In this post, I explore and analyze some e-commerce customer data by identifying patterns in customer satisfaction and churn.

The dataset used for this analysis includes information on customer demographics, purchasing behavior, and satisfaction scores. Key features include:

  • CustomerID
    Unique identifier for each customer.
  • Gender
    Gender of the customer (Male/Female).
  • MaritalStatus
    Marital status of the customer (Married/Single/Divorced).
  • PreferedOrderCat
    Preferred order category of the customer (e.g., Fashion, Grocery, Mobile).
  • SatisfactionScore
    Satisfaction score given by the customer (1 to 5).
  • Complain
    Whether the customer has made a complaint (Yes/No).
  • Churn
    Whether the customer has churned (0 for no, 1 for yes).

Key Analyses and Insights

Who are the customers?

I start off by getting the gender and marital status distribution and found:
Male: 3384
Female: 2246

Gender count

Married: 2986
Single: 1796
Divorced: 848

Marital status count

The customer base is predominantly male, with males making up 60% and females 40% of the total customer population.

Discovering Preferred Order Categories

I examine customer preferences by analyzing preferred order categories Product popularity

Categories like “Mobile Phone” and “Laptop & Accessory” have the highest satisfaction scores, indicating that these product categories are highly favored by customers.

I also explore the relationship between marital status and preferred order categories to understand how different demographic groups shop. Product popularity by marital status

General Observations

Dominance of Married Customers:
Across all product categories, married customers consistently show higher numbers compared to single and divorced customers. This indicates that married individuals might have a higher purchasing power or different shopping needs compared to other groups.

Single Customers:
Single customers generally follow married customers in numbers, with a considerable gap in categories like Laptop & Accessory and Mobile.

Divorced Customers:
Divorced customers consistently form the smallest group in all categories. This might reflect different shopping habits or economic conditions impacting their purchasing behavior.