What is an AI shopping visibility platform?
An AI shopping visibility platform monitors how a merchant appears in AI shopping answers for the queries a merchant cares about. It records what each engine surfaces, classifies the appearances, and tracks changes over time so a team can prioritize catalog and content work.
A visibility platform is distinct from a feed distribution tool. Distribution sends product information to a destination. Visibility measures whether that information, or the merchant's brand, then shows up in answers. Paz.ai does both, but this page is about the visibility measurement.
What Paz.ai measures
For each configured query and engine, Paz records four appearance types, position, found rate, and trends.
Product card
A structured product result the engine renders, such as an image, price, merchant, and link where the engine provides them.
Product mention
A natural-language reference to a merchant product in the response without a structured card.
Brand mention
A reference to the merchant brand in the response without a specific product.
Source citation
An outbound URL the engine cites as a source for the response.
A brand mention without a URL is not a source citation. Paz records them separately so a merchant can distinguish being named from being cited.
Which AI engines Paz.ai monitors
- Google AI Mode: monitored with per-engine appearance counts, found rate, position, and trends.
- ChatGPT: monitored with per-engine appearance counts, found rate, position, and trends.
- Perplexity: monitored with per-engine appearance counts, found rate, position, and trends.
- Google AI Overviews: captured and displayed with a tri-state outcome (present, not shown, failed). Diagnostic in Shopping Visibility and reported separately.
Paz monitors AI shopping visibility across Google AI Mode, ChatGPT, Perplexity, and Google AI Overviews. See the engine table for what is measured and each plan's monitoring cadence.
How product cards, mentions, and citations are detected
Paz runs a configured shopper query against an implemented engine and reads what the engine returns. A structured product result with image, price, merchant, and link is recorded as a product card. A natural-language reference to a merchant product is recorded as a product mention. A reference to the brand without a specific product is recorded as a brand mention. An outbound URL the engine cites as a source is recorded as a source citation.
Paz reports appearance counts, found rate, position, and trends per engine. See the methodology page for the found-rate denominator and other reporting definitions.
How to evaluate AI shopping visibility software
Use this checklist to evaluate any AI shopping visibility platform, including Paz.ai.
- Does it monitor the engines your shoppers actually use?
- Does it separate product cards, product mentions, brand mentions, and source citations?
- Does it record position and found rate as observed values and trends, not grades?
- Does it treat Google AI Overviews as diagnostic when an overview is not triggered?
- Does it connect visibility gaps to catalog or content fixes?
- Does it document cadence and reporting methods clearly?
Example visibility report
The visibility report shows query results and the four-type appearance breakdown. The images below are illustrative Paz.ai product interface views, not a specific customer's data.
Monitoring cadence and data freshness
Monitoring runs on a scheduled cadence: weekly on Starter, daily on Growth and Enterprise.
Cadence reflects when Paz runs configured queries. A merchant reviews results on the cadence their plan provides.
Where Paz.ai fits
Paz fits commerce teams that want to monitor product and brand visibility in AI shopping, improve catalog data, distribute to supported destinations, and attribute AI-referred traffic.
Teams can use those observations to prioritize catalog improvements, distribute updated product information to supported destinations, and measure AI-referred traffic.
Workflow coverage by plan
| Feature | Scope | Plans |
|---|---|---|
| Shopping visibility monitoring | Google AI Mode, ChatGPT, Perplexity, Google AI Overviews | All plans |
| Cadence | Weekly on Starter, daily on Growth and Enterprise | All plans |
| Appearance classification | Product card, product mention, brand mention, source citation | All plans |
| Google AI Overviews treatment | Diagnostic; tri-state outcome; reported separately | All plans |
| Catalog optimization | Human-in-the-loop proposals | All plans |
| Distribution destinations | Google Merchant Center, OpenAI Commerce feed, UCP, ChatGPT App or MCP | Growth and Enterprise; ChatGPT App or MCP on Enterprise |
| AI traffic attribution | Paz pixel and traffic-attribution APIs | Growth and Enterprise |
See public pricing for current plan details.
Frequently asked questions
What is an AI shopping visibility platform?+
Which AI engines does Paz.ai monitor?+
How often does Paz.ai monitor?+
How does Paz.ai help teams improve AI shopping visibility?+
Choose your next step
Start with a product-level readiness check, review the operating workflow, or compare current plan coverage.
Related
- Shopping Visibility methodology : engines, cadence, definitions, and reporting methods
- AI visibility for commerce : definition
- Answer engine optimization (AEO) : definition
- Generative engine optimization (GEO) : definition
- How to optimize a product feed for AI search : eight-step checklist
- AEO and GEO optimization software for ecommerce : software selection
- AI Readiness : evaluate a product URL
- Pricing : current plan details
- Press : public partner evidence