We are analyzing a well-established company in the retail food sector, which currently serves a large customer base, with several hundred thousand registered customers and close to one million consumers annually. The company offers products across five major categories: wines, rare meat products, exotic fruits, specially prepared fish, and sweet products. These products are further segmented into two tiers: gold and regular. Customers can purchase items through three distinct sales channels: physical stores, catalogs, and the company’s website.
While the company has enjoyed solid revenues and a healthy bottom line over the past three years, the outlook for profit growth over the next three years is less optimistic. In response, several strategic initiatives are under consideration to reverse this trend. One key initiative is to enhance the effectiveness of marketing activities, particularly focusing on optimizing marketing campaigns.
The marketing department is under pressure to allocate its annual budget more efficiently. The success of this initiative is crucial, as it will not only validate the new approach but also help gain support from skeptical stakeholders within the company.
As data analysts, our role is to thoroughly analyze the available data, identify business opportunities and insights, and recommend data-driven actions to optimize campaign performance and drive value for the company.
- Provide a better understanding of the characteristic features of respondents
- Propose and describe a customer and product segmentation based on customers behaviors
- Visualize data and provide written reasoning behind discoveries.
- Python: Major programming language used for the project.
- Pandas & NumPy: For data manipulation and numerical calculations.
- Jupyter Notebook: For interactive data analysis and sharing of results.
A working demonstration is provided in the notebooks folder: notebooks/food_marketing_EDA.ipynb