Many brands are using Foursquare to generate interest in their brands by giving some freebies to the users who check-in the most into their store. But in terms of actual business, check-ins are not enough. Showing up does not equate to profit. A customer might be checking in without purchasing anything, or their purchases might be small, deeply discounted, or one-time due to competitor loyalty. Additionally, user points on most location-based networks are tied to a specific location. For instance, if a customer frequents multiple Starbucks locations, she could still never become a Foursquare Mayor — even though she may be a loyal and profitable customer. Brands have data about spending trends of users in their stores but lack any external knowledge of spending trends in other stores and brands.
This is where Location based services can prove useful. If location-based services began collecting the size and frequency of purchases across all locations and mining the data of check-ins (including likes and dislikes), they could begin to build the next generation of loyalty rewards programs comprised of customer, spending, location, and sentiment.
Take this example: if every day a consumer purchases a latte from Starbucks and then walks across the street to Dunkin’ Donuts to pick up a turkey sausage flatbread, both companies could benefit from that information. If many customers display similar habits, Starbucks could add a similar breakfast sandwich to their menu or even discontinue their current breakfast fare at that location.That level of data provides a more holistic view of consumer behavior, and could ultimately help brands become more relevant and timely.
Running promotions to entice customers to what they even otherwise would buy, is a simple waste of money. Using location based services to understand consumer behavior and further enhance sales is the need of the hour for businesses.