Learn Segmenting Customers by Behavior | Customer Data Analysis Essentials

Python for Customer Success Managers

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Customer segmentation is the process of dividing customers into groups based on shared characteristics or behaviors. In the context of Customer Success, segmentation allows you to identify patterns in how customers interact with your product or service. By grouping customers according to their behaviors—such as usage frequency, feature adoption, or support interactions—you can develop personalized engagement strategies that address each segment's unique needs. This targeted approach helps you deliver more relevant support, anticipate issues, and ultimately drive better outcomes for both your customers and your organization.


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# Segment customers into 'high', 'medium', and 'low' engagement based on activity scores

customers = [
    {"name": "Alice", "activity_score": 92},
    {"name": "Bob", "activity_score": 67},
    {"name": "Carol", "activity_score": 45},
    {"name": "Dan", "activity_score": 80},
    {"name": "Eve", "activity_score": 30},
    {"name": "Frank", "activity_score": 76}
]

def segment_customer(activity_score):
    if activity_score >= 80:
        return "high"
    elif activity_score >= 50:
        return "medium"
    else:
        return "low"

for customer in customers:
    segment = segment_customer(customer["activity_score"])
    customer["segment"] = segment

for customer in customers:
    print(f'{customer["name"]}: {customer["segment"]}')

Segmenting customers in this way enables you to design tailored outreach and support strategies. For example, customers in the "high" engagement group may benefit from advanced feature tutorials or advocacy programs, while those in the "low" group might need proactive check-ins or onboarding assistance. The segmentation logic above uses activity scores to determine which group each customer belongs to, making it easy to identify where to focus your efforts for maximum impact.


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# Summarize the number of customers in each segment using a dictionary

segment_counts = {"high": 0, "medium": 0, "low": 0}

for customer in customers:
    segment = customer["segment"]
    segment_counts[segment] += 1

print(segment_counts)

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Section 1. Chapter 4

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Section 1. Chapter 4

Segmenting Customers by Behavior

1. What is the main benefit of segmenting customers by behavior?

2. Which Python structure is useful for counting items in different categories?

3. How might you use segmentation results to improve customer retention?