Tomasz Tunguz
Benchmarks for *aaS Businesses

Tomasz is a Partner with Redpoint Ventures. As a former Google Product Manager he introduced AdSense to Europe and Asia, and managed the Google-MySpace partnership. He also developed business management systems for the Department of Homeland Security and co-founded a billing and document management system for law firms in Chile.

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Thanks, everyone for having me, James in particular for inviting me. It's been a real pleasure to see Heavybit grow into the huge success that it is today. I'm thrilled to be here.

As Tom mentioned, I like to invest, or we as a firm like to invest in software-as-a-service and platform-as-a-service companies. The great part about those businesses is that they tend to be very technically focused and they tend to be started by engineers a lot of the time. I'm also an engineer, but what I know about an engineer's mind is they like to make decisions, or generally engineers like to make decisions using data. As I started to work with a lot of these businesses quite a few questions come up throughout the progress and the evolution of these as-a-service businesses, as to how you develop the business side of the business in addition to the engineering side, which seems to be the expertise of a lot of the founders.

My goal in this talk is really to kind of share with you a lot of the answers that I've developed for founders that I work with as to how you build the business side of the business and what benchmarks exist in the market that you can use as you build your developer-facing services or platform-as-a-service businesses or software-as-a-service businesses. That's where we're going to get started. If there are any questions throughout the talk, feel free to interrupt. This is meant to be totally conversational.

First things first, every business is a snowflake, every business is unique. These benchmarks aren't rules. They're not recipes for success. They're just data points. And I'm happy to walk through the biases, and the sample sizes, and the details of all those analyses; but I just want to get that out front.

Revenue growth is really kind of the ultimate goal of most businesses that we invest in as venture investors.

A very simple way of thinking about revenue growth is you grow revenue by increasing your customers, by increasing the average amount you charge those customers, and by maximizing the difference between the growth rate of the business and the number of customers who churn. What I've done is I'm going to structure this presentation around this equation, because we're all engineers, and we'll talk about each component.

This is a chart. On the Y axis you've got annual revenue, revenue growth, and on the X axis you have the log10 of enterprise value in dollars. These are for all the publicly traded as-a-service businesses in the market today. And you can see that there's actually a pretty strong correlation. There are about 36 publicly traded as-a-service businesses and there's a really strong correlation, actually the R2 is about 0.56, between revenue growth and the value of the business. So what does that tell you?

It means in order to be a valuable business you have to grow really fast.

The most valuable businesses grow around 200%, in the last year, and that includes businesses like Workday, Viva, which just went public, FireEye and a bunch of others. This is why revenue growth is so important and that's why I start with it in the equation.

If you look at those companies on a cohort basis by number of years since founding, this is the revenue growth actually smoothed over the life of those businesses. They started around 0 and then within 5 years they're roughly at around $75 million on average. And so what we want, I think, as founders and as investors is to find companies that have these kinds of characteristics and to inform those businesses and founders so that they can create these kinds of businesses that grow really fast so that everyone in the company benefits.

Let's first talk about customers. A lot of the businesses that are in this room and in Heavybit are freemium businesses, and at the bottom of the freemium pyramid you have freemium marketing. And that freemium marketing can be any number of different things. For Zendesk, it was really community marketing. For Expensify, it's app store. There are lots and lots of different — for some businesses like Intercom, it's all done through content marketing. Lots of individual users sign up and then there's a monetization vector.

Ideally at some point what ends up happening is the business builds an inside sales team in order to capture the larger customers. This is the customer acquisition model we'll be talking about.

One of the key questions that comes around from technical founders is: What are the relative sizes of the sales team and the engineering teams over the company's life? How much should I be investing in building the product versus actually taking the product to market and selling it and putting it in the hands of customers? Of the 36 publicly traded companies that I showed you at the beginning, this is the ratio between their spend in sales and marketing, and research and development. In order words, customer acquisition versus product. You can see that over the life of the business it's a 2:1 ratio on average for these companies.

For every dollar they put into engineering, they tend to invest two dollars into sales and marketing. That trend continues basically over the life of the business.

