Ecommerce AI Search
Make your products easier for AI shoppers to find, compare and trust.
Schmitdy runs AI search visibility for ecommerce brands. We improve the product facts, brand evidence and comparison pages that answer engines and shopping assistants can use, then measure the path into qualified store visits and connected commerce outcomes.
For ecommerce teams with a live catalog and someone who can approve product, policy and brand changes. Engines and shopping services decide what they show.
The shopping journey
The shortlist can form before a shopper reaches your store.
A shopper can ask for the best product for a specific need, compare two options and check delivery or returns in one conversation. Your product pages, merchant data, policies, reviews and independent sources may all shape that research. We find where those facts disagree, go missing or fail to answer the comparison.
Google explains that product data can come from page markup, Merchant Center feeds or both, and that the two sources can help it understand and verify product information. Google’s product data guidance.
The working loop
Follow the buying question from answer to product page.
We agree a product set, buyer questions, markets, languages and engines before tracking starts. Each sample records the question, engine, date, products shown, claims made and sources linked. Daily checks guide the work. Complete-period comparisons help us judge movement. Missing results and unavailable data remain visible as gaps.
What the harbormaster checks
- Discovery gapsA relevant category or use-case question returns other products, while yours is absent from the valid sample.
- Product fact conflictsPrice, availability, variants, materials, delivery or returns differ between the store, merchant surfaces and public sources.
- Comparison gapsThe page lists features but does not explain who the product suits, how options differ or what evidence supports the claims.
- Source patternsThe sampled answer relies on product pages, guides, reviews or retailers that explain the category clearly.
- Journey handoffsA cited link reaches the wrong variant, an unavailable product or a page that leaves the next step unclear.
- Citation changesA product or page gains or loses a link in the same agreed sample. The change is a signal to inspect, not proof of cause.
How the month runs
- MapChoose the product families and buying questions that matter commercially.
- VerifyCompare visible store facts with feeds, structured data, policies and approved brand sources.
- PrioritizeRank gaps by buyer value, product availability and the evidence your team can substantiate.
- ShipImprove approved product pages, comparisons, policies and source material.
- Read backCheck the published result, then compare the next complete measurement period.
The four pillars
Four inputs make ecommerce answers more dependable.
Buyer questions
A versioned set of discovery, comparison and reassurance questions, tied to real product families and markets.
Product truth
Names, identifiers, variants, prices, availability, policies and claims checked against the pages and systems your team approves.
Source evidence
Brand pages, merchant surfaces, useful guides and independent coverage that support what a shopper needs to decide.
Measured handoffs
Sampled visibility, cited product pages, qualified store visits and connected commerce outcomes kept as separate measures.
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What we improve
Five parts of the product discovery chain.
The monthly plan uses the systems and permissions you already have. We agree every platform, product set and publishing step before work begins.
Product information buyers can use
We turn thin or inconsistent product details into clear, supportable answers without inventing benefits.
- Product names, identifiers, variants and category relationships
- Materials, dimensions, compatibility and use constraints
- Visible price, availability, shipping and return information where applicable
Store pages and structured product data
We align machine-readable product information with what shoppers can see on the page.
- Product and offer fields checked against visible content
- Variant, image, availability and policy consistency
- Validation issues recorded for the team that owns the storefront
Comparison readiness
We build the explanations a serious buyer needs before choosing between products or categories.
- Plain-language fit, trade-offs and selection criteria
- Tables that compare like with like
- Evidence beside claims, with limitations kept visible
Merchant and brand source surfaces
We check the approved places where product and brand facts are published, then document the corrections that are possible.
- Google Merchant Center, OpenAI product discovery routes and approved marketplace consistency
- Organization, policy and category information
- No assumption of access to a platform your team has not connected
Citation monitoring and measurement
We retain the exact questions, answers and linked pages needed to compare complete periods.
- Product mentions and linked product pages in valid samples
- Qualified visits to agreed product and category pages
- Add-to-cart, checkout, purchase or revenue signals where a connected system can support them
Works with your team
Product, content and growth decisions stay in one working channel.
Your ecommerce, merchandising and marketing owners can review the exact page, feed field or claim involved. Each item has a clear status, owner and readback.
Publishing rights remain with your team unless a specific platform and approval path are agreed. We never treat a draft, feed upload or successful request as proof that the shopper-facing result changed.
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What is included
The work arrives in three connected parts.
Baseline and product map
- An agreed product and comparison set
- A versioned question set by market and language
- A source map with conflicts and unavailable inputs labeled
Prioritized execution
- Approved product and category page improvements
- Comparison and policy content where a buyer needs it
- Structured-data and merchant-surface recommendations for connected systems
Readback and reporting
- Published-page verification
- Citation and qualified-visit comparisons
- Connected add-to-cart, checkout, purchase or revenue signals when attributable data is available
Measurement
What do we count?
We agree the client commerce outcome before work starts. This might be qualified product-page visits, add-to-cart, checkout, purchase or revenue where connected data supports it. Sampled product presence and citations are separate leading indicators. Unavailable analytics or commerce data remains unmeasured.
| Measure | What we count | What it tells you |
|---|---|---|
| Product discovery | Valid sampled answers that include an agreed product or brand, divided by all valid answers in the set. | Observed presence in this sample, not total demand or market share. |
| Product-page citations | Valid answers linking to an agreed product, category or policy page, with the exact URL retained. | Which store pages serve as sources in the measured sample. |
| Qualified store visits | Visits to agreed product or category pages that meet the written market, product and source criteria. | Whether measured discovery brings relevant shoppers to the store. Lost referral data remains a gap. |
| Connected commerce outcome | The agreed add-to-cart, checkout, purchase or revenue signal where analytics and commerce data are connected. | Commercial progress in the available data. It does not assign every sale to one answer or citation. |
Every report states the questions, engines, markets, dates, valid answer count and missing runs. A recommendation, ranking, citation or sale is never guaranteed. Movement after a change does not prove that the change caused it.
Who it is for
A practical fit for brands that can keep product truth current.
This is a fit if
- You sell products through a live ecommerce store
- Your team can verify product, policy and availability claims
- Buyers compare your products by use case, feature, value or trust
- You can approve changes to the pages and connected merchant surfaces in scope
Start elsewhere if
You need a one-off technical report with no owner for product corrections, or expect guaranteed placement in an answer or shopping result.
FAQ
Questions ecommerce teams ask before starting.
Can you guarantee that ChatGPT or Google will recommend our products?
Do you need access to our store or merchant accounts?
What product information do you review?
Is structured data enough to appear in shopping results?
How does the result-based fee work?
Does this replace ecommerce SEO?
How do you handle fast-changing prices and availability?
What happens after the free audit?
How will we measure progress?
Primary guidance behind the service
These sources describe product data and shopping surfaces. They do not promise inclusion or a commercial result.
Works with your commerce stack
Keep the storefront. Improve the product evidence around it.
Squarespace
Vercel
Webflow
Sanity
Shopify
HubSpot
Platform support depends on the systems, permissions and publishing path agreed for your scope.
Next step
Start with the products buyers struggle to compare.
The free audit maps one product family across buyer questions, store facts and cited sources. You will see what is clear, what conflicts and which correction is worth making first.