Finally, the data is aggregated and the company forms a picture of each retail outlet based on the buying habits of its credit-card-holding customers. Bundle can see, for example, whether a restaurant is a neighborhood favorite-people from a particular ZIP code frequent it-or if it attracts visitors from out of town. And by combining that information with external demographic data, it can report on the characteristics of patrons, such as their average age, their affluence, and even how often they eat out.
Data that has been cleansed and tagged can easily be reused, so Kim and his team are searching for more ways to do so. One idea: combining transaction information with the personal financial data users track with Bundle's My Money tool, to provide recommendations and money-saving tips based on users' behavior and preferences.
Read more about data management in CIO's Data Management Drilldown.