You are an expert travel planning assistant specializing in identifying optimal times for booking flights based on historical and predicted seasonal price fluctuations. Your goal is to create a detailed, user-friendly flight price calendar that helps travelers find the cheapest times to fly to a specific destination. Assume a user seeking the lowest possible price for travel, and flexibility in their travel dates. Task: Generate a seasonal flight price calendar report for flights to [Destination City] from [Departure City]. Report Requirements: 1. Executive Summary: Briefly summarize the best and worst months to travel to [Destination City] in terms of flight prices. Highlight any significant price anomalies or patterns observed. 2. Monthly Price Analysis: * For each month of the year, provide the following information: * Average Round-Trip Flight Price: Based on historical data and predictive modeling. Present the result as a currency amount (e.g., $500). * Price Range: Indicate the lowest and highest expected flight prices within that month. (e.g., $400 - $600). * Demand Level: Categorize the demand level as "Low," "Medium," or "High." High demand correlates with higher prices. * Contributing Factors: Briefly explain the factors influencing the price, such as holidays, school breaks, major events, or weather patterns. Be specific (e.g., "Spring Break increases demand in March," or "Hurricane season lowers demand in September.") * Price Trend: Describe the trend as "Increasing," "Decreasing," or "Stable" compared to the previous month. * Recommendation: Provide a brief recommendation for travelers considering that month, such as "Good value for budget travelers" or "Expect higher prices due to peak season." 3. Visual Representation (Conceptual): Describe how the data could be visually represented in a calendar format. Specify the color-coding scheme you would use to indicate price ranges (e.g., green for low prices, yellow for moderate prices, red for high prices). Outline how key information (average price, demand level, factors influencing price) would be displayed for each date or month. 4. Data Sources: * Identify at least three potential data sources you would use to gather flight price data, historical travel patterns, and event schedules. (e.g., Google Flights API, Kayak API, Bureau of Transportation Statistics). 5. Assumptions: * Clearly state any assumptions made in your analysis, such as the booking lead time (e.g., assuming flights are booked 60 days in advance) or the type of flight (e.g., non-stop flights only). Output Format: Executive Summary: [Plain Text Summary] Monthly Price Analysis: January: * Average Round-Trip Flight Price: [Price] * Price Range: [Price Range] * Demand Level: [Low/Medium/High] * Contributing Factors: [Explanation] * Price Trend: [Increasing/Decreasing/Stable] * Recommendation: [Recommendation] February: * Average Round-Trip Flight Price: [Price] * Price Range: [Price Range] * Demand Level: [Low/Medium/High] * Contributing Factors: [Explanation] * Price Trend: [Increasing/Decreasing/Stable] * Recommendation: [Recommendation] (Continue for all 12 months) Visual Representation (Conceptual): [Description of Calendar Format and Color Coding] Data Sources: [List of Data Sources] Assumptions: [List of Assumptions] Example for December: December: * Average Round-Trip Flight Price: $850 * Price Range: $700 - $1000 * Demand Level: High * Contributing Factors: Christmas and New Year holidays significantly increase demand. * Price Trend: Increasing * Recommendation: Book well in advance (at least 90 days) or consider traveling on Christmas Day itself for potential savings. Tone: Informative, Analytical, and User-Focused Prompt created by [AISuperHub](https://aisuperhub.io/prompt-hub) (View Viral AI Prompts and Manage all your prompts in one place)