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  • TikTok’s AI Revolution: How Neural Networks Are Changing Advertising and UGC Content

    TikTok’s AI Revolution: How Neural Networks Are Changing Advertising and UGC Content

    The era of mass video generation by neural networks is already here. If you’ve ever considered running ads on TikTok, but the Ads Manager interface seemed too complex and the entry barrier too high, then this article is for you. We will tell you how new AI videos for advertising and AI-powered tools like Agentic Hub, Symphony Creative Studio, and Content Suite simplify campaign creation, management, and optimization, allowing you to generate AI UGC for a crypto project or any other business without deep expert knowledge of the platform.

    TikTok AI: New Horizons for Advertisers

    TikTok is actively implementing AI tools to democratize the process of creating and managing ad campaigns. According to Melissa Lorie, a short-form video expert, if TikTok Ads Manager is a restaurant, then MCP (Marketing Campaign Platform) is the waiter, and AI tools (like Claude or ChatGPT) are the menu.

    Thanks to this integration, marketers can interact with platforms in a normal way, asking questions about campaign performance, requesting reports, and generating ideas.

    MCP: Two-Way Data Exchange with AI

    Before MCP, connecting AI tools to ad platforms required complex API integrations implemented by developers. MCP provides two-way communication between AI and the platform, allowing not only data extraction but also actions to be taken.

    Some connections are read-only (for reports), while others are read-write (for creating campaigns or adjusting settings directly from an AI tool).

    Pro Tip: AI recommendations should not be taken as gospel. If a new creative has only been running for a few days, TikTok’s AI might suggest pausing it because it’s performing worse than older creatives. However, this ignores the fact that the platform prioritizes ads that have been running longer.

    Marketers need to rely on their own judgment and challenge AI suggestions by asking questions like: “Is there another way to do this?” or “Can I do this better?” Often, AI revises its recommendations when challenged.

    AI Skills: Shortening the Path to Success

    Available skills include Viral Video Creator, Ad Group Optimizer, Account Diagnosis Co-pilots, and ByteDance’s C-Dance video creation tool. These skills can be found by searching for “TikTok AI skills” online.

    • Viral Video Creator: This skill, a favorite of Melissa Laurie, analyzes millions of videos processed daily by TikTok to identify the most effective ads. Marketers can use this data to model their own videos, from the catchy beginning to the call to action. Melissa estimates that the skill brings creative work to 70% completion; the remaining 30% requires human refinement, such as emphasizing specific product benefits. This allows the AI for UGC advertising to operate at peak efficiency.
    • Skill Flexibility: Since skills are files, they can be modified, copied, and improved. Marketers familiar with AI can add additional instructions on top of official TikTok skills, customize recurring tasks, and create their own automations.
    • Cross-Platform Compatibility: An unexpected benefit is that skills are not tied to the platform on which they were created. A marketer can use a TikTok copywriting skill to create ads for Meta or find that Meta’s Instagram copywriting skill works better for their TikTok campaigns. This interoperability represents a complete paradigm shift.

    Campaign Management Automation

    For campaign management automation, Melissa recommends starting with the following basic tasks:

    • Automating daily performance reports.
    • Querying AI about which creative has the strongest “hooks.”
    • Monitoring creative fatigue.

    When setting up a campaign, marketers can tell the AI their budget and goals (e.g., “I have $5,000, and I want to achieve X”) and request specific recommendations for campaign setup. This allows mass video generation by AI to become truly manageable.

    Symphony Creative Studio: AI-powered Production by Subscription

    Symphony Creative Studio is TikTok’s hub for creating AI-powered commercials. The updated Symphony Agent uses TikTok trends, signals from top-performing ads, business goals, and brand guidelines to create creatives at scale.

    The tool can take a campaign from brief to finished video, generating product briefs, insights, storyboards, scripts, avatars, and videos. Marketers then intervene to revise scenes, add voiceovers, and refine calls to action. This is true AI content production.

    Instant Video Generation from Text

    The interface is simple and resembles the query window of any other AI tool. Marketers add their prompts, brand guidelines, and other details, and Symphony generates videos almost instantly. This allows for generating video from text with unprecedented speed.

