AI Readiness Score
How Lumio scores your product data across six dimensions of AI discoverability.
The AI Readiness Score is a per-SKU metric from 0-100 that measures how well a product’s data is structured for discovery by AI shopping agents like ChatGPT Shopping, Perplexity, and Google AI Mode.
Why it matters
When an AI shopping agent decides which products to recommend, it evaluates the structured data available for each product. Products with rich, well-organized data get recommended. Products with thin data get skipped — no matter how good the actual product is.
The AI Readiness Score tells you exactly where each product stands and what to fix.
Dimensions
Each dimension is weighted based on its importance to AI agent discovery:
| Dimension | Weight | What it measures |
|---|---|---|
| Identifier coverage | 15% | GTINs, MPNs, brand, model numbers — the unique identifiers that help AI agents match products across sources |
| Title quality | 20% | Structured format with brand, product type, key attributes, and variants — not marketing slogans |
| Description density | 20% | Attribute-rich content that answers implicit questions: materials, dimensions, use cases, compatibility |
| Conversational fields | 20% | Q&A pairs, usage scenarios, and comparison data that match how real shoppers query AI assistants |
| Availability precision | 10% | Exact stock levels, pricing accuracy, shipping details, and handling times |
| Schema completeness | 15% | Product, Offer, and Review JSON-LD markup quality and completeness |
Score ranges
- 0-39 (Needs attention): Products are likely invisible to AI agents. Missing critical structured data.
- 40-69 (Fair): Partial visibility with significant gaps. AI agents may find these products but can’t confidently recommend them.
- 70-100 (Good): Competitive for AI-powered discovery. Products have the data density AI agents need to make recommendations.
How scores are calculated
Each dimension is scored independently from 0-100 using Lumio’s AI evaluation engine. The scoring model examines your product’s raw data (titles, descriptions, JSON-LD, meta tags) and evaluates it against each dimension’s criteria.
If you’ve set up a brand profile, the scoring engine also considers your product vertical and customer persona. A hiking boot is evaluated differently than a lipstick — the attributes that matter are industry-specific.
The overall score is the weighted average of all six dimensions.
Gap reports
For any dimension scoring below 70, Lumio generates a gap report with:
- Specific issues — What’s missing or weak (“No GTIN identifier found”, “Title is generic and lacks key attributes”)
- Actionable suggestions — Exactly what to add (“Add material composition and fit information to description”)
These gaps feed directly into the enrichment engine, which can automatically generate the missing content.
Improving your scores
The fastest way to improve scores:
- Run enrichment — Lumio’s enrichment engine generates content specifically targeting your lowest-scoring dimensions
- Add structured data — Ensure your product pages have JSON-LD Product schema markup
- Include identifiers — Add GTINs/UPCs, MPNs, and brand information to every product
- Write for AI, not just humans — Include specific attributes (materials, dimensions, compatibility) that AI agents use to match products to queries