Name: E-commerce Customer Behavior Dataset
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

E-commerce Customer Behavior Dataset

Dataset Description: E-commerce Customer Behavior

Overview:
This dataset provides a comprehensive view of customer behavior within an e-commerce platform. Each entry in the dataset corresponds to a unique customer, offering a detailed breakdown of their interactions and transactions. The information is crafted to facilitate a nuanced analysis of customer preferences, engagement patterns, and satisfaction levels, aiding businesses in making data-driven decisions to enhance the customer experience.

Columns:

Customer ID:
- Type: Numeric
- Description: A unique identifier assigned to each customer, ensuring distinction across the dataset.
Gender:
- Type: Categorical (Male, Female)
- Description: Specifies the gender of the customer, allowing for gender-based analytics.
Age:
- Type: Numeric
- Description: Represents the age of the customer, enabling age-group-specific insights.
City:
- Type: Categorical (City names)
- Description: Indicates the city of residence for each customer, providing geographic insights.
Membership Type:
- Type: Categorical (Gold, Silver, Bronze)
- Description: Identifies the type of membership held by the customer, influencing perks and benefits.
Total Spend:
- Type: Numeric
- Description: Records the total monetary expenditure by the customer on the e-commerce platform.
Items Purchased:
- Type: Numeric
- Description: Quantifies the total number of items purchased by the customer.
Average Rating:
- Type: Numeric (0 to 5, with decimals)
- Description: Represents the average rating given by the customer for purchased items, gauging satisfaction.
Discount Applied:
- Type: Boolean (True, False)
- Description: Indicates whether a discount was applied to the customer's purchase, influencing buying behavior.
Days Since Last Purchase:
- Type: Numeric
- Description: Reflects the number of days elapsed since the customer's most recent purchase, aiding in retention analysis.
Satisfaction Level:
- Type: Categorical (Satisfied, Neutral, Unsatisfied)
- Description: Captures the overall satisfaction level of the customer, providing a subjective measure of their experience.

Use Cases:

Customer Segmentation:
- Analyze and categorize customers based on demographics, spending habits, and satisfaction levels.
Satisfaction Analysis:
- Investigate factors influencing customer satisfaction and identify areas for improvement.
Promotion Strategy:
- Assess the impact of discounts on customer spending and tailor promotional strategies accordingly.
Retention Strategies:
- Develop targeted retention strategies by understanding the time gap since the last purchase.
City-based Insights:
- Explore regional variations in customer behavior to optimize marketing efforts based on location-specific trends.

Note: This dataset is synthetically generated for illustrative purposes, and any resemblance to real individuals or scenarios is coincidental.

Tables

E Commerce Customer Behavior Sheet1

@kaggle.uom190346a_e_commerce_customer_behavior_dataset.e_commerce_customer_behavior_sheet1

11.8 kB
350 rows
11 columns

CREATE TABLE e_commerce_customer_behavior_sheet1 (
  "customer_id" BIGINT,
  "gender" VARCHAR,
  "age" BIGINT,
  "city" VARCHAR,
  "membership_type" VARCHAR,
  "total_spend" DOUBLE,
  "items_purchased" BIGINT,
  "average_rating" DOUBLE,
  "discount_applied" BOOLEAN,
  "days_since_last_purchase" BIGINT,
  "satisfaction_level" VARCHAR
);