Telecommunications companies, including wireless providers, have historically struggled with high rates of customer churn (aka customer attrition), with customer defection rates as high as 40% for some wireless companies.
By contrast, the customer attrition rate for banks is 12.5% annually, according to a white paper by Financial Publishing Services.
This is important for telecom executives to recognize for several reasons. For starters, it costs more to find and replace telecom customers than it does to keep existing customers.
Numerous industry studies have found that it costs a company five times as much to acquire a new customer than to retain an existing customer.
There are numerous opportunities for telecom companies to use data analysis and data discovery tools and techniques to identify customers who are about to defect or are at risk of defecting.
As Donna Fluss points out in a recent article for C-GEM, many customers view mobile service as a commodity. In addition, many mobile carriers have focused on customer acquisition at the expense of service quality and retention, says Fluss.
There are sound business reasons for paying greater attention to customer retention. Reducing a company’s churn rate by as little as 1% can add millions of dollars to its bottom line, says Fluss.
And improvements that are made to customer service can dramatically affect customer loyalty and retention.
In fact, a one-point improvement in customer service satisfaction (on a scale of 1 to 5) generates a 5% improvement in implied retention rates among grocery customers, according to a study by Bain & Company. Meanwhile, in consumer electronics, a similar improvement in customer service satisfaction scores has resulted in a 2% gain in customer retention.
Contact center leaders and other decision makers in telecom companies can use data analysis and data discovery, in part, to determine the factors in customer service experiences that upset customers and prompt them to shift to other providers.
This can be done in a number of ways, including analyzing voice recorded contact center interactions with customers; the use of text analysis against email and chat exchanges with customers; and sentiment analysis that can be applied against social media comments made by customers that reference their feelings about the service and/or quality of particular telecom companies.
Taken a step further, data discovery can enable business leaders to identify the actions that can be taken that are most likely to prevent or deter customers from jumping ship.
For instance, telecom executives can use analytics and business intelligence dashboards to determine the types and value thresholds for offers that are most likely to keep high-value customers in the fold.
Telecom executives can also use customer data and analytics to determine where the company’s customer retention investments are best spent. For example, analytics can reveal historical trends about the propensity for customers to defect who exhibit certain behaviors or share particular characteristics related to their current lifecycle statuses.
So, analysis may reveal that 98% of a certain group of low- or mid-value customers who have been subscribers for five years or more are almost certain to break ties with their telecom carriers regardless of whatever offers might be extended to them.
From there, executive leaders can decide whether it’s worth the investment to try to retain certain sets of customers, including an evaluation of what their likely customer lifetime values are expected to be going forward based on historical averages.
