Customer Success Consultant

An autonomous agent that designs customer success programs — building onboarding flows, health scoring models, churn prediction, expansion playbooks, and QBR frameworks to maximize customer lifetime value.

When to Use This Agent

Choose Customer Success Consultant when:

• You need to build or improve customer onboarding workflows
• You want to implement health scoring to predict and prevent churn
• You need expansion and upsell playbooks for existing customers
• You are designing QBR (Quarterly Business Review) frameworks

Consider alternatives when:

• You need customer support ticket resolution (use a support agent)
• You need marketing automation for prospects (use a marketing agent)
• You need product analytics and feature usage tracking (use a product analytics tool)

Quick Start

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# .claude/agents/customer-success.yml
name: customer-success-consultant
description: Design customer success programs for retention and expansion
agent_prompt: |
  You are a Customer Success Consultant. Help build CS programs:

  1. Design onboarding workflows with time-to-value milestones
  2. Create health scoring models based on usage and engagement
  3. Build churn early warning systems with intervention playbooks
  4. Develop expansion playbooks for upsell and cross-sell
  5. Design QBR frameworks that demonstrate ROI
  6. Set up CS metrics and reporting (NRR, churn, CSAT, NPS)

  Focus on outcomes for the customer, not features of the product.
  The goal is to make customers successful, which makes retention natural.

Example invocation:

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claude "Design a customer health scoring model for our B2B SaaS with 500 enterprise customers"

Sample health score model:

Customer Health Score Model
━━━━━━━━━━━━━━━━━━━━━━━━━━

Score Range: 0-100

Components:
  Product Usage (40%)
    - DAU/MAU ratio (0-10)
    - Feature adoption breadth (0-10)
    - Usage trend (growing/stable/declining) (0-10)
    - Integration count (0-10)

  Engagement (30%)
    - Support ticket sentiment (0-10)
    - Training completion (0-10)
    - Executive sponsor engagement (0-10)

  Commercial (30%)
    - Contract renewal proximity (0-10)
    - Payment history (0-10)
    - Expansion conversations (0-10)

Thresholds:
  80-100: Healthy (green)  → Expansion opportunity
  60-79:  Neutral (yellow) → Proactive outreach
  40-59:  At Risk (orange) → Intervention required
  0-39:   Critical (red)   → Executive escalation

Alert Triggers:
  - DAU drops >30% week over week
  - No login from executive sponsor in 30 days
  - Support ticket with negative sentiment + score < 60
  - Contract renewal in 90 days + score < 70

Core Concepts

Customer Lifecycle Framework

Stage	Goal	Metrics	Playbook
Onboarding	Time to first value	Days to activation	Welcome sequence + training
Adoption	Feature breadth	Features used / total	Guided feature discovery
Retention	Prevent churn	Health score, NPS	Risk intervention
Expansion	Grow revenue	NRR, upsell rate	Business review + proposals
Advocacy	Generate referrals	Referral rate, G2 reviews	Advocacy program

Onboarding Workflow Design

Day 0: Welcome + account setup
  → Automated email: Welcome + quick-start guide
  → CSM intro call (15 min): understand goals, set milestones

Day 1-3: Technical setup
  → Integration wizard
  → Data import assistance
  → Check-in: "Did the integration complete successfully?"

Day 7: First value milestone
  → Guided walkthrough of core feature
  → "Aha moment" — customer sees first result
  → Celebration email: "You just completed your first [X]!"

Day 14: Adoption check-in
  → CSM call: Review initial results
  → Identify next use cases
  → Share best practices from similar customers

Day 30: Success review
  → Measure: Did customer achieve initial goal?
  → If yes: Discuss expansion opportunities
  → If no: Root cause analysis + remediation plan

Net Revenue Retention (NRR) Components

NRR = (Starting MRR + Expansion - Contraction - Churn) / Starting MRR

Example (monthly):
  Starting MRR:     $100,000
  Expansion:        + $15,000 (upsells, seat additions)
  Contraction:      - $5,000  (downgrades)
  Churn:            - $3,000  (cancellations)
  ─────────────────────────────
  Ending MRR:       $107,000
  NRR:              107%

Target NRR by segment:
  Enterprise: > 120%
  Mid-Market: > 110%
  SMB:        > 100%

Configuration

Option	Type	Default	Description
segment	string	"enterprise"	Customer segment: enterprise, mid-market, smb
healthScoreWeights	object	{ usage: 40, engagement: 30, commercial: 30 }	Health score component weights
onboardingDays	number	30	Target onboarding completion period
qbrFrequency	string	"quarterly"	Business review frequency
churnAlertThreshold	number	60	Health score threshold for churn alert
nrrTarget	number	110	Target Net Revenue Retention %

Best Practices

1. Define "time to first value" and obsess over reducing it — The single most important metric in customer success is how quickly a customer achieves their first meaningful outcome. For a project management tool, it might be "team completes first sprint." Track this metric relentlessly and remove every friction point in the path to that moment.

2. Use leading indicators, not lagging ones — Churn is a lagging indicator — by the time a customer cancels, you have already lost them. Track leading indicators: login frequency drops, feature usage decline, support ticket sentiment, and executive sponsor disengagement. These give you 30-90 days of warning to intervene.

3. Segment customers and differentiate your approach — Enterprise customers need white-glove onboarding and quarterly business reviews. SMB customers need scalable, automated touchpoints. Applying the same playbook to both wastes resources on SMB and under-serves enterprise. Design distinct journeys for each segment.

4. Make QBRs about the customer's goals, not your product — A QBR that shows feature usage statistics is a product demo, not a business review. Instead, show how product usage maps to the customer's business outcomes: "Your team's code review time decreased 40% since adopting our tool, saving an estimated $50K/year in engineering time."

5. Automate the bottom of the risk pyramid, humanize the top — For low-risk accounts, automated health monitoring and email sequences are sufficient. For high-risk accounts with score drops, a human CSM should intervene with a personalized phone call. The threshold for human intervention depends on account value and segment.

Common Issues

Health scores do not predict churn accurately — The health score model was built on assumptions rather than historical data. Backtest the model against your last 12 months of churned customers: did the model flag them as at-risk before they churned? If not, adjust the weights and add new signals. A good model should identify 70%+ of churned customers at least 30 days before cancellation.

Onboarding drops off after initial setup — Customers complete technical setup but never adopt advanced features. The onboarding flow focuses on "getting started" but not "getting value." Add milestone-based onboarding that guides customers through increasingly advanced use cases over 30-60 days, with check-ins at each milestone.

Expansion conversations feel salesy, damaging the CS relationship — Customers expect their CSM to be an advocate, not a salesperson. Frame expansion in terms of customer outcomes: "Based on your usage patterns, the Enterprise tier's API access would let your team automate the manual export process I know has been a pain point." The customer should feel helped, not sold to.