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Movie Ticket Sales Forecast
Data Science and Analytics
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About
This dataset provides a detailed history of cinema ticket sales, allowing for advanced time series analysis and forecasting. Its primary purpose is to empower the cinema industry, much like sectors such as retail and banking, to leverage predictive modelling for significant cost reduction and improved return on investment (ROI). By forecasting sales, cinemas can optimise screening schedules across various locations, implement more effective market targeting, and refine pricing strategies. Furthermore, the historical sales data, combined with details on movies (e.g., cost, cast, crew) and project schedules, can assist producers in identifying high-performance cast and crew, and in planning future projects for better ROI. It also aids in strategically assigning screening locations to hot spots and high-demand areas.
Columns
- film_code: A unique identifier for each movie.
- cinema_code: A unique identifier for each cinema location.
- total_sales: The total revenue generated per screening time.
- tickets_sold: The total number of tickets sold for a given screening.
- tickets_out: The total number of tickets that were cancelled for a screening.
- show_time: The specific screening time within a day.
- occu_perc: The occupation percentage of the cinema, reflecting its capacity utilisation.
- ticket_price: The price of a single ticket at the time of the show.
- ticket_use: The total number of tickets that were actually used.
- capacity: The total available seating capacity of the cinema.
- date: The date when the event or screening occurred.
- month: The month of the event.
- quarter: The quarter of the event.
- day: The day of the event.
Distribution
The dataset is provided in a CSV format (cinemaTicket_Ref.csv) and is approximately 11.24 MB in size. It comprises 14 columns and contains 143,000 records, representing eight months of sales history. Two columns,
occu_perc and capacity, have 125 missing values each.Usage
This dataset is ideal for:
- Performing time series analysis and sales forecasting for individual cinemas.
- Optimising cinema screening strategies and schedules.
- Developing more effective market targeting and pricing models.
- Cinema clustering based on sales patterns.
- Aiding producers in selecting successful cast and crew and planning high-ROI projects.
- Identifying optimal cinema locations for specific screenings or new developments.
- Future applications could include movie genre recommendations and detailed cast and crew ratings, once more detailed movie information is integrated.
Coverage
The dataset covers approximately eight months of sales history from 2018, specifically from 21 February 2018 to 4 November 2018. It includes data from various cinemas with anonymised locations. The dataset currently lacks detailed movie attributes such as genre, full cast, and crew information; these details are planned for inclusion in future versions to enable more advanced recommendations.
License
CC BY-NC-SA 4.0
Who Can Use It
This dataset is valuable for:
- Cinema industry professionals seeking to enhance operational efficiency and profitability through data-driven decisions.
- Data scientists and analysts focused on time series forecasting, regression analysis, and predictive modelling.
- Marketing teams in the entertainment sector for targeted campaigns and pricing optimisation.
- Movie producers and studios for strategic planning related to film development and distribution.
- Researchers in arts and entertainment, specifically those interested in movies and television.
Dataset Name Suggestions
- Cinema Sales 2018
- Movie Ticket Sales Forecast
- Theatre Sales History
- Cinema Operations Data
- Ticket Sales Analytics
Attributes
Original Data Source: Movie Ticket Sales Forecast
QUALITY