Foursquare: Using Crowdsourcing to Fuel a Turnaround
Foursquare used crowdsourcing to pivot in the midst of stalled growth, quietly becoming the world’s leader in location-based data.
Foursquare, launched in 2009, was once (and largely still) known for its original functionality as a check-in app that integrated with Facebook. Users would “check-in” to a brick and mortar retail store or restaurant, which would post to the user’s Facebook account and alert the user’s friends of their activity. In turn, users would often receive some incentive from the retailer such as an in-store discount. After a few years of rapid growth, Foursquare abruptly hit a plateau and growth stalled. In 2014, the company spun out its original social-oriented check-in business into a new improved app called Swarm[1]. In order to stoke the embers of its waning growth engine, the company decided to pivot to location-based recommendations powered by crowdsourcing.
Using Crowdsourcing to Pivot
Foursquare chose to leverage its existing assets capabilities garnered while building out the check-in business to move into user-generated reviews and local recommendations. This strategic pivot was particularly an elegant one, because the existing data the business had generated created a distinct advantage relative to incumbents in the space such as Yelp. For example, Foursquare knew how many times existing users had “checked-in” to certain locations and could therefore identify which users were best qualified to generate reviews. Further, users could view how many times reviewers had visited restaurant locations, which allowed the most relevant and accurate reviews to naturally emerge among the crowd based on user feedback. Foursquare also chose to require less information from users when entering reviews (i.e. giving them the ability simply to rate and / or enter a short form review), which differs starkly from Yelp, where reviews are often deemed more credible for being long as opposed to being written by users that are most qualified to review.
Foursquare’s new crowdsourced business model has opened up many new avenues for data collection which, as evidenced by its ability to raise a large new round of funding, is likely to open up new ways of monetizing. Because of its newfound strength in location-based recommendations, millions of users are now willing to contribute reviews to the platform as well as opt-in to passive location tracking, which has allowed the company to track user traffic. After this pivot, Foursquare was able to raise $45mm in January 2016 to pursue enterprise monetization strategies with its wealth of location-based data[2].
Value Creation, Value Capture, and Operating Model
Foursquare’s current value proposition for consumers is lightweight, location-based, reviews and recommendations for brick and mortar retailers (most frequently restaurants, bars, and other service-based businesses). Foursquare also has slanted its recommendations slightly more internationally than Yelp has, making it a competitor for TripAdvisor in the travel-recommendations space (e.g., where should I go for lunch in Paris?). Combining the perceived superior accuracy of reviews as well as its international orientation, Foursquare has proven to be compelling for users. As of September 2016, the company has logged over 10 billion user check-ins[3]. This wealth of location-based and consumer foot traffic data has proven to be very useful for enterprise customers as well. The company has struck large scale deals with tech giants such as Uber (powering location suggestions when entering destinations by name) and Snapchat (powering location-based advertising and filters)[4][5] . The company has just recently released a new product that it calls the “Google Analytics for the physical world,” enabling retailers to track their foot traffic data in the most granular and accurate way possible today. The company captures value to date by charging retailers for advertising space in the search UI, charging retailers for location-based advertising push notifications, licensing its technology and data to large tech firms, and now through its analytics tool. This value capture model reinforces its value creation model quite nicely: the more accurate and relevant the crowdsources review and check-in data is, the more effective the sponsored ads and push notifications will be. Foursquare’s new found, crowdsourced model has set it up nicely to become the world’s leader in location-based user data.
Sources:
[1] http://www.businessinsider.com/foursquare-launches-swarm-2014-5
[2] https://techcrunch.com/2016/01/14/foursquare-gets-45m-and-a-new-ceo-to-build-out-enterprise-business/
[3] http://venturebeat.com/2016/09/13/foursquare-users-have-checked-in-over-10-billion-times/
[4] https://techcrunch.com/2016/05/25/uber-taps-foursquares-places-data-so-you-never-have-to-type-an-address-again/
[5] http://www.adweek.com/digital/snapchat-signs-data-deal-foursquare-better-targeted-geofilters-174627/