Rating 50% Volume 50%
A handful of excellent reviews counts — but cannot carry the score. With thin data, the star average leads.
Volume signal saturates at 100 reviews.
Every product on PickSmartly earns a PM Score from 0–10. Most sites keep that number in a black box — here is the exact formula, every weight, and every tier that produces it.
Two public Amazon signals go in; one number comes out. The customer rating measures quality; the review count measures consensus — how many people are standing behind that rating.
PM Score = wQ × Quality + wC × Consensus
The weights are not fixed: they shift with review volume, in three tiers. The fewer reviews exist, the more the star average has to say; once tens of thousands have weighed in, the crowd is the evidence.
Each product is scored in exactly one phase, decided by its review count.
Rating 50% Volume 50%
A handful of excellent reviews counts — but cannot carry the score. With thin data, the star average leads.
Volume signal saturates at 100 reviews.
Rating 30% Volume 70%
The crowd has spoken. Consensus now dominates, and a lone wave of early hype can no longer prop a product up.
Volume signal saturates at 1,000 reviews.
Rating 10% Volume 90%
At this scale the volume signal saturates at maximum. A 4.2★ across 25,000 reviews is what the world actually receives.
Volume signal saturates at 1,000 reviews.
One product, one rating — three phases. The same 4.5☆ earns a higher score as consensus grows, while the star average itself matters less and less. Every value below is computed live by the same formula the rankings use.
Why 8.5 → 9.7 → 9.9 for the same stars? Quality contributes 4.5, then 2.7, then 0.9 — as consensus firms up, the crowd’s verdict takes over the score.
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0.0 × 0.5 + 10.0 × 0.5 = 5.00
A $19 kettle and a $190 kettle face the identical rubric. Price is a purchase decision, not a quality signal — and Amazon prices move too fast to score against.
Both inputs — star rating and review count — come from Amazon’s own public data. Nothing proprietary, nothing self-reported by brands.
The same equation scores every product on the site, with no per-brand overrides, no manual boosts, and no exceptions — including the ones on this page.