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Tag: 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.

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.
02.09.2026
Repurposing for AI Search: How Creators Bypass Brand Algorithms
In a world where AI chatbots are becoming the new entry point for customers, brands are changing their visibility strategies. A new item has appeared in creator briefs: AI visibility. Marketers have realized that traditional SEO and paid advertising methods are no longer sufficient when LLMs (large language models) actively scan social media, blogs, and news portals in search of answers to user queries. The key becomes the “video DNA” and “matrix” of content that AI can interpret.

AI Visibility: The New Reality of Content

Previously, the brand itself dictated what would be said about it online. Today, AI search takes the initiative, relying on external, more authentic sources.

“The machine moves to the most accessible public information and the most authentic to get closer to an answer. It’s not what comes from the brands themselves,” notes Joe Gagliese, CEO of Viral Nation.

Creators as Key to AI Trust
- Authenticity: AI prefers content created by real people, not corporate marketing departments.
- Accessibility: Social networks and creator blogs are open data sources for LLMs.
- Trust: Positive reviews and feedback from creators build a brand’s reputation in the eyes of AI.
The Zoom example demonstrates this trend: the company collaborated with journalist-creator Naima Raza to enhance authority through storytelling. This is a step towards bypassing the advertising ban when a direct advertising message doesn’t work.

Measuring and Optimizing AI Visibility

While the direct link between creator campaigns and AI visibility is still under development, the correlation is already evident. Christina Coughlin, SVP and General Manager at Trevant, notes that requests to track creator content in AI search results come in almost every new pitch.

This pushes agencies towards repurposing content and adapting strategies.

Agency Strategies for AI Visibility
1. Audit existing content: Trevant analyzes which creators and content types generate the most citations in LLMs.
2. Continuous monitoring: Tracking citations during campaigns to optimize and plan future partnerships.
3. Integration with SEO: Crispin’s teams, for example, work with SEO specialists to reverse engineer GEO processes to amplify creator influence.
This approach allows brands, previously skeptical of influencer marketing, to see the value in unique video and content for AI search.

Technical Aspects of AEO and Content

Creators are actively mastering AEO (Answer Engine Optimization), creating specialized sites and conducting audits. It’s important that social media post captions are machine-readable and contain enough information for LLMs to scan.

“In addition to simply sharing information and all the usual things you expect from a caption, we’re now suddenly saying, ‘Okay, this is the new long tail of online search, and we need to make sure this caption is working as hard as possible,’” emphasizes Daniella Wiley, CEO of Sway Group.

What creators need to consider:
- “Gluing” information: Creating cohesive, informative content that is easy to “repackage” for AI.
- “Splitting” content: Turning one webinar into 50 short clips for different platforms.
- Metadata: Maximally detailed and relevant descriptions, tags.
However, experts warn against overdoing it. Scott Sutton, CEO of Later, notes that 300,000 TikToks about a new soap might not make it into AEO if they are not in the right place for indexing.

This highlights the importance of a uniqueness package and a strategic approach to content scaling.

Frequently Asked Questions

What is AI visibility and why is it important?

AI visibility is the ability of a brand’s content to be discovered and cited by large language models (LLMs) and AI chatbots when responding to user queries. It is important because more and more people are starting their purchasing journey with AI search, and a brand not present there loses potential customers. It’s like a “clone” of your content working for you in a new digital reality.

How can creators help brands improve AI visibility?

Creators can create authentic, informative, and well-structured content that is easily scannable by LLMs. Their positive reviews and testimonials are perceived by AI as more reliable than direct brand advertising. They help to “trick” algorithms by providing quality, natural content.

What is AEO and how does it differ from SEO?

AEO (Answer Engine Optimization) is the optimization of content for answer engines, such as AI chatbots, which aim to provide a direct answer to a user’s question. Unlike traditional SEO, which focuses on keywords for search engines, AEO is geared towards providing clear, authoritative, and complete answers that AI can easily extract and use. It’s like “repurposing video for advertising” with AI logic in mind.

Yes, repurposing and unique-ifying existing content is an effective approach. This can include changing the background and tone in videos, adapting for TikTok, Shorts, Reels, rewriting captions for machine readability. The goal is to create 100 unique pieces from one, but it’s important to ensure that the new content meets AEO requirements and will be correctly indexed by AI.

Conclusion

The era of AI search is changing the game for brands and creators. Investing in AI visibility through authentic creator content is becoming not just desirable, but critically important. This is not just a “price comparison from scratch”, but a strategic step towards dominating the new digital reality.

Start adapting your content strategy today so that your brand is not just visible, but also cited in tomorrow’s AI world. Explore the possibilities of generating variants for A/B tests and adapting for different social networks to make the most effective use of every bit of your content.
24.08.2026
AI Changes Search: Why Your Content Needs to Provide an Immediate Answer
The era of fragmented queries is fading. Data from a year of Google’s AI search mode shows: users are asking complete questions, not fragments of phrases. This is critically important for stream highlights and any other content: now the main information should be at the beginning so that AI algorithms can instantly extract it and present it in their reviews. If you bury the essence in long introductions, your content risks going unnoticed.