When we think about what those sales teams ought to be doing, one of the key questions is: How do I measure the success of a salesperson? When I started in the venture business I didn't know how much a salesperson was paid, what the productivity of that salesperson ought to be, what the differences between an inside and an outside sales rep are.

An inside sales rep, as we talked about before, is someone who they're called inside sales because they're not making outbound calls. There's business coming in, there are users signing up, there's Google starting to use your product, or there's Heroku that's starting to use your product and so you call them. You've got a bunch of data about that customer and your goal is to close them and convert them and make them pay you more money or pay you money at all. An outside sales rep is a very different kind of salesperson. An outside sales rep sells by being out in the field, by building relationships, by playing golf, going out to steak dinners, all that kind of stuff.

The sales cycles for these 2 kinds of sales reps are very different. The typical inside sales rep, and we'll walk through the numbers in a second, but the typical inside sales rep sells about 10 customers a quarter, while the typical outside sales rep sells about 4 a year, 4 or 5 a year. Let's walk through these numbers and we can kind of differentiate the difference between an inside and salesperson.

The first line here is OTE. That's a sales term that stands for "On Target Earnings." Every salesperson when they sign up for a job they're given a quota, which is the amount of money they need to sell of the product in a given year or some given period. For an inside salesperson, that's roughly around $300,000 to $600,000 depending on the product. For an outside salesperson, that's $1 million to $2 million; if they hit that quota, then their OTE or on target earnings is their total compensation. Typically for an inside sales rep, depending on the sector, it's around 65K — half of that is salary, half of that is bonus. Then for an outside sales rep, that's split differently. Instead of being split 50/50, it's split 25/75 — 25% salary, 75% bonus.

You can see the second line is the quota. The third is the average size of the sale that they typically make. An inside sales rep often sells something between 5K to 25K a year in revenue. An outside salesperson is selling somewhere between $250,000 a year to multimillion dollar contracts depending on the seniority of that salesperson. Just kind of walking through the math, that means that the inside salesperson has to sell 10 customers a quarter. The outside salesperson, I said it's 4 to 5 a year.

Typically what we see with inside sales teams is their close rate. The close rate is out of 5 customers they call, 1 of them will convert to be paid. That's a 20% close rate. For field sales reps, because the field sales rep is much more individualized and personalized, is around 30% to 50%. And if you back that out, that means you probably need 200 leads for an inside sales rep in order for them to hit their quota; you need about 17 for an outside sales rep. The ratio between the revenue they generate to the cost of the sale is about 5:3.

What I'm trying to give you here is a sense of how a sales team operates, how expensive it is, and what the return on investment ought to be typically for these kinds of businesses.

Again, for those 36 publicly traded companies, they invest a lot of time into acquiring customers and the question is: How much should I be spending to acquire these customers? On a cohort basis and averaged out over the entire group, this is the average payback period, or also known as the sales efficiency or magic number, for these as-a-service businesses. The sales efficiency is: How much did I spend last quarter to generate this quarter's incremental revenue? Or, how much did I spend last year in sales and marketing to acquire this year's incremental revenue? If you spend $1 this year, how many dollars do you get next year out of revenue?

The higher the multiple, the more efficientyour sales process is, and actually the inverse of that multiple is the payback period.

How long does it take for your customer to be paying in order for you to recoup the costs of acquiring that customer, also known as the payback period?

The typical publicly traded company takes about 15 months to pay back the acquisition of their customers. For startups, best in class tend to be between 3 to 6 months, so all the dollars invested in sales and marketing can be recouped in 3 to 6 months.

At scale we kind of see businesses with a sales efficiency ratio between 0.8 and 1.2. The higher that number, the more you want to invest in sales because what that tells you is each incremental dollar in sales generates a disproportionate amount of revenue back to the business and you can grow really, really fast. And this is an arbitrary or a very, very deterministic metric of understanding how performant the sales team is.

Moving on from customers, we can talk about average contract value. Average contract value is just a really fancy word of saying pricing. This is kind of the way to think about pricing for as-a-service businesses. There are typically four pricing models I've seen in the market. The first and the most common is freemium. And a freemium, we all know what this is. Typically what ends up happening is a user uses a product. The value to the end user increases with time as you put in more data.

