The Definitive Guide To a Successful SaaS Controlling Setup
We’ve spent years perfecting our SaaS controlling setup. Here’s how you can copy what we’ve built, incl. KPIs and templates.
Any VC will happily tell you about the handful of metrics that really let them compare SaaS companies ‘at a glance’. However, there is scant advice on how to actually, reliably produce the numbers you need to run a SaaS startup. This article will help you build a controlling setup that delivers what you need to steer a growing team and answer any investor questions with confidence.
To get you started, I’ll reveal the controlling process we’ve been perfecting at awork over the last 8 years including a complete list of important KPIs and ways to consistently measure their development.
Based on this you‘ll be able to copy the setup that has allowed us to manage several funding rounds, steer through liquidity shortages and build our user-base to more than 15.000 paid business-accounts.
Why SaaS companies with a superior controlling setup win
In 2020, they days where any type of B2B-SaaS was by definition an uncontested market with enough volume for limitless growth are long over. Being ‘in the cloud’ with your business application is no longer enough to move ahead of the competition and into blue ocean territory.
SaaS is a red ocean — and your controlling tools are your shark’s teeth.
The incumbent sharks in SaaS (Salesforce, Dropbox, the big G, and all the rest) have virtually limitless resources. But a firm grip on your business model metrics can give you the edge you need to carve out a profitable and growing niche in a highly contested industry. If you’re sure about your conversion rates and acquisition costs, you’ll be able to outbid your competition for the marketing placements that really matter. Gross profit margins of 30% and more are anything but unusual, if you get this right.
What you can’t measure, doesn’t exist
The huge advantage of SaaS business models is their built-in measurability. Using this as a strategic tool also means that campaigns and projects you can’t measure are a problem for your business — there is just too much danger of wasting resources on them. Which is why we invest heavily in tracking infrastructure of all kinds.
Up-to-date, reliable and meaningful reports let us invest into the right marketing campaigns, steer through liquidity shortages, quickly answer investors’ questions, and create commitment within the team.
The 3 crucial elements of a successful controlling setup
We’ve been developing our controlling framework for more than 8 years and it is a living thing. We keep automating, switching out the tool stack, replacing KPIs for more accurate ones and so on, because we recognise it for the strategic advantage that it is.
From our experience, different projects and purposes require different numbers and levels of detail in their data. The major tools you’ll need to provide them are the company-level budget, the liquidity forecast, and the tactical KPIs. Below I’ll explain how they work.
1 The strategic company-level budget
This is where we plan our teams’ budgets. Creating it is an annual strategic process that’s updated once a month based on current forecasts.
It solves the challenge of having to report against a fixed annual plan for our investors in a constantly changing environment. It therefore includes the frequently updated forecast. The underlying agreement we have with our investors is that we can move budget freely within our top-level cost centers (like marketing or infrastructure) but for significant unplanned shifts between them, we’d have to get renewed approval.
Inputs for a company-level budget
Our company-level budget is an annual spreadsheet that does a great job at cost-controlling. What it does and how it works:
- PLAN-Data: Contains annual plan values for our team-budgets (we use these as cost centers in our accounting). These are the numbers we coordinate with and get approval from our shareholders annually.
- ACTUAL-Data: Imports our monthly accounting entries (in our case it uses monthly DATEV-data we export). We’ve written a bit of VBA-code that transforms the raw accounting data into a more convenient format. Once imported, every head-of gets their team’s monthly expenses and can update their forecast.
- FORECAST-Data: Every team’s head-of submits a monthly updated budget forecast for the rest of the year in the form of a spreadsheet template.
Sounds complex, but apart from the underlying accounting process, it only takes our head-ofs a few minutes per month to update those forecasts. Larger and more variable budgets like marketing have their own financial planning process and just generate a forecast as its result. Based on this data we calculate a summary that contains basic financial KPIs (cost, billing, revenue, EBT etc.).
