This fully synthetic dataset simulates digital sales transactions, marketing channels, and customer feedback for an online store environment. It was designed to support hands-on exploration of sales analytics, marketing attribution, customer segmentation, and business intelligence workflows.

Highlights:

~3,000 transactions with realistic structure while preserving privacy.

Detailed features including product categories, pricing, quantities, calculated revenue.

Customer demographics (country, gender), marketing channels, sales platforms.

Customer feedback captured as Net Promoter Scores (NPS).

Ideal for practicing data cleaning, exploratory data analysis, dashboard design, and predictive modeling in marketing and e-commerce contexts.

File Information

File format: CSV

Total rows: 3,000

Columns: 15

Encoding: UTF-8

Delimiter: Comma (,)

Columns Overview

date: Date of purchase

first_name: Customer names

gender: Gender (Male/Female/Other)

product_name: Name of the digital product

category: Product category (e.g., Course, Template, Webinar)

price: Unit price

quantity: Number of units purchased

revenue: Total revenue = price × quantity

customer_country: Country of the customer

platform: Sales platform (e.g., ClickFunnels, Kajabi)

marketing_channel: Marketing source (e.g., Email, Organic Search)

nps_score: Customer Net Promoter Score (0–10)