Amazon Product Dataset

Product data from Amazon is delivered by WebDataInsights in CSV, Excel (XLS/XLSX), JSON, and API feed formats as default delivery options. For data engineering teams with larger data pipelines, an additional option for delivering Amazon product datasets in Parquet format is available upon request, facilitating quick column-based access to Amazon product dataset files with millions of rows when loaded into Apache Spark, Databricks, Snowflake, or BigQuery. The same schema is used across all data formats so that your ingesting pipelines remain unchanged with the selected delivery type.

The update frequency will depend on the type of data you require as well as the plan that you subscribe to. The pricing data on the Amazon product data set can be updated as often as a couple of hours, and it will incorporate information on intraday lightning deal launches, price cuts, and coupons. The product listing data is updated on a daily basis. Availability and inventory data will be updated daily, with real-time updates being offered for enterprise-level users who track fast-moving categories.

Indeed, the personalization process forms a vital element of the provision of the Amazon product database by WebDataInsights. In contrast to the generic export option, users indicate which types of products they need, what information they require, on which markets (US, UK, EU, CA, IN, or their combinations) the data should be provided, and how often. Thus, your database will contain only relevant data which will not distract your ingestion processes or increase storage expenses unnecessarily.

Yes. The Amazon product database has a historical database that goes back more than three years on price history. It includes current prices, list prices, deal prices, and coupon amounts with timestamps on when the changes occurred. Historical data is critical in establishing a time-series model for forecasting, evaluating price elasticity per category, recognizing seasonal promotions, and comparing your price strategy against those used by other companies. Historical data can be purchased either as a historical database or an ongoing database addition to the delivery.

MAP tracking is another application of our Amazon products dataset that sees widespread use from our brand customers. This particular sub-dataset stores the current price of each seller on all Amazon marketplaces listings, updated at consistent intervals. Brands can set up automated logic comparing prices against the MAP limit; if a seller’s price is below the MAP limit, an alert is automatically sent to the brand’s channel compliance team. Our Amazon products dataset also logs historical price data of sellers, which can be used by compliance teams to track violations.

Absolutely. The availability sub-dataset in the Amazon products data set is responsible for recording the availability of each SKU in the FBA, FBM, and 1P fulfillment methods. These granular details include the availability of an item being in stock, out of stock, limited quantity, third party only, and discontinued. All this historical data enables you to track how long your SKUs have been out of stock.

WebDataInsights harvests Amazon product dataset data only from the public sections of the Amazon marketplace via ethical and rate-based harvesting practices. Data points harvested are those available for viewing by any average user visiting Amazon.com – the name of products, prices displayed publicly, sellers’ information, and reviews submitted by customers publicly. No authentication is required to obtain this data, and there is no use of any restricted API nor bypassing of security features at all. Companies utilizing the Amazon product dataset for analysis are within normal commercial practice.

This difference is crucial. An unrefined scrape yields messy, inconsistent data extracted from HTML code that will need significant data engineering before it is ready for analysis. The Amazon products data set provided by WebDataInsights is a complete product where the schema normalization, data cleansing, and de-duplication have already been performed. Data types are properly structured, categorizations standardized, price points in numeric format, and duplicates removed through multiple rounds of harvesting. We deliver our customers a ready-for-use Amazon products data set, and not one that will take weeks to prepare before you can analyze any data at all.