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Industry Announcements

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Telcos must turn big data into smart data to manage customer churn and loyalty

Via Ovum Media center

Aug 5, 2015

Utilizing big data analytics to personalize the customer experience will be crucial for telcos to manage customer churn and improve loyalty, says Ovum. It takes on average, at least 3.5 years for telcos to break even on SAC (subscriber acquisition cost), however the average customer lifetime for telcos is currently only 2 years. To offset this, telcos must look to monetize their big data analytics investments and launch initiatives that will deliver value to their customers, reduce churn propensity and reduce the overall telco SAC.

As a part of its “Using Big Data Analytics To Manage Customer Churn and Loyalty KPIs” report, Ovum explores the key KPIs that telcos must use to improve customer loyalty, and highlights practical uses of big data analytics across the business.

Ovum analyst, Chantel Cary, commented: “Churn rates among telcos have reached staggering heights and are climbing. Across all regions, telcos are seeing customers churn at rates as disparate as 1.5% to nearly 6% per quarter. Telcos recognize the importance of customer retention and understand that big data analytics will help to differentiate the customer experience; many, however, have hesitated to launch big data analytics initiatives that will drive personalized offers and encourage the cross-sell of products that will lead to greater loyalty. This was confirmed further in our survey results which showed that while more than 70% of telcos that have invested in big data have planned to apply big data analytics across the business, less than 20% of these telcos have been able to fully deploy analytics to support customer-focused initiatives.”

“Poor management of customer-centric KPIs such as Average Revenue Per User (ARPU), Subscriber Acquisition Cost (SAC) and customer satisfaction scores have resulted in a vicious cycle of customer churn for telcos. When leveraged properly, however, big-data analytics can be used monitor customer sentiment, anticipate their activities and provide actionable insights to trigger proactive measures; it supports a wide range of business initiatives, and can be used to improve churn and loyalty metrics, as well as ARPU and customer satisfaction” concludes Chantel.

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