Boosting Your Business With E-Commerce Web Scraping
Web scraping is a widely used process that helps businesses gather data from different digital sources and use it for further analysis.
It is performed either manually or through specialized tools that collect the content of the targeted websites and convert it into a preferred format to glean insights and make informed choices.
This process benefits businesses operating in various sectors in a number of ways, especially E-commerce. To help you understand e-commerce web scraping, we’ll cover the main use cases of e-commerce data scraping and a few data scraping challenges and solutions out there.
But first, let’s have a look at the most common types of e-commerce data.
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Types of e-commerce data for scraping
E-commerce data is data related to the e-commerce market that gives brands insights into consumer behavior and enhances their experience. Following are the four main types of e-commerce data that businesses can scrape:
- Product data – Product data includes information about a product, such as name, description, category, price, reviews, manufacturer and supplier details, and brand information. These data points help brands evaluate which products customers often search for, view, buy, and compare with other products. They use these insights for marketing strategy, pricing, inventory, supply chain, and customer retention.
- Store data – Data, related to providers, sellers, and platforms, builds an all-inclusive database of competitors. Businesses can use this data to drive competitive analysis and monitor competitor activities.
- Sales data – Sales data and third-party datasets are useful in tracking sales and forecast trends. Historical sales data enhances analysis for price optimization, stock management, demand prediction, and strategy planning.
- Customer data – This kind of e-commerce data provides information about digital shoppers and their shopping. Customer data include demographic data, purchasing behavioral data, preferences, historical data, and search patterns. Such data can help analyze customer behavior and offer a more personalized shopping experience.
Use Cases of E-commerce Web Scraping
E-commerce web scraping helps businesses collect data and take the lead in the industry. Below are the primary use cases of web scraping:
1- Market Analysis & Research
Market research is the ultimate source of information for new or existing businesses. Data scraping allows researchers to find important business data in real-time, like industry trends, research and development, and price analysis. This process makes data collection easier and cost-effective.
2- Price Intelligence
Buyers frequently try to find the best service or product at a reasonable price. Such factors motivate businesses to perform pricing comparisons, including sales and discounted prices, price history, and so on. They use web scraping to collect data from sundry E-commerce stores to make data-driven decisions.
3- Brand Visibility
Web scraping helps users organize data, draw insights, and build dynamic SEO strategies. Keywords in the obtained data can assist users in improving search engine rankings. This process greatly helps lead the competition and boost brand visibility.
4- Competitor Monitoring
Competitive intelligence is another type of market research. E-commerce web scraping allows businesses to discover trends and business opportunities by keeping tabs on the industry and competitors’ activities.
It gathers competitive data useful in tracking information, like real-time prices, product updates, customer data, reviews, and feedback.
5- Targeted Advertisements
Web scraping can also help with targeted advertisements by integrating location-based IP addresses to collect data from certain geographical regions. Collecting data related to customers’ purchase journeys can help businesses adjust their advertising campaigns according to market trends, locations, and consumer behavior.
Web Scraping Challenges and Solutions
Though an increasing number of companies use web scraping to collect business data, the process is not always smooth. They might face different challenges at the time of scraping data, such as:
- IP bans – When a website receives too many requests from the same IP address, it usually ends up blocking or banning that particular IP address to prevent further data scraping.
- CAPTCHAs – CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is used to differentiate humans from scrapers by displaying pictures or logical problems that may appear easier to solve to humans than bots.
- Honeypot traps – It is a trap containing hidden elements or links that put the crawling bot into an infinite loop of requests and restrict further data extraction.
- Structural changes – Webpages are often based on HTML files that undergo changes every now and then. These frequent changes affect the web scraper setup and sometimes result in data loss.
But the good part is that there are some solutions designed for businesses to bypass any limitations and make the most of the valuable data. Many businesses use scraper APIs, which are specialized tools designed to collect web data while handling CAPTCHAs, rendering JavaScript, and avoiding geo-restrictions with an API call.
Proxy servers are another common choice among brands to overcome web scraping challenges. These servers are capable of changing IPs and making scrapers appear as normal users to enable a safe data scraping process.
Summary
Web scraping is a powerful technique for accessing data to make better business decisions. While different websites implement different anti-scraping measures, you can rely on the above-mentioned solutions to make the most of the benefits scrapers have to offer.
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