Segmentation Analysis

Overview

Segmentation Analysis helps when the team needs to know who the best customers are, marketing wants distinct groups to target, or churn is high and at-risk users need identifying before they leave.

What it covers

• Clarifies the segmentation goal first, since it determines which variables matter and how many segments are useful, typically 3 to 7.
• Selects 3 to 7 attributes and behaviors, handling missing values and scaling before clustering.
• Runs k-means clustering for data-driven segmentation, or applies rule-based logic for business-defined segments.
• Profiles each segment by its defining characteristics expressed as percent above or below the overall average, and names it descriptively.
• Validates that segments are statistically distinct and business-meaningful, then maps each one to a recommended strategy such as retain, monetize, or win back.

Part of Data Analytics Skills

This is one of 31 skills in the Data Analytics Skills library, in the Data Analysis & Investigation group.

Installation

1. Clone the repo once: git clone https://github.com/nimrodfisher/data-analytics-skills.git
2. Copy just this skill: cp -r data-analytics-skills/03-data-analysis-investigation/segmentation-analysis ~/.claude/skills/ (or ~/.agents/skills/ for Codex)
3. Ask your agent something like "segment our customers by value and behavior" and it activates on its own.

See the Data Analytics Skills entry for the full library.