Product features serve three masters simultaneously: the buyer (who needs to decide), the search engine (which indexes the copy), and the marketplace feed (which maps to structured attribute fields). Getting all three right requires a clear separation between attribute data and narrative copy.
The two layers of product features
Every product has two parallel feature representations:
- Structured attributes: color (hex + name), material (% composition), weight (grams), dimensions (cm), certifications (CE/RoHS). These feed Google Shopping, filters and APIs.
- Narrative features: benefit-led sentences that explain what those attributes mean for the buyer. These live in the long description and drive conversion.
UX: 3-7 features, prioritized
SEO: bulleted lists with data
Google Shopping: attribute mapping
| Industry | Top feature priority | Mandatory attribute |
|---|---|---|
| Fashion | Material + care instructions | material, size_type |
| Tech | Compatibility + certifications | mpn, certification |
| Outdoor / sport | Waterproofing + weight | material, item_weight |
| Beauty | Skin type + INCI | scent, size |
| Home | Dimensions + assembly | item_dimensions, item_weight |
Managing product features at scale
The challenge with features at scale is maintaining consistency: the same material described as "cotton blend" on one listing and "65% cotton, 35% polyester" on another creates both data quality issues and SEO fragmentation.
Seegea solves this by maintaining structured attribute fields as the single source of truth and generating narrative features from those attributes via AI. Every listing gets the same format, the same level of detail, and the same brand voice — regardless of which team member added the product. Created in France between Annecy and Chantilly, we help you audit your current feature consistency on a live Google Meet session.
Audit your product feature consistency
30 min Google Meet · we review your top 10 listings together