Perry Walter

Data extraction at scale from multiple websites is technically complex and challenging to solve ( especially if you are building things from scratch). Self-service tools and Data as a service using self-service tools tend to fail when the project turns complex.

It is not always feasible for companies to set up an in-house team to do data extraction at scale, especially when they are having tight deadlines. There are a few things people get confused about when it comes to web data scraping. Many of them find it difficult to understand the pricing logic of a web scraping project.

A few years back, a typical online buyer looking to buy apparel or an electronic gadget would scour the web to compare prices from various e-commerce sites and look for the best deals available. Prices of the same commodity would vary vastly over different sites which in turn prompted sites to monitor price changes in real-time using analysts. In today’s hyper-competitive e-commerce scenario, retail players grab every opportunity to attract potential customers. Price comparison websites are one of the opportunities e-retailers leverage to attract customers.

Today, data has become an indispensable tool in a business’s profitable functioning. Companies resort to data insights to understand theirs and their competitor’s standing in the market. In an age where organizations strive to find the right product to sell in a hyper-competitive market, data not only becomes quintessential to monitor your growth but also needs to be used to understand how your competitor is attracting a loyal customer base and mounting sales.