Learn Segmenting Audiences with Python | Marketing Data Analysis with Python

Audience segmentation is a fundamental process in marketing that involves dividing a broad customer base into smaller groups, or segments, with shared characteristics. This approach allows you to better understand your customers' needs, preferences, and behaviors. By segmenting your audience, you can tailor your marketing strategies, messaging, and offers to specific groups, resulting in more effective and relevant campaigns.


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import pandas as pd

# Create a DataFrame with customer data
data = {
    "Customer_ID": [1, 2, 3, 4, 5, 6],
    "Age": [22, 35, 27, 45, 52, 31],
    "Location": ["New York", "Los Angeles", "New York", "Chicago", "Chicago", "Los Angeles"],
    "Purchase_History": [200, 450, 150, 300, 500, 250]
}

df = pd.DataFrame(data)

# Segment customers into age groups
bins = [18, 30, 40, 60]
labels = ["18-29", "30-39", "40-59"]
df["Age_Group"] = pd.cut(df["Age"], bins=bins, labels=labels, right=False)

print(df[["Customer_ID", "Age", "Age_Group"]])

Segmentation is a powerful tool for marketers because it enables personalized campaigns that speak directly to the interests and needs of each group. When you know which segment a customer belongs to, you can send them tailored messages, recommend relevant products, and offer promotions that are more likely to resonate. This personalization not only improves the customer experience but also increases engagement, conversion rates, and ultimately your return on investment (ROI).


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# Group the DataFrame by 'Location' and summarize purchase totals
location_summary = df.groupby("Location")["Purchase_History"].sum().reset_index()
location_summary.columns = ["Location", "Total_Purchases"]

print(location_summary)

1. What is the main goal of audience segmentation in marketing?

2. Which pandas method is commonly used for grouping data by a specific column?

3. Fill in the blank: To segment customers by age, you can use the pandas ______ function.

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Section 1. Chapter 4

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