Retail & commerce20253–4 months
Client: An omnichannel retailer
One of the project’s screens, in a phone frame. It is shown again with its caption under “On screen”.
At a glance
Search and AI visibility measurement
Structured product data and feeds
Answer-shaped category content
From brief to result
The brief in full, how we approached it, what we built and what it set out to change.
Shoppers were asking AI assistants which product to buy, and the answers cited review sites and forums — rarely the retailer’s own guides, even where those guides were the better source. A search ranking no longer described how visible the retailer was.
The brief: be cited in AI answers, not only ranked in search results.
We fixed the questions before touching the content: a panel of priority questions shoppers actually ask, checked on a schedule across the main AI assistants, so visibility could be measured rather than guessed.
Then we made the product data and the category content easy to cite: complete structured data, clean feeds, and guides written as direct answers with the evidence beside them.
Priority questions by category, each with the answer we would want cited.
The product data model, feeds and schema markup brought to complete.
Category guides rewritten as direct answers, each with its sources.
The panel re-run on a schedule; citations reported by category and by assistant.
Structured product data, schema markup and answer-shaped content, tracked against a fixed panel of priority questions across AI assistants.
The work sets out to make the retailer’s product data complete and its guides citable, and gives it a way to see, question by question, which assistants cite its guides and which cite someone else.
Share of AI answers is read from the fixed panel. The client approves any figure before it is published.
Picture story
The pictures on this page are illustrative: licensed stock photography and code-built mock-ups chosen to show the setting, not the client’s own work. Credits are at the foot of the page.
On screen
Illustrative screens, built in code to show the kind of screen the programme produced — not the client’s own. Open any of them full screen.
Before and after
An illustrative before and after, built in code to show the kind of change the work made — not the client’s own screens. Drag across the picture to compare.
Before · not cited
After · cited
Outcomes
What each measure is compared with, when it is read and who reports it — and the results, once the client approves them.
Share of AI answers citing the brand
Organic revenue from priority categories
Product data completeness
Figures pending client approval
We publish results only with the client’s written approval. Until then, the plan beside this is what the programme is judged on, and we can walk you through it under NDA.
Credits
People are named only with their agreement.
Licensed stock photography and code-built mock-ups, chosen to show the setting — not the client’s own work.
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