Applying technology to boost customer loyalty

Guesswork no longer cuts it. Smart companies are using business analytics software to improve customer loyalty.

In today's intensely competitive and fast-changing marketplace, companies can no longer rely on gut instinct, guesswork or "business as usual." Across all industries, businesses are turning to data analytics to quickly and accurately respond to and even predict buyer behavior in their quest to grow revenue while securing customer loyalty.

The desire to engage with customers more effectively is fueled in part by what many see as a shift in power from sellers to buyers, thanks to social media and the rise of mobile computing. In IBM's most recent Global CEO Study, in fact, more than 70% of CEOs said they were seeking a better understanding of individual customer needs and improved responsiveness to those desires. And according to IDC research, the global market for business analytics software grew 14% in 2011, compared with 11.6% the year before, and is slated for 9.8% compound annual growth between now and 2016.

Here is a look at two companies that are striving to capture the loyalty of their customers through the use of analytics.

T-Mobile: Combating Customer Churn

For wireless providers, customer churn can be a killer. According to research from Strategy Analytics, at the end of 2011, the percentage of mobile customers who switch service providers every year reached 44%, its highest level ever.

T-Mobile is one carrier that has been feeling that pain. Dwarfed by AT&T and Verizon Wireless in market share, the company was losing one customer for every customer it gained in early 2012, according to a statement by former CEO Philipp Humm earlier this year. To offset that trend, T-Mobile is digging into its customer data to better understand buyer behavior and more precisely target customer needs.

"Customers have so many dynamic options right now," says Alison Bessho, director of IT enterprise systems at T-Mobile. "They can easily get intrigued by something new with a different company, so in order to keep them happy, we're always looking for creative ways to give them something new and different."

To that end, T-Mobile uses a Teradata database and analysis tools from SAS to collect and analyze customer data, including current plan rates, the number of family plans versus individual plans, credit ratings, network usage metrics and statistics comparing the amount of talking time and the amount of texting time. It then segments the customer base, builds focused campaigns for different customer profiles and presents offerings via its various sales channels, including stores, call centers and websites.

The marketing team then analyzes how customers respond to these campaigns to project financial returns and fine-tune the offers. To do that, it feeds data into the Hana real-time data analytics appliance from SAP, which uses in-memory computing to perform rapid analytics on large data sets. This allows statistics modelers and business analysts to query the data and -- if they find something unexpected -- query further, without involving IT.

"You don't have to pre-think what types of analytics you're going to do or pre-build the aggregation tables that you build with traditional BI solutions," Bessho says. Plus, the data can be loaded more quickly into the appliance than it can with traditional analytics platforms, and the queries run 55 times faster than with a traditional database. That speed encourages analysts to explore creatively, she says.

"A lot of the benefit is finding the unknown," Bessho says. "They get a surprising result, and they want to drill down into the data in ways they never anticipated. So it's important that the tool is responsive and cuts through rows of data quickly."

Analysts can now determine the types of campaigns that work best for various customer groups. "We now know how to go to different customers with [different] offers," Bessho says. For instance, one way to segment customers is by how close they are to the end of their contracts. Knowing this -- as well as what type of plans they have, what their credit scores are, and where they live -- T-Mobile can, for example, send phone upgrade offers to long-term customers and offers for different rate plans to newer ones.

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