    Product Videos: Where AI Shines Brightest

    Product videos are an area where Symphony is currently delivering the strongest results. Melissa gives the example of a furniture company that uses this tool to create 100 videos a week, each showcasing a separate piece of furniture.

    Since these videos don’t require people on camera, the company can produce content at a scale that would be impossible with traditional video production. This is an AI pipeline of 500 videos per day for e-commerce.

    AI Avatars: Challenges and Prospects

    Animated AI characters in videos are not yet ready for most brands. The consensus among many leading companies is that the technology is not yet mature enough to create convincing human presenters. The trust issue is real: an AI avatar saying “all my friends are talking about this” raises obvious concerns. However, AI avatars with subtitles and AI voiceovers are already actively used for other purposes.

    Hybrid Approach: AI-Enhanced Real Videos

    Melissa sees potential in using AI to enhance real videos, rather than completely replacing them. Her agency, Oysterly Media, works with 3M on content for a mop. Creators film themselves demonstrating the mop, and then AI adds visual elements, such as animated “angry germs,” to dramatize the before-and-after effect.

    AI-революция TikTok: Как нейросети меняют рекламу и UGC-контент — illustration 2

    This hybrid approach—real creator plus AI enhancement—is one of two main ways that prominent brands are using AI video now. The other is product demonstration videos without people, especially in the beauty industry, where AI can render product materials, textures, and effects, such as how lip gloss looks when applied.

    Content Suite: Market Research with AI

    Content Suite is a library of UGC-style videos and ads running on the platform. The new AI search update significantly simplifies finding relevant content for research and ideas, solving one of the biggest challenges marketers face: coming up with new content ideas. This is a powerful tool for AI UGC for crypto projects and other niches.

    Smart Search and Competitive Analysis

    Marketers can search Content Suite by keywords, industry categories (e.g., airlines or beauty), time filters (e.g., last 30 days), campaign goal (sales, lead generation, or brand awareness), and geography. The tool functions similarly to Facebook Ads Library, but is easier to navigate, especially with AI search.

    Melissa recommends starting by searching for the company’s own brand, then expanding to competitor products and the broader industry category. The real value lies in seeing what creatives other brands in the same niche are launching and using that insight to create original content.

    Content Suite can also be used for direct competitive research, identifying what types of ads competitors are investing in and what creative approaches they are testing. For those who have not yet used TikTok advertising, Content Suite is the best starting point. Before spending money, browse the library to see what videos are being created in the relevant industry. This research expands creative thinking and provides concrete models to work with.

    Anatomy of a High-Performing TikTok Video

    As AI tools make ad creation more accessible, the quality bar on the platform is rising. Melissa argues that the way to stay above this rising bar is to understand what makes a video high-performing. The first frame matters most, not the first three seconds.

    Key elements of a captivating video:

    1. First Frame: The initial image of the video that a viewer sees before deciding to scroll past. This single frame determines whether someone stops.
    2. Billboard Text: A large text overlay on the screen. Melissa calls it “billboard text” because it works like a roadside billboard: the viewer has one moment to glance at it while scrolling, so it must instantly grab attention and convey the video’s value.
    3. Opening Words: If there’s a voiceover or someone speaking, the first few spoken words must immediately hook the viewer after the visuals have stopped the scroll.
    4. Connecting Tissue: Melissa’s term for the element that connects the beginning of the video to its middle section. Without this connecting tissue, viewers drop off between the “hook” and the main body.
    5. Middle Content: When sharing tips, Melissa recommends grouping them in sets of 3 or 5. Three is the ideal number to keep content concise.
    6. Abrupt End: The video should end with a sharp cut so that viewers don’t realize it’s about to end. A common mistake is slowing down and speaking more slowly towards the end, which signals the video’s conclusion and gives viewers a reason to scroll past. A clean cut tells the algorithm that viewers watched until the end, which helps with distribution.

    Authenticity vs. Polish

    Melissa’s agency preaches creating videos that feel like content from a family member or friend. Polished, staged videos make viewers scroll past because they are immediately perceived as ads. Naturalness is what drives performance.

