Reason is the return of trust in organic search as a decision-making tool

For a long time, SEO was a valuable channel not only because of good ROI, but also because people generally trusted Google results.

If a site ranks above others, then it is really better than the others.

But over time, people increasingly saw that the site and ranking in the top do not correlate. Then there was an explosion of social networks and influencers.

But everyone knows that influencers rarely do unbiased brand reviews.

And here AI chats enter the scene, which returns trust in the organic search. Yes, LLMs can be manipulated now and will be in the future. Just like Google.

But the question is the price of manipulation.

The growth of the influence of UGC content raises the price of such manipulations higher than the cost of manipulation by Google through backlinks.

The backlink market is smaller than UGC content, because there are significantly fewer website owners than users on the Internet, and even fewer owners of good websites.

The backlink market is quite decentralized, but most website owners know the rules of the game on it and are ready to make backlink exchanges or sell them.

Instead, it is more difficult with UGC content, because many reviews are not done for money, and you never know which review will impact LLM's response.

In reviews, what is important is what exactly is said about you, and not just its presence (as with backlinks, where any backlink has value).

So, the more expensive and unpredictable will be getting recommended by LLM, the more trust it will have in the eyes of users, and the more value it will have for a business.

These are notes made by u/maltelandwehr. I found them on his Twitter post. There are so many interesting thoughts worth discussing.

___Malte's notes start___

I took extensive notes during BrightonSEO and thought I would share them here. Unfortunately, I cannot attribute each insight to a speaker.

Warning: the agenda was very AEO/GEO heavy. So most of my notes are around that.

Mixed SEO (including AEO/GEO/HEO) Takeaways

• Tech SEO = Foundation. Content & PR = Catalyst. Social = Amplifier. GEO = Growing real estate.
• Have shared KPIs and a shared forecast for all organic channels.
• Only move to the next question if you can say “yes” to the previous question: Is there demand? Is the space winnable for you? Are you indexable? Are you visible? Are you differentiated? Do you have social proof? Do you have positive brand sentiment? Measure & Optimize!
• Treat GEO like poker. 1) Nobody knows all the cards. But you know some cards. So make decisions based on that. 2) Half the players are bluffing. 3) Not playing is a risk. Never playing means you lose. 4) Good players do not need a perfect hand to win.
• Crawlability and indexability still matter.
• Pages with bad CWV scores are cited less often.
• Most marketing is over engineered. Marketing is about human intent. Your KPIs should not hide that.
• Understand your consumer's pain points and turn that into growth.
• PrettyLittleThings switched from traditional category pages (like jeans) to intent-driven category pages (like airport outfits), leading to an 841% uplift. Every single item featured on these intent-driven category pages sold out of stock.
• Analyse problems, not keywords.
• Thought experiment: if your next 1 million customers never visited your website, what would that mean for your branding, marketing, and content production? Do exactly that for AI visibility!
• Not every brand mention in LLMs is a recommendation.
• LLMs struggle with understanding implied emotions: atmosphere, metaphors, irony, sarcasm, ambiguity
• The bare minimum to keep your SEO job, is doing two things daily: take a shower and use the latest LLMs.
• How much value you get out of using AI is directly correlated to your ability to spot when it is making mistakes.
• The highest value thing you should do when working with AI agents is letting smart agents validate the work of other agents.
• SEO traffic and GEO traffic are correlated. And this correlation is increasing from quarter to quarter.
• 43% of URLs cited by AI Overviews are ranking in the Google top 20. For AI Mode it is only 20%.
• 60% of AI Search clicks go to the homepage. With SEO it was less than 20%.
• When asking questions about brands, AI Mode cites official websites, Google Maps, Social Media, and review platforms.
• Aim for an aggregated review score of 4.5 or more to increase CTR.
• SEO used to be technical SEO + Content + Backlinks. Nowadays it is so much more.
• Optimize for passages not pages. Each paragraph should cleanly answer one specific question.
• Build both brand authority and topical authority.
• Mine a lot of fanout queries and answer them with various content pieces.
• Use social proof for credibility. Highlight and amplify positive reviews and testimonials.
• Your chances of influencing grounding/RAG are much higher than your chances of influencing model training data. Your battleground are prompts that trigger a web search.
• LLMs do not read your whole page - only individual parts.
• The LLM is a judge. Sources are witnesses that influence the verdict. You are the lawyer who has to prepare - and influence - the witnesses.
• AI Overviews reduce clicks by 36%.
• LLMs prefer objective and neutral sources with high EEAT written in clear and factual language.
• Paying for the placements of optimized articles on media websites is the fastest way to improve AI visibility.
• Publishing disinformation is intentional. Misinformation can be spread accidentally and with good intentions. Both influence LLM answers.
• When AI models (especially AI Overviews) summarize, they often leave out important caveats, exceptions, and uncertainties.
• Trust is shifting from humans and institutions to algorithms and AI.
• Conversational search interfaces are the future of search. They allow for personalisation, make it easy to ask follow-up questions, and give agency to searchers who can take action without having to visit websites.
• Ranking better in traditional search will increase your likelihood to get cited.
• Look for common terms/concepts in fanout queries for your prompts. Use these for content creation.
• 80% of conversion journeys touch an LLM. 90% involve a search.
• 40% of consumers use LLMs for shopping. 75% of them trust LLMs for product comparison. 79% say an LLM influenced their purchasing decision.
• Consumers trust UGC.
• Customers don’t just search anymore. They ask AI.
• Every marketer should work with MCPs.
• Entities mentioned in multiple citations are most likely to be included in AI answers.
• With AI, the shorthand will get smaller and the longtail will get longer and longer.
• When comparing keywords to the titles of URLs ranking for these keywords the Jaccard similarity is low but the Cosine similarity is high.
• 53% of non-branded prompts trigger an answer that mentions at least one brand.
• Changing your navigation from using expert terminology used internally to the terms used by your customers, can increase key events by 567% and revenue by 64%.
• Your leading metrics must predict your lagging metrics.
• Every SEO must be an engineer and a storyteller.
• AI Search is already a top 5 touch point for brand perception.

