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Estimated from public data — and we show how: Store counts and best-seller ranks are what we crawled that day. Sales and traffic are modelled from those, so we label them as estimates and say how each one is formed.
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Example product
This product is the #7 best-seller at A little bit of hope (~36 products), has stayed in the top 10 for 4 days, and shows up on ~288 other stores under the same title. Winner score 46/100 — moderate.
- Winner score
- 46/100
- Price
- $100.00
- Best-seller rank
- #7
- Stores selling this
- ~288
- Advertising
- None on file
Moderate
Price last seen on the store's page
of the ~36 products this store sells
Tracked stores listing this same title — not a live crawl of every shop
No ad match on file — not the same as confirmed zero spend
How this product scores 46 out of 100
Built from three things we can see. It estimates how strongly a product is performing — it is never sales, revenue or ad spend.
Ranked #7 of the ~36 products this store sells. A high rank in a big store counts for more than one in a small store.
How many days it has stayed in this store’s top 10 over the last 30 days. A rank that holds is harder to fake than one good day.
No live ad match is backing this product up right now. About 288 tracked stores already list the same title, which is too crowded to count as an edge — it adds no points here.
Where else this product is sold
The store selling this product
How busy the store looks, and how many products it sells.
More products from this store
Listing details
Reference data taken from the store's own public product listing.
Price history
100 → 100 USD
Observed shelf price across 2 scans (signal, not live checkout)
