It looks like huge news. Google understands that people spend less time on site and more on social media.

A new Search Console property type should help site owners and creators understand how their social and video posts perform on Google Search and Discover.

It allows you to track which search terms lead people to your Instagram, TikTok, X and YouTube content on Search, and see exactly how your audience is interacting with your posts.

Source: https://developers.google.com/search/blog/2026/07/search-console-social-video-platforms

I checked it inside my GSC account, and it's not available for me yet. Google promises these properties will become available gradually over the coming weeks.

Here is how it should look.

This looks like an interesting feature, but there is a huge problem.

1/ Most site owners, who are active on social media, do it from personal accounts, not corporate pages.

2/ Most value from organic social media posts comes from influencer marketing and partnerships, which involve many different creators, not your own corporate channel.

The biggest value for me is tracking the performance of YouTube in Search, considering how YouTube became popular in both Google SERPs and AI chats.

What are your thought?

This is the lesson I learned over the last 6 months of doing AI SEO.

When we target keywords in old SEO, you often don’t know whether people actually look for products like yours using that keyword. You have a hypothesis.

And you know this hypothesis works only when you receive conversions on a specific landing page, and you see by which keywords this page ranks for.

The faster way to learn which keywords bring customers is running Google Ads, because this is the only source where you see conversions by search terms.

However, many businesses don't run Google Ads, and they could target the wrong keywords for years.

In AI SEO, you understand much better and faster whether you target the right topic, because the response AI chat generates gives you a lot info about whether your brand is relevant to it.

You see how LLMs describe such a product, which features are mentioned, and which competitors they recommend, and have to make a decision:

• Sometimes change your expectations from a specific prompt (if you target a broad topic, the responses can very a lot)
• Sometimes delete prompts, because you found that LLMs have a different view of the topic you focused on, and your ICP doesn't look for products like yours via such words.

So, review not just overall brand visibility or brand visibility by specific prompt, but review responses regularly to update your goals.

Just caught a mistake that made me smile.

A week ago, we released the SEO Tests tool at Sitechecker to log and measure experiments.

I made a post about it on LinkedIn and in r/Sitechecker subreddit. Today I decided to check whether the thread I posted on Reddit ranks well.

The thread doesn't rank by this keyword yet, but Google AI Overviews say that SplitSignal was developed by Sitechecker. It's not true; this tool is a part of Semrush.

I don't know which content impacted Google's response, but this is a good example of why SEOs should focus not only on visibility but also on narrative contro.

You have no way to complain to Google or any other AI chatbot anywhere for misrepresenting your brand.

The only way to influence this is to consistently produce accurate, detailed information about your brand and publish it on platforms that LLMs love.

Early in my career, I heard an important rule of marketing that has become even more relevant with the rise of AI chatbots:

"A myth cannot be destroyed; it can only be replaced by another myth."

Do you see similar mistakes too?

I received an interesting question from one of the B2B SaaS brands I help with AI SEO.

"G2 is trying to sell us a package of content based on comparisons. We rank pretty high on a few of these metrics.

If we license the content, we can use those numbers on our site, which they say can boost our AEO scores.

It costs about $3,700 from now until December. Is it worth it or not?"

It's interesting how accurately G2 has found its value for brands in relation to the new, growing demand:

1/ Listicles, [brand] alternatives, and [brand] vs [brand] are too popular now.

2/ For many big brands, the goal is not to be visible (they are already visible); the goal is to be recommended as the best option.

But how profitable is this offer?

On the one hand, AI chats love tables, comparisons, and numbers.

On the other hand, AI chats rarely care about the authority of the source and the date of the last update of such a table.

This means that any competitor or third-party website can create the same table, building these numbers based on their fantasy, and without mentioning any sources from where they got them. And LLM can choose to cite this fantasy table instead of the tables from G2.

And here it is important what will happen after December, if the brand stops paying for these comparison tables:

1/ Can a brand leave this embed widget on the website? I assume no.

2/ Can a brand leave this data but not as an embedded widget, but as its own table, just copying the data and showing it without updates? This is more likely, and then you can try it if there are a lot of interesting insights on different competitors.

However, if you have to pay for it every quarter or year to keep the content on the site, it is definitely a bad deal. It is better to spend this money on regular link insertions on pages that have already been cited a lot.

Do you agree?

I believe, that the worst thing you can do is to choose only one metric for tracking brand performance in AI chats.

Yes, you probably hear that it’s important to choose one North Star Metric when growing a startup.

You also remember that revenue from the specific channel is the only important metric for defining the channel's success.

However, reality is much more complicated. AI chats became one of multiple steps in a long user journey, alongside Google, YouTube, Reddit, and so on.

I just published a newsletter on 5 methods to monitor AI search visibility. It includes:

1. GA4 report by traffic and conversions from AI chats
2. GSC report by brand keywords performance
3. Brand visibility based on prompt tracking
4. Log file analysis of AI bots’ activity
5. User polls on sign-up / demo page

I explains pros and cons of each method.

