Becoming a predictive enterprise

While consumers may be seduced in the short-term by lower prices, the battle to stay ahead is being won by forward-thinking organisations that are realising competitive edge is often retained by factors unrelated to cost. Strengthening customer relationships is imperative for business success for one simple reason: customers drive revenues and profits.

Knowing what customers really want

Powergen is one of the UK’s leading energy suppliers, operating over nine million electricity and gas accounts across the country. The company produces electricity from a portfolio of world-class power stations and is also one of the leading names in ‘green’ power generation. Powergen decided to invest in SPSS’ predictive analytics software to help establish a clearer picture of what customers really wanted from their power supplier. This has helped to analyse past and current behaviour in order to predict how customers are likely to behave in the future.

Improving its call centre processes was fundamental to Powergen’s success. Using SPSS software meant the company was able to identify patterns in how customers were behaving on calls, and to analyse the reasons for that behaviour. The company was also able to improve the accuracy of meter readings by analysing previous statistics for the property in question. In addition, this helped the company’s aim to cut down the number of times customers needed to use its call centres.

“It was in everyone’s best interest to cut down on the number of calls customers needed to make,” explained Stewart Robbins, Customer Knowledge Manager at Powergen. “Fewer calls mean happier customers, and it allows us to run our call centres more efficiently, especially at busy times of the year. Using SPSS’ predictive analytics software, we were able to establish links between customer activities. For example, if customers were calling about meter readings, we were able to tell if it was appropriate to discuss paying by direct debit at the same time.”

Valuing loyal customers

Besides using SPSS for predicting customer behaviour, Powergen is also using the software to analyse customer feedback. This information is used to improve the design and tone of customers’ power bills. “It might seem like a small matter,” said Robbins, “but on the basis of customer feedback we discovered that the way power bills were written was extremely important to customer satisfaction levels. We used SPSS to analyse payment behaviour and establish which customers were most likely to default on payments. As a result, customers who have loyally paid their bills on time for years won’t receive a red reminder just because they’ve gone on a three-week holiday and missed their usual payment date.

“Similarly, commercial and domestic customers have very different priorities, and we’ve tailored their bills accordingly. It’s all about being more sensitive to customers’ needs and tailoring our activity to individuals as far as possible.”

The ability to better target its marketing and CRM activity at individual customers with SPSS’ software has inevitably saved Powergen a lot of money. Using SPSS has also reduced overhead due to the quick and efficient system. The analytics team is now able to look at a particular problem or situation, develop and execute on findings quickly, and then move on to the next step. Robbins continued: “Using SPSS as one of our core analytical solutions, we have reduced unnecessary marketing activity. The software helps us avoid targeting the wrong people with inappropriate campaigns, which could be potentially damaging to our reputation.”

Customers rule the economy

In today’s increasingly global and competitive marketplace, customers have more options available to them than ever before. Attracting customers cost-effectively and meeting their expectations for price, quality and service are essential to a customer lifetime value strategy. It is equally important, however, to identify and retain profitable customers and increase their value over time. This requires the ability to anticipate customer needs and present attractive offers in the right way, at the right time. The companies who can do this will be the companies that thrive in the customer economy.

What the Powergen example demonstrates is that predictive analytics is emerging as critically important in driving customer value and maximising returns from operational customer contact systems. When organisations deliver what customers need – what’s valuable to them – customers are more likely to remain open to future marketing efforts, buy more products and services, and, as a result, become more valuable. This is a win-win relationship for both the customer and the organisation. To achieve this type of relationship requires support from both operational and analytical CRM systems.

Currently, operational customer contact systems often rely on historical analytics, providing only a “rear-view mirror” of customer relationships and offering little support for optimising the decisions that shape the future. Meeting customers’ evolving needs, however, requires forward-looking solutions that anticipate changes in customer attitudes, preferences and actions. Only through the use of predictive analytics solutions incorporated into daily operations, will organisations be able to effectively direct their decisions to meet defined business goals and improve business processes – and hence become a Predictive Enterprise.

Industry leaders are therefore evolving their analytical capabilities by adding data mining and other predictive capabilities to their operational CRM systems. The most evolved analytical CRM systems continuously apply predictive analytics technologies and deploy the results enterprise-wide, so that whether customers interact with your organisation online, by phone or face-to-face, they receive the kind of treatment that meets their present needs and anticipates new ones. This increases their tendency to remain loyal and make additional purchases, increasing their lifetime value – and your organisation’s profits.

About SPSS

SPSS Inc is a leading global provider of predictive analytics software and solutions. By incorporating predictive analytics into their daily operations, organisations become predictive enterprises – able to direct and automate decisions to meet business goals and achieve a measurable competitive advantage. For additional information, please visit www.spss.com.