Evernote is a great example. At the beginning, you're not really willing to pay for it. As you fill in more and more notebooks, the ability to search across that data becomes more valuable and so you end up being paid for it. Typically those products are pretty simple. Most of the time the end user actually ends up buying it, but sometimes it actually goes up to a purchaser. So in the case of Expensify, which is a freemium expense reporting business, individual employees within a company adopt Expensify and then convince an accountant to buy a site license. That would be a case where the end user actually doesn't buy, but it's the controller, or the CFO, or the VP of Finance who does.

And typically for most freemium businesses, the average seat price is somewhere between $5 to $75. On the $5 to $10 range, those tend to be kind of more "consumery" products, and on the $75 range you have products like CRM tools or kind of real workflow tools.

The next three pricing structures or pricing models, they're all kind of marketing tactics in order to entice customers in order to convert; and the next three are kind of geared at average contract values in the $2,000 to $25,000, $100,000 a year range.

The freemium works really well when you have a huge funnel of incoming users, a huge number of leads, and your goal is to convert somewhere between 1% to 4% of those leads into paying customers, and the market size is large enough to generate a big business given that funnel structure.

When you're targeting a smaller set of users, say fewer than 1 million, your goal then is to use an inside sales team in order to convert those customers. And the marketing tactics that SaaS companies or platform-as-a-service companies use, they're threefold.

The first is a limited free trial — Salesforce uses this extensively. They first started with a 30-day free trial, and then they tested a 7-day free trial and a 14-day free trial. They found no difference between the 14-day conversion rate and the 30-day conversion rate. Typically what ends up happening is smaller free trials for these kinds of products converts just as much because the users want to end up either committing to the product immediately or they churn anyway.

Limited free trial works really well when a user is trying to understand a product and will really only understand it when they experience it. It's another product like a freemium product whose user value increases with time. The product complexity for limited free trials tends to be more complex, like CRM tools. Often the end user buys, but sometimes not, and the average seat value is kind of low or medium. As you move up towards the ACVs, you get these different structures. One is an upfront payment and the other is a money back guarantee.

An upfront payment is: the only way that a customer can use your product is if they pay you upfront for a year. Those tend to work really well when a user can perceive the value right away, they think it's an absolute must-have product, and so the product complexity tends to be simple. The end user often buys, so the decision making process is fast and tight, and the average seat price is very high and justifies the cost of an inside salesperson.

Then the last one is a money back guarantee. It's basically a free trial that's subsidized by a customer paying for 3 months or 6 months, and it works for those kind of categories and products.

This is a conceptual framework for typically how we tend to think about pricing structures. There's lots of variants, different sales teams might move from a limited free trial to money back guarantee; but these are all the different vectors that we see.

Q: On that last slide, what do you think the value is of Low/Medium/High?

A: I think a low seat value is probably $5 to $25 a month, and then a higher seat value is $50 to $75. Those don't overlap, but that's kind of how I think about it. On an annualized basis, if you were to look at it on a per customer basis, the freemium products tend to generate somewhere between $500 to $2,000 per user/company per year, and then the mid-range products tend to generate somewhere between $25,000 to $150,000 a customer per year. Then high would be north of that; so high is anything a quarter of a million and above.

Q: Can you give me an example of the upfront payment where it's an obvious must-have and it's a simple product?

A: Yeah, it tends to be things like LinkedIn would be a really good example. The recruiter product for LinkedIn — you cannot try that product as a recruiter because you would extract so much value from your initial usage that you wouldn't want to pay for it anymore. Often they tend to be social network products coupled with SaaS products.

Any other questions on this slide? Okay.

Let's talk about growth rate. How do you deduce growth? There are three ways to grow that we see in these as-a-service businesses. The first is to grow through sales teams. Let's walk through this table. There are 2 tables here; the first is a hypothetical business. The first line, the customer's line, demonstrates a growth from 100 customers to 50,000 paying customers. The average contract value, the amount the typical customer pays per year, is held flat at 20,000.