Side-note for the experts: The particularities of B2B-SaaS (up-front licence fees, different payment cycles etc.) together with official accounting legislation result in our revenues usually being significantly lower than billing (this gets worse for later months of the year, as more of the revenue from billed licence fees need to be deferred to the next year). For operational purposes we therefore usually work with billing data only.
2 The reliable liquidity forecast
Our liquidity forecast is, no surprise, one of the most important day-to-day controlling tools and my co-founder has been perfecting its data sources for years. In the end, this is a spreadsheet as well, albeit a sophisticated one.
This report boils down to 2 important spreadsheet lines: cash-balance and cash-balance incl. credit lines on different levels of granularity: daily, weekly and monthly for a period of about 12 to 18 months.
How we use this information depends on the current business situation. In general, we use the liquidity forecast at least once a month to plan and update our investment budgets. We also identify potential liquidity shortages 6 to 9 months before they occur (giving us enough time to react). When the need for fast and short term planning arises (COVID-19 is a good example), the tool allows us to switch to a weekly or even daily perspective and adjust cash flows more or less live as we gather information on burn-rate, remaining runway, etc.
Inputs for a reliable liquidity forecast
We use a Google Sheet because of its easy accessibility via API. Its mostly automated data sources are:
- Billing forecast for existing customer contracts: We pull this information from Chargebee, our subscription management tool, via API.
- Billing forecast for new customers (sales forecast): We use a factor on our new business MRR to estimate billing (e.g. 1€ new MRR = 10€ billing). This is based on historical average payment cycles. For the next month, this forecast is updated manually based on our head-of-sales’ estimation. Future months use a conservatively discounted plan value (from our budget).
- All open invoices incl. their due dates: Also pulled from Chargebee. This list allows for manual adjustment of estimated payment dates. Usually, we just leave this alone — our dunning process works quite well. However, when push comes to shove and significant invoices remain open, we do intervene manually.
- A detailed cost forecast incl. payment dates: For larger recurring payments there is a list with the actual recurring payment date of the month (such as salaries, large ad accounts like Google, Facebook etc., servers and infrastructure, office rent, etc.).
- Our bank accounts’ cash balance: Well, it’s just that. No magic involved ;-)
- Our available credit lines: We use our credit lines to smooth out peaks due to lumped billing (e.g. there is a tendency to invest in business software at the end of the year, so this is where our billing peaks).
- A list of central settings: Parameters can easily be adjusted. For example avg. payment cycles, factor of MRR to billing, discounts on sales forecasts, expected churn, avg. time invoices remain open, etc.
In the end, while most of these data sources are automated, some degree of manual intervention is always required. For example: Our outgoing invoices can range from 10 € to 100.000+ € per invoice. While the former can be left to the automated process, the latter will always require a little human judgement to plan.
3 The tactical SaaS metrics
Finally, the part of our controlling-setup that matches most what you would expect from a growing SaaS company. This is where we collect our unit-economics and other product and process related numbers. See below for a complete list of KPIs we track on a monthly basis including a brief explanation of their impact.
These are the numbers we use to evaluate marketing experiments, short-term sales success, product usage, etc. Because of these many applications, they need to be up-to-date and as precise as possible.
Inputs for precise SaaS metrics
In terms of infrastructure for these KPIs, we’ve iterated a lot over the years. We’ve tried using standardised tools like ChartMogul or the Revenue Story module offered by our subscription management platform (Chargebee) for years. While these do a reasonably good job at the basics (MRR development, basic cohort analysis), we were ultimately disappointed. The major reasons for finally deciding to go our own way:
- Steep pricing for basic controlling reports once MRR scales
- Often inexplicable (yet obvious) errors in the data and poor support in resolving them
- Limitation to the absolute standard in terms of billing and contract models (and we experiment frequently with these)
- Many relevant SaaS KPIs require more than “just” contract data and the standard tools usually have no room for them
For contract data, we now use a self-developed controlling platform that integrates via API with our subscription management and tracking systems. It delivers only a fraction of the reports that most standardised tools have to offer (theoretically) but they are the ones we really use for steering purposes and they deliver accurate numbers for our pricing and billing policies. They are: MRR development (incl. expansions, contractions, churn etc.), cohort based conversion rates, invoicing (split by new vs. existing contracts), and churn (both scheduled and effective).
