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Ahrefs' analysis shows that AI Chatbots are beginning to impact the customer journey, acting as a new referral layer. While traffic from tools like ChatGPT is still small compared to Google, preparing for an environment where AI search will influence product discovery is essential. AI Chatbots do not replace search engines but offer new opportunities for SEO through answer engine optimization. Content must be accurate and reliable, with a focus on E-E-A-T, to enhance brand visibility in AI-driven environments.
AI Chatbots have now entered the actual customer journey and not just the theoretical discussion around AI. The interesting finding from Ahrefs' analysis is that visits coming from tools like ChatGPT, Perplexity AI, Google Gemini, Microsoft Copilot and Claude are already present in the analytics of many websites, but still remain small in absolute volume compared to organic traffic from Google. For an e-commerce owner, this means two things at once: first, there is no need to panic or hastily abandon the classic SEO- Secondly, there is a clear reason to start preparing now for an environment where generative AI search will increasingly influence the discovery of products, brands and solutions.
The key conclusion is not that AI Chatbots are directly replacing search engines. The more practical conclusion is that they act as a new referral layer between user intent and website visit. The user doesn't necessarily type a keyword phrase like “best running shoes for asphalt”, but asks a more complex question: “I want asphalt running shoes, I have a neutral footprint and a budget of up to 120 euros, what should I look for?” If the content of an e-shop is structured, reliable and helpful, it is more likely to be used as a source or referred to indirectly by a conversational interface. This is the essence of answer engine optimization, i.e. optimizing content to be understandable, usable and reliable for answer engines.
In the breakdown of AI chatbot traffic presented by Ahrefs, ChatGPT appears as the dominant referrer, followed by other tools such as Perplexity AI, Google Gemini, Microsoft Copilot, Claude and smaller platforms. This is important because it shows that the market is not homogeneous: each platform has a different way of responding, different referral behaviour and a different degree of connection to the web. As shown in the graph below, the picture of AI chatbot traffic today is mainly concentrated around a few big players.
The traditional digital marketing journey had a relatively clear logic: the user searches, sees results, compares, clicks, reads and buys. With AI Chatbots, the journey becomes more condensed. The user can ask for product comparison, feature interpretation, usage-based recommendations, and even a short list of options without visiting ten different sites. This creates a new challenge for e-commerce SEO: the brand must be present not only in traditional search results, but also in the data, references and responses used by AI tools.
This change is directly linked to the phenomenon of zero click search. The more answers are given directly in the search engine or chatbot interface, the less obvious it is that the user will go from the results page to the site. This is not to say that content marketing loses its value. Rather, it means that content needs to become more accurate, more informed and more useful. A generic 500-word article with repetitive keywords will hardly gain a place in an AI-driven environment. A comprehensive buying guide with real criteria, comparisons, FAQs, structured data (Schema markup guide: what it is and how to use it for better SEO), expert input and clear product information has a much better perspective.
Gartner has predicted that the volume of traditional search engine queries may decrease by 25% by 2026 as users turn more to AI chatbots and virtual agents. This prediction should not be read as “SEO is ending”, but as an indication that SEO strategy needs an upgrade. As shown in the chart below, if we take 2024 as an index of 100, Gartner's prediction corresponds to an index of 75 for 2026.
For an e-shop, the discussion around AI Chatbots should not be limited to whether “they currently bring enough traffic”. The right question is different: what content, product data and trust signals are needed to keep the brand visible when search becomes more conversational? AI search optimization does not replace technical SEO, backlinks, loading speed or category page quality. It extends them. An e-shop that has poor product descriptions, incomplete schema markup, unclear return policies and weak informational content doesn't just lose organic rankings; it also loses chances to be recognized as a trusted source by generative AI search systems.
On a practical level, AI Chatbots prefer content that clearly answers real questions. If you sell fitness equipment, it's not enough to have a “fitness treadmills” category. You need guides like “how to choose a treadmill for a small apartment”, “treadmill or elliptical for weight loss”, “what does CHP motor power mean” and “what features affect noise”. If you sell cosmetics, you need content that explains ingredients, skin types, contraindications, frequency of use and product combinations. This type of content serves the user, but also gives answer engines material that can be analyzed and leveraged.
