SaaS Churn Analysis Skill

Deep-dive churn and retention analysis for SaaS businesses. Build cohort tables, calculate NRR/GRR, identify at-risk accounts, and produce investor-ready retention metrics with actionable recovery playbooks.

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When to Use This Skill

Trigger phrases:

• - "Why are customers churning?"
• "What's our retention rate?"
• "Build a cohort analysis"
• "Show me net revenue retention"
• "Which accounts are at risk of canceling?"
• "Investor wants to see our logo churn"
• "What's our gross/net dollar retention?"
• "Analyze our expansion vs contraction MRR"

NOT for:

• - Executing recovery outreach (emails, calls) — use CRM/email tools
• Billing changes, refunds, or cancellation processing — use billing platform
• General MRR tracking — use saas-metrics-dashboard or INLINECODE1
• Revenue forecasting — use INLINECODE2
• Customer success management — use a CS platform skill

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Core Churn Definitions

Logo Churn (Customer Churn)

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Revenue Churn

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Net Revenue Retention (NRR / NDR)

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NRR Benchmarks (SaaS industry):

NRR	Signal
>120%	Elite (enterprise, product-led)
110–120%

Strong — expansion > churn |
| 100–110% | Healthy |
| 90–100% | Adequate — watch churn trends |
| <90% | Red flag — structural problem |

Gross Revenue Retention (GRR)

GRR = (Beginning MRR - Contraction MRR - Churned MRR) / Beginning MRR × 100
     (excludes expansion — pure retention, no upsell credit)

Healthy GRR benchmarks:
  Enterprise SaaS: >90%
  Mid-market: >85%
  SMB SaaS: >75%

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Cohort Analysis

Building a Cohort Retention Table

Track customers by their acquisition month and measure % remaining in each subsequent month:

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Example cohort table output:
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Revenue Cohort (Dollar Retention)

Track MRR retained and expanded per cohort:

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Churn Curve Analysis

Identify when in the customer lifecycle churn peaks:

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Churn by tenure bucket:

def churn_by_tenure(subscriptions_df: pd.DataFrame) -> dict:
    """Calculate churn rate for different tenure buckets."""
    buckets = {
        '0-3mo': (0, 90),
        '3-6mo': (90, 180),
        '6-12mo': (180, 365),
        '12-24mo': (365, 730),
        '24mo+': (730, float('inf'))
    }
    
    results = {}
    for bucket_name, (min_days, max_days) in buckets.items():
        mask = (
            (subscriptions_df['tenure_days'] >= min_days) &
            (subscriptions_df['tenure_days'] < max_days)
        )
        bucket_df = subscriptions_df[mask]
        if len(bucket_df) == 0:
            continue
        churned = bucket_df[bucket_df['cancel_date'].notna()].shape[0]
        results[bucket_name] = {
            'total_customers': len(bucket_df),
            'churned': churned,
            'churn_rate_pct': round(churned / len(bucket_df) * 100, 1)
        }
    return results

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At-Risk Customer Identification

Churn Risk Scoring

Score each active customer by leading indicators:

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Early Warning Signals

Usage-based signals (product telemetry):
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Financial signals:

🔴 High risk:
  - Payment failure (retry in progress)
  - Requested invoice-based payment shift (budget freeze)
  - Contract not opened with 30 days to renewal

🟡 Medium risk:
  - Asked about pricing alternatives
  - Billing contact changed
  - Discount request submitted

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MRR Movement Analysis

MRR Bridge

Decompose monthly MRR change into components:

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Python MRR bridge calculation:
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SaaS Quick Ratio benchmarks:

Quick Ratio	Signal
>4	Elite growth efficiency
2–4

Healthy |
| 1–2 | Growing but inefficient — churn drag |
| <1 | Shrinking — churn exceeds new + expansion |

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Churn Recovery Playbooks

Playbook 1: Early Churn (Month 1-3)

Root cause: Failed onboarding, didn't reach first value moment

Diagnosis questions:
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Recovery actions:
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Playbook 2: Mid-Term Churn (Month 4-12)

Root cause: Value plateau, competitive evaluation, budget pressure

Diagnosis questions:
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Recovery actions by root cause:
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Playbook 3: Renewal-at-Risk (30-60 days to renewal)

Proactive renewal pipeline:

60 days out:
  □ Usage review: send personalized "Your results with [Product]" email
  □ Identify any open issues — resolve before renewal conversation

45 days out:
  □ QBR or check-in call — confirm value, surface upsell opportunity
  □ Flag to AE if NPS < 7 or usage declining

30 days out:
  □ Renewal proposal sent — include current plan + upsell option
  □ Executive sponsor confirmation (for accounts >$1k/mo)

14 days out:
  □ Follow-up if no response — switch to phone
  □ Escalate to manager if no reply

7 days out:
  □ Final decision call — accept reduced terms if needed to retain

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Output Formats

Investor-Ready Retention Summary

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CSV Export for Spreadsheets

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Step-by-Step Workflow

Full Churn Audit

Step 1: Data collection
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Step 2: Calculate headline metrics

• - Logo churn rate (monthly and annualized)
• Gross and net revenue retention
• Quick ratio
• Churn by tenure bucket

Step 3: Build cohort table

• - M0–M12 retention by acquisition cohort
• Identify best and worst cohorts — find what's different

Step 4: MRR bridge (last 6 months)

• - New vs expansion vs contraction vs churn
• Trend analysis: is churn improving or worsening?

Step 5: At-risk identification

• - Score all active customers by churn risk signals
• Prioritize by MRR at risk (highest first)
• Output: top 10 at-risk accounts with reasons

Step 6: Root cause analysis

• - What's driving churn? (onboarding failure, competition, budget, product gaps)
• Which segments have highest churn? (plan size, industry, use case, acquisition channel)

Step 7: Recommend playbook

• - Match root cause to recovery playbook
• Estimate MRR at stake if intervention succeeds (recovery potential)
• Prioritize actions by expected ROI

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Churn by Segment Analysis

Segment churn to find structural patterns:

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Key segments to analyze:

• - By plan tier (free trial → paid → enterprise)
• By acquisition channel (organic, paid, referral)
• By company size (SMB, mid-market, enterprise)
• By industry vertical
• By geographic region
• By sales rep / CSM (is one rep's book churning faster?)

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Integration Points

• - saas-metrics-dashboard — Display NRR, GRR, and churn rate KPIs in dashboard
• kpi-alert-system — Trigger alerts when monthly churn exceeds threshold
• startup-financial-model — Feed churn rate assumptions into revenue forecasts
• subscription-revenue-tracker — MRR bridge data source for churn calculations
• crypto-tax-agent — N/A (different domain)

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Key Formulas Cheat Sheet

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