The Client
Leading telecommunications provider offering ‘triple play’ services (broadband, landline, TV) developing high-value add-on services including on-demand video and domestic security monitoring to increase loyalty and revenue.
The Challenge
Complex preferences made demand prediction difficult
Determining effective rollout strategy for new high-value add-on services required accurate understanding of customer behaviour and choices.
Complex relationships between customer preferences, price sensitivity and service adoption made it difficult to predict demand and plan acquisition strategies.
What We Did
Decision tree algorithms with data fusion
- Commissioned quantitative market research measuring interest, price sensitivity and competitor analysis
- Applied decision tree probabilistic algorithms modelling relationships between research, usage and loyalty
- Leveraged data fusion to extrapolate research findings and calculate probable responses
- Controlled for response biases whilst incorporating lifetime value and churn probabilities
- Created comprehensive demand model providing market forecasts and customer-level predictions
The Impact
Accurate forecasting enabling phased rollout
93%
Behaviour prediction accuracy
8%
Subscription uplift
12%
Cross-sell improvement
Achieved 93% accuracy in customer behaviour prediction enabling 8% uplift in new service subscriptions and 12% improvement in targeted cross-selling. Provided five-year market demand forecast identifying priority areas for phased rollout.
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