Using AI for market research in AI for Everyone - Mini Project: Build & Apply

Using AI for Market Research

📖 Scenario: You work for a small business that wants to understand customer preferences better. You decide to use AI tools to analyze customer feedback and market trends.

🎯 Goal: Build a simple step-by-step plan to use AI for market research, including data collection, setting criteria, analyzing data, and summarizing insights.

📋 What You'll Learn

Create a list of customer feedback comments

Set a keyword to focus the analysis

Use a loop to find comments containing the keyword

Summarize the number of relevant comments found

💡 Why This Matters

🌍 Real World

Businesses use AI to quickly analyze customer opinions and market trends from large amounts of feedback.

💼 Career

Understanding how to prepare and filter data is a key skill for market researchers and data analysts using AI.

1

Create customer feedback data

Create a list called feedback with these exact customer comments: 'Love the product quality', 'Customer service was slow', 'Great value for money', 'Delivery was late', 'Product exceeded expectations'.

AI for Everyone

# Create the list called feedback with the given comments
# Your code here

Need a hint?

Use square brackets [] to create a list and include all comments as strings inside quotes.

2

Set the keyword for analysis

Create a variable called keyword and set it to the string 'product' to focus on comments about the product.

AI for Everyone

feedback = ['Love the product quality', 'Customer service was slow', 'Great value for money', 'Delivery was late', 'Product exceeded expectations']
# Create the variable keyword with the value 'product'
# Your code here

Need a hint?

Assign the string 'product' to the variable keyword using the equals sign.

3

Find comments containing the keyword

Create an empty list called relevant_comments. Use a for loop with the variable comment to go through each item in feedback. Inside the loop, use an if statement to check if keyword is in comment (case insensitive). If yes, add comment to relevant_comments.

AI for Everyone

feedback = ['Love the product quality', 'Customer service was slow', 'Great value for money', 'Delivery was late', 'Product exceeded expectations']
keyword = 'product'
# Create an empty list relevant_comments
# Use a for loop to check each comment for the keyword
# Your code here

Need a hint?

Remember to convert both keyword and comment to lowercase to ignore case differences.

4

Summarize the analysis

Create a variable called summary and set it to a string that says: 'Number of comments about product: ' followed by the number of items in relevant_comments. Use an f-string to combine the text and number.

AI for Everyone

feedback = ['Love the product quality', 'Customer service was slow', 'Great value for money', 'Delivery was late', 'Product exceeded expectations']
keyword = 'product'
relevant_comments = []
for comment in feedback:
    if keyword.lower() in comment.lower():
        relevant_comments.append(comment)
# Create the summary string using an f-string
# Your code here

Need a hint?

Use len(relevant_comments) inside the curly braces of the f-string to get the count.