- The short — how value is actually created
- Cohort engine & repeat usage
- Take rate, incentives & contribution margin
- LTV/CAC math & payback months
- Sensitivity table & valuation bridge
- Red flags & diligence asks
The short
- Core: This is a frequency + trust engine. Cohort health—not GMV headlines—drives durability.
- North star: Contribution Margin 2 (after variable ops and CX) turning sustainably positive on mature cohorts.
- Cash: OCF/EBITDA trending to > 0.8 with low receivable days is the de-risking tell.
Cohort engine & repeat usage
What to read
- Monthly active users by vintage; 12/18/24-month retention curves.
- Service-mix drift: one-off high-ticket vs repeat low-ticket categories.
- Professional supply: activation, utilization, churn, NPS.
Operator cues
- Drive habit-forming categories (cleaning, grooming) to lift repeat frequency.
- Cap incentives once a cohort’s repeat rate stabilizes; avoid rent-seeking “promo loops”.
Take rate, incentives & contribution margin
| Component | Illustrative range | Levers | Investor read |
|---|---|---|---|
| Gross take rate | 18–24% | Category mix, bundles, surge pricing | Higher in repeat categories with lower cancellations |
| Incentives/subsidies | 2–6% | Promo discipline, LTV gating | Watch tapering in mature cohorts |
| Variable ops (CX, ops, payments) | 5–8% | Automation, payment costs | Scale should compress per-order cost |
| Contribution Margin 2 | 4–9% | Mix & discipline | North-star metric |
Note Exact figures depend on category/market maturity; use ranges to stress-test the bridge.
LTV/CAC math & payback
- LTV: Avg order value × orders per user per year × CM2 × years of relationship (discounted).
- CAC: Performance + brand + referral costs attributable to first purchase.
- Payback months: CAC ÷ (CM2 per user per month).
Guardrail Aim for payback < 12 months in mature cities; < 18 months in build-out markets.
Sensitivity table (illustrative)
| Orders/user/yr | Avg order (₹) | CM2 % | LTV (₹) | CAC (₹) | Payback (months) |
|---|---|---|---|---|---|
| 3.0 | 900 | 5% | 1,215 | 900 | ~8–10 |
| 3.5 | 1,000 | 6% | 1,890 | 1,050 | ~7–9 |
| 4.0 | 1,100 | 7% | 3,080 | 1,200 | ~6–8 |
Method: Discount factor simplified; purpose is directional sizing for diligence, not a valuation opinion.
Valuation bridge (illustrative)
| Step | Metric | Illustrative | Comment |
|---|---|---|---|
| 1 | GMV | ₹X,XXX cr | Scale proxy; not a profit driver alone |
| 2 | Net revenue (take-rate) | 20% of GMV | Category mix critical |
| 3 | CM2 | 6–8% of GMV | Automation & cancellations |
| 4 | Adj. EBITDA | Breakeven → low double digits | City maturity curve |
| 5 | EV/Revenue | 3–5× | Asset-light services range |
Red flags & diligence asks
Red flags
- Promo-led growth without cohort stickiness.
- High cancellations/refunds in new categories.
- Receivable days rising; negative OCF despite EBITDA optics.
Diligence asks
- Cohort tables by city/month with CM2, repeat, CAC, and payback.
- Pro supply health: utilization, churn, NPS, training funnels.
- Complaint rates and SLA breaches by category.
Investor playbook
- Anchor quality and float trump GMP chatter.
- Size allocations to free float and lock-in schedules.
- Track post-listing disclosures on CM2 and city-maturity mix each quarter.