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Understanding Quality Scores

Read this before showing scores to a customer

The Quality Scores on every product (Durability, Quality Perception, Value for Money, Price Positioning, Typical Competitors) are 100% generated by the LLM based on the product text. They are not backed by reviews, returns, sales data, certifications or any external evidence — yet.

What the LLM uses​

When scoring a product, Clione passes the LLM:

  • Title
  • Description
  • Price + currency
  • Vendor
  • Categories
  • Any answers you provided in the Enrichment Wizard (target audience, materials, key benefits, etc.)

What the LLM does NOT use​

  • Real customer reviews (Google / Trustpilot / internal)
  • Returns rate
  • Sales / conversion data
  • External catalog comparatives
  • Manufacturer certifications (ISO, CE, GOTS, OEKO-TEX, etc.)
  • Lifecycle test results
  • Sustainability databases

What this means for you​

  1. Scores are synthetic opinion, not verified facts.
  2. Same product can produce different scores between runs if the model temperature is non-zero.
  3. Useful relatively, not absolutely — the LLM has common sense (Hermès → luxury, Primark → budget). Scores help you differentiate products within your own catalog; they don't benchmark you against competitors.
  4. typical_competitors has the same limitation — they're plausible inferences, not verified market data.

How to tell which scores are grounded​

Each product shows a badge next to the Quality Scores:

  • 🟢 Data-grounded — external evidence backs the score (future: reviews, returns, certifications)
  • 🔵 AI + owner hints — you filled the Enrichment Wizard for this product
  • 🟡 AI-inferred — pure LLM opinion based on title/description/vendor (default)

How we're fixing this​

Already shipped (April 2026)​

Enrichment Wizard — evidence questions. The Wizard now has a dedicated Evidence section after the original context questions. Five new fields, all optional:

  • Warranty — None / 6m / 1y / 2y / 3y / 5y / 10y / Lifetime
  • Certifications — comma-separated list (ISO 9001, CE, GOTS, OEKO-TEX, MIL-STD-810, B-Corp, Fair Trade, etc.)
  • Returns rate — brackets from <2% to >20%, plus a Don't know opt-out
  • Customer reviews — aggregate rating + count from any source (Google, Trustpilot, internal, marketplaces)
  • Manufacturing origin — country + manufacturer name

Filling 3+ of these upgrades your product's badge from amber (AI-inferred) to green (Data-grounded). Filling 1-2 upgrades to cyan (AI + owner hints). The wizard tells you when you've reached the evidence section and what filling does.

Owner-verified Typical Competitors. The Edit tab on a product now has a Typical Competitors section where you can list the real competing products (brand + model + optional reference price + notes). When at least one entry is saved, Clione flags the list as owner-verified and stops letting the LLM regenerate it on re-enrichment. This is the same grounding pattern as the evidence wizard — your input wins over the LLM's guess.

If you don't fill anything, the LLM's inferred competitors continue to appear with an AI-INFERRED label so you always know what you're looking at.

Roadmap (coming)​

  1. External data connectors — Google Analytics conversion rate, Judge.me & Yotpo reviews APIs, Shopify Refunds API / BigCommerce Returns webhook
  2. Per-score provenance — each individual score carries its own source (owner / reviews / returns / llm_synthetic / composite) with an evidence trail, and the UI shows why this score on demand
  3. Composite scoring — when multiple sources disagree, the dashboard explains the weighted result instead of picking one and hiding the others

See the full grounding roadmap for technical detail.

Until the external connectors land, treat scores as the LLM's reading of your catalog text, sharpened by whatever evidence + competitors you feed in via the Wizard and Edit tab.