Business analytics helps telecommunications companies keep tabs on customers

The days of decisions based on a hunch and prayer are over. Now, European telecommunication companies are using business analytics for everything – from customer retention to planning more effective marketing activities.

There is an extremely close relationship between customers and their telephones. After all, many people would no more leave home without a phone than without their keys. This tie to mobile phones seldom extends to service providers, however. While consumers bind themselves to a particular brand of mobile phone, they are often willing to switch providers if a competitor offers a better deal on the same phone.

One benefit to the customer-phone bond is that it allows service providers to get a clear picture of customer habits. With terabytes of data on phone use, phone companies know:

• Who customers call.
• How long they talk.
• Where they call to and from.
• How many text and picture messages they send and receive.

Service providers are increasingly discovering that this data can be analyzed – through business analytics – to deliver an important piece of the customer retention puzzle.

Michael Berry, Founder of US-based Data Miners, comments on the complexity of customer retention.

“Will the customer be here tomorrow? Yes, probably. Will the customer be here in ten years? No –the telephone company probably won’t even exist by then. So the task is to find out how long it will be before the customer switches companies. The number of customers varies constantly, and we cannot just use averages when discussing when they will leave a company, since there are many variables involved in the decision,” he explained.

A sharp eye on customer behavior
Poland’s leading telecommunications company, Telekomunikacja Polska, is among those using business analytics to improve customer retention. It describes the importance of basing analytics efforts on business priorities to ensure that it becomes firmly anchored within the organization.

For example, the Polish company began by looking for usage patterns among the 10 percent of its customers who generate 70 percent of sales.

Jaroslaw Kosinski, Project Manager at Telekomunikacja Polska, shares his company’s experience. “We have a group of very active customers who create a lot of revenue. And we have a group of very loyal customers who do not create much revenue. But we are not interested in customers moving from the first group to the second, since changes in customer behavior always indicate increased risk of them leaving us,” he says.

Finding patterns in random data equals a hunch
TeliaSonera, another European carrier, explains how it uses business analytics to improve marketing campaigns. The company has moved far beyond sending different versions of its marketing materials to different target groups, taking a much more scientific approach that saves both time and money.

“We now have much better control of our campaign components,” says Riku Mäkeläinen of TeliaSonera.

Companies using business analytics find that the greater the amount of data, the greater the probability for accurate conclusions. In addition, it is best not to second-guess analytical software results – unless analysts have important information outside of the database; for example, knowledge of a market price reduction.

“This is because we humans are incredibly good at finding patterns in randomness. We are programmed to look for patterns and trends,” says Professor Paul Goodwin from the Management School at the University of Bath in England.

To illustrate his point, he shows a graph based on completely random numbers.

“See how perfectly this matches a six-month cycle,” he says, laying a second graph on top of the first. “We humans are also good at inventing series and cycles even where there are none. And what happens when we base forecasts on such a cycle?” he asks, rhetorically.