Square, a company best known for their portable payment processing solutions, is changing the way retailers are using their customer data. As one of several mobile payment providers on the market, Square has distinguished itself from competitors by offering powerful analytics that can help business owners understand customer behavior in order to make strategic decisions. The company’s success and rapid growth in the past few years has led to an accumulation of massive amounts of transactional data, which Square is now leveraging to apply analytics across several scenarios.
Square first focused their efforts on the services industry, examining how well customers across the United States tipped their waiters, waitresses, cab drivers, baristas, and other customer service professionals. Square learned that Alaska had the highest average tip amount while Delaware had the lowest, and that fewer customers tip when compared to conventional wisdom. In a similar example, Square used data from salon transactions to determine the price range of a haircut across the country in order to provide retailers with an assessment of the willingness of customers to spend money when considering the cost of living in a particular region and customer satisfaction.
Thinking more broadly, Square analyzed the effect of severe winter weather on customer behavior in the local economies of several cities. By comparing transactional data from a previous storm-less winter season to current information, they were able to track hour-by-hour transactional trends. This study provides retailers and service providers with insight into the way they can utilize advanced analytics to make informed decisions that increase operational efficiencies and save money, such as adjusting staff allocation and/or improving the development of a marketing campaign.
One of the most compelling use cases for Square’s transactional retail analytics can be found in the world of major league sports. Facility operators, merchandisers, concession companies, and team owners all have an interest in the successful financial operation of a stadium or arena. In partnership with WIRED, Square analyzed the connection between walkability and retail sales on opening day at baseball stadiums around the United States, and discovered that local economies benefit the most when sporting areas are pedestrian friendly. With the ability to track details to a granular level (such as type of merchant, time of transaction, item sold, proximity to stadium), Square’s capabilities continue to inform both short- and long-term strategic decisions in the retail and service sectors.
Praescient Analytics is a Veteran-Owned Small Business that delivers training, data integration, platform customization, and embedded analytical services in partnership with leading technology providers. Praescient’s teams of analysts and engineers provide comprehensive solutions to federal and commercial clients engaged in critical defense, law enforcement, intelligence, cyber security, financial, investigative, and legal analytics missions.
Charlotte Stasio is Praescient’s Communications Specialist.