AI Prompt to Forecast Quarterly Revenue After a Price-Hike

ChatGPT-ready prompt to forecast quarterly volume, revenue after price increases—returns assumptions, scenario comparisons and actionable recs for finance/ops.

September 25, 2025

For companies weighing a price increase, today’s prompt provides a fast, data-driven blueprint to forecast quarterly volume and revenue; it’s ideal for finance, ops, or product managers and can be repurposed for investor decks, pricing committees, or scenario playbooks.

Today's Prompt:

You are to analyze the effects of a proposed {PERCENTAGE_PRICE_INCREASE}% price increase on the quarterly sales volume and revenue of a specialty coffee brand. The analysis should utilize the provided historical sales data, considering prior sales volumes, prices, and any notable seasonal or market trends. The goal is to simulate how sales volume may change in response to the price increase (using reasonable elasticity assumptions or extrapolations if needed) and then calculate the projected revenue across each quarter. Conclude by summarizing the potential business outcomes of this price change.

Details and Guidance: 

- Use the attached historical sales data (provided below) to understand baseline sales volumes, historical pricing, and revenue by quarter.

- Apply a {PERCENTAGE_PRICE_INCREASE}% price increase to simulate new scenarios.

- Model the likely change in sales volume based on the impact of the price increase. If explicit price elasticity is not provided, use reasonable industry-standard assumptions for specialty coffee or infer from past data trends.

- Clearly calculate and compare projected revenue and sales volumes by quarter before and after the price increase.

- Note any limitations in the analysis, such as unaccounted external factors or missing data.

Output Structure: 

1. Executive Summary: High-level overview of key findings and projected business impacts.

2. Assumptions: State all key assumptions, especially price elasticity or other modeling choices.

3. Quarterly Comparison Table: Side-by-side table of historical vs. projected sales volume and revenue for each quarter.

4. Analysis: Narrative discussion of how the price increase affects volume, revenue, and overall business outlook.

5. Recommendations (Optional): Any actionable insights or next steps for the coffee brand.

Template Variables: 

- {PERCENTAGE_PRICE_INCREASE} – The percent increase in price to model (e.g., 15).

*If you have it, add {ADDITIONAL_BUSINESS_CONTEXT} – Any other relevant business context, constraints, or goals (optional).

Why we like this prompt:

1. The prompt is explicit in its communication by clearly stating the core task—analyzing and simulating the effects of a specific percentage price increase on both sales volume and revenue.

2. It provides relevant and helpful details, such as utilizing historical sales data and encouraging the consideration of price elasticity, seasonality, and market trends, which are critical for an accurate and context-aware simulation.

3. The output requirements are precisely specified, outlining a structured, multi-part response (executive summary, assumptions, comparison table, analysis, and optional recommendations) which guides the AI toward a consistently formatted and comprehensive report.

4. The goals are articulated with clarity, emphasizing both the simulation of sales dynamics and the summarization of potential business outcomes, ensuring the AI fully understands the intent and expected depth of the analysis.

5. Template variables and data attachment instructions make the prompt reusable and adaptable, while also ensuring the AI receives complete and relevant context to perform meaningful, data-driven analysis.

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