Top 5 e-Commerce Web Scraping Use Cases in 2024

The growing volume of online data is accelerating business adoption of data-driven decision making strategies and it has been estimated that data-driven companies are 19 times more likely to be profitable, and are 52% better at understanding their customers. (see Figure 1) This makes web scraping crucial for businesses that rely on data, especially online e-commerce platforms which make use of publicly available data in order to:

• Analyze competitors
• Monitor customers
• Generate leads

This article discusses top five use cases of web scraping in e-commerce and the challenges of scraping e-commerce websites.

Figure 1: The total amount of data created, captured, copied, and consumed worldwide 2010-2020, with forecasts to 2025

Source: Statista¹

Top eCommerce data scrapers of 2024: Quick comparison

Vendors are ranked according to their average score, with the exception of the products of the article’s sponsors which are linked to sponsor websites.

What is e-commerce data?

E-commerce data is any type of data collected from e-commerce platforms and online retail marketplaces which can include:

• Customer data: demographics, search queries, interests, and purchasing habits.
• Product data: price ranges, stock availability, vendors, and ratings.
• Transaction data: payment methods, shipping costs, and applied taxes.

Most e-commerce data is public since e-commerce platforms display their product data and transaction data to customers, and can be scraped using traditional web scrapers or RPA bots.

Top 5 use cases of web scraping in e-commerce

Web scraping automate the extraction of online e-commerce data, therefore, online marketplaces can leverage web scrapers or web scraping APIs for:

1. Price comparison

As dynamic pricing models are rising in popularity, it is important for businesses to optimize their prices based on consumption trends and competitor behavior. Crawling e-commerce websites and platforms can help businesses understand the general value of a product in the market and customize prices accordingly.

Additionally, web scrapers can be programmed to crawl data in an almost real time manner, thus e-commerce platforms can leverage this data to provide campaigns on products which competitors are displaying at higher prices.

2. Targeted advertisements

Web scraping can benefit from integrating location-based IPs to extract data from a certain geographical zone. An IP-enabled web scraper can provide data about a customer’s purchase journey, such as their search queries, geographical locations, ratings or comments on certain products, experience with product set up, as well as seasonal or periodic requirements. This data can be used to launch targeted campaigns based on locations, market trends and customer behavior.

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Bright Data’s Data Collector implements residential IPs in order to extract location-based data from e-commerce platforms and marketplaces, and deliver it to clients in the desired format (e.g. JSON, CSV, excel).

3. Product research

Product research is the process of understanding products on the market and estimating the success and failure of launching a new product or modifying an existing one in terms of features or prices. Web scrapers can extract all kinds of product data including images, descriptions, prices, reviews, etc. The extracted data can be used to identify:

• Products in high demand
• Features useful and significant to users
• Niche ideas in the market

In order to understand how to gain a competitive edge with scraping product data, read our comprehensive guide on the topic.

4. Customer sentiment analysis

Identifying customer sentiment is crucial for e-commerce. Web scraping provides e-commerce platforms with data from customers’ reviews and feedback which can be used for optimizing existing products or launching customized new products based on consumer behavior and requirements.

5. Lead generation

Web scrapers can collect data about customers’ contact information, such as email address, phone number, social media accounts. This data can be used by e-commerce marketers to reach out to potential customers and introduce them to the platform.

There are numerous applications of web scraping for marketing and sales for both e-commerce and non e-commerce platforms.

Check out how to use web scrapers for Instagram scraping.

What are the challenges of scraping e-commerce websites?

Automating data extraction from e-commerce websites can be a difficult task due to:

• Interface changes: Most e-commerce websites change their formats and fonts to enhance customer experience and attract a diverse audience. Changes in a website’s interface requires reprogramming the scraping bot to match the new content display.
• Anti-scraping techniques: Many e-commerce platforms implement anti-scraping techniques, such as CAPTCHAs, to ensure that their visitors are humans and decrease network congestion. CAPTCHAs are difficult to bypass by web scrapers, however, some web scrapers integrate CAPTCHA solvers to tackle this issue.
• Cloaking: Cloaking is the practice of presenting different data if a website believes that the visitor is a bot. Many e-commerce websites utilize cloaking to feed bots with incorrect product data or redirect them to irrelevant URLs. However, cloaking is considered illegal and a violation of Google’s Webmaster Guidelines, therefore, websites that use cloaking often get banned from Google Search.

Web scraping faces other challenges such IP bans and honeypots. Feel free to read our ultimate guide to web scraping best practices to learn more.

If you believe that your business may benefit from a web scraping solution, check our list of web crawlers to find the best vendor for you. Also, don’t forget to check out our sortable/filterable list of e-commerce software.

For more on web scraping

To learn more about how web scraping works and its applications in different industries, feel free to read our in-depth articles:

• Top 5 Web Scraping Case Studies & Success Stories
• Top 18 Web Scraping Applications & Use Cases
• What is Web Crawling? How it works & Examples

And we can guide you through the process:

External links

• 1. Taylor, P. (Sep 8, 2022). Amount of data created, consumed, and stored 2010-2020, with forecasts to 2025. Statista. Retrieved January 11, 2023.