Social commerce news is coming thick and fast as the holiday season gets underway.  In the first of several ‘extra’ posts today, Walmart and Etsy have launched Open Graph powered Gift Recommendation apps.

The world’s biggest retailer has launched Shopycat, a social commerce Facebook app, designed to

solve your gifting problems for your friends and family…[by] looking through your Facebook friends to find pieces of shared information that tie to real interests, then we show you the best gifts for those friends.

In other words, Shopycat is a social recommender app using open graph data to make gifting socks a thing of the past, with smart gift recommendations. Transactions aren’t handled in the app, but users are linked through to the checkout page on Walmart’s main e-commerce site.

The Shopycat app is, we think, the shape of things to come, but not here (just) yet.

The potential of Open Graph data to make shopping and shoppers smarter is enormous, but the technology, data and protocols are young and suboptimal. For example, whilst Shopycat app isn’t fully functional yet, it may be hampered by an (over?) enthusiastic concern for user privacy – not only does the app user have to opt in, but so do their friends.  Otherwise, you just get iTunes gift card recommendations. Whilst noble, this speed bump may hobble the app.

Meanwhile over at eBay-done-right – aka – Etsy, the P2P marketplace has installed a new gift recommender app, Gift Ideas, on its website that makes gift recommendations based on shared Open Graph data – essentially Facebook likes. As you’d expect from the global handmade marketplace, the design is slick and a joy to use.  Of course, the recommendations are only as good as the data, and the algorithm is not perfect; a hockey mom pendant was recommended for a very male hockey buddy.  We’ll buy it for him anyway.

The use of Open Graph data to improve ‘shopper intelligence’ by informing product discovery and purchase decisions is a concept we’re really excited about.  A case in point and that illustrate potential in B2B as well as B2C:

Whilst testing the apps, our activity was posted to the Facebook ticker, which prompted two separate conversations in Facebook’s instant messenger from friends, asking us what what we thought of the app. We shared our opinion, and learned about a neat Berlin startup, Recommender, that is developing a similar web app, LikedBy, for sharing stuff you ‘Like’ and connecting people with similar ‘Likes’; Match.com meets instagram.  We’re convinced that there is – or will be a smart outfit – working out how to use live Facebook ticker data to allow prospects to inform discovery and decisions by connecting with existing customers, and potentially rewarding the latter for referrals.  Think Branchout for shopping. Goosebumps.