.
You’re expanding what SEO covers. Not replacing it.
Let me break down what’s changed and what it means for your team.
What’s Changed
Search behavior itself has evolved a lot over recent years.
A growing number of people don’t just “Google” anymore. They discover, compare, and decide across multiple platforms. (And this has been the case since long before ChatGPT came along.)
Someone might start on TikTok, check Reddit reviews, search on Google, and ask ChatGPT for a summary before taking action. And they might revisit these platforms at various stages of the journey.
That journey looks less like a straight line and more like a network.
Here are five other changes reshaping how search works today:
Whole-web signals: AI pulls from your website and everywhere else your brand appears online. Your entire digital footprint influences your AI visibility.
Entity recognition: AI understands your brand as a concept it can connect to products, industries, and related topics, not just keywords to match (learn more in our guide to entity SEO)
Passage-level retrieval: AI extracts specific sections from your content to use in its answers, not entire pages. This means it needs to be clear what each section of your content is about.
Conversational search behavior: AI search queries tend to be longer and more specific. People describe problems in detail rather than typing short keywords, which means the AI often cites highly specific content rather than generic guides.
Zero-click reality: Users can now get complete answers without visiting websites. Traffic from search is no longer guaranteed, even with strong visibility.
What This Means for Your Team
These changes don’t require you to rebuild your team from scratch.
But they do require expanding what your team focuses on:
Your content team still writes. But now they also need to structure content so AI can easily understand it and extract sections for its answers.
Your technical SEO team still optimizes site architecture. But priorities shift toward AI crawlability, performance, and schema implementation.
Your strategist still tracks performance. But now they also need to measure citations and brand mentions across AI platforms.
Most of these skills build on what your team already knows. Again, they’re extensions, not replacements.
4-12 months is a typical timeline to get your team comfortable with AI SEO fundamentals.
You’ll need some combination of internal training, external guidance, and selective hiring — depending on your current gaps. I’ll talk more about this later.
First, let’s break down the specific skills your AI SEO team needs.
Essential AI SEO Skills Your Team Needs
Not everyone needs to be an AI SEO expert in all areas.
One person (typically a lead or strategist) needs strategic understanding. They understand how AI search works and can adapt when platforms change.
The rest of your team needs execution capability. They can follow guidelines and apply best practices.
It’s helpful if they show interest in understanding AI SEO, but it’s not required.
Here are the key skills that bridge traditional SEO and AI search.
Understanding AI Retrieval
AI platforms find and reference content differently from Google’s traditional ranking systems.
Some platforms, like Perplexity, search the web in real-time.
Others, like ChatGPT, can search the web or pull from their training data.
And AI Overviews use Google’s existing index and Gemini’s training data.
To optimize for and appear in these places, your team needs to understand how these systems select what to cite and mention.
When someone asks a question, these platforms look for content that directly answers the query. They prioritize sources that are clearly structured and contextually relevant.
Note: AI systems also use a process called query fan-out. This involves expanding one user prompt into multiple related sub-queries behind the scenes.
That means your content can surface even if it doesn’t match the original question exactly. If it covers a related angle or entity that the AI connects to the topic, it can be cited or mentioned.
Your SEO lead or strategist typically owns this skill.
They already understand search intent and ranking logic — the same foundations that AI retrieval builds on.
In smaller teams, a content strategist can also take this on with a shallow learning curve.
Typically, they’ll spend 2-3 hours monthly testing how your brand appears across AI platforms. Document patterns in what gets cited. And adjust content strategy based on what’s working.
Writing for AI Extraction
AI search tools don’t respond to user queries with entire articles. Instead, the AI pulls specific passages that answer those queries.
If a passage requires a lot of surrounding context to make sense, AI may be less likely to understand its relevance and therefore be less likely to use it.
This means each section of your content needs to still make sense even when taken out of the context of the rest of the article.
Each section should answer a specific question on its own, without relying on references to other parts of the article.
This is generally just good writing practice. If you find yourself making too many unique points in one section, it’s probably best to split it into subsections.
But clarity here is also key.
For example, avoid: “As we mentioned earlier, this approach works well…”
Instead, write: “Structuring content into self-contained passages helps AI extract and cite your information more effectively.”
Here’s another example of effective writing for AI extraction:
The second version makes sense whether someone reads your full article or sees just that paragraph in an AI response.
This doesn’t mean every sentence needs a complete context. It means key passages should stand alone.
Who Can Own It?
Your content or editorial team can handle this.
SEO provides the framework and guidelines. Writers implement it in their daily work.
For example, editorial reviews the article structure before publishing, ensuring each section has a clear, standalone takeaway.
Sometimes that means breaking a 500-word section into three shorter subsections with specific headers.
By the way: As a content marketer myself, I don’t think this shift is dramatic.
Most great content teams already write clearly and structure information logically. This just prioritizes ensuring key passages work independently.
Building AI-Readable Structure
AI needs clear signals to understand your site’s structure and how content relates to other pages on your site.
For example, schema markup makes your data more structured by defining what your content represents.
This can make it easier for AI systems to interpret and cite your content accurately.
While the full impact is still unclear, structured data makes your content easier to parse, which is helpful for search engines anyway. And since Gemini can lean on Google’s search infrastructure, it’s not all that unreasonable to expect that schema could at least indirectly affect your visibility in places like AI Overviews and AI Mode, now or in the future.
Similarly, internal linking shows how topics connect.
And a clear site hierarchy indicates which pages are most important.
Think of it as creating a map.
Instead of making AI infer relationships, you’re explicitly defining them.
Beyond your site: Entity databases
Once you have the basics down, consider registering your brand and products in databases like Wikipedia, Wikidata, or Crunchbase.
These knowledge bases help AI systems understand entity relationships and how your brand fits into broader industry contexts.
This bridges on-site structure (like schema markup) with off-site presence. You’re helping AI systems recognize your brand across the web, not just on your site.
You don’t need this starting out. But it’s worth exploring once your core AI SEO structure is in place.
Who Can Own It?
Your technical SEO can take ownership of this skill.
They already handle the fundamentals like implementing schema markup, managing site architecture, and optimizing internal linking structures.
The approach doesn’t change much. They’re just applying the same technical skills with AI systems in mind.
Tracking AI Performance
Traditional SEO metrics (like rankings, organic traffic, and click-through rates) still matter.
But they don’t say anything about your brand’s AI search visibility.
You need different metrics now, including:
Platform breakdown: Where you’re showing up (ChatGPT, Perplexity, Google AI Overviews, etc.)
Citation frequency: How often your content gets cited as a source in AI responses
Mention rate: How often your brand appears in AI-generated answers or recommendations
Mention sentiment: Whether those mentions are positive, neutral, or negative
These numbers indicate whether your AI SEO strategy is working.
Without specialized tools, you’ll need to manually search key queries across platforms and track when your brand appears.
Who Can Own It?
Your SEO analyst or whoever handles performance reporting can own this.
They’re already tracking traditional metrics. AI performance metrics become an addition to that dashboard.
If using AI visibility tools, they’ll monitor your visibility score and citation trends monthly.
Without specialized tools, they’ll need to manually search key queries across platforms, document when and how your brand appears, and track changes over time.
