Customer Lifecycle
What happens after the deal closes determines whether you build a business or a treadmill.
Acquiring a customer costs 5-25x more than retaining one. The lifecycle workflow ensures every customer progresses from payment to partnership — or gets flagged before they churn.
Overview
| Attribute | Value |
|---|---|
| Purpose | Manage customers from onboarding through retention, expansion, and advocacy |
| Trigger | Deal status changes to "Won" in CRM |
| Frequency | Continuous — stage-specific touchpoints at defined intervals |
| Duration | Ongoing per customer |
| Owner | Customer Success (human relationship) + AI (health scoring, automation) |
| Output | Customer health score, expansion signals, churn alerts, advocacy pipeline |
Human Role: Relationship management, outcome strategy, escalation, trust AI Role: Health scoring, churn prediction, usage analytics, trigger automation Spectrum: AI-Assisted (health scoring AI-led, relationship human-led)
Prerequisites
Tools Required
| Tool | Purpose | Access |
|---|---|---|
| CRM | Customer records, activity tracking | Sales CRM |
| Product analytics | Usage data, feature adoption | App analytics |
| Email automation | Onboarding sequences, renewal reminders | Resend / similar |
| Health scoring | Automated risk and opportunity signals | Compound Rate algo |
Knowledge Requirements
- Product value mapping per customer segment
- Onboarding milestones and activation criteria
- Expansion triggers and pricing tiers
- Churn signals from historical data
Inputs
| Input | Source | Required? |
|---|---|---|
| Won deal with customer context | Funnel Engineering | Yes |
| Product usage data | Application analytics | Yes |
| Customer communication history | CRM activities | Yes |
| Pricing/contract terms | Deal record | Yes |
Process
Phase 1: Onboarding
Duration: First 7-30 days post-close Responsibility: Human-led, AI-assisted
Onboarding is the most dangerous period. The customer just bought your promise. Now you have to deliver.
Step 1.1: Welcome and Setup
| Action | Owner | Timeline | Verification |
|---|---|---|---|
| Welcome email with next steps | AI (automated) | Day 0 | Email delivered |
| Kickoff call to confirm goals | Human | Day 1-3 | Call completed, goals documented |
| Account setup and access | AI + Human | Day 1-5 | Customer can log in and see their data |
| Data migration/import | Human-led | Day 1-14 | Existing data loaded and verified |
| Training session | Human | Day 7-14 | Customer completes core workflow |
Step 1.2: Activation Milestone
The single most important moment in the customer lifecycle: first value delivered.
| Product | Activation Metric | Target Timeline |
|---|---|---|
| CRM & RFP | First answer approved to library | 7 days |
| ETL Data Tool | First data pipeline running | 14 days |
| Agent Platform | First agent productive task | 7 days |
If activation doesn't happen within 2x the target timeline, escalate. The customer is at high churn risk.
Step 1.3: Onboarding Scorecard
| Criterion | Status | Notes |
|---|---|---|
| Account configured | ? | |
| Data imported | ? | |
| First workflow completed | ? | |
| Activation metric achieved | ? | |
| Key stakeholder trained | ? |
Phase 1 Output: Activated customer with documented goals and confirmed first value
Phase 2: Adoption
Duration: Days 30-90 Responsibility: AI-led tracking, human-led coaching
The customer is set up. Now they need to build habits.
Step 2.1: Usage Monitoring
| Metric | Healthy | At Risk | Critical |
|---|---|---|---|
| Weekly logins | 3+/week | 1-2/week | 0/week for 2 weeks |
| Core feature usage | 3+ features used | 1-2 features | None after onboarding |
| Data growth | Growing weekly | Flat | Declining |
| Team adoption | Multiple users active | Only 1 user | Champion went quiet |
| Support tickets | 0-2 (good — means using it) | 5+ (friction) | 0 after initial spike (gave up) |
Step 2.2: Adoption Coaching
| Trigger | Action | Owner |
|---|---|---|
| Feature underuse detected | Share tutorial or use case for unused feature | AI (email) |
| Usage plateau at 30 days | Schedule coaching call | Human |
| New feature released | Personalized notification if relevant to their use case | AI |
| Usage spike | Recognize and reinforce ("You processed 5 RFPs this week") | AI |
| Usage drop | Check in — ask what changed, not "are you okay?" | Human |
Phase 2 Output: Customer achieving regular usage patterns across core features
Phase 3: Retention
Duration: Ongoing from day 90+ Responsibility: AI-led health scoring, human-led relationship
Step 3.1: Customer Health Score
| Component | Weight | Score (0-100) | Source |
|---|---|---|---|
| Usage | 30% | ? | Product analytics |
| Engagement | 20% | ? | Response to comms, support interactions |
| Outcome | 25% | ? | Are they achieving stated goals? |
| Relationship | 15% | ? | NPS, satisfaction, stakeholder access |
| Growth | 10% | ? | Expansion signals, team growth |
HEALTH SCORE = weighted components
Above 75: Healthy — nurture and expand
50-75: Monitor — proactive outreach
Below 50: At risk — intervention required
Below 25: Critical — executive escalation
Step 3.2: Churn Prevention
Churn rarely happens suddenly. These signals precede it by 30-60 days:
| Signal | Lead Time | Response |
|---|---|---|
| Login frequency drops 50%+ | 30-60 days | Check-in call — understand what changed |
| Champion leaves company | Immediate risk | Map new stakeholder, re-onboard |
| Support tickets spike then stop | 30 days | They gave up solving it — proactive fix |
| Competitor content shared internally | 14-30 days | Value reinforcement, address gaps |
| Renewal conversation delayed | 14 days | Direct conversation about concerns |
| "Just checking" requests for data export | Immediate | They're preparing to leave — escalate |
Step 3.3: Retention Touchpoints
| Interval | Touchpoint | Owner | Purpose |
|---|---|---|---|
| Monthly | Usage summary email | AI | Show value delivered |
| Quarterly | Business review call | Human | Confirm goals, surface new needs |
| Semi-annual | Executive check-in | Human | Relationship depth, strategic alignment |
| Pre-renewal (60 days) | Renewal planning | Human | Confirm continuation, discuss terms |
Phase 3 Output: Health score per customer, churn alerts, retention actions
Phase 4: Expansion
Duration: Triggered by signals Responsibility: Human-led, AI signals
Expansion revenue from existing customers is 3-5x more cost-effective than new acquisition.
