Impressions from the 5th annual PNC SaaS Founder Meetup (AKA PNC SaaS Camp)

We have a tradition here at Point Nine that once a year, we organize a meetup for the founders of our SaaS portfolio companies. The first meetup took place in SF back in 2012 and gave the founders in our (at that time still rather small) portfolio a unique opportunity to learn about what works and what doesn't work in SaaS, compare notes and share war stories.

About two months ago, the 5th annual PNC SaaS Founder Meetup took place in a small lake town a little bit outside of Berlin. To celebrate the 5th anniversary, we turned the meetup into a 48-hour long "camp" and invited about 150 founders and key people from our SaaS portfolio companies, along with a handful of external SaaS experts, to a nice resort close to Potsdam.

Here's a short video that we recorded at the meetup:

Spending two full days and two full nights together not only allowed us to put together an amazing agenda with more than 60 presentations and workshops; it also led to countless great conversations, connections, and friendships. We're truly thankful to all the amazing speakers and attendees who made this possible.

SaaS Funding Napkin, the 2017 edition

Today is January 10, 2017. That means that in ten days, this jerk will become the leader of the free world. Ugh. It still feels surreal to me. In less earth shattering news, the fact that it's 2017 also means that my "SaaS Funding in 2016" napkin needs an update.

As a reminder, in the original post I tried to give a "back of a napkin" answer to this question: What does it take to raise capital, in SaaS, in 2016? Today I'd like to take a stab at the (early) 2017 answer to that question.

Like in the 2016 version, the assumption is that the founding team is relatively "unproven". Founders with significant previous exits can raise large seed rounds at high valuations early on, so the "rules" are different for them. On another note, when I say "what does it take to raise capital" I mean "what does it take to have an easy time raising capital from great investors". If your company doesn't meet the (very high) bar pictured on the napkin it doesn't mean that you won't be able to raise money at all. It just means that it probably won't be easy, that you will likely have to talk to a large number of investors and that you may not be able to raise from a well-known firm.

So, what does it take to raise capital, in SaaS, in early 2017? I don't think a huge amount has changed since I created the first version of the napkin about nine months ago, but here are a few observations:

1) The bar keeps getting higher and higher

I already wrote about the rising table stakes in SaaS two years ago, and since then the bar has kept increasing. The SaaS companies included in Tomasz Tunguz' benchmarking analysis of exceptional Series A companies grew on average from $10k to more than $90k in MRR in their first year of commercialization and then to over $400k of ending MRR in their second:

Twilio, Workday, and Zendesk have shown that the best SaaS companies can get to $100M in ARR in 6-7 years and continue to grow at around 50-70% year-over-year after hitting that milestone. Slack, unbelievably, reached $100M in ARR just 2.5 years after launch. Slack is an outlier even among the outliers, but getting to $100M in about seven years and hitting $300M 2-3 years later is the type growth which the best investors in the Valley are looking for in 2017.

I didn't have to make a lot of changes to the napkin to reflect this since the growth rates that I had put into the 2016 version were already in line with the "T2D3 path". I've increased the Series B amount, valuation and MRR range, though, and because the expectations of later-stage investors trickle down to the earlier stages I've changed the ARR potential number in the "Seed" column from "$100M+ ARR" to "$100-300M+ ARR".

2) Being a workflow tool is no longer enough

Investors are increasingly questioning if you can build a large and long-term sustainable SaaS business by being primarily a workflow tool. The thinking is that every successful software product will eventually be commoditized because it attracts lots of people who will copy the product and offer it for a lower price. That concern isn't new, of course, but given how crowded most SaaS categories have become by now, investors are increasingly looking for additional ways to build moat around a business.

So if you want to raise capital for your SaaS startup in 2017, investors will wonder if you can become a true system of record, build a real platform/ecosystem/marketplace or build a unique data asset over time. The latter option will get particular attention this year, so I highlighted that in the "Defensibility" row of the napkin. The ability to gather large amounts of data from the entire user base, and use that data along with AI/ML to make your software smarter, is one of the big themes at the moment. For what it's worth, I know AI and Machine Learning are a hyped topic but I think the hype is justified.

You might think that some of the things that I've written here – getting to $100M ARR within a few years, thinking about $300M ARR at the seed stage – are just crazy. I won't argue with that. The vast majority of SaaS companies will never get to this level of growth or scale, and yet they can be successful and profitable companies that generate life-changing wealth for the founders and great returns for early investors. VCs need outliers to make their business model work, but that's not your problem. If you think you don't have strong potential to become one of these crazy outliers, maybe VC isn't right for you.

OK. Enough words. Here's the 2017 SaaS Funding Napkin!