AI tools go beyond just looking at your website and pull from everywhere your brand is mentioned online. Including:
G2 reviews comparing tools
Reddit threads discussing your product
Forum conversations about your industry
News articles mentioning your company
If those mentions are sparse or outdated, AI has less information to pull from when someone searches for your brand specifically or asks about your product category.
This is where AI search extends beyond your domain.
Who Can Own It?
No single person can own this entirely.
PR, community management, and customer success each control different pieces of the puzzle.
Someone from SEO can take the coordination role, ensuring these teams understand how their work affects AI visibility.
In practice, this often means your SEO lead or director works cross-functionally to align off-site efforts with AI discoverability goals.
For example, they work with customer success to encourage reviews on platforms like G2 or Trustpilot.
They also monitor where your brand gets mentioned across forums, social platforms, and community discussions.
Different AI platforms retrieve and display information in their own ways.
For example:
Perplexity searches the web in real-time and shows numbered citations
ChatGPT can search the web or pull from its training data
Google’s AI Overviews draw from Google’s search index and Gemini’s training data
What gets you cited on one platform won’t automatically work on another because each platform follows patterns in what it mentions and cites.
For instance, I searched “which is the best camera phone of 2025” across three platforms.
ChatGPT cited multiple YouTube videos, a Reddit thread, Tom’s Guide, Yahoo, and Tech Advisor.
Google’s AI Mode cited one YouTube video along with a bunch of other websites — no Tom’s Guide, Yahoo, or Tech Advisor.
Claude cited Quora and Android Authority twice. No Reddit threads, YouTube, or Tom’s Guide.
Same query, completely different sources and mentions.
Your team needs to understand these differences when optimizing for AI visibility.
You don’t need separate strategies for each platform. But knowing how different platforms prioritize sources helps you structure your entire approach, from content to technical implementation to off-site presence.
Who Can Own It?
Your SEO lead or strategist can typically own this.
They can track how your brand appears across platforms and identify what’s working where.
They’ll spot gaps in coverage on LLMs that matter to the brand. For example, strong presence in ChatGPT but weak in Perplexity.
Then they work with content, technical, and other teams to adjust the overall strategy.
Query Intent Mapping
People search differently in AI platforms than they do in Google.
Traditional Google: “best CRM software”
ChatGPT: “I need a CRM for a 50-person sales team, budget around $10K annually, must integrate with Salesforce”
The queries are longer. More conversational. More specific.
I checked my own most recent 100 prompts to ChatGPT. They averaged 13 words each.
Compare that to traditional Google searches, which typically run 3-4 words.
Understanding these prompt patterns helps you create content that answers the actual questions people ask AI.
You need to think beyond traditional keywords.
What detailed questions are the people in your audience asking? What context are they providing? What outcome do they want?
Who Can Own It?
Whoever leads keyword research or content planning can take this on, usually your SEO strategist or content planner.
This builds directly on existing keyword research skills.
You’re expanding from “what keywords do people use?” to “what problems are people trying to solve?”
(Which you should have been doing all along, but now with a stronger focus.)
This person will analyze how people search in AI platforms and document the longer, conversational queries they use.
Then they’ll build content briefs that address those specific questions and scenarios.
The Build, Buy, or Borrow Decision: Getting AI SEO Skills on Your Team
You know which skills your team needs.
Now comes the practical question: how do you actually get them?
You have three options:
Build internally
Hire new talent
Bring in outside expertise
Here’s a snapshot of the pros and cons of all three:
Most teams end up doing some combination of all three. The key is knowing which approach works best for specific skills.
Let’s look at each one in detail.
1. When to Build (Develop Internally)
Upskilling your current team is almost always the smartest first move.
They already know your brand, your workflows, and your audience. That context shortens the learning curve dramatically.
Focus on developing skills that evolve naturally from what your team already does.
For example:
Train writers to structure content for AI extraction
Help your SEO lead understand AI retrieval patterns and how citations work
Encourage your analyst to track AI visibility metrics alongside rankings
These are logical extensions of existing expertise. Not entirely new disciplines.
Now, training doesn’t have to mean building a full internal curriculum.
Start small. For example:
Run short internal workshops to explain how AI search retrieves and cites content
Review recent AI-generated answers for your top keywords and note which competitors get mentioned
Compare their cited passages to yours, and update one or two articles using those patterns
To make internal training effective, use this quick checklist:
Upskilling may not be the fastest route to output. It can take a few months before you see real traction.
But it is the most sustainable.
Once your team starts applying AI-first thinking, you’ll see compounding returns with every new SEO campaign.
Best For
Startups and mid-sized teams that already have strong SEO foundations but a limited budget for new hires.
Watch Out For
Don’t overload your team with theoretical “AI SEO” training.
Focus primarily on skills that directly connect to visibility outcomes, like structure, clarity, and retrievability.
Also watch for skill concentration. If one person (like your SEO lead) ends up owning 3+ new AI skills, that’s a bottleneck. Consider hiring or borrowing expertise to spread the load.
2. When to Buy (Hire New Talent)
When you need expertise faster than you can build it internally, it’s time to hire.
Bringing in new talent makes sense when the skill is both specialized and strategic.
Something that gives your brand a long-term edge, not just a short-term fix.
For example:
Hiring a data or visibility analyst who understands how to measure citations and brand mentions across AI platforms
Bringing in a technical SEO who can model entities and implement structured data at scale
Adding an AI content strategist who can guide how your content aligns with AI retrieval patterns
These hires extend the capabilities of your existing SEO team. They don’t replace it.
The key to finding the right people?
Clarity before you post the job. Decide what outcome you’re hiring for.
Do you need faster technical execution, deeper analytics, or dedicated AI visibility leadership?
Before you start recruiting, here’s a quick checklist to work through:
With clear hiring criteria, you’ll know which expertise to prioritize and what title makes sense for your organization.
Best For
Mid-sized and enterprise teams that have budget flexibility and want to move faster than internal training allows.
Watch Out For
Don’t over-index on shiny new “AI SEO” titles. Few people have that exact label yet.
Instead, look for specialists in areas like data, structured content, and retrieval systems. These are people who can bridge SEO and AI.
3. When to Borrow (Outsource or Consult)
Not every skill is worth building or hiring for.
Some are highly specialized. Others you only need for a short period.
That’s where borrowing expertise makes sense — through consultants, freelancers, or agencies.
Outsourcing works best when you need to move fast on projects that require niche expertise.
For example:
Hiring a consultant to set up AI visibility tracking before your analyst takes over
Partnering with a content firm to scale passage optimization across hundreds of pages
Bringing in a Reddit marketing expert to boost your brand’s presence in relevant subreddits
This approach gives you access to deep expertise without expanding headcount.
You can bring in specialists to handle complex projects, fill capability gaps, or run pilot programs that would slow your internal team down.
Sometimes that means a one-off engagement.
Other times, it’s a recurring partnership that supports your strategy long-term.
The goal isn’t to offload responsibility. It’s to fill gaps your team can’t cover yet and to get critical work done without slowing down larger projects.
