Practice SaaS churn vocabulary: monthly churn rate, revenue vs. logo churn, net revenue retention, cohort churn analysis, and churn prediction models.
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'Monthly churn rate is 2.3%.' This means that each month, 2.3% of customers:
Monthly churn rate is the percentage of customers who cancel in a given month. 2.3% monthly churn compounds to ~25% annual churn, a significant retention challenge.
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What is the difference between 'revenue churn' and 'logo churn'?
Logo churn counts the number of customers lost. Revenue churn measures the MRR lost. A company can have low logo churn but high revenue churn if large accounts are leaving.
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'Net Revenue Retention (NRR) > 100% means _____.' What does this indicate?
NRR > 100% (also called 'negative net churn') means expansion revenue from upsells and cross-sells in existing accounts exceeds revenue lost from churn — a very healthy SaaS signal.
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'The churn cohort analysis shows month _____ is the risk point.' At which month do users most commonly churn?
Month 3 is the example given as the churn risk point. Cohort analysis groups customers by start month and tracks their churn over time, revealing when customers are most likely to leave.
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A 'churn prediction model' is used to:
A churn prediction model uses product usage data, engagement signals, and support history to identify accounts at high risk of churning, enabling proactive intervention by customer success teams.
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Reviewer: 'This PR has a high churn risk. The user flow isn't intuitive and the onboarding process is confusing.' What does the reviewer likely mean in this context?
Churn in this scenario refers to users discontinuing their use of a product or service. The reviewer isn't pointing out technical bugs but rather the impact on user behavior—specifically that the changes are making it harder for new users to get started and ultimately leading them to leave. This aligns with the concept of a poor onboarding experience driving churn.
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Slack Message from Sarah (Product Manager): 'We need to investigate why our new user retention rate dropped by 15% last month. I suspect a problem with the initial setup flow.' What is Sarah primarily concerned about regarding churn?
Sarah's message focuses on retention – the rate at which new users stick with the product after initial signup. A decline in this metric directly indicates a rise in churn, as it measures how effectively new users are being converted and retained. The setup flow is identified as the potential cause of this loss.
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API Response (Partial):
{ "metric": "monthly_churn", "value": 0.075, "unit": "%" } What does the 'monthly_churn' value represent in this context?
This API response provides data on monthly churn. 'Monthly_churn' represents the percentage of users who ceased using the service within a single calendar month. This is a standard metric for tracking user attrition and directly relates to the concept of churn.
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PR Description: 'Implemented new UI improvements based on user feedback. Aimed at increasing engagement.' Which of the following best describes how this PR *could* contribute to reducing churn?
Churn is often driven by factors like poor usability and low user engagement. If the UI improvements genuinely make the product more intuitive and enjoyable, it can significantly improve user satisfaction – a key factor in preventing users from abandoning the service. This directly addresses the goal of reducing attrition.
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Standup Update from David (Data Scientist): 'I'm building a churn prediction model using historical usage data. We're focusing on identifying users who are likely to cancel their subscriptions within the next 30 days.'
What is the primary purpose of this churn prediction model?
A *churn* prediction model's core function is to forecast which users are most likely to cancel their subscriptions. This allows the team to proactively engage with these 'at-risk' users—for example, through targeted support or incentives—to prevent them from actually churning. It's about intervention, not just observation.
What will I learn from the "Churn Vocabulary" exercise?
Practice SaaS churn vocabulary: monthly churn rate, revenue vs. logo churn, net revenue retention, cohort churn analysis, and churn prediction models.
Is this exercise free to use?
Yes. Every exercise on CoderSlingo, including this one, is free to use with no account, sign-up, or paywall required.
How many questions are in this exercise?
This set contains 10 multiple-choice questions, each with a detailed explanation shown after you answer.
Do I need to create an account to track my progress?
No account is required. Your progress bar and score reset each time you reload the page, but you can retry the exercise as many times as you like.
Who is this SaaS Metrics exercise for?
This exercise is built for IT professionals and non-native English speakers who need to read, write, and discuss saas metrics topics confidently at work.
What happens if I answer a question incorrectly?
You will see the correct answer highlighted along with a detailed explanation of why it is correct -- so every wrong answer becomes a learning moment, not just a lost point.
Can I retry this exercise?
Yes -- click "Try again" on the results screen at any time to reset your score and go through all the questions again.
How long does this exercise take to complete?
Most learners finish all 10 questions in under 10 minutes, since each question is answered by clicking a single option.
Where can I find more SaaS Metrics exercises?
See the full SaaS Metrics exercises hub for more vocabulary drills on this topic.
Is this exercise mobile-friendly?
Yes -- the exercise works on any device with a modern browser, including phones and tablets, with no app download required.