E-commerce has been experiencing accelerated growth over the recent years. Nowadays, online businesses are rife with data scraping opportunities. As both businesses and customers leave increasing amounts of data during transactions, all of this information can be garnered to gain insights into profitable opportunities.
Data can be scraped from nearly any e-commerce platform to great effect. While some platforms might be more protective than others, each of them can still provide a lot of valuable insights through data. However, understanding which data sources are the most beneficial for business purposes will greatly improve the efficiency of the entire data scraping and analysis pipeline.
Insightful data sources
Keywords and rankings
Most of the largest e-commerce platforms have a search function. Therefore, keywords become the bread and butter of any such platform. Understanding how to ensure that products appear first in internal search results will bring greatly increased revenue to both sellers and service providers.
There are two primary data sources to be scraped: keywords for relevant products and the rankings. By combining these two sources, insight into the ranking algorithm can be gained through data analysis. Over time, a fairly accurate understanding of the ranking algorithm can be acquired, which can then be used to drive revenue.
If general purpose, search engines are anything to go by, ranking in the first place as opposed to the 10th increases the clickthrough rate ten-fold. Therefore, understanding how the search algorithm works in e-commerce platforms and ranking highly can be a tremendous driving force for business growth.
Sellers: For those who just want to make sure their products get the best possible rankings, scraping data from relevant categories will be enough. Understanding how to beat the competition in rankings will be the greatest driver of increased revenue.
Service providers: Those looking to sell improved rankings as a service will have to scrape as much data as possible. Due to the amount of data acquired, predictions are likely to be a lot more accurate when compared to scraping just a few categories. Product ranking strategies can then tailored to each customer in order to deliver the highest possible value. However, the costs of reverse engineering the algorithm are likely to be significantly higher.
Product IDs are an often underrated data source. By themselves they might not be very useful. However, scraping product IDs in concordance with keywords allows data analysts to keep track of nearly all products, categories, and the changes.
Another benefit of scraping product IDs is the ability to easily keep track of any changes that happen to listings. After mapping relevant data to IDs, any changes to descriptions, listings, and other details can be quickly discovered.
Additionally, by mapping keywords, IDs, and rankings and tracking all of them at once will reveal many insights into the search algorithm of any e-commerce platform. Essentially, e-commerce-SEO strategies can be revealed by simply following these data sources.
Sellers: Tracking product IDs is unlikely to be very useful to businesses not looking to sell e-commerce SEO services. A minor use case is keeping an easy index of all competitor products in order to monitor them for any newcomers or changes.
Service providers: Product ID scraping will be a necessity due to the sheer amount of data acquired daily. Keeping track of all old and newly listed products will be nearly impossible without creating an index of IDs for that specific e-commerce platform. Creating an index will have the added benefit of being able to deliver more accurate SEO recommendations for nearly any product.
Categories and Bestsellers
Every e-commerce platform separates its products into categories. Each category often has its bestsellers. Data on category performance, fluctuations, and prices can reveal business opportunities. Historical and real-time data on all products listed on one category reveal customer sentiment, common pain points, and opportunities to enter the market.
Bestsellers are another great option tied to categories. Scraping data on their keywords, customer reviews and sentiment, and all other related information can reveal the reasons for their performance. Data can then be used to be sold as a service or to adapt products, descriptions and their keywords to increase the chances of becoming a bestseller.
Creating a bestseller requires understanding two important facets: the product and the marketing side. Scraping product data and ratings will provide a better understanding on what makes a bestseller from the development side. Scraping category performance, rankings, and fluctuations will provide insights into the marketing side of creating a bestseller. Of course, price monitoring will provide relevant data for both sides.
Sellers: Two vectors of attack are the most important – tracking relevant category bestsellers and sold products. Comparing both the product development side will provide valuable insights into avenues for improvement.
Service providers: Most of these will be covered by scraping keywords, rankings, and product data. Of course, keeping track of best selling products or services is a necessity due to every business wanting to rank highly in every e-commerce platform. Being able to provide actionable advice on how to do exactly that will definitely put one service provider above another.
Data is all about modeling and predictions. With enough data scraped from e-commerce platforms, predictions can become increasingly accurate. Finding upcoming items can be either a source of data or a conclusion from currently held sets.
Some e-commerce platforms offer upcoming best sellers (i.e. those that have quickly risen in sales). Scraping data from these sources can provide insight into consumer habits and market trends. Clearly, knowing what items will become (or are becoming) popular can net great revenue gains.
Finding upcoming items can be done manually by scraping keywords, search volume, and changing prices. By scouring through the data, certain trends can be discovered, which might reveal changing consumer sentiment and habits. Trends scraping is a powerful way to predict possible avenues for business growth.
Sellers: If the e-commerce platform itself doesn’t provide data on upcoming items, finding a good third party service provider would be the best option. Simply tracking every category for market movers will likely run up the costs too much.
Service providers: If the e-commerce platform does provide data on upcoming items, scraping categories and the products themselves will reveal market changes and trends. Without such a data source, it can be created from a large amount of data and sold as a service to other companies.
Manufacturers and suppliers
Manufacturers and suppliers are a niche area for data acquisition. It requires more legwork to become functional and useful but putting in the effort can bring unprecedented business development opportunities. Luckily, there is a perfect starting point as most e-commerce platforms list manufacturers (or suppliers) in the product page.
In order to match the manufacturers with relevant data, a more advanced web crawler will have to be developed. Most e-commerce platforms will only share the name of a supplier or manufacturer. Other data will have to be acquired from the web or other sources.
Gaining access to databases where products, manufacturers, and suppliers are matched can have tremendous impact on business performance. From the ability to find new suppliers to creating better product supply lines, the benefits can be nearly endless.
Sellers: For most sellers, developing advanced web crawlers to match products, manufacturers, and suppliers will not be worthwhile. Management and development costs are likely to be high and will detract from the primary focus of the business.
Service providers: Building a powerful web crawler is a great step in the evolution of the business. Collecting public data from different platforms can be difficult as the crawler will need modifications to gather and parse the data. Yet, providing access to manufacturers and suppliers will be a tremendously valuable feature.
Review pages are one of the simplest to scrape, yet effective data sources. User comments and reviews will reveal the most about any product, its flaws and strengths, possible improvement opportunities, and many other important features. Customer sentiment can also reveal the best marketing angles, required additions to product descriptions, etc.
An additional web crawling layer for further product development could be added by scraping off-site customer reviews. Internet users have a penchant for leaving product reviews on a wide variety of websites. Regularly scouring the internet for any mentions of products will provide additional pointers for product development and marketing.
Sellers: Building a simple scraper for product review monitoring is an efficient way to keep track of important data. Once such a tool has been developed, monitoring relevant competitor products can deliver awareness on how to improve current and create future products.
Service providers: Scraping reviews is a vital component for any business that provides e-commerce data as a service. Helping businesses understand how to approach product development is a surefire way to deliver value to clients.
These are just a few of the possible data sources to be scraped. Truthfully, for data analysis, combinations of different sources are the most important. Many eye-opening business revelations can be revealed by combining and analyzing large sets of data. Want to start acquiring data from e-commerce platforms and search engines? Check out our data extraction tool Real-Time Crawler or book a call with our sales team to get started!