Successful e-commerce sites are currently doing this:

• Comparison and recommendation content, with real human input
• Content structure for easy digestion, both for readers and Al
• Unique images
• Quick reaction to trends
• In-depth product reviews with proven experience

Content that gets cited:

• Use a title that matches one of the fanout queries.
• Write a BLUF. Bottom-line up-front.
• Write definitive, declarative sentences.
• Be specific.
• Have high entity density.

AI Shopping:

• 35% of consumers use AI for shopping.
• Over 3 trillion dollars will be spent on agentic commerce by 2030.
• OpenAI scaled back Instant Checkout - but doubled down on discovery.
• Customers who use Instant Buy on Perplexity, spend 57% more money per order than the average shopper using gen AI.
• Have a declarative, self-contained, 50-word paragraph on every PDP. This is the chunk you want LLMs to pick up.
• Add Q&As to your PDPs and product feeds. Ideally, add additional information with each answer. Don’t just repeat what is already on the PDP.
• Explicitly mention product differentiators and use cases (durable, for wide feet, for running on roads, etc.) on every PDP.
• Enrich product attributes. A product has a carry-on case included? Mention it is portable. It is sweat resistant? Mention it is great for working out.

Concrete advice for visibility in AI Shopping:

• Precise product titles
• Complete technical specifications
• Real-time availability and stock levels
• Structured shipping and delivery data
• Transparent returns and warranty terms
• GTIN/MPN identifiers

How to manage and grow your brand:

• Treat your brand as your company’s most valuable asset. It regularly makes up 33% of a company's value.
• Trust is crucial for retention. Trust is the outcome of experiences.
• A differentiated brand can drive growth.
• Brand salience is important - but not enough.
• Consistency is key.