    Tips for creating natural content:

    • Don’t stand still and talk directly into the camera. Instead, creators should be doing something while talking: picking up a water bottle, applying makeup, or walking through a door.
  • Even raw videos benefit from light editing. Melissa recommends setting a clear start and end point, adding subtitles (as many viewers scroll without sound), and using occasional jump cuts. These jump cuts signal to the brain that something interesting is happening, helping to retain viewers.

Pro Tip: Don’t give away the ending at the beginning of the video. Build anticipation by first hinting at the implications, then deliver the reveal in the middle or at the end. For example, instead of starting with “Instagram just launched feature X,” start with “Instagram just made a very big update. This will change how you do X, Y, and Z.” Then explain the implications before finally revealing the specific update. When the answer is given first, viewers have no reason to keep watching.

Conclusion: The Future of AI Production

Melissa Laurie, founder of Oysterly Media, believes that marketing agencies still have an important place in this new landscape. She compares it to flying: economy, business class, and first class all get passengers to the same destination, but some companies prefer the full range of agency services.

What has changed is that the economy option – doing it yourself with AI – is now a viable path for businesses willing to invest time in learning. Want to learn more about how AI writes scripts and edits, and how to use mass generation APIs? Explore new TikTok tools, browse Content Suite, and start experimenting. The future of AI clips with face swapping and AI video factories for e-commerce is already here, and it’s accessible to anyone willing to master these technologies. Start scaling your content production today!

Frequently Asked Questions

What is Agentic Hub and how does it help with TikTok advertising?

Agentic Hub is a TikTok platform that allows the integration of AI tools for creating, managing, and optimizing advertising campaigns. It simplifies marketers’ interaction with Ads Manager, enabling them to ask questions and receive reports in natural language, and automate routine tasks.

Can TikTok AI tools be used for other platforms?

Yes, one of the key advantages of TikTok’s AI skills is their cross-platform compatibility. For example, TikTok’s copywriting skill can be used to create ads for Meta, opening up new opportunities for marketers and changing the paradigm of working with different ecosystems.

How effective is Symphony Creative Studio for video creation?

Symphony Creative Studio allows you to generate videos from text, using TikTok trends, effective ad signals, and brand books. The best results are achieved when creating product videos without people in the frame. Some companies generate up to 100 videos per week, which would be impossible with traditional production. This is an excellent Synthesia alternative for mass production.

Should you use AI avatars in advertising videos?

Currently, AI avatars are not ready for most brands due to issues with persuasiveness and trust. Experts recommend using AI to enhance real videos, for example, by adding visual effects or animated elements, rather than completely replacing human presenters. However, AI avatars with subtitles and AI voiceovers can be useful in other contexts.

How to get started with AI advertising on TikTok?

Melissa Laurie recommends starting by exploring new TikTok tools and reviewing the Content Suite to understand what content other brands in your niche are creating. This will help form the basis for developing original creatives without initial advertising costs.

  • AI Transformation: Meta Reduces Staff, The Trade Desk Implements “Agents”

    AI Transformation: Meta Reduces Staff, The Trade Desk Implements “Agents”

    In a world where neural networks and AI avatars are becoming the norm, tech giants are actively restructuring their strategies. Recent events show how AI transformation and mass video generation by neural networks are changing the market landscape, forcing companies to optimize processes and cut costs. A Reuters report sheds light on Meta’s large-scale “Organizational Transformation” (Project OT), aimed at significantly reducing staff by transferring functions to agency technologies.

    Welcome to a new era where artificial intelligence is not just a tool, but a driving force behind global corporate changes. From Meta, re-evaluating its priorities after ambitious projects, to The Trade Desk, implementing intelligent assistants for advertising campaigns, and USA Today, adapting content for AI bots — each company is finding its way in this rapidly evolving reality. Get ready to learn how AI is changing the rules of the game, optimizing processes, cutting costs, and opening new horizons for business.

    Meta: From Metaverse to AI Optimization

    After an ambitious but not very successful dive into the metaverse, Meta has focused on staff optimization and automation. Project OT is an internal project to reduce the number of employees and transfer services to agency technologies.