(click here for a larger version)

What we're looking for in SaaS in 2017

As the year is coming to an end I’d like to share a few thoughts on what we’ll be looking for in the SaaS world in 2017. This is not meant to be an exhaustive enumeration but rather a brief outline of a few big themes that I feel particularly strongly about.

1) Viral growth and/or negative churn

In the last couple of years I’ve come to the opinion that in order to build a SaaS unicorn you need to have either (a) a highly viral customer acquisition engine or (b) significant negative net churn (that is, a dollar retention rate significantly above 100%). The rationale behind this statement, which might seem odd at first sight, is actually simple math. If you don’t have negative net churn you’re losing an increasing amount of MRR every month to churn, simply because your churn rate is applied to an ever-increasing base. That means that as long as you have positive net churn, you’ll have to add an increasing amount of new MRR from new customers every month just to offset churn. As you’re getting bigger and bigger it will become extremely difficult to maintain a high growth rate if you have to replace an ever-increasing amount of churn – unless you have an inherently viral product.

At a somewhat theoretical level, what I’m saying is that since net churn MRR grows as a function of your MRR base, you better have a mechanism that lets you add new MRR as a function of your existing base as well. I know this is a somewhat simplified way of looking at it and I’m sure there are a few exceptions to this rule, but I’m convinced that almost all SaaS startups that want to become big should strive for viral growth, negative churn, or both.

Related posts (from this blog):

• Why (most) SaaS startups should aim for negative MRR churn
• How fast is fast enough?
• Five ways to build a $100 million business

2) Obsessive focus on user experience

Companies like Slack or Zendesk have shown that a superior user experience can provide a decisive competitive advantage and can become a critical success factor for SaaS businesses. Pundits might object that you don’t win enterprise customers by having a prettier interface. I think that’s shortsighted for at least two reasons.

First, user experience is not only about making the UI more beautiful. As legendary UX expert Jakob Nielsen defines it, “user experience encompasses all aspects of the end user's interaction with a company, its services and its products”. An excellent user experience requires an elegant product that meets the needs of the customer and is a joy to use, but it goes beyond that. The design of your marketing website, the tone of voice of your marketing emails, interactions with customer service – all of this is part of the experience that you offer.

Second, today more and more buying decisions are made by the actual users of the software (e.g. someone in marketing looking for a marketing automation solution) as opposed to the IT department. When the buyer is also the user, usability becomes one of the key decision criteria.

This decentralization of software buying, which has led to the consumerization of enterprise software both from a product as well as a go-to-market perspective, is maybe the most important driver of change in the software industry that we’ve seen in the last 5-10 years. But it’s far from over. Millennials arguably have even less tolerance for slow, bloated, ugly enterprise software. If you grew up with UBER and Spotify, if you’ve never ordered a cab by phone and never went to a store to order a CD, chances are you expect your work software to work flawlessly as well. :-) As millennials continue to rise up the ranks, a focus on great design and a delightful user experience will become even more important for software companies.

Two of our most successful SaaS investments to date, Zendesk and Typeform, owe a large part of their success to what I like to call a “10x” improvement in user experience over the status quo. It will be extremely interesting to see which companies can accomplish a similar quantum leap in 2017 and how it will look like. Will it be a SaaS solution with voice as the primary form of input? A mobile-first SaaS app that truly leverages the smartphone’s camera, sensors and other applications to provide a 10x better user experience? Or a software with a conversational interface, powered by a bot? I don’t have the answer, but I’m pretty sure that new ways to input data – methods that are more natural than dropdown menus or smartphone keyboards – will be a part of it.

Further reading:

• David Skok, Consumerization of the Enterprise – Phase 2
• Mark Suster, The Coming Shift in Enterprise Software
• SketchDeck blog, How design impacts the psychology of sales

3) Smarter software and more automation

Up until recently, the main job of software was to make people more efficient by digitizing paper-based processes, doing calculations and enabling more efficient communication inside and between companies. This has led to huge efficiency gains, and I honestly have no idea how companies used to be operated without computers until 40-50 years ago.

And yet, the biggest disruption is still ahead of us. I am, of course, talking about artificial intelligence (AI). How long it will take until AI will reach human intelligence – or if that’s never going to happen – is an extremely interesting topic that goes far beyond the scope of this post (and of course one that I’m not an expert in). It’s safe to assume, though, that software is getting better and better at more and more tasks which were previously thought to be impossible for computers to learn. Watson’s victory against two “Jeopardy” champions a few years ago and AlphaGo’s win against one of the best Go players are two legendary examples, but there are lots of other, less publicized cases, of computers winning against humans.

If close to 50% of jobs will be done by computers in the not too distant future, as an Oxford University study suggests, this will of course have unprecedented consequences for our society. How those consequences will look like, and if the net impact will be positive or negative for most people, is another extremely interesting topic that I’m not going to delve into here. What’s clear is that this disruptive force will create enormous opportunities for SaaS companies.