You can see how the revenue scales, you can see how revenue churns, and then you can see over time the typical SaaS business tends to churn between 1.5% to 3% of its revenue per month. You annualize that, it's roughly 20%. So they're losing 1/5 of their business every year. That's the leaky bucket.

If you really want to grow, one of the key parts is mitigating that churn risk.

You can see as it grows — at a $20 million clip, the business is losing $4 million every year. In order to just hold its revenue steady it needs that $4 million in incremental business every year. It's a real weight on the business. And there are three strategies to accomplish mitigating this churn. The first is to replace the customers who've churned with new customers. Here's all the math, then that net is it's actually really expensive to do it that way.

That's because acquiring new customers is the most expensive way to grow.

In order to recoup $40 million in revenue at the 10,000 customer mark, you need to invest about $50 million in this hypothetical scenario, if your payback period is 14 months, 15 months.

The next more efficient way, but still less efficient way is to upsell your existing customers. You have customers that are leaving, what you want is to grow your existing customers and have them pay more and more over time. This is a model where what you have is you have a team that's a customer success team and they use their time in order to get customers to buy more products. And this is a more efficient model. We can walk through the math later.

And then the most efficient model is if customers grow by themselves. You guys will be most familiar with this with Amazon Web Services. This is utility-based pricing where customers just kind of grow by virtue of their own growth and the incremental investment that you need to invest in order to have those customers grow is basically minimal. It's just product development work. Most of the businesses that we work with, they use a combination of these three.

But, the more that you can grow organically, the more efficiently you can grow, the more capital efficient business you can build and the better valuation you can command.

The last component of the equation is churn. As I mentioned before, the typical as-a-service business churns between 1% to 3% of customers per month. This is a chart I use with a lot of our companies. It's a cohort chart and it's a Revenue at Risk chart. Every month 1% to 3% of our revenue is at risk, and what we do is we look for the months in which a lot of revenue is at risk because it's not evenly distributed. The sales process actually is very seasonal.

This chart is showing on the X axis the months since a customer became paid and on the Y axis the revenue that that customer generates. And in the board meetings what we do is we look at the ones who are coming up on their, say 12-month renewal cycle or their 24-month renewal cycle on their contract and then we double click on the ones that are really, really big and we make sure that we keep those customers because they disproportionately impact churn.

And then the next question is: Well, if our goal is to mitigate revenue at risk, how much should a business spend mitigating revenue at risk?

Let's take a look at the unit economics for a business in their first year. If you sign up a business, let's say we've got a hypothetical business that's got a customer who's going to spend about 24 months on a product. The first 15 months of that is the revenue that we use to pay back the costs to acquire the customer, and then the 15 to 24-month mark is what's known as the contribution margin, that's all the profit. If they were to churn, then the revenue coming from this customer would go away.

But if we were to invest a bunch of time — here we've got the same chart and what we're trying to do is we're trying to elongate the life of the customer from 24 months to 36 months. We've got the same thing; we've got the first 15 months allocated towards acquiring the customer, the next few months is contribution margin, some period of time where we actually invest in customer support and service in order to keep that customer. And then the last part is a saved contribution margin, additional profit as a result of having made the investment and keeping that customer.

And if you do the math, a really great simple rule of thumb is you want to spend about three months worth of a customer's revenue in saving customers. That's what this all kind of boils down to. That's kind of the equation in a nutshell. I just wanted to give you a high level overview of the way that I look at these businesses.

If you're able to maximize your revenue growth in this way, then you can benefit from what's happening in the market today.

This is a chart of the valuations, basically of valuation to revenue multiples of as-a-service businesses over the last, call it 10 years, 9 years. The 2 different lines are: the red ones are all businesses and the blue ones are high fliers. High fliers tend to be newer IPOs or better known brand names. You can see that these companies are fetching multiples of 20x revenue which is really unheard of in the market. Part of it is there's a lot of enthusiasm around these subscription businesses and investor really darlings at this point.

The great part about this for entrepreneurs is the valuations in the public markets are often very, very quickly reflected in the private markets, which is why we've seen, and I've seen firsthand, pretty dramatic acceleration of as-a-service business valuations of late.

I know that was a lot, but that's my presentation. Thank you very much for the time.