How to get price history data
What price history data is, why it cannot be backfilled, and how to get it through an API instead of building collection yourself.
Price history is the record of what a product has cost, at which seller, over time. It sounds like a lookup and is actually the hardest thing in commerce data to acquire, because it only accumulates forward. Nobody can sell you the history of a product they were not watching last year.
That single property decides the build-versus-buy question. Every other component — search, matching, alerting — can be built in a quarter. History cannot be built at all; it can only be started. A team that starts today has a ninety-day window in ninety days, and there is no shortcut.
What to look for in a history API: per-seller series rather than a blended average, since blending hides the seller you would actually buy from; append-only storage, so a figure you cited last quarter still reads the same today; and provenance on each observation, so you can weigh a value rather than trust it uniformly.
What to be suspicious of: a single price per product per day. Real prices change at odd hours and hold for uneven stretches, and a daily snapshot silently converts that into something tidier and less true.
Keep reading
What is commerce intelligence?
Commerce intelligence is the layer above price monitoring: an index of what exists, who sells it, at what, and what that means.
Why percentile beats percent-off
A percentile against a product's own history is a defensible measure of discount depth; percent-off a reference price is not.
Product matching and why it fails quietly
How cross-seller product matching works, the three ways it fails, and why published match confidence matters.
GTIN, UPC, EAN and ASIN
How product identifiers relate, why check digits matter, and what to do when there is no identifier at all.
Data provenance in commerce data
Why every price should carry its origin and a confidence weight, and what goes wrong when it does not.