Transforming Customer Retention & Revenue with Data Modernization
RTS helped a leading U.S. wireless carrier reduce churn, increase revenue per customer, and modernize analytics through AI/ML enablement and data modernization.
Helping a Wireless Leader Turn Data Into Retention and Revenue Growth
One of the largest wireless carriers in the United States, with more than 143 million subscribers, partnered with RTS to improve customer retention, increase monthly customer revenue, and modernize IT operations.
Client
Telecommunication leader.
Scale
143M+ subscribers.
Focus
Churn reduction and revenue growth.
Solution
AI/ML and data modernization.
A Competitive Market Required Smarter Customer Intelligence
As competition intensified, the carrier needed a better way to understand subscribers, identify churn risk, and use data to improve retention and revenue performance.
Customer Churn
The carrier needed to identify customers at risk before they left.
Revenue Visibility
Teams needed clearer insight into revenue per customer across segments.
Data Modernization
The organization needed modern analytics to support AI/ML-driven decisions.
Reducing Customer Churn with Predictive Analytics
RTS created a modernized data and analytics dashboard that helped the carrier better understand customers, identify churn behavior, and act before subscribers left.
Churn Identification Framework
RTS developed a framework to identify churn behavior and help the client proactively address at-risk subscribers.
AI/ML Algorithms
RTS modeled churners, created a factor map and hypothesis matrix, identified required data elements, and generated leading indicators of churn.
More At-Risk Customers Reached Before They Churned
The new churn identification approach helped the client address 73–79% of potential churners compared to the previous 30% reach.
Potential Churners Addressed
Lift Over Previous Reach
Overall Customer Retention
Increasing Revenue per Customer per Month
RTS helped the wireless leader use big data and cloud migration to calculate revenue per customer per month for residential and commercial customers.
Data Warehouse Strategy
RTS created a KPI-driven data strategy that loaded subscriber data into a data warehouse for advanced reporting and analytics.
Self-Service Analytics
Marketing, finance, and operations teams used data to analyze profitability, segment customers, and maximize recurring revenue.
Stronger Revenue Visibility Across a Major Subscriber Base
With improved data and analytics, the client gained better visibility into customer segments, profitability, market position, and opportunities to increase monthly recurring revenue.
U.S. Market Share
Monthly Customer Revenue
Yearly Revenue Growth
Data Modernization Built for Customer and Revenue Intelligence
RTS helped the telecom leader turn subscriber data into actionable insights, enabling proactive retention strategies, self-service analytics, and stronger revenue decision-making across the business.
Use AI and Analytics to Improve Customer Outcomes
RTS helps organizations modernize data platforms, identify customer behavior patterns, and turn analytics into revenue and retention strategies.