What is GRR?
Gross Revenue Retention (GRR), also known as gross dollar retention, measures the percentage of revenue retained, excluding expansions, over a period of time.
For example; if you have a total monthly recurring revenue (MRR) of $100k on day one, excluding any contribution from expansions, what percentage of that revenue do you still have 12 months later.
In SaaS, people tend to focus overly on NRR as the key revenue retention metric, and GRR is often overlooked. However, in many cases, gross retention can help provide a more complete picture of retention. Gross revenue retention tells you how much revenue you maintain when activities like upsells, cross-sells that increase your average customer value aren’t factored in.
Gross revenue retention answers the question of how well you retain your customers, while net revenue retention digs deeper into your ability to expand revenue from those customers.
Calculating gross revenue retention (GRR)
To calculate gross revenue retention, divide your monthly recurring revenue (MRR) today from customers one year ago (excluding any expansion revenue generated) by MRR from the same group of customers one year ago.
Here is the formula for gross revenue retention:
Let's look at an example
One year ago, you had 4 paying customers with a total MRR of $770.
This time, we’re excluding any expansion, and the MRR today from the same group of customers who existed one year ago is $630.
So the gross revenue retention rate is $630 divided by $770.
GRR is 81.8%.
What is a good gross retention rate?
The best-in-class gross revenue retention rate at any stage of the business is over 86%. That means that the most successful SaaS businesses lose ~14% of gross revenue in a year.
Take a look at the chart below. The top quartile of companies with an ARPA over $500/month hit 90%+ gross retention, while the top quartile of companies with an ARPA less than $50/month only hit 60 to 70%.
When judging whether a SaaS company has good gross revenue retention, keep ARPA in mind.
Gross revenue retention rate (%) by ARPA range
- 75th percentile
- Median
- 25th percentile
ARPA per month range | 75th percentile | Median | 25th percentile |
---|---|---|---|
<$10 | 62.4% | 46.8% | 35.9% |
$10-50 | 70.2% | 57.4% | 39.3% |
$50-100 | 80.4% | 66.6% | 54.9% |
$100-250 | 81.0% | 71.2% | 61.5% |
$250-500 | 83.0% | 74.0% | 64.8% |
>$500 | 88.1% | 80.6% | 66.2% |
Net revenue retention vs gross revenue retention
Both gross and net revenue retention rates are crucial for understanding overall revenue growth from existing customers and are important metrics to measure customer retention. However, they are used in different contexts.
GRR is useful when a company wants to measure the retention of their core existing customer base without factoring in any expansion revenue. Your net revenue retention rate (NRR) is useful when a company wants to measure the overall revenue growth from the existing customer base, including expansion revenue.
GRR is helpful to assess how well your retention strategies are keeping existing customers. In contrast, NRR is more useful to assess how effective your expansion strategies are at growing expansion revenue from the existing customer base.
Customer success efforts play a significant role in influencing both GRR and NRR, as they help ensure customers achieve their desired outcomes and continue to use the product. Improving customer loyalty is essential for both GRR and NRR, as loyal customers are more likely to stay and expand their usage.
Tracking gross revenue retention
Retention can be measured over any time period, but it is common to measure it over 12 months. Analyzing retention over 12 months works well for both annual and monthly subscriptions. It allows for the full customer lifecycle, including adoption and expansion. And it also nullifies any impact from seasonality, which can cause short-term fluctuations. If you’d like to track shorter intervals, make sure to look at the same intervals consistently.
ChartMogul calculates all your core SaaS metrics by importing, cleaning, and analyzing data. It then renders them into easy-to-see dashboards and charts that are fully customizable.