Shopping, Fashion Timeline Apps Ride Facebook’s Open Graph

By David Cohen 

Facebook touted the use of its open graph by brands in the shopping in fashion categories in a post on its developer blog, highlighting how five brands created effective timeline applications and offering a best practices guide.

The five timeline apps spotlighted by the social network were:

  • Fab: The daily design app has seen membership grow to more than 4.5 million since launching with open graph in January, from 1.8 million previously, and 20 percent to 40 percent of its traffic is referred by Facebook on a daily basis.
  • Pose: The style app has experienced a tenfold increase in daily signups since launching with open graph, and its total poses viewed per month has skyrocketed to 40 million from fewer than 10 million prior to the launch.
  • Giantnerd: Traffic from Facebook has leaped by 214 percent since launching with open graph, while new users signing up via the social network are up 69 percent, and the order value of Facebook-connected users is 18 percent higher than the average order value.
  • Fashiolista: The European style app saw a 200 percent increase in traffic from Facebook after month one of using open graph, and that figure is currently nearing 300 percent. In addition, nearly one-third of new daily registrations are arriving via open graph.
  • Lyst: The London-based social shopping site said that since launching open graph, its user base has doubled, traffic has more than doubled, and visitors from Facebook spend 50 percent more on the site. In addition, more of its sales com via Facebook than from all other social networks combined.

Facebook also suggested three best practices for brands incorporating open graph timeline apps:

  • Use a call to action: Display a clear call to action to encourage people to add your app and start connecting with their friends. For example, Fab offered a limited-time, promotional credit to encourage people to opt in to the social shopping experience, and it currently shows a facepile of friends during sign-in to increase personalization. See more here.

  • Create multiple action types: Apps should experiment with actions related to each point of the buying lifecycle, from discovery through purchase. Fab enables people to “fave” products, Pose users can “pose” items, and Fashiolista users can “follow” other people, creating more opportunities to share that are meaningful for each community. Details can be found here.

  • Use object types to create categories: Developers should create objects for categories that enable people to compile interesting timeline aggregations. For example, Pose displays a person’s “most loved brands” and “top loved style items.” More can be found here.