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AutoData 2.0: Answering Hard Questions About Your Customers Using Your Own Data and Comparables

Project description:

Last year we studied how Autodata (i.e., automatically generated data) coupled with smart analytics and clever visualizations, might be used to answer difficult enterprise questions. In a pilot study, we showed how transactional data could be used to highlight differences between satisfied and unsatisfied customers, and what to do about it. In a continuation of that project, we plan to 1) collect data from 3-4 banks in different global regions and 2) automate the collection and hypothesis testing and 3) make real time decisions on how to improve profit per customer.

Research questions include:
  • Can we create a visualization that four banks can use to compare customer satisfaction, digital engagement, and profit per customer data to help answer challenging questions?
  • Can we create a model of transactional data that keeps a running tab of customer satisfaction and actions to improve it?
  • What drives customer profitability?
Project team:

Peter Weill and Stephanie Woerner