For cost data, we use the tools described above (global cost controlling and liquidity).
Finally, we blend this with our marketing attribution data (a topic for a different novel) and activity data from Mixpanel (this is where we track feature usage etc.).
End result:
Surprise 🎉, a simple Google Sheet with daily updated data :-)
The SaaS metrics every controlling setup should track
This is a complete list of all the KPIs we track for our decision-making process. While some are quite specific to team oriented B2B-SaaS, most are really quite universal for subscription-based businesses.
General SaaS
- Current total MRR under contract
- Number of customers with active contracts
- Number of users in active contracts
- Conversion rate signup → subscription
- MRR growth monthly
- Avg. MRR / customer (ARPA)
- Avg. MRR / user
- Avg. users / customer
- Customer lifetime value (LTV)
- MRR lifetime value
- Campaign cost / signup
- Campaign cost / customer (CAC)
- Campaign cost / user
- Campaign cost / MRR
- Avg. payment cycle
- Avg. months to cash break even
- LTV / CAC
- New scheduled cancellations (MRR)
- New scheduled cancellations (% of MRR)
- Gross MRR churn (abs)
- Gross MRR churn (%)
- Net MRR churn (abs)
- Net MRR churn (%)
Marketing
- Signups per channel (mobile vs. web, organic vs. paid)
Sales
- Avg. sales cycle
- Sold services (€)
- Qualification rate of incoming deals
Product
- Weekly active users (WAU)
- New teams (by industry)
- New active teams (by industry)
- New active users
- Conversion rates along funnel (by industry)
Leveraging the controlling setup for growth
There are three kinds of situations where we benefit from our controlling setup: Special projects, continuous steering and transparency.
Special projects are the most complex, yet the easiest to describe: Preparing business plans, funding rounds, due diligence or long term strategic decisions — all of these are based on the same central data and usually require deep dives from there.
Continuous steering is best described by our monthly controlling meeting. In the first part (about 45min), my co-founders and I do a detailed run-through of all the budgets and talk about the need for funding etc. The second part (another 45min) is together with our team-leads and everybody gives some context to “their” KPIs. We discuss outliers, developments and short-term targets.
We try to create as much transparency around our business model as possible for the entire team. This sharpens a shared understanding of everyone’s impact, the targets we have and how we’re doing as a team and company. Most of this is based on our controlling infrastructure:
- A (very) central dashboard in our office rotates through about two dozen of the most important KPIs and is accessible to everyone
- Regular presentations in our All Hands meetings include our financial and product performance
- This gives us the opportunity to answer questions about our business situation rather freely and in depth and use the data and tools we have to back up strategic decisions
Wrapping up
SaaS business models have a built-in strength: superb measurability. Getting the controlling setup right can therefore deliver tremendous strategic insight.
Every successful SaaS controlling consists of three major building blocks:
- The strategic company budget for mid and long term planning, resource allocation and investors’ decisions
- A reliable liquidity forecast for day-to-day decision making and a firm grip on the company’s burn rate and run way
- Tactical SaaS metrics for evaluating the health of the business model itself, including unit economics and the long term potential for profit
Building these Elements requires the technical skills to extract, merge and summarise data as well as deep understanding of one’s business model and its KPIs.
Teams setting up a framework like the one we built at awork therefore usually include a (co-)founder with financial expertise as well as an engineer. While this may seem like an expensive project team for an internal process, it is well worth the time and will pay off in the long term as it enables
- precise financial decisions,
- higher returns on marketing investments, and
- confident negotiations with (potential) investors.
Hi, I’m Tobi 👋, co-founder at HQLabs // awork.io where I head marketing & sales teams for two B2B-SaaS products. We’re a Hamburg, Germany based productivity company and love to build delightful products that help teams grow. While I hold a degree in mechanical engineering, I found my passion in entrepreneurship and team culture rather than mechanics. I firmly believe that we can improve our lives by unsucking work.
