Innovation Owner
Miss NAPAPAT SUKKASEM
Student
Details
This project focuses on segmenting and analyzing customer behavior at Punthai Coffee to enhance business strategy. By utilizing Machine Learning techniques such as Naive Bayes, Random Forest, and Deep Learning, the study identifies distinct customer groups based on their purchasing patterns.
In a highly competitive business, understanding customers is crucial for an organization to determine its success. Effective marketing is not just about offering good products, promotions, or services; it also requires strategies to reach and build strong relationships with customer groups. Segmenting customers is one method that helps businesses deeply understand the needs and behaviors of the customers who use their services.
In this internship, the objective is to understand the behavior of customers purchasing coffee and tea at a large cafe group by analyzing stored customer data. The project employed the following techniques to compare accuracy and suitability:
- Naive Bayes
- Random Forest
- Deep Learning
As a result of this process, customer groups were segmented, and the insights gained from this analysis can be used for further development in analyzing other data sets in the future.
Objective
The objectives are to segment customers based on their beverage purchasing patterns using Machine Learning techniques and to analyze the specific characteristics and behaviors of each identified customer group.
- To segment customers based on their beverage purchasing patterns using Naive Bayes, Random Forest, and Deep Learning.
- To analyze the characteristics and behaviors of customers in each group.