    These are not just cutbacks, but a strategic redistribution of resources, where AI efficiency versus real UGC becomes a key factor.

    The Trade Desk: “Ask Koa” — A New Level of AI Interaction

    Intelligent Assistant for Advertising Campaigns

    The Trade Desk (TTD) introduces “Ask Koa” — a centralized AI interface that serves as a “single point of entry for various AI agents.” These chatbots will manage various aspects of the programmatic workflow, including audience creation, campaign optimization, and insight generation.

    This significantly increases AI production efficiency, allowing for scaling the impossible.

    Expanding Functionality and Combating “Ad Fatigue”

    • Transition to closed beta: “Ask Koa” is transitioning from alpha to closed beta this week, with plans for further expansion.
  • Frequency Capping Tool: A new tool automatically adjusts ad frequency based on brand performance data and campaign pace. This reduces “ad fatigue” and increases AI creative conversion.

    • “Much of the input for our product development process comes from customer feedback,” notes Eric Bosco, VP of Product Management at TTD. This confirms a customer-centric approach to AI solution development.

    USA Today: Content for Bots, Not Just Humans

    Restructuring Content for AI Systems

    USA Today Co. joins publishers like Time and The Economist in restructuring its content for AI bots. The new format will make it easier for AI systems to process and cite USA Today content.

    This is part of the publisher’s broader GEO strategy aimed at optimizing for search engines using AI.

    AI Transformation: Meta Cuts Staff, The Trade Desk Implements “Agents” — illustration 2

    Invisible Changes for Users

    Kara Chiles, Senior Vice President of Product Management, emphasizes that these changes will not affect how people perceive content. “Most of the modifications will not be visible to people. This concerns infrastructure, metadata, how we structure our formats and templates to be as discoverable as possible for AEO and GEO,” she says.

    The goal is to conclude more licensing agreements with AI companies and increase the value of current deals, which opens up new opportunities for AI UGC for crypto projects and other niche markets.

    Other AI Industry News

    Frequently Asked Questions

    What are “agent technologies” in the context of Meta?

    “Agent technologies” at Meta are AI systems capable of performing tasks and providing services that previously required human involvement. This allows for significant staff reductions and scaling operations, for example, in subscription neuro-production.

    How will The Trade Desk’s “Ask Koa” improve advertising campaigns?

    “Ask Koa” integrates various AI agents to optimize advertising campaigns. It assists in audience creation, improving efficiency, and generating insights, leading to more effective AI advertising and a reduction in the cost per AI creative.

    Why are publishers restructuring content for AI bots?

    Publishers, such as USA Today, are restructuring content for AI bots to improve its discoverability in AI systems, facilitate citation, and secure more licensing agreements with AI companies. This also aids in SEO optimization and text-to-video generation.

    Conclusion

    The era of AI video generation and automation has arrived. Companies like Meta and The Trade Desk are actively investing in neural networks and agent technologies to remain competitive. This opens up unprecedented opportunities for mass video generation by neural networks, creating AI commercials, and even AI video factories for e-commerce.

    If you want to know how much one AI creative costs or how a neural network writes scripts and edits, follow our updates. The future of content production is in AI. Don’t miss your chance to be at the forefront of this revolution! Learn more about AI content production.

  • Google vs. AI Content: What Did the August Spam Update Bring?

    Google vs. AI Content: What Did the August Spam Update Bring?

    Google’s recent August spam update appears to have targeted mass-generated AI content for SEO. Reports from online sources indicate that part of this update involved the removal of materials created by neural networks solely to manipulate search rankings. This aligns with Google’s recent research on identifying such spam, which is an important clue for anyone involved in AI video for advertising or mass video generation by neural network.

    It’s important to understand: using AI itself doesn’t make content spam. However, any material created for the purpose of ranking for keywords often balances on the line between regular content and spam. It seems Google has implemented new mechanisms to detect AI-generated content that crosses this line, which may explain the decline in rankings for many sites actively using neural networks for UGC advertising.

