SiteZeus introduces brand new solution for retailers powered by geosocial and mobile location data
Accurately predicting future sales is the key to surviving and thriving in today’s highly competitive, rapidly-changing retail marketplace. But who exactly is your target customer and what drives his or her buying decisions? That is a common question that keeps many decision makers up at night. For the first time ever, SiteZeus has introduced a solution that provides tangible answers with greater insight into consumer behavior. SiteZeus’ new Customer Segmentation feature combines the power of social media conversations and mobile path-to-purchase data to more accurately predict consumer behavior and improve sales forecasting.
Traditional methods relied on demographics and psychographics, and more recently, POS data from credit cards and loyalty programs to understand customers. “All of these sources are missing a critical piece of the story. They make assumptions about how a group of individuals with similar characteristics, such as age, ethnicity and income, should behave. The reality is that individuals don’t always fit neatly into the same box,” said Spatial.ai CEO, Lyden Foust.
SiteZeus has partnered with leading data providers Spatial.ai and UberMedia to bring together insights gleaned from social media conversations and mobile geofencing. Spatial.ai gathers data from billions of social media conversations, on everything from fashion and food to music, art and sporting events. Layered on top of that is UberMedia’s mobile location data with customer pathing and draw areas. Gone are the days when brands had to rely on counting cars on main highways and intersections. UberMedia leverages location-enabled smart phones to gather data on actual travel patterns to see where customers are traveling up to two hours before and two hours after visiting a store. “Mobile location data is a much faster and more scalable way to understand real-world customer patterns and behaviors,” said UberMedia CEO, Gladys Kong.
SiteZeus’ A.I. brings both of these data sets together in one platform by identifying patterns of consumer behavior, which it groups into 70 unique Customer Segments. Brick and mortar brands can use this data to more accurately predict performance for prospect sites, as well as predict how changing certain variables would impact the performance of existing stores. The end result is a more meaningful predictive model that empowers brands to make faster decisions they can trust.
Subway is one of the early adopters to leverage this Customer Segmentation feature to help analyze their stores. “One store we looked at had a lot of students in the late-night leisure segment, which prompted us to think about adjusting hours. This data has effected up to +10% sales increases since changing store hours,” said Philip Mesi, Leasing Assistant at Subway.
“Better understanding the consumer through Customer Segmentation is a huge advantage for brands that are looking to be a first mover in a new market. It also gives brands the added security of knowing that their decision-making is backed by science that is quantifiable and explainable,” said SiteZeus CEO, Hannibal Baldwin.