Optimizing Customer Value by Analyzing Application Navigation Behavior

I found a talk in which Vineet Singh of Intuit company discusses some research his company did to better understand how users are using apps and to ultimately optimize customer value.  I found this particularly interesting because it focuses on how applications are used (sequence of activities) and the huge amount of data that this consists of.   Because of the huge volume of data and large number of attributes the unique solution below was used.

Because considering all users is unrealistic, the cost-benefit optimization was used and provided below.  Additionally, Markov chain models were also used to find transition probabilities and users likely to cross sell products.

In the end they found which users are most valuable, which models best serve customers, and were able to identify emerging customer needs.



The video can be found in the link below:

http://bigdata.theiegroup.com/article/4ec18c1c3723a84f31000f05/Optimizing-Customer-Value