The project’s goal is to do create a machine learning model to do customer personality analysis for a hypermarket in hopes to be able to see the correlation between cusomter’s behaviour and the business. Information will then be used to do prediction model. The main objective is to use these information to help reduce percentage of cusomter churn for Hypermarkets.
Analyzing customers' personalities, businesses can better understand their customers' motivations, preferences, and pain points in hopes of being able to control or reduce customer churn. This analysis allows companies to delve deeper into comprehending what motivates their customers' decisions, what preferences guide their choices, and where they encounter challenges or dissatisfaction within the offered services or products. Using these insights into these aspects through personality analysis, businesses aim not just to understand but also to actively address and cater to customer needs and expectations. This strategic understanding empowers businesses to tailor their approaches, services, and engagement strategies. This in hopes will be able strengthen customer loyalty and minimize the probability of customer churning with the company's products or services.
###Technology
- The platform used is Databricks
- The programming language that is used for this project is Scala
- Languages used for visualization is SQL
- You can run the program by just installing the html file