Retailers aren’t short on data — the challenge is making sense of it at scale. To stay competitive, businesses must not only maintain a clear view of internal operations but also track key external factors such as competitor pricing, promotions and viral social media trends. However, with so much data to collect and process, manual tracking is no longer a viable option.
One of the most effective ways to automatically gather data is through web scraping. By using bots to extract publicly available information, web scraping delivers unstructured but real-time insights that fuel smarter decision-making. Whether for market research or competitive analysis, having access to real-time market data allows retailers to stop making decisions within a vacuum and instead make decisions based on more accurate information.
Types of Data to Scrape
The first step is ensuring you’re gathering the right data. Key data categories retailers should automatically collect include:
- Real-time price tracking: Real-time price tracking is often used for dynamic pricing algorithms, which allow retailers to automatically adjust prices to stay competitive. It’s also crucial to take a global view, as pricing strategies often vary by region. Retailers should track not just base prices but also short-term discounts, promotional offers and seasonal/long-term pricing trends;
- Product reviews: While individual product reviews are often copyrighted, tracking the volume of reviews and average ratings provides insights into customer interest, product popularity and consumer sentiment;
- Inventory and sales estimations: Some ecommerce sites display inventory levels, and tracking this over time can provide valuable insights into sales trends and product popularity. Large marketplaces such as Amazon can provide a gold mine of useful data, including product availability, seller activity and pricing history. Even if you don’t sell on Amazon, analyzing this data can help inform pricing strategies and identify emerging trends; and
- Stock market and financial data: For any competitor that is public, analyzing stock performance and earnings reports can reveal an overview of the company’s financial health.
All of this data can serve as a foundation for go-to-market strategies for new products while also helping to address inefficiencies in inventory management. Additionally, it enables businesses to adapt quickly to trending products in the B2C market.
The Ethical and Legal Considerations of Web Scraping
Web scraping to gather competitive intelligence is a widely used and accepted business practice; however, it’s important to make sure methods comply with legal and ethical standards. The legality of data scraping depends on two key factors: the type of data being collected and the method of collection.
While this is not legal advice, scraping publicly available data is generally permissible as long as it does not require a login to access. When a website requires a login, users typically agree to terms of service that often prohibit data collection. Ignoring these terms and proceeding with data scraping could expose your company to legal risk.
However, even within this general guideline of focusing on what is “publicly available,” it’s important to avoid scraping copyrighted content or personally identifiable information (PII) — such as dates of birth, employment history and social media posts linked to an individual. Regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) impose strict requirements on data collection, and noncompliance can lead to serious legal consequences.
It is highly recommended to consult with a legal professional before engaging in any web scraping as it’s the only way to be sure that you’re not exposing your business to undue legal risk.
Technology Considerations
If you’ve ever explored web scraping, you know that competitor websites often deploy anti-scraping measures like bot detection systems, CAPTCHAs and geo-restrictions to block automated data extraction — just as your own company might. While VPNs can work for occasional scraping tasks, a residential or ISP proxy service provides a more scalable, business-grade solution. These services allow scrapers to appear as genuine users by rotating IP addresses, helping to bypass rate limits, avoid detection from sites monitoring repeated requests and access data globally.
Once data is collected, making it usable is the next challenge. Websites are built with HTML, meaning raw scraped data often appears cluttered and difficult to interpret. Several tools and programming languages can help structure this data so it can be analyzed quickly.
Python is the most popular choice for web scraping, thanks to its powerful libraries like BeautifulSoup, Scrapy and Selenium, which enable efficient data extraction, cleaning and analysis. The data can then be moved to a SQL database or other data storage solution for further analysis. While Excel VBA and Power Query can handle small-scale projects, they are rarely used in business settings given their lack of scalability.
If you’re interested in diving into this further, here is a step-by-step guide on using Python for web scraping.
Gaining a Competitive Edge with Competitive Data
In today’s fast-moving, fiercely competitive retail landscape, leveraging all available business intelligence can make all the difference. With vast amounts of data at their disposal, businesses must incorporate as many external insights into their decision-making process as possible to drive more informed, strategic decisions.
Technology like web scraping provides a scalable, automated way to monitor critical external factors like pricing, promotions, customer sentiment and financial trends in real time. By adopting a smart, compliant data strategy, retailers can replace guesswork with data-driven decision-making and gain a competitive edge.
Justas Palekas is Head of Product at IPRoyal, a premium residential proxy provider, where he leads major marketing and product initiatives, working across SEO, paid search, affiliate marketing, email marketing and retention. He plays a key role in project management, driving new features, fostering innovation and contributing to the overall growth of IPRoyal’s products.