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Category: Prices, CPM, ROI

  • Is CPM profitable? Should Perplexity be excluded from AI visibility tracking?

    Is CPM profitable? Should Perplexity be excluded from AI visibility tracking?

    In the world of AI search, leaders are constantly changing, and the question of which platforms to track becomes critical for SEO specialists. Recent discussions have revolved around the Perplexity platform: should we continue monitoring it or focus exclusively on giants like ChatGPT, Gemini, and Claude? We will examine how changes in market share affect visibility assessment and how much money each spent ruble will bring to understand if CPM is profitable.

    Is Perplexity really losing ground?

    Ross Hudgens, CEO of Siege Media, claims that Perplexity’s market share is shrinking. Including it in general metrics alongside ChatGPT, Gemini, Claude, and Google AI products can distort the real picture of visibility. Hudgens urges: “Everyone should remove Perplexity from their LLM trackers today.”

    However, as experience shows, hasty conclusions can be erroneous. In March 2002, at the Search Engine Strategies conference, the reduction of tracked search engines from 15 to 5 was discussed. Google was then excluded from the list. This turned out to be a serious oversight, as Google was rapidly gaining momentum. A similar situation could repeat itself today.

    Data confirms Perplexity’s decline

    • According to StatCounter, in June 2026, Perplexity held 7.91% of AI chatbot referral share, almost on par with Gemini (7.94%).
    • By August 2026, Perplexity’s share had fallen to 4.31%, while Gemini grew to 10.9%.

    “A small market share does not always mean small strategic importance. It’s like investing in stocks: you shouldn’t always look only at current capitalization, but also at growth potential.”

    The market is consolidating, but not around a single leader

    The latest Similarweb data for May 2026 shows the dominance of ChatGPT (53.9% of global web visits among seven major AI assistants). Gemini accounts for 27.9%, Claude – 9.2%, DeepSeek – 4.1%, Grok – 2.4%, and Perplexity and Copilot – 1.3% each.

    Significant changes occurred not in the disappearance of Perplexity, but in the emergence of a strong second player. ChatGPT’s share of AI chatbot web traffic decreased from 76.4% a year ago to 52.7% in May 2026. Gemini grew from 9% to 27.3%, and Claude – from 1.6% to 8.9%.

    Key players and their advantages

    • ChatGPT: over 900 million weekly active users (February), over 1 billion active users across all products (end of July). This is a huge direct consumer base.
  • Gemini: The Gemini app exceeded 1 billion monthly users (August). It has Google distribution through Search, Android, and the entire product ecosystem.
  • Claude: Has gained a strong position in the enterprise segment and among developers. In April, over 100,000 customers used Claude on Amazon Bedrock. Annual revenue exceeded $65 billion (August).

These are not three versions of the same business, but three different distribution advantages. The market looks like an emerging oligopoly, not a “winner takes all” situation.

What SEOs Should Track

Google AI Overviews and AI Mode should not be viewed as ordinary LLMs. They are much more important. In June, Google reported that AI Overviews cover more than 2.5 billion users per month, and AI Mode exceeded 1 billion monthly users. AI Mode queries have doubled every quarter since launch.

According to Similarweb, AI Overviews appeared in 43% of Google search queries in the US by May 2026, compared to 15% a year earlier. AI Mode visits grew from 126 million in June 2025 to 279 million in May 2026.

This means that Google AI is a separate layer in the world’s dominant search ecosystem. For B2B companies, Claude is also of immense importance, despite relatively low consumer traffic. PwC, TCS, and Cognizant are actively integrating Claude into their workflows, training tens of thousands of employees. Over 1,000 business customers spend more than $1 million annually on Claude.

Three-Tier AI Visibility Measurement System

  1. First Tier: Platforms with scale and strategic importance. Track ChatGPT and Gemini separately. Add Claude for B2B, corporate, and professional audiences.
  2. Second Tier: AI search embedded in existing ecosystems. Track Google AI Overviews and AI Mode separately from ChatGPT, Gemini, and Claude. The goal is to measure how AI changes the search journey. Microsoft Copilot can also be included in this tier if the company has a significant presence in Microsoft 365.
  3. Third Tier: Emerging or specialized platforms. This includes Perplexity, Grok, DeepSeek. Do not ignore them, but do not give them equal weight. Monitor them for unusual visibility, referral traffic, citations, and growth.

Don’t Let Averages Mask Real Data

An aggregated LLM visibility metric can create a false sense of accuracy. For example, if a brand has 40% citation rate in ChatGPT, 35% in Gemini, 30% in Claude, and 90% in Perplexity, a simple average would be 48.75%. This number says little if Perplexity accounts for only a small fraction of the traffic important to the business.

CPM выгодный? Стоит ли исключать Perplexity из отслеживания ИИ-видимости? — illustration 2

Instead of asking, “What is our average LLM visibility?” you should ask, “Where do the people important to this business actually encounter our brand?”

This requires combining three data sets:

  • Audience Reach: usage, visits, platform distribution.
  • Visibility: mentions, citations, referring URLs, queries that generate them.
  • Business Impact: linking AI referrals to engagement, leads, sales, and other conversions.

My Verdict on Perplexity

Ross Hudgens is right about the problem, but not entirely right about the solution. Don’t remove Perplexity from your LLM tracker, but reduce its weight. If Perplexity generates 1% of your AI traffic, giving it 25% or 33% weight in your visibility score is unjustified. However, if it accounts for more than 5% of referrals, as Hudgens himself suggests, the argument for it becomes stronger.

Perplexity’s trajectory is worth watching. Similarweb’s August 2026 analysis still describes Perplexity as an active player in the AI search market, noting its ad-free strategy and focus on subscriptions and enterprise deals. This shows why “small” and “insignificant” are not synonyms.

Frequently Asked Questions

What CPM should be considered profitable for AI platforms?

Profitable CPM in AI platforms depends on your target audience and ROI. If a platform generates high-quality leads or sales, even with a relatively high CPM, it can be profitable. The main thing is to consider not only the cost per impression but also the conversion rate.

Is it worth testing hypotheses cheaply on new AI platforms?

Yes, cheap hypothesis testing on new AI platforms is essential. This is how you can discover the next Google. You shouldn’t spend huge budgets on them, but monitoring and minimal testing will allow you not to miss a potential breakthrough.

