Smarter campaigns, lower churn

In the US, the consumer market for wireless telecom is well-saturated, leading to pitched battles for customer acquisition among the major carriers. And as those acquisition costs begin to spiral, the marketing team at T-Mobile is looking at new ways to keep its hard-earned customers through new insights that it uncovers in its massive volumes of highly detailed customer data. According to Mikael Weigelt, Director of Customer Intelligence for T-Mobile USA, the company is increasingly drawing on the value that SAS^® can provide to perform customer analytics, modeling and campaign execution.

"What we've realized is that the clues we need to formulate more effective offers and campaigns lie in the massive volumes of data that we collect every hour of every day," he said. "We've used SAS to create numerous behavioral models of all of our millions of customers and then develop scores that distinguish among customers who are interested in different products or customer types who've historically shown a propensity to churn.

"Once we select the customers who are, we combine that with SAS Marketing Automation to execute our campaigns with much more efficiency. There are many business rules that determine if a customer is a good fit – things like customer tenure, whether they're eligible for a new/upgraded handset, their rate plan, their credit class and more. SAS Marketing Automation helps us keep all of these attributes straight."

Understanding the social networks of lnfluencers

To take these insights to an even higher level, T-Mobile has begun to work with a new tool, SAS Customer Link Analytics. This solution improves customer retention, cross-sell and up-sell by enabling marketers to identify social communities based on relationships among customers, measure and segment customers based on social influence, and target customers based on changes within their social communities. It enables T-Mobile marketers to quickly visualize social networks among customers who were previously unknown and uncover leaders, followers and other members within social communities. By incorporating such role-based variables, SAS Customer Link Analytics enhances existing segmentation models, enabling T-Mobile to discover how best to target its influencers.

"Like any telecom provider, T-Mobile has a large number of call detail records," said Weigelt. "We use SAS to sift through these records and understand how our customers interact with each other. What time of day do they call each other? How frequently do they call each other? How long are the calls? How many messages do they exchange? Metrics like these measure the strength and intensity of their interactions and create a map of their social network. We can use this to identify the influencers and followers and use these distinctions in our marketing campaigns."

According to Weigelt, the decision to use SAS for this strategic initiative was straightforward. "During our proof-of-concept stage, we evaluated multiple vendors, and SAS was clearly the best. We were examining roughly 1 billion distinct links, so the complexity was very high. The results from SAS customer network analysis were substantially better than the competitors.

"SAS gives us significantly more confidence in the decisions we're making with respect to whom we market to, the offers we make and the way we put campaigns together. What's more, the benefits appear to ripple out through our target market's followers as well. We expect to identify additional attributes for every subscriber and use them to enhance and refine our existing models. This could and should increase the precision of our models and increase our lift. By identifying the influencers, we can make very special offers that will have a high 'take' rate and lead to a viral effect among their followers.

"We're also looking at the reverse effect – what's the effect on followers if an influencer churns? Preliminarily, we believe that SAS Customer Link Analytics will help us retain our influencers to drop our churn rate roughly 25 percent. That would drop our churn from 2 percent to 1.5 percent, which would be a huge win for T-Mobile. While it's too early to declare victory, our testing has shown that we can expect great results and that our return on investment for this tool will be very, very high."