Challenge: Calculate Key Metrics
Daily Active Users (DAU) and churn rate are two essential metrics for any product manager tracking user engagement and retention. DAU indicates the number of unique users interacting with your product each day, providing a snapshot of daily engagement. A higher DAU often signals a healthy, active user base. Churn rate, on the other hand, measures the percentage of users who stop using your product over a certain period. Monitoring churn helps you understand retention challenges and identify when users are leaving, which is crucial for improving your product and maintaining growth.
123456789# Example of printing formatted product metrics average_dau = 2450 churn_rate = 0.08 print(f"Product Metrics Report") print(f"----------------------") print(f"Average DAU for the month: {average_dau}") print(f"Churn Rate: {churn_rate:.2%}")
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Write a function that calculates and prints the average daily active users (DAU) and churn rate for a product, given two lists: one containing daily active user counts for each day of the month, and one containing churn statuses for each user (1 if the user churned, 0 if not).
- Compute the average DAU by summing the values in
daily_active_usersand dividing by the number of days. - Calculate the churn rate as the percentage of users who churned, using the
churn_statuseslist. - Format the output to display the average DAU as an integer and the churn rate as a percentage with two decimal places.
- Print a report including both metrics with clear labels.
Oplossing
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Can you explain how to calculate DAU and churn rate?
What are some strategies to reduce churn rate?
How do DAU and churn rate impact product growth?
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Daily Active Users (DAU) and churn rate are two essential metrics for any product manager tracking user engagement and retention. DAU indicates the number of unique users interacting with your product each day, providing a snapshot of daily engagement. A higher DAU often signals a healthy, active user base. Churn rate, on the other hand, measures the percentage of users who stop using your product over a certain period. Monitoring churn helps you understand retention challenges and identify when users are leaving, which is crucial for improving your product and maintaining growth.
123456789# Example of printing formatted product metrics average_dau = 2450 churn_rate = 0.08 print(f"Product Metrics Report") print(f"----------------------") print(f"Average DAU for the month: {average_dau}") print(f"Churn Rate: {churn_rate:.2%}")
Swipe to start coding
Write a function that calculates and prints the average daily active users (DAU) and churn rate for a product, given two lists: one containing daily active user counts for each day of the month, and one containing churn statuses for each user (1 if the user churned, 0 if not).
- Compute the average DAU by summing the values in
daily_active_usersand dividing by the number of days. - Calculate the churn rate as the percentage of users who churned, using the
churn_statuseslist. - Format the output to display the average DAU as an integer and the churn rate as a percentage with two decimal places.
- Print a report including both metrics with clear labels.
Oplossing
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