What is cheaper: a banner or a blogger, when compared to AI platforms?

The question of what is cheaper, a banner or a blogger, is incorrect in the context of AI. AI platforms offer a different type of interaction. Price comparison should be done through efficiency metrics: how much does 1 million impressions via a banner cost versus the cost of generating 100 AI videos or the cost of publishing 500 videos via AI tools. Each channel has its own unit economics.

How to estimate the cost of uniqueizing one video using AI?

The cost of uniqueizing one video using AI depends on the complexity of the task and the tool used. It is important to evaluate not only direct costs but also the time that AI will save. The price per minute of AI video with an avatar also varies, but it often turns out to be more profitable than manual labor, especially for large volumes.

Conclusion

The AI search market is dynamic. Ignoring Perplexity or other niche platforms entirely means risking missing important signals. However, blindly giving them equal weight with giants distorts the picture. A mathematical approach to analysis, weighing platforms by their real business impact, and constant monitoring of new players are key to success in SEO and a profitable CPM strategy.

We count cash, not just the number of platforms in the tracker. Don’t overlook the outsiders who are gaining momentum. Perhaps among them lies the next market leader. Start analyzing your data today so you don’t miss new opportunities!

  • ChatGPT Ads: 6 Months Later — What is a Good CPM?

    ChatGPT Ads: 6 Months Later — What is a Good CPM?

    Six months after the launch of OpenAI’s advertising platform, ChatGPT Ads still raises questions among advertisers. The figures vary widely: cost per click (CPC) ranges from less than $3 to $13, and a profitable CPM is not always clear. Some campaigns bring quality leads at a competitive price, while others yield minimal results. The problem is that there are no clear criteria for evaluating effectiveness, and the platform’s reporting is limited.

    Reporting is available at the campaign, ad group, and ad levels. Conversion tracking is implemented through OpenAI Pixel and Conversions API, supporting actions such as purchases, leads, and registrations. OpenAI can also use modeled conversions. This is where the reporting functionality ends, which complicates price comparison and the assessment of real ROI.

    Reporting Limitations and Competition

    The lack of comprehensive competitive reporting is a critical issue. If CPC increases, current data does not allow understanding whether this is due to increased competition, changes in relevance, inventory volume, bids, or the types of dialogues in which ads appear.

    This hinders accurate cheap hypothesis testing and campaign optimization.

    Hostinger’s Experience: $70,000 on Tests

    One of the largest public tests was conducted by Hostinger, spending almost $70,000. Hussein Ograk, Head of PPC, initially noted that CPC was no higher than in Google Search, and campaigns generated purchases. However, as the budget increased, his assessment became more nuanced.

    “CPM exceeded $65, but the main problem was CTR. More specific cases worked better, while broad messages consistently failed. Traffic quality was unstable, and evaluating ROAS based solely on direct conversions proved difficult,” Ograk noted.

    This example demonstrates that what CPM to consider profitable is a matter of context and traffic quality.

    Other Tests: Attribution and Lead Quality

    CTC reported attributed revenue ranging from $19,000 to $38,000, depending on the attribution model, with ROAS from 3.3x to 6.8x. They used Triple Whale to assess downstream performance, as ChatGPT Ads reports were insufficient.

    Floyd Blakey, analyzing a B2B campaign with a budget of $7,000 CAD, recorded an average CPC of $9.29, CPM of $64.34, and CTR of 0.7%. Using visitor de-anonymization, her team identified 146 organizations from 336 paid clicks. Of these, only five matched the ideal customer profile.

    This highlights the problem of traffic quality and shows that cheaper than influencers does not always mean more effective.

    Geographical Differences and Recommended CPC

    The Synter test showed significant geographical differences. With an overall CPC of $9.89 (at $4,428.84), it ranged from $5.10 in the UK to $10.62 in the US. In Australia, CPC reached $17.59, in New Zealand — $22.89, although volumes there were significantly lower. Cost per click heavily depends on the region.

    OpenAI recommends a starting maximum CPC from to . However, this recommendation is often perceived as a benchmark, although it is not. This creates false expectations regarding a budget alternative to seeding and how much 1 million impressions cost via banner compared to AI advertising.

    ChatGPT Ads: 6 months later — what is a profitable CPM? — illustration 2

    ChatGPT Ads Audience

    Advertising in ChatGPT is only available to Free and Go plan users, who constitute the majority of the audience. More expensive subscriptions (Plus, Pro, Business, Enterprise, Edu) remain ad-free, as do accounts of minors. This means that the advertising audience does not coincide with the overall ChatGPT user base.

    There is insufficient public information about the demographics and purchasing power of this audience. General ChatGPT user statistics are also irrelevant, as they include those who do not see ads. Geography further narrows the comparison.

    • Pilot launch: USA, Canada, Australia, New Zealand (February).
    • Expansion: UK, Japan, South Korea, Brazil, Mexico (May-August).
    • Access to Ads Manager: 52 countries (August 31).

    How to Approach ChatGPT Ads Now

    When starting to test hypotheses cheaply on this platform, it is important to understand its current limitations. Set expectations before spending, based on what will make the channel profitable for your business. Someone else’s CPC or CTR will provide little value until we know so little about the competition, audience, and types of dialogues behind these results.

    Early results require more thorough analysis than on mature platforms. Due to a lack of diagnostic signals, it is difficult to distinguish a real performance problem from display peculiarities, relevance, or available dialogues during the test period. There is no universal number yet that determines the success of a campaign in ChatGPT Ads. “Good” is what the channel brings to your specific business, not abstract figures.

    Frequently Asked Questions

    What is a profitable CPM in ChatGPT Ads?

    A profitable CPM in ChatGPT Ads does not have a fixed value. It depends on the niche, traffic quality, campaign goals, and the ROI you receive. Hostinger’s experience showed a CPM above $65, but with CTR issues. It is important to evaluate not only CPM but also the quality of leads and the final ROAS.

    Is it worth investing in ChatGPT Ads for a cheap hypothesis test?

    ChatGPT Ads can be a tool for a cheap hypothesis test, but with caveats. Limited reporting requires additional analytics tools (e.g., Triple Whale, visitor de-anonymization) for a full evaluation. Be prepared for the price vs. result to vary greatly.

    What’s cheaper: banner ads or ChatGPT Ads?

