Lighter starting point
AI Visibility Snapshot
One buying moment. One real finding. One practical next step.
AI Commerce Visibility Audit
AI is already deciding which products get recommended. Are yours?
See where your products are selected, overlooked or replaced in the AI buying moments that matter to your growth. Find what is holding them back and what to change first.
Built around your growth goals
Repeatedly tested
Manually verified
Deeper diagnosis
Full AI Commerce Visibility Audit
Across the products, target audience and markets that matter to your business.
Why products are not considered
A visible brand can still have an invisible product.
Appearing in a broad brand or category answer does not mean an individual product will qualify when a customer asks what to buy.
Specific buying questions depend on product-level facts such as price, availability, delivery, ingredients, suitability and claims. AI assesses the match using the information and supporting evidence available to it.
If those facts are missing, outdated or inconsistent across product pages, feeds, retailers and third-party sources, a suitable product may still be omitted or replaced.
Brand visibility gets you into the conversation. Clear, consistent product evidence helps you remain in the consideration set.
The Lex Agentica audit
Your growth priorities determine the evidence we test.
We begin with the product, customer, market and commercial outcome that matter to you. Then we build realistic buying situations and identify the product data, owned content and third-party evidence AI may use to evaluate the match.
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.
Technology helps us test consistently. Senior judgement connects the evidence to the commercial decision.
What we test
Visibility can lead to five very different outcomes.
A product may be selected, omitted, replaced, cautioned against or misdescribed. Visibility can therefore create opportunity, but it can also create commercial and brand risk.
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
That turns an AI answer into a business finding your team can investigate, prioritise and act on.
Evidence before recommendations
A one-off AI answer is not enough.
Findings are grounded in repeated responses from live AI systems and verified source evidence, not inferred from a website score alone.
Our audits combine Lex Agentica’s in-house tools, AI-assisted workflows and senior review.
Control 1 of 4 Follow how an answer becomes verified evidence.
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01
Realistic buying scenarios
Built around actual customer needs, budgets, markets and product requirements.
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02
Repeated clean-session testing
Patterns are checked across multiple runs, not inferred from one answer.
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03
Relevant systems and markets
Testing reflects the platforms, languages and countries that matter to the business.
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04
Verification and senior review
Observed behaviour is compared with product facts and source evidence before recommendations are made.
Inside a full audit
A finding goes beyond what AI answered.
It separates observed behaviour from verified product facts, identifies a likely contributing gap and connects it to one recommended action.
- 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
AI does not rely on your product page alone.
AI systems may draw on multiple sources when deciding whether a product is relevant, credible and suitable for a buying situation.
We examine product data alongside owned content, third-party sources and repeated AI behaviour before identifying which gaps deserve action.
Product data
Attributes, claims, availability, price, shipping and structured product information that may influence consideration.
Owned content
How product pages and supporting content explain relevance, evidence and differentiation.
Third-party sources
External sources, recommendations and evidence that may reinforce or contradict the product story.
Automated tools are useful for tracking patterns at scale. Senior review connects those patterns to product truth, commercial relevance and action.
Recommendations are tied to the evidence we find, not a standard instruction to publish more content or generate more mentions.
What you get
Your Evidence File turns findings into priorities.
Your team receives a verified record of what was tested, what happened, what was checked and what should be addressed first.
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.
AI Visibility Snapshot
Start with one buying moment.
A focused way to see how the method works before deciding whether you need a full audit.
Tell us which product, category or market matters most. We test one relevant buying situation and send you one bounded finding with one practical next step.
One buying moment. One bounded finding. One practical next step. Not a full diagnosis.
Full AI Commerce Visibility Audit
Request a full investigation built around your priorities.
Tell us the business question you need to answer. We confirm the right products, markets, customer profiles, AI systems, languages, competitors and buying situations 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.
Start with the Snapshot 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 are useful for continuous tracking at scale. This audit is designed for diagnosis: it starts with your business priorities, repeatedly tests realistic buying situations, verifies product and source evidence, and applies senior judgement to decide what deserves action.
How is this different from AI SEO?
AI SEO often focuses on mentions, citations and visibility. We also test what happens when your target audience move closer to a buying decision: whether products are selected, omitted, replaced, cautioned against or misdescribed.
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.
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.