When evaluating potential partners, here’s a quick checklist to follow:
Best For
Teams that need quick access to specialized expertise or extra hands for complex, time-bound projects.
Watch Out For
Don’t treat outsourcing as a default fix.
If a skill becomes core to your strategy, consider bringing it in-house. But for niche or technical projects, keeping trusted external support can be more practical.
Choose partners who understand your brand voice. AI-first SEO still needs human context.
In practice, it’s rare that a team is fully built, bought, or borrowed.
You’ll probably use all three, often at the same time.
How much you lean on each one depends on factors like:
Your current team’s strengths and bandwidth
Budget flexibility for hiring or contracting
The urgency of upcoming SEO goals
How quickly AI search is evolving in your industry
Leadership’s appetite for experimentation
In my experience, many teams land somewhere near a 70-20-10 split. Which is roughly 70% built internally, 20% borrowed through outside experts, and 10% bought as new hires.
The exact ratio matters less than how deliberately you manage it.
Here’s how to keep that balance right:
Prioritize by impact: Build skills that sustain long-term visibility. Borrow when you need speed or experimentation. Buy only when a role becomes essential to your strategy.
Keep ownership internal: Even if outside partners execute the work, ensure someone on your team owns the outcome and applies the learnings.
Plan for rotation: As new AI SEO trends emerge, your mix will likely shift. What starts as a borrowed skill may become core within six months.
Audit regularly: Review your mix every quarter to see which skills rely too heavily on outside help. If a borrowed skill becomes recurring, start building it internally.
Follow this quick team review checklist to keep stock of your built, bought, and borrowed setup.
The key is flexibility and adaptability.
As priorities shift, don’t hesitate to rebalance how your team works.
That might mean promoting someone internally to take ownership of AI visibility, bringing in a freelancer to handle off-site optimization, or hiring a new analyst to deepen your data capability.
Adjust your structure based on what delivers the most impact, not what’s written on the org chart.
Your AI SEO Adoption Roadmap
You don’t need a massive reorg to evolve your SEO team for AI search.
You need a plan that helps your team build capability, test what works, and scale what proves effective.
This roadmap gives you that plan.
It breaks down:
What to focus on in each phase
How to build momentum
What progress should look like along the way
By the end, your team will know how to apply AI SEO principles consistently.
Note: This timeline is a starting point, not a rule.
Startups with smaller teams might compress this into 6 months. Enterprises coordinating across departments might need 15-18 months.
The timeline matters less than starting now and making steady progress.
Phase 1: Foundation
Start by taking stock of where your team stands.
Before diving into new tactics, align everyone around what AI SEO means for your brand and how your current approach fits into it.
This stage sets direction and gives your team the confidence to move with purpose.
Here’s what to focus on in the first three months:
Assess current capabilities: Review your team’s strengths across content, technical, and analytical areas. Identify which AI-era skills exist internally and which ones you’ll need to hire for or outsource.
Establish your visibility baseline: Search your most important topics in tools like ChatGPT, Perplexity, and Google AI Overviews. Track if (and how) your brand shows up.
Pick 2-3 priorities to act on: Choose the areas with the clearest opportunity to improve. That might mean tightening content clarity, mapping entities, or aligning off-site mentions.
Run a small pilot: Select a few representative pages and update them based on what you’ve learned. Then recheck whether those updates help your brand appear more often in AI answers.
Document key learnings: Capture what worked and what didn’t in a short internal memo. This becomes the foundation for next quarter’s priorities.
Goal: Build clarity, alignment, and a shared understanding of how AI search changes what your team prioritizes.
By the end of this phase, your team should understand what makes content discoverable in AI search, have a documented baseline to track progress, and have at least one small win that proves the approach works.
Phase 2: Acceleration
Once you’ve built your baseline, it’s time to turn insights into action.
The second phase focuses on building capability and momentum. This involves scaling what worked in your pilot, closing skill gaps, and introducing systems that help your team move faster together.
Here’s what to focus on over the next few months:
Strengthen capability: Run short training sessions to deepen AI SEO understanding across functions. If a skill gap exists, bring in a freelancer, consultant, or new hire to fill it quickly.
Encourage cross-functional collaboration: Bring content, SEO, analytics, product, and brand together under one shared visibility goal. Clarify ownership so responsibilities don’t overlap.
Expand your pilot: Apply what worked from Phase 1 to more pages or campaigns
Build repeatable workflows: Turn early learnings into working systems. Standardize how technical, analytical, and content tasks are executed for AI-driven discovery. Each function should know what “AI-ready” means in its area.
Use shared dashboards: Track AI visibility metrics in one place and review them as a team so everyone sees how their work contributes to results
Run monthly reviews: Check how well your team is adapting to new systems and responsibilities. Identify where people need support, additional training, or outsourced help.
Goal: Build capability, consistency, and accountability across your team’s AI SEO initiatives.
By the end of this phase, your team should operate with clear workflows and defined ownership across technical, analytical, and content areas.
You should also have unified dashboards that let all stakeholders track progress and collaborate without duplicated work.
Phase 3: Scale
This final phase turns AI-first thinking into how your team operates by default.
The goal now is to make the new skills, workflows, and decision habits permanent. This way, your AI SEO capability grows without needing constant resets.
Here’s what to focus on in the next six months:
Integrate what works: Expand the proven approaches from earlier pilots across your full SEO and content programs. Keep the frameworks that consistently improve visibility; drop the ones that don’t.
Solidify roles and ownership: Define who leads AI-related strategy, measurement, and experimentation. Clarify responsibilities so the team stays agile even as you scale.
Strengthen internal training: Turn what your team learned into short onboarding sessions, playbooks, or process docs. This keeps new hires aligned and prevents knowledge loss.
Plan for selective specialization: As your AI SEO programs mature, assign ownership where consistent work is required. That could mean promoting a team member to lead AI visibility reporting, assigning an SEO specialist to oversee off-site signals, or partnering long-term with a proven external expert.
Create leadership visibility: Share quarterly reports on AI-driven results and learnings with senior stakeholders. This keeps support (and budgets) growing with your progress.
Goal: Make AI-first execution routine and scalable across your team.
By the end of this phase, your team should operate with defined roles and responsibilities. You should have internal systems for training, reporting, and process consistency.
Leadership should have visibility into AI performance outcomes so the team treats AI SEO as an integrated function, not an experiment.
Measuring AI SEO Team Success
You can measure your AI SEO team’s success by tracking how often your brand appears in AI-powered answers.
Here are important AI SEO metrics to track:
Citation frequency: How often AI platforms cite your content as a source
Brand mention rate: How often your brand appears in AI responses
Platform coverage: Which AI platforms reference you (ChatGPT, Perplexity, Google AI Overviews, etc.)
Sentiment: Whether those mentions align with your brand positioning
It shows your AI Visibility Score and how many times your brand is mentioned across different AI platforms.
It also shows which prompts your brand appears for, revealing which topics your team’s content strategy is successfully targeting.
In your Brand Performance report, you can compare your brand’s visibility against multiple competitors.
The report includes insights like your Share of Voice (percentage of mentions compared to competitors) and sentiment analysis. This tells you whether AI platforms present your brand positively or negatively.
