🎙️ Hey there, SaaSpreneurs!🎙️

📢 Introducing the latest edition of SaaS Metrics School Newsletter! 🎉

In this episode, host Ben Murray dives deep into the crucial topic of measuring the time period for revenue retention. Ben recently received an intriguing question from a student in his SaaS metrics course—what exactly is the ideal time period to measure retention?

Tune in as Ben uncovers the various approaches to measuring aggregate revenue retention. He discusses the significance of tracking retention on a monthly basis, trailing three-month and six-month periods, and even warns about the potential pitfalls of relying solely on a trailing twelve-month basis.

But that's not all! Ben also delves into cohort retention, shedding light on how to measure retention for specific customer cohorts over time.

Join us for this highly informative episode, where we unravel the mystery of measuring retention time periods—one vital metric at a time. If you find value in our content, we encourage you to share this newsletter below and receive rewards, helping us spread the knowledge to even more SaaS enthusiasts.

You can also listen to the episode here.

📓Key Concepts to Learn💡

1. Aggregate Revenue Retention: When measuring overall revenue retention, Ben suggests using a trailing three-month basis (T3M) and annualizing it for a more accurate representation. A trailing six-month basis (T6M) can also provide a smoothed-out view of retention trends. However, caution is advised when using a trailing twelve-month basis (T12M) due to potential inaccuracies in metrics caused by the exclusion of customers who enter and exit within this time period. ⏳🔢

2. Subjectivity in SaaS Metrics: Deciding on the time period for retention measurement involves some subjectivity. Different time periods may emphasize recent changes or provide a broader perspective on customer retention. It's essential to select the most suitable time period based on specific business needs and goals. 📅🤔

3. Cohort Retention: Cohort retention focuses on analyzing the retention of a particular customer group over time. Unlike aggregate revenue retention, there is no fixed time period for cohort retention measurement. Instead, each cohort is continuously tracked from the month of acquisition, providing ongoing insights into customer retention and revenue generation. 🚀💪

4. Danger of Trailing Twelve-Month Retention: While TTM retention may seem useful, there is a potential data discrepancy when new customers join during the analysis period. If a customer is not part of the starting balance, their subsequent expansion, downgrade, or churn activity may skew the metrics. Hence, extra attention should be given when using T12M retention metrics. ⚠️📉

📝 Episode Recap 🎧

In this episode of SaaS Metrics School, Ben Murray delves into the crucial topic of determining the appropriate time period for measuring revenue retention. A student from his SaaS metrics course posed the question, "What time period should I measure for retention?" Ben provides insights and guidance on how to approach this challenge.

For aggregate revenue retention, Ben suggests measuring on a monthly basis, utilizing a trailing three-month (T3M) and trailing six-month (T6M) approach, which is then annualized. He also highlights the importance of considering varying contract lengths, such as multi-year contracts, which may require measurement on a trailing twelve-month (TTM) basis.

Ben emphasizes the relevance of these time periods in understanding the trend of revenue retention.

The T3M allows for the reflection of recent changes, while the T6M provides a smoother outlook. Furthermore, it is essential to segment retention data based on customer profiles, product lines, and other key factors.

When discussing cohort retention, Ben explains that there is no fixed time period to measure because cohort retention entails tracking a specific group of customers over time, and continuously evaluating their retention rates and the revenue they generate.

However, Ben advises caution when analyzing trailing twelve-month retention. If a new customer joins after the initial measurement period, their impact may not be accurately represented in the metrics, potentially skewing the results.

Ben concludes by emphasizing the subjectivity of SaaS metrics related to time periods and highlights the significance of accurately collecting and evaluating data.

Stay tuned for the next episode of SaaS Metrics School, where Ben will provide further insights into the world of SaaS metrics. 🎙️📊