Published on the 06/08/2015 | Written by Newsdesk
Using big data analytics to personalise the customer experience will be crucial for telcos to manage customer churn and improve loyalty, says Ovum…
The research company says it takes on average, at least 3.5 years for telcos to break even on SAC (subscriber acquisition cost) – but the average customer lifetime for telcos is currently only 2 years. To offset this, telcos must look to monetise big data analytics investments and launch initiatives that will deliver value to their customers, reduce churn propensity and reduce the overall telco SAC.
Locally, at least one telco is on to big data. Spark, through Spark Ventures, operates Qrious, which offers analysis for the transport, local government, advertising, tourism and retail industries. While there is no evidence of its use of big data analytics on Spark itself, the possibility is strong – particularly if the resulting insights can help manage churn.
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.”
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.
Cary said telcos recognise 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 personalised 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), SAC and customer satisfaction scores have resulted in a vicious cycle of customer churn, Cary continued. “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,” she added.