Evolution of Search: From Keywords to Dialogue

Since the launch of AI mode, user queries have fundamentally changed. According to Shivani Mohan, Google’s VP of Data Science, AI mode has reached 1 billion active users per month. But it’s not just about the increase in the number of queries.
- Query length has tripled: The average query in AI mode in the US is three times longer than traditional queries.
- Multimodal search: More than 1 in 6 queries now include images, voice input, or interactive dialogue.
- Growth of images: Image-based queries are growing by 40% monthly.
- Follow-up questions: Users ask clarifying questions, indicating the depth of their search.
The most common first words in AI mode queries are “what,” “how,” “I,” “is,” and “can.” This demonstrates a shift from searching by individual words to task- and question-oriented search, similar to communicating with a human.

Five User Behavior Modes in AI Search

Mohan identifies five main user behavior modes, each requiring a specific approach to content:
- Explore: Open-ended queries for brainstorming. Growing 30% faster than overall AI mode traffic.
- Decide: Queries with comparison words (“which of,” “which one”). Growing 40% faster.
- Learn: Understanding new concepts and professional development.
- Create: Queries for image creation have tripled since the beginning of the year.
- Do: Planning (workouts, travel, budgets). Growing 80% faster in the last six months.
“This is not just a change in ranking factors; it’s a transformation of user behavior. If you’re still building content around keywords, that model is rapidly becoming obsolete,” says Greg Jarboe.

How to adapt your content strategy for AI search

To make your content effective in the new reality of AI search, follow these five steps:

1. Start with the main point

Place the main definition, key metrics, or main conclusions directly in the first sentence of each main section. This allows AI algorithms to quickly extract the necessary information.

2. Use specifics

Formulate sentences with specific brand names, geographical markers, exact dates, and verified numerical values. Avoid vague generalizations so that your text is “mathematically readable” for search engines and reduces the risk of AI “hallucinations.”

3. Structure for scanning

Organize the main text into short paragraphs (2-3 sentences). After section headings, use brief summaries, ordered lists, or structured tables. This facilitates segment extraction for AI and ensures readability for humans. This is especially important for mass cutting of 100+ clips, where each fragment must be self-contained and informative.

4. Prepare answers to follow-up questions

If multi-turn dialogues are growing by 40% per month, your content should answer the second and third questions a reader will ask after the first. Structure long content so that each section can serve as an answer to a specific follow-up question. This increases the likelihood that this particular “chunk” will be provided by the AI mode. For cutting game streams, this means creating clips that answer specific viewer questions.

5. Optimize multimodal content

With the growth of image queries (40% monthly) and a threefold increase in image creation requests, alt-text, image context, and visual content quality are becoming key ranking factors. They are no longer secondary but are part of what the AI mode reads.

Conclusion: From “assembly line” to “smart content production”

Success in modern SEO is not about flooding the internet with templated texts, but about mastering structural clarity that provides immediate and verified benefits to both algorithms and readers. Just as 19th-century journalists adapted to the telegraph, we must rethink our approach to content creation for the AI era. Cutting streams without losing quality, creating highlights, and cropping 9:16 from horizontal — all this requires not just technical skills, but also a strategic approach to information delivery. Remember that the person who cuts streams must now think like an SEO specialist so that every Twitch clipping or podcast video cutting works as effectively as possible to attract an audience. Contact us to find out how we can help you with this.

Frequently Asked Questions

How long does it take to cut a 2-hour stream?

The cutting time depends on the complexity of the content and the desired number of highlights. On average, professional cutting without loss of quality of a 2-hour stream into 5-10 clips can take from 1 to 3 hours, including adding subtitles for cuts and optimization. If you need bulk cutting of 100+ clips, automated tools such as Opus Clip analog service are used, which significantly speed up the process but require subsequent manual refinement.

What moments are usually cut from streams for highlights?

For highlight editing, the most emotional moments, key game events (e.g., “kills”, “win rates”), funny jokes, important announcements, Q&A sessions, and fragments that evoke a strong audience reaction are usually cut. The goal is to create cuts for TikTok from Twitch or YouTube that quickly grab attention.

Are subtitles needed for stream cuts?

Yes, subtitles for cuts are extremely important. They improve content accessibility, allow videos to be watched without sound (e.g., in public places), and increase engagement. In addition, subtitles contribute to better indexing of content by search engines, which is important for stream monetization through cuts.

What is the price for 1 hour of stream for cutting 20 clips?

The price for cutting 20 clips from a stream for 1 hour can vary depending on the specialist’s qualifications, the complexity of the editing, and the need to add graphics and subtitles. Approximately, the cost can range from 1000 to 3000 rubles per hour of source material, if it is a high-quality work taking into account SEO optimization and 9:16 cropping from horizontal for different platforms.
24.08.2026
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.