    Comparing what’s cheaper: banner or blogger with ChatGPT Ads is not directly correct. CPC in ChatGPT Ads can be significantly higher than in traditional banner advertising, reaching $10-$20 in some regions. However, if the quality of traffic and ROAS justify these costs, then ChatGPT Ads can be more effective. It is important to calculate unit economics.

    What CPC should be considered normal for ChatGPT Ads?

    OpenAI recommends a starting maximum CPC of $3 to $5, but this is not a benchmark. The actual CPC can be significantly higher, up to $13-$22. A “normal” CPC is one that provides a positive ROAS and aligns with your unit economics. Do not rely solely on recommendations; always conduct a cheap hypothesis test and analyze your data.

    Conclusion

    ChatGPT Ads is a new platform with potential, but also with serious limitations, especially in terms of reporting and transparency. Advertisers accustomed to detailed statistics face the need for deep off-platform analytics to assess real effectiveness. To understand how much money each ruble spent will bring, do not rely on general figures, but focus on your metrics and goals.

    Conduct a cheap hypothesis test, analyze each stage of the funnel, and optimize campaigns based on your own data and expert opinions. This is the only way to find your profitable CPM and achieve success.

  • CPM profitable: Google and AI — people use both, not replace

    CPM profitable: Google and AI — people use both, not replace

    In the modern digital landscape, where technology is evolving at an incredible pace, the question of how artificial intelligence (AI) affects traditional traffic generation methods is becoming increasingly relevant. This is especially true for a metric like profitable CPM. Information categories are losing clicks, Google is losing queries, but retaining its audience. AI does not replace search, but complements it. How much cache will this bring? Let’s calculate.

    95% of ChatGPT users are still on Google: What does this mean?

    According to Similarweb, 95% of ChatGPT users continue to use Google. This figure remained at 95% from September 2025 to May 2026, even though traffic to generative AI platforms grew by 70% year-over-year. Similarweb interprets this as AI complementing search, not replacing it.

    However, a study by Bocconi University showed a decrease in traditional search queries by 9.4% among households that gained access to ChatGPT Search. The discrepancy in data is explained by Similarweb counting people (overlap), while Bocconi counts queries per household. The same user might use Google for maps or login, and redirect specific queries to ChatGPT.

    How does AI affect search behavior?

    • Reduced queries: Households with access to ChatGPT Search reduced the number of traditional search queries by an average of 3.14 per week, which is 9.4% less than the pre-expansion level (33.51 queries). The reduction reached 17.0% after 20 weeks.
    • Drop in referrals: The largest drop in referrals was observed in information categories: academic sites (-32.8%), reference sites (-26.5%), developer sites (-15.1%), news sites (-13.4%).
    • Increased ChatGPT reach: Google’s household reach remained stable (around 49%), while ChatGPT grew from 4.6% to 7.9%.

    “When people use our AI-powered features in Search, they use Search more often,” — Sundar Pichai, CEO of Google.

    However, Google does not provide baseline data or user-level data to independently verify these claims. We are seeing an increase in the use of AI features in Google, which may replace the traditional results page.

    Experiment with AI Mode: What happens to clicks?

    A study by Stephanie T. Wang and her team (August 2024) involving 1100 Chrome users showed that when AI Mode was forced (94.7% of queries via AI), the number of clicks to external sites decreased by 18.8 percentage points.

    • Search sessions decreased by approximately 0.92 per day.
    • The average session duration increased by 0.43 minutes.
    • Clicks to news sites fell by 12.5 points, Reddit by 21.2 points, Wikipedia by 9.9 points.
  • The share of participants using Bing, DuckDuckGo, or Yahoo increased by 11.2 points.
  • Trust, satisfaction, and usefulness ratings decreased.

    • At the same time, 15.3% of AI Mode users experienced difficulties accessing specific websites. It is important to note that in March 2024, AI Mode did not display ads. Since May 20, Google has been testing new ad formats created with Gemini in AI Mode, which may change satisfaction and click metrics.

    What do current data not account for?

    None of the current datasets track individual users across different platforms (Google Search, AI Mode, ChatGPT, Gemini) at a task level over the long term.

    Google does not disclose user-level data to support its claims. It is unclear what types of queries transition to AI and which remain in traditional search. Bocconi’s data on the division into informational and transactional categories is only descriptive.

    CPM выгодный: Google и AI — люди используют оба, не заменяют — illustration 2

    Conclusion: CPM is profitable, but where does the cash go?

    We see that Google retains users but loses some queries and clicks. Optimization for voice search and AI functionality are becoming critically important. If you are paying for a profitable CPM in traditional search, but users are switching to AI, your unit economics may suffer.

    Cheap hypothesis testing using AI tools for content creation (generating 100 AI videos, video uniqueization) can be more effective than traditional methods. Is AI worth investing in? Facts show that it changes user behavior. The question is how to convert this into cash.

    For an arbitrageur, this means: a CPM cheaper than 50 rubles for a banner may be useless if clicks go to AI. Strategies need to be adapted. Analyze your metrics, compare price vs result, to understand what CPM to consider profitable for your niche.

    Frequently Asked Questions

    Q: What is cheaper: banner or target?

    A: This depends on your target audience and campaign goals. Data shows that AI changes user behavior, reducing the clickability of traditional ads. It may be worth considering a budget alternative to seeding through AI content.

    Q: Is it worth investing in AI for content?

    A: Yes, data indicates a growing use of AI for information retrieval. The cost per finished clip created by AI, or the cost of making a video unique, can be significantly lower than manual production, while still providing effective reach.

    Q: What CPM should be considered profitable?

    A: A profitable CPM is determined not only by the cost per thousand impressions but also by conversion. If users use AI to get answers without visiting websites, then even a very low CPM will not yield the desired result. It is important to evaluate ROI.

    Q: How does AI affect SEO?

    A: AI can reduce the number of direct clicks to your site, especially for informational queries. Optimizing content for AI Overviews and creating FAQ sections for voice search becomes critically important.

    Call to action: Analyze your data, test new hypotheses, and adapt strategies to changing user behavior. AI is not the future; it is already the present. How much cash are you willing to lose by ignoring this?

