Customer Lifetime Value Modeler

Build rigorous Customer Lifetime Value models using probabilistic frameworks (BG/NBD, Pareto/NBD), cohort-based retention analysis, and predictive analytics — transforming transaction data into actionable LTV predictions that drive acquisition budgets, segmentation, and growth strategy.

Platinum

v1.0.00 activationsFinance & BusinessBusinessexpert

SupaScore

85.1

Research Quality (15%)

8.6

Prompt Engineering (25%)

8.5

Practical Utility (15%)

8.6

Completeness (10%)

8.4

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.7

Best for

▸Build BG/NBD models for e-commerce CLV prediction using transaction history
▸Design cohort retention curves for SaaS revenue forecasting
▸Calculate optimal LTV:CAC ratios for paid acquisition budget allocation
▸Implement Pareto/NBD models for non-contractual customer lifetime value
▸Create RFM segmentation frameworks for customer portfolio analysis

What you'll get

●Statistical model implementation with parameter estimates, goodness-of-fit metrics, and CLV predictions with confidence intervals
●Cohort retention tables showing logo/revenue retention rates by month with visual dashboards
●Customer segmentation matrix with RFM scores, predicted CLV, and recommended treatment strategies

Not designed for ↓

×Real-time recommendation engines or personalization systems
×Basic customer satisfaction surveys or NPS analysis
×Attribution modeling for marketing touchpoints
×Inventory forecasting or demand planning

Expects

Clean transaction data with customer IDs, purchase dates, amounts, plus business model classification (contractual vs non-contractual).

Returns

Probabilistic CLV predictions, cohort retention analysis, customer segmentation tiers, and LTV:CAC optimization recommendations with statistical confidence intervals.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

customer-lifetime-valueclvltv-caccohort-analysisretention-modelingbg-nbdrfm-analysisunit-economicschurn-predictionsaas-metricspredictive-analyticscustomer-segmentation

Research Foundation: 8 sources (2 books, 2 academic, 3 industry frameworks, 1 official docs)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/16/2026

Initial release

Prerequisites

Use these skills first for best results.

Python Data AnalystGold SQL Query OptimizerPlatinum

Works well with

Cohort Analysis DesignerGold Customer Acquisition Cost OptimizerPlatinum Customer Segmentation AnalystGold Revenue Forecasting AnalystGold Subscription Churn AnalystGold

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Bayesian Statistics ExpertPlatinum Time Series Forecasting ExpertPlatinum Predictive Maintenance Edge SpecialistGold

Common Workflows

SaaS Unit Economics Optimization

Model CLV, optimize acquisition costs, then build comprehensive unit economics framework for growth planning

customer-lifetime-value-modeler→Customer Acquisition Cost Optimizer→saas-unit-economics-planner

Customer Portfolio Analytics Pipeline

Build retention cohorts, predict lifetime value, then create segmentation strategy for personalized growth

Cohort Analysis Designer→customer-lifetime-value-modeler→Customer Segmentation Analyst

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