SEO in the Era of Agentic Commerce. How to Prepare Your E-commerce for AI Customers and Agents

Agentic commerce will not make SEO disappear or lose its importance. It will remain a solid foundation that allows information about your store and products to be discovered and interpreted correctly.

So it is not the role of SEO that changes, but its audience.

Until now we optimized websites with Google’s algorithms and human users in mind. Now we will increasingly have to optimize them for AI systems as well, systems that analyze and compare offers on behalf of users and ultimately recommend specific products. AI agents are joining the audience for SEO, and they will have a growing influence on e-commerce conversion.

Visibility online is no longer one dimensional and centered on Google. The question “What position does product X hold in the search results?” is being replaced by “Can an AI agent find product X, understand our offer and trust the site?”. Modern digital search marketing will develop around exactly these questions.

In agentic commerce, the definition of visibility will cover:

• Citations, mentions and brand recommendations in AI answers
• Presence of products on the recommendation lists of AI agents
• Accessibility of the site for agents

For an agent to select your store as the place where it will buy on behalf of a customer, it has to be able to:

In practice this means that e-commerce store owners will have to pay much closer attention to the quality of their product data, so that it is complete and current and covers price, availability, clear return and warranty terms, product variants and applications.

Brand authority will matter too, and building it is supported by earning mentions of the brand and its products in credible, topically related sources (AI Authority Link Building), along with consistency between the brand information published everywhere online. Reviews also help increase trust in a site, so it is worth encouraging customers to leave them.

SEO is not the only thing gaining a new audience. The purchase path and the offer itself are gaining one too. In agentic commerce, an online store will design two different experiences in parallel: one for people and one for AI systems.

A customer needs an attractive visual presentation of the product, high quality photos and video, a product page that is friendly in terms of UX, but also emotion, storytelling and sales arguments that will convince them this is the perfect product for them.

Agents will need unambiguous, organized and current information that can be compared, verified and rendered. When you build the layer for agents, a helpful solution will be WebMCP, a new standard Google released in February this year, which lets a website expose specific, ready to call functions that AI agents can execute in the browser. Thanks to a WebMCP implementation, instead of guessing, an agent receives precise instructions on how to check product availability, how to add it to the cart and how to process the payment. For now this is still a solution in the testing phase, part of a public trial in the Chrome browser, but it is definitely worth watching, because there is a lot to suggest that solutions like this will be a fundamental element of agentic commerce.

Agentic commerce means the dispersal of standard purchase paths and, at the same time, the end of fighting for positions in a single ranking displayed to every user in the search engine. Agents are taking on the role of personal shopping advisors, which means they will present different, hyperpersonalized recommendations to each user, based on aspects such as:

• The budget set aside for the purchase
• Preferred brands
• Delivery date
• Store location
• Limitations and requirements indicated by the user

The KPIs used so far to assess the effectiveness of SEO work will not be enough in the world of agentic commerce. Considerable change and evolution are ahead of us in web analytics.

Over the next 5 to 10 years we face one of the biggest changes in digital analytics since e-commerce became widespread. Already today we see situations where a user starts the buying process in ChatGPT, Gemini or in Google with AI Overviews, and part of the decision path happens outside the brand’s website. Agentic commerce will accelerate this trend even further.

More important than the number of sessions or organic positions will be the metrics that measure brand presence in the AI ecosystem:

• The number of recommendations made by AI tools
• Brand presence in answers generated by LLMs
• Visibility in shopping agents
• Traffic from AI systems
• AI assisted conversions
• Transactions initiated and completed by agents

The attribution models used until now will gradually give way to new ones that account for the role of AI in purchase decisions. We already see gaps in analytics, with more and more conversions landing in the direct channel even though the actual purchase intent came from a recommendation made by an AI tool. In the future, companies will need far more advanced analytical methods that let them understand the influence of AI on sales, even when it is not directly visible in standard reports.

From the perspective of SEO and content marketing in the era of agentic commerce, four areas take on particular importance.

• Visibility and authority
  

Authority built with the help of SEO and AISO, based on a thoughtful brand presence in the media, in industry rankings and in credible sources, all helps you gain visibility in the recommendations of AI tools, which increasingly build their answers from a broad ecosystem of information rather than a single website.

• Content and product data
  

As part of preparing their sites for agentic commerce, e-commerce brands should above all take care of the quality of their content and product data. Complete specifications, applications, comparisons, usage examples, FAQs, transparent data and clear return, delivery and complaint policies are the key to an agent understanding your offer well and matching a product to the user’s purchase intent based on the information available.

Learn more: How to prepare e-commerce content for AI shopping agents? A practical guide

• Technical improvements
  

Research conducted by the SE Ranking platform indicates that 65% of the pages cited in AI Mode and 71% of the pages cited by ChatGPT contain structured data. While implementing schema alone is no guarantee that an agent will pick your store to complete a purchase, it makes data easier for bots to interpret and is worth treating as good practice.

Learn more: Structured data and AI Search: which schemas support visibility in AI answers?

Beyond that, it is worth taking care of your product feed, a simple purchase path and technical accessibility for agents, eventually with the help of the WebMCP standard mentioned earlier.

• Analytics
  

It is worth defining and adopting new KPIs right now, ones that match the need to monitor visibility in AI. The next step will be looking for tools and solutions that make it possible to collect and report data tied to AI and its influence on conversions and on the purchase path.