The telecom and banking industries were the pioneers in taking full advantage of big data to get a complete view of a customer. The Telecom industry, for instance, was the first to segment customers based on their life time value. This can isolate fringe customers who might be high individual revenue earners for the company, but who also came with high maintenance and servicing costs. Segmenting customers by life-time value rationalizes the revenues being earned by a customer today and looks at the long term attractiveness of acquiring or retaining a particular segment of customers. To enable such segmentation, a 360 degree view of the customer is not enough anymore. That is, businesses need to not only look at their internal data on a customer when they contact them through their own channels, but also look outside of their owned channels to sources like social media, reviews and experiences etc. to understand their real motivations to use the service.
Utilities, who were mostly operating in a regulated market with significant monopolistic advantages, never really felt the need to operate from an ‘outside-in’ view of the customer. Their focus remained on technology and operations with an ‘inside-out’ view of their customers. With deregulation coming in various markets, utility customers are now spoilt for choice. Further, today’s socially connected consumer tends to have a much deeper relationship with businesses and the interactions between businesses and consumers are not purely transactional anymore. It is extremely essential for a utility business to understand who their most valuable customers are. Aggregating data from all internal and external sources around a customer, combined with an almost continuous data stream coming from increasingly ubiquitous smart meters, advanced data modelling techniques can clearly segment the most valuable customers who need to be retained and also help design specific products targeted to these segments.
The advantages of utilizing big data for effective business decision making, lies beyond just customer segmentation. A single view of the customer can lead to a much better consumer experience with the service, better asset utilization, fault prediction, better regulation and compliance and also bring in efficiencies in deployment of field forces.
For utilities today, a lot of this data already exists, but being huge in volume and existing in silos, there are not many actionable insights that can be extracted at the business level. According to a survey of 151 Utility executives in the US and Canada, an average utility with at least one smart meter program in place has increased the frequency of its data collection by 180x – collecting data once every four hours as opposed to just once a month. However, despite improvements, 45% of utilities still struggle to report information to business managers as fast as they need it while 50% miss opportunities to deliver useful information to customers.
There is a perceptible shift in mindset already happening in a lot of major utilities to do more with data. Businesses that have a clear understanding of the use cases where effective use of big data will help and who have a clearly defined roadmap for this initiative stand to benefit the most.