customer-segmentation

name	customer-segmentation
displayName	Customer Segmentation
tagline	Segment customers by behavior, purchase history, and lifetime value for targeted marketing.
description	Creates customer segments based on purchase behavior, engagement patterns, and lifetime value. Implements RFM (Recency, Frequency, Monetary) analysis and behavioral cohorts. Enables targeted marketing campaigns, personalized recommendations, and churn prediction for each segment.
department	["E-commerce","Marketing","Data & Analytics"]
use_cases	["Customer Analytics","Personalization","Retention Marketing"]
tools_required	["Shopify MCP"]
agents_compatible	["Claude / Claude Code","Cursor","Windsurf","ChatGPT","Any MCP-compatible agent"]
author	Webrix
verified	true
updatedAt	"2026-05-08T00:00:00.000Z"
version	1.0.0
exampleInput	Segment our Shopify customers by purchase behavior. Use RFM analysis. Identify VIPs and at-risk customers.
exampleOutput	Customer Segmentation — RFM Analysis SEGMENTS (4,200 total customers) Champions (8%): 340 customers — High R, High F, High M Avg LTV: $1,240 Action: VIP rewards, early access Loyal (15%): 630 customers — Med R, High F, Med M Avg LTV: $680 Action: Loyalty program, upsell At Risk (12%): 504 customers — Low R, Med F, Med M Avg LTV: $420 Action: Win-back campaign, survey New (20%): 840 customers — High R, Low F, Low M Avg LTV: $85 Action: Onboarding sequence, welcome offer Dormant (45%): 1,886 customers — Low R, Low F, Low M Avg LTV: $45 Action: Re-engagement or sunset KEY INSIGHTS - Champions generate 35% of revenue (8% of customers) - 504 at-risk customers represent $211K in potential churn - New customer conversion to Loyal: 22% within 90 days

Customer Segmentation

Segment customers by behavior, purchase history, and lifetime value for targeted marketing.

Integrations: Shopify

When to Use

• The user wants to segment customers for targeted campaigns
• Customer lifetime value analysis is needed
• The user mentions "customer segmentation", "RFM", or "cohort analysis"

Steps

Step 1: Pull Customer Data

Extract purchase history, engagement data, and customer attributes.

Step 2: Apply RFM Analysis

Score customers on recency, frequency, and monetary value.

Step 3: Define Segments

Create actionable segments with recommended marketing strategies.

Output

Deliver:

• Customer segments with counts and characteristics
• Recommended actions per segment
• LTV analysis and churn risk assessment