About Prompt
- Prompt Type – Dynamic
- Prompt Platform – ChatGPT, Grok, Deepseek, Gemini, Copilot, Midjourney, Meta AI and more
- Niche – Market Analytics
- Language – English
- Category – Agri-Business Support
- Prompt Title – AI Prompt for Forecasting Market Prices of Agricultural Products
Prompt Details
**Prompt Type:** Dynamic
**Target Audience:** Agri-Business Support Professionals
**AI Platform Compatibility:** Designed for broad compatibility across various AI platforms including Large Language Models (LLMs), Machine Learning APIs, and specialized forecasting tools.
**Prompt Structure:**
This prompt uses a structured approach to provide the AI with the necessary information and guide its analysis. Users should replace the bracketed placeholders with their specific details.
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## Task: Forecast the market price of [Specific Agricultural Product] in [Target Market/Region]
**1. Product Specification:**
* Name: [e.g., Red Delicious Apples, Grade A]
* Variety/Breed: [e.g., Starkrimson, Holstein Friesian]
* Quality Standards: [e.g., USDA Grade A, Organic Certified, Fair Trade]
* Unit of Measurement: [e.g., USD per bushel, EUR per kg]
**2. Market/Region Specification:**
* Geographic Area: [e.g., California, USA; EU; Global]
* Market Type: [e.g., Wholesale, Retail, Futures Market]
**3. Timeframe:**
* Forecast Horizon: [e.g., Next 7 days, Next 3 months, Next year]
* Frequency: [e.g., Daily, Weekly, Monthly]
**4. Data Inputs:**
* **Historical Price Data:** Provide a link to a CSV or JSON file containing historical price data for the specified product in the target market. Include date, price, and optionally volume traded. [e.g., URL to CSV, Google Sheets link] If no direct link is available, describe the available historical data and its accessibility.
* **Relevant Factors (Optional but Highly Recommended):** Include data related to factors influencing price, such as:
* **Production Data:** [e.g., Planted acreage, expected yield, historical production data]
* **Weather Data:** [e.g., Temperature, rainfall, historical weather patterns]
* **Demand Factors:** [e.g., Consumer trends, export/import data, economic indicators]
* **Supply Chain Disruptions:** [e.g., Transportation costs, logistical challenges, storage capacity]
* **Policy and Regulations:** [e.g., Trade agreements, subsidies, import/export restrictions]
* **Market Events:** [e.g., News related to the product, industry conferences, disease outbreaks]
For each factor, provide data sources if possible (e.g., URLs, file uploads, API endpoints). Describe the data format and its relevance to the price forecast.
**5. Forecast Output:**
* Desired output format: [e.g., Table, chart, JSON]
* Include:
* Predicted price values for the specified timeframe and frequency.
* Confidence interval/range for the prediction (if available).
* Key factors influencing the predicted price movements.
* Potential risks and uncertainties associated with the forecast.
**6. Additional Instructions (Optional):**
* Specify any specific models or algorithms to be used (e.g., ARIMA, time series analysis, machine learning models).
* Indicate preferences for specific analytical approaches (e.g., focus on seasonality, trend analysis, volatility estimation).
* Specify any constraints or assumptions to be considered in the forecast (e.g., no major policy changes, stable weather conditions).
**Example:**
## Task: Forecast the market price of Red Delicious Apples, Grade A in the Wholesale Market of Washington State, USA
**1. Product Specification:** … (fill in details)
… (fill in the rest of the sections)
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**Explanation of Dynamic Elements:**
This prompt is designed to be dynamic by using placeholders. Users can easily customize the prompt by replacing the bracketed information with their specific requirements. This allows for flexible and tailored forecasting across different products, markets, and timeframes.
**Best Practices:**
* **Clarity and Specificity:** The prompt is structured to elicit specific information from the user, minimizing ambiguity and ensuring the AI understands the task.
* **Data-Driven Approach:** Emphasis is placed on providing relevant data inputs to enable accurate forecasting.
* **Contextual Information:** The prompt encourages users to provide context through relevant factors, improving the quality of the forecast.
* **Output Specification:** Clear instructions on the desired output format ensure the results are presented in a usable manner.
* **Flexibility:** The dynamic structure accommodates various scenarios and allows for customization based on user needs.
By using this comprehensive and adaptable prompt, agri-business professionals can leverage AI to generate valuable market price forecasts, supporting informed decision-making and optimizing business strategies.