Dealer’s Choice: A Deep Dive on Picking the Right NDR Formula for Your Business Model
Net Dollar Retention (NDR) rate is perhaps the most telling metric when it comes to a company’s future revenue durability. It’s a window into how SaaS companies embed future growth into their model. In my humble opinion, it’s the highest signal into how much operating leverage you have.
What’s more, each company’s calculation sheds light on the most important levers within their business: how do you retain and expand customers?
Because NDR is not a standardized GAAP (generally accepted accounting principles) metric, there are subtle changes companies make when it comes to measurement around the edges. Some of these moves are logical, given their customer behavior and selling motion. Others are purely playing ‘hide the ball’.
For Reference: This is the most “vanilla” way to calculate NDR
Let’s dive into how MongoDB, Snowflake, and HubSpot calculate their NDR, deconstructing the formulas, inputs, and nuances that set them apart.
One formula is geared towards multi product, multi channel businesses (MongoDB)
One formula is geared towards usage heavy, seasonal businesses (Snowflake)
One formula is geared towards subscription heavy, seat based models (HubSpot)
And then we’ll discuss how your choice impacts both how you forecast your business, and how fluctuations potentially impact your valuation (you won’t want to miss that part, as it’s not widely written about).
Letttt’s ride…
Three Proven Methodologies (And When to Use Each)
MongoDB's Segmented ARR Expansion: For Multi-Product, Multi-Segment Businesses
How it works:
Tracks ARR changes from existing customers over 12 months
Segments direct sales (90-day usage) vs. self-serve (30-day usage)
Excludes professional services
Choose this approach when:
You have distinct customer segments with different expansion behaviors
Your direct sales motion differs significantly from self-serve growth
You need to isolate which segments drive your larger accounts (and also have higher S&M costs)
Operational implications:
Higher reporting complexity but superior actionability (you'll know exactly which segment to double down on)
More volatile quarter-to-quarter due to usage sensitivity, so budget for 3-5% swings in your forecasts
Earlier warning signals when segments start diverging in health
Trade-off you're accepting: Increased reporting burden for granular insights that directly inform resource allocation decisions. Do you invest more in product? Or direct sales?
Snowflake's Long-Term Consumption Model: For Usage-Heavy, Seasonal Businesses
How it works:
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