← Back to All Projects

Customer Data Analyzer

Build a system to analyze customer purchase patterns and segment customers by behavior

ProgressSection 1 of 6

Section 1: Understanding Customer Data

📖

EXPLAIN: Understanding the Concept

👥 What We're Building

We're building a Customer Segmentation Tool that analyzes customer purchase data and automatically categorizes customers as:

  • High Value: Customers who spend $1000 or more
  • Medium Value: Customers who spend $500-$999
  • Low Value: Customers who spend less than $500

Why this matters: Businesses treat different customer segments differently. High-value customers get premium support, special offers, etc.

What you'll learn: How to process multiple records, make decisions with code, and categorize data.

👀

SHOW: Here's How It Works

👀 Customer Data Structure

Customer data typically looks like this:

Customer: Alice, Total Purchases: $1,250 → HIGH VALUE
Customer: Bob, Total Purchases: $450 → LOW VALUE
Customer: Carol, Total Purchases: $750 → MEDIUM VALUE

We'll store this as a list of lists (nested data):

customers = [
    ["Alice", 1250],
    ["Bob", 450],
    ["Carol", 750]
]
✍️

PRACTICE: Now You Build It!

✍️ Your Turn: View Customer Data

Run the demo code to see how customer data is structured!

Notice how each customer is a list with two items: [name, purchase_amount]

Code Editor
Initializing editor...
💻 Output:
Click 'Run Code' to see output here...