With today’s software it can sometimes be hard for a SaaS startup to prove the ROI of its product to prospective customers. Putting a dollar sign on the efficiency gains that a customer can realize by using your software can be difficult, and your product may provide lots of pretty intangible benefits that are hard to quantify. Now imagine that your SaaS solution allows your customers to get work done with significantly less people or maybe no people at all. In that case, the ROI will be pretty obvious.

What if future versions of sales automation software will not make your sales force more efficient but become your sales force? I can’t imagine how bots could take over sales calls … or wine and dine with a client. :) But think about jobs like web-based prospecting, lead qualification or email campaigns and the idea starts to sound a lot less far-fetched.

Although we developed a strong interest in AI in the last few years we have not yet seen a large number of “AI startups” that we fell in love with (one notable exception is our portfolio company Candis, which is automating accounting work). This could be because the industry is still at a nascent stage or because it’s still early days for us in terms of learning and developing an investment thesis around AI, or both. In any case, we’re excited to spend more time on this topic in the coming year!

Further reading:

• Carl Benedikt Frey and Michael A. Osborne, The Future of Employment
• Nick Bostrom, Superintelligence: Paths, Dangers, Strategies

Introducing the French Cloudscape

For some reason we keep finding great early-stage SaaS startups in France, and it's not because of my command of the French language. In the last few years we've invested in four awesome SaaS companies from France: Algolia, Front, Mention and Critizr. We recently did #5, which hasn't been announced yet, and are in advanced talks with a potential #6. Besides our SaaS investments, we're also proud investors in StarOfService, an online marketplace to hire a wide range of professionals. Something is clearly going on in France, and we like it.

Our good connection to the French startup ecosystem was one of the reasons why we picked France as the first country for our "European SaaS Landscape" project. Another reason was that Clément not only speaks French, he IS French, and knows the market very well.

Without further ado, here it is: an industry map of the most important SaaS startups founded in France.

To learn more about our methodology and some of the insights we got while doing the research, check out Clément's post on Medium. If you have any questions, comments or suggestions, give us a shout!

SaaS Financial Plan 2.0

Almost exactly four years ago I published a financial plan template for SaaS startups based on a model that I had created for Zendesk a few years earlier. I received a lot of great feedback on the template and the original post remains one of the most viewed posts on this blog up to this day.

In the last few weeks I've finally found some time to create a "v2" of the template ... just in time for a little Easter gift to the SaaS community. ;-) I'd recommend that you read this post first since it includes some important notes, but if you prefer to check out the template right away click here to download the Excel sheet.

The original v1 model was a very simple plan for early-stage SaaS startups with a low-touch sales model. As I wrote in the original post:

It's a simple plan for an early-stage SaaS startup with a low-touch sales model – a company which markets a SaaS solution via its website, offers a 30 day free trial, gets most of its trial users organically and through online marketing and converts them into paying customer with very little human interaction. Therefore the key drivers of my imaginary startup are organic growth rate, marketing budget and customer acquisition costs, conversion rate, ARPU and churn rate. If you have a SaaS startup with a higher-touch sales model where revenue growth is largely driven by sales headcount, the plan needs to be modified accordingly.

The new version comes with a number of improvements:

• Support for multiple pricing tiers
• Support for annual contracts with annual pre-payments
• Much more solid headcount planning
• Better visibility into "MRR movements"
• Better cash-flow planning
• Charts galore :-)

The downside of these improvements is that the spreadsheet has become significantly larger and more complex, but I tried my best to find the right balance. Also, the vast majority of the numbers in the sheet are calculated and the number of input cells is fairly limited.

The spreadsheet should be pretty self-explanatory but I've included a number of comments in the spreadsheet. Make sure to check them out - some of them are important in order to understand the model (in case you're not familiar with that Excel feature, hover over the little red triangles).

Here are a some additional notes:

1) General comments

• The sheet is hot off the press and given the large amount of formulas I can't rule out that there are bugs. If you find one, please email me at and I'll fix it ASAP.
• Blue numbers indicate data-entry cells. Black and grey numbers are computed.
• The model contains a lot of simplifications. Don't expect that it will perfectly fit your specific business - consider it a starting point.

2.) "Summary" tab

• The "Summary" tab contains only two types of input cells: Your starting bank balance and cash injections from financings. Everything else is calculated, mostly using data from subsequent tabs.
• As with all input cells in the model, consider the values that I've put in to be dummy data. Fill those cells with your own data and assumptions.
• The model doesn't take into account interest or taxes (except for payroll taxes).
• The "Revenues" line shows your end-of-month MRR for the respective month. This is not compliant with the US GAAP definition of "revenues", which uses different revenue recognition rules, but since SaaS companies live and breathe MRR I think it's the right approach for a SaaS financial model.

