The Integration Framework
Quality of earnings and customer due diligence answer complementary questions:
| Dimension | QoE Answer | CDD Answer | Integrated Insight |
|---|---|---|---|
| Revenue recurring? | Historical recurrence rate | Customer renewal intent | Forward-looking recurrence probability |
| Churn trend | Historical churn rate | Customer switching signals | Risk-adjusted churn projection |
| Revenue concentration | Top-account revenue share | Top-account satisfaction and switching risk | Concentration risk probability-weighted |
| Pricing trajectory | Historical pricing changes | Customer price sensitivity by segment | Pricing power boundary conditions |
| Expansion revenue | Historical upsell rate | Customer expansion intent | Credibility-weighted expansion forecast |
Integration Point 1: Churn Rate Adjustment
QoE finding: Historical gross churn is 8% annually.
CDD finding: 18% of 150 independently-recruited customers show Tier 1 or Tier 2 churn indicators (active evaluation, conditional retention, or switching intent).
Integration: Not all interview-signaled churn converts to actual churn. Apply a conversion factor based on industry benchmarks (typically 40-60% of signaled intent converts within 18 months). Adjusted forward churn estimate: 8% baseline + (18% signal x 50% conversion) = 17% annual churn risk.
Model impact: At $65M ARR, a 9% churn differential = $5.85M annual revenue at risk.
Integration Point 2: Revenue Concentration Risk
QoE finding: Top 5 customers represent 35% of ARR.
CDD finding: Interviews with representatives from top 5 accounts show mixed signals — 3 accounts expressing strong renewal intent, 1 expressing pricing concern, 1 actively evaluating alternatives.
Integration: Probability-weight the concentration risk. Instead of modeling top-5 retention at the portfolio average, assign account-specific probabilities based on interview evidence. If the at-risk account represents 8% of ARR, model a scenario where that account churns.
Integration Point 3: Pricing Power Validation
QoE finding: Company has implemented 8-12% annual price increases for 3 consecutive years.
CDD finding: Enterprise customers (>$100K ARR) show low price sensitivity. Mid-market customers ($20K-$100K) show high sensitivity — 28% cite price as primary concern, 14% have priced alternatives.
Integration: Future pricing power is segment-specific, not uniform. Model enterprise price increases at historical rates. Model mid-market increases at 50% of historical rate with elevated churn sensitivity. Segment-weighted pricing trajectory is lower than historical trend.
Integration Point 4: Expansion Revenue Credibility
QoE finding: Net revenue retention is 115% (indicating strong upsell/expansion).
CDD finding: 40% of customers identify specific expansion use cases. 25% express willingness to increase spend by 20%+ for planned features.
Integration: Customer-validated expansion potential supports the NRR assumption, but the addressable expansion base may be smaller than management projects. Model expansion at the customer-validated rate (40% of base with 20% expansion) rather than the management-projected rate.
Presenting the Integrated Model
The combined QoE + CDD model produces a revenue durability assessment that is both historically grounded and forward-looking:
- Base case: QoE-validated historical revenue quality
- Risk adjustment: CDD-identified churn, concentration, and pricing risks quantified
- Growth adjustment: CDD-validated expansion potential calibrated against QoE expansion history
- Revenue durability range: Low/mid/high scenarios with evidence backing each
This integrated model is the deliverable that investment committees need — a revenue projection that is backed by both financial history and independent customer evidence.
For the complete framework on structuring CDD evidence for IC presentations, see Presenting CDD Findings to Investment Committee.