By Bob Johns
Mobility is driving changes in retail though purchases, but one of the places it really is beginning to benefit retailers is through data. Kevin Outcalt, head of consumer insight at SAP, says “This is all about understanding consumer population behavior. By understanding this behavior, retailers can adjust their sales strategies and marketing/advertising plans.”
Outcalt, who came to SAP through the acquisition of Sybase, works in the Mobile Services division and focuses on SAP 365, which is focused on mobile data. “We manage the interconnect for messages going between carriers for SMS, which gives us the relationships with the large agencies and carriers to access the user data,” Outcalt says. Specifically, what they are pulling is marketing intelligence. All of the data is based on mobile user activity. “We can collect data on location, time at the location, what they are accessing on the web at that time through web clickstream, the device type, and some demographic data. However, all of the data is anonymous. We do not collect any personal information.”
The company collects massive amounts of mobile user data. In a recent proof-of-concept trial, they collected over 51 billion rows of data. The web portal interface was able to produce sub-second response times to queries and produce fairly sophisticated reports. “We produced heat maps within specific parts of London and what users are searching for at certain times in certain areas,” says Outcalt. “These systems become absolutely huge, since we need to keep historical data for long periods of time to be able to study trends.One of the UK operators said a year ago they dealt with a terabyte of data per month, and now they are dealing with a terabyte a day. It is our job to store that data and provide it to the retailers in a usable format.” This is where the reporting comes into play.
Retailers access a web portal which includes query tools and analytics to create custom reports for the areas they are targeting. Marketers can look at a shopping district to see user demographics by time of day, interest level from clickstream data, and how long they spend there. This allows them to adjust mobile marketing plans to make them relevant to who is in the shopping district at lunchtime vs. who is there in the evening. “It’s all about customization and relevancy,” Outcalt says. “Why push out a local message at noon geared to teenagers, when you can see the people in the shopping center are not shopping for teenager merchandise, but they are looking a lot at housewares.” With information like this, marketers can change their message to relate to the home, decorating, or updating your kitchenware.
This is where the SAP 365 solution uses predictive analytics and subscriber demographics to determine who is in the shopping center. For example, females, 18-30, interested in luxury goods — gender/age/interest indicators for any area. Add clustering to the mix like, time, location, mobility, and browsing behaviors that result in users visiting a real or virtual location and your marketing becomes even more targeted and relevant.
As the amount and types of user data grows, solutions will be able to provide retailers with actionable data. Do you change up product mix at a location? Do you alter digital signage to appeal to the demographic that is present at certain times of day? What types of websites are consumers going to while in the store? Can that be leveraged into in-store sales? The possibilities are endless.