    Impact on AI-Generated Content

    Experts are actively discussing the consequences of the update. For example,

    Oka Takuma (@OkaTakuma1) wrote: “Regarding this Google spam update, it seems that sites automatically publishing content using Claude Code, Codec, etc., are being universally filtered and losing rankings. Google may automatically identify such content by attaching some kind of ‘AI credit,’ similar to generated images or videos.”

    He also noted that sites that started with manual publishing and then switched to LLM automation have survived in some cases. This is explained by accumulated domain trust. Sites entirely created with automation from scratch do not have “trust signals” from Google.

    Manual Review as a Buffer

    Oka Takuma provided an interesting example, mentioning a Japanese magazine that publishes AI-generated content and was not affected by the update. The reason is simple:

    “…but so far it has not received any penalties (naturally, we conduct a manual visual review by humans before publishing articles).”

    This highlights the importance of human control, even when using technologies such as AI avatar with subtitles or AI voiceovers. Manual review can be a lifeline for AI production by subscription.

    Not AI, but the Purpose of Use

    Seiichi Satoweb (@seiichi_satoweb) believes that the problem is not with AI content itself, but with its mass production to manipulate search results. He noted:

    “Companies managing media should check their rankings from August 18th to 21st. …If it dropped, I think the first thing to suspect is not the quality of the articles, but the ‘mass production method’.”

    Google defines malicious use of mass-generated content as creating a large number of pages primarily to manipulate search rankings, rather than to support users. This is critically important for those looking for AI content production or where to order for crypto similar services.

    • Mass video generation by neural network for SEO purposes can be risky.
    • AI clips with face swap or AI avatar with subtitles should serve a real purpose.
    • Focusing on quality, not quantity, is key to survival in Google’s new reality.

    “AI Junk” and its Consequences

    On forums like Blackhat World, users complain about the prevalence of “AI junk” in search results. One participant wrote:

    “They finally realized that AI junk is taking over the SERPs. I recently searched for a quick tutorial on how to change settings in an app and saw 4 sites in a row, clearly AI-generated to create articles answering that question — all looked absolutely identical, with the same AI formatting of subheadings and bullet points, poor spacing between sections, 3 sentences inflated to 500 words. AI junk pages are the new doorways, and Google is struggling to deal with it.”

    This confirms that the effectiveness of AI versus real UGC is still questionable when it comes to low-quality content. Generating 100 videos or an AI conveyor of 500 videos per day must be supported by a quality strategy, not just volume.

    Google vs. AI Content: What did the August spam update bring? — illustration 2

    Google’s New System: S-CTS

    Google recently published research on a new system called S-CTS (Scalable Cluster Termination System). This system is designed to identify and terminate networks of AI-generated spam. This means that an AI video factory for e-commerce or video generation from text via mass generation API are now under close scrutiny.

    How much does one AI creative cost or the cost of 1 minute of AI video — these metrics now need to be evaluated not only from a production perspective but also from the perspective of potential SEO risks.

    Conclusion: The Future of AI Content

    Google’s August spam update clearly showed that the era of mindless mass generation of AI content for SEO is coming to an end. Now that AI UGC for crypto projects or creating AI commercials are becoming increasingly accessible, it is critically important to focus on quality, uniqueness, and real value for the user. It’s not just about a neural network writing scripts and editing, but about creating something meaningful and useful.

    For those who want to scale their content production, solutions like Synthesia alternatives should be used wisely and supported by a strategy that does not contradict Google’s principles. Only then can sustainable success be achieved in a world where scaling was impossible — now it’s possible, but with an eye on quality.

    Frequently Asked Questions

    What is “AI junk” in the context of Google?

    “AI junk” is low-quality, mass-generated artificial intelligence content created primarily to manipulate search rankings, rather than to provide valuable information to users. It is often characterized by repetitive phrases, poor formatting, and a lack of originality, as in the case of AI video for advertising created without proper oversight.

    How does Google distinguish quality AI content from spam?

    Google does not penalize the use of AI per se. The main focus is on the purpose of content creation and its value to the user. If an AI avatar with subtitles or AI voiceovers are used to create useful, unique material that has undergone human review, it is not considered spam. The problem arises with mass video generation by neural networks solely for SEO without regard for quality.

