This document discusses using analytics to predict the success of Bollywood movies. It notes that while India produces many films each year, few are commercial successes. It then outlines collecting data on factors like budget, genre, actors, release date for movies from 2013-2017 to develop regression models. The models show release date, production house, critics' ratings, tweets, and budget are significant predictors of total revenue and first-week box office collection. This could help the film industry make more informed decisions and reduce risks.

1. Analytics Based
Decision Making: A
case of Bollywood
Industry

2. Indian Entertainment Industry
India’s entertainment industry is growing rapidly.
The Media and Entertainment (M&E) companies of the world are taking
note of it.
With favorable demographics and rise in disposable incomes the
propensity to spend on leisure and entertainment is growing faster than
the economy itself.

3. Indian film Industry
The Indian film industry produces the maximum number of movies per year, higher than
any other country’s movie industry
However, very few movies taste commercial success.
With 3.3 billion tickets sold annually, India also has the highest number of theater
admissions.
With so much at stake and highly uncertain nature of returns, it is of commercial interest to
develop a model which can predict the success of a movie.

4. Bollywood Industry
Indian Hindi Movie industry popularly known as Bollywood has reached staggering
proportions in terms of volume of business, employment, movies produced (more
than 100 in a year) and its reach (more than 100 countries worldwide).
Movies have been described as experience goods with very less shelf life, therefore,
it is difficult to forecast the demand for a movie.
There are number of parameters that may influence success of a movie like – time
of its release, marketing, lead actors, director, producer, writer, music director –
being some of the factors.

5. Analytics Adoption in Film Industry
• Data scientist may develop the models and
mechanisms to predict reliably the ranking
and / or box office collections of a movie &
can help de-risk the business significantly
and increase average returns.
• Various stakeholders such as actors,
financiers, directors etc. can use these
predictions to make more informed
decisions.
Source: Mishra & Sharma(2016)

6. Data
Analytics
Efficient
Film
Making
Process
Increase
Revenue
Reduce
the Risk of
Failure
Consumer
Engageme
nt
Marketing:
Better
Decision
Making
Behavioral
Modelling
Data Analytics in Film Industry
In a BBC article, film director Karan Johar is
quoted as saying only 45 of the 300 million
(India’s middle class) is reached by the movie
industry. A vested effort in using data
analytics to improve India’s film industry
could be the way to reach the remaining 255
million. By making the filmmaking process
more efficient, more profitable, more
relatable and less risky, a great return on
huge investments is guaranteed with data
analytics.

7. To predict success of a Movie
Objectives of the Study
Determine the key variables
that results in predicting the
success of a Bollywood
movie
Determining whether budget
is an important factor for the
success of a Bollywood
movie.
Create a model to
predict the success of a
Bollywood movie.

8. Stop
Model Satisfies
Perform diagnostic analysis
Estimate the parameters
Apply Regression Analysis
Explore data
Data Preprocessing
Collect data
Yes
No
Methodology

9. Data Collection
• Secondary data for four years (2013-
2017) were collected from reliable
sources- IMDB, Bollywood Hungama,
Wogma
• Dependent Variables
1. Total Revenue
2. First week box office collection

10. Independent
Variables
Release date
Budget of
Movie in
Crores
Genre
Lead Actor /
Actress
No. of movies
made by
Director
Sequel
Production
House
Critic’s ratings IMDB ratings
Bollywood
Hungama
Ratings
Social Media

11. Data
Preprocessing
Phase
Release Date: festive, non-festive
Genre: action/adventure, children/family, comedy, drama, horror,
mystery/suspense, and Others
Lead Actor / Actress: Debut, Star, Super Star
Production House: Yash-Raj films, Dharma productions, UTV
motion pictures, Balaji films,Eros international,Red Chillies
Entertainment ,Foxstar Studios, Reliance Entertainiment,
Nadiadwala Grandson Entertainment and others

12. Statistics
• The sampled movies earned
average revenue of Rs 49.24 crores.
• The mean of the first week box
office collection was Rs 30.19
crores, showing that the
performance of the first week
accounted for approximately
61.31% of the total box office
revenue.
• The average budget of the sampled
movies was Rs 35.66 crores which
accounted for approximately
72.42% of the average box office
revenue.
Action
Family
Comedy
Drama
Horror
Mystery
Others
CHART TITLE

13. Summary of
regression
analysis
Independent Variable Total Revenue First Week Box Office Collection
Dummy Release date 42.363** 19.191**
Yashraj 24.199*
Tweets 15.434* 8.740*
Critics’ Rating 8.274** 4.919**
Bollywood Hungama 3.312*
Budget 0.955** 0.697**
Dharma 29.133**
N 192 192
R 0.821 0.894
R2 0.674 0.798
Adjusted R2 0.621 0.765
F 12.569 24.053

14. Conclusion
• This research study attempts to propose models for
measuring the success of the Bollywood movies.
• Two models were proposed to predict the box office
collection of first week and total box office collection.
• The key contribution of this research is to give
direction to the film maker regarding the significant
drivers of the success of the movie.

15. Thanks
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