ARPU increase
Customer segmentation and pricing strategy drive premium tier success
A rapidly growing FinTech startup needed clarity on unit economics and pricing strategy. Through advanced customer lifetime value modeling and segmentation analysis, Lumen Insights enabled the successful launch of a premium tier that increased ARPU by 45% while improving forecasting accuracy from 60% to 92%.
Despite rapid growth, leadership couldn't confidently forecast revenue or determine optimal pricing strategy for new product tiers. The existing customer base showed varied engagement patterns, but the team lacked insights into which segments drove the most value.
Unclear customer lifetime value across segments
No data-driven pricing strategy for premium features
Revenue forecasting accuracy below 60%
Limited understanding of customer behavior patterns
Lumen Insights conducted deep-dive cohort analysis, built comprehensive customer lifetime value models, and implemented price elasticity testing. We developed dynamic forecasting capabilities with scenario planning to support strategic decision-making.
Comprehensive customer segmentation analysis
Lifetime value modeling across all cohorts
Price elasticity testing for premium features
Dynamic forecasting model development
A/B testing framework for pricing strategies
Timeline: 3 weeks for analysis, 6 weeks for premium tier launch
Analysis revealed that 20% of customers drove 80% of lifetime value. This insight enabled the launch of a premium tier specifically targeting high-value segments, resulting in significant ARPU improvement and enhanced forecasting capabilities.
Average revenue per user improvement with premium tier
Improvement from 60% to 92% accuracy
Of target segment adopted premium tier within 3 months
"Finally, data insights we can trust. They delivered clarity when our team was completely stuck."
Marcus Rodriguez
Head of Marketing
FinTech Startup
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The client is now implementing dynamic pricing based on customer behavior and exploring expansion into adjacent market segments using the segmentation framework.