    What is Google’s S-CTS system?

    S-CTS (Scalable Cluster Termination System) is a new Google system designed to identify and terminate networks engaged in AI-generated spam. It is a tool to combat large-scale operations producing low-quality content that use mass generation APIs to create thousands of pages or videos.

    Can AI be used to create UGC content?

    Yes, neural networks can be used for UGC advertising, but with caution. The key to success is creating valuable and unique content that is perceived as authentic. The effectiveness of AI versus real UGC will depend on how well AI integrates with the creative process and how thoroughly the content is human-reviewed to avoid “AI junk.”

  • Harvard and AI Avatars: How Neural Networks Scale Entrepreneurial Education

    Harvard and AI Avatars: How Neural Networks Scale Entrepreneurial Education

    Harvard Business School (HBS) is launching an innovative Foundry bootcamp where AI avatars of instructors will provide personalized feedback. This is a new step in scaling educational programs, significantly increasing learning efficiency. The cost of the eight-week course for entrepreneurs is only $699.

    The Foundry bootcamp, developed by HBS, offers weekly live sessions with instructors. However, a key feature is the use of animated AI characters for interactive engagement. These neural networks, created by the startup HeyGen, provide personalized feedback during practical presentations and simulated board meetings.

    This approach significantly increases the volume of individual support that would be impossible to provide through traditional methods.

    AI Avatars in Action: Personalized Feedback

    New York Times reporter Sarah Kessler personally tested the system, presenting her “Uber for bananas” project to the AI avatar of Flybridge Capital co-founder Jeff Bussgang. Although neither the real Bussgang nor his digital copy were impressed with the idea, Kessler noted that the virtual version displayed a “noticeably frozen smile” during her pitch.

    This highlights the potential of AI avatars with subtitles and facial expressions to create more realistic interaction.

    From Chatbot to Mentor: The Evolution of AI in Learning

    Project director Katharina Rings initially envisioned the AI component as a regular chatbot. However, after a pilot launch, students expressed a desire for a more structured and guided experience.

    This feedback led to the development of more sophisticated AI avatars, capable of not only answering questions but also actively participating in the learning process. This demonstrates the adaptability of neural production by subscription to user needs.

    “My students are thrilled with the digital copy,” said Jeff Bussgang, admitting that his AI avatar is a bit “creepy” but extremely useful in the learning process.

    The Effectiveness of AI vs. Real UGC: New Horizons

    Foundry bootcamp participants, unlike some students who express negative attitudes towards AI, positively evaluated the use of animated AI characters. This confirms that, with proper application, mass video generation by neural network and creation of AI commercials can be not only effective but also in demand.

    Гарвард и AI-аватары: как нейронки масштабируют обучение предпринимателей — illustration 2

    How much does one AI creative cost compared to traditional methods? Obviously, significantly less, which opens up new opportunities for AI UGC for a crypto project and other niches.

    Advantages of AI in Education and Marketing

    • Scalability: Allows providing individualized feedback to thousands of students simultaneously, making what was impossible to scale — now possible.
    • Cost-effectiveness: Reduces the cost of training and content creation. The cost of 1 minute of AI video is significantly lower than traditional production methods.
    • Personalization: AI avatar with subtitles and an individual approach improves the quality of learning.
    • Innovation: The use of neural networks for UGC advertising and an AI conveyor of 500 videos per day open up new opportunities for marketing and education.

    Frequently Asked Questions

    What is an AI avatar in the context of education?

    An AI avatar is a digital copy of a person, created using artificial intelligence, capable of mimicking their appearance, voice, and mannerisms for interactive engagement, such as providing feedback or conducting lectures. This allows for generating 100 videos or more with the same “instructor.”

    How do AI avatars help scale educational programs?

    By using AI avatars, educational institutions can provide personalized learning and feedback to a significantly larger number of students than is possible with live instructors. This reduces operational costs and increases access to quality education. It’s like an AI video factory for e-commerce, but for education.

    Which companies develop technologies for AI avatars?

    One of the key players in this field is the startup HeyGen, which created AI avatars for Harvard Business School. There are other companies offering similar solutions, for example, a Synthesia alternative, specializing in video generation from text and mass generation API.

