In the competitive landscape of the coffee industry, understanding customer preferences is vital for startup coffee shop owners and entry-level baristas. This project focuses on analyzing coffee sales data to identify the most favored coffee types by customers. By doing so, we aim to provide valuable insights that can help coffee businesses align their offerings with customer preferences, thereby enhancing marketing strategies and customer satisfaction.
The objective of this analysis is to delve into customer buying behavior and preferences in the coffee market. By examining sales data, we aim to uncover patterns and trends that indicate which coffee types are most favored by customers. This information can guide coffee shop owners and baristas in making informed decisions about their product offerings and marketing strategies.
Coffee shops are a thriving business in many regions, particularly in Indonesia. For startup coffee shop owners and entry-level baristas, understanding customer preferences is crucial for achieving marketing success and building a loyal customer base. This analysis seeks to provide actionable insights that can help coffee businesses thrive in this competitive market.
- Python Libraries:
- pandas
- numpy
- seaborn
- matplotlib
- scipy
- plotly