A multinational consumer electronics organisation needed to find a solution which would enhance their understanding of their performance, and their competitors performance. We built a tailored web scraping solution, leveraging Microsoft Azure, Data Factory and SQL, to deliver broader, and more granular, insights into online performance.
A multinational consumer electronics company were looking for a solution which would enhance their understanding of the performance of their own, and their competitor’s products, across a number of eCommerce retailer sites across the world. They wanted a solution which would provide refreshed data on a regular cadence to ensure they had up-to-date information. They needed an all-encompassing solution which provided insights around customer reviews, ratings, out of stock percentage price, on-site search ranking and share of voice.
We developed a solution which involved creating multiple Python scripts that could extract the relevant information from numerous eCommerce sites in parallel. This scraped data, alongside additional third-party data, was then inputted directly into Excel, and stored in the cloud using Microsoft Azure. By leveraging Azure Data Factory, the team then created pipelines which transferred the data from Azure to SQL, enabling us to clean and transform the data into a format which was ‘dashboard-ready’.
Consequently, the client was able to gain access to a wider breadth of data that was much more granular than pre-existing data sets. This solution also allowed them to benefit from enhanced automation capabilities, providing them with timely insights without the risk of human error. We were able to provide them with a forward-looking solution which can be expanded across many more retailer sites, products, KPIs and languages, and ultimately will aid them with identifying opportunities for growth.
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