  • Profitable CPM: How to Restructure Marketing in the Era of AI Search

    Profitable CPM: How to Restructure Marketing in the Era of AI Search

    The era of traditional SEO, where CPM is profitable and hypothesis testing is cheap, is becoming a thing of the past. Today, buyers are increasingly turning to AI assistants, such as ChatGPT, Gemini, or Perplexity, to get direct answers to their questions. This changes the rules of the game for marketing teams and requires a re-evaluation of budgets. If your company is not mentioned in these AI answers, you are losing potential customers.

    Why the old marketing structure doesn’t work?

    Traditional marketing department structures were geared towards ranking in Google. SEO specialists were responsible for positions, content teams generated articles based on keywords, and paid advertising filled the gaps in organic traffic.

    All of this assumed that the buyer would see the results page and click on a link. However, today many skip this page, directly asking AI questions. For example, the query “best contract management software for mid-market legal teams” now yields a list of three vendors. If you’re not there, you’re out of the game.

    “I asked one question: which department is responsible for ChatGPT recommending you? No one had an answer, because the answer was — no one.”

    Ranking does not guarantee citation

    • Companies with first-page Google rankings are often mentioned in only a few of the 20 answers from AI assistants.
    • One of our clients with 14 keywords on Google’s first page was mentioned in only 4 of 20 AI answers.
    • Work that ensures AI citation, such as creating consistent entity signals, third-party endorsements, and structured original content, is often not part of anyone’s job description.

    Because budgets follow organizational structure, money continues to be spent on methods that AI models no longer reward. Planning a year in advance only exacerbates the problem, locking in old bets.

    Three role changes to adapt to AI search

    You probably don’t need new employees. You need three changes in areas of responsibility and a clear answer to the question of ownership.

    1. SEO Leader becomes AI Search Leader

    1. The SEO team becomes the AI Search team

    Usually, it’s the same person. Their task expands from “where do we rank” to “where are we cited.” This means managing the brand entity everywhere AI models read information: your website, LinkedIn, G2, Crunchbase, Reddit, industry directories.

    Entity fragmentation is the most common problem. Different brand names, domains, conflicting descriptions — AI perceives this as several weak companies instead of one strong one. A single owner can fix this in a quarter, and it costs almost nothing but attention.

    2. The content team shifts from volume to evidence

    Halve your publishing calendar. Redirect those hours to creating content that can be cited by AI: original data, customer results with specific numbers, expert comments from company employees, and pages structured to extract clear statements.

    Eight general posts a month lose to one article with unique data. Evaluate the team not by volume, but by the number of citations received and the impact on the sales funnel.

    3. Digital PR moves from the brand budget to the performance budget

    AI models reward consistency of information from independent sources. Mentions in industry publications, review platforms, and communities now do the same work that backlinks did a decade ago.

    This means PR stops being a “soft” expense item that can be cut in a bad quarter and becomes an acquisition channel with quarterly goals and KPIs. CPM cheaper than 50 rubles is possible through PR with clear metrics.

    CPM profitable: how to restructure marketing in the era of AI search — illustration 2

    Budget Math: How to Reallocate Funds

    Consider an example of a client who spent $60,000 per month on marketing. Price comparison before and after restructuring:

    Before restructuring:

    • Paid Search: $30,000
    • Content Production: $12,000
    • SEO Retainer: $8,000
    • Brand & PR: $5,000
    • Tools: $5,000

    After one quarter:

    • Paid Search: $24,000 (20% reduction, to protect branded queries and converting non-branded campaigns)
    • Content: $10,000 (fewer articles, but with more substantial evidence)
    • AI Search Program: $10,000 (entity cleanup, structured data, measurements)
    • Digital PR with targeted citation metrics: $10,000
    • Tools: $6,000 (added AI visibility tracker, e.g., Peec AI or Semrush AI toolkit)

    Don’t completely abandon paid search. It’s the purest source of data on buyer intent, which is necessary for testing AI assistants. The rule is simple: move 15-20% of the budget in the first quarter, then let the evidence guide the rest. No one should stop a working paid program “on faith.”

    90-Day Action Plan

    Don’t reorganize the team on day one. First, measure, then experiment, then scale what works.

    Weeks 1-4: Baseline

    • Test 20 of your key buyer queries in four major AI assistants.
    • Record every answer, every mention, every competitor.
    • Fix entity fragmentation. It costs nothing and has a cumulative effect.

    Weeks 5-8: Pilot Launch

    • Create a small team: an AI search leader, one content specialist, and a portion of the PR budget focused on a single product line.
    • Everything else operates as usual, providing a control group and reassuring the rest of the team.

    Weeks 9-12: Compare and Scale

    • Compare citation rates for test queries, referral traffic from AI assistants, and the number of inbound deals that mentioned discovering you through an AI tool.
    • Move budget where the evidence points. Reorganization follows results, not the other way around.

    Three Mistakes That Burn Budget

    1. Hiring an AI specialist before conducting baseline measurement. It’s impossible to write a job description until you know where your citation gaps are.
    2. Completely cutting classic SEO. AI assistants still rely on search indexes. Well-ranked pages are more often read by models. This is a rebalancing, not a burial.
    3. Launching AI search as a side project. If it doesn’t have a separate line in the budget, it doesn’t have an owner, and work without an owner doesn’t move. Allocate a budget, even a small one, and assign responsibility.

    Six months after restructuring, the mentioned software company increased its mentions in AI responses from three to 12 out of 20. Demo requests received through AI assistants are now tracked in their CRM. The size of the marketing team has not changed. Only the direction of investment has changed, aligning with current buyer behavior. Your organizational structure is a bet on how buyers will find you. Most structures still bet on the search results page, which fewer buyers are viewing each month. It’s time to change that bet.

    Frequently Asked Questions

    What is the role of an SEO specialist in the era of AI search?

    The role of an SEO specialist expands: they become an AI search leader, responsible not only for ranking but also for the brand’s citation by AI models across all relevant platforms and directories. This includes managing brand entity and eliminating information fragmentation.

    What’s cheaper: a banner or a blogger?

    In the context of AI search, what’s cheaper: a banner or a blogger is an outdated question. More important is which channel provides citation and evidence for AI models. Digital PR, aimed at getting mentions in authoritative sources, can be more effective than direct advertising or influencers, as AI values consistency from independent sources.

    What CPM should be considered profitable for AI-oriented marketing?

