There are a ton of shopping product search engines out there right now. It’s a crowded space and to distinguish themselves companies have been focusing on advanced features such as deep product feature search (Retrevo) or price trend tracking (Mpire) to stand out. There’s The Find, Mpire, Crowdstorm, Bountii, Retrevo, SmartShopper, Pricefight, Ugenie, and many more. Google had it’s own notable stumble in online product search as well.

Of the engines, Twenga is most like “The Find”. Search results are returned as a wall of product images and can be refined by price and features. It also has several advanced features include price tracking and user reviews. This allows the engine to run more complex searches properties such as a 10% price drop. It also focuses on Europe and comes translated in an impressive six different languages (French, German, Italian, Polish, Spanish, and English). The network reached 7 million visitors in November 2007 and indexed over 40 million offers from 25,000 merchants

With so much choice, there’s no excuse to not get the lowest price on your Christmas gifts.

Crunch Network: CrunchBoard because it’s time for you to find a new Job2.0

Before, the site was entirely dependent on user submitted products and written reviews. The new site adds a host of other review sources, such as expert reviews (Cnet, TrustedReview, Stuff …), buyer guides, video links, and q&a sessions. Users can bookmark their own relevant product review content on the site. It also brings in new price search engines such as Amazon, eBay, and Shopping.com.

CrowdStorm hopes not only pull content from the web, but also let you take your content with you. You can take your reviews and post them to other blogs, review sites, or online stores. The hope is that CrowdStorm will function as a hub for review content instead of a walled garden.

The more significant change is how it takes advantage of user generated content. CrowdStorm has a new algorithm that ranks user reviews in aggregate and for each user based on the quality of reviews, the similarity between users, and social network relationships. The idea being that similar users closely linked to you have more relevant and trustworthy reviews. The algorithm can also generate a relevant crowd of experts you can ask questions.

It’s very similar to what VibeAgent is doing with their travel review system. Analyzing the social network graph has become a sensible way to deal with the potential spammyness of user generated sites and I expect to see it incorporated into even more products.

Crunch Network: CrunchGear drool over the sexiest new gadgets and hardware.