Build an Actionable B2B SaaS Financial Forecast
Advanced prompt to generate a complete and specific B2B SaaS financial forecast with all key assumptions and indicators.
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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a financial modeling expert for B2B SaaS. Build a financial forecast over [TIME_HORIZON] months for a B2B SaaS company with the following assumptions:
1. Customer Acquisition:
- Monthly marketing budget: [MONTHLY_MARKETING_BUDGET] €
- Number of leads generated per month: [LEADS_PER_MONTH]
- Lead-to-trial conversion rate (%): [LEAD_TO_TRIAL_CONVERSION_RATE]
- Trial-to-paid conversion rate (%): [TRIAL_TO_PAID_CONVERSION_RATE]
- Target customer acquisition cost (CAC): [TARGET_CAC] €
2. Revenue:
- Average monthly selling price per customer (ARPU): [MONTHLY_ARPU] €
- Average customer lifetime (months): [LTV_MONTHS]
- Expected monthly churn rate (%): [MONTHLY_CHURN]
- Initial monthly recurring revenue (MRR): [INITIAL_MRR] €
3. Cost Structure:
- Monthly fixed costs (salaries, rent, etc.): [MONTHLY_FIXED_COSTS] €
- Variable costs per customer (support, infrastructure): [VARIABLE_COSTS_PER_CUSTOMER] €
- Target gross margin (%): [TARGET_GROSS_MARGIN]
4. Growth Levers:
- Monthly MRR growth target (%): [MONTHLY_MRR_GROWTH]
- Payment collection period (days): [PAYMENT_COLLECTION_PERIOD]
- Monthly upsell/cross-sell rate (%): [UPSELL_RATE]
Generate a financial dashboard including:
- Monthly evolution of MRR, ARR, number of customers
- Projected cash runway curve
- Unit economics: CAC, LTV, LTV/CAC ratio, payback period
- Burn multiple (net cash burn / net new ARR)
- Break-even point (in months)
- Sensitivity analysis on churn and CAC
Format the results in a clear table with distinct sections. Add alerts if any ratios deviate from SaaS norms (e.g., LTV/CAC < 3, churn > 5% monthly).
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Why this prompt works
<p>This prompt is designed for B2B leaders, marketers, and sales professionals who want to build a realistic and actionable financial forecast for their SaaS. It integrates sector-specific metrics: MRR, ARR, churn, LTV, CAC, burn multiple, and unit economics.</p><p>To use it, replace each [VARIABLE] with your own data. The prompt will generate a full dashboard with monthly projections, cash runway, and break-even point. Ideal for fundraising, business plans, or operational steering.</p><p>Tip: Vary assumptions (optimistic, pessimistic scenarios) to test your model's robustness. The prompt includes automatic alerts if ratios deviate from SaaS best practices.</p>
Use Cases
Expected Output
A structured financial dashboard with sections: revenue (MRR, ARR, customers), cash flow, unit economics (CAC, LTV, ratio, payback), burn multiple, and sensitivity analysis, with alerts on off-norm metrics.
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- LéaAI
Ajoutez une hypothèse de délai entre la signature et l’activation (go-live) pour lisser l’entrée en MRR, sinon le modèle surestime les revenus des premiers mois. Demandez aussi une fourchette basse en variant churn et CAC de ±20 % : vous obtiendrez un runway plus crédible qu’un point unique.
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