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.
19.08.2026
Cannes Lions 2025: Creator Marketing Goes Core

Five days in Cannes, dozens of conversations — and one clear signal for creator marketing. Brands have stopped asking if it works. Now they are frantically building the infrastructure to scale before competitors pull ahead.

The most candid discussions happened outside official panels — at breakfasts and lunches where brand leaders and content creators dropped the scripts. Creator marketing is finally measurable down to the last dollar. Brands that embrace this rigor are pulling ahead.

Marketers Finally Have the Measurements They Were Missing

Previously, you couldn’t pinpoint which post led to a purchase. That has changed. We can now show a brand exactly which post drove which purchase, who saw it, who clicked, what they bought, and at what price — fully attributed down to the dollar.

Without this transparency, every decision becomes a negotiation between the CMO and CFO, speaking different languages. Closing this attribution gap is the biggest breakthrough in the industry right now. That’s why creator marketing is moving from a test budget to a core line item in annual planning.

“Brands get more from integrating and supporting smaller creators than they realize. Snapchat gives audiences a unique, unfiltered view of the creator’s life, and this deeper access is what drives real connection.” — David Dobrik

Brands That Underestimate Small Creators Lose Real Connection

We opened the week with a conversation between top creator David Dobrik and Quincy Kevaan, head of creator partnerships at Snap. The discussion centered on the value of authentic closeness between a creator and their audience. This is something brand strategists often miss.

A creator with a smaller but engaged audience on a platform built for intimate communication can outperform a much larger creator on a broadcast platform — depending on the goal. The trust Dobrik speaks of is harder to measure than reach, but it’s what turns attention into action.

The Best Brand-Creator Partnerships Start Before the Brief

The most memorable conversation was a lunch discussion with Dhar Mann and Shira Lazar. Dhar built a 200-person studio without taking a single brand partner for the first five years. This gave him the leverage to say “no” to unsuitable deals.

In that conversation, one theme kept surfacing: strong partnerships rarely start with a price list. They begin with a shared perspective, closer to creative collaboration than a media buy. Shira added that creator sustainability and partnership quality are not separate issues. A burned-out or financially unstable creator cannot consistently deliver for a brand, no matter how good the brief.

Brands Still Cling to Creative Control They Don’t Need

In a discussion with Keiko Mori (TikTok), Sabrina Callahan (Southwest Airlines), and comedian Connor Wood, a key insight emerged. Sabrina uses creator marketing to engage customers in real changes — including the airline’s controversial product shifts. This only works if the brand trusts creators enough to make content feel native to the platform, not committee-approved.

Connor put it simply: “When comedy feels forced, it’s dead.” Brands getting real returns from TikTok understand that the platform rewards content made for its feed, preserving the creator’s voice. Keiko noted that TikTok has long outgrown its reputation as a purely brand-awareness platform — discovery, consideration, and conversion all happen in a single scroll.

Creators Understand Your Brand Better Than Your Internal Team

Let’s be direct: a creator who communicates daily with your target audience for years understands how your brand is actually perceived better than any report or analysis. Marketers who accept this insight move faster and spend smarter than those who see it as a threat to control.

Advice for CMOs still hesitating: give creators strategic direction, then get out of the way and let them work.

Creator Content Becomes Raw Material for Brand Presence in AI Search

According to McKinsey, brand websites make up only 5–10% of what AI search references. The remaining 90–95% is third-party content: creator posts, community discussions, long-form videos, product reviews. Platforms leading in LLM citations include YouTube (16% of responses), Reddit (around 40%), Substack, and niche communities.

Brands fastest to build infrastructure for AI search understand that being good enough to rank in traditional search engines is no longer sufficient.

Cannes Confirmed the Model That Was Already Forming

Every conversation during the week returned to one idea: creator marketing has become part of the core marketing infrastructure. Brands that have embraced this are already building systems around it. As H2 planning progresses, the question has shifted from “whether to work with creators” to “how to weave creator content into every part of the funnel” — from awareness to conversion, into product pages, into paid traffic, into places where AI assistants pull answers.

Brands doing this well see growth and efficiency simultaneously. That combination convinces CFOs this is no longer a marketing experiment. Cannes confirmed the speed of this shift and provided the evidence.

Frequently Asked Questions

How do you measure the effectiveness of creator marketing?

Use end-to-end attribution: track specific posts to purchase via UTM tags, promo codes, and pixels. Modern platforms allow you to attribute every action down to the dollar.

Is it worth working with micro-creators?

Yes. A creator with a small but engaged audience on a platform built for close communication (e.g., Snapchat) can deliver higher conversion than a large blogger on a broadcast platform.

How does AI search impact creator marketing?

AI models increasingly reference creator content (YouTube, Reddit, Substack) rather than brand websites. Investing in such content boosts brand visibility in AI search.

If you’re building in this space, let’s talk. Plan, publish, and analyze campaigns with Later.

06.07.2026