How to Scrape Data from Any E-commerce Website?
Time is changing, and buying, selling, and trading have got a complete makeover, and it has become a requirement to play with new rules. The retail industry is gradually losing those who fear trading online as web data optimization has become the substance of future trading. Historical e-commerce data scraping might provide insight into product introductions, sellers’ behavior, and buyer responses. Our blog utilizes some data we have collected about leading e-commerce websites to discuss their growth curve.
Helpful Data Points for Making Predictions
There are many websites of different sizes, magnitudes, and content. Different e-commerce sites are generally on the weightier end of the spectrum because of the data amount they hold. Location, products, ratings, buying behavior, and millions of other dimensions, could be gathered. Let’s go through the most important ones:
1. Pricing Details
We can start by gathering and comparing the pricing of products for different websites. For instance, you might wish to know if a seller has uploaded a similar product like yours at a lower price. For small and large sellers, it allows them to know the market rates and adjust numbers.
2. Product Data
Thinking about what and how is getting sold online gives tremendous insights regarding what is in demand. For instance, the Walmart VS. Amazon competition might get boiled down to the total products they bring onto a virtual shelf and how quickly. Any player who increases competition will reduce and add products, and you can record all the research data
3. Expansion of Market Data
Historical data scraping from e-commerce will disclose information like partnerships, store information, or expansion plans through e-commerce data crawling websites and millions of new updates (however, this relies mainly on your infrastructure). It proves to be useful while positioning the competitors and planning before them.
4. Customer’s Feedbacks
Scraping e-commerce customer reviews & ratings might tell you where your product stands on the website. The real estate and travel industries are using customer evaluation scores effectively. Let’s assume you are an online brand partnered with the retailing platform. In case your partners have overpriced your products or not offering the right products, it might reflect the ratings and reviews your customer leaves for you. Many players depend on this data to know where their products and brand stand regarding customer satisfaction.
Case Studies
Since scraping e-commerce product data for so long, we’ve observed a few interesting patterns and comparisons among different e-commerce platforms. A few of these platforms have led the e-commerce market for years: Amazon, Amazon Now, Walmart, and Walmart Grocery. Let’s take a quick look at a few insights.
Product Development of Amazon.com
The graph here shows the product development of Amazon.com ever since 2015. Though the product counts have increased considerably between the first and second quarters of 2015, they dropped in the second half of 2016 and the initial part of 2017. Amazon launched the Prime Now service in mid-2017, which might have impacted the development graph of Amazon.com. By 2017, the number had increased and dropped slightly at the start of 2018.
Sales of Amazon Globally
This graph is the comparison of worldwide product counts of Amazon between 2017 as well as 2018. Countries like the USA, Germany and the UK are countries with maximum products respectively, and Japan, Italy, and Spain come next respectively. Amazon extended its product count to the maximum in the US, Mexico, China, Australia, and India last year, which has decreased slightly in the UK. All these numbers might be because of increased user sign-ups or a rise in the total number of sellers within this area.
Walmart Grocery VS Amazon Prime Now – The Compression War
The changes in Walmart Grocery’s product count between 2017 and 2018 indicate Walmart’s ongoing efforts to compete with Amazon, despite Amazon Prime’s launch in 2017. Amazon Prime Now started with below one million products in 2017 and hasn’t made much progress until one year late. Walmart grocery had started with 46 M products to be a clear winner of this segment.
Following Buyer Patterns – Top Seller Ranks, Reviews & Rating
Recently, we have tried to understand the Bestseller ranks and how they are associated with buying satisfaction and behavior. We found that Ratings and Reviews don’t significantly impact the Bestseller ranks. A few of the minimum-rated products and brands have carved their way to reach the Bestsellers list. Look at the following product graph rated among 1 and 2 to be available on the Best seller’s rankings.
Use Cases for Collected E-Commerce Data
In the e-commerce industry, the advantages are more direct. With increased social media and community platforms, optional data has become a ‘Must-Have’ tool for hedge funds, investment firms, and property firms.
1. Customer Evaluation and Pricing Optimization
Many retailers are already utilizing data science to price the products right and avoid offering unwanted discounts. For instance, Amazon is well-known for changing its prices over 2.5 million times daily, and they have done it using price optimization algorithms, which they have been using consistently. Many buyers aren’t as picky about discounts as selling low-quality or faulty products. While managing different selling partners, the brands need to know what would help buyers select their products. Certainly, price monitoring can help them to price the products towards utmost purchases. However, getting reviewed and rated well is better than becoming simply the cheapest.
2. Commercial Due Diligence
Commercial due diligence appointment organizes a market environment analysis, competitor’s position, and its effect on the company’s business plans.
Historical e-commerce data extraction can be the backbone of commercial due diligence and market research for e-commerce platforms and online retailers.
For example, Walmart has mainly been collecting data from buyers and sellers to deal with its competition, Amazon, for many years. At the 2017 year-end, Walmart had closed the breach on price variances, with Amazon averaging merely .3% higher than Walmart. Because of our predictions, it is obvious how one can easily predict the expansion, growth, buyer and seller traffic, and product mixing of brands.
At X-Byte Enterprise Crawling, we can collect pricing, products, and other vital data related to your site from different websites. Use the form below to contact X-Byte for more details regarding historical e-commerce data scraping.
