How Indosat grew revenue and reduced churn with a targeted loyalty program

2-minute read

Success Stories

"Our goal with this transformative program was to bring greater transparency of services to our customers, use real-time data driven campaigns to help retain high value customers, and grow revenue from lower and mid-tier customers with contextual marketing programs and incentives that drive service usage."

Ritesh Singh

Chief Marketing Officer, Indosat Ooredoo

10X increase in revenue linked to real-time marketing campaigns

Call for Change

Being the major mobile operator in Indonesia and has a digital footprint that supports 59 million subscribers over the country’s 17,000 islands. Indosat wanted to position itself as a customer-centric technology leader, where digital transformation would drive customer loyalty through greater simplicity and transparency of services and pricing.

A lack of real-time contextual marketing capabilities creates challenges for the operators to provide personalized services to different users, including loans for users whose balances are too low and notifications for customers who have not consumed services over a certain period. Lack of transparency and service visibility has in turn led to high churn rates.

Technology at Play

10X

increase in revenue linked to real-time marketing campaigns

3.5X

increase in revenue from new digital engagements

50%

High value customer churn has dropped

Indosat set out to address its revenue and churn challenges through the development of a real-time customer value management program with Comviva Technologies, enabling real-time marketing and subscriber loyalty programs

Comviva implemented its MobiLytix^TM Real Time Marketing Platform along with MobiLytix^TM Rewards, which enabled Indosat to capture and measure over 800 business data characteristics of its customers and creates a dedicated loyalty program that allows subscribers to earn and redeem points based on service consumption.

Indosat’s new real-time CVM platform leverages AI/ML-based models and real-time decisioning in milliseconds to better predict customer usage patterns of its more than 59 million subscribers.

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