Customer Segmentation Analyst

Expert analyst for designing and implementing customer segmentation strategies — from RFM analysis, behavioral clustering, and cohort modeling to persona creation, segment sizing, and actionable marketing recommendations based on data-driven customer groupings.

Gold

v1.0.00 activationsData & AnalyticsTechnologyintermediate

SupaScore

84.2

Research Quality (15%)

8.4

Prompt Engineering (25%)

8.5

Practical Utility (15%)

8.6

Completeness (10%)

8.3

User Satisfaction (20%)

8.2

Decision Usefulness (15%)

8.5

Best for

▸RFM analysis for e-commerce customer lifecycle optimization
▸Behavioral clustering to identify high-value customer segments for targeted campaigns
▸Cohort analysis to track customer retention and lifetime value evolution
▸Creating actionable customer personas with specific marketing recommendations
▸Churn prediction segmentation for proactive retention campaigns

What you'll get

●RFM segmentation with 8-10 named segments (Champions, At Risk, etc.) showing customer counts, revenue contribution, and specific email campaign recommendations for each
●K-means clustering results with 4-6 behavioral segments including feature importance, segment profiles, and recommended product positioning strategies
●Cohort retention heatmap with monthly retention curves by acquisition source plus actionable insights for improving customer lifecycle marketing

Not designed for ↓

×Lead scoring for prospects who haven't made purchases yet
×Real-time personalization engines requiring millisecond response times
×Demographic-only market research without behavioral data
×Single-transaction fraud detection or anomaly identification

Expects

Rich customer transaction data (purchase history, dates, amounts) plus behavioral engagement metrics (email opens, website visits, app usage) with clear business objectives for segment usage.

Returns

Detailed segmentation framework with clearly defined customer groups, sizing, characteristics, behavioral patterns, and specific marketing tactics for each segment with ROI projections.

Evidence Policy

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

customer-segmentationrfm-analysisbehavioral-clusteringcohort-analysisk-meanscustomer-lifetime-valuepersona-creationsegment-sizingmarketing-analyticschurn-preventiondata-driven-marketingunsupervised-learningcustomer-data-platform

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

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