I Built a Free Tool That Scores How Visible Your Store Is to AI Search
A few weeks ago I published a checklist for getting found in AI search: structured data, answer-style product copy, FAQs, speed, topical authority. The feedback I kept getting was the same question:
"Okay, but how do I actually check all that without hiring someone?"
So I built a tool that does it for you. Paste any store URL, and it scores the page against the exact signals AI search engines and shopping agents look for. Here's what it checks — and why each item matters.
The scorecard: 100 points, 6 checks
JSON-LD structured data (30 points) — This is the single biggest miss. AI engines parse schema.org markup to understand what your page is: a Product with a price, an Offer with availability, an Organization with a logo. The most common failure I see: e-commerce homepages with zero JSON-LD at all, even when the site's blog has FAQPage markup. Product pages need Product + Offer at minimum. AggregateRating only if you have real reviews — never fabricate.
Title & meta description (15 points) — Your title tag is still the anchor for how both Google and AI engines label your page. It should name the product and the category. "Home" is a wasted title.
robots.txt (10 points) — Shocking how many stores block their own crawlers without knowing it. If robots.txt disallows your product paths, you're invisible to every crawler that respects it — including AI engines.
Canonical tags (10 points) — Duplicate URLs (with-utm, /products vs /products/) split your authority. Canonicals tell engines which version is the real one. Missing canonicals = diluted signals.
Sitemap (20 points) — AI engines and search engines both use your XML sitemap as the entry point to your catalog. If your sitemap is missing, broken, or missing your newest products, discovery slows to a crawl.
SSL (15 points) — The boring one. No HTTPS, no trust, no ranking. Usually fine, but the tool catches it because people forget on staging domains.
What the scores actually look like
I ran real stores through it while building it:
- sellerstack.cc — 50/100. Working sitemap, robots, SSL, title, description. Zero JSON-LD on the homepage. It's an e-commerce toolkit site with decent fundamentals, but AI engines can't tell what it is without structured data.
- example.com — 25/100. This is the baseline most small stores sit near: nothing structured, no real description, no sitemap worth crawling.
The pattern is consistent: most stores are one structured-data pass away from doubling their AI-search visibility. It's the highest-leverage, most-neglected fix in e-commerce right now.
How to use the results
Don't treat the score as a grade — treat it as a triage list:
- 0-30: Fix the fundamentals. Sitemap, robots, SSL, title/description. One afternoon of work.
- 30-60: Add JSON-LD. Product pages first, then homepage (Organization/WebSite schema), then blog posts (Article schema). If you're on Shopify or WooCommerce, the plugin handles it — just verify it's actually rendering, because most of the time it isn't.
- 60+: You're doing better than 95% of stores. Focus on content: answer-style product descriptions, FAQs, and guides that make AI engines cite you as a source.
Why this matters more every week
AI shopping agents don't browse like humans. They fetch pages, parse them, extract facts, and recommend. A store with clean Product + Offer markup and answer-rich copy gets recommended; a store without it doesn't exist to them. This isn't a ranking tweak — it's whether you're in the game at all.
The checklist I published earlier is the theory. The tool is the practice. Run your store through it, fix what's broken, and you've done more for your AI-search visibility than most competitors will do all year.
If you're a small e-commerce brand trying to stay visible as search changes, this is exactly the kind of stuff I work on. I build tools for sellers navigating these shifts — SellerStack is the e-commerce toolkit I'm building around them.
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