With FavRav, Get Recommendations from Friends

FavRav, which launched on Monday, lets consumers find quality, trusted referrals from the people they already know. The Facebook-enabled site displays recommendations for nearby service-oriented small businesses, but only displays results from people in that user's existing network. A user's recommendation also display in their Facebook wall, providing new users with incentive to discover the site and create recommendations of their own.The result, hopes FavRav, will be a recommendations engine with more meaningful results to consumers and will convert to new customers for businesses.

"If you're looking for a recommendation on a great 'date night' restaurant or local bar, you can use the other myriad of referral/recommendation sites like Yelp or Citysearch," said Bill Manos, co-founder, FavRav.  "We're really the place people come when you need a trusted referral from friends on important decisions like your first child's pediatrician, a realtor for your next home purchase or an insurance agent to help you protect your family."

FavRav also provides small business accounts, targeting small business owners who rely primarily on referrals, and who want to promote themselves in a more engaging way via social media. FavRav enables business accounts to provide discounts and special offers underneath customer testimonials, both on FavRav and on Facebook They also provide real-time analytics on their referrals. "With FavRav, companies setup quickly, engage customers to refer them and end up with more serious inquiries as a result. It's hassle-free and lets them focus on their business," says Manos.

For more information on FavRav, check out the demo video below:

StyleFeeder: Personal Shopping Engine

StyleFeeder offers personalized shopping recommendations to over 1.5 million users each month. The site was created for fashion-conscious shoppers interested in hearing about new products. StyleFeeder connects users to emerging trends, not only in the clothing and accessories categories, but also electronics, books, music, even sports and pets. According to InStyle Magazine, “If you just bought the perfect party dress and now need a clutch to match, go to StyleFeeder.com where you can get advice from like-minded buyers.”

The registration process for StyleFeeder is similar to other social shopping sites who offer personalized recommendations. Users sign up, then rate a variety of products on a 5 star scale. Afterwards, users receive a "Style Feed" of suggested items. The Style Feed can be turned into a widget, added to users' Facebook profiles, or simply shared with friends. My StyleFeed included items as disparate as pink, fake fur-lined head phones, Mediterranean patterned bath tiles, and gray sandals with ruffles, all of which I would consider buying. In addition to the Style Feed, users are also matched with "Style Twins" to enhance the product search and discovery process.



StyleFeeder has been lauded for their unique collaborative filtering technology. "The software creates a giant matrix or spreadsheet of items and their relationships. Then it looks for patterns among those who rate items similarly. The basic idea is that if two people like product X and one of them also likes product Y, then they probably both like product Y,” says Women's Wear Daily.

With over 5 million monthly pageviews, a weekly newsletter, and a popular Facebook application, StyeFeeder has successfully carved out a niche in the crowded social shopping space.

Retailers Add Social Media Capabilities to Shopping Sites

A recent eMarketer report revealed the site features and functions retailers planned to add to their sites. A variety of social media functions made the list, including plans to build communities, add customer ratings and reviews, and even blogs. The most popular social media function on the retailers' list, however, was personalized product recommendations.


Peer recommendations are common on social shopping sites, such as Polyvore and StyleHop. Says senior eMarketer analyst Jeffrey Grau:"There are situations where peer recommendations provide more meaningful results. Take for example a woman who has just moved to Manhattan and needs help choosing and purchasing appropriate business attire. An automated recommendation system would be challenged to find suitable suggestions based on her historical shopping data. A better source of apparel advice would be other professionals working in New York.”

And the benefits of peer recommendations are not limited to customers. “Retailers like personalized product recommendations because they create cross-sell and upsell opportunities,” says Mr. Grau. “They also cite long-term benefits such as a higher degree of customer engagement and loyalty.”