Compare changes for a fixed product set
Track the agreed offers over successive observations. Preserve variant and seller identifiers so a change in pack size or merchant is not mistaken for a price increase.
Product Price History Dataset
Specify product price history by seller, market and observation interval. Define identifiers, currencies, availability and the dates your analysis needs.
Markets on requestAvailability on inquiry13 proposed fields
Coverage, pricing and delivery confirmed individually. Requests open your email app.Make product price changes comparable
A price-history dataset is a series of dated observations for identifiable product offers. Its usefulness depends on matching the same item, variant and seller across collection runs. Keep currency, stock state, shipping and promotional conditions separate from the displayed item price. One current product snapshot does not provide a historical series, and an unavailable observation should not be silently replaced with an estimated or carried-forward price.
Review promotions and stock signals
Keep regular prices, displayed discounts and source availability labels in separate fields. A missing offer, an out-of-stock message and a failed observation represent different conditions.
Prepare reproducible market research
Define a stable sampling schedule and record when each value was collected. Analysts can then describe the observed time window and gaps instead of assuming uninterrupted price coverage.
Specify the offer and comparison rules
Provide product URLs or identifiers, the target market and whether the unit is a product, variant or seller offer. Matching equivalent items across stores may require brand, model, pack size and a public product identifier. Shipping, tax, membership conditions and coupons can change the payable total. Decide which components are in scope and avoid comparing differently conditioned prices as if they were equivalent.
Agree on the time window and observation process
State the required start date, interval and treatment of collection gaps. Existing product scrapers can provide supported current observations, while a historical series requires repeated collection and storage. This specification does not contain a pre-existing archive of past prices. Backdated coverage, change alerts and recurring delivery must be confirmed separately before they are included in an order.
Explore related collection tools
These tools cover the actions described below. Dataset discovery, qualification, historical coverage and recurring delivery are confirmed separately.
Define your structure
Data fields to discuss
Use this field guide to plan your request. Coverage and completeness will be confirmed individually. The CSV template contains column headers for planning.
| Field | Column name | Description |
|---|---|---|
| Product ID | product_id | Source product identifier, such as an ASIN or merchant product ID. |
| Variant ID | variant_id | Size, color or other specific variant identifier when available. |
| Product title | product_title | Published product name at observation time. |
| Brand | brand | Brand stated by the source. |
| Seller | seller | Merchant or seller associated with the observed offer. |
| Observed price | price | Displayed item price without inventing absent values. |
| Currency | currency | Currency of the price; no implicit conversion between observations. |
| Reference price | reference_price | Separately published list or previous price, if the source returns one. |
| Availability label | availability | Source stock or availability wording at the time of collection. |
| Shipping price | shipping_price | Explicit shipping charge for the agreed context, if available. |
| Market context | market_context | Agreed country, variant and other conditions needed to interpret the offer. |
| Observed at | observed_at | Timestamp of this price observation. |
| Product URL | product_url | Source offer page used to trace the observation. |
From requirements to a clear scope
Share your requirements
Send your target sources, locations, essential fields, dates and expected volume. Mention the Product Price History Dataset so the team has context.
Confirm the details
Discuss availability, source coverage, sample requirements, pricing and delivery timing before deciding.
Agree on the output
Confirm the final fields, file format and delivery method for the agreed dataset.
Frequently asked questions
Is this a ready-made download?
This page defines a dataset specification. Contact Extracto to confirm source coverage, available records, price and delivery timing for your requirements. A displayed sample is a saved example with its own location and collection date.
Can I download last year’s price history?
Historical coverage must be confirmed for the requested source and products. A scraper run today cannot reconstruct past prices that were not recorded or otherwise made available by a suitable source.
Can the same product be matched across stores?
Include product identifiers and variant requirements in your inquiry. Matching can require additional normalization and review. Similar titles alone do not establish that pack sizes, specifications or seller conditions are equivalent.
Are current product scrapers available?
Extracto has Amazon and Shopify product scrapers for supported inputs. They collect current source observations. Building a dated history, retaining past snapshots or delivering a recurring series requires a separately confirmed workflow.
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Your market. Your requirements.
Discuss your dataset requirements
Have a narrower location, a specific field list or a target volume in mind? Send your requirements to the Extracto team.