For larger organizations, Semrush offers Enterprise AIO, with team collaboration features and advanced analytics.
Specifically, your AI Visibility Score is a good overall indicator of your AI SEO team’s performance.
If it has improved over 3-12 months, it means your team is executing well. The skills are translating into real visibility.
If results aren’t showing after two quarters, revisit your priorities. You might be focusing on the wrong skills first or need to adjust your build/buy/borrow mix.
Pro tip: When you start building your team’s AI SEO skills, benchmark your brand’s AI Visibility Score alongside five competitors.
After 3-12 months, compare growth rates, not just final scores.
Your score might increase from 30 to 40 (+10 points). But if competitors jumped from 40 to 60 (+20 points), not only are they more visible — they’re also outpacing you.
Track relative growth to understand your true competitive position.
Get a Custom AI SEO Team Plan in 20-30 Minutes
AI SEO is built on traditional SEO. But there are more layers to it.
Your SEO team needs updated systems and upgraded skills so your brand gets mentioned (and your website cited) in AI search results.
We created the free AI SEO Team Building Assistant to turn everything you just read into a custom action plan for your team.
Download the file, upload it into your AI platform of choice (Claude, ChatGPT, Gemini), and follow the conversation.
This is an interactive session that adapts to your specific team, budget, and constraints. It’s not just a cookie-cutter report after a basic prompt.
It takes around 20 minutes to work through (but you should take your time with it). At the end, you’ll walk away with a complete implementation plan.
Here’s an example of the output, starting with the one-page plan:
You’ll also get a “Skills Ownership Map” showing which team member owns which skill. And which skills to build, borrow, or buy.
Plus a Phased Roadmap, KPI Tracking Framework, Leadership Brief, and 30-day checklist.
Everything is tailored to the specific inputs you provide in the interactive conversation.
Here are some tips for getting the most out of this assistant:
Block 30 uninterrupted minutes so you can really engage with the conversation
Have your current team structure in mind
Be specific in your answers (vague input = generic output)
Be honest about constraints (like budget, time, and capabilities)
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-12 17:58:082025-12-12 17:58:08How to Build an AI-Ready SEO Team: A Complete Guide
Word count is not a ranking factor in itself, but it still plays a significant role in SEO. A minimum number of words helps search engines understand your topic, helps users understand your message, and supports content quality and relevance. The right length for your content depends on search intent, topic depth, competition, and purpose. In this guide, you will learn why word count matters, when length helps or hurts, and how to decide the right length for every page you publish.
Aim for over 300 words for posts and 200 words for product descriptions to enhance SEO and user experience.
Word count helps Google understand context and relevance, though it is not a direct ranking factor.
Longer content provides opportunities for the inclusion of keyphrases, synonyms, and internal links, thus supporting SEO.
Prioritize quality and clarity over simply hitting a word count; irrelevant filler can damage user experience.
Always align your content length with user intent and ensure it adds real value to readers.
What does word count mean for SEO?
Word count refers to the total number of words on a page, including headings, body text, and lists. In SEO, word count is often used as a rough indicator of the amount of information a page contains about a topic. It is not a quality signal by itself, but it strongly influences how much context, explanation, and clarity a page can provide.
Search engines aim to understand what a page is about and whether it satisfies the user’s search intent. A page with sufficient text provides both readers and search engines with the signals they need to interpret meaning, relevance, and usefulness. When word count reflects real depth and not just filler, it supports SEO. If it turns into padding, it works against you. That’s not all, though; in fact, longer articles contribute to SEO in several ways.
Longer content will naturally contain your keyphrase more often. This also gives you more opportunities to use synonyms and related keyphrases, too. Additionally, longer content enables you to utilize more headings, links, and images. These elements help support your keyphrase and enhance how well your page aligns with user intent.
Longer text can also help you rank long-tail variants of your keyphrase. That’s because you have more opportunities to address various topics in a lengthy text. What’s more, if you do some clever internal linking, you’ll drive more organic traffic to your site.
Why very short content often struggles
Pages with extremely low word counts often fail to perform well in search results. This is usually not because they are short, but because they lack sufficient context, depth, and usefulness. Very short pages often leave important questions unanswered. They also provide little supporting explanation and struggle to show expertise and build trust.
From a user perspective, thin content rarely feels complete. From a search engine perspective, it provides fewer clues about relevance and topic coverage. This combination makes it harder for very short pages to compete in most informational and commercial search results. Thin content also weakens your overall site quality signals, which can affect more than just one URL.
Minimum word count guidelines
Minimum word counts exist to help prevent thin content, not to guarantee rankings. As general thresholds:
Regular posts and pages typically require a minimum of 300 words
Product descriptions typically require a minimum of 200 words
Cornerstone content typically requires a minimum of 900 words
These numbers act as a quality floor. You can go above them when a topic requires more explanation, and you can sometimes go below them when the intent is extremely narrow. What matters is whether the page truly fulfills its purpose.
What does Yoast SEO check when it comes to text length?
Yoast SEO checks the length of your content as part of the SEO analysis. You can find this check in the SEO tab of the Yoast SEO meta box or in the Yoast SEO sidebar while you are editing a page. It simply calculates how many words you have added and evaluates whether that amount is likely to be sufficient to support your SEO goals. The same check is also available in the Yoast SEO for Shopify app.
Every page on your site needs to contain a certain number of words to be helpful for your site visitors and for Google. The minimum length of your text depends on the type of page. Taxonomy pages, or collections if you use Shopify, usually require less content than blog posts, while cornerstone content is often your most important content and therefore needs to contain a significant number of words.
How the Yoast SEO text length check works
This length check exists to help you avoid publishing pages that are too thin to be useful. A page with too few words often lacks context, misses important details, and struggles to demonstrate relevance or expertise. By flagging very short pages, Yoast SEO helps you improve the overall quality of your content.
The text length check in Yoast SEO
It is essential to note that this check serves as a guideline only and does not guarantee rankings. Adding more words alone will not make a page rank. The goal is to ensure that your page contains sufficient, meaningful content to explain the topic properly, align with user intent, and enhance overall content quality.
In the table below, you can see how Yoast SEO assesses the different types of pages on your site. If a page contains fewer than the advised minimum number of words, you will see a red traffic light in the Yoast SEO analysis. When you meet or exceed the minimum word count, you will receive a green traffic light.
Word count assessment by page type
Page type
Minimum advised word count
Post or page
More than 300 words
Cornerstone post or page
More than 900 words
Taxonomy description
More than 30 words
Product description
More than 200 words
Cornerstone product description
More than 400 words
Product short description
Between 20 and 50 words
Content depth vs content length
One of the most common SEO mistakes is confusing length with depth. Content length is the number of words you use. Content depth refers to the thoroughness with which you cover the subject.
Depth means that your content answers the main question clearly and addresses relevant subtopics. It also anticipates follow-up questions and provides enough context for users to understand what they are reading. A page can achieve strong depth with a few hundred words for simple topics, while complex subjects may require far more.
Search engines are increasingly evaluating whether a page demonstrates genuine understanding rather than superficial keyword usage. That understanding comes from depth, not from word count alone. This is also where concepts like E-E-A-T become important.
