Behavioral Attributes: Actions and patterns (purchase frequency, channel preference)
Firmographics: Company characteristics (industry, size, revenue)
RFM: Recency, Frequency, Monetary value segmentation method
Propensity Score: Statistical likelihood of behavior or outcome
Index: Comparative measure showing over/under representation vs baseline
Penetration: Percentage of segment that exhibits behavior or owns product
Concentration: Degree to which behavior/value is focused in specific segments
Affinity: Statistical association between segment and behavior/product
Lift: How much more likely segment is to exhibit behavior vs average
Profile Variable: Attribute used to describe segment characteristics
Discriminating Variable: Attribute that differs significantly between segments
Homogeneity: Similarity within segment (low variance)
Heterogeneity: Difference between segments (high variance)
Segment Size: Count or percentage of population in segment
Segment Value: Economic worth or strategic importance of segment
Addressability: Ability to reach and communicate with segment
concepts:
Actionable Segmentation: Segments must be identifiable, accessible, substantial, and differentiable to drive business decisions
Within vs Between Variance: Effective segmentation maximizes differences between segments while minimizing differences within segments
Descriptive vs Predictive Profiling: Describing what segments look like vs predicting what they will do enables different business applications
procedures:
Build Demographic Profile: Select segment, calculate distribution of age/gender/location/income, compare to population baseline, identify over/under index
Create Behavioral Profile: Aggregate transaction data by segment, calculate RFM metrics, identify product/category preferences, measure channel usage patterns
Generate Segment Index Report: Calculate segment's rate for behavior, calculate overall population rate, divide segment rate by population rate, multiply by 100
Develop Persona Narrative: Analyze top characteristics of segment, identify motivations and pain points, create representative story and archetype, name persona
Compare Segment Performance: Select key metrics (revenue, margin, retention), calculate by segment, rank segments, visualize contribution and trends
Predictive Analytics: What segments will likely do next
Prescriptive Analytics: How to optimize engagement with segments
A Priori Segmentation: Predefined business-rule segments
Post Hoc Segmentation: Data-driven discovered segments
Single Dimension: One variable segmentation
Multi-Dimensional: Multiple variables combined
themes:
Customer-centricity and personalization
Market basket and cross-sell optimization
Resource allocation and prioritization
Targeted marketing and communication
Product development and positioning
Pricing and promotion strategy
Customer lifetime value optimization
Retention and churn management
Acquisition strategy and targeting
Channel strategy and optimization
trends:
Real-time dynamic segmentation
AI-driven micro-segmentation
Privacy-conscious profiling (cookieless)
Behavioral signal integration
Predictive lifetime value scoring
Graph-based relationship profiling
Intent-based segmentation
Cross-device identity resolution
Lookalike audience modeling
Segment-of-one personalization
Ethical AI in profiling practices
First-party data enrichment strategies
use_cases:
Retail Customer Segmentation: RFM analysis of transaction history to identify VIP, promising, at-risk, and lost customer segments for targeted reactivation campaigns
Healthcare Patient Profiling: Segment patients by chronic condition, risk score, and engagement level to personalize care management outreach
B2B Account Segmentation: Firmographic and behavioral profiling to prioritize sales efforts on high-potential accounts
Membership Organization Analysis: Profile members by engagement frequency, event attendance, and volunteer hours to design retention programs
Product Line Performance: Profile customers by product category purchases to identify cross-sell opportunities and under-penetrated segments
Channel Optimization: Behavioral profiling by channel preference (web, mobile, store, phone) to optimize communication strategy
Churn Prevention: Profile at-risk segments by declining engagement patterns to trigger proactive retention offers
New Product Launch: Identify early adopter segments through innovation index and category affinity for targeted beta testing
Geographic Expansion: Profile existing customers by location characteristics to identify similar markets for expansion
Pricing Strategy: Value-based segmentation to identify price-sensitive vs premium segments for tiered pricing models
Content Personalization: Psychographic and behavioral profiling to match content themes to segment interests
Donor Segmentation: Profile nonprofit donors by giving capacity, affinity, and recency to optimize fundraising appeals