Ecommerce web scraping is a process of extracting data from several ecommerce websites using automated tools and software. When we say data, it can include product information, product features, pricing, customer reviews, ratings and the like.
Today, more than ever, web scraping has become necessary because businesses need these data points to make better product, customer and strategic decisions.
A study shows that data-driven businesses are 19% more likely to be profitable, and 52% more likely to understand their customers better.
Top Ecommerce Data Types to Scrape
There are different kinds of data that businesses can collate during web scraping;
- Product information, which includes product names, descriptions, images, and specifications.
- Pricing data, which includes the price of the product, discounts, promotions, and shipping costs.
- Information on whether the product is in stock or out of stock.
- Reviews, ratings and feedback given by customers who have purchased the product.
- Sales data related to the number of sales, revenue generated, and other sales-related metrics.
- Customer information like demographics, interests, purchase history and such.
- Competitor data related to pricing, product offerings, and other relevant information.
- Search engine rankings on how well the product ranks in search engine results pages.
Why is Ecommerce Web Scraping Necessary?
Aside from the primary fact that data that can be used to drive more strategic and relevant business decisions, ecommerce data scraping has a number of benefits.
It can help businesses gain a competitive advantage by providing insights into their competitors’ pricing, product offerings, and marketing strategies. Businesses can optimise their pricing strategies by analysing data on competitor pricing, customer behaviour, and market trends.
Businesses can better understand customer preferences, buying habits, and pain points, thus improving overall customer experience. They can monitor product availability and stock levels, thus managing their inventory more efficiently. They can use this as a cost-effective way to conduct market research and collect large amounts of data quickly and easily.
7 Challenges in Ecommerce Web Scraping
A Merit expert says, “When it comes to working with any form of data, among the first challenges that arise is adhering to data privacy and protection and ensuring that data is being taken and used ethically and transparently.”
While this is just one challenge, let’s look at what else can potentially be a roadblock to ecommerce data scraping.
- E-commerce web scraping may be subject to legal and ethical considerations. Web scraping may be prohibited or restricted by the website’s terms of service, and certain types of data may be subject to privacy or copyright laws.
- Ensuring the accuracy and quality of the scraped data can be a challenge, as websites may frequently change their layouts or data structures, causing errors or inaccuracies in the collected data.
- Scraping can put a strain on the target website’s servers and may result in security issues if not done correctly. Websites may employ measures to prevent web scraping, such as captchas or IP blocking.
- To avoid being detected by the target website, web scraping may require the use of proxies or rotating IP addresses, which can be expensive and may require additional setup and management.
- Scraping large amounts of data can be time-consuming and may require significant computing power for data processing and storage.
- E-commerce websites may have dynamic content, such as pricing or stock availability, that is subject to frequent changes. This can require continuous monitoring and updating of scraped data.
- Some websites may restrict access to certain regions or countries, which can make web scraping difficult or impossible.
For example, the UK has stringent data protection laws, such as the General Data Protection Regulation (GDPR), that govern the collection, processing, and use of personal data.
Companies that engage in ecommerce web scraping must comply with these laws and ensure that they obtain consent before collecting personal data. Similarly, ecommerce websites that process payments are subject to payment processing laws in the UK, which require compliance with specific security and privacy standards. Companies must ensure that they do not violate these laws when collecting or using payment processing data.
Ecommerce Web Scraping Best Practices
Now that we’ve seen how, what and why of ecommerce web scraping, let’s look at best practices your business should follow to implement this process.
Review terms and conditions of each website
Before conducting web scraping, review the website’s terms of service and ensure that you are not violating any rules or agreements. Some websites may prohibit web scraping or have specific rules about how data can be collected.
Use reliable and compliant web scraping tools
Use reliable and trusted web scraping tools to avoid security issues and ensure the accuracy of the collected data.
Prevent interference with website traffic
Ensure that web scraping is not causing excessive traffic on the target website. This can cause the website to slow down or crash, affecting the user experience for other visitors. Then, collect only the necessary data to avoid overloading your systems or impacting the performance of the target website.
Monitor website structure
Also remember that websites may update their data structure or layout, which can affect the accuracy of the data collected through web scraping. Regularly monitor for any changes to the website structure and update your scraping tool accordingly.
Minimise scraping frequency
Avoid excessive scraping frequency, which can put a strain on the target website’s servers. Set appropriate intervals between scraping sessions to ensure minimal impact on the website performance.
Avoid scraping personal and sensitive data without permission
Ensure that personal or sensitive data is not collected without explicit permission and is handled with appropriate care and security measures.
Merit’s Expertise in Ecommerce Data and Intelligence
Our state-of-the-art ecommerce data harvesting engine collects raw data and provides actionable insights;
- Three to four times faster than standard scrapers
- At lower cost
- With Increased accuracy (up to 30% compared to standard scrapers)
Our powerful, new scraper engine can gather massive data sets from multiple sites and geographies in real-time so you can stay informed on customer behaviours and market trends.
Merit’s eCommerce and retail data engine provides a high degree of confidence in insights generated from analytics – thanks to confidence in the data quality and access to enriched data.
To know more, visit: https://www.meritdata-tech.com/service/data/retail-data/
Related Case Studies
-
01 /
AI Driven Fashion Product Image Processing at Scale
Learn how a global consumer and design trends forecasting authority collects fashion data daily and transforms it to provide meaningful insight into breaking and long-term trends.
-
02 /
A Bespoke Retail Data Solution for Better Insights and Forecasting
A pioneer in the retail industry with an online solution providing easy access to global retailer data, had the challenge of creating retailer profiles through the data capture of financial and operational location information.