This is where E-E-A-T comes in strongly: Experience, Expertise, Authoritativeness, Trustworthiness. In e-commerce, E-E-A-T is not a theoretical luxury. It is a commercial advantage. Add names of editors or experts where it makes sense, explain product selection methodology, show real tests, mention technical specifications, incorporate reviews, answer questions before the customer asks them, and keep the information up to date. AI Chatbots don't “buy” from you, but they can influence which brands the customer will consider. This changes the importance of brand visibility and makes digital marketing more closely tied to information quality.
A practical plan for e-commerce owners should start from data rather than general assumptions. A 90-day period is enough time to lay the groundwork, measure existing AI chatbot traffic and create content that can perform in both organic search and responsive environments such as ChatGPT, Perplexity AI, Google Gemini and Microsoft Copilot.
Step 1: Check analytics for referral traffic from AI platforms. Look for domains and referrers such as chat.openai.com, chatgpt.com, perplexity.ai, gemini.google.com, copilot.microsoft.com and claude.ai. Don't just look at the number of sessions. Consider engagement rate, time on site, assisted conversions, add-to-cart events and revenue attribution where available.
Step 2: Map the customers' questions. Gather queries from Google Search Console, site search, customer support, emails, live chat, reviews and social media comments. Then group the queries by purchase stage: information, comparison, selection, trust, after-sales. This mapping is the basis for content marketing that isn't just written for keywords, but for actual purchase decisions.
Step 3: Create or upgrade market drivers. Each major product category needs a detailed guide that explains selection criteria, common mistakes, technical terms, suggestions by need, and clear FAQs. The page's Focus Keyword can remain a classic SEO keyword, but the content should also cover long-tail conversational questions.
Step 4: Improve product pages. Product descriptions should answer “who it's for”, “what problem it solves”, “when it's not suitable”, “what it compares to” and “what the buyer should look out for”. Add structured data for Product, Review, FAQ where applicable, as well as clear information on availability, shipping, warranty and returns.
Step 5: Build brand credibility. Post pages about your team, experience, quality policies, partnerships and certifications. If you have a physical store, showroom, technical department or expert consultants, highlight them. AI Chatbots leverage trust marks that exist publicly on the web.
Step 6: Monitor mentions and citations. Ask test questions in the main AI tools for categories you are interested in. See which brands are mentioned, which sources are used, and which features are highlighted. This isn't absolute measurement, but it's useful qualitative research on how models perceive your market.
Step 7: Count by month and adjust. AI chatbot traffic may be small today, but the trend matters more than the instantaneous percentage. Create a simple dashboard with sessions of AI referrers, conversions, top landing pages, branded mentions and organic performance of new leads.
One point that is often overlooked is the quality of visits. If ChatGPT traffic or Perplexity AI traffic brings a few but highly targeted visits, the conversion rate may be higher than that of a generic informational keyword. Conversely, a high volume with no commercial intent does not have the same value. Therefore, the right question is not only “how much traffic do AI Chatbots bring?”, but “what is the quality of intent of this traffic and which pages receive it?”.
Ahrefs' analysis of AI chatbot traffic shows a market in early but substantial transition. AI Chatbots do not yet have the volume of Google, but they have already begun to influence the way users search, compare and decide. For an e-shop, the right strategy is not to abandon SEO, but to evolve it. It needs technical excellence, clean architecture, fast pages, reliable content, structured data, a strong brand and real customer service to answer customer questions.
The big opportunity lies in the fact that most businesses don't yet have an organized strategy for AI search optimization. Those that start now can build a foundation before the channel becomes too competitive. Content written with expertise, accuracy and commercial utility will continue to perform in organic search, answer engines, social discovery and conversational commerce. In other words, AI Chatbots do not diminish the need for quality digital marketing. They make it more imperative.
Ahrefs Blog: AI Chatbot Traffic Analysis
Gartner: Search engine volume will drop 25% by 2026 due to AI chatbots and virtual agents
Google Search Central: Introduction to Structured Data
Google Search Central: Creating Helpful, Reliable, People-First Content
