Metrics to focus on during the growth stage of your SaaS journey: Part 1
This series was written in light of a talk I gave at the Aleph.Bet: Building a Successful SaaS Business workshop which took place on February 21, 2018 (to view the full slide deck click here).
The SaaS industry has evolved so much in the last ten years. We’ve standardized many ways of measuring and benchmarking different SaaS companies and if you’re a SaaS founder / SaaS enthusiast / metrics geek, we can assume you’re familiar with some basic SaaS terms like ARR (Annual Recurring Revenue), CAC (Customer Acquisition Cost) / CAC Payback Period, LTV (Lifetime Value) and ACV (Annual Contract Value).
As your company grows though, you may find that these metrics are not enough to effectively scale your business. They are definitely necessary to track the progress of your company, and they’re an absolute must if you’re planning to raise capital, but — they’re insufficient to deeply understand how to maximize your company’s growth trajectory or to understand which figures may come back to haunt you as your revenue increases.
In this post, I’ll share some of the challenges and additional metrics that we now track at monday.com, which help us scale effectively. I’m pretty sure you’ll find them relevant for your company, too…or at least some of them :)
Intent and Predictions:
Acquiring new customers requires a lot of cash. Often, customer acquisition grows into your largest expense as you scale. The more money you efficiently invest into performance marketing, the more customers you acquire, the faster you scale your company.
At monday.com, we’re metrics-obsessed and this mentality has been essential to our growth. We built our own BI tool, fondly called BigBrain, which tracks every dollar that goes into the company, every dollar that goes out, and just about every KPI in between.
As we scale, we expanded our marketing budget from $5K per day to nearly $60K per day. In addition to that, we’ve always offered a 14-day trial to new users. We’ve stumbled across situations where we spend large amounts of money on marketing, only to find out 14 or 21 days later, that the marketing audience we reached didn’t convert as well as expected. As a result, a ton of cash goes down the drain.
In order to improve that, we built a prediction model (which you can see below) that assesses our daily signups and predicts how many will convert to paying users:
These models are super important as our performance marketing budgets continue to scale rapidly. Because of the free trial we offer, we know we’re not going to get our money back for 2 weeks (at least!). The model takes into account our potential user’s activity within the system and outside. Outside of system, we evaluate things like the source of the traffic or the operating system used, etc. And within the system, we look at which features are used within the first 24 hours, how many users are invited, and so on. We rely on our hyper-accurate prediction model to keep us on track. The model helps us decide where to spend every marketing dollar. If we see a campaign is doing well, we will increase the budget but if we see it’s underperforming, we can adjust the budget almost in real-time.
Sometimes, it can happen that we receive tons of sign-ups but they do not convert well. So far, the models don’t consider specific behavioral trends of different countries. This can result in a situation where we get lots of signups with great intent but they ultimately have poor conversion. We’re always refining our models to reflect what we learn and it remains a critical metric for us. I highly recommend figuring out something similar that makes sense for your business to always keep you alert.
Cash Payback and Cash Cycle:
Measuring your “cash payback” is essential. Cash payback is really the measurement of how much time it takes to return (reinvest) your marketing budget…and in our case, keep our sanity. Why is this so important? Because no company has endless buckets of money. Tracking your cash payback helps you figure out the most efficient way to utilize your funding, how to maintain strong cash flow, and how to best reinvest the money to increase your growth. Other related metrics like ARR, CAC, LTV or churn, don’t take cash flow into account and that’s an important differentiator.
Being the metrics maniacs that we are, here’s a snapshot of how we measure cash payback at monday.com:
But measuring cash payback is not enough, let’s talk Cash Cycle…
It’s great to know when your company reaches 100% positive ROI on your marketing budget, but are two companies with the same payback period equal? Well actually, they’re not.
Take the example of two companies that both have a 7-month payback period:
The rate of return (as seen above: 80% after the first month and the other 20% after 6 months vs. 30% return on the first month and the remaining 70% after 6 months) is even more critical than the payback period. The faster you get your money back, the faster you can reinvest it into marketing again, and accelerate your growth rate.
We measure Cash Cycle as the ratio between a dollar invested in January and how many times we can reinvest it repeatedly throughout the year, considering our rate of return. In comparing Company A and Company B above, we see the same cash payback time but with very different cash efficiencies due to different Cash Cycle metrics.
Sales Net Contribution:
So, we are new to the sales arena. We operated (almost) entirely as a no-touch funnel until we reached 10,000 paying companies. Once we passed that landmark, we decided to add an “inside sales” team to help grow accounts that signed up through the funnel. Our overall goal with the team is to optimize the ARR overlap of the no-touch funnel and the sales funnel. We optimize our sales-qualified leads (SQLs) to be the ones with the biggest net gain potential. All leads go through BigBrain, which assesses them according to a bunch of algorithms evaluating account size, intent, activity, signup date, and many other differentiating factors. We determined that focusing on these qualified leads has the greatest impact on the overall company ARR. We built the team to enhance our growth so it’s really important to effectively measure their efforts to make sure they’re succeeding.
To understand an essential part of how we measure sales net contribution, allow me to introduce you to Mushon :) We added a fake alias to our sales team named Mushon and we assign him quality leads as we do to the rest of our reps. Unlike the rest of our reps though, Mushon does nothing to improve the monetization of the leads he’s assigned. We use his presence to set benchmarks to assess the impact of the actual humans on the team. To achieve this, we measure their net revenue contribution instead of total added revenue. We deduct the revenue “generated” by Mushon to determine the team’s actual contribution, in contract to what would happen naturally from the no-touch funnel. To make a long story short, the actual humans we hired rock and make a huge impact. But, Mushon is critical to knowing just how effective they are.
Stay tuned for Part 2 of this series where we will discuss churn, growth speed, and how to align your team!
Eran Zinman is the Co-Founder & CTO @ monday.com
At monday.com, our philosophy is complete transparency. If you’re interested in any additional metrics or advice, please reach out to Lior Krengel at firstname.lastname@example.org.
First launched in 2014, monday.com is a team management tool designed to be the first thing our users check upon arriving in the office and the last before they leave. It’s the platform on which they run the core of their business. The tool is used by teams of all sizes, from two freelancers working together to thousands collaborating across the globe, from startups to Fortune 500 companies.
monday.com has 23,415 paying teams, $22M in ARR, and raised $34.1 Million to date.
Disclaimer: monday.com is not an Aleph portfolio company