fa-unit-economics-model

name	fa-unit-economics-model
description	Provides the single shared, versioned unit-economics model for consumer one-off / in-app-purchase products, created in Discovery and re-run at every gate. Covers inputs (CPI, install->payer conversion, ARPPU, repeat purchase, ad ARPDAU), the gross-to-net stack (store commission, refunds, chargebacks, fraud, tax), LTV by segment, payback window, and a cashflow/working-capital check. Use whenever product economics must be initialized, updated with measured data, or evaluated at a gate.
license	MIT

Gaia Unit Economics Model

Scope and when to use

Use to maintain ONE canonical, versioned model that every stage reads and updates. No stage re-derives economics from scratch. Premium LTV is realized at install (finite, no tail); IAP LTV is back-loaded and whale-driven.

Use when:

• Discovery must initialize model v0 (all inputs flagged as assumptions)
• a specialist returns measured inputs (CPI, WTP, ARPPU, retention) to fold in
• a gate needs the current net-of-fee LTV:CAC, payback, and cashflow read

Do not use when:

• the product is B2B SaaS (different LTV/churn math)

Required inputs

• acquisition: CPI per source/geo, organic share, blended CAC
• conversion: install→payer rate, repeat-purchase rate, time-to-first-purchase
• value: ARPPU (lifetime/per-cohort, NOT monthly), ad ARPDAU, segment mix
• haircuts: store commission (15/30%), refund/chargeback %, fraud %, indirect tax %
• timing: retention curve (D1/D7/D30+), paying lifetime, payout lag

Owned outputs

• net blended LTV per install (IAP net-of-fee + ad net-of-rev-share)
• LTV:CAC ratio and payback window
• cashflow gap to break-even and required runway
• a version stamp (v0..vN) and a changelog of which inputs became measured

Core workflow

1. Initialize v0 with assumptions; label every input assumption-vs-measured.
2. Compute gross revenue per payer and per install from conversion × ARPPU.
3. Apply the gross-to-net stack: commission, refunds, chargebacks, fraud, tax.
4. Add the ad component (eCPM × fill × sessions, net of network rev-share) for hybrid titles.
5. Compute net LTV per install, LTV:CAC, and payback window by source.
6. Run conservative/base/optimistic cases and sensitivity on install volume and conversion × ARPPU.
7. Run the cashflow check: payout lag vs CAC timing; compute the cash gap to break-even.
8. Re-version whenever a measured input replaces an assumption; keep the changelog.

Segments

• non-payers (monetize via ads), minnows, dolphins, whales (top decile drives most IAP).
• treat whale concentration as a fragility risk, not a static fact.

Anti-patterns

• do not quote gross revenue at a gate
• do not use monthly ARPPU or MRR framing (that is subscription math)
• do not ignore the payout-lag cash gap
• do not freeze assumptions as if measured

Handoff and downstream impact

• give the money gate the net-of-fee LTV:CAC, payback, and cash gap
• give specialists the current version and which inputs still need measuring

Completion checklist

• every input is labeled assumption or measured
• net-of-fee LTV:CAC, payback, and cash gap are current
• the version and changelog are updated

References

• Model schema
• Money gate