Shopping in ChatGPT means that part of customers' decisions is moving into conversations with an AI assistant that suggests brands, products and purchase options. For online stores in Poland, this is a signal to optimize their offer and content for AI answers, measure whether the brand is mentioned and adapt marketing to consumers' new habits.
How is ChatGPT changing the way people shop?
ChatGPT and similar models have become, for many people, the first layer of advice before a visit to an online store. Instead of classic search, the customer holds a conversation: asking for recommendations, comparisons, pros and cons, and tips on what to look out for. Such a dialogue shortens the path from need to decision and moves the moment of discovering a brand to the stage of the AI's suggestions.
According to the Adyen Index: Retail Report 2025 study, 37% of Poles use ChatGPT and other AI assistants when shopping. That is no longer a niche behavior but a channel that affects traffic and conversion in e-commerce. According to the same study, 52% of consumers use AI to discover new brands, so an AI suggestion is sometimes the first contact with your offer – before the customer visits the site or sees an ad.
The buying journey itself is changing as a result. Customers phrase questions in full sentences and expect direct answers, not a list of links. Reasoned recommendations, arguments and the sources the AI cites carry more weight, and AI readily cites content that answers users' questions clearly and precisely. The funnel stops being linear: some comparisons and objections are settled in the conversation with the assistant, so the person who lands on your site is already closer to buying.
For a store this means one thing: AI needs something to "assemble" a good answer from. It needs clear product descriptions, clear return policies, reliable guides and a FAQ.
What are the benefits of using AI in e-commerce?
AI brings practical benefits both to the customer and to store operations. The most visible is better recommendation accuracy: the model connects the user's needs with the right assortment based on descriptions of uses, usage context and preferences. If the brand's content is clear, AI uses it more often and customers discover the right products faster – this translates into better conversion from informational traffic, because the answer shortens the path to purchase.
The second group of benefits concerns customer service. Chatbots and sales assistants answer objections consistently: they explain differences between variants, clarify technical parameters and sharpen the selection criteria. They also surface the most important information, such as availability, delivery, returns or compatibility, before frustration or cart abandonment sets in. Along the way they take over repetitive tasks – summaries, comparison shortcuts, answers to frequent questions, and support with category descriptions and guides.
A single language engine can also keep current rules, arguments and policies consistent across all your own channels, which gives you better control of the message. The customer searches and compares less across many browser tabs, and the store gains a predictable process and can scale service without losing quality.
How do you adapt your marketing strategy to changes in e-commerce?
Effective adaptation doesn't require radical moves, just systematic steps that help AI notice and understand your offer.
Start by mapping the questions AI answers. Collect topics and intents such as "what to choose for…", "which [product type] for [use]" or "what to look out for when…", and then turn them into specific content: guides, checklists, comparisons and a short FAQ under each category.
Next, improve the quality of the sources AI can draw from. The product page should give parameters, use, compatibility, care and package contents. Delivery, return, warranty and service policies must be visible and written in the language of benefits, with concrete scenarios. Lay it all out in a clear structure – headings, lists, question-and-answer sections – so the model can easily pull out the answer. In parallel, tidy up product data: standardize attribute names and values, remove duplicates and mismatches in feeds, and update availability statuses and variant information.
The next step is content that can be cited. Decision guides, comparison sheets and glossaries of terms are materials AI can quote directly. Also publish expert articles signed with a first and last name, because AI interprets content with clear authorship and topic better. In campaigns, move to "AI-first" communication: instead of slogans alone, give answers to the questions "who is it for", "what for" and "when not to choose it", and on landing pages and in ads use the language of intent that customers use when talking to AI.
Finally, measure and improve. Regularly check whether assistants mention your brand for key questions and who they put alongside it, and fill the "blind spots", meaning topics where competitors appear and you are missing, with new, better answers. Turn the findings into concrete changes. If AI skips your product because of information gaps, fill in the content and data. If it has doubts about policies, simplify and clarify the rules. And when it cites external sources, build your own equivalents on your site – more complete and easier to understand. That way you treat AI as a new channel for distributing information about the brand, where consistency and completeness of content count, not tricks.
What are the challenges of shopping online with AI?
The biggest risk is reliability. AI can give wrong or outdated advice, so your content and product data must be clear and current. Tied to this is the consistency of the offer: the model compares claims from different sources, so a mismatch in prices, availability or parameters between your site, feeds and PR materials can end with your proposal being skipped.
Attribution is changing too. Some answers are given without clicking links, so the balance between discovery and site visits shifts, and counting clicks alone is no longer enough – you also need to measure visibility in AI answers. Another problem is data bias: if competitors' content dominates the web, AI may cite it more often, which argues for systematically publishing material that organizes knowledge in your niche. Finally, generative content can make fraud and impersonation easier, so it is worth strengthening credibility signals and official contact channels.
