Customer churn has and continues to be a big problem for wireless carriers. The problem is so severe that more than one-third (36%) of U.S. customers are considering leaving their mobile carriers over the next 12 months.
Moreover, only 13% of wireless customers demonstrate a level of loyalty required to retain them from competitive offers and service disruptions, according to a study by WDS, A Xerox Company.
Despite these challenges, the use of big data and analytics represents a tremendous opportunity for wireless carriers to identify customers who are at risk of defecting as well as opportunities to provide customers with services and support that can strengthen loyalty.
In fact, mobile operators worldwide are poised to see a $4 billion swing in revenue through their uses of big data analytics to help reduce customer churn by anticipating and taking action to prevent customer defection, according to a new report from Jupiter Research.
And a number of leading wireless carriers have already experienced significant reductions in customer churn following the implementation of analytics platforms, according to the report.
For instance, the report notes that MTN South Africa has deployed a big data program that combines subscriber information and social network analysis to determine priority users and customer networks. By analyzing and acting on the insights generated through these efforts, MTN South Africa has seen annualized customer churn drop by more than 20%.
The report also finds that wireless companies in more mature markets such as the U.S. are increasingly coupling analytics with loyalty programs to improve customer retention.
Other information about customer behavior, device ownership, sentiment about service interests, and other information can also be analyzed by wireless carriers to identify opportunities to stem defection and strengthen loyalty.
As an example, customers who use 4G LTE-enabled devices experience fewer data-related issues than do customers who use 3G and other 4G-related devices, according to a study by J.D. Power & Associates.
It’s hardly surprising, then, that the likelihood of switching carriers among 4G LTE customers is significantly lower than among smartphone customers using other network technology (11% versus 15%, respectively).
So while wireless carriers continue to support a certain number of 3G and other network customers, they can analyze behavioral, transactional, and lifecycle status information among customers and prospective customers with similar attributes to craft messaging and offers that are aimed at attracting 4G LTE customers.
Meanwhile, an analysis of customer data by segment (e.g., high-value customers; customers who use specific WiFi services) can reveal correlations between customers who use certain wireless services and the likelihood of specific types of customer to purchase additional services.
For instance, studies have shown that shared data plans encourage higher data usage (which translates into higher revenue for carriers).
An analysis of current customers and prospects who demonstrate similar demographic and behavioral traits can help carriers devise messaging and offers aimed at cross-selling or upselling customers and prospects on shared data plans.