Make your catalogue usable by AI shoppers.
A feed can pass every structural check and still fail a real buying question. Herm tests whether AI shopping systems can find the right product, understand the attributes that matter, trust the information and complete the next step.
Connect a feed URL, export or API.No change to your catalogue. what a test does
I’ve got rosacea-prone skin and I want to start using vitamin C. I reacted badly to one last year, so I need something that won’t sting. I’d like to stay under £40.
- Velora Bright Boost C fragrance-free · 10% vitamin C in stock · £38.00
- Velora Bright Boost C Intense Rejected · strength above stated tolerance
- Velora Clarity C Gel Rejected · strength above stated tolerance
- Velora Overnight Repair Mask Rejected · overnight repair step not matched to a first vitamin C
| Requirement | State |
|---|---|
| Correct category | Answered |
| Correct market | Answered |
| Budget respected | Answered |
| Fragrance-free claim supported | Answered |
| Gentle-form suitability | Not stated |
| Tolerance confirmation | Unclear |
| Valid retailer destination | Answered |
Observation The product is in stock, correctly priced and structurally valid. It fails because one of the customer's stated requirements cannot be resolved from the information the catalogue publishes.
Feed health tells you whether the file works. It does not tell you whether the shopping journey works.
Traditional catalogue checks are designed to catch structural errors: missing fields, invalid values and schema problems. AI shopping introduces another test. Can a system use the information you provide to satisfy a customer's actual constraints?
- volume present
- strength present
- price present
- base present
- format present
- gtin present
- will these fit a wide foot?
- do they need breaking in?
- genuinely fragrance-free, or merely unscented?
- in stock in my size?
Test the journey the way a customer experiences it.
One request, one product, four stages. A stage only runs on what the previous stage produced.
- 01 Pass
Find
Can the agent retrieve the right eligible product?
What happened here Four candidates shortlisted from the connected catalogue, the target product ranked first on category and price. - 02 Fail
Answer
Does the available product information resolve the shopper's important questions?
What happened here Gentle-form suitability unresolved and tolerance unconfirmed, from a record that carries neither. - 03 Partial
Trust
Can the agent rely on the identity, claims and commercial facts it is using?
What happened here The fragrance-free claim is supported. The form claim is asserted without a published specification behind it. - 04 Pass
Close
Can the shopper reach an appropriate place to buy?
What happened here Price, stock and UK destination all resolved. Never reached: the journey stopped at Answer.
See exactly where the product journey breaks.
Every journey is recorded: the request, the requirements read out of it, what the system looked for, what it found in your product record and the point at which it could go no further.
- environment
- Controlled agent
- catalogue
- Connected feed · read only
- journeys
- 50 · UK / EN
- checkout
- Not attempted
- Velora Bright Boost C
- Velora Bright Boost C Intense
- Velora Clarity C Gel
- Velora Overnight Repair Mask
Read only. Retrieval reads the connected catalogue and nothing is written back.
I’ve got rosacea-prone skin and I want to start using vitamin C. I reacted badly to one last year, so I need something that won’t sting. I’d like to stay under £40.
- Correct category Complete
- Correct market Complete
- Budget respected Complete
- Fragrance-free claim supported Complete
- Gentle-form suitability Not found
- Tolerance confirmation Ambiguous
- Valid retailer destination Complete
Insufficient active-form evidence across 34 variants.
Turn shopping failures into a product-data backlog.
Every row traces back to the customer requirement that failed and the products it affects.
| Issue | Affected SKUs | Customer impact | Priority | Owner |
|---|---|---|---|---|
| Missing attributes Important specifications absent from the catalogue. | 214 | Gentle-form suitability cannot be answered across the vitamin C range. | High | Product data |
| Ambiguous claims Information exists but is too unclear to answer the customer's constraint confidently. | 88 | "Fragrance-free" does not resolve to a declared ingredient statement. | High | Merchandising |
| Conflicting data Different product or data surfaces disagree. | 21 | Feed weight and product-page weight differ, so neither can be trusted. | Medium | Ecommerce ops |
| Weak evidence A claim is present but cannot be reliably supported. | 46 | The no-sting claim is asserted with no published test behind it. | Medium | Product data |
| Channel blockers The product is understood but the next commercial step cannot be completed correctly. | 12 | Destination geography is missing, so the request cannot be completed for those markets. | Low | Marketplace |
Fix the information that matters to the buying decision.
The goal is not to add more product copy indiscriminately. It is to resolve the information gaps that stop a system from answering a real customer need.
- 01 Finding 19 failed journeys, one root issue
- 02 Affected products 214 products, 34 variants first
- 03 Proposed data field-level changes, each with evidence
- 04 Review queued for brand review
- 05 Approve brand decides what is accurate
- 06 Download / export no write-back to your PIM
- 07 Source updated, re-test you publish, Herm re-runs the same journeys
Fit: standard.no width range, no last description, requirement unresolved
THD ascorbate, a buffered form. Declared per variant across 10% and 15% strengths.requirement satisfied on re-test, the same claim stated precisely evidence: approved claim register v4 · fit test summary 2025
Herm proposes the information that would close a requirement, with the evidence behind it. Your team reviews it, publishes through your own systems, and the affected journeys are re-tested.
Work with the product information you already maintain.
Read in, evaluate, hand findings back. Your systems stay the record of truth.
Existing commerce systems
Your PIM, product platform, catalogue and channel feeds continue to own the product record.
Shopping tests and findings
Customer requirements are tested against the catalogue you connected. Findings name the requirement that failed, the evidence read and the products affected.
- 01 Customer requirements defined per category
- 02 Find, Answer, Trust and Close tested per product
- 03 Failures traced to the missing information
- 04 Findings grouped into a product-data backlog
Product-data remediation
Approved corrections and enrichment are exported for your team to publish. Once the source data changes, the affected journeys are re-tested.
It does not replace your PIM or commerce platform, and it does not write into your feed, product platform or Merchant Center account. The test reads the product information you already publish and reports what an AI shopping system could and could not do with it.
As shopping interfaces change, product information becomes part of the selling experience.
When a buyer asks an AI system for a product that meets five specific constraints, the product that can be evaluated confidently has an advantage over one whose catalogue leaves the important questions unanswered.
- The request
- Buying questions arrive as several constraints at once, not as a keyword.
- The test
- A system either resolves those constraints from your product information, or it does not.
- The consequence
- Unanswered constraints read as uncertainty, and uncertainty is not a recommendation.
Product Readiness is one part of AI Commerce Readiness.
Product Readiness focuses on whether your catalogue can support the buying task. Start here if product data, merchandising or digital commerce is your responsibility.
- Be Visible Brand Visibility Live Does AI know and recommend you?
- Be Sellable Product Readiness Live Can AI actually complete the recommendation: specs, price, stock, where to buy?
- Be Relevant Customer Intelligence Early access Are your own experiences right for the shopper in front of them?
- Be Preferred Offers Live Do the shoppers who buy your category buy you, and keep buying you?
Find the customer questions your catalogue cannot answer.
Test real buying requirements against your product information and see exactly where the journey fails.
- starts with
- A feed URL, catalogue export or API connection
- tests
- Real customer requirements across Find, Answer, Trust and Close
- you receive
- The failed requirements, the evidence read and the products affected
- boundary
- Read only: nothing is written back to your catalogue