Use case 01
When you need to estimate future values for a key metric.
Data AnalystForecastingIntermediateTemplate
Scenario Planning Forecast AI Prompt
Scenario Planning Forecast is a intermediate template for forecasting. This prompt focuses on projecting future outcomes based on historical patterns in the data. It guides the AI to compare methods, state assumptions, and present forecasts with appropriate context and uncertainty. Use it when you need forward-looking estimates for planning, monitoring, or scenario analysis. It is structured as a reusable template, so placeholders can be filled in for a specific table, metric, or business context. The requested output can include more technical detail, prioritization, and interpretation while still staying practical.
Prompt text
Generate a 3-scenario forecast for {{metric}} over the next {{forecast_horizon}}:
Scenario definitions:
- Pessimistic: assume {{pessimistic_assumption}} (e.g. growth slows to half the current rate, churn increases by 20%)
- Base case: continue current trend with normal seasonality
- Optimistic: assume {{optimistic_assumption}} (e.g. growth accelerates by 50%, a new product launch captures additional market)
For each scenario:
- Plot the forecast line with a distinct color
- Show the projected value at 30, 60, and 90 days
- State the key assumption driving each scenario
Highlight the range between pessimistic and optimistic as a shaded uncertainty band.
Add a plain-English paragraph explaining what would need to be true for the optimistic scenario to materialize.When to use this prompt
Use case 02
When planning targets, capacity, budgets, or scenario ranges.
Use case 03
When comparing simple and advanced forecasting approaches on the same data.
Use case 04
When you need forecast assumptions, uncertainty, and commentary alongside the numbers.
What the AI should return
The AI should return forecast outputs in a structured format that includes method, assumptions, projected values, and a short interpretation of the trend. It should compare models or scenarios when requested, and include accuracy metrics or uncertainty intervals where possible. Charts and tables should support the explanation rather than replace it. The final answer should help the user understand both the forecast itself and how much confidence to place in it.
How to use this prompt
1
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
2
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
3
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
4
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Forecasting.
Frequently asked questions
What does the Scenario Planning Forecast prompt do?+
It gives you a structured forecasting starting point for data analyst work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for data analyst workflows and marked as intermediate, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Scenario Planning Forecast is a template. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Demand Forecast with External Factors, Full Forecast Benchmark Chain, Growth Rate Analysis.