The promise of Big Data looms large as banking institutions worldwide launch major customer centricity initiatives. Today we have the means to capture and analyze much bigger quantities of data than ever before, and to make meaningful connections between different types of it. We can analyze data in-stream for real-time decisions. We can distribute analytic tasks in a massively parallel manner across many processor nodes, then algorithmically assemble their outputs into a single result.
But is any of that helpful for achieving customer centricity?
It’s most helpful when we can systematically extract the most valuable analytic insights—causal relationships—from Big Data. These insights enable us to understand individual customer behavior and sensitivities, anticipate needs, and predict likely responses to offers and treatments. In some situations, we must find and act on such insights as data is streaming in. In others, we can use out-of-stream methods to dive deeply for them.
Big Data computing infrastructures are making it practical to employ automated machine learning algorithms for this purpose—but human expert oversight is essential to ensure results make business sense and are useful in operations. And, ultimately, whether any of these insights impact customer centricity depends on how quickly we can pump them into operations so that they inform every decision and every customer interaction.
These essentials for turning Big Data into an enabler for customer centricity are fundamental to what I call “next-generation analytic learning.” At its core, next-generation learning elevates test-and-learn methods to a new level of efficacy. It’s a systematic, highly efficient way of continuously advancing what we know about our customers and improving how we use those insights to interact with them.Over the next few weeks, I’ll be discussing the imperatives of next-generation analytic learning here, as well as on the FICO Labs Blog. So stay tuned…or check out my recent Insights white paper on the topic: "When Is Big Data the Way to Customer Centricity?" (registration required). These imperatives can be practiced by every company, irrespective of size or analytic sophistication. In fact, my paper talks about how to get the most value from what you have right now, even if your data has “holes” and other imperfections, and your customer treatment strategies have been inconsistently applied.