Data Extraction & Integration

Despite the fact that popular e-commerce platforms such as Amazon, Shopify, and Walmart provide various reports in their interface and offer APIs, this data is often insufficient to gain an edge over competitors and improve sales efficiency. Many data points are not directly accessible or are located in different places, making them difficult to apply directly.

Proper Data Extraction is the first and crucial step for gathering market data for subsequent analysis to stay informed about trends.

The process of data integration and processing consists of the following two stages:

Data Retrieval Stage – through APIs (direct or third-party service) or by parsing. Data is regularly collected and placed in a Data Lake. It is essential to store all collected and minimally processed data. Often, not all data is needed immediately, but as data accumulates, it can become a subject of future analysis and a competitive advantage. Many parameters may seem redundant but can provide additional insights with a large amount of data (a year or more).

Data Processing Stage – raw data is processed by scripts into a structured and processed form in a Data Warehouse (in a database or structured reports). These are data ready for use, verified, and cleaned. The data structure is created depending on the existing structure or the reports and BI reports that need the data.

All data retrieval methods can be divided into three ways: using official API, Third-Party APIs or Parsing.

API – if the service or marketplace has an API (a programmatic mechanism for retrieving data), this is the ideal option. Unfortunately, many APIs do not provide all data or provide it with significant limitations. For example, Amazon SP-API does not provide the ability to get user reviews or Vendor Invoices.

Third-Party APIs – Some companies and services provide fairly good data scraping that the vendor lacks. For example, this includes user reviews and product data for Amazon. Using SP API, you can only get limited product data and cannot get, for instance, user reviews. But some services provide this. This is also a good and recommended option.

Parsing – In the absence of an API, data can be collected by making requests to the web server or directly from the browser (using Selenium), emulating user actions. It is important to understand that this method requires constant maintenance. First, the structure of data and pages may change; second, many systems have bot detection methods, which can complicate the collection of large volumes of information.

The speed of data retrieval and the response mechanism are also extremely important. For example, if a competitor starts selling the same product at a lower price, you need to find out about it as early as possible; otherwise, you will lose profit. It's important to know this BEFORE your sales start to decline. A negative review will begin to deter your customers immediately after it is posted, and it's crucial to respond to it promptly.

We have extensive experience in Data Extraction for e-commerce companies. Our team successfully implements data collection technologies through APIs and parsing methods like Selenium. We set up automated data collection into a Data Lake and subsequent processing into a Data Warehouse. This allows our clients to receive structured and cleansed data, ready for market analysis and strategic decision-making. We also integrate advanced BI tools such as Tableau, Looker Studio, Power BI, and Google Spreadsheets to help you stay competitive and effectively respond to market changes.