We built a free AI Visibility Scanner that checks how well Shopify stores show up in ChatGPT, Perplexity, Google AI Mode, and Claude. We pointed it at 100 real Shopify stores, from Allbirds and Glossier to fast-growing DTC brands, and scored them across 9 dimensions on a 0-100 scale.
The headline numbers
Average AI Visibility Score: 44.5 out of 100. Not a single store out of 100 scored above 79. Zero stores earned an A grade.
Grade distribution:
- A (80-100): 0 stores.
- B (65-79): 15 stores. The top 15% includes Wild One (79), Honest Paws (78), Gymreapers (75), Rothy's (74).
- C (50-64): 45 stores. The largest group. Glossier, ColourPop, Brooklinen, Allbirds all live here.
- D (25-49): 11 stores. Gymshark (41), Skims (42), AG1 (41), Bombas (38).
- F (below 25): 29 stores. Close to a third. Includes MVMT (15), Hydro Flask (15), Our Place (16).
46% scored below 50. Ten stores scored 70 or above.
The 9 dimensions, ranked worst to best
Each dimension measures whether AI engines can find, understand, and recommend a store's products. AI visibility problems concentrate in four areas: machine-readable identity, content depth, social proof, and product catalog completeness. The infrastructure layers (crawler access, meta tags, page speed) are in decent shape.
1. llms.txt Presence: 6% of possible points
86 out of 100 stores have no llms.txt file. Only 14 have attempted one, and most of those earned partial credit for incomplete content. The llms.txt standard tells AI models what a business sells in a format they can parse. Almost no one uses it.
2. Structured Data Quality: 24% of possible points
40 stores had zero structured data. No Product schema, no FAQ markup, no Organization data, no aggregate ratings in JSON-LD. This is the foundation. Without it, AI models guess at what you sell, what it costs, and whether customers like it.
3. Reviews and Social Proof: 29% of possible points
86 stores scored 3 or below out of 10. Thirty-six scored zero. AI engines weight social proof when recommending products: aggregate ratings, review volume, review quality. Most Shopify stores either lack a reviews app or output review data in formats AI can't read.
4. Content Quality: 33% of possible points
42 stores scored zero. This dimension measures product description depth, alt text coverage, benefit-oriented language, and Q&A content. Many stores rely on manufacturer descriptions or minimal bullet points.
5. Product Data Richness: 47% of possible points
34 stores scored zero. This measures whether a product catalog exposes multiple images, variant details, GTIN/barcodes, product types, and tags. Stores with rich product data give AI models the specificity to recommend with confidence.
6. Technical Performance: 50% of possible points
Every store scored 5/10 on Google PageSpeed. The most uniform dimension. Shopify's infrastructure handles the basics, but few stores optimize beyond the default.
7. Agentic Commerce Readiness: 57% of possible points
The newest dimension. It measures whether a store is ready for AI agents that browse, compare, and purchase on behalf of consumers: return/shipping policies in machine-readable format, checkout accessibility, knowledge base presence, catalog mapping. 36 stores scored 3 or below.
Shopify's Agentic Storefronts are activating for US stores and OpenAI's ChatGPT Shopping is growing. This dimension will matter more every month.
8. Meta Tags and Open Graph: 64% of possible points
The strongest non-infrastructure dimension. 38 stores scored a perfect 10/10. Shopify themes handle basic meta tags well. But 22 stores scored zero, usually from missing or broken Open Graph tags on product pages.
9. AI Crawler Access: 96% of possible points
The one bright spot. 68 stores scored a perfect 10/10, and the average was 9.6. Most Shopify stores allow GPTBot, ClaudeBot, PerplexityBot, and other AI crawlers to access their pages. The door is open. Nothing behind it is worth reading.
Big brands are failing too
These aren't small stores. Some of the most recognized DTC brands scored poorly:
| Brand | Score | Grade | Biggest weakness |
|---|---|---|---|
| MVMT | 15 | F | Zero across 6 of 9 dimensions |
| Hydro Flask | 15 | F | Zero across 6 of 9 dimensions |
| Our Place | 16 | F | Only store to score 0 on AI Crawler Access |
| HelloFresh | 25 | D | No structured data, no content, no product data |
| Ruggable | 26 | D | Zero on structured data, content, product data, reviews |
| Bombas | 38 | D | Zero on content quality and product data |
| AG1 (Athletic Greens) | 41 | D | Zero content quality, zero reviews |
| Gymshark | 41 | D | Zero structured data, zero reviews |
| Skims | 42 | D | Zero content quality, weak agentic readiness |
| Allbirds | 49 | C | Zero structured data, minimal content |
| Glossier | 56 | C | Minimal structured data |
| Kylie Cosmetics | 56 | C | Zero content quality |
Well-funded brands with sophisticated marketing teams aren't optimizing for AI visibility. They spend millions on Instagram and Google Ads while remaining invisible in the fastest-growing discovery channel in e-commerce.
The B-grade stores share two traits
The 15 stores that earned a B grade (65+) separate themselves in two areas.
They invest in structured data and content. Every B-grade store scored 8+ on structured data. They have Product schema, Organization markup, and most have FAQ or aggregate rating data in JSON-LD. Wild One (79, the highest overall score) earned 16/20 on structured data alone. B-grade stores average 9.7/15 on content quality versus 5.0 for the full dataset. They write original product descriptions with benefit-oriented language, include comprehensive alt text, and give AI models enough depth to understand their value proposition.
They have working reviews. 10 of the 15 B-grade stores scored 8+ on reviews. They use review apps that output structured rating data AI engines can parse, not display-only star widgets.
For Shopify merchants
More consumers search through AI every month. ChatGPT Shopping, Perplexity Product Search, Google AI Mode, and Shopify's Agentic Storefronts are all live or rolling out. A consumer asks "best insulated water bottle under $40." The AI recommends 2-3 specific products based on what it can parse about each one.
Your competitor scoring 74/100 gets the recommendation. A store scoring 15/100 doesn't.
Two fixes cover the most ground for most stores, based on this data:
1. Add structured data (JSON-LD) and install a reviews app with structured output
40% of stores have zero structured data. 86% scored 3 or below on reviews. Adding Product, Organization, and FAQ schema is a one-time fix that makes your catalog parseable by every AI engine. Judge.me, Loox, Yotpo, and others output AggregateRating schema that AI engines use for recommendations. Together, these two changes address the two largest scoring gaps.
2. Write real product descriptions
42% of stores scored zero on content quality. AI models can't recommend a product described in three bullet points. Descriptions need benefit language, specific attributes, and enough depth to differentiate from competitors.
Check your own store
We built the scanner that generated this data as a free tool. Enter your Shopify store URL and get your AI Visibility Score in 30 seconds, with a breakdown across all 9 dimensions and specific fixes.
See how your Shopify store scores on AI visibility. Get your AI Visibility Score in 30 seconds.
Methodology: We scanned 100 Shopify stores across 9 dimensions using InsightPath's AI Visibility Scanner. Stores were selected to represent a mix of well-known DTC brands (>$5M annual revenue) and smaller Shopify merchants. All scans were conducted on March 24, 2026. The scanner checks publicly accessible data including robots.txt, JSON-LD structured data, product catalog endpoints, meta tags, PageSpeed scores, llms.txt presence, and review app output. Full scoring methodology is transparent and available at insightpath.ai.