Geo-location and Privacy: A Subtle Balance

This post is also featured on the recently launched "Typing On The Wall" Blog.....

Location Based Social Networking (LBSN) is prominent within the media zeitgeist at the moment, driven by the increasing growth of the category's current darling, Foursquare. As Foursquare recently added its 2,000,000th user and its 100,000,000th check-in, some can argue that the increasing growth rate (having added its 1,000,000th user only 3 months ago) and press coverage of the network are currently the most prominent stories.







CNN partnered with Foursquare during the World Cup to direct users to check-in at certain locations worldwide, unlocking badges and interacting with content


Given the company's growth rate and the utilization of the network by advertisers such as Domino's, the Huffington Post and CNN, this may be set to change. For media however, questions about Foursquare and other LBSNs go past the common questions of user growth and campaign concepts into "What insights can the network's data generate?"

Campaign metrics are key to creating attractiveness for advertisers, as greater data availability allows marketers to justify activity and modify comms efforts. Standing conversely against data availability however is user privacy.







User privacy concerns are inherent in social networking, but even more so when dealing with a user's location history. Sites such as PleaseRobMe.com popped up early on in the emergence of the current geo-location trend, highlighting a feed of users exposing their locations through auto posts onto Twitter. Concerns about user privacy have also been illustrated in recent studies, with a recent US/UK survey showing 55% of respondents worry about privacy relating to geo-location (Webroot).

Balancing privacy, key to growing the base of active users, and providing useful data & insights, key to growing advertiser investment, means that LBSNs must strike a careful balance as both network operators and data providers. Foursquare's solution to this issue has been two fold, providing basic data about venues & friends through the API (Application Programming Interface), while also providing business level analytics to venues claimed by the owners.

Given the open nature of the API, anyone can obtain a key and begin obtaining data and building applications, data is limited to what is available on the website. User specific data is limited to friends, while venues can provide the current amount of check-ins, who the mayor is and venue information. Data from the API is useful to monitor popular venues for a certain area or to create visualizations such as these, but it doesn't provide the specific level of data required to manage a large amount of CRM or loyalty plans.

Alternatively, the Foursquare analytics dashboard for a venue currently displays check-in data over time, different time periods and whether users clicked through to provided Facebook & Twitter links. In addition, it provides a stream of recent check-ins & top users, creating the ability to target individual users based on their behaviour for promotions. User check-ins not relevant to the specific venue are still protected.

Foursquare's approach to data visibility balances user privacy with metric creation in a way that provides venues an opportunity to customize promotions, while not risking user outrage by making data completely public to marketers. This strategy seems to be the way forward for LBSNs, as it encourages growth by unlocking the value of the network's data, without leveraging the privacy of the user base.