This repository contains code for conducting a market analysis of the cinema industry, specifically focused on the viability of introducing an original language cinema in Milan, Italy. The analysis is based on a questionnaire survey conducted among cinema-goers in Milan. Problem Statement
The goal of this analysis is to determine whether there is sufficient demand and interest in original language movies in Milan to support the establishment of an original language cinema. The analysis aims to provide insights into customer preferences, habits, and motivations when it comes to cinema selection, as well as identify potential customer segments that would be most receptive to the concept of an original language cinema. The conclusion is done through customer segmentation using Kmeans Clustering.
The dataset used for this analysis consists of responses from the questionnaire survey conducted among cinema-goers in Milan. The survey collected information on various aspects, including cinema habits, preferences for original language movies, personality traits, demographics, and more. Analysis Plan
Perform data cleaning and handle missing values, if any. Prepare the dataset for analysis, including data transformation and feature engineering, as required.
Exploratory Data Analysis: Conduct univariate analysis to explore the distribution and summary statistics of the variables. Perform bivariate analysis to examine the relationships between variables and identify any notable patterns or trends.
Cinema Habit Analysis: Analyze cinema habits of the respondents, including frequency of cinema visits, factors influencing cinema selection, and willingness to spend on movies. Identify key motivators and demotivators for cinema-goers in Milan.
Original Language Movie Analysis: Evaluate the interest and preferences for original language movies among the respondents. Assess the frequency of watching original language movies in Milan and identify the factors influencing the choice of movie version (original language, dubbed, or no preference).
Respondent Personality Traits Analysis: Analyze the personality traits of the respondents, including traits like openness, curiosity, sociability, and spontaneity. Investigate how these personality traits relate to cinema preferences and behaviors.
Demand Segmentation: Conduct Principal Component Analysis (PCA) to reduce the dimensionality of the dataset and identify underlying factors that drive cinema preferences. Perform cluster analysis to segment the respondents into distinct groups based on their cinema preferences, motivations, and demographics. Describe and analyze each cluster to understand their characteristics and preferences.
Managerial Implications: Draw insights from the analysis to provide managerial implications for introducing an original language cinema in Milan. Provide recommendations on target customer segments, marketing strategies, movie packages, customer experience enhancements, and potential collaborations with universities.
Conclusion
This analysis aims to provide valuable insights into the viability of introducing an original language cinema in Milan, Italy. The findings from the questionnaire survey and subsequent analysis will help inform decision-making processes related to target customer segments, marketing strategies, movie offerings, and customer experience enhancements.