3.) "Revenues" tab

• The model assumes that you have three pricing tiers. I've called them "Basic", "Pro" and "Enterprise". If you have more or fewer pricing plans you can of course adjust the model accordingly (with some effort). It is further assumed that all Basic and Pro customers are on monthly plans and that all Enterprise customers are on annual plans.
• The model assumes that you're getting signups organically and via paid marketing and that you're converting a percentage of them into Basic customers and Pro customers. You can change the key assumptions such as your organic growth rate and your conversion rates in the grey area on the left.
• The Enterprise customer segment follows a different logic, based on the assumption that Enterprise customer acquisition is sales-driven as opposed to the marketing-driven low-touch sales model for Basic and Pro customers. The key drivers in the Enterprise segment of the model are your revenue targets, sales team quotas and your assumptions for churn and upsells.
• The spreadsheet shows the impact of e.g. Basic customers who upgrade to Pro and Pro customers who upgrade to Enterprise, but to keep things simple it doesn't support each and every possible movement between plans. For example, I didn't include the option for Basic customers to upgrade to Enterprise straight away or for Enterprise customers to downgrade. If this is a relevant factor in your business, you can of course accommodate for that by adding a few extra rows.
• For Basic and Pro customers, the model allows you to project ARPA development using a given ARPA at the beginning of the planning period along with assumptions on monthly ARPA increases. For Enterprise customers, the model assumes pricing increases at the time of renewal but not during the term of the subscription. Depending on your specific pricing model you'll have to modify that, e.g. to allow for Enterprise customers to add more seats continuously.
• In order to be able to calculate churn for Enterprise customers in the 1st year of the plan, it is assumed that existing Enterprise customers have been acquired over the course of the previous 12 months. This is of course a somewhat theoretical assumption and you need to adjust the model to include your actual numbers.
• As you can see in one of the charts below the numbers, the model allows you to calculate your "MRR movements". It's worth pointing out that the model currently doesn't show "Expansion MRR" and "Contraction MRR" separately but only the delta of the two, which I've called "Net Expansion MRR". In order to calculate Expansion MRR and Contraction MRR separately I'd have to add a couple of additional rows. To avoid making things too complicated, I decided against doing that for now. Fortunately ChartMogul (a Point Nine portfolio company, sorry for the plug) makes it super easy to drill down into all of your MRR movements.
• Please note that the CAC data and "CAC payback time" calculation are based on pretty crude simplifications. A solid planning of CAC payback times, CAC/LTV ratios etc. would require a lot of additional input data.
• The rows with the "Thereof bonuses..." label contain matrix formulas. Handle with care. :)

4.) "Costs" tab

• In order to adjust headcount planning in the G&A, R&D and marketing departments, change the assumptions for start date, base salary and bonus in the grey "Assumptions" area. You can remove, change or add roles in column H.
• With the exception of the VP of Sales role, sales staff headcount planning is done on the separate "Sales Team Hiring Plan" tab (re-using a model that I've built for this post). It calculates the number of sales people that you need based on the growth targets for your Enterprise customer segment, the quota of your sales people and a few other variables.
• Headcount planning for the Customer Success team is (again with the exception of the VP) done formulaically as well, based on assumptions on how many customers a customer success team member can handle.
• It is assumed that there's only one team, which I've called Customer Success, which does both customer support and customer success. Many SaaS companies have different teams for the two functions; if you're one of them you can adjust the plan accordingly. 
• The costs for the Customer Success team are attributed to CoGS. This is debatable – if your Customer Success team plays an important role in converting signups or upselling customers you should consider allocating at least a portion of these costs to S&M and include those costs in your CACs. Please note that changing the "cost type" in column I will not automatically move the costs to a different category on the "Summary" tab so you'll have to do that manually.
• The model assumes that payroll tax is the same for all employees. This may have to be adjusted, e.g. if you have people in different countries.
• Regarding the cash impact of expenses, the model assumes that:
• payroll taxes are paid monthly
• bonuses are paid yearly (except for the sales team)
• sales team bonuses are paid quarterly (since bonuses/commissions play a much stronger role in sales compared to other departments)
• The model (somewhat simplistically) assumes that there are no capital expenditures. If you make investments into things like servers, computers or office furniture you should add these expenses accordingly.

If you've made it this far and haven't downloaded the Excel sheet yet: Here it is.

If you have any questions, comments or suggestions, let me know in the comments or email me. And if you like the model, tweet it out. :)

Finally, big thanks to Chris Amani, Sr. Finance Director at Humanity, as well as to Pawel and Dominik of Point Nine, for reviewing drafts of the model and for providing valuable feedback.

That’s a nice little $1-2M SaaