Pavla Munzarova, VP Finance, Mews, explains the importance of investing time in data quality, systems and reporting to give everyone in the business the information they need to make better decisions.

Nailing SaaS metrics in hyper-growth

Pavla Munzarova, VP Finance, Mews, explains the importance of investing time in data quality, systems and reporting to give everyone in the business the information they need to make better decisions.

Highlights

  1. Invest in data, finance systems and automation as early as possible.
  2. Managing cash in hypergrowth is tough - gather all your incoming and outgoing cash flows in one place and get as near real-time as possible.
  3. Empower your business with insights on the metrics and measures that matter most to them.

Summary

Understanding unit economics and underlying capital efficiency is a critical topic for any company, but in particular for SaaS businesses. SaaS business models are becoming increasingly complex with multiple price components. They are recurring revenue businesses, often with large up front acquisition costs, so any contribution that a customer makes will typically be in the second or third year.  Therefore, understanding the basics: how much does it cost to acquire a customer; how much revenue from that customer is contribution after gross margin; how long do we keep them; and how can we grow the revenue associated with that customer in subsequent years, are all incredibly important.  This article is based on an interview with Pavla Munzarova, VP Finance, at Mews recorded in early March, at the start of the current COVID-19 pandemic.  Mews is a Prague-based Hotel Property Management System with customers in more than 50 countries. They have been growing exceptionally fast and have a sophisticated SaaS model: subscriptions; transactional payments; and third party apps from a marketplace.

With such fast growth and a complex business model, how do you think about measuring capital efficiency?

At the start have a really detailed tracking system. Our model is complex with seven different revenue streams. We have subscription fees, which are flat per month, subscription fee per space, we have commission based revenue, depending on the volume of payments within our clients, we also have flat per transaction fees. So there is really pretty much everything you can imagine. So you need sophisticated tracking and data capture and you need to automate it.

The technology you use is really important and something that we definitely had to focus on. In terms of the tracking, we had to build our own. So we developed  tracking within our own product. We capture all the data from the moment the deal is signed and then measure everything and calculate the fees on a monthly basis.

The other part though, is that there needs to be connection between the revenue and the related costs. So this means booking all of the revenues with all of the details of the associated costs and then importing all the details into accounting software. You need to have a certain level of automation to be able to track it - technology and automation are very important.

We use one central database, so all the tracking systems we use are connected. Then for analysis we use Power BI, which we love. We may even have too many dashboards, but it's working pretty well for us.

Then what’s important, of course, is the metrics you choose.

So from our point of view, there are some metrics we want to track and we have benchmarks in place to be able to compare it to other SaaS companies. But there are also areas that you need to analyze with your own metrics, your own KPIs, such as growth and new products and new projects. We are always coming up with our own internal metrics and being quite creative.

In such a complex business, how do you manage cash flow?

When I started with Mews, back in 2016, this was one of the biggest projects for me. I think the key is to know your actual goals in the most detail possible.  

So, for me, the most important part is to get everything down. Create a weekly report with all of the inflows and all of the outflows. Preferably by item/client/supplier level. Then try to group it. Maybe even rank it by importance, by how often you're paying what and when and also check what you need to pay on a weekly or monthly basis, so that you're sure you’re not paying earlier then you have to. This is equally as important the other way round; you need to be on top of your receivables and receivable management. So getting all the inflows in as early as possible is obviously very important, thinking about prepayments for the clients and offering discounts for prepayment for a year or two. So this is the first part: to analyse where you are and then plan the cash flow properly.

Keep this regularly refreshed. Real time is the best, but it's not always possible. But keep a close eye on this, and have a look at the upcoming weeks so you know what's coming. And also look at where the risks may be and have a back up plan so you know that, if you’re not getting this inflow, what you can postpone. I think that cash flow planning is even more crucial than budgeting or reporting, especially in the early stages.

What metrics do you and the leadership team obsess about?

The main one is monthly recurring revenue (MRR), which we look at in different forms. We split it per product, or per revenue model. We also look at MRR in different stages: what's being signed, onboarded and then what’s being recognised. Due to the nature of our business, we usually sign a customer and then only two months later, we're onboarding them and we see merchant or marketplace revenue coming in. So we're analyzing this gap in between each of these phases to be sure that nothing gets delayed.

Next we’re looking at margins. Gross margins, net margins, margins per product.

Then customer acquisition cost, not only per client or per average client, but also revenue acquisition costs, given our client revenues can differ one by one and there are different sizes.

Burn rate, of course, is an important one, I guess for every Series B company out there.

And then we have another set of metrics, around merchant products for example. And a lot of these we have had to come up with ourselves. I think the most important ones are average volumes that are being processed per day. Because in our case, we see seasonality within our client base. So hotels can have higher ADRs (average daily rates) and higher occupancies in the summer months and that's influencing the revenues we recognize.

We need to be looking at this very closely and checking it per territory - right now we are in 55 countries around the world. Then there are different business segments - for example leisure guests or corporate guests. We have to be pretty granular.

We're also looking at interchange rates and bank fees that we’re paying and the invoicing because that has an influence too.

Recently we came up with MPI (merchant performance index), where we look at our share of wallet of the customers and also their total payment volumes that they are processing. Based on that we can compare clients between one another by one metric. And we normalise the values so the index can achieve a score only between 1 and 10. They’re fairly simple metrics for account managers to have a look at and means they can figure out quickly if something's going on.

With such complexity how are you measuring CAC payback?

There are a couple of things that we need to look at in terms of the CAC payback and we need to decompose that into what we call external and internal CAC.

By external we mean the classic view, where we’re just taking the total marketing and sales costs and simply dividing it by the number of subscriptions that were created and built in the system within the same time periods. This one we use to see benchmarks and to see the trends month by month.

But then, when we dig deeper into it, we had to come up with our internal measurement because we see that with our growth rate and with the expansion that we're going through now, CAC is growing faster than we would expect. It's because we just have to hire all these salespeople, which takes time before you see them actually bringing the deals in. So it's two to three months before they get trained. It takes some time before they get the pipeline and it takes more time before the client actually receives their subscription and that the account is created. So the costs happen before the subscriptions are created.

We mapped out the full commercial cost and we split it into groups. We're looking at account management, sales, marketing, events separately and then we're looking at how long does it take for these costs to appear versus gaining the customer and then effectively we are postponing the costs, so that we see the real effect of the CAC and how it's behaving in time.

So that's for the CAC. The other part is the average revenue per client. In our case, it really depends how big the client is. We can have small hotels around 20 rooms. But again, we can also have large ones with 150-200 rooms and then chains. We are now signing bigger customers for higher prices, so that’s something that needs to be taken into consideration when evaluating the data, but is not necessarily changing the calculation.

How are you calculating gross margin?

For us the direct costs would be server costs, customer support and mainly technical customer support costs. Account management we account partially because part of their job is also to upsell and generate revenue. And then we would include any reseller commissions and any percentage costs on the revenue that is really driven directly. So these are the main parts for our platform margin.

Then we recognize merchant margin where that's quite simple. It's all the payment fees, fees to our payment gateway providers, but also interchange and scheme fees that would all come up to this to the section of the P&L.

How are you accounting for logo and revenue churn?

In our case for revenue churn, it gets quite complex. There are platform fees, which all the clients are paying and then merchant fees which can vary and marketplace where it's completely up to customers which integration they subscribe to. So from our point of view, we're mainly looking at the platform churn, because that's basically the mandatory revenue. And that's also how we look at the contracted revenue value at this stage.  For the other types of revenue, what we are really tracking is share of wallet.

What about revenue expansion, or DRR as it’s sometimes known?

We’ve built a cohort analysis in Power BI to analyze this almost real-time. We have to normalise the data, taking seasonality into account.  We have two approaches to understanding revenue expansion.

First is the revenue recognition and the data pulled from our accounting software - that way, we're sure that everything matches and that we are really invoicing what we are recognizing in the bookings, and that also requires some cleanup. So we're checking credit notes and cleaning up the data and then looking really at the net values.

Then on the other hand, we are comparing it with the reports that we have from our CRM. And we're looking at how much are the upsells and what are the regions that influence it the most.

What data would you really like to get hold of, that you just can’t, to understand company performance?

The biggest thing for me is the market data and metrics around merchants. I wish we had more info about the market, the seasonality around the hotels, occupancy and average prices. That's the most important part and really the biggest driver. That's something that influences the business the most and we wish that we could look at it in more detail.

How do you balance your role in managing costs and enabling the business to invest for growth?

This is the most important part. I love analyzing data, maybe too much, which might be the reason why we have so many metrics in the first place. But I think the most important thing is the presentation and creating the focus for the business.

That's why we're trying to achieve having everything visualized in Power BI and giving everybody access to the data.

Within our finance team, we have three data analysts that create all these dashboards, graphs and infographics and also help with automation. We have created this open database with a full transactional breakdown for anybody that wants to have a look. So it's public for the whole company. Anyone can look and see the full detail of the underlying data. And it refreshes on a daily basis not only for revenues but also for the cost. So, for example, if anybody in the company would like to see how much I spent on expenses on my last trip to London, they can.

Also, managers have immediate insights of the data and they see quickly how much they are spending within the team. And then they see the comparison with the plans. So they know if for example CAC is increasing and can do something about it.

In the end, it's all about giving focus because when you have so much data it’s sometimes hard to see what to focus on. We have regular calls with all of the budget owners presenting the data, explaining the metrics behind it, showing them where they can improve, what can be done better. So I think that helps tremendously. Now everyone is asking about budgets which I'm super happy about.

And then we also have our financial results channel, which is company-wide. We share MRR results every first of the month and a financial scorecard, with the top 10 to 15 metrics in one table. Actuals versus target, green or red.

Helping people understand the importance of the data is for me one of the most important things we do.

Lastly, what’s your advice to a Finance Leader dealing with rapid growth?

Get the data, the systems, the reports and the automation in place as early as possible.

Out of these, the most important thing is to take the data, normalise it and create the insights for the business, because that's the main purpose of the finance department.

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