Download the dataset below to solve this Data Science case study on Customer Behaviour Analysis.
Customer Behavior Analysis is the process of examining how customers interact with a product, service, or platform to understand their actions, preferences, and decision-making processes.
We have a dataset that captures the behavior of e-commerce customers. The dataset contains the following columns:
- User_ID: Unique identifier for each customer.
- Gender: Gender of the customer (e.g., Male, Female).
- Age: Age of the customer.
- Location: Location of the customer.
- Device_Type: Type of device used for browsing (e.g., Mobile, Tablet, Desktop).
- Product_Browsing_Time: Amount of time spent browsing products (in minutes).
- Total_Pages_Viewed: Total number of pages viewed during the browsing session.
- Items_Added_to_Cart: Number of items added to the shopping cart.
- Total_Purchases: Total number of purchases made.
Your task involves:
- Understanding the distribution and characteristics of customer demographics (e.g., age, gender, location).
- Exploring how different types of devices are used by customers and their impact on behavior.
- Investigating the relationship between browsing time, pages viewed, items added to the cart, and actual purchases.
- Segmenting customers based on their behavior and identifying distinct customer groups.
- Analyzing the customer journey and identifying potential areas for improvement in the conversion funnel.
- Assessing the impact of customer behavior on revenue generation and identifying opportunities for increasing sales and customer engagement.
