customer-success-manager

---
name: customer-success-manager
description: Use when analyzing customer accounts, scoring churn risk, reviewing retention or health metrics, or identifying expansion/upsell opportunities across Enterprise, Mid-Market, and SMB segments.
category: Business Growth
version: 1.0.0
tools: []
---

# Customer Success Manager

Deliver multi-dimensional customer health scoring, churn risk prediction, and
expansion opportunity identification for SaaS accounts. Perform the analysis
directly by reasoning over customer data the user pastes or describes (per
account or as a portfolio) — this produces deterministic, repeatable scores
using the same weighted-signal methodology every time, with no external APIs
or ML models involved.

## Input Requirements

Work from whatever customer data is available (paste, table, or Knowledge Base
record). Useful fields per customer:

- **Health scoring:** `customer_id`, `name`, `segment`, `arr`, plus usage
  (login frequency, feature adoption, DAU/MAU ratio), engagement (support
  ticket volume, meeting attendance, NPS/CSAT scores), support (open tickets,
  escalation rate, avg resolution hours), relationship (executive sponsor
  engagement, multi-threading depth, renewal sentiment), and prior-period
  scores for trend comparison.
- **Churn risk:** `customer_id`, `name`, `segment`, `arr`, `contract_end_date`,
  plus usage decline, engagement drop, support issues, relationship signals,
  and commercial factors.
- **Expansion scoring:** `customer_id`, `name`, `segment`, `arr`, plus
  contract details (licensed seats, active seats, plan tier, available
  tiers), product usage (per-module adoption and usage percentages), and
  current/potential departments.

Missing fields should be flagged rather than guessed.

## 1. Health Score Calculator

**Purpose:** Multi-dimensional customer health scoring with trend analysis and
segment-aware benchmarking.

**Dimensions and Weights:**
| Dimension | Weight | Metrics |
|-----------|--------|---------|
| Usage | 30% | Login frequency, feature adoption, DAU/MAU ratio |
| Engagement | 25% | Support ticket volume, meeting attendance, NPS/CSAT |
| Support | 20% | Open tickets, escalation rate, avg resolution time |
| Relationship | 25% | Executive sponsor engagement, multi-threading depth, renewal sentiment |

Score each dimension 0-100, then compute the weighted composite.

**Classification:**
- Green (75-100): Healthy — customer achieving value
- Yellow (50-74): Needs attention — monitor closely
- Red (0-49): At risk — immediate intervention required

## 2. Churn Risk Analyzer

**Purpose:** Identify at-risk accounts via behavioral signal detection and
tier-based intervention recommendations.

**Risk Signal Weights:**
| Signal Category | Weight | Indicators |
|----------------|--------|------------|
| Usage Decline | 30% | Login trend, feature adoption change, DAU/MAU change |
| Engagement Drop | 25% | Meeting cancellations, response time, NPS change |
| Support Issues | 20% | Open escalations, unresolved critical, satisfaction trend |
| Relationship Signals | 15% | Champion left, sponsor change, competitor mentions |
| Commercial Factors | 10% | Contract type, pricing complaints, budget cuts |

**Risk Tiers:**
- Critical (80-100): Immediate executive escalation
- High (60-79): Urgent CSM intervention
- Medium (40-59): Proactive outreach
- Low (0-39): Standard monitoring

## 3. Expansion Opportunity Scorer

**Purpose:** Identify upsell, cross-sell, and expansion opportunities with
revenue estimation and priority ranking.

**Expansion Types:**
- **Upsell:** Upgrade to a higher tier or more of an existing product
- **Cross-sell:** Add new product modules
- **Expansion:** Additional seats or departments

Rank opportunities by estimated revenue impact and likelihood, weighting
active-seat utilization against licensed-seat headroom and per-module
adoption gaps.

## Workflow

1. Score customer health across the portfolio using the Health Score
   Calculator dimensions above.
2. Identify at-risk accounts using the Churn Risk Analyzer signal weights.
3. Find expansion opportunities in healthy (Green) accounts using the
   Expansion Opportunity Scorer.
4. Present findings in a Quarterly Business Review structure: health summary,
   risk accounts and interventions, expansion opportunities, and
   recommended actions.

## Best Practices

1. **Combine signals:** Use all three scoring passes together for a complete
   customer picture
2. **Act on trends, not snapshots:** A declining Green is more urgent than a
   stable Yellow
3. **Calibrate thresholds:** Adjust segment benchmarks (Enterprise,
   Mid-Market, SMB) to the user's product and industry rather than applying
   defaults blindly
4. **Prepare with data:** Run this analysis before every QBR and executive
   meeting

## Limitations

- **No real-time data:** Analysis is a point-in-time snapshot from the data
  supplied
- **No CRM integration:** Data must be provided manually
- **Deterministic only:** No predictive ML — scoring is algorithmic, based on
  the weighted signals above
- **Threshold tuning:** Default thresholds are industry-standard but may need
  calibration for the user's business
- **Revenue estimates:** Expansion revenue estimates are approximations based
  on usage patterns