    What CPM should be considered profitable now depends on citations. If you get a CPM cheaper than 50 rubles through Digital PR, which leads to mentions in AI responses and, as a result, to leads, this is more profitable than a high CPM in traditional advertising without such an effect.

    Is AI worth it?

    Yes, AI is worth it if you want to remain competitive. AI search is not just a trend, but a new reality. Investing in adapting your marketing strategy to AI search allows for cheap hypothesis testing and ensures visibility where your customers are.

    How to measure the effectiveness of investments in AI search?

    Effectiveness is measured by several indicators: the citation level of the brand by AI assistants, referral traffic from these assistants, and the number of inbound deals that indicate AI as the source of discovery. These metrics help to understand how much money each ruble spent will bring.

    Conclusion

    The marketing landscape is changing. The focus is shifting from traditional SEO to AI search, where price vs. result is evaluated by citation and impact on the sales funnel. Reallocate your budget, change roles, and test hypotheses to stay in the game. Your organizational structure should reflect how customers search for and find information today. Learn more about our AI marketing strategy.

  • Google AI: Judge doubts spam update hits AI content

    Google AI: Judge doubts spam update hits AI content

    This week, the SEO world is buzzing with activity: a judge questions Google’s monopoly on AI content, a spam update pulls the rug out from under automated publications, and the old debate about geotargeting flares up again. Let’s break down what this means for your cache, especially in the context of Google AI.

    Legal Battles: Google AI and “Unfair” Content Usage

    A federal judge questioned Google’s practice of using web content for its AI overviews, calling it “grossly unfair.” This jeopardizes the current “traffic in exchange for content” model.

    Details of Penske Media vs. Google Case

    • During the antitrust hearing for Penske Media, Judge Amit Mehta questioned whether Google’s AI overviews could be considered a “product improvement.”
    • Digital Content Next CEO Jason Kint quoted the judge, who called the situation “really unfair” and noted that the improvement is being developed “at the expense of publishers.”
    • Judge Mehta has not yet ruled on Google’s motion to dismiss the lawsuit.

    “Publishers have no control over how Google uses their content,” Kint noted, emphasizing that opting out of Google indexing is not a realistic choice for publishers dependent on search traffic.

    Google Spam Update: A Blow to AI Publications

    Although Google has not officially stated that it is targeting AI-generated content in the August spam update, reports from website owners indicate problems for automated publications. Is cheap AI content worth such risks?

    Initial Observations and Conclusions

    • Roger Montti collected examples where fully automated sites lost visibility, while resources using AI with human refinement suffered less.
    • These are currently anecdotal reports, not official confirmation of changes in Google’s algorithms.
    • Google released the S-CTS system to detect coordinated synthetic abuse on video platforms, but this is not related to Google Search.
    • The mere fact of AI authorship is not a reason for a drop in rankings. Google’s policy concerns large-scale content created to manipulate rankings, regardless of the author.

    • SEO consultant Takuma Oka warns that his sample is small and the conclusions are not definitive. What matters is not the AI itself, but the method and purpose of mass production.

    SEO vs. GEO: What John Mueller Says

    John Mueller from Google once again commented on the “SEO vs. GEO” discussion, clarifying that there are no special requirements for generative AI answers in search. That is, testing hypotheses cheaply does not mean that basic principles can be forgotten.

    Nuances for AI Answers

    Dan Akedju summarized: “The fundamentals are the same. The extraction level is different.” This is a key point: favorable CPM only when the platform’s features are taken into account.

    AI Recommendations: Brands are Recommended, but Others are Cited

    New data shows that a brand recommendation in an AI answer does not guarantee a direct link to your site. This affects ROI and requires a review of metrics.

    Shero Commerce Analysis

    Aleyda Solis emphasized: “Your brand may be recommended in the answer… while the citation (and click) goes to a magazine or marketplace.” This means that the cost of uniqueizing one video or the price of generating 100 AI videos should pay off not only with mentions but also with direct links.

    ChatGPT and Reddit: Complex Citation Dynamics

    Promptwatch data showed a sharp drop in Reddit’s citation share in ChatGPT in mid-August, but new tests show that Reddit still plays an important role in the information extraction process.

    Google AI: The judge doubts, the spam update hits AI content — illustration 2

    Variability of ChatGPT Behavior

    Mohanadasan summarized: “Reddit citations were not simply ‘turned off.’ They seem to be query-dependent.” This demonstrates that price comparison of various sources and their citability is a dynamic process and requires constant monitoring.

    Conclusion: Visibility vs. Value – New Metrics

    This week, it became clear that visibility and real value are beginning to diverge. Publishers share information, but don’t always get traffic. Brands receive recommendations, but links go to others. Reddit may be a data source for AI, but not appear in final citations. “AI visibility” is becoming too broad a concept, requiring more precise metrics to assess ROI.

    It’s important not only to be indexed, but also to get a mention, a citation, a click, and ultimately, a conversion. How much money will each dollar spent bring – that’s the main question. Re-evaluate your strategies and metrics to avoid wasting your budget.

    Frequently Asked Questions

    What is “unfair” use of content by Google AI?

    Judge Amit Mehta opined that Google, by using publishers’ content for its AI overviews without adequate compensation or control from publishers, creates an unfair advantage, as publishers cannot opt out of Google indexing without losing traffic.

    Is Google’s spam update really targeting AI-generated content?

    Google has not officially confirmed this. However, according to reports from website owners, resources that use fully automated content generation have lost visibility. At the same time, sites where AI content was refined by humans suffered less. The focus is on large-scale content created to manipulate rankings, regardless of the generation method.

    What does John Mueller advise regarding SEO for AI answers?

    Mueller states that there are no special requirements for generative AI answers in Google Search. If you are already optimizing your site for Google, no additional technical checklists are needed for AI overviews. However, it is important to remember that different AI systems extract and select sources differently.

    Why might a brand be recommended by AI, but the link goes to another site?

    Shero Commerce research showed that AI systems often recommend brands by name, but cite third-party resources (e.g., magazines or marketplaces) instead of the brand’s official pages. This means that brand visibility does not always convert into direct clicks and traffic to your resource.

    How has ChatGPT’s behavior regarding Reddit citations changed?

    Data shows that Reddit citations in ChatGPT have become more complex and depend on the specific query. In some cases, Reddit is actively used and cited, in others, a lot of data is extracted, but there are no citations. This indicates the dynamism of algorithms and the need for constant analysis of sources that AI systems prefer for specific topics.

