Direct answer

Merchant Center now has an AI-native visibility report built around conversational shopping, not classic keyword rankings. The strongest feature may be the least glamorous one: it shows which product terms and structured attributes shoppers care about while exposing where your catalog is incomplete.

What to remember
  • Merchant Center now has an AI-native visibility report built around conversational shopping, not classic keyword rankings. The strongest feature may be the least glamorous one: it shows which product terms and structured attributes shoppers care about while exposing where your catalog is incomplete.
  • Google Merchant Center now has an AI Performance Insights report in pilot for a limited number of U.S.
  • Google says it helps merchants understand how their brands and products appear across conversational AI shopping experiences such as: AI Mode; AI Overviews.

01

Preconditions

Merchant Center now has an AI-native visibility report built around conversational shopping, not classic keyword rankings. The strongest feature may be the least glamorous one: it shows which product terms and structured attributes shoppers care about while exposing where your catalog is incomplete.

Google Merchant Center now has an AI Performance Insights report in pilot for a limited number of U.S. accounts.

Google says it helps merchants understand how their brands and products appear across conversational AI shopping experiences such as:

  • AI Mode;
  • AI Overviews.

Current reporting includes:

  • share of voice;
  • competitor average share;
  • query frequency;
  • query type;
  • shopping journey phases;
  • frequently used AI shopping terms;
  • popular product attributes.

The current report is limited to organic AI traffic, not paid Ads traffic.

Why this is one of the most important new ecommerce reports.

Traditional Merchant Center reporting tells you how products perform in listings and campaigns.

AI Performance Insights asks a different question:

When shoppers use conversational AI to research products, how visible is my brand relative to competitors?

That is much closer to the “GEO share of voice” metrics agencies have been inventing independently.

Google now provides a first-party version for shopping.

Share of voice.

Google defines the merchant’s share of voice based on AI impressions relative to the merchant and defined competitors for related queries.

Use it directionally.

Do not treat:

43% share of voice

as:

43% market share

It is a visibility metric inside the report’s eligible conversational query set.

Sources reviewed.

  1. About AI performance insights — Google Merchant Center Help; accessed 2026-08-07. [1]
  2. Insights for AI-powered shopping experiences — Google Merchant Center Help; accessed 2026-08-07. [2]

02

Ordered process

Use the article in this order:

  1. Why this is one of the most important new ecommerce reports
  2. Share of voice
  3. Competitor average share
  4. Query frequency
  5. Shopping journey phases
  6. Discovery
  7. Evaluation
  8. Purchase
  9. Frequently used AI shopping terms
  10. Product attribute insights
  11. Category filtering
  12. Geographic rollout
  13. How to find the report
  14. Build a monthly AI commerce review

Competitor average share.

Merchant Center supplies the competitor set.

Google says merchants cannot currently change the competitors used for this report.

That limitation matters.

If the comparison set seems odd, record it.

Do not manually swap in a favorite competitor and still label the number “Google AI Performance Insights.”

Query frequency.

Query frequency represents how popular particular query types, product terms, journey phases, or product attributes are.

This is demand context.

It is not the same thing as monthly keyword search volume.

Use it to prioritize catalog improvement.

Do not turn it into fake exact traffic forecasting.

Shopping journey phases.

Google classifies conversational shopping into three broad phases:

  1. Discovery
  2. Evaluation
  3. Purchase

This is useful because one brand can perform differently across the journey.

Example:

Discovery share: high
Evaluation share: low
Purchase share: low

That can suggest the catalog is discoverable but weak on comparison-ready specifications or transactional detail.

Discovery.

Users explore categories or needs.

Queries can emphasize:

  • use case;
  • style;
  • problem;
  • broad feature.

Content needs:

  • category clarity;
  • product type;
  • use cases;
  • visual variety.

Evaluation.

Users compare.

They need:

  • specifications;
  • materials;
  • size;
  • compatibility;
  • reviews;
  • price;
  • differences.

This is where missing product attributes hurt.

Purchase.

Users are closer to transaction.

They care about:

  • exact model;
  • price;
  • availability;
  • shipping;
  • merchant;
  • promotion.

Keep operational data current.

Frequently used AI shopping terms.