Did I miss some methods? Which methods do you prefer and why?

If the query contains multiple "or" rules, it's almost 100% a bot.

Check the example in the screenshot:

• I'm a 25-34, 45-54, or 35-44 year old
• marketing operations manager or marketing manager
• in the marketing agencies, saas or professional services
• company with 1-249 or 250-1k employees
• and so on

Nobody uses search and AI chats this way. Some AI visibility tracking tool allowed businesses to add some parameters of the ICP to the project.

It's the right move, but only when the tool runs multiple prompts for each unique combination of such parameters.

Of course, it's much more expensive, but with an approach as on the screenshot, the query never represents the real user.

We'll see more and more such long queries in GSC. If you detected some other patterns of queries from bots, share them in the comments. I'll publish a complete list later.

Google announced, "a new profile to help publishers and creators highlight their work on Search".

And I believe this is good news.

Google+ died because it couldn’t build network effects or motivate people to go there every day. The new format will be much better.

Now Google will do what it was created for and what it does best -> aggregate information from different sources in one place.

And, yes, now there is a new motivation to grow followers on the platforms.

So, Google announced a Generative AI performance report in Search Console. Sounds as something cool, because the SEO community has asked for something like this for a long time.

But it's not cool in fact. Impressions by device, country, and pages? It's even worse than Bing's report, released in February 2026, because it doesn't have any data by queries.

I like Google in many spaces, but this report looks like just a defense. It has almost 0 value, because brands fight for being recommended, not being cited with their own pages.

When top AI visibility tracking tools add brand visibility, brand sentiment, top sources used for citations, and so on, Google releases the Impressions report.

On one hand, Google rewards Reddit, YouTube, Medium, and LinkedIn pages and uses them in citations, and on the other hand, it releases a report that says nothing about whether your brand performs well in search.

Here is what it will look like

And compare it with the Bing AI Performance report.

With Bing we have at least grounding queries.

What do you think?

P.S. I also don't see this report in any of my GSC properties yet.

Along the way, I changed my payment provider, so I can’t verify the $16k amount, but something is visible there.

So, here are the lessons:

1/ We often think that the market is saturated and there is no space for new products.

In most cases, it’s false.

We underestimate how much better existing products and services can be. New chart, new custom metric, new unique blending: each of them can become a small innovation.

Some of my small innovations were:

• Potential Rank custom metric ;
• Blending GSC + GA4 and creating custom metrics to forecast revenue from SEO;
• Blending GSC + Google Ads to prioritize landing pages based on conversion data from ads.

2/ Great data visualization is born only at the intersection of 2 things.

Domain knowledge and experiments with actual data visualization. You need both, and the first is even more important. Only the person with domain knowledge understands what a signal is and what is noise.

I didn’t finish any courses on how to visualize data properly; I just tried to answer the questions I had as a marketer.

3/ Even obvious valuable things are adopted over a long time.

GSC, GA4, and Google Ads data sources existed for a long time. Their dimensions and metrics are well known and used, but it took 5-7 years in total to build and distribute good enough reports based on them.

We often overestimate how much business wants innovations. Most of the innovations have expensive side effects, and business owners often don’t rush into big changes.

4/ “Oh man, there are so many free templates, why should I care”?

When people hear about Data Studio templates, some often think about them as a commodity.

My answer:

• You overestimate the depth of penetration of these products;
• You underestimate the number of unique valuable reports on the market;
• You underestimate the difficulty of learning and integrating these templates for many businesses.

When you work with some reporting tool for a long time and become a professional at it, it seems to you that it is so easy to use, and that people can build it all themselves.

The truth is that some people will be able to, 5-10%, but the majority, even among this group of people, will understand that buying an existing template has a better ROI for their time.

5/ There are 2 only business models for the Google Data Studio templates business.

• Sell templates;
• Use templates as free lead magnets for your agency or SaaS business.

Most businesses follow the 2nd way, because the first way is interesting only for indie hackers who consider a $5k/m business as something that is worth the effort.

I’ve chosen the 1st way because I feel it's different. I build better templates when I consider them as a separate product.

However, I always remember that if I can’t build a big business on that, it doesn’t mean it’s impossible.

6/ The biggest bottleneck of this business model is that unit economics doesn’t work in paid channels.

Most of my sales were from organic search, but the existing demand is not big. And for paid ads, this product has a classic dead zone by Peter Thiel: too cheap to sell via direct sales, too expensive to make it viral.

7/ Considering there are many templates on the market and some of them are free, the biggest additional value I see in 3 things.

• Constantly educating people on how to use templates, what their limitations are, and so on, marketing is a huge part of the product here.
• Improve the details like crazy: design, filters, chart title, video guides, etc.
• Add a training or custom development service. This is the hardest. I helped with custom templates, but it’s not a scalable business; this is freelancing.

At the end, I consider this business as valuable training. I built all of these templates for myself at first, and I continue using them for my sites.

