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Analytics: A New Model for Creating Great, Personalized Customer Experiences

While certainly exciting, buying a new house, can also serve as a revealing exercise in understanding data science.

A couple of weeks ago I went to my bank to investigate my financial options for buying a new house. To my surprise, my account manager gave me a stack of paperwork to fill out—and I soon realized that my bank was already in possession of 90 percent of the information I was being asked to provide. So why was I having to take the time to fill in information the bank already had, or could easily acquire?  And more importantly, why couldn’t my account manager quickly access information about my client status and my personal preferences, and immediately provide a tailored offering, decreasing the chance that I would look elsewhere for this service?

Figure 1. Centralized, Decentralized, and Distributed Networks. A distributed, virtualized approach to database management enables quick combination and analysis of large volumes of data—where and when it is needed.

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Source: Paul Baran, Rand Corporation.

I wrote in one of my recent blogs about the issues and solutions related to quickly combining data that comes in large volumes by focusing on data virtualization and cloud. This can enable seamless customer interactions and decrease client churn, be it in financial services or in the telecom sector. But what is required at an organizational level so that people, process, data, and things come together to enable a superior customer experience and create entirely new revenue possibilities?

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