taps the power of the Web with crowdsourced product recommendations taps the power of the Web with crowdsourced product recommendations

Web shopping site has injected a large dose of ‘social’ into its product recommendations feature after it launched ‘Decide Score’, a new ranking system that recommends products by aggregating ratings and reviews from across the Web.

We last wrote about the company when it launched a nifty iPhone app that allows users to monitor prices and buy when the time is right, and now it is turning to the Web’s own expertise to help customers make a buying decision.

Ever been to a tech festival?

TNW Conference won best European Event 2016 for our festival vibe. See what's in store for 2017.

The new system is powered by the crowds, and the company explains that it takes information from more than 7,000 product “experts” and some 2 million user-generated reviews to give a far more comprehensive recommendation about a product than you’ll find on services like Amazon.

Further to that point, each product’s Decide Score is calculated out of 100, which puts them into one of four brackets:

  • We Love It: 9 percent of products are the highest rated with a “We Love It” recommendation and score of 90 and above
  • We Like It: 31 percent of products have a “We Like It”
  • You Can Do Better: 48 percent of products fit into a “You Can Do Better” recommendation
  • Don’t Buy It: 12 percent of products have a rating that triggers a “Don’t Buy It” recommendation

Commenting on the gradual introduction of the new system, Mike Fridgen, CEO of, said:

Decide leverages big data to makes complex shopping decisions easy for consumers. First we introduced when to buy predictions and today we take an important step towards becoming the next-generation consumer advocate by releasing data-driven what to buy recommendations.

The system is out in beta — ranking 22,000 different consumer electronics items — and the company plans to extend it across other categories and products in due course. says it has saved its customers $75 Million since June 2011 thanks to its “Buy” or “Wait” price recommendations.

Image via Shutterstock / Sevenke

Read next: Data-driven publishing: How Hiptype hopes to be the Google Analytics for eBooks

Here's some more distraction