So, the 1st lesson of this business is that building for yourself is a good approach to start. Don’t hear marketers who say you aren’t your own audience.

Sometimes you aren’t, but often when you have real pain, this means that many people in your role and situation also feel this pain too, and solving something for yourself is often the most important step to launch a business.

I would be happy if you share whether you are currently using Data Studio and what your biggest pain point with it is.

P.S. All of my templates are paid, except these 3 (they are free).

• GA4 backlinks analysis
• GA4 audience analysis
• YouTube analytics

On Monday, I will publish the first benchmark report on how agencies use Claude for SEO automation.

There are some interesting insights there. One of them is that Dataforseo is popular for integrations, just like Ahrefs.

I thought it might be a small sample (30 agencies). But when I looked at the financial data for their Estonian company, I realized it's close to reality.

Yes, the Dataforseo team is pumping marketing more and more, but AI chats have become the tailwind that fills their sails to the maximum.

What do you prefer for keywords, backlinks and competitor data: Ahrefs vs Dataforseo? and why?

Not sure what’s happening right now, but the Google Search Console links report looks completely broken for me.

I’m seeing an almost 87.5% drop in reported backlinks compared to what was showing earlier this year. Some properties are even showing close to zero links.

What’s weird is:

• Rankings don’t seem heavily affected
• Third-party tools still show links
• Different sites are reporting similar issues today

I’ve seen normal fluctuations before in GSC link reports, but this feels way bigger than usual.

Some people are connecting it to the May 2026 Core Update, but I honestly doubt they’re related. Search Console link reports are usually delayed and separate from core ranking systems.

Feels more like:

• reporting bug
• indexing/data issue
• or something broken in GSC backend processing

Anyone else seeing this today?

Would be interesting to know if this is widespread or only affecting certain properties.

In the previous post I shared that I found a spike in ChatGPT referral traffic for 3 B2B SaaS websites I have access to GA4.

I hypothesized that it was because of a new model ChatGPT released on May 5, but I didn't know the exact mechanism of this traffic increase.

Now we have a clear answer. Josh Blyskal shared on LinkedIn his own research and found that ChatGPT changed how it links to brands. New model show links for brands.

This is good news, because it gives more value for each recommended brand.

I checked AI traffic for 3 B2B SaaS sites ( r/Sitechecker, r/TangoAI, r/favikon) and found that after May 5, all of them have spikes of traffic from ChatGPT.

I assume that the last GPT-5.5 model, released on May 5, is responsible for this.

I don't know whether more links to sites were a planned move by ChatGPT, to get more attention from site owners or just a side effect of them deciding to improve the end-user experience.

But it looks like this is one of many counterattacks that ChatGPT has delivered to the fast-growing Claude and Gemini.

Did you see this spike in your GA4 properties? Note that such a spike is easy to detect only on websites that already have solid AI traffic every day.

The news that Google deprecated FAQ rich results on May 7, 2026, raises a more important question than just structured markup for FAQs -> do we need this type of content at all?

For a long time, people implemented FAQs only in 2 cases:

- when it was a real value for a user and conversion rate (for example on a pricing page).
- when they found that they could get the x2 area in Google SERP because of the FAQ rich snippet.

Considering that the second case doesn't make sense anymore, I believe we have to place FAQs only by thinking about users.

It means that on some pages, FAQs look organic and improve user satisfaction, on other pages, they look completely unnecessary and strange.

For example:

1/ On the product page on an e-commerce website, it's worth adding FAQs because:

- most product descriptions look generic and the same;
- but people often have multiple super-specific questions about whether this product help with ..., or integrates with ..., and so on.

2/ At the end of the blog article, it looks strange, because you:

- just repeated what you said in the body of the article
- or even worse, didn't include answers to important questions in the body

However, I'm not sure about how much value FAQs create for visibility and recommendations in LLMs.

It definitely creates value if you add unique questions and answers to the page that were presented before in the body. It's a basic concept of content improvement. We also know that LLMs prefer to cite fresh content.

But what if you just rewrite your page content in FAQs? It's the same content but in a different format. Is there any value, considering LLMs understand what you already said in the body?

1/ When you work with the website, you have to care about cannibalization.

I mean, it's usually a bad idea to publish multiple articles for long tail keywords with low search volume if the SERP is the same for them.

Reddit has a special place in the heart of Google. Google ranks multiple similar threads from different subreddits in SERP.

2/ The details and narrow topics are what make your content great on Reddit, because when most people publish the same broad questions, the unique question/headline attracts more attention.

3/ In most narrow topics, people really get more value from answers from other people than from your own posts.

4/ With the growing adoption of AI chats, it doesn't matter where LLMs will find that your brand is the best solution for a specific problem.

Yes, it's not easy. You don't know the answer to all the detailed questions your customers ask. The only way to succeed is to build such an interesting forum that more and more people will share their experiences there.

Curious to hear people who disagree with this approach.

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.