    Can AI avatars be used to create advertising content?

    Absolutely. AI avatars and AI video for advertising are actively used to create AI face-swap clips, AI voiceovers, and AI writes scripts and edits videos. This significantly reduces the cost and speeds up the production of advertising content, making the effectiveness of AI versus real UGC very attractive.

    Conclusion

    The integration of AI avatars into Harvard Business School’s educational programs demonstrates a significant breakthrough in EdTech and AI content production. This not only increases the accessibility and quality of education but also opens new horizons for the application of artificial intelligence in various fields, from education to marketing.

    If you are looking for where to order mass video generation for crypto or other projects — the technology is already here. The future of education and content production lies with neural networks, and Harvard is already setting the pace. Learn more about creating AI commercials on our website.

  • Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    92.8% of dialogues in ChatGPT end without a transition to the website — this is Profound data that Kevin Indig analyzed in the digest on July 21. Measured on live traffic of a real product, the figure can be trusted. All search promotion relied on a single deal: you get to the top of search results, a person clicks the link to your site, and converting that visit into a lead is your concern. The link was the point where a business first touches a customer. In the AI response, this deal breaks at the very first step: the click most often simply doesn’t happen.

    Why 92.8% of dialogues in ChatGPT end without a transition to the website

    For several months, I’ve been measuring how ChatGPT, Perplexity, Alisa AQI, and GigaChat name brands in their responses: I run control prompts and see which model mentioned whom and which didn’t. Behind these runs, a figure surfaced that breaks the usual SEO logic — and made me change what I track for clients altogether. Let me break it down in order.

    Three weeks ago, we ran prompts for a client in the food delivery niche through ChatGPT. Usual routine: you type a question like “which delivery service to choose in Moscow,” and look at the response. At that point, the client had far more links from external sites than the nearest competitor. In Ahrefs — a service that calculates a site’s link weight — this is immediately visible: both the overall authority score is higher, and the number of different sites linking to it is one and a half times greater. ChatGPT named the competitor. The client — no. Didn’t mention it at all, not once in twenty prompts.

    I double-checked three times, changed the wording of the question, the date of the dialogue, and the region. The result was the same. For an hour and a half, I honestly couldn’t understand what was going on. Twenty years of website promotion taught a simple rule: the more links point to you, the higher you rank in Google and Yandex results, and therefore the more readily neural networks should name you. Here, the rule didn’t work. Only there was no search results page in the usual sense. There was a model that decided on its own whom to name and whom not to. And it decided not by a link counter.

    A brand mention cannot be bought with links — it accumulates like reputation

    At the same time, AI traffic itself is tiny in volume — Ahrefs reports that ChatGPT accounts for about 0.19% of all link transitions on the internet, compared to 42% for Google. Ridiculously small if you compare head-on. But here’s what’s more interesting: those few who do click from ChatGPT convert far more readily — conversion is about 7.1%, and the visit itself is valued 4.4 times higher than a regular one. Fewer people reach the site, but those who do — came ready to make a purchase or any other target action.

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    And here’s an important twist. If the decision is made BEFORE the click, inside the model’s response itself, then you need to fight not for the click. You need to fight for how you’re named at the moment when the click hasn’t happened yet and, most likely, won’t happen at all. A mention in a ChatGPT response is not structured like a spot in search results. A spot can be earned by working on the site — links, loading speed, technical cleanup. A mention can’t be bought that way. The model gathers it from two sources: from the texts it was trained on and from pages it pulls up right during the response. And what decides is not the number of links, but how the brand is generally written about — in reviews, on forums, in industry articles, in comparisons.

    Search promotion used to be about taking top positions, because a position led to a click on the site. Promotion in AI answer engines works differently: you have to fight for the mention itself, because a click may not happen at all, and the person will still make a decision — based on how the model named the brand. A link is a one-time asset. It works as long as the page holds in the search results, as long as the site is alive, as long as the algorithm values it. A mention accumulates differently: it is reputation that has already settled into the texts on which the model was trained and which it reads now. Remove one article — the mention will not go anywhere; it is spread across dozens of sources.