In practice, the winner is whoever reduces uncertainty on the model's side: provides unambiguous, current information and keeps it consistent across all channels.
How do you monitor brand visibility in AI answers?
Monitoring is not about position. In AI answers, what counts is whether the brand is mentioned, in what context and for which questions. A simple action plan:
- Define a set of questions: customer problems, comparisons, recommendations for your category.
- Check four sources of answers: ChatGPT, Gemini, Perplexity and Google AI (AI Overviews), because they differ in style and sources.
- Record whether the brand was mentioned, who the AI recommends alongside you, which sources it cites and what arguments it gives.
- Mark the "blind spots": questions where competitors are mentioned and your brand is missing.
- Compare visibility week to week and respond with changes to content or product data.
Visibility in AI answers is today a metric that really affects sales – if you aren't mentioned, you don't exist in the customer's conversation with the assistant. Regular measurement lets you detect blind spots, understand where AI gets its knowledge and which arguments persuade users. On that basis you can plan content, PR and optimizations that the model will start to cite.
If you want to do this systematically, you can use Attent – a tool that monitors brand visibility in AI answers. Every week it asks your questions in ChatGPT, Gemini, Perplexity and Google AI and shows whether the brand was mentioned, who the AI recommends alongside you, which sources it takes its knowledge from and where the blind spots are. On top of that you get a brand AI visibility score, share of voice against competitors, alerts about changes, a leadership report in PDF, a content generator and a Google Search Console integration. 78 companies use the tool, and you can book a call about monitoring at getattent.com.
What are the future AI-related trends in e-commerce?
We are approaching a stage where assistants will not only advise but also carry out some shopping tasks. There is more and more talk of AI agents taking over part of households' everyday shopping. The customer will set the criteria and budget, and the agent will select the products itself from among trusted brands and sources.
For stores this means a few shifts. Assistants will prefer offers with clear delivery, return and service terms that are easy to verify and cite. Content prepared as unambiguous answers and comparisons will more often make it into recommendations. For an agent to quickly assemble an offer that meets the customer's conditions, attributes in feeds and on pages must be consistent. SEO alone will no longer be enough – brands will regularly measure whether they are mentioned in AI answers to key questions and how their share of voice changes over time.
The advantage will go to stores that deliberately design content and data around how AI understands customers' needs and regularly check whether they are present in recommendations.
How do you protect customers in the context of AI?
Security starts with clear trust signals: company details, terms and conditions, and return and warranty policies written in plain language. Alongside them, official contact channels should be well visible – email, phone, live chat – so the customer always knows where to verify information.
Sign guides and answers with a first and last name and update them together with changes to the offer, because verifiable content is harder to fake and easier to cite. Also add short tips for customers on how to recognize official communications and avoid impersonation attempts. That way you reduce the risk of misinformation and make it easier for AI to cite correct, current information about your brand.
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Book a callFrequently asked questions
What does an online purchase mean?
An online purchase is the process of choosing and acquiring a product or service over the internet – from looking up information, through comparing offers, to payment and delivery. More and more often, part of this journey is a conversation with an AI assistant that helps clarify needs, compare options and point to brands that meet your criteria.
What is e-commerce about?
E-commerce is the sale of products and services over the internet, combining the offer, informational content, customer service and logistics in one experience. AI plays a growing role here: it helps customers find the right product faster and helps stores create clear, citable answers to the questions that come up before a purchase.
Is e-commerce safe?
It can be safe if the store maintains transparent payment, delivery and return rules as well as clear contact channels. In the context of AI, it is important that content is current and verifiable, which reduces the risk of misinformation. On the customer's side, extra protection comes from paying attention to official communications and website addresses.
How many online stores are there in Poland?
Estimates differ depending on the definition of a store and the data source, and the number of stores changes constantly. Whatever the exact figure, competition is high, so it is worth making sure your brand is mentioned in AI answers to customers' key questions – a growing source of offer discovery.
What are the advantages of shopping online?
Convenience, a wide choice and quick comparison of options without leaving home. AI additionally organizes information: it helps clarify needs, points out differences between products and reminds you of important conditions, such as delivery or returns. That shortens decision time and reduces the risk of a wrong purchase.
What are the disadvantages of shopping online?
No physical contact with the product, possible misunderstandings about parameters and the risk of misinformation. AI partly limits this, but it works only as well as its sources are good. That is why it is worth buying from stores with clear descriptions, clear policies and easy contact, and asking questions before finalizing the order if in doubt.