  • Yandex: Sales via Search and Alice AI without a website – profitable CPM?

    Yandex: Sales via Search and Alice AI without a website – profitable CPM?

    Yandex is opening a new sales channel for sellers without their own online stores, offering a unique opportunity to achieve a profitable CPM. Now their products are available in Search and chat with Alice AI, and purchases happen in one click. Connecting to the service is free, which makes it potentially beneficial for cheap hypothesis testing and finding new traffic sources. It’s important to calculate unit economics to maximize profit.

    What does Yandex offer sellers without a website?

    The new feature allows sellers without their own website to place products in Yandex search results and Alice AI. This expands opportunities to reach an audience without significant investment in developing an e-commerce platform.

    How does it work?

    • Yandex Commerce Protocol (YCP): the neural network selects relevant products, displaying them as cards.
    • Yandex Universal Checkout: users make purchases with a “Buy in one click” button.
    • Beta testing: the feature is currently in test mode.

    “Traffic from Alice AI to Russian e-commerce has grown 4.6 times since the beginning of the year. These are not just numbers, this is sales growth potential that cannot be ignored,” — quote from an analytical report.

    How much does it cost to connect and how to start selling?

    Connecting to the service is free. The main costs will be associated with payment processing and logistics. This makes the offer an attractive budget alternative to seeding or expensive integrations with influencers.

    Steps to start selling:

    1. Yandex Products: submit an application for checkout connection.
    2. Yandex KIT: upload assortment, specify prices, set up payment and delivery.

    After these settings, products are automatically displayed in Yandex Search and Alice AI for relevant queries. This is a direct path to the buyer, bypassing the creation of an expensive website.

    Logistics and analytics: counting cash

    To fulfill orders, the seller can use various logistics options, which provides flexibility and allows for cost optimization. This is a key factor in achieving a profitable CPM.

    Available logistics options:

    • Marketplace logistics (if already present).
    • Own logistics.
    • External services: Yandex Delivery, SDEK, PEK, Dalli.

    Analysts note that traffic from Alice AI to Russian e-commerce has grown by 358% since the beginning of the year. This is not just statistics, it is an indicator of a growing audience that can be converted into sales. How much money will it bring for every ruble spent – that’s a question for your unit economics.

    Яндекс: Продажи через Поиск и Алису AI без сайта — выгодный CPM? — illustration 2

    Frequently asked questions

    What CPM can be considered profitable when working with Yandex?

    A profitable CPM is one that provides a positive ROI. In this case, with free connection, the cost will be formed from payment commissions and logistics. It is necessary to conduct test sales to determine the optimal CPM for your product.

    What is cheaper: banner advertising or sales via Yandex Search/Alice AI?

    Sales via Yandex Search and Alice AI can be significantly cheaper than traditional banner advertising, especially at the initial stage. The absence of a connection fee and the possibility of cheap hypothesis testing makes this channel attractive for small and medium businesses. Banner advertising requires large budgets and does not always guarantee a direct transition to purchase.

    Is it worth investing in AI sales channels without your own website?

    Yes, it is. Especially for a quick start and demand verification. Yandex provides ready-made infrastructure for accepting payments and delivery, which lowers entry barriers. This allows you to focus on the product and marketing, rather than the technical side of e-commerce.

    Conclusion: cash or lost opportunity?

    The new sales channel from Yandex is not just an option, it is an opportunity for sellers without a website to gain access to millions of potential buyers. Free connection and flexible logistics conditions allow you to compare prices with other channels and, possibly, find that very profitable CPM. Don’t miss the chance to test hypotheses cheaply.

    Start accepting applications and uploading your assortment today to assess the real potential of this sales channel and turn it into a significant source of income for your business.

  • Nvidia Invests in Cloverleaf: What Does This Mean for AI Infrastructure Prices?

    Nvidia Invests in Cloverleaf: What Does This Mean for AI Infrastructure Prices?

    Nvidia continues to actively invest in the development of artificial intelligence infrastructure, which directly impacts its revenues. The company recently announced a strategic partnership with Cloverleaf Infrastructure. This deal could change the landscape of the AI infrastructure market and potentially reduce the cost of deploying new capacities.

    Nvidia’s Investments: Facts and Figures

    Cloverleaf Infrastructure, founded in 2024, specializes in creating foundational infrastructure for data centers. In its founding year, the company attracted $300 million in investments. Its key role is to mediate between utility providers and data centers, ensuring critical power sources and other elements for site development.

    How much did Nvidia invest in Cloverleaf?

    • The terms of the deal have not been disclosed.
    • According to The Wall Street Journal, Nvidia’s investment in Cloverleaf is likely to be several hundred million dollars.
    • Reuters reports that the chipmaker now owns a minority stake in Cloverleaf.

    “Nvidia is increasingly involved in financing and developing AI data centers, which, in turn, purchase its AI systems,” analysts note.

    Nvidia’s Strategy: AI Flywheel and Unit Economics

    This deal is part of Nvidia’s broader strategy to reinvest its enormous profits into maintaining the “AI flywheel.” The goal is to ensure continuous demand for its high-performance chips and systems. The company aims not only to sell hardware but also to actively participate in creating conditions for its large-scale use.

    Specific examples of investments in AI infrastructure

    Earlier this week, Nvidia announced another major investment:

    • $1.5 billion in SB Energy.
    • This is a data center project associated with OpenAI, located in Ohio.

    Such investments show that Nvidia is not just waiting for the market to develop but is actively shaping it. For arbitrageurs and marketers, this means a potential reduction in CPM costs due to increased availability of computing power and, consequently, more favorable conditions for cheap hypothesis testing on large volumes of data.

    Nvidia invests in Cloverleaf: what does this mean for AI infrastructure prices? — illustration 2

    Frequently Asked Questions

    How profitable will CPM be thanks to these investments?

    The direct impact on CPM is still difficult to assess, but increased availability and reduced cost of AI computing infrastructure can make advertising platforms more efficient. This could potentially lower the costs of data processing and content generation, which will ultimately affect the cost per thousand impressions.

    What is cheaper: banner advertising or AI-generated content?

