In this exploration, we delve into the structure and characteristics of the data, identify outliers, and assess the impact of demographic features on product purchases. We'll represent marginal probabilities, uncover correlations, and answered specific questions about customer behavior. The ultimate goal is to provide actionable insights and recommendations for informed decision-making.
Dataset Link:https://drive.google.com/file/d/1m3c1-kM3JDIhunnx0PQn240ZdVcmA7VA/view?usp=drive_link
Key Objectives:
- Identified outliers using boxplots and the "describe" method.
- Investigated the impact of marital status and age on product purchases.
- Represented marginal probabilities for specific treadmill models.
- Explored correlations among different factors using visualizations.
- Addressed specific queries, like the probability of a male customer buying a KP781 treadmill.
- Categorized users based on identified patterns for customer profiling.
- Provided insights into marginal and conditional probabilities.
- Offered actionable insights for strategic decision-making.