Google’s report can surface terms shoppers use to describe functional benefits or product features.

Examples in Google’s documentation include:

  • maximum cushioning;
  • arch support.

This is excellent merchandising vocabulary.

Use the terms when they truthfully describe the product.

Do not add:

maximum cushioning

to every shoe because the report says the phrase is popular.

Popularity is not product truth.

Product attribute insights.

Google can also highlight structured attributes shoppers care about, such as:

  • size;
  • color;
  • material.

The report can expose missing structured product information.

This creates an unusually direct workflow:

popular attribute
→ catalog gap
→ product feed cleanup
→ monitor future visibility

That is much more actionable than another generic AI-readiness score.

Category filtering.

Google says the dashboard is filtered by individual product category rather than one universal all-category report.

Respect the context.

A footwear brand’s AI terms should not be mixed with furniture performance as one “company score.”

Geographic rollout.

The report is currently in pilot with limited U.S. accounts.

Google says broader expansion is planned for markets including:

  • Australia;
  • Canada;
  • India;
  • New Zealand.

Availability can change.

Check the Merchant Center account itself.

How to find the report.

Google’s current instructions:

Merchant Center
→ Analytics
→ Products
→ AI performance

If the tab is absent, the account may not be in the pilot.

Do not pay a plugin vendor to unlock a server-side Google rollout.

Build a monthly AI commerce review.

Export or record:

CATEGORY
SHARE_OF_VOICE
COMPETITOR_AVG
DISCOVERY
EVALUATION
PURCHASE
TOP_TERMS
MISSING_ATTRIBUTES
DATE

Then assign actions.

Example:

High query frequency for waterproof
Low matching product coverage

Action:

  • verify which products are actually waterproof;
  • add accurate structured/material details;
  • update titles/descriptions where natural.

Common misreadings.

100% share of voice.

Google notes that if an account lacks sufficient defined competitor data, the report can show 100%.

That does not mean total market domination.

0% share.

Google says insufficient impressions can appear as zero.

Again, do not oversell the number.

Paid traffic.

Current data is organic AI traffic only.

Do not attribute an AI Max campaign to this report.

03

Failure cases

FAQ.

Is AI Performance Insights available to everyone?

No. It is currently a limited pilot.

Does it show AI Mode?

Yes. Google specifically describes AI Mode and AI Overviews.

Does it include paid ads?

Current report scope is organic AI traffic.

Can I change competitors?

Google says not currently.

Are shopping terms keyword-volume numbers?

No. Query frequency is a relative demand signal inside the report.

Optimization checklist.

  • AI Performance tab checked.
  • Category selected.
  • Share of voice recorded.
  • Competitor average recorded.
  • Journey phases compared.
  • High-frequency terms reviewed.
  • Product claims verified before adding terms.
  • Missing structured attributes filled.
  • Price/availability checked.
  • Organic and paid reporting separated.
  • Date stamped.

Verdict.

Merchant Center AI Performance Insights is the closest thing Google has released to a first-party AI shopping visibility and query-opportunity dashboard.

Use it carefully.

The valuable part is not the shiny share-of-voice percentage.

It is the catalog gap the report can actually help you fix.

Verification record.

  • Current pilot scope, metrics, category filters, competitor limits, and organic-only traffic were checked against Merchant Center Help on 2026-08-07.
  • 0% and 100% edge cases are preserved from Google’s documentation.
  • No universal rollout date is invented.

Duplication and search-intent record.

No prior RankBuilder package targets the live Merchant Center AI Performance Insights pilot as a full measurement workflow.

References

Sources behind this record

  1. About AI performance insights — Google Merchant Center Help (accessed August 7, 2026)
  2. Insights for AI-powered shopping experiences — Google Merchant Center Help (accessed August 7, 2026)

Corrections

Correction history

No corrections recorded.

To report an error, use the public corrections path.

Claim limit

The cited sources supporting this Merchant Center AI Performance Insights review were checked through 2026-08-07.

Merchant Center AI Performance Insights documentation, interfaces, measurement methods, policies, and availability can change after publication.

Correct handling of Merchant Center AI Performance Insights does not guarantee rankings, traffic, citations, advertising delivery, or commercial outcomes.