More and more purchases start with a question to an AI. We check whether your store shows up in those answers and whether a shopping agent can complete a purchase on your site. Then we fix it and measure it every month.
A shopper asks ChatGPT, Gemini or Perplexity before deciding. The AI answers with three or four stores. If you're not there, you're not competing — they don't even see you to rule you out. The same is happening inside Google with AI Overviews.
You sell well, you have a solid catalogue and good service, but when someone asks about your sector the AI names others. There is no second page to appear on.
Many stores deny these crawlers access in their technical configuration without being aware of it. It's the most common issue and the fastest to fix.
Even if it finds you: if it can't pick the size, close the cookie banner or tell your product's button apart, it abandons the order and moves to another store.
That lost sale leaves no trace in your analytics: for a human customer your site works perfectly. It only surfaces if someone measures it.
Being recommended by the AI is useless if the agent can't finish the purchase afterwards. And vice versa. We work on both in the same project.
We measure your real presence across ChatGPT, Gemini, Perplexity, Claude and Google's AI answers for your sector's purchase queries. Then we work on your content and brand signals so you become a citable source: direct answers, concrete data, useful FAQs, structured data and brand consistency beyond your website.
Buying is a five-stage journey: enter, get oriented, pick the product, act and pay. With our own tool we measure all five on your key templates and tell you exactly where the agent gets stuck, with concrete tickets for your dev team.
Nobody controls OpenAI's or Google's models. Anyone guaranteeing you'll appear is selling smoke. We guarantee diagnosis, implementation and measurement.
We deliver what can be executed: the stage that cuts the purchase, the prioritised tickets and what gets measured next. No padding to justify the price.
An agent has to clear them in order, and gives up at the first one that fails. That's why the diagnosis isn't a list of errors: it's knowing where your journey breaks. Full context in AI shopping agents for your ecommerce.
Can it enter and read the page unobstructed? Cookie banners and overlays that can't be closed block 100% of visits.
Does it understand where it is and how the store is organised? Heading structure, navigation and breadcrumbs.
Can it identify the product, its price and its variant? This is where most journeys die: size or colour pickers the agent cannot use.
Can it perform the right action on the right product? Twenty identical buttons are twenty indistinguishable actions.
Can it fill in the details and complete the order? Unlabelled form fields turn the checkout into a dead end.
The result is a 0-100 score per template, with the blocking stage flagged. It's the metric we compare when we finish.
Six weeks with a closed scope. It starts with a diagnosis and ends with comparable numbers.
We test twenty to twenty-five purchase queries from your sector across the five engines and measure the agentic journey on your five key templates. Weeks 1 and 2.
We show you what the AI answers today, which competitors appear, where your purchase journey breaks and in what order to tackle it.
Citable content, FAQs from real queries, structured data, technical access and development tickets. Weeks 3 and 4.
We repeat the same queries and the same analysis: what changed, what index we close with and what comes in the next ninety days. Weeks 5 and 6.
We'd rather say it upfront than charge you for a project that won't pay off.
The bigger your revenue, the sooner the project pays for itself. If a small share of your sales already justifies the investment, this is your moment.
Health and pharmacy, nautical, home, sports, professional beauty and industrial B2B: long queries, comparisons and recommendation.
A store Google can't understand is a store AI models can't understand either. We start there, and this comes after.
Models refresh their information at their own pace. This is built and measured, not switched on.
No — it builds on it. A store Google cannot understand is a store AI models cannot understand either, so technical SEO comes first or in parallel. What changes is that here we also optimise for the engine that answers, not just the one that lists results.
No, and be wary of anyone who guarantees it: nobody controls OpenAI's or Google's models, just as nobody controls the search algorithm. What we do guarantee is the diagnosis, the implementation and a reproducible measurement that shows exactly where you stand every month.
The diagnosis is ready in two weeks, and changes go live in weeks three and four. Presence in AI answers depends on when each model refreshes its information: we've seen movement in weeks and also in months. That's why we measure continuously instead of promising a date.
We prepare the content and the structured data. Template changes can be applied by your team using the tickets we deliver — each one includes a code example — or by us, quoted separately depending on scope.
Yes. We work on the layer that usually goes untouched and hand the technical tickets to your team or directly to your agency. We're not here to replace anyone or question their work.
The name may go out of fashion; the work underneath won't. It's technical SEO, content and structured data — the same things you've been paying for over the years. Every improvement keeps performing in Google, improves mobile conversion and moves you forward on the European accessibility act. There is no scenario where the work is wasted.