Harnessing Predictive Choice Modelling to Optimise Telco Service Rollout Strategy

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Case Study
Harnessing Predictive Choice Modelling to Optimise Telco Service Rollout Strategy

Industry: Telecommunications

Challenge: New Product Launch, Customer Acquisition and Customer Insights

Solution: Machine Learning and Predictive Choice Modelling

Technology: Python

Telecommunication tower of 3G, 4G and 5G network during sunset. Technological concept in communication. Pylon, antenna, microwave and nature background..

Situation and Challenge

A leading telecom provider, already offering “triple play” services (broadband, landline, and TV), sought to enhance customer loyalty and revenue through high-value add-on services, including on-demand video and domestic security monitoring. The critical challenge was to determine an effective rollout strategy for customer acquisition, necessitating:

  1. Accurate understanding of customer behaviour and choices
  2. Prediction of potential impact on demand and product adoption
  3. Informed planning for accelerating customer acquisition

Insight and Action​

Our approach encompassed:
  1. Commissioning quantitative market research to gauge customer interest, price sensitivity, and competitive landscape
  2. Applying decision tree probabilistic algorithms to model relationships between variables and predict outcomes
  3. Leveraging data fusion methods to extrapolate research findings and calculate probable responses to different choices for each customer
  4. Controlling for response biases to ensure accuracy of predictions
Key components of the model included: – Research findings – Product usage data – Customer lifetime value – Churn probabilities – Loyalty status
Results and Impact

Our intervention delivered substantial benefits:

– Achieved 93% accuracy in predicting customer behaviour

– Enabled an 8% uplift in new service subscriptions

– Facilitated a 12% improvement in targeted upselling and cross-selling to existing customers

– Provided a five-year market demand forecast for new services

– Generated revenue projections and churn predictions for each customer

 

Key Achievements:

– Developed a highly accurate predictive choice model for complex customer behaviour

– Identified priority areas for phased rollout of new service offerings

– Enabled data-driven decision-making for product launch and marketing strategies

– Provided long-term market insights for strategic planning

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