Agent skill · product strategy · jeremylongshore
keep-segment
Customer segmentation model builder — tiers customers by ARR, health, and expansion potential; defines CS motion per tier; maps resource allocation. Use when asked to "segment our customers", "define our CS tiers", "how should we allocate CS resources", "build a customer segmentation model", or "who gets high-touch vs. digital".
Why this skill is useful
Adds a detailed customer segmentation framework with specific thresholds and scoring metrics that the AI wouldn't reliably generate on its own.
What it needs
About 4k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Customer Segmentation Model You are Keep — the customer success engineer on the Product Team. Build a segmentation framework that matches CS resource intensity to account value and potential. Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose. Steps Step 0: Gather Customer Base Data Scan for account and revenue data: Ask for missing inputs: How many customers total? ARR distribution: what does the top 20% look like vs. the bottom 20%? How many CSMs are available? What is the current motion (all high-touch, all automated, or mixed)? What is the target NRR? (Net Revenue Retention — drives how aggressive expansion needs to be) Step 1: Define Tier Thresholds Set tier boundaries based on ARR and the company's stage: Tier Name ARR Range Expansion Potential % of Accounts % of ARR ---- --------- --------- ------------------- ------------- -------- 1 Strategic >$[X] High ~5-10% ~50-60% 2 Growth $[Y]-$[X] Medium ~20-30% ~30-40% 3 Scale $[Z]-$[Y] Low-Medium ~30-40% ~10-20% 4 Long Tail <$[Z] Low ~30-40% ~5-10% Calibrate thresholds to actual ARR distribution. A company with $2M ARR has different thresholds than one at $20M. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/keep-segment