GEO Scoring
BetaGenerative Engine Optimization (GEO) is the practice of optimizing product data for AI-powered discovery. As AI agents increasingly help consumers find and purchase products, having well-structured, literal, and complete product information becomes critical for visibility.
Our GEO score provides a quick assessment of how ready your product data is for the age of agentic commerce. This page explains our methodology.
Want a personalized audit instead of doing it yourself?
Skip to requestHow We Score
Each product receives a score from 0-100 based on five factors. The score is rule-based and deterministic—no AI is used in the scoring itself, making results explainable and consistent.
Title Quality
25 pointsHow well the product title describes what the product actually is.
What we check
- Sufficient length (10-150 characters)
- Avoids marketing buzzwords (e.g., "amazing", "revolutionary", "best-in-class")
- Uses literal, descriptive language
- Clearly identifies the product type
Why it matters
AI agents parse titles to understand product identity. Marketing language that works for humans ("The Ultimate Sleep Experience") fails for AI that needs literal descriptions ("Memory Foam Mattress, Queen Size, 12-inch").
Description
25 pointsPresence and quality of product description content.
What we check
- Description is present
- Minimum 100 characters of content
- Includes specific details (measurements, materials, use cases)
- Avoids excessive marketing language
Why it matters
Descriptions provide context that titles can't. AI agents use descriptions to answer follow-up questions like "what is it made of?" or "will this work for...?"
Data Completeness
20 pointsStructured product attributes and metadata.
What we check
- Top features are defined (3-5 bullet points)
- Technical specifications are present
- Product attributes are populated (brand, material, etc.)
- Unique selling point is defined
- Options are properly structured
Why it matters
Structured data enables precise filtering and comparison. When an agent needs "wireless headphones under $100 with 20+ hour battery," structured specs make that query answerable.
Variant Structure
15 pointsHow well product variants are organized.
What we check
- At least one variant is defined
- Options (size, color) are properly linked to variants
- Variants have dedicated images where applicable
- Not over-fragmented (too many similar variants)
Why it matters
Well-structured variants help agents understand product availability and present options clearly. Poorly structured variants create confusion about what's actually available.
Media & Alt Text
15 pointsProduct images and their accessibility.
What we check
- At least one product image
- Multiple angles/views (3-5 images ideal)
- Alt text is present on images
- Alt text is descriptive (not "product image")
Why it matters
While AI agents primarily work with text, alt text describes visual content. Multimodal AI models can also analyze images directly. Good media helps both scenarios.
Grade Scale
| Grade | Score Range | Meaning |
|---|---|---|
| A | 90-100 | Excellent GEO readiness. Product data is well-optimized for AI discovery. |
| B | 80-89 | Good GEO readiness with minor improvements possible. |
| C | 70-79 | Moderate GEO readiness. Some issues may limit AI discoverability. |
| D | 60-69 | Below average. Significant issues impact AI discoverability. |
| F | 0-59 | Poor GEO readiness. Critical issues need attention. |
Further Reading
Our scoring methodology is informed by Shopify's guidance on preparing product data for the age of AI-powered commerce:
Need Personalized Guidance?
This scoring rubric provides general guidance based on best practices. For a detailed audit of your specific catalog with actionable recommendations tailored to your products and category, get in touch.