This project focuse on analyzing café sales data to identify the most popular product combinations and optimize combo offers. Additionally, a user-based recommendation system has been developed to suggest café products tailored to customer preferences, enhancing the customer experience and driving sales.
- What are the most popular product combinations purchased by customers?
- How can we optimize combo offers to increase sales?
- How can we recommend products to customers based on their preferences?
The analysis is based on sales data from Blooming Café located in jeddah.
The project follows the standard steps of a data analysis workflow:
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Defining the problem statement: Identifying key business questions and goals.
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Preparing data: Cleaning and organizing the dataset for analysis.
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Conducting exploratory data analysis (EDA): Identifying patterns, trends, and correlations in the data.
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Developing a recommendation system: Building a user-based recommendation model using customer preferences.
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Visualizing and communicating results: Presenting insights and findings.