Imagine this scenario:
You want to know how your LTV is changing over time so you can invest the right amount in sales and marketing. You’re hoping to see a trendline that shows your customers are more valuable now than they were a year ago.
Unfortunately, when you look at your report, you notice that your LTV fluctuates wildly from one month to the next, with a low of $4,000, a high of $250,000, and no consistent upward or downward trend.
What’s going on here?
Most B2B SaaS businesses experience some fluctuation in their metrics month-to-month, even if business is “normal.” While that’s to be expected, it can be frustrating when you’re trying to understand your financial health and make wise decisions based on the data.
In the example above, the data tells us nothing of use. If you’re like most finance leaders, you’re looking for more helpful insights than “it varies” to share with your leadership team.
That’s why it’s important to understand:
- Why your metrics can vary dramatically from one month to the next
- Which metrics are susceptible to this variance
- How you can get a more insightful picture of these metrics
Why your B2B SaaS metrics fluctuate month-to-month
Many B2B SaaS businesses experience some form of seasonality.
For example, maybe you sell to educational institutions, which nearly always buy new products during the summer. If so, your business will close an outsized number of deals in Q3, and Q3 will also be the time when most of your customers are up for renewal.
If that’s the case for you, then calculating LTV numbers based on customer churn between April and March (or any other months outside of Q3) will lead you to some bad decisions.
Your LTV during those months will look artificially high because that’s simply not the time of year when customers are going to churn. If you’re looking at monthly data during those months, you’re not getting an accurate picture of what’s normal for your business, and you’ll get false confidence about your retention.
To make it even more complicated, your business can experience these seasonal swings even if seasonality is uncommon among your customer base.
For example, perhaps one September your Sales team had an exceptionally effective sales push, and you added tons of high-value accounts in that month. That’s great!
But, unless you expect to see those results repeat themselves every month going forward, you’re spiking your ARPA for one month in particular. And, when you look at your results, that spike in ARPA is going to lead to a spike in LTV.
This leaves you with data that’s too messy to give you any helpful insights to confidently base business decisions on.
What to do about it
To get more useful insights out of your data, it’s helpful to use Trailing Twelve Months (TTM) to calculate most of your metrics.
With TTM, you’re calculating the metric based on the average of the twelve-month period prior to the date of the report. This reduces those dramatic dips and spikes month-to-month, as it includes a whole year of data. By using TTM, we get a clearer picture of any actual upward or downward trends that are occurring over time, allowing us to draw better conclusions.
For businesses that sell annual contracts, consider measuring these metrics using TTM:
💰 Retention Metrics
If many of your accounts renew around the same time of year, your retention metrics are likely to experience monthly shifts. Don’t forget that this will also impact any metrics that are calculated based on retention metrics, like LTV.
- Gross Customer Retention
- Gross Revenue Retention
- Net Revenue Retention
🔥 Efficiency Metrics
If you pay sales commissions on a quarterly basis, your Sales and Marketing costs will swing upward during the last month of each quarter, impacting your efficiency metrics.
- Payback Period
- Rule of 40
- Burn Multiple
💲 Unit Economics Metrics
Seasonality can play a huge role in both recurring revenue and metered revenue from month to month.
- Gross Margin
📈 SaaS Metrics
For any metrics that are calculated with formulas that use other fluctuating metrics as variables, it’s extra important to bear seasonality in mind and use TTM where possible.
A more sensible LTV chart
Let’s revisit the LTV example once more. If you were to measure your LTV based on TTM instead of just one month of data at a time, you’d get a much more helpful picture of your business’s LTV over time.
Using this data, you can see an LTV that varies between a low of $13,000 and a high of $25,000 throughout the year—a much more helpful range than we got before we used TTM. You can also see an overall upward trend over the course of the year, which wasn’t clear when you were solely measuring monthly data.
Now, since you have a more accurate picture of what your LTV actually is, you can also make more informed decisions around projected future revenue and whether your LTV:CAC is healthy.
Measure with TTM, without the hassle
With Subscript, you can measure many of your most important SaaS metrics as TTM with the click of a button, and you can toggle TTM on and off at any time to compare the data.
Subscript gives you access to all of your B2B SaaS metrics, including ARR, churn, LTV, and more, in a visually intuitive dashboard. That way, you’ll spend less time digging through data in Excel, and more time gaining helpful insights.
Ready to see a demo? Let us show you around.