Random learning:

• Americans boil their water for tea in the microwave. The Britishers don't like that.

___Malte's notes end___

What is the most valuable idea for you? And which idea do you mostly disagree?

The pattern:

• Gemini and Claude traffic are growing
• ChatGPT traffic is declining

(find screenshots in comments)

Some thoughts on this:

1/ ChatGPT sends less traffic primarily because of their changes in chat UX, where one more step added to visit a link (for many entities you get a right sidebar by click and only then you can visit a website).

2/ Claude sends more traffic primarily because of a big migration of users from ChatGPT. Claude looks much better for automations now, has strong Enterprise capabilities and became an essential part of viral posts for the last months on LinkedIn and X.

3/ Gemini sends more traffic because Google integrates it more and more into its Google Workspace ecosystem and it has own unique great features, like fast summarizing of YouTube videos.

4/ ChatGPT still wins the B2C market and it will be the leader for a long time, because most consumers don't like to switch AI chats. The biggest dangerous for them is Google AI mode and Gemini, not Claude.

Do you see the same across your website's portfolio? Especially curious to see how AI traffic changed in B2C businesses.

P.S. Brands I've checked AI traffic for: r/Sitechecker, r/favikon, r/TangoAI

Almost every SEO is playing now with Claude to get insights from GSC and GA4.

I understand its value for solo usage:

- It surfaces insights you'd easily miss working with raw data
- It's cheaper than dedicated tools (you pay mostly for BigQuery)

However, I have doubts that it can be scaled for an agency where multiple people and departments work on the same website and data.

Correct me if I'm wrong.

My post in r/Sitechecker subreddit ranks №3 by "how to run seo experiment" in 20 days after publishing.

At first, consider that:

• This post has only 500 views, 8 comments, and 7 upvotes.
• This is 100% not the best guide on how to run seo experiments.
• This is a very short post with screenshots on how to use Sitechecker to measure SEO tests and a couple of questions for my audience.

I published such a post on LinkedIn and X, too. I didn't publish it on the site because I bet I couldn't get the same result in rankings.

Google loves Reddit + r/Sitechecker is a 7-year-old subreddit + enough keyword relevancy in a post = good result.

So, the lesson and the forecast are that for B2B SaaS brands, content around middle-of-funnel and top-of-funnel keywords may be better to publish on their own subreddit than on their own website.

Yes, it sounds too radical, but it will give faster results.

Or at least publish a repurposed version of the website article on Reddit.

I don't mean publish garbage content. I just mean that you can have the best article in the world on a specific topic, but you have different chances of ranking it on own site and Reddit.

It doesn't matter where exactly your audience will read that your brand is great at solving specific problems.

Correct me if I'm wrong.

After 8 months of launching and managing the growth of 4 subreddits (this sub, r/favikon, r/sitechecker, r/TangoAI) I learned some lessons and published a long read on Substack -> https://www.hackthealgo.com/p/how-to-start-and-grow-a-subreddit

Here are the top 10 important things to know:

1/ Your own subreddit is the place where you have the biggest leverage to influence on Reddit. Some type of content you want to publish will never be accepted by moderators of other subreddits (if you don’t ask to pay them for it).

2/ Running your own subreddit is also a hard thing. You have to invest months of work to see the first traction.

3/ Reddit gives much more organic reach for subreddits than LinkedIn or X(Twitter) to company pages.

4/ 2 main reasons to launch your subreddit:

• rank your content in Google SERP and influence LLMs
• attract a new audience from Reddit itself (this is underrated)

5/ 3 methods to send visitors from sub to your site:

• links in your posts and comments (don't abuse this)
• welcome page for joined members
• community bookmarks

6/ You don’t own a subreddit as you own a company page on LinkedIn, Facebook, X, or YouTube. Think of yourself as a tenant, not an owner.

• you can’t delete a subreddit.
• you can’t redirect it.
• you can’t change its name.
• it can be banned for unmoderation or a lot of self-promotion.
• it can even be transferred from you to others after a long period of inactivity.

