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Another Standout Submission For The Co.Labs & Target Retail Accelerator

With one day left before the contest closes, entrants are preparing to submit their pull requests tonight before midnight. Here we spotlight another early entry and talk about what could make them winners.

Another Standout Submission For The Co.Labs & Target Retail Accelerator

Since this is an app-building contest, we’re for anyone to see. (Don’t know about the contest? Learn why you should build Target’s next-gen retail app here.) While most entrants have chosen to keep their submissions secret until the last minute–tomorrow, April 30, 2013 at midnight–some enterprising contestants have chosen to show off their ideas early. To reward them for their bravery, we’re talking about great submissions on our site, in the hopes that it will help last-minute entrants hone their pitch. Here’s today’s entry:

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A/B by David Lu

This app allows shoppers to get second opinions from friends while comparison shopping. But what makes this app impressive is the clear thought given to the data play. Contestant David Lu lays out a use-case for the app’s main task here:

Tracy is trying on dresses in a Target store. She’s here alone, while on a lunch break from her day job. She wants the opinion of friends, and has narrowed her choices down to two items: a Missoni for Target Sleeveless Sweater Dress and a Jason Wu for Target Poplin Dress in Navy. She adds a poll with A/B, substituting a couple self portraits taken in the dressing room mirror for the regular product images from target.com. She makes the poll private, so only her friends can see it. As she changes into her work clothes, she sees her phone buzzing with notifications. Four of five friends so far preferred the Missoni. Done and Done. She purchases it a few minutes later.

Lu envisions this as an open data platform: “Unlike many ‘Like economies,’ he says, “this is a completely open data platform. Anyone in the system can look at the data of anyone else in the system.” He makes a point of highlighting how the utility of the data isn’t diminished by its openness–even for Target:

  • Poll Authors – get a second opinion.
  • Poll Voters – get to express their opinion. They may feel a sense of altruism in helping others have a broader point of view in their purchasing decisions.
  • Target – gets demand data on the products in Target’s inventory (which products are most wanted, which products are preferred regionally).
  • Target – gets improved related product clustering (“customers frequently compared this product to that product”).
  • Target – gets to identify customers of influence, based on number of followers and votes.
  • Target – gets to identify expert users, based on commenting activity.

Lu imagines his app living on iOS, and included the following screenshot mockups of a user’s profile, navigation and the “feed” of incoming A/B comparisons, respectively:



One interesting feature here is the ability to see your “sameness” quotient with another user; this is a great preamble to social features, which might highlight how you and your friends share (or don’t share) the same taste across certain parts of Target’s product matrix.



Lu is opting for the side-drawer navigation pioneered by Facebook for iOS, among other third-party developers. Prebuilt, open source frameworks for this kind of navigation are plentiful, making it easy for you to integrate a familiar navigation paradigm without building anything custom (although, we don’t know if this entrant rolled his own).



Another notable UI choice Lu has made: The floating main task button. The earliest that most of us saw this style of control was in the second version of Path, which allows users to create multi-media posts from a similarly placed button floating over the user’s feed. Foursquare has also recently adopted this free-floating control style for its check-in button in iOS.

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About the author

I've written about innovation, design, and technology for Fast Company since 2007. I was the co-founding editor of FastCoLabs

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