Our Forrester Groundswell Awards Submission

Here at StyleFeeder, we created a personal shopping engine built upon the idea of making online shopping easier and more personalized. Our personal shopping engine learns your style and delivers results that you’ll love in seconds. As you’ll see, this blog post serves as our official entry to the Forrester Groundswell Awards. Groundswell is a cool book that discusses harnessing the power of social technologies like blogs, social networks, and YouTube. We are all about tapping into the aggregate power of consumers at StyleFeeder, so obviously, we think these guys know what they’re talking about; Groundswell co-author Charlene Li has been very gracious with her time and advice as StyleFeeder has grown.

We wrote a bit about the idea of recommendations in a previous blog entry, but we’ll reiterate for convenience. If you’re a user of the StyleFeeder site, you’ve likely noticed a recommendations link at the top of every page. Click on it (if you are logged in) and you will see a list of products: your recommendations. If you’ve never rated anything on StyleFeeder, your recommendations still work, but they get better as we learn more about your style. At first, we’ll show you a list of the most highly rated products on StyleFeeder. Begin rating and updating your recommendations and something interesting things will happen: the products you see will start to become more relevant to your tastes. We use what is known as a collaborative filtering algorithm to determine your recommendations. By comparing how you rate products to how others rate them, we can find products you will like. The more products you rate, the better we understand your preferences and the better recommendations we can make…even search results will be personal to you.

You can easily add your personal StyleFeed to your blog, Facebook profile, MySpace page or social networking home so others can keep track of what you’re finding. Check out some short videos to see StyleFeeder in action.

All in all, let us know what you think. What you love or what you’d like to see in a personal shopping engine…? Feedback is much appreciated!

Name of entry: StyleFeeder’s Personal Shopping Engine

Category: Embracing

Description of entry:

StyleFeeder, the Web’s only personal shopping engine, is revolutionizing online shopping by enabling consumers to find what they want through the power of social data. The site takes advantage of the fact that existing search engines aren’t built to facilitate product searches; Google et al might work if you know exactly what you’re looking for, but what if you’re stuck at the category level (I need a new shirt or a new rug)? Delivering personalized results in seconds, StyleFeeder’s core functionality of personalized recommendations has been developed by Dr. Jason Rennie, a graduate of MIT. Since his Ph.D. work on recommendations, Jason has adapted recommendations technology to work on real-world data instead of toy data sets, and developed ways to crunch all of this data in practically real-time, which no other recommendation service is currently doing.

As shoppers rate items on the site, StyleFeeder learns about each person’s unique sense of style so we can help them find products they’ll like faster. But, why? Why are we doing this? How could a computer possibly understand “fashion” and “taste?” How can a web site know my taste as well as or better than my best friend? In a sense, it can’t. Our recommendation engine can’t “look” at an outfit and give you feedback. But, the engine has an advantage over your best friend: data, and lots of it. The engine can’t “see” the products that are added to the StyleFeeder site, but it has access to the opinions of thousands of users. Each of those users has expressed their taste by rating and bookmarking products. The recommendation engine can identify products you’ll like by comparing your ratings and StyleFeed to that of others. Whereas your best friend may only be able to browse a few sites a day, the StyleFeeder recommendation engine incorporates and filters thousands of new items daily, from mainstream retailers all the way to so-called “long tail” products created and marketed by individuals.

The site is also constantly on the lookout for new users whose style is compatible with yours: your StyleTwins. We’re not suggesting that you ditch your best friend, but the StyleFeeder recommendations engine gives you something that neither your best friend nor all the fashion magazines can provide: a product discovery service that’s personal to your tastes.

For fun, we also built a shopping application on Facebook that was designed to not only increase our userbase, but tap into people’s personal networks of friends on in a place where they’re already spending a lot of time – helping grow awareness and visibilty of StyleFeeder through word-of-mouth. We set out to create an app that was fun and viral but also useful – most of the functionality of our web site is accessible directly on Facebook,. Launched just last summer, StyleFeeder is, by far, the top shopping application on Facebook. We blew away the competion, believe me!

How does this entry accomplish business goals?

As with most Web 2.0 startups, our goals were simple — create a fun, useful personal shopping engine for people and capture as many users as possible. Oh yeah…and to revolutionize online shopping while we’re at it. Since StyleFeeder’s website revamp last year, the site’s growth has skyrocketed, aided by the shopping engine and its inherent viral appeal and ease-of-use. Check out some stats below:

  • 900,000+ Registered Users (up from 20,000 in August 2007)
  • 4.5MM Monthly Page Views (up from 500,000 in August 2007

  • ~1.2MM Monthly Unique Visitors
  • Largest Shopping App on Facebook (1.6MM+ Installs)

  • 14,000,000+ product links on StyleFeeder, added by users and data feeds from top retailers and brands
  • Extremely positive revenue growth and affiliate revenue growth; model calls for profitability by early 2009