    This is where my mistake with that food delivery client was. His link profile was strong, but almost all of it came from aggregators and directories, where the brand is simply listed in a list. The competitor had fewer links, but had three detailed editorial reviews describing how the service differs from others. The model was trained on them, among other things. It did not count links — it read context. The first place in Google, by the way, does not at all guarantee a mention in ChatGPT. We checked this on several clients separately: search and AI engines have different selection mechanics, and the first place in regular search results does not by itself turn into a line inside the model’s answer.

    Where a link still brings a client, and where the question is closed right in the answer

    The link has not died entirely — it is important not to confuse this. In regular Google, 68% of searches in the US by early 2026 also end without a click, according to SparkToro citing Search Engine Land. An answer without a click to the site has also come to good old search, it is just that it was visible there earlier — through blocks with ready answers, knowledge cards, and direct answers at the top of the results.

    The link still works where the decision is made AFTER the first touch: price comparison, reading reviews, technical documentation, everything that requires going into details that simply do not fit in the model’s short answer. It works in niches with a long decision-making cycle — there, a person will still reach the site, just later. The link does not work where the question is closed with one phrase in the answer. “Which delivery service to choose” — closed with a phrase. “How much does delivery from a specific restaurant in a specific area cost tomorrow evening” — not closed, a click is needed there. The same business lives on both sides of this boundary — it all depends on which specific query the user asked.

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    What I now measure for clients instead of search positions

    I stopped looking only at positions in the search results and added a separate measurement: how often and in what context models mention the client’s brand directly, without a click, without a transition. We run control prompts — real audience questions — through ChatGPT, Perplexity, Alisa AI, and GigaChat, and see whether the model names the brand, in what order relative to competitors, and with what wording. ChatGPT is not the only one here. Perplexity builds its answer almost entirely from cited sources and shows them as a list — the model readily takes from articles on third-party platforms. Alisa AI mixes in fresh Yandex results, GigaChat answers in its own way. A brand that sounds in one model may be silent in another — so one ChatGPT is not enough for the measurement.

    From this, three things emerged that I now advise any marketer to track:

    • Share of mentions among top competitors for your own key questions: a specific percentage for a specific set of prompts, without general ratings.
    • Tone of phrasing: the model may mention the brand neutrally, or it may add an evaluative word like “trusted” or “expensive” — this influences choice more than the mere fact of mention.
    • Sources from which the model apparently draws this phrasing: often it’s one or two articles — these should be prioritized for strengthening, instead of spreading the budget across dozens of platforms.

    With that food delivery client, we ultimately didn’t chase new links. We wrote several detailed materials about the product on platforms that the model clearly reads and cites — and after a month and a half, the mention appeared, and visibility in AI responses grew. The client had more links, but ChatGPT named a competitor. Now we know why.

    Frequently Asked Questions

    How to measure brand mentions in ChatGPT?

    Run control prompts — real audience questions — through ChatGPT, Perplexity, Alice AI, and GigaChat. Calculate the share of mentions among top competitors, record the tone and the sources from which the model draws information.

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    Can you buy a mention in neural networks with links?

    No. Links work in classic search, but neural networks don’t count them directly. A mention depends on how the brand is written about in reviews, articles, and forums — it’s reputation that accumulates in the texts on which the model is trained.

    What to do if the brand is not mentioned in ChatGPT?

    Find the platforms that the model cites most often and place detailed materials about the product there. Strengthen editorial reviews, comparisons, and expert articles — they influence mentions more than link mass.

    Should you abandon SEO in favor of neural networks?

    No. Links still work in niches with a long decision-making cycle and for transactional queries. The optimal strategy is to combine classic SEO with work on mentions in AI responses.

    Conclusion

    The bottom line is simple: 92.8% of dialogues in ChatGPT end without a click, but the decision to choose a brand has already been made. A link is a one-time asset; a mention is cumulative reputation. To win in AI search results, stop chasing links and start managing how you are written about in the texts that models read. Run control prompts, track the share of mentions and tone — and you’ll see where you’re really losing customers. Start with an audit of your mentions today.