OuterciteOutercite

Shopping overview

Product-level visibility: which of your products AI engines recommend for real shopping questions, and which are invisible. In beta.

Brand visibility and product visibility are different problems. "Which CRM should I use" names companies. "What is the best waterproof hiking boot for wide feet" names products. Shopping measures the second one.

What you'll learn

  • What Shopping measures, and how it differs from the rest of the platform
  • How access works, and which plans include it
  • What the product caps mean in practice

What it measures

Your products, checked against shopping prompts on the chat engines, so you can see:

  • which products get named in answers to real shopping questions
  • which are invisible
  • what the answers say about them, in their own words
  • where a competitor's product is named instead

It is the same evidence model as the rest of the product: counted checks, verbatim answers, no invented numbers.

Beta access

Shopping is in beta. On the core plans you request access from the Shopping page and the team grants it. The Shopcite lanes include it, so they never see the request.

Being in beta means the surface is still moving. The data is real, and the shape of the screens is not yet settled.

Which plans, and the caps

Two things are capped: how many products you can track, and how many shopping prompts.

The caps differ by lane, and the Shopcite lanes are the shopping-first versions of Starter and Scale at the same price as their core twins. Current figures live on the pricing page, which is generated from the same configuration the product enforces.

The practical point: a product check is metered per product, per engine, per check window, so a catalogue of two thousand products is not a thing you track exhaustively. Track the products that earn the coverage.

Choosing which products to track

  1. Your margin leaders, not your bestsellers. Visibility on a low-margin product is a cost.
  2. Products with a describable buyer. Engines name products with a qualifier attached: for wide feet, for a small kitchen, for beginners. A product with no such angle is hard to recommend.
  3. Products where you lose deals to one competitor. The answer usually tells you why.

What it will not do

  • It will not price-optimise. Prices are shown as context, not as a recommendation.
  • It will not cover every engine. Shopping questions are asked of the chat engines, and AI Overviews is a different surface with different behaviour.
  • It will not fix an unquotable product page. If the specification only exists in an image, no engine can quote it.

Try this in Outercite

Open Shopping. If you are on a core plan, request access. If you already have it, connect the store and start with ten products you would defend in a margin meeting.

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