Speedinvest Blog

Looking Beyond the $1M ARR Mark: A Framework and Benchmarks To Assess Revenue Quality

January 24, 2023

The startup and venture world are filled with various rules of thumb; some helpful, some less so. One of the most common ones has been some variant of: ~$1 million in annual recurring revenue (ARR) is what you need for a successful Series A in a SaaS business. 

This rule has been popularized by all of your favorite SaaS thinkers. You can find it on the infamous SaaS napkin (although for 2022, Christoph actually hedges his bets with a slightly broader range of $500,000 to $2.5 million) and many VCs, including ourselves, wield it like a big signpost to guide seed stage founders to their next fundraising milestone. We think $1 million ARR on its own may be necessary but is rarely sufficient.

Directionally, $1 million ARR is a reasonably useful piece of venture wisdom. Even in the throes of the 2021 bull market where valuations in private markets detached from fundamentals, the $1 million mark was still a reasonably steady cue for founders to market their Series A. The underlying reason is that a million dollars in recurring revenue is supposed to be a solid indicator of initial product-market fit. You have something that works and can now scale and add more acquisition channels. As such, $1 million ARR is a good indicator of a business ready to scale.

That being said, a $1 million ARR top-line figure is at best a door opener in conversations with your Series A VC. Additionally, and given the new market environment, the magical number of $1 million ARR may no longer be enough. What matters is the quality of that revenue as well as the efficiency with which it was attained. Demand signals have grown in importance and as a result, VCs will take a closer look at how exactly your revenue is composed in addition to its absolute amount and the pace of its growth.

The following is supposed to be a quick outline of factors that a VC may look at to assess your traction. It’s also helpful to understand internally for steering your company. Please be aware that there is a trade-off. The more quantitative a measure is, the more comparable it is. At the same time, the more likely it is that a quantitative measure will overlook something in the aggregate.

Good VCs will use a broad lens to access a business and so should you as a founder. Similarly, you probably won’t excel in every metric. Ultimately, venture capital is supposed to pre-finance product development and very early-stage companies likely won’t have amazing sales efficiency. Lastly, a lot of these metrics are interdependent and none should be used in isolation. We still think this framework may be a helpful starting point.

Assess Revenue Quality Chart

Qualitative factors – not all revenue is created equal

Customer types

This means looking at who your customers are. For example, going into a tech correction, it may be important whether all your customers are Series A startups (more likely to churn) or non-tech legacy enterprises. It could also be important whether your customers are:

  • All very early-stage vs later-stage companies
  • Innovation departments (easier to acquire, harder to expand) or business units themselves
  • All from the same sector (e.g. European manufacturing suffering from energy prices)
  • Structurally important i.e. strategic customers. An example could be a large tech company, whose business you may ultimately cannibalize and who are likely to drop you as a result. Customers with long-term incompatible vested interests may be heavily discounted. Similarly, there may be strategic customers who can accelerate your company (e.g. through unique access to a data set) in which case they will be seen as more valuable.

Contract terms

Terms are the second most important characteristic of your early customers and play a huge role in how high quality your revenue will be perceived. Here are some considerations:

  • One-off vs recurring: For some business models, recurring revenue doesn’t make sense or would feel unnatural. But not contractually recurring revenue may still be discounted.
  • Duration: Do you have yearly, monthly, or even multi-year contracts in place?
  • Pilot or proper contract: Is your contract connected to certain milestones and did you already pass vendor certification and procurement?
  • Delivery model: This broadly refers to how your product gets from closed sale to the customer. That is, how big is the service component, how long is the onboarding process, and how much hand-holding or manual work is required?

Stats 101 - Descriptive characteristics of your customer base

Customer engagement

In short, a highly engaged customer is a better customer because they are less likely to churn and more likely to expand their account. There are many ways to measure engagement. The most common aggregate measures are:

  • Active users: Number of users who achieve a certain action in the product (e.g. login)
  • DAU/MAU ratio or DAU/WAU ratio: measures the percentage of active users who log in per day / week
  • Power users: users who log in X times per period Y or a similar definition

There are no hard and fast rules about what “good” engagement looks like. But keep in mind that good engagement should approximate expected behavior. That is, what you would expect to see how people use the product if it worked perfectly is what good engagement should look like. 

