In 2025, more than 30% of e-commerce users in Ukraine made at least one purchasing decision based on artificial intelligence recommendations – and this number continues to grow exponentially. From our team’s experience, classic SEO promotion no longer guarantees getting into the client’s field of vision: generative models like ChatGPT and AI Overviews from Google create entirely new sales channels where traditional optimization methods lose effectiveness.
Today, businesses face the challenge: how not to lose traffic and sales when users increasingly consult ChatGPT instead of Google about what to buy, where to order, which brand to trust? Why do some products instantly get into AI recommendations, while others remain overlooked despite investments in advertising and promotion?
I am convinced that the first to master product promotion in ChatGPT will gain not only an advantage in traffic but also trust from a new audience. In this article, I will examine how BUSINESS SITE addresses visibility and sales growth in the era of artificial intelligence, and which strategic approaches work in Ukrainian realities.

Promotion of Products in ChatGPT – A New Sales Channel

ChatGPT and AI Overviews from Google have already changed the landscape of digital sales. Previously, users would enter a query in a search engine, visit sites, and compare offers. Today, they receive a structured, relevant response directly in a dialogue with AI. For e-commerce, this means ChatGPT becomes an independent platform where trust and purchase intention are formed.

In BUSINESS SITE’s practice, we observe that new clients are increasingly coming not from search engines but after AI assistant recommendations. For instance, when choosing home appliances or pharmaceutical products, a user asks ChatGPT: “Which air humidifier to choose for an apartment?” – and receives specific models, marketplace links, reviews, and even usage scenarios.

Key Scenarios of Interaction with AI Assistants:

  • Quick selection of products by parameters (price, characteristics, availability at “Nova Poshta”).
  • Personalized recommendations based on reviews and ratings.
  • Product comparisons taking user scenarios into account (the best smartphone up to 10,000 UAH with delivery through “PrivatBank”).

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For businesses, this opens new opportunities: getting into ChatGPT recommendations means being at the very center of the purchasing decision process.

How AI Product Output is Structured

ChatGPT and AI Overviews from Google form responses based on three key principles:

  • Structuredness: AI “likes” clearly structured data, product cards, lists, tables, FAQ.
  • Relevance: Priority is given to fresh, expert, semantically rich content that answers the user’s specific questions.
  • Trust in the source: ChatGPT more often recommends products and websites that confirm their authority with external signals: reviews, mentions, ratings, marketplace, and social media activity.

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According to BUSINESS SITE specialists, the formulation of a user query (“best reviews for laptops for studying”) directly influences which products and brands will appear in the AI output. Hence, it is important not only to optimize content but also to build the brand’s digital reputation.

Site Optimization for ChatGPT

In the era of generative models (ChatGPT, DeepSeak, Gemini, Grok 4, and others), those sites that speak the “AI language” will win. This is not just about SEO, but a deep work with the semantics, structure, and expertise of content – AIEO.

Key Site Requirements:

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  • Clear hierarchy of categories and subcategories.
  • A semantic core adapted for AI assistants.
  • GPT-friendly content: succinct, informative, structured product descriptions, usage scenarios, comparisons, FAQ.
From BUSINESS SITE’s experience, errors like “watered-down” descriptions, information duplication, and lack of structured blocks (e.g., comparison tables) significantly decrease the chances of getting into ChatGPT recommendations.

Structured Content for AI

Implementing a hierarchy of headings (H1-H3), lists, tables, and infographics makes content as understandable as possible for generative models. At BUSINESS SITE, we recommend building a product card with the following structure:

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  • Brief description: up to 2-3 sentences reflecting the essence and advantages.
  • Key features: a table or bulleted list.
  • Usage scenarios: specific examples (e.g., “ideal for office and home”).
  • Reviews and ratings: integration of real reviews from marketplaces (“Rozetka”, “Prom.ua”).
  • FAQ: answers to typical questions formatted with FAQPage microdata.
  • Comparison tables: if there are alternative products.
In a case from one of the e-commerce projects implemented by BUSINESS SITE, introducing such a structure increased the depth of product card view by 35% and enhanced the likelihood of appearing in AI output.

Technical Requirements for ChatGPT Indexing

For successful indexing by generative models, it is essential to ensure:

  • Openness of HTML code for ChatGPT-User-Agent, no blocks in robots.txt or nosnippet meta tags.
  • Minimization of JavaScript content: AI processes dynamic elements loaded with scripts less effectively.
  • Correct operation of API integrations (e.g., for displaying product availability at “Nova Poshta” or “Rozetka” warehouses).
  • Validation of page accessibility with microdata and crawling checking tools.
Practice at BUSINESS SITE showed: even small technical errors (e.g., hidden product description blocks) can lead to a site being excluded from AI output.

Microdata and Structured Data for AI Product Output

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Microdata according to the schema.org standard is the key to making generative models “understand” the structure of your site and products. Especially important are:
  • Product: detailed product description, features, price, availability.
  • Review and AggregateRating: integration of reviews and ratings from marketplaces and the site.
  • BreadcrumbList: navigational chains for better category indexing.
Implementing microdata allows obtaining rich snippets in AI output, increasing CTR and user trust. According to BUSINESS SITE’s experience, using schema.org/Product and Review increases the probability of being recommended by ChatGPT by 1.5-2 times.

How to Increase Trust in ChatGPT for Your Site

Generative models actively use FAQ and real reviews to shape recommendations. Thus, we recommend:

  • Formatting FAQ with FAQPage microdata to answer typical questions (“How to choose?”, “How to pay via ‘PrivatBank’?”).
  • Integrating reviews and ratings from marketplaces (“Rozetka”, “Prom.ua”), as well as collecting your own on the site.
  • Publishing case studies and usage scenarios, supported by real examples and numbers.
In one of the pharmaceutical company projects that the BUSINESS SITE team worked on, implementing review and case microdata increased AI-driven referrals by 28%.

External Signals for ChatGPT

ChatGPT and other generative models evaluate not only the site’s content but also its “reputation” in the external environment. Key external signals include:

  • Reviews and mentions on authoritative platforms: marketplaces, industry blogs, thematic portals.
  • Social media activity: regular publications, discussions, audience feedback.
  • Links and brand mentions: the more natural links and mentions, the higher AI trust.

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In BUSINESS SITE practices, we recommend integrating reviews from marketplaces (“Rozetka”, “Prom.ua”), launching review collection campaigns, and working with digital PR to create a positive information field.

Tracking and Analyzing AI Traffic

One of the key challenges is understanding how much traffic and sales are brought by AI output. Modern tools allow:
  • Using UTM tags to track transitions from AI assistants (e.g., ChatGPT, Gemini).
  • Analyzing User-Agent logs to identify visits with OpenAI-User-Agent.
  • Monitoring brand and product mentions in LLM through services like Ahrefs, AI References.
  • Evaluating ROI metrics for AI channels: cost of acquisition, average order value, LTV, conversion.

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In a case for an online store implemented by BUSINESS SITE, introducing UTM tags and analytics for AI sources made it possible to identify that up to 12% of new orders came precisely from ChatGPT recommendations – this became a justification for scaling the strategy.

Conclusion

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Those who first implement structured data, optimize content for generative models, and begin monitoring AI traffic will not only see sales growth but also gain a sustainable advantage in customer trust. BUSINESS SITE’s experience confirms: adapting to new formats of AI output is not a one-time task but a strategic process that already today determines e-commerce success in Ukraine.
I recommend starting with a site structure audit, implementing microdata, and setting up AI traffic analytics. This will not only get you into ChatGPT recommendations but also build a long-term digital strategy aligned with the challenges of the new era of artificial intelligence.