SIS-led study examines the benefits that special deals offered on location-based social-media networks have for American business owners
A burger joint in Lawrenceville gives free orders of fries with every Foursquare check-in. A café on the South Side offers a discount on a dessert for every first-time visitor review submitted on Yelp.
Special deals, such as these, on social-media networks should provide a win-win situation for everyone involved. The consumer saves money by simply using the mobile app, while the business owner reaps the benefits of inexpensive means of advertisement. A simple scenario where everyone wins, right? “Not so fast,” says a recent study conducted by researchers at the University of Pittsburgh’s School of Information Sciences and the Stevens Institute of Technology.
According to the study, offering special deals on social media, while a useful tactic for increasing the visibility of an establishment, is not a reliable means for increasing patronage in isolation. Researchers point to a number of factors—such as venue type, area population density, the length of the special-deal offer, and the manner in which potential customers learn of offers—that play a significant role in making special deals a worthwhile promotional strategy for business owners.
“Our primary findings indicate that the positive impact of special deals through location-based social-media networks is not quite what the anecdotal success stories would lead one to believe,” said Konstantinos Pelechrinis, the study’s lead researcher and an assistant professor in Pitt’s School of Information Sciences. “We are not saying that special deals are not useful to business owners, quite the contrary. What we are saying is that business owners should be well versed on the best means for using social media, and they should have realistic expectations on how social media can help their individual ventures grow.”
The study is the first large-scale analysis of the benefits of special deals through location-based social-media networks. Titled Analyzing and Modeling Special Offer Campaigns in Location-based Social Networks, the analysis was originally presented at the ninth annual International Association for the Advancement of Artificial Intelligence Conference on Web and Social Media in Oxford, England.
For the study, Pelechrinis’ team used Foursquare’s public-venue application programming interface to collect data from more than 14 million venues over the course of seven months. The researchers analyzed variations in the number of daily check-ins before, during, and after special deals were offered. Their analysis showed that a large number of venues did enjoy an increase in check-ins during and after the special-deal period. An almost equal number of venues showed no such increase, suggesting that the benefits of special deals are contingent on outside features.
The study identified three categories of features that potentially contribute to the level of success of a special-deal promotion. Taken together, researchers say these features provide a road map for business owners to navigate their decision making with social-media networks. The categories are:
- Venue-based features include the type of business as well as the existing popularity of the establishment, which, for the purposes of the study, was determined by the cumulative number of Foursquare check-ins.
- Promotion-based features focused on the details of each special-deal offer, including the duration of the special deal, the number of special deals offered in the given time span, and the manner in which the consumer learned of the deal.
- Geographical-based features examined the surrounding attributes in a given area, such as population density and proximity to other popular venues.
“Each one of these factors contributes to the success of the promotion. More importantly though, we believe that our work can shed light on possible tweaks of the way these promotions are offered through the underlying platform,” said Pelechrinis. “Active notifications for nearby deals can increase awareness of the system’s user base and consequently their effectiveness. Foursquare, potentially realizing this, is actually moving towards this direction as far as we know.”
A faculty member in Pitt’s School of Information Sciences since 2010, Pelechrinis leads Pitt’s Network Data Science Lab. The lab conducts in-depth research on empirical and theoretical studies of networks and their applications in social, urban, technological, economic, and biological networks. Other authors of the study are Pitt doctoral candidate Ke Zhang and Theodoros Lappas, an assistant professor within the School of Business at the Stevens Institute of Technology in New Jersey.
Read 90.5 WESA's coverage.
Read Pittsburgh Post Gazette's coverage.