How user intent determines ideal length
User intent is the foundation of every word count decision. Once you understand why someone is searching, determining the appropriate length becomes much easier.
Informational searches usually need more explanation, context, and structure. Navigational searches often need only a few words to guide users to the right place. Transactional searches prioritize clarity, trust, and persuasion over lengthy educational content.
When length matches intent, users feel understood. If it does not, they struggle to find what they need. They can also feel overwhelmed by unnecessary information. Our guide on analyzing search intent explains how to align your content with what users actually want.
Cornerstone content and long-form pages
Cornerstone content represents the most important, comprehensive pages on your site. These articles define your expertise around core themes and often serve as hubs for related content through internal linking.
Because of their role, cornerstone articles are naturally longer and more detailed. They typically cover a broad topic comprehensively, address multiple subtopics, and provide a clear structure for both readers and search engines. While 900 words may be a starting point, many strong cornerstone pages grow far beyond that. This happens when the subject matter demands more detail.
When building cornerstone content, ensure that you also mark it correctly in your site structure and internal linking strategy. Our guide on how to create cornerstone content walks you through this step-by-step.
How to decide the right length for your page
Instead of starting with a word target, start with a set of questions. What is the main intent behind this page? What does the user need to know to feel satisfied? What do the top-ranking results already explain? What additional value can you realistically add?
Outlining your content before writing makes this process easier. It also helps you stay focused while you write. When each section has a clear purpose, the final word count becomes the natural result of good coverage rather than an arbitrary goal.
Word count for product pages
Product pages require a careful balance between information and usability. Insufficient content can erode trust and hinder visibility in search results. Too much content can distract users from taking action.
A strong product page clearly explains what the product is, what it does, who it is for, and why it is worth buying. For many products, a few hundred words of clear copy is enough. More complex or high-consideration products often require more detailed explanations. This helps remove uncertainty and build confidence.
Here, clarity matters far more than hitting any specific word target. Good product pages also benefit from solid internal linking and structured data, which are covered in our guide to site structure for SEO.
Word count for blog posts
Blog posts vary widely in length because they serve a range of purposes. Some posts aim to provide a concise answer to a specific question. Others aim to explore a topic in depth and become long-term reference material.
Shorter blog posts can perform well when they are tightly focused and match a simple query. Longer blog posts often perform well for broader or more competitive topics because they allow you to explore nuances, include examples, and cover related questions that users frequently ask.
A long blog post should never feel long. When structure and readability are handled well, even detailed articles remain easy to read. If you want to improve how readable your articles are, see our article on how to improve your readability score.
Word count for landing pages
Landing pages exist to convert, not to provide in-depth education. Their success depends on whether they clearly communicate value, build trust, and guide users toward a single, actionable outcome.
Some landing pages convert best with only a few hundred words. Others need significantly more space to overcome objections and establish credibility. The right length is determined by how much explanation your audience needs before committing.
Testing real user behavior through analytics and A/B testing is the only reliable way to determine the optimal length for landing pages.
How competition affects word count
Search results show what Google already considers competitive for a query. If the top-ranking pages are detailed and comprehensive, users likely expect that level of depth. If the top results are short and direct, that usually signals simpler intent.
Before deciding on your own content length, take time to study the pages that already rank. Look at their structure, coverage, and clarity. Your goal is not to match their word count, but to match or exceed their usefulness.
This process is closely connected to keyword research and SERP analysis. If you need a refresher, our guide on keyword research covers this topic in detail.
Why readability matters more than raw length
Length only helps when people can actually read and understand the content. Long pages fail when they are filled with dense paragraphs, unclear structure, or overly complex language.
Strong readability stems from using short, clear sentences and maintaining a logical flow between paragraphs. It also depends on well-placed headings and simple vocabulary. Good structure makes even long content feel approachable and encourages users to keep reading.
Readability also supports accessibility and user experience. Both of these indirectly influence SEO performance. That is why readability is a core part of how Yoast SEO evaluates content quality.
Internal linking and topical coverage
Word count influences how much topical ground you can cover and how naturally you can include internal links. Internal links help search engines understand your site’s structure and enable users to discover related content.
Longer, in-depth pages naturally create more opportunities for internal links that are meaningful. This is because they touch on more aspects of a topic. Short pages often limit those opportunities. Strong internal linking enhances topical authority and improves the performance of cornerstone content.
If you want to improve your internal linking strategy, you can start with our guide to internal linking for SEO.
Common mistakes with word count
One common mistake is writing only to hit a number. This often leads to repetition and filler that reduce clarity and trust. Another mistake is publishing large amounts of thin content at scale. This can weaken the overall quality signal of a site.
Ignoring user intent is equally damaging. A very long article for a simple query can frustrate users just as much as a very short article for a complex topic. Finally, many sites overlook updating older thin pages as topics evolve and user expectations shift.
Regular content audits help prevent this problem and keep your site aligned with what users and search engines expect.
Conclusion on word count and SEO
Word count can influence how your posts and pages perform, but it should never come at the expense of quality. Writing more words only helps when those words improve clarity, structure, and usefulness. If you stretch your text just to reach a number, you risk making your content harder to read and less helpful for your visitors.
Focus on writing readable, well-structured content that genuinely answers the user’s question. Use headings to guide readers, keep paragraphs clear and concise, and make sure every section serves a clear purpose. That is what helps users engage with your content and what search engines aim to reward.
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You’re investing in ads and other marketing strategies, but have you ever stopped to think about the data you’re using to inform those investments? For many companies, the biggest blind spot is tracking. Hidden misfires are skewing channel reporting and attribution, ultimately throwing off your marketing decisions.
At NP Digital, we’ve helped hundreds of clients uncover recurring patterns of tracking failure. Today, we’re sharing the most common issues we see and exactly how you can fix them. No fluff. Just real problems, real fixes, and proven next steps.
Key Takeaways
Attribution: Attribution bias is mitigated by using a shared taxonomy across data sources and maintaining clean first-party data.
GA4: Discrepancies around revenue and event tracking with business systems are solved by integrating GA4 data with those business systems.
Consent Management: Consent misconfigurations can lead to legal risk and lost data when CMPs are not mapped correctly to tag categories in the tag manager.
Cross-device: Use customer IDs to unify fragmented cross-device journeys.
Campaign Tracking: Custom setups need governance, so be sure to standardize campaign tracking structures, audit tags regularly, and align dashboards across marketing channels.
The Impact of Bad Data Tracking
Poor data tracking can be dangerous because it has the potential to distort every decision downstream. If your tags misfire, if a user doesn’t opt in and your scripts still run, or if your UTM query parameter structure breaks mid-campaign, you won’t know it until the numbers don’t add up. And by then, the damage is done.
We’ve seen firsthand how these silent issues erode marketing performance. The root causes usually fall into a few key categories:
Incomplete or incorrect tracking setups
Tracking that isn’t validated regularly
Misaligned naming conventions or taxonomies
And what happens when those issues go undetected?
Data gaps that make campaign comparisons impossible
Attribution errors that over-credit paid and undercount organic and vice-versa
Privacy violations if tags fire before consent, creating legal risk
Accurate tracking is the foundation of good marketing. And when it’s off, your strategy is too.
