[ AI Product Visibility ]

Make your products easier for AI to understand

AI Product Visibility examines how your products are read and compared in AI answers. I review a sample of product pages, variants and catalog data to identify missing or ambiguous information. You receive the observed issues and a prioritized correction plan for your team, tied to your customers' questions and buying decisions.

Assess your catalog
[ The decision ]
Which information makes your products difficult to understand and compare.
[ The deliverable ]
An agreed sample review and correction specifications for pages, variants and data.
[ Who does what ]
I identify the gaps. Your e-commerce team updates the catalog and website.

what you receive

  • Visibility assessment of the agreed product and category sample
  • Comparison with alternative products observed in AI answers
  • List of gaps in product pages, variants, structured data and feeds
  • Recommendations for buying guides and comparison pages
  • Prioritized correction plan for your e-commerce team

who it's for

E-commerce brands whose customers compare alternatives before buying

When users ask AI what to buy, you need to know whether it recommends you or a competitor.

Brands with digital catalogs

You have a catalog, product pages, and campaigns, but do not know whether the available information is sufficient to distinguish and compare products.

E-commerce teams with SEO in place

Ranking and traffic are not enough if AI recommendations cite marketplaces or alternative products.

Sound familiar? Send me the context and I'll tell you whether starting here makes sense.

Assess your catalog

how we work

  1. 01

    Product query map

    I map commercial prompts by category, use case, price, comparison, problem, alternative, and buying intent.

  2. 02

    Recommendation audit

    I check whether ChatGPT, Perplexity, Gemini, Claude, and Google AI recommend your products or your competitors' products.

  3. 03

    Product pages and catalog readiness

    I review product pages, categories, schema, merchant data, attributes, variants, images, reviews, and FAQ content.

  4. 04

    Priority content gaps

    I define what is missing to make products easier to understand: buying guides, comparison pages, attributes, tables, and verifiable claims.

  5. 05

    Action plan

    I deliver a sequence of improvements for product pages, categories and source content, prioritized by commercial impact.

how it starts

[ First step required ]

We select a representative product sample and collect pages, variants, feeds and available data. The sample and buying questions are agreed before the assessment, so the findings can inform corrections across the wider catalog.

[ after the baseline ]

After the initial assessment, AI Visibility Monitor compares new observations every 90 days using the same question set. It is a separate recurring engagement for reviewing changes and catalog priorities.

AI Visibility Monitor

[ advertising on ChatGPT ]

For eligible catalogs, a separate pilot can test ChatGPT Ads and product feeds without attributing organic effects to the campaign.

Explore ChatGPT Ads Pilot

scope and boundaries

  • I deliver correction specifications; platform code changes remain with your e-commerce team.
  • The first cycle covers the agreed sample, not the entire catalog.
  • Recommendations require verifiable data; missing attributes are not filled with generic values.
  • I do not run campaigns or advertising feeds inside this service. The paid channel, where eligible, has a separate pilot.

[ the next step ]

After correcting the sample, your team can apply the specifications to the wider catalog. If the same issues return with each update, we can assess how to organize data, responsibilities and checks in a reusable process.

Integrate AI into business processes

related reading

Want to know where to start?

Send context, website, and objective. I'll reply with the most sensible first step.

Assess your catalog