Our Methodology
No sponsored content. No affiliate bias in rankings. Every score, comparison, and recommendation on Details is derived from structured data and transparent formulas.
Data Collection
We pull raw product data from manufacturer sources and retail APIs, including specifications, availability, and customer reviews. Every data point is timestamped and version-tracked.
- Technical specs sourced directly from product APIs
- Customer reviews analyzed for sentiment patterns
- New products discovered automatically via category monitoring
Spec Normalization
Raw data is messy. We normalize every specification into strict, typed values using AI-assisted parsing. "15 pounds" and "15lbs" and "15 lb" all become the same structured number.
- Category-specific schemas enforce data types (numbers, enums, booleans)
- AI parsing converts free-text specs into structured data
- Unit standardization across all products in a category
- Missing data flagged transparently — we never fabricate specs
Details Score
Our composite score (0–100) combines three signals into a single at-a-glance rating. It is not a subjective opinion — it is a formula applied consistently across every product, and the weights are published below.
- Customer rating, 40% — shrunk toward the category average in proportion to how few reviews back it, so a 5.0 from 30 reviews cannot outrank a 4.6 from 50,000
- Spec completeness, 30% — how much of the category spec sheet we hold for the product
- Popularity, 30% — review count on a log scale, as evidence of real-world adoption
- Scores are recalculated whenever the underlying data changes
AI-Powered Verdicts
Comparison verdicts and "who should buy" recommendations are generated by AI that analyzes the structured spec data — not marketing copy. The AI sees the same numbers you do.
- Verdicts based on normalized specs, not subjective opinion
- Key differences extracted automatically from spec deltas
- Advantages quantified with specific numbers (e.g., "2× more suction")
- AI text limited to 300 characters — density over fluff
By the Numbers
See It in Action
Browse our categories to see data-driven comparisons built on this methodology.
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