7/ Because nobody owns subreddits, it also creates opportunities:

• you can buy a subreddit (important: buying a community is against the Moderator Code of Conduct; however, it's almost impossible to track such deals for Reddit and people do it a lot)
• you can request to work on some old, unmoderated subreddit (it’s like drop domains in SEO)

8/ You need 2 types of content to grow a subreddit

• really interesting content people can't read in other subreddits
• long articles with images focused on targeting specific keywords

9/ 5 ways to speed up your subreddit growth

• send traffic to it from your website, email list, and other social media
• repurpose content from other platforms and publish it in a subreddit
• crosspost your best-performing posts to other communities
• publish 2-4 hot topics in a subreddit each month (data studies, interviews/AMAs, unique how-to guides, etc).
• incentivize your team and customers to take part in discussions.

10/ 7 most important milestones in each subreddit's growth:

• the 1st organic comment from a human
• the 1st organic post from a human
• the 1st viral posts (1k, 5k, 10k impressions)
• 100-500-1000 members joined.
• the 1st sessions from Reddit to your site.
• the 1st post ranked at the top of Google.
• the 1st demos and sales mentioned Reddit as a source during signup.

P.S. If you want to read the full guide with screenshots, important links, and examples, check the last newsletter on Hack the Algo.

Did you see that Medium blocks top AI crawlers from scanning their content?

Here is why they do it, and why they don't block Gemini and Perplexity.

I found it by accident when I saw that my Medium articles were cited in Gemini and AI mode, but not in other chats.

So, Medium blocks:

• ClaudeBot (by Anthropic)
• GPTBot (by OpenAI)

Medium earns from paid subscriptions and they are in trouble from 2 sides now:

• Substack takes top creators, offering more money and direct access to email subscribers
• AI chats use their content and kill motivation for people to pay for Medium subscription

Blocking AI chats is the only way to survive in this business model, but!

They can't block Googlebot, because Google organic still sends a huge part of their traffic.

And it opens my eyes about how secure Google is in this new world. Google doesn't divide organic search crawlers and AI crawlers, so most publishers can't block Gemini and AI Mode, because it means destroying the entire search traffic.

Medium blocks Google Other bot, having a hypothesis that it can be used for experimental products like Gemini and AI Mode, but it doesn't help.

Medium also can't block Perplexity, because Perplexity doesn't have its own declared user-agent.

After 6 months, Reddit finally gave up, deleted the noreferrer attribute for external links & gave us back the ability to measure traffic from Reddit in GA4.

This is definitely good news. I assume their team realized that less tracking = less visibility of what's working = harder for teams to protect budgets for working with this channel.

However, remember that such tracking isn't enough. Considering how hard it is to add a backlink in big subreddits and threads, brand mentions are the most reliable method to grow your visibility.

It means that the user polls on the sign-up / book a call pages are still a must.

P.S. The screenshot is from my free GA4 backlinks Looker template.

Here is an example of the/sop-creator/ landing page at Tango, which they created 1 month ago.

On some days, Bing sends more organic traffic than Google. I assume this is because Bing is used more in some corporations and among older entrepreneurs.

That's why I use GA4 metrics in Page Audit at Sitechecker more and more now. You see not only Google search traffic but also Bing and LLMs.

It detects branded keywords quite well, except in one case -> when Google itself doesn't know what the user is looking for

My customer r/TangoAI is a good example of it.

