Predictive Analytics in the Telecom Industry: Elevate Your Customer’s Experience and Reduce Churn
Customer churn costs telecommunications companies big money. Based on recent studies, a company with 5 million customers experiencing a 2% average monthly churn rate for customers paying an average of US$100 per month would lose US $1.4 billion each year. The question is, how much is churn costing your organization?
It’s no wonder identifying and preventing churn tops the list of drivers behind telecom customer insight and analytics initiatives.
But reversing the churn trend is about more than offering a discount or other incentive to stay – it’s about understanding, anticipating, and satisfying consumers’ expectations for an outstanding experience.
Proactively satisfy customer expectations at every turn
This ties in perfectly with increased focus on the customer experience. One of the guiding principles of customer experience management is to look at how customers are engaging at every stage with the organization. This includes interactions before they sign on as customers, all the way through the end of their engagement with the company. The goal is understanding the customer’s experience and taking measures to shape it in the most positive way possible. In other words, it’s about anticipating needs and delivering services that keep customers happy, rather than reacting to ameliorate problems.
Clearly telecoms are embracing this principle. European Communications’ second annual customer experience survey shows that the percentage of operators with someone leading customer experience management in their organizations jumped six percentage points over 12 months.
Predict and prevent churn
Your company can make this vision a reality by applying predictive models and analytics. Based on certain events occurring – such as calls to customer support or lack of service usage – you can determine the probability of a contract ending. Certain predictive analytics software even recommends ways to reverse trends such as churn. Your organization can take these into account as it devises strategies and offers designed to mitigate churn. For example, it can use this insight to deliver a more unified experience across channels and devices, or offer new plans based on the consumer’s usage patterns.
Consider the example of Cox Communications. This leading telecom built predictive models that enabled it to quickly and precisely poll millions of customer observations and hundreds of variables to identify issues including the likelihood of churn. It then personalized offers across 28 regions. By acting upon the insights and recommendations it saw through predictive analytics, Cox Communications reduced customer churn by 28%.
As your organization stems the tide of customer abandonment, in many cases it will actually boost its revenue streams. That’s because it has pinpointed compelling motivations and triggers that prompt your customers to stay on board.
Want to understand how predictive analytics can help your organization deliver a better customer experience and reduce churn? Check out these additional real-world examples of telecommunications companies realizing success with predictive analytics.