Full audit
Brand + 3–5 priority products
4 AI systems · 40–60 buying situations
Full action plan and retest.
Visibility, representation and product selection
AI Visibility Audit for Ecommerce
Are your products recommended when customers ask AI what to buy?
We test how ChatGPT, Gemini, Perplexity and other relevant AI systems find and recommend your products in the buying situations that matter to your business.
Built around your growth goals
Repeatedly tested
Manually verified
Free product diagnostic
1 product
3 AI systems · 1 buying situation
What we found and what to fix first.
The buying decision
Why an AI commerce audit matters for product selection
A brand can appear in a broad AI answer and still be absent when a customer asks which product to buy.
At that point, details such as price, availability, delivery, ingredients, suitability and claims can change the answer. Those facts may differ across your site, product feeds, retailers and other sources.
A brand visibility score cannot show whether a specific product was selected, omitted or described accurately. General advice to publish more content cannot identify which product fact or source needs attention.
The audit tests specific buying situations, checks the product and source evidence, and shows what to fix first.
What we do differently
We start with your business goals, then test the AI buying situations that matter.
We treat AI as a tool that can support or limit growth, not as a score to chase. We define the product, customer, market and commercial question first, then test the buying situations that matter to that goal.
Step 1 of 5 Follow the audit from commercial objective to testing plan.
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01
Business objective
Define the growth, market, brand or product question the audit must help answer.
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02
Priority customer and market
Focus the test on the people and places that matter to your growth plan.
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03
Product or category
Choose the products, claims and attributes that should influence selection.
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04
Buying situations
Build realistic discovery, comparison and choice questions around the customer.
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05
Evidence and testing plan
Agree the systems, markets, languages, competitors, repeat runs and product evidence to verify.
Our tools help us test consistently. Senior review turns the evidence into a business recommendation your team can act on.
What we test
Where product visibility breaks down
Being mentioned is only one layer. In a buying answer, a product can be selected, omitted, replaced by a competitor, cautioned against or misdescribed. Each outcome calls for a different response.
What we examine around each result
- Which market, language, platform and buying situation produced it
- Which product attributes and claims the answer relied on
- Which competitor was selected instead and what the answer appeared to favour
- Whether the behaviour repeats across clean-session runs
- Which product-data, owned-content or third-party-source gaps may be contributing
You see the commercial problem, the evidence behind it and where action is most likely to matter.
Explore: How AI product recommendations differ across systems (blog)
What you get
You get a clear action plan for improving how your products are found, represented and recommended.
We show what happened, why it matters, which evidence supports the finding and what your team should address first. You also receive the underlying record so the recommendation can be challenged, shared and retested.
Component 1 of 6 Select any box to focus on one part of the Evidence File.
Visibility & Selection Map
Where products are found, considered, selected, omitted or replaced.
Competitive Analysis
Who AI selects instead, in which buying situations and what the answer appeared to favour.
Representation Analysis
Where products are represented accurately, hedged, misdescribed or cautioned against.
Prioritised Recommendations
What to address first, why it matters, which team owns it and what to do next.
Evidence File
The questions, responses, sources and observations behind every important finding.
AI Commerce Monitoring
Track the priority systems, markets and buying moments your business decided matter after the audit.
You do not leave with another dashboard. You leave knowing what your team should do next.
Inside a full audit
Example audit finding
This format shows how an AI answer is compared with product facts and source evidence before a recommendation is made.
- AI prioritised
- Competitor X was selected; your product was omitted.
- Verified on product
- Four of the five buying requirements were met.
- Gap found
- The fragrance-free claim was not consistently supported across priority sources.
Why Lex Agentica
Senior judgement, product evidence and a European view
The audit connects AI buying answers with product facts, commercial priorities and the sources that may shape a recommendation.
Pilar Berrío leads the audit. Her 25 years in marketing and ecommerce include senior SEO work. View Pilar’s profile.
Senior SEO and commerce judgement
Findings are assessed for commercial relevance, so a brand mention is not mistaken for a product recommendation.
Own method and tools
Relevant buying situations are tested repeatedly, with an evidence record that can be checked and retested.
European markets and governance
The audit compares markets and languages in scope, and flags claim or source gaps that could create trust or governance risks for European brands.
Lex Agentica combines in-house tools, AI-assisted workflows and senior review so the final recommendation is based on evidence, not a single response or automated score. See how product claims intersect with AI recommendations in beauty ecommerce.
Free product diagnostic
Test one priority product before committing to a full audit.
We test one product in one realistic buying situation across three relevant AI systems.
You receive what we found, the evidence behind it and what should be fixed first.
1 product. 3 AI systems. 1 buying situation. Not a full audit.
AI Commerce Visibility & Selection Audit
Get a full view of how AI finds, represents and recommends your products.
Tell us the commercial question you need to answer. We build the scope around the right products, customers, markets, AI systems, languages, competitors and buying situations, then confirm it with you before any work begins.
- Products and categories
- Priority target audience and markets
- Relevant AI systems and languages
- Competitors and buying situations
Best suited to consumer brands with active e-commerce catalogues, priority European markets and internal teams able to act on cross-functional recommendations.
Test a product insteadAfter the audit
Fix, verify, then monitor what matters.
Implement the priorities
Your internal teams or trusted partners address the product-data, content and source gaps identified in the audit.
Retest the same buying situations
We verify whether the relevant visibility, representation or selection behaviour changed after the fixes.
AI Commerce Monitoring
Track the platforms, markets and buying moments your business decided matter.
Optional add-onLex Agentica does not alter your systems or publish changes. We provide the evidence and priorities; your internal teams or trusted partners implement them.
Questions
Frequently asked questions.
What is an AI Commerce Visibility Audit?
It shows how AI systems find, describe, compare and recommend your products in the buying situations that matter to your business. It also investigates the gaps that may be limiting selection.
How is this different from an automated AI visibility tool?
Automated tools can track visibility trends. The audit diagnoses specific product outcomes by testing buying questions, checking the product facts and sources behind the answers, and prioritising the gaps that matter to your business.
Is this the same as AI SEO, GEO or AEO?
There is overlap, but the commercial question is broader for ecommerce. AI SEO, GEO and AEO often focus on mentions, citations or visibility. We also test whether your products are represented correctly, considered and selected as buyers move closer to a decision.
Which AI systems do you test?
We select the systems that matter to your target audience and markets. This can include ChatGPT, Gemini, Perplexity, Claude and other relevant AI discovery or shopping systems.
Why can a brand appear in AI answers while its products are omitted?
A broad answer may name a brand without comparing products. A specific buying question can depend on current price, availability, suitability, claims and source information. The audit checks what happened for the products and markets in scope.
Can the audit compare markets and languages?
Yes. The scope defines the relevant markets and languages. Results are tested and compared in context, rather than assuming an answer in one language represents another market.
Do you use a standard list of prompts?
No. The test set is built around your products, target audience, markets and business priorities.
How much does the audit cost?
There is no fixed package. Scope depends on the products, markets, AI systems, languages and business questions we need to investigate. We confirm the scope and cost before any work begins.
Can you guarantee more sales?
No. We can show where AI visibility and product selection may be helping or limiting your commercial goals, and what your team should address. We do not claim that an AI recommendation automatically causes a sale.
What happens after the audit?
Your team can implement the priority changes, then Lex Agentica can retest the affected buying situations. Ongoing AI Commerce Monitoring is available as an optional add-on.