Step 4.1: Expansion Signals
| Signal | What It Means | Action |
|---|---|---|
| Hit usage limits | They need more capacity | Propose upgrade |
| New team members added | Adoption spreading | Offer team training |
| Asked about feature not in plan | Need exists, willing to pay | Demo advanced feature, propose tier change |
| Referred someone | High satisfaction, trusts you | Thank, offer referral incentive |
| Achieved stated goals early | Looking for next challenge | Propose new use case or product |
| Industry change (growth, regulation) | New needs emerging | Proactive outreach with relevant solution |
Step 4.2: Expansion Playbook
| Type | Trigger | Offer | Evidence Needed |
|---|---|---|---|
| Upsell | Usage limits, power user signals | Higher tier, more seats | Usage data proves need |
| Cross-sell | Adjacent pain discovered | New product module | Customer confirms the pain |
| Expansion | Company growing, new teams | Enterprise agreement | New stakeholders engaged |
| Referral | High NPS, advocacy signals | Referral program, case study | Customer agrees to participate |
Phase 4 Output: Expansion pipeline with qualified opportunities
Phase 5: Advocacy
Duration: Earned over time Responsibility: Human-led
Advocates are your most powerful sales channel. They sell with credibility you can't buy.
Step 5.1: Advocacy Ladder
| Level | Ask | Value to You | Value to Them |
|---|---|---|---|
| Reference | "Can we mention your name?" | Social proof | Recognition |
| Case study | "Can we document your results?" | Content asset | Industry visibility |
| Referral | "Who else has this problem?" | Warm introductions | Reciprocity, helping peers |
| Co-creation | "Help us build the next feature" | Product direction | First access, influence |
| Champion | "Speak at our event / on our podcast" | Authority | Platform, personal brand |
Step 5.2: Advocacy Triggers
Only ask when:
- Customer has achieved measurable results (quantified)
- Relationship is strong (health score >80)
- They've expressed satisfaction unprompted
- You can offer something in return (visibility, access, recognition)
Phase 5 Output: Advocacy assets (case studies, referrals, testimonials)
Customer Feedback Loop
The lifecycle isn't just about the customer. It's a feedback channel back to product and marketing.
CUSTOMER EXPERIENCE
↓
OBJECTIONS → Product improvement backlog
PRAISE → Marketing proof points
CHURN → ICP refinement
EXPANSION → New feature validation
REFERRAL → Channel effectiveness data
Objections as Product Intelligence
| Objection Category | Routes To | Action |
|---|---|---|
| Feature gap | Product backlog (PRDs) | Spec if demand > 3 customers |
| Usability friction | Engineering sprint | Fix in next cycle |
| Pricing concern | Business strategy | Validate pricing model |
| Integration need | Platform team | Assess build vs partner |
| Competitor advantage | Competitive intelligence | Analyze, decide: match, differentiate, or accept gap |
Outputs
| Output | Format | Destination |
|---|---|---|
| Customer health score | Numeric (0-100) per customer | CRM dashboard |
| Churn alerts | Triggered notifications | Account owner |
| Expansion pipeline | Qualified opportunities | Sales pipeline |
| Advocacy assets | Case studies, testimonials | Marketing |
| Product feedback | Structured objection log | Product team |
Success Criteria
Quality Metrics
| Metric | Target | Measurement |
|---|---|---|
| Onboarding completion rate | >90% reach activation | Activation tracking |
| Health score accuracy | Health predicts renewal (r > 0.6) | Correlation analysis |
| Churn prediction | >70% of churns flagged 30+ days early | Alert review |
Performance Metrics
| Metric | Target | Timeframe |
|---|---|---|
| Net Revenue Retention | >110% | Annual |
| Gross churn rate | <5% monthly | Monthly |
| Time to activation | <14 days | Per customer |
| Expansion revenue | 20%+ of total revenue | Quarterly |
| NPS | >50 | Quarterly |
Failure Modes
| Failure | Symptom | Diagnosis | Solution |
|---|---|---|---|
| Onboarding dropout | Customer never activates | Setup too complex or value unclear | Simplify onboarding, show first value faster |
| Single-threaded | Only one contact, they leave | No relationship depth | Map stakeholders, engage multiple people |
| Value fade | Usage declines after initial spike | Novelty wore off, habits not formed | Coaching call, show metrics they care about |
| Expansion avoidance | Healthy customers but zero upsell | Not asking, or asking wrong people | Train on signal detection, build ask into QBR |
| Feedback black hole | Objections collected, nothing changes | No routing to product/engineering | Structured feedback → PRD pipeline |
Context
- Funnel Engineering — What feeds the lifecycle (won deals)
- Lead Generation — Referrals close the loop
- ICP Framework — Churn patterns refine ICP
- Sales CRM & RFP — The tool for tracking lifecycle
- Sales Work Chart — Human/AI split for customer success
- Process Optimisation — How to improve this workflow