The Tracking Issues We See With Clients
Website tracking issues come in all shapes and sizes, but the same trends seem to emerge over the years of our experience working with clients. Across industries and platforms, we’ve found five tracking challenges that consistently disrupt clean data:
Broken or biased attribution
GA4 discrepancies.
Vendors restrict audience splits or don’t provide raw data
Algorithms self-optimize in ways that obscure true lift
Privacy-driven consent issues
Fragmented cross-platform journeys
Custom setups without a scalable structure
These issues don’t just mess with reporting, they impact performance and decision-making. In the next few sections, we’ll break down the causes of each issue and the solutions we provide to our clients.
Incrementality Measurement & Attribution Bias
Clients come to us with concerns about the accuracy of their reporting and questions on how they can determine what’s working/not working using their web analytics data. Once we dig into the attribution model, we realize it’s only telling half the story.
Attribution bias occurs when platforms over-credit or under-credit paid clicks and under or over-count the earlier part of the customer journey. Skewing the data this way creates inflated ROI on paid channels, while undervaluing organic search or even direct traffic.
It also leads to budget decisions based on faulty data. In either case, decisions made on data that consider attribution in a silo are faulty ones for most brands .Even with incrementality testing, that in theory controls for attribution bias, there can be issues.
Savings can be attributed to fixing attribution:
What we recommend:
Use a cross-platform testing platform that lets you build holdouts and unify taxonomy across campaigns.
Design holdouts that abide to allowed audience splits.
Leverage raw ad platform data mapped to a business, meaningful taxonomy, and business-sourced total conversions data to model incrementality.
When analyzing results, consider factors that might skew the measurement (e.g. self-optimizing platforms) and how that might change the decisions you make based on the results before you run the test, not after.
Run ongoing incrementality tests, not one-and-done experiments.
Map paid and organic together when evaluating top-of-funnel performance.
Incrementality doesn’t have to be a guessing game, but you need the right framework in place to get real answers.
GA4 Data Reliability & Integration
Since the switch to GA4, we’ve seen a surge in tracking headaches. It’s not that GA4 is broken, it’s that many teams rely on it to reconcile platform data and drive reporting dashboards. But GA4 doesn’t always sync cleanly with everything else.
Here’s what we’ve seen go wrong:
GA4 data lags behind real-time performance, which delays optimization
Revenue in GA4 doesn’t match backend systems, causing reporting conflicts
A/B test data often doesn’t align with GA4 sessions or events
Key events are misconfigured or underreported due to GA4’s stricter event model
How we help clients fix this:
Integrate GA4 with other platforms via a Customer Data Platform (CDP) to unify user-level data
Create source-of-truth dashboards that include backend data, not just GA4
Align testing platforms with GA4 event structure to ensure clean comparisons
GA4 can be a powerful part of your analytics stack, but only if it’s connected to everything else.
Consent Management & Privacy Compliance
Marketing teams need to prioritize tracking and consent management because tracking issues can occasionally turn into legal issues. Privacy regulations like GDPR and CPRA are becoming stricter, and many businesses aren’t ready. We’ve seen major data loss and even risk exposure due to simple missteps in consent setup.
Here’s what typically goes wrong:
Consent Management Platforms (CMPs) fire too late or not at all
Tags run before consent is granted, leading to compliance risks
Cookie categories aren’t mapped correctly in GTM, causing incorrect cookies to fire
Cookie deprecation isn’t planned for, so key audiences can disappear because steps haven’t been taken to solve for lost cookie data
These gaps could mean lost data and legal trouble.
How we help:
We run audits using tools like ObservePoint to check tag behavior against consent status
We configure CMPs (like OneTrust) to block tags until users opt in, mapped by cookie category
We support clients with server-side tracking and cookieless solutions to maintain data flow
You can’t afford to guess when it comes to consent. A single misfire can cost you visibility and trust.
Cross-Platform & Funnel Visibility
Even with great tracking on individual platforms, we still see clients struggle with stitching it all together. In our experience, teams often struggle to connect the dots between a user’s first ad exposure and their final conversion, especially across devices, platforms, and channels.
Common problems include:
No consistent customer ID across tools
Offline or backend actions (like CRM updates or sales calls) not tied to digital campaigns
Metrics that mean different things across platforms (e.g., “conversions” in Facebook vs. Google Ads)
The result is fragmented customer journey tracking and incomplete funnel visibility.
Here’s how we address it:
Implement first-party data strategies that collect and unify customer IDs
Use platforms like Segment or Tealium to connect CRM and analytics data
Build funnel dashboards that reflect the full customer path, not just last-click attribution
Without complete visibility, optimization becomes a matter of guesswork. Clean data across platforms turns your funnel from a black box into a roadmap.
Custom Tracking & Tagging Infrastructure
Every client wants data tailored to their business, but too often, custom tracking setups become unmanageable over time. We’ve seen teams inherit messy GA4 configurations, inconsistent UTM naming conventions, and dashboards that pull data from five sources with little to no alignment.
That makes auditing a nightmare and decision-making unreliable.
Common breakdowns we’ve seen:
Event tracking is implemented manually, inconsistently, or without clear documentation
Tools like Claravine or Funnel.io are underused or misconfigured
Data (SEO, paid media, etc.) and backend teams all report on different numbers
How we fix it:
Run full tag audits to spot inconsistencies or redundancies
Standardize UTM frameworks and naming conventions across channels
Set up integrated dashboards that map channel and revenue data in one view
Clients need a more complex measurement solution to accommodate today’s users. The modern customer is more mature and selective. They’re doing more research on who you are as a brand, across channels, before they convert. Teams are doing a great job of implementing multiple channels to bring these customers into the fold, but you need to implement a unified solution to make the most of the data they provide.
Tracking Issues in 2025 vs 2024
Tracking in 2025 looks very different from where we were just a year ago.
Last year, the biggest issues were setup-related: getting GA4 live, consistently tagging campaigns, and stitching data together across ad platforms. Clients were exploring tools and figuring out where things were breaking.
This year, the challenges have matured. Now it’s about optimizing what’s in place, shifting from basic implementation to smarter, scalable solutions.
What’s changed:
Tagging stability has improved, but the pressure is on to prove ROI with less data
Consent compliance and cookie deprecation are non-negotiable, not “nice to haves”
Incrementality testing and attribution refinement are top priorities
Teams are pushing beyond dashboards to revenue-backed insights
New platforms (like ArtsAI and OptiMine) are being evaluated with deeper scrutiny
The takeaway: In 2024, it was about getting things up and running. In 2025, it’s about whether your setup can scale, adapt, and stay compliant.
How You Can Start Improving Your Data Tracking Today
If you’re running into tracking issues or even suspect something’s off, don’t wait for a reporting crisis to assess the situation. You’ll save yourself time and headaches by looking into the issue now.
Here’s where we recommend starting:
Run a Full Audit: Use tools like ObservePoint to validate which tags are firing, where, and under what conditions. Focus on consent compliance, event coverage, and load order.
Standardize UTM and Taxonomy: Create a documented framework across your paid, organic, and internal teams. Inconsistent naming kills cross-platform clarity.
Reconcile GA4 With Backend Data: Build a dashboard that includes both GA4 and revenue data from your CRM or database. That’s your source of truth. Don’t only rely on platform-reported numbers.
Fix Consent Setup: Audit your consent management platform (CMP) setup and make sure no tags fire before consent. Use active group triggers (like in OneTrust) mapped to tag categories.
Rethink Attribution: Move beyond last click. Explore incrementality testing or multi-touch attribution models that actually reflect how your audience buys.
If your tracking setup isn’t solid, your data and every decision built on it is at risk. From attribution errors to consent gaps, we’ve seen how small misfires create major problems. But the good news is that most of these issues are fixable with the right audits and tools in place.
Whether you’re optimizing GA4, cleaning up cross-platform reporting, or getting your consent setup compliant, now’s the time to level up. Better data means better marketing, and it starts with tracking that works.
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Headings structure your content for both readers and search engines. They help users scan a page, understand its content, and quickly locate the information they need. Search engines and AI systems use headings to interpret the topic and structure of your content. By using one clear H1, supported by well-written H2 and H3 headings, you can improve readability, accessibility, and SEO simultaneously.
Headings are the titles and sub-titles used to structure your content. In HTML, headings range from H1 to H6. These tags inform browsers, search engines, and assistive technologies about the organization of your content.
On a typical page, the H1 is used for the main topic. H2 headings divide the text into main sections. H3 headings divide those sections further. This hierarchy creates a logical outline of your page, similar to the table of contents of a book.
Without headings, your content becomes difficult to scan. With clear headings, readers can immediately see what your page is about and which sections are relevant to them.
Why are headings important for SEO?
Headings help search engines understand what your content is about and how different topics on the page relate to each other. They provide structure, context, and signals about the importance of different sections.
Your H1 usually tells search engines what the main topic of your page is. Your H2 and H3 headings support that topic by introducing related subtopics. When this structure is clear and logical, it becomes easier for search engines to interpret your content correctly.
Headings also support semantic SEO. Rather than focusing on one keyword, search engines now assess topical relevance and context. Well-written headings naturally contain related terms and concepts that reinforce the overall topic of the page. This approach works best when combined with thorough keyword research and in-depth content. You can read more about this in our guides to keyword research and high-quality content.
Headings also play a role in how content is interpreted by AI driven search systems. Clean structure makes it easier for these systems to extract accurate answers from your pages.
Why are headings important for readers?
Most visitors do not read every word of a page. They scan first. They look at the title, skim the subheadings, and only then decide which parts to read in detail. Headings support this natural reading behavior.
Clear headings improve readability by breaking long texts into manageable sections. They help readers understand what each part of the article is about before they start reading it. This lowers the effort required to engage with your content and keeps people on the page longer.
Readability is a key quality signal. If you want to go deeper into this topic, our readability guide explains how structure, sentence length, and headings work together to create content that is easy to read.
How to use headings correctly
Using headings correctly means following a logical hierarchy and writing them with the reader in mind. Each page should have one clear H1 that describes the main topic. This is usually your page title. Below that, use H2 headings for your main sections. If a section becomes lengthy or complex, use H3 headings to further divide it.
Do not skip heading levels. An H3 should always follow an H2, not jump directly from an H1. This keeps the structure logical for both users and machines.
Your headings should describe what the section is about. Avoid vague labels such as “Introduction” or “More information.” Instead, write headings that clearly explain what the reader will learn in that section.
How many H1 headings should you use?
In most cases, you should use one H1 per page. The H1 defines the main topic of the page and helps both users and search engines understand what the page is about at a glance.
Although modern HTML allows more than one H1, using multiple H1s often creates confusion about the primary focus of the page. For consistency and clarity, one H1 is still the best practice for most websites.
Your H1 should be written naturally and should not be stuffed with keywords. It should read like a real headline written for humans. If you need help with this, Yoast SEO can balance clarity and optimization in headlines and titles.
How to use H2 and H3 headings
H2 headings divide your article into its main sections. Each H2 should cover one important aspect of your topic. When someone scans only your H2 headings, they should still be able to understand the overall structure and purpose of your article.
H3 headings are used within an H2 section to break it down into smaller parts. They are useful when you explain steps, compare options, or cover several closely related points within one larger section.
You should not use H3 headings unless they add clarity. Headings are meant to support the reader, not to decorate the page.
Common mistakes when using headings
A common mistake is using headings only for visual styling. Headings are not just larger or bolder text. They define the structure of your content in the HTML. Choosing a heading level solely based on its appearance can compromise the semantic structure of your page.
Another frequent issue is skipping heading levels, such as jumping directly from H2 to H4. This disrupts the logical structure of the page and creates issues for screen readers and search engines.
Repeating the same heading text in multiple places is also a problem. Each heading should be unique so that users and search engines can clearly distinguish between sections.
Keyword stuffing is another mistake. Headings should sound natural. If they read like a list of search terms, they reduce trust and harm readability. Clear, descriptive language always works better.
Headings and accessibility
Headings are essential for accessibility. Screen readers utilize headings to assist users in navigating a page efficiently. With a proper heading structure, visually impaired users can easily navigate from section to section and understand how the content is organized without needing to listen to the entire page.
A clear and logical heading hierarchy improves usability for everyone, not just for users of assistive technology. It is also strongly aligned with how search engines assess page quality.
If accessibility is part of your broader optimization work, it should be considered alongside internal linking and overall site structure. Don’t forget that, in many cases, what’s good for accessibility is also good for SEO!
Yoast SEO uses headings as part of both its SEO analysis and its readability analysis. One of the checks it performs is on your subheading distribution, which looks at how evenly your text is divided into sections with headings. If large blocks of text appear without any subheadings, Yoast will flag this and suggest you add subheadings to improve the readability of that part.
Effective subheading distribution means readers regularly encounter clear signposts that help them navigate the page without feeling overwhelmed by long, uninterrupted paragraphs. See the video below to find out more about the subheading distribution check and the keyphrase in subheadings check in Yoast SEO:
How to get a green traffic light for your subheading distribution
What do you do if you get an orange or red traffic light in the Yoast SEO plugin for your subheading distribution? First of all, and this is quite obvious, don’t forget to use subheadings. You should try to create a subheading for every separate topic in your text. This could be for every paragraph or a couple discussing the same topic.
We suggest that you include a heading above every long paragraph or group of paragraphs that form a thematic unit. The text following a subheading should be 250-350 words.
An example heading structure
Let’s say that we have a blog post about ballet shoes. We’ve chosen “ballet shoes” as our focus keyword and written an article about why we like ballet shoes. Without headings, there’s a risk that we might end up writing a long, rambling piece that is hard to understand. But if we structure things logically using headings, we make it easier to read and help focus our writing.
Here’s what the structure of that post might look like:
H1: Ballet shoes are awesome
H2: Why we think ballet shoes are awesome
H3: They don’t just come in pink!
H3: You can use them for more than just dancing
H3: They might be less expensive than you think
H2: Where should you buy your ballet shoes?
H3: The ten best ballet equipment websites
H3: Our favorite local dancing shops
See how we’ve created a logical structure, using H2 tags to plan sections and H3 tags to cover specific topics? We’ve done the same thing in the post you’re reading right now!
This is an excellent example of how your headings should be structured in a medium-length article. You should use fewer (or more general, high-level) headings for a shorter article. If you want to go into more detail, nothing stops you from using H4 tags to create even ‘lower-level’ sections.
Adding headings
Knowing how to structure is all well and good, but how do you add headings? The best way to explain this is in two of the most popular CMSs: WordPress and Shopify!
Note: The instructions below will walk you through how to add in-text subheadings. Don’t forget to add a post title at the top of the page, too! In Yoast SEO Premium, you’ll get a reminder to do so if the ‘Title’ field is empty. In addition, if you use Yoast SEO Premium, you get various other AI features, like Yoast AI Optimize, that help you do the hard work.
How to add a heading in WordPress
If you’re using WordPress, there are a couple of ways to do this:
Via the editor The easiest way to add headings is through the editor. If you use the block editor, click the + button and select ‘Heading’. Then, you can select which heading (H2, H3, etc.) you want to add.
Selecting a heading type in the block editor of WordPress
If you’re still using the classic editor in WordPress, it’s easy, too. Ensure you’re on the visual tab of the editor and select ‘Heading 2’ or another heading from the dropdown menu.
Change the heading type from the dropdown menu in the classic editor
Using HTML It’s also possible to add headings using HTML. In the classic editor, you will need to make sure you’re on the text tab (or directly in the code) and use heading tags <h1>, <h2>, <h3>, etc., to specify each type of heading. End each heading with a closing tag like </h1>. Like this:
Be sure to select the Text tab in the classic editor in WordPress
You can switch between the visual editor or edit as HTML in the block editor. Click on the three vertical dots in the block toolbar to do that. Then, select the Edit as HTML option. Like this:
You can also edit a post as HTML in the block editor
How to add a heading in Shopify
Adding headings in Shopify is similar to that in WordPress’s classic editor. If you’re in the content editor, you can select a piece of text and select the appropriate heading from the dropdown in the formatting menu item:
Select the text and choose a heading in Shopify
If you prefer to work in HTML, you can select the code sign in the upper right corner of the editor and create headings in HTML as described in the instructions for WordPress above.
Click the code sign to switch to HTML in the Shopify editor
Using your keyphrase in the subheadings
Headings allow you to prominently use your focus keyword (or its synonyms) to clarify what the page is about. By adding your focus keyphrase to your subheadings, you stress its importance. Moreover, if you’re trying to rank for keywords, you must write about them. You’ll probably have difficulty ranking if none of your paragraphs address the main topic.
Still, just like keyphrases, it’s important not to overdo it. Add your keyphrase where it makes sense and leave it out where it doesn’t.
Yoast SEO can help you with the keyphrase in headings assessment
After you insert your keyphrase in Yoast SEO, the keyphrase in subheadings assessment checks whether you’ve used it sufficiently. In Yoast SEO, you’ll get a green traffic light if you use the keywords in 30 to 75% of your subheadings. Please note that we’ll only review your H2 and H3 subheadings. If you have Yoast SEO Premium or if you’re using the Yoast SEO for Shopify app, you can even check your use of synonyms.
A green traffic light for the keyphrase in subheadings assessment in Yoast SEO
How to add your keyphrase in your subheadings
Whether you add your keyphrase to a subheading depends on the paragraph(s) it’s connected to. Every paragraph in your text should tell the reader something about the topic. In addition, your subheadings are nothing more than a very short outline of what you will say in one or more paragraphs. Therefore, adding your keyphrase to one or more subheadings should always be possible. If you’re still struggling to achieve this, ask yourself a couple of questions about the structure of your article.
Does my text discuss the topic described in the keyphrase? If not, should I pick other keywords?
Do my current subheadings accurately describe what I discuss below?
What paragraphs are most closely connected to the topic and the keyphrase?
What questions do these paragraphs answer concerning the topic and the keyphrase?
Most of the time, you’ll find that answering these questions helps you add the keywords to one or more of your subheadings. If you can’t, you should probably reconsider question number one. If that doesn’t solve your problems, consider educating yourself on copywriting and text structure, to get a clearer view of how a good piece is structured. Your keyphrase should be central to the topic. Therefore, you should be able to add the keywords to several subheadings.
Headings in themes
Most themes will use headings as part of their HTML code, but some don’t follow best practices. Almost all themes will automatically use the name of your article in an H1 tag. This is helpful because you don’t need to repeat the post name inside your content.
Unfortunately, some themes use tags incorrectly, in an illogical order (e.g., an H4, then an H2) or use tags messily in sidebars, headers, and footers. This can cause accessibility problems, as the order of your headings may not make sense. Users, search engines, and assistive technologies typically examine the entire page, not just your content area.
If you have a custom theme, you may be able to resolve this issue by adjusting your HTML code. You may need to contact the developers if you’re using an off-the-shelf theme. Either way, you should verify that your headings are consistent across each template type on your website.
Check your blog’s headings
Using headings well is helpful for your users. It increases the chances of people reading your article, improves accessibility, and might even contribute to SEO. So add them to your copy, but make sure you use them correctly!
The document overview is a handy button located in the upper left corner of the WordPress block editor’s content editing screen. This shows an outline of the page you’re editing. If you’ve structured your content well, it should look like this!
If you’re using Shopify or the Classic Editor in WordPress, you can test your published article via the W3 Validator.
Check the heading hierarchy in the WordPress outline feature
Final thoughts
Headings are one of the simplest and most powerful tools you have for improving both readability and SEO. They guide your readers through your content and help search engines understand what each part of your page is about.
Use one clear H1 to define your topic. Use H2s to structure your main ideas. Use H3s where they genuinely improve clarity. Write your headings for people first and let optimization support that goal.
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Today, we are excited to introduce a new feature in the Search Console Performance report: weekly and monthly views.
This new functionality allows you to adjust the time aggregation of any of the performance charts,
helping you smooth out daily changes and focus on the overall trend of traffic to your website.
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Google is rolling out a new Data Manager API that lets you plug first-party data into Google’s AI-powered ad tools with less friction. The goal: stronger measurement, smarter targeting, and better performance without the hassle of managing multiple systems.
Why we care. The Data Manager API helps you get more value from the data you already have by sending reliable first-party data into Google’s AI. This improves your targeting, measurement, and bidding. It also replaces several separate APIs with one easy connection, cutting down on engineering work and getting insights back into your campaigns faster.
About the Data Manager API. It will replace several separate Google platform APIs with one centralized integration point for advertisers, agencies, and developers. It builds on Google’s existing codeless Data Manager tool, which tens of thousands of advertisers already use to activate their first-party data.
You can use it to:
Upload and refresh audience lists.
Send offline conversions to improve measurement.
Improve bidding performance by giving Google AI richer signals.
Partnership push. To speed adoption, Google is launching with integrations from AdSwerve, Customerlabs, Data Hash, Fifty Five, Hightouch, Jellyfish, Lytics, Tealium, Treasure Data, Zapier, and others.
Available today. The API is available starting today across Google Ads, Google Analytics and Display & Video 360, with more product integrations on the way.
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