In the FICO Insight whitepaper, When Is Big Data the Way to Customer Centricity? Next-generation analytic learning finds critical insights in an ocean of false clues, Dr. Andrew Jennings, FICO Chief Analytics Officer and Head of FICO Labs, shares that “the real value of Big Data for business is the opportunity to learn about our customers at such depth and speed that we can truly put them at center stage.”
Full disclosure – I work at FICO and am a big fan of what we do with customer analytics but this is not an advertisement.
Dr. Jennings shares the four analytic imperatives for next-generation learning:
- Design and automate smart experiments that enable causal prediction
- Analyze and learn from customer behavior on the fly
- Get the machine learning /human expertise balance right
- Turn every customer touch into an opportunity for more service and learning
While the easiest relationships to find customer insights are correlative – when A occurs, B also occurs – the most valuable insights, according to Dr. Jennings, are causal – A affects B. By finding and testing causal relationships, we can better understand our customer to optimize our product, services and brand and predict how individual customers are likely to respond to a special offer or treatment.
To operate in this customer-centric manner, we need to respond to our customers’ actions as they take place. Data analysis and data-driven “decisioning” occurs in real-time or near real-time, based on the stream of data coming from mobile phones, online activity, point-of-sales (POS) devices, and more.
Machine learning speeds up our ability to crunch through Big Data. But to make these insights useful, it requires human involvement. Analytic experts are essential to identify biases and “holes” in the data and bridge the gaps of “production data” which is constantly changing in real-time or near real-time.
Promising analytics-driven customer decision strategies must be immediately deployable into your operations with your customers through all your channels. Streaming analytics and batch analytic results, deployed as integral part of these strategies, work together. Entering into each interaction, organizations know who the customer is and has already made a decision about a range of appropriate treatments. During the interaction, organizations make additional intelligent decisions on the fly based on customer reactions and new data – and this is the opportunity to transform customer experience.