Restaurant C is struggling to maintain profit margins and growth at its Asian food location. Sales data shows differences between dine-in and delivery customers. The current menu and offerings may be inadequate. Data Vision was hired to uncover consumption patterns and product relationships to provide insights to improve practices and increase profits.
- Business Understanding - Identified business objectives, success criteria, assessed current situation, and defined data mining goals
- Data Understanding - Collected initial data, described and explored it to become familiar with it
- Data Preparation - Cleaned data, integrated external data, formatted it, and created new features
- Modeling - Selected Apriori algorithm to create a market basket analysis model
- Evaluation - Evaluated model results against business objectives and data mining goals
- Deployment - Provided recommendations for seasonal campaigns, cost-saving menus, and delivery options
- Maintenance - Detailed monitoring and maintenance plans to ensure continued model performance
Restaurant C engaged Data Vision to perform market basket analysis using sales data to uncover consumption patterns and assess product offerings. The Apriori algorithm identified meaningful associations between menu items purchased together. Insightful recommendations were provided, including seasonal campaigns, cost-saving menus, and delivery options to help the restaurant boost revenue. Regular monitoring and adaptation of the model was advised to ensure continued success.
The final suggestion and result: Targeted marketing campaigns and menu optimizations were recommended based on associations found between products frequently purchased together. The data-driven insights aim to increase profits by acquiring new customers and better serving existing ones.