Scraping Product Prices and Reviews

Case Study

A furniture retailer improves sales by 27% with price scraping

PromptCloud helps a leading furniture retailer improve sales by 27% in 12 months. Read the full story to know how.

Client’s Background

The client is a furniture manufacturer with 13 stores across Scotland, United Kingdom. Offering ready-to-assemble modular furniture via eCommerce retailers, the client foresees to be the leading supplier across Aberdeen, Dundee, Edinburgh, Glasgow, and Perth. The strength of the brand is the vast range of products available in the catalog (currently more than 130 products).

Business Challenge

When the funiture manufacturer came to PromptCloud, they were trying to reverse a sharp decline in sales, which in turn, had led to falling revenue.

With consumers having numerous choices when it comes to online shopping, the competition is high in all major sectors, and the furniture industry is no exception. Perfecting optimal prices, attracting the right audience, and hitting the perfect spot on the demand-supply curve was becoming challenging for the client.

A quick audit of the case indicated that the decline in demand for their funitures across eCommerce platforms was due to lack of an optimal pricing strategy.

By partnering with PromptCloud, they wanted to ensure they remained at the forefront of innovation by finding new ways to differentiate their product based on customer's needs and creating a optimal pricing strategy based on competitor's prices.

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Proposed Solution: Scraping Product Prices and Reviews

Proposed Solution

We started by addressing the most pressing issue: optimizing the product prices based on the market pricing trends. The team setup crawlers on the client's competitor sites and extracted the pricing data using SKU IDs and product names.

Once the product pages were identified, extracting pricing-related data and reviews were concise, although some websites had a few blocking techniques. As soon as a particular day’s crawl is completed, the data gets merged into one file per site and is pushed to the client’s FTP folder from where they import the data into their internal systems which automatically tracks the price discrepancies across the multiple vendors.

Implementation Time

As soon as the crawl specifications were finalized, we setup the crawlers and started delivering the data in no time. For 20 websites, which is equal to 40 site setups (20 for products and 20 for reviews), we had the entire setup, up and running in about 7 working days.

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Results

With our site crawling service, the client made sure that there is no manual layer involved in the data acquisition process, thereby saving up on a lot of man hours, server costs, and human resource costs of having a dedicated team.

After a year of collaboration, the client has seen some impressive results:

The product description extracted from competitor sites gave the client a clear picture of their competitor's USPs. With similar products being available in the market, price increases were condoned through the addition of characteristics/features within the product.
Based on competing companies’ information on particular products, prices were either marked up (increased) or marked down (decreased).
The client was able to make better use of peak-of-season sales by closely monitoring competitors' discounts and deals depending on the trend.
The client was able to make better use of peak-of-season sales by closely monitoring competitors' discounts and deals depending on the trend.