---
title: "Revenue Forecast Template"
description: "Build detailed revenue forecasts with growth modeling, seasonal adjustments, and multi-stream projections for any business"
slug: "finance/revenue-forecast-template"
tags: ["finance", "revenue-forecast", "financial-planning", "business", "forecasting"]
author: "AgentDock Team"
agentdockUrl: "https://agentdock.ai/prompt-library/finance/revenue-forecast-template"
chatgptDemoUrl: "https://chatgpt.com/share/69a69414-790c-800a-8f85-0f77d926182e"
claudeDemoUrl: "https://claude.ai/share/1b36b356-ef94-4eb0-be2d-874e7928730e"
perplexityDemoUrl: "https://www.perplexity.ai/search/revenue-forecast-template-belo-wE7uNYluQcCqQO.Hbfsn2Q"
qwenDemoUrl: "https://chat.qwen.ai/s/t_3da70ab9-9689-45e9-8b52-d65d8be57c10?fev=0.2.9"
---

# Revenue Forecast Template

You are a financial planning and analysis professional who has built revenue forecasts for companies ranging from pre-revenue startups to established enterprises with complex, multi-stream income models. You understand that a revenue forecast is not just a projection of numbers but a structured hypothesis about how a business will generate income over time. You know how to translate market conditions, historical patterns, and pricing strategies into realistic projections that stakeholders can trust and act on. You present financial data clearly enough for non-finance executives to follow while maintaining the rigor that CFOs and investors expect.

I need you to create a detailed revenue forecast for [BUSINESS_NAME] operating in the [INDUSTRY] industry.

The forecast should cover a [FORECAST_PERIOD:select:Monthly,Quarterly,Annual] timeline extending [FORECAST_HORIZON:select:3 months,6 months,12 months,24 months,36 months,5 years] into the future.

The company's primary revenue streams are: [REVENUE_STREAMS]. For each stream, model the revenue separately so we can see which lines of business are growing, flat, or declining.

The pricing model is [PRICING_MODEL:select:subscription,one-time,usage-based,freemium,hybrid]. This will shape how revenue accumulates over each period. For subscription models, account for new customer additions, churn, and expansion revenue. For one-time models, focus on unit sales volume and average transaction value. For usage-based models, project consumption trends and per-unit pricing. For hybrid models, break out recurring and transactional components separately.

Historical revenue data for the most recent periods is: [HISTORICAL_REVENUE]. Use this data to establish baseline growth rates and identify any existing trends or patterns.

Growth assumptions to incorporate: [GROWTH_ASSUMPTIONS]. These might include planned product launches, market expansion, sales team additions, marketing spend increases, or expected competitive changes.

Known seasonal patterns or cyclical factors: [SEASONALITY?]. If seasonal data is provided, apply monthly or quarterly adjustment factors to reflect demand fluctuations throughout the year.

Current market conditions and external factors: [MARKET_CONDITIONS?]. Consider how industry trends, economic environment, regulatory changes, or competitive dynamics might influence revenue trajectory.

Currency for the forecast: [CURRENCY?].

Create a complete revenue forecast document. Open with a one-paragraph executive summary stating projected total revenue for the full horizon, the implied growth rate versus the most recent historical period, and the two or three biggest assumptions driving the numbers.

Build the detailed forecast as a table with time periods as columns and revenue streams as rows. Include a total revenue row summing all streams and a growth rate row showing period-over-period percentage change.

After the table, provide a revenue bridge analysis that breaks down how revenue moves from the current baseline to the forecasted end point. Quantify components like organic growth from existing customers, new customer acquisition, pricing changes, new product launches, and expected losses from churn or market contraction.

Include a sensitivity analysis with three scenarios. The base case uses the assumptions provided. The upside case increases growth drivers by 15 to 25 percent. The downside case reduces them by the same range and raises churn rates. Present a comparison table showing total revenue at the end of the horizon for each scenario.

Add an assumptions section documenting every input: growth rate per stream, churn rate, average deal size, and any external market growth rates used. If seasonal data was provided, show the monthly or quarterly index factors applied and which periods run above or below average.

Conclude with three to five risks that could cause results to differ from the forecast. For each, note direction of impact, estimated magnitude, and what leading indicator to monitor. Format all tables with consistent decimal places and clear headers so the document works for investor presentations, board packages, loan applications, and internal planning.

