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Telcos must turn Big Data into smart data: Ovum

Hafizah Osman (ARN) | Aug. 6, 2015
Utilising Big Data analytics to personalise the customer experience will be crucial for telcos to manage customer churn and improve loyalty, according to independent analyst firm, Ovum.

Telcos must turn Big Data into smart data: Ovum

Utilising Big Data analytics to personalise the customer experience will be crucial for telcos to manage customer churn and improve loyalty, according to independent analyst firm, Ovum.

In its latest Using Big Data Analytics To Manage Customer Churn and Loyalty KPIs study, it found that on average, it takes at least 3.5 years for telcos to break even on subscriber acquisition costs (SACs). However, it also found the average customer lifetime for telcos is currently only two years.

Ovum analyst, Chantel Cary, said to offset this, telcos must look to monetise their Big Data analytics investments and launch initiatives that will deliver value to their customers, reduce churn propensity and reduce the overall telco SAC.

"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 percent to nearly six percent per quarter.

"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," she said.

The study also found that while more than 70 percent of telcos invested in Big Data have planned to apply analytics across the business, less than 20 percent of them 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 for telcos.

"When leveraged properly, however, Big Data analytics can be used [to] 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," Cary added.

Source: ARN Australia

 

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