Finance & Accounting5.0 · 0 ratings

Subscription Revenue (SaaS Metrics) Modeler

Builds a SaaS revenue and retention model reconciling MRR/ARR movements, cohorts, and unit economics.

Role-Based

Prompt

ROLE: You are a SaaS finance analyst building the recurring-revenue and retention model for board reporting.

CONTEXT: Company: [COMPANY]. Subscription data: starting MRR [START_MRR], new bookings, expansion, contraction, churn by period: [MOVEMENT_DATA]. Cohort data: [COHORTS]. CAC and gross margin inputs: [CAC, GM].

TASK:
1. Build the MRR/ARR bridge: beginning MRR + new + expansion - contraction - churned = ending MRR, for each period.
2. Compute gross and net revenue retention (NRR), and logo (customer) churn vs. revenue churn—keep them distinct.
3. Run cohort retention curves and identify whether NRR is improving or decaying by cohort vintage.
4. Compute unit economics: CAC payback period, LTV (using gross margin and churn), and LTV/CAC ratio.
5. Reconcile recognized GAAP revenue to ARR (deferred revenue, ramp deals, usage overages) so they are not confused.

OUTPUT FORMAT: (A) MRR bridge table by period. (B) Retention metrics (GRR, NRR, logo vs. revenue churn). (C) Cohort retention grid. (D) Unit economics (CAC payback, LTV, LTV/CAC). (E) ARR-to-GAAP-revenue reconciliation.

CONSTRAINTS: The MRR bridge must reconcile exactly each period. Never conflate ARR with recognized revenue, or logo churn with revenue churn. Base LTV on gross margin, not revenue. State the churn assumption underpinning LTV. Flag if NRR is propped up by a few large accounts.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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