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StoreCited
Free tool

Are your product pages ready for AI search?

A product-page readiness check should answer a practical question: what useful product evidence was visible in the representative page StoreCited fetched? The free scan may select at most one product page from links on the submitted homepage. It reviews returned Markdown for specifications, word-count context, price or availability clues, direct buyer answers, and trust or policy clues. Raw HTML is checked separately for selected JSON-LD type presence. The result helps merchants improve a verifiable PDP, but it does not compare every product, run live prompts, or decide which seller wins a citation or recommendation.

Free · No login · Results in ~60 seconds

Free · No login · ~60 seconds
Mini shopping cart with cosmetics and a 50% discount sign on a neutral background.
Photo: www.kaboompics.com / Pexels
What this checks

What StoreCited inspects — and what it does not

Which product page enters the sample?

StoreCited starts with the public homepage submitted by the merchant. It may choose at most one representative product page from links discovered on that homepage. That keeps the free check fast and reproducible, but it also limits the conclusion. The selected page is evidence about one fetched example, not the entire catalog or every template state. StoreCited does not enter Shopify admin, inspect unpublished products, or enumerate all PDPs. Merchants should apply a sample finding cautiously, then test high-revenue products, variants, sale states, unavailable items, translated markets, and any distinct templates before making a site-wide change.

What visible PDP evidence is reviewed?

The checker reviews fetched Markdown for concrete specifications, descriptive depth, price clues, availability clues, and direct answers to likely buyer questions. Useful facts may include material, dimensions, compatibility, ingredients, care, fit, use case, limitations, shipping, returns, or warranty when relevant to the product. It also notes review, FAQ, guide, and company clues exposed in the sample. Raw HTML is used for selected JSON-LD type presence, not full field certification. A word count or detected clue is context, not a quality verdict. Specific, accurate answers matter more than padding the page to reach an arbitrary length.

How should a weak PDP be improved?

Repair the decision path, not a score in isolation. State the exact product and variant, then add the specifications buyers need to evaluate fit. Put price and availability context where it can be verified, explain material limitations, and link shipping, returns, warranty, care, or safety details when relevant. Use authentic reviews and substantiated claims. Keep visible facts aligned with Product and Offer markup, then validate the properties separately. Re-run the same page after deployment and inspect the underlying checks. Better public evidence can improve clarity and implementation quality, but actual citations, recommendations, traffic, and sales require their own measurement.

Method and primary references

These official sources define the platform-specific controls and evidence limits behind this readiness check. StoreCited's result remains a dated observation of its own public fetch.

Frequently asked questions

Does the checker review every product page?
No. The free scan may inspect at most one representative product page discovered from the submitted homepage. That page can reveal a template or content issue worth investigating, but it cannot represent every product, variant, market, or state automatically. Test additional priority PDPs and edge cases before applying a broad content or schema change.
Does a low word count mean the product page is poor?
No. Word count is a clue about descriptive depth, not a target or quality score by itself. A concise page can be excellent when it answers the buyer's real questions with specific facts. A long page can still be vague. Focus on product identity, specifications, fit, limitations, price context, policies, and supportable evidence rather than adding filler.
Can StoreCited tell which product wins an AI citation?
No. The checker does not run live prompts, compare recommendation results, audit inferred peers, or observe citations. It reports public evidence in one representative PDP and related storefront material. Use a separate, fixed answer-sampling method for observed mentions or citations, and keep those outcomes distinct from the StoreCited readiness score.
What if important content is not present in the fetched output?
StoreCited reports the Markdown, raw HTML, links, and metadata its fetching service returned. If an accordion, widget, tab, or other element is absent from that output, the report can only mark the clue as undetected in this sample. Check the live page and other relevant fetches before concluding that no external system can access the content.
Does fixing the PDP guarantee more recommendations?
No. Fixing a PDP can make product facts clearer, more consistent, and easier for people and systems to verify. That is a valuable outcome, but it does not prove future retrieval, ranking, citation, recommendation, traffic, or sales. Measure those outcomes separately, preserve the baseline, and avoid attributing a change to one edit without stronger evidence.

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