    Nvidia’s investments in AI infrastructure are making AI-generated content increasingly accessible and cheaper to produce. If previously the cost of banner advertising was predictable, now the price of generating 100 AI videos or a mass posting package can be significantly lower with comparable or even greater efficiency.

    Should one invest in AI solutions now?

    Given the active investments of giants like Nvidia in AI infrastructure, the market is becoming more stable and predictable. This is a favorable time to consider investments in AI solutions, as entry barriers and operating costs may decrease.

    Conclusion: Cash and Prospects

    Nvidia’s investments in Cloverleaf Infrastructure and SB Energy are not just financial operations, but strategic steps to strengthen its dominant position in the AI sector. The company aims to create an ecosystem where its chips will be indispensable. For businesses, this means a potential reduction in AI development and operating costs, opening up new opportunities to optimize unit economics and generate more profit from every dollar invested. We are watching the numbers and preparing for new opportunities that this “AI flywheel” will bring.

  • AI Dialogues in Search Console: How to Recognize and Use Them

    AI Dialogues in Search Console: How to Recognize and Use Them

    In August, SEO specialist Anastasia Kuru noticed queries in the Search Console report that didn’t look like search queries: “Yes,” “Yes, continue,” “Yes, price.” John Mueller confirmed that Search Console includes data from AI Overviews and AI Mode in the overall report, and subsequent questions within AI Mode are recorded as new queries. This opens up the opportunity to analyze fragments of AI dialogues that appear in your statistics.

    In this article, we’ll break down how to recognize such fragments in Search Console data, how they differ from regular queries, and how to use this information for optimizing content for AI search.

    Seven types of AI fragments in Search Console data

    I analyzed 16 months of data from my site and identified seven categories of such queries. Each has its own origin and characteristics.

    Short answers

    These are single words or phrases like “yes,” “of course,” “show me.” They occur when a user responds to AI during a dialogue, and the response is treated as a search query. Positions in such cases are taken from the answer block, not from the search results.

    Comparisons in dialogue

    Phrases like “what about Resend?” or “what if we try Gemini?” — the user asks AI to compare an alternative with the already received answer. This signals a specific interest in your content.

    Questions addressed to a conversational partner

    The grammar of such queries implies the presence of a listener: “Can Meta Ray-Bans be hacked?”, “How do I sell this?”. They differ from regular search phrases.

    Synthetic prompts from SEO tools

    Regular queries, for example, “evaluate [company] by [criterion]” or “. my location is usa.” They repeat daily for months, indicating automation.

    Full instructions for agents

    Machines sometimes log entire prompts, for example, “find on the web… return 3 most relevant results… don’t invent URLs.” Such strings end up in the report as queries.

    Errors and table headers

    People and pipelines search as-is. In my data, there was an entire row from a ranking tracker CSV file that received 146 impressions.

    Long queries without markers

    Phrases of 10+ words without obvious signs of dialogue. The classifier sends them for manual review, as they could be either AI fragments or regular long-tail queries.

    AI-диалоги в Search Console: как распознать и использовать — illustration 2

    How to distinguish AI fragments from regular queries

    The key difference is the addressee. A regular long query is addressed to no one, while a conversational one is directed at a conversational partner. Four signals reveal the conversational nature:

    • presence of an address;
    • interrogative construction;
    • incomplete sentences;
    • conversational particles.

    Length itself is a weak signal, so queries of 10+ words with interrogative intonation are classified as conversational, while those without markers are sent to quarantine.

    Practical conclusions from the analysis

    On my site, AI fragments began appearing in March 2026, steadily 20–30 impressions per month. For example, the query “yes” gave 110 impressions and 6 clicks at an average position of 4.5 — this is impossible in regular search results, but typical for an AI answer block.

    Comparative queries perfectly correlate with my articles: “what about Claude?” led to the WebMCP guide, “what about Xcode?” — to the post about Xcode. This shows that users actively compare alternatives, and your content can be mentioned in AI answers.

    Frequently asked questions

    Can AI Overviews be separated from AI Mode in the data?

    No, Google combines them in the report as web search. The fragment indicates the fact of a dialogue, but not the specific type of surface.

    Why does Google hide queries and clicks in the Generative AI report?

    The report shows impressions, pages, countries, devices, and dates, but not queries and clicks. The API does not support this data, and the BigQuery export does not contain an AI column. The only way to get data is the export button in the interface.

    How to set up a classifier for your site?

    The classifier genai_conversation_queries is available in the free Search Console MCP v2.4.0. Install MCP with one command, select your project, and run the analysis. For large sites, use the BigQuery version v4.1.0.

    Conclusion

    Analyzing AI fragments in Search Console provides unique insights into how users interact with AI and find your content. Use the classifier to uncover hidden opportunities and optimize content for AI dialogues.

    Start with the free tool and get data that most SEO specialists miss.

  • Online school reduced DRR from 30% to 13.75% and reached revenue of 3+ million rubles: case study

    Online school reduced DRR from 30% to 13.75% and reached revenue of 3+ million rubles: case study

    An online school reduced DRR from 30% to 13.75% and reached stable revenue of over 3 million rubles per month — this is not a promise, but a real case study from the Academy of Modern Psychology. In this article, we break down how changing the approach to promotion and restructuring the funnel made it possible to achieve these numbers without relying on launches.

    Initial data and task

    The client is the Academy of Modern Psychology, specializing in online courses for beginners and practicing professionals. Average check — 60,000–130,000 rubles, deal cycle — from 1 to 3 months. The task was to increase budget and revenue while maintaining advertising profitability.

    We worked with the project for almost two years. During this time, we encountered several challenges: moving to a new advertising account, seasonal demand fluctuations, and the need for structural changes in campaigns.

    Key changes in strategy

    Transition to separate campaigns for each course

    Previously, all courses were promoted with a single strategy and a shared budget. When the number of courses increased, this approach stopped working: each program has its own audience and its own decision-making cycle.

    We split the campaigns so that each course is now managed separately. This allows us to disable ineffective areas and scale successful ones.

    Dividing the funnel into three levels

    All campaigns were divided into three directions: brand traffic, traffic for each course, and general traffic. Each level solves its own task:

    • the top level fills the funnel with new people;
    • the middle level converts those who have made a choice;
    • the bottom level closes those ready to buy.

    “Remove any level — the system will start to deplete,” notes Kristina Shev, managing partner of the Verga agency.

