Customer Segmentation

Updated May 27, 2026

What this skill does

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.

Example

PROMPT

Segment our Shopify customers by purchase behavior. Use RFM analysis. Identify VIPs and at-risk customers.

OUTPUT

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

Required Tools

Shopify

Compatible Agents

Claude

Cursor

Windsurf

ChatGPT

Any MCP-compatible agent

Add to your agent

Download Skill

Or install via CLI:
$ npx skills add webrix-ai/agent-skills --skill customer-segmentation

Deploy Org-wide

Provision to teams via RBAC

Identity-aware execution

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Auto-bundled with required MCP servers

Use with

Free for up to 5 users

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