Social and geo-location in-store media wall for Niketown stores

Project

The brief was to devise an idea for a media wall for the interior of flagship Nike stores that aggregates a live stream of local (Nike related) data that engages the user and promotes the brand. It needed to focus on the local community, rather than the commercial side of selling products. It's primary use would be as an in-store media wall, but could be adapted for use online or as an app, automatically streaming local information based on the users' location.

The idea

My idea was to create a visually engaging stream that aggregates relevant (local) geo-tagged tweets, mentioning Nike products, teams or athletes relevant to that area (e.g. New York Knicks in New York). It also displays live check-ins to that Nike store (via foursquare and Gowalla), engaging the user even further. More info below…

Involvement

Ideas
Wireframes

Client

Nike

Date

Oct 2010

Agency

JESS3

Tweets & trending topics

The circles to the left are all trending topics on Twitter (based on geo-tagged tweets), in this case New York. These would be animated, with enough motion, so not to be annoying. The larger the circle, the more popular that topic is!

Periodically a different trending topic is selected at random, or in-order of popularity at that time… The topic name is displayed to the right of the screen, along with keywords commonly being used in tweets associated with the topic, along with a cycle of 2-10(+) tweets.

When a topic is being streamed (active topic), the related circle/photo/image is enlarged and brought to the foreground. A circle appears around the image, which acts as a countdown for how much longer this topic will be streamed for. Moving clockwise around the image.

Check-ins

As an engaging and fun incentive… When someone checks-in at the Nike store, their foursquare or Gowalla account profile picture appears (temporarily) on the screen along with a personal message to them, in this case "HELLO JAY".

Local data

Other local and demographic data can also be included (to the bottom-right), like the breakdown of male to female people tweeting, or the local time and weather conditions.