    Results by direction

    General traffic

    From January to March, it attracted 16,063 clicks at 48 rubles each. This is not a direct sales channel, but it constantly brings new people into the funnel, who later return through brand search.

    Online school reduced DRR from 30% to 13.75% and reached revenue of 3+ million rubles: case study

    Traffic for courses

    It consistently keeps DRR below 14% with budget and lead volume growth. Some March sales are not yet closed in CRM — we expect improved metrics.

    Brand traffic

    DRR has stayed below 14% for the entire quarter, and the conversion to leads grew from 3.4% in January to 5.2% in March. The best format is the extended snippet, which takes up the entire search results screen and leaves no room for competitors.

    March: record indicators

    In March, several factors came together: seasonal demand growth, budget redistribution after Telegram Ads restrictions, the start of new streams, and the maturation of leads with a long deal cycle.

    The budget grew from 338,000 to 430,000 rubles, and the number of leads reached 136, which is 53% more than in February. The final DRR in March was 13.75% with revenue of 3.13 million rubles.

    Plans for the future

    April is traditionally weaker, but the next peak is June-July. We plan to increase the budget to 500,000 rubles, launch auto-funnels, and test free webinars as an entry point.

    We are also expanding the list of advertised courses — the client is preparing about 35 new programs.

    Frequently asked questions

    What DRR is considered profitable for online schools?

    In this case, a DRR of 13-14% with an average check of 60,000+ rubles provides good margins. But there is no universal value — it all depends on the product’s margin and the share of variable costs.

    Online school reduced DRR from 30% to 13.75% and reached revenue of 3+ million rubles: case study

    What is cheaper: banner or targeting?

    In this case, a banner on Yandex partner sites for narrow audiences showed a CPA of 1,681 rubles, which is cheaper than many other formats. But for broad topics, search works better — there is more targeted traffic.

    How much does 1 million banner impressions cost?

    In our case, CPM was about 48 rubles per 1,000 impressions — this is within the norm for Yandex Display Network. But the main thing is not the cost of impressions, but the cost of the result.

    Should AI be used for creating videos?

    If you need to quickly test hypotheses, AI generation can be cheaper than ordering from a contractor. But for sales videos where expertise matters, it is better to involve professionals.

    Conclusion

    March’s record is not a coincidence, but the result of a built system: funnel separation, managing each course individually, constant communication with the sales department, and optimization by revenue rather than leads.

    If you want predictable revenue and lower DRR, start with an audit of your current campaign structure. Maybe you also need to divide your funnel into levels.

    Want the same result? Contact us for a consultation.

  • YouTube tightens Shorts monetization requirements starting in 2027

    YouTube tightens Shorts monetization requirements starting in 2027

    YouTube tightens Shorts monetization requirements starting in 2027

    Starting February 1, 2027, YouTube is raising the entry thresholds for the Partner Program. To earn ad revenue from Shorts, creators will need twice as many views, and for access to overall ad revenue and Premium, more watch hours. This is a step toward making short videos generate “meaningful” income, but only for a select few.

    The new Shorts monetization rules will affect everyone planning to earn on the platform. If you’re just starting your YouTube journey, it’s important to understand how the landscape will change in the coming years.

    New requirements for the Partner Program

    Currently, joining the YouTube Partner Program requires 1,000 subscribers and either 4,000 watch hours per year or 10 million Shorts views in 90 days. Starting February 2027, new applicants will need to reach 8,000 watch hours over 365 days or 20 million Shorts views in 90 days.

    Current program participants retain their terms—thresholds remain unchanged for them. This grandfather clause protects already-earning creators from sudden changes.

    Restrictions on Shorts ads

    Separately, requirements for accessing Shorts ad revenue are being tightened. Regardless of how you enter the Partner Program, to earn a share of ad revenue from short videos, you’ll need at least 10 million Shorts views in 90 days.

    If a creator drops below this threshold, their Shorts ads are automatically disabled but resume once views exceed the mark again. This makes Shorts monetization more exclusive and geared toward large channels.

    Why YouTube is doing this

    According to YouTube’s Vice President of Creator Products, Amjad Hanif, the changes are based on “the growth of the creator ecosystem over recent years.” In a video on the Creator Insider channel, he emphasized that the goal is to make Shorts ads a “meaningful” source of income.

    YouTube tightens Shorts monetization requirements starting in 2027

    To earn real money from Shorts, you need millions of views—hence the new requirements. YouTube is deliberately restricting access to ad revenue, pushing smaller creators toward alternative monetization methods.

    What doesn’t change: Fan Funding and new incentives

    Requirements for Fan Funding remain the same: 500 subscribers, three uploads in 90 days, and either 3,000 watch hours per year or 3 million Shorts views in 90 days. This allows smaller channels to receive direct fan support.

    YouTube’s blog states: “We’re expanding earning opportunities by introducing new incentives rather than relying solely on ads.” For channels below the 10 million view threshold, bonuses for achieving goals will be introduced, such as for YouTube Shopping, brand deals, and participating in trends. Details are promised later.

    Impact on creators

    YouTube’s Partner Program has existed for nearly 20 years and continues to generate income for millions of creators. However, the revenue structure is shifting: more creators are earning through direct funding methods.

    The new rules acknowledge this trend but don’t abandon those who rely on ads. Current partners retain their terms, while newcomers will have to work harder to get into the program.

    Frequently asked questions

    When do the new requirements take effect?

    Starting February 1, 2027.

    YouTube tightens Shorts monetization requirements starting in 2027

    What are the new thresholds for joining the Partner Program?

    You need 8,000 watch hours over 365 days or 20 million Shorts views in 90 days.

    What happens to current Partner Program participants?

    Their terms won’t change—they retain the old thresholds.

    How do I now earn ad revenue from Shorts?

    You need to reach 10 million Shorts views in 90 days, regardless of your Partner Program status.

    What alternatives exist for smaller channels?

    Fan Funding (500 subscribers, 3 uploads, 3,000 watch hours or 3 million Shorts views) and new bonus programs that will be introduced later.

    Bottom line: YouTube is betting on quality and scale. If you plan to grow a channel, focus on a long-term strategy: combine Shorts with long-form videos, use Fan Funding, and keep an eye on new bonus programs. Adapt to changes early—and your channel will remain profitable.