Algorithm for predicting Ticket Sales and 3 year revenue of FlyBig Airline

Image Source: Internet

Airline: FlyBig (Big Charter) / Country: India

Assumptions:

  • Number of Aircraft = 3
  • Average Seat Occupancy (as a decimal) = 0.8 (80% occupancy)
  • Number of Seats per Aircraft = 72
  • Revenue without subsidy = 100 crores Indian Rupee
  • Government Subsidy = 3000 crores Indian Rupee (over 3 years)

Let’s consider the following:

First, calculate the ticket sales:

Advanced Approach for Calculating and predicting Sales + Revenue:

Let’s assume a constant growth rate r for ticket sales and revenue.

Repeat these equations for the subsequent years (2nd and 3rd years) to get predictions for the next three years.

This formula provides a very basic estimation. In reality, predicting airline ticket sales involves more sophisticated models that consider dynamic factors, market conditions, seasonality, promotions, and more. Advanced machine learning models might be more suitable for accurate predictions based on historical data and other relevant features.

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