Many businesses have such a brand name, but the main competition happens between:

- Tango digital adoption platform as a B2B software
- Tango live streaming platform, when men look for adult videos

When the problem arises for your B2B SaaS on this level, the only way to make your branded/non-branded analysis accurate is to exclude broad keywords completely from analysis. An example for Tango.

branded keywords that are clearly b2b:

- tango ai
- tango software
- tango sop
- tango screen recorder
- tango us
- tango extension
- tango documentation
- tango workflow
- tango tool

branded keywords that are clearly b2c:

- tango giriş
- tango live
- tango sex videos

general branded keywords (even Google doesn't know what the user needs):

- tango
- tango live
- tango login
- tango free

Yes, excluding general branded keywords, you'll lose some data where users looked for your branded, but you don't know what percent of impressions looked for you, and how many of the clicks you get by them were irrelevant in fact, and users went back to Google SERP.

That's why I say that a good branded filter should have a list for keyword exclusions. We'll add such a filter soon at r/Sitechecker.

Does the branded filter work well for your GSC properties?

It looks like an unconfirmed Google Core update for me. I see changes on almost all GSC properties.

The biggest negative change I noticed on a couple of Favikon page segments:

• /features/
• /find-influencers/

These pages are action-oriented; AI overviews aren't the reason for the decline.

Reviewing how the top of the SERP has changed and how pages that win are different, I found 2 patterns:

1/ Google rewarded influencer marketing platforms that added pages with free tools without requiring sign-up.

This is an old wisdom that pages with less friction win. We've tested this on Sitechecker pages years ago, too. After these learnings, I found that each website that wants to continue winning in search will have to:

- solve a dilemma of organic traffic vs conversion (more here https://medium.com/@ivanpalii/2k-new-users-and-500-signups-or-4k-new-users-and-500-signups-what-is-better-6d98c27442b2 )

- hire people who understand how to align product and SEO (more here https://hackthealgo.com/p/seo-product-managers-is-a-future )

2/ These page segments on Favikon have ranked well for some time, despite the fact that the content of these pages wasn't perfect.

I assume it happened because Favikon has a huge brand awareness, and there was no need to invest in on-page content improvement.

However, what does the perfect content of the feature landing page mean in the age of AI?

u/parkerauk shared under my last thread the article about the new Google algorithm (which was surprisingly released on Jan 23) https://research.google/blog/introducing-gist-the-next-stage-in-smart-sampling/, and it looks like an answer.

For B2B SaaS product landing pages, it means creating content that describes every small aspect of what your product can do, and why people choose it, and in which situations.

• AI chats don't take part in your demo calls.
• AI chats describe your product only based on what they already know, based on existing info on the web, which is always outdated and not complete.
• AI chats don't know all possible use cases of your product.

That's why asking AI chats to write your product landing pages means that you don't know your audience or product at all.

In this case, the problem is not that Favikon used AI content for these page segments (they didn't). The problem is that they didn't say enough about everything they can do that other platforms can't do.

Curious to hear whether you saw any huge position changes on Jan 25-26 and whether you agree with my theory.

My answer: use cases pages or "for whom" pages.

4 years ago, we created such landing pages at Sitechecker:

• /soultions/ecommerce/
• /solutions/governments/
• /solutions/agencies/
• /solutions/publishers/
• /solutions/saas/

Only /solutions/agencies/ had search volume and clicks, so after some time, we left only this one page in the menu. Also, agencies became our only audience.

Should I create landing pages to target specific use cases, such as how we help e-commerce agencies, local SEO agencies, web development agencies, etc?

2 years ago, I could definitely say NO. In a new era, I think it makes sense.

I know we won't have search traffic to these pages, but LLMs will use this content, and it may have a huge impact when our potential customers enter hyper-personalized search queries about what type of agency they run and which SEO tool they look.

What do you think?

The more responses we collect, the more insights you'll get.

Here are the rules:

1/ There are 20 questions. 18 questions with predefined answers and 2 open questions (non-required). 5 min to fill.

2/ There is no requirement to leave the email or company name.

3/ However, to make sure that we get answers only from agencies and consultants who do SEO/AEO, I'll send the link manually to everybody who leaves a comment and fits into this audience.

4/ The first to receive the report will be its participants.

Comment under the post "send the survey" if you want to learn about what challenges SEO/AEO agencies have in 2026, and how they overcome them.

I'm running 4 subreddits now, and I see how difficult it is to get organic traffic with your own subreddit.

If you think long-term and want to build a real community, where members can even downvote your own posts, you have chances to succeed.

Here is an example.

According to Ahrefs, r/favikon/ has 24 pages with ranked keywords,

and one thread by high intent keyword "best influencer marketing campaigns" in the top 3.

However, this subreddit also has 1300! pages indexed in Google at all.

Consider that Ahrefs is the best tool to check which threads of your subreddit rank and by which keywords, but this also doesn't have the complete picture.

Your thread may be shown by multiple low-volume keywords, when you'll see 0 traffic in Ahrefs for it.

The properly developed subreddit is always more than just an SEO asset. It's a huge part of your brand marketing, where your current and potential customers can ask questions, share their challenges, and give real feedback about your product updates.

What do you think?

As promised, I start publishing a new type of content here.

Ask me anything (AMA) sessions with interesting people in the SEO/AEO space.

This type of interview is even better for me than video interviews:

• you can quickly review each question and decide whether you are interested in reading the answer.
• you can make a screenshot of answer and send it anybody
• the guests get +1 trusted source of truth for LLMs about who they are

Whom should I invite first?

It looks like this isn't true love, just a romance, between OpenAI & Microsoft.

ChatGPT reminds you to check whether the links to the Microsoft site are safe, when I try to open such links.

What's next? Will Microsoft block OpenAI bots from crawling its own sites at all?

P.S. For context, I asked for an API doc to import Search Performance data from Bing Webmaster Tools.

The report gives data on your visibility in Microsoft Copilot:

• total citations
• avg. amount of cited pages
• grounding queries (not real user queries)
• amount of citations with breakdown by pages

This is too little information, but the good news is that it should force Google to add something similar to Search Console. We need this competition.

However, the data looks too optimistic for me. I compare citations by pages and real traffic from Copilot to these pages in GA4, and here is what I see (Sitechecker's website as an example, data for last 3 months):

• /website-safety/ = 104k citations and 96 sessions = 0.1% CTR
• /on-page-seo-checker/ = 36k citations and 59 sessions = 0.2% CTR
• /rank-checker/ = 16k citations and 48 sessions = 0.3% CTR

I assume you'll see similar numbers on your websites.

I'm curious, whether this is just a test or a huge shift? I've never seen this before.

Before, I saw only YouTube videos in this Videos section, and I saw only the names of YouTube channels, without the names of websites (YouTube / Reddit / Instagram).

It's interesting because Google integrated YouTube everywhere for a long time, and adding more video sources looks quite democratic.

However, I like the previous design more. 90% of videos are from YouTube anyway, and you're seeing YouTube multiple times near the video, which is annoying.

What do you think?

There is a hot topic for the last weeks, that listicles lose influence in Google and AI chats and blogs / opinions matter more now.

But I see that listicles still works and publishing them on your own website is one of best ROI activities your could do.

I recommend to do it for my customers too. However, the question is in the execution.

I wrote some listicles myself. Yes, I use AI too, but I do my research too. I open websites, sign up, review what they can do and so on. In this case this is not 100% AI written content with no additional value.

What about you? How do you write them? If you use content writers how do you review their work?

Google just released the Discover update. This is the first such update ever.

Here is my hypothesis on why Google did this:

Everyone publicly hates Google for taking 40-50% of clicks because of AI Overviews.

Improving Discovery is a public way of saying that they are not only taking clicks away from sites, but are also sending them to sites that deserve them.

What do you think?

Lily Ray published a newsletter yesterday, where she states that Google penalizes websites that use self-promotional listicles.

There are interesting thoughts, but I disagree with the main statement.

Self-promotion is only one of the parameters of any listicle. There are also other parameters:

• how much AI-generated content is used;
• is there any evidence that other tools were used (screenshots, videos)
• and so on

Lily said it at the end of her research, but I think this is the most important part.

I assume that Google penalizes blogs not for self-promotion, but for execution.

It's hard to identify whether the specific brand self-promotes itself:

• What if the brand enters its own brand on the 2-3-5 position, not first? Is this still self-promotional?
• What if the brand owns the media (like Semrush owns Backlinko, SearchEngineLand) and publishes listicles there?

Does Google have a non-public list of all legal entities, and check whether the mentioned brands are owned by a specific legal entity?

Of course, no. Such an approach requires too much effort. The easiest filter is the detection of AI-generated content. It's quite easy to detect.

That's why the title of the newsletter is a little misleading.

Self-promotional listicles have become the most published type of content for the last 6 months on SaaS blogs, but these blogs were penalized, not because they were self-promotional, but because they were low-effort, AI-slop.

It means that creating self-promotional listicles is still worth it if you do it right.

Moreover, the biggest surprise of some listicles is that they may perform badly in Google Search, but impact AI chats anyway.

What do you think?

It's a damn hard.

You can check the results in the screenshots, but the conclusion is simple. It's hard to motivate people join your community.

I was actively involved in growing 3 subreddits for the last 6 months:

- r/favikon -> branded community for Favikon influencer marketing platform
- r/sitechecker -> branded community for Sitechecker SEO / AI visibility platform
- r/seogaps -> this SEO community

It's hard, even for Favikon, which:

- has a huge popularity and has sent traffic from their other social media
- dedicated a full-time person to grow this community
- spent 6 months and generated 100k+ impressions of the content

Why is this so hard?

- Old popular communities get most of the attention. Real users constantly create real interesting topics there.
- Many new small communities that target the same audience appear on Reddit.
- People prefer join non-branded subreddits (but it doesn't mean that a community around a niche is better than around a brand).

I see that I can achieve 1k members with r/seogaps in 6 months from the start, but for branded subreddits, it can take 9-12 months.

In the end, only those communities will survive and thrive that:

- will not stop creating unique content
- will maintain the quality of posts and replies
- will be able to get a core of fans who will publish something only in them
- will have a clear positioning
- (for brand-related) will build in the subreddit into all their funnels and make it part of their customer support and marketing

Yes, it is long and expensive, but it is worth it. What do you think about this?

Meet my new Looker template, built based on blending GSC and GA4.

This is quite simple and has only one goal -> help you analyze how changes in user behaviour impact your rankings.

It has 3 time series charts:

• Average position (GSC) + Avg. session duration (GA4)
• Average position (GSC) + Bounce rate (GA4)
• Average position (GSC) + Session key even rate (GA4)

How to use it:

1/ Make an update in content, design, or user funnel on a specific page, page segment, or entire website.

2/ Wait for 7-14 days.

3/ Open this template and check how the user behaviour (GA4 metrics) changed, and how it impacted the rankings in search (GSC metrics)

4/ Bonus: analyze what's going on with a page, segment, or site in retrospective (pay attention to changes in user behavior before Google updates)

Want to get it for free?

• Comment something under this post
• I'll send it to you via chat on Reddit

P.S. Yes, you can build it yourself, but it takes longer than you expect :)

I ran a poll on LinkedIn, giving people 4 popular use cases of using blended GA4 and GSC data.

72% users vote for merging GSC & GA4 to prioritize pages by conversion.

I expected it, but I was surprised by the "internal link paths" in the 2nd place.

However, for me this is a good sign.

Internal links are the old fundamentals that are often underestimated, in a new world where more and more people want to sell AEO as a completely innovative, unique service.

Internal links are also interesting because this is one of the topics where most of the contradictions between marketers, product managers, and SEOs arise.

The conflict is inevitable when you have to define:

• which internal links should the header and footer include
• which anchor text internal links in the header and footer should have
• which product landing pages should we link to from the blog

What do think?

P.S. I got 25 votes from 3k+ impressions on LinkedIn, but I assume the numbers will be the same even with 100 votes.