thedixitjain 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:
find . -name "*.md" -o -name "*.csv" -o -name "*.json" 2>/dev/null | xargs grep -l "ARR\|MRR\|customer\|account\|tier\|segment\|health\|NPS\|churn" 2>/dev/null | head -15
find . -name "*.md" 2>/dev/null | xargs grep -l "CSM\|customer.success\|expansion\|upsell\|NRR\|GRR" 2>/dev/null | head -10
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.
Step 2: Health Score Components
If no formal health score exists, define one:
| Signal | Weight | Score Range |
|---|---|---|
| Product usage (DAU/MAU ratio) | 30% | 0-30 |
| Feature adoption (core features used / available) | 20% | 0-20 |
| Support health (CSAT score, open escalations) | 20% | 0-20 |
| Relationship quality (exec access, champion active) | 15% | 0-15 |
| NPS / satisfaction signal | 15% | 0-15 |
Total: 0-100
| Score | Status | Color |
|---|---|---|
| 80-100 | Healthy | Green |
| 60-79 | Stable | Yellow |
| 40-59 | At Risk | Orange |
| 0-39 | Critical | Red |
Step 3: Expansion Potential Score
Add an expansion lens (separate from health):
| Factor | Indicator |
|---|---|
| Seats used / seats licensed | >80% utilization = expansion ready |
| Feature requests in support | 3+ requests for features in higher tier |
| Company growth signals | New job postings, funding, headcount growth |
| Multi-team mentions | Using product across more than one team |
| API usage spikes | Integration depth suggests platform potential |
Score: HIGH / MEDIUM / LOW per account.
Step 4: Define CS Motion Per Tier
Map each tier to the appropriate CS motion and resource level:
## Tier 1 — Strategic (High-Touch)
CSM ratio: 1 CSM : 5-8 accounts
Motion: Named CSM, dedicated AE, executive sponsor from vendor side
Cadence: Monthly business review, QBR every quarter, executive sponsor call bi-annually
Channels: Phone, Slack Connect, in-person / video
Playbooks: Full onboarding, custom success plan, expansion proactive, multi-year renewal
Escalation: CSM manager and VP CS have direct visibility
## Tier 2 — Growth (Mid-Touch)
CSM ratio: 1 CSM : 15-25 accounts
Motion: Pooled CSM with account ownership, AE on expansion calls only
Cadence: Bi-monthly check-in, QBR twice per year
Channels: Email, video, occasional Slack
Playbooks: Templatized onboarding, health-triggered outreach, expansion at 70%+ utilization
Escalation: Health score drop triggers CSM manager review
## Tier 3 — Scale (Digital / Light Touch)
CSM ratio: 1 CSM : 50-100 accounts
Motion: Automated health monitoring, CSM engages on signals only
Cadence: Quarterly email QBR, automated in-app nudges
Channels: Email, in-app messaging, help center
Playbooks: In-app onboarding, automated health alerts, self-serve expansion
Escalation: Red health score or expansion signal queues CSM outreach
## Tier 4 — Long Tail (Self-Serve)
CSM ratio: 0 (community + product-led)
Motion: Community forum, knowledge base, in-app guidance
Cadence: Lifecycle emails only (triggered by behavior)
Channels: Email, in-app, community, chatbot
Playbooks: Automated onboarding sequences, upgrade prompts at usage limits
Escalation: High ARR accounts in this tier should be reviewed for tier promotion
Step 5: Resource Allocation Model
## CS Resource Map
Total CSM headcount: [N]
Tier 1 CSMs: [N] (handle [N] accounts, $[X] ARR)
Tier 2 CSMs: [N] (handle [N] accounts, $[X] ARR)
Tier 3 CSMs: [N] (handle [N] accounts, $[X] ARR)
Tier 4: automated (handle [N] accounts, $[X] ARR)
CSM : ARR ratio per tier:
Tier 1: $[X] ARR per CSM (target <$500K for premium coverage)
Tier 2: $[X] ARR per CSM (target $1M-$2M)
Tier 3: $[X] ARR per CSM (target $2M-$5M)
Step 6: Tier Promotion / Demotion Rules
Define when an account moves between tiers:
- Promote: ARR crosses threshold on renewal OR expansion event
- Promote: Expansion potential score = HIGH for 2 consecutive quarters
- Demote: ARR drops below threshold on renewal
- Demote: No expansion signals for 4 quarters (Tier 1 → 2 only, after review)
Delivery
Output: (1) tier definitions with thresholds, (2) health score framework, (3) CS motion per tier, (4) resource allocation model. If output exceeds 40 lines, delegate to /atlas-report.
Source: jeremylongshore/claude-code-plugins-plus-skills → plugins/ai-agency/tonone/bundle/revenue-team/skills/keep-segment/SKILL.md