  • Margin structure: The most important metric here is gross margin, which measures the margin on revenue minus the Cost of Goods Sold (COGS) where COGS would usually be any cost of data, hosting, or software to deliver the product. Good SaaS businesses should eventually converge around the 80 percent Gross Margin (GM) mark.
  • Revenue concentration: This looks at how revenue is distributed across your customer base (think boxplot from your undergrad stats class). For example, if 80 percent of your revenue comes from 10 percent of your customers, this may indicate that a customer is an outlier. 

Ratios and efficiency metrics –– benchmarking yourself

Ratios are to be taken with a grain of salt as they, by definition, consist of a numerator and denominator, making them more susceptible to obfuscating underlying problems. That said, here are the most commonly used ones:

Growth: The one metric that matters the most. How fast is your company growing? Ultimately, growth is an indicator of product-market fit and (hopefully) future performance. The most common ways to measure growth are either the percentage of growth month-over-month (especially for early-stage companies) or year-over-year (especially from Series A and beyond).

Net revenue retention: For a given cohort, net revenue retention (NRR) measures the revenue generated by that cohort per period of time accounting for churn, contraction, and expansion. Great companies can have NRR > 100 percent where expansion exceeds contraction and churn.

Sales productivity: There are various ways to measure this, but ultimately what you are looking to understand is:

  • The (net) new ARR generated per dollar spent on sales and marketing, sometimes referred to as “the magic number”
    The total cost of acquiring one customer factoring in all sales and marketing expenses (i.e. your customer acquisition cost)
  • The payback period for your Customer Acquisition Cost (CAC) which brings together CAC, revenue, and margin

Burn multiple: This is commonly calculated as a ratio of burn and net new ARR, therefore giving you an implicit figure of how much money a company is burning per incremental revenue dollar generated.

Hype ratio: This is a bit of a wildcard, but can still be interesting. The hype ratio (coined by Dave Kellogg) divides capital raised by ARR. It’s an additional metric that gives an indication of capital efficiency.

Predicting future business success

Taken together, these indicators can give someone a good idea of how high the quality of revenue in a given software business is. Good Series A VCs will use these to measure how indicative your traction is in predicting future business success. A lot of these measures are interlinked and should be looked at together rather than in isolation. In combination, they can give a good overview of the health of your go-to-market motion and quality of revenue. 

In order to help you see where you fall on all of these, we have pulled together some benchmarks that we consider to be reasonably representative. They are a mix of our experiences, input from Series A VCs, and general wisdom from the main proponents of some of these (like David Sacks and ScaleVP). Opinions will range widely and there are a ton of resources available on the internet, so take these as our guidance rather than absolute truths.

Assess Revenue Quality

List of Abbreviations:

Compound Monthly Growth Rate (CMGR)
Annual Recurring Revenue (ARR)
Year-on-Year (Y-o-Y)
Net Revenue Retention (NRR)
Customer Acquisition Cost (CAC)
Lifetime Value (LTV)
Annual Contract Value (ACV)

If you have feedback on this blog post, our SaaS & Infra team spends far more time of the day thinking about these topics than is probably healthy and advisable. Come find us at saas@speedinvest.com or on LinkedIn and Twitter: @fredhgnr, @DominikTo, @AudreyHandem, @YTR4N_, and @markus0lang.

Want more updates on our portfolio? Sign up for our monthly newsletter and follow us on LinkedIn.

From The Blog

Navigating the AI Era: A Survival Guide for B2B SaaS Founders

There's no denying that we have firmly entered the AI era. But how and when should B2B SaaS founders begin implementing AI into their products and services? Frederik Hagenauer shares 3 concrete pieces of advice.

How Revyze is shaping the future of education for Gen Z

We are constantly on the lookout for innovative companies that have the potential to reshape industries and create lasting impact. That’s exactly what we found in Revyze, a Paris-based Edtech redefining how Gen Z approaches learning.

Smart Solutions in Healthcare: How AI is Shaping the Future of Medicine

Speedinvest joins forces with Dealroom to take a detailed dive into the current landscape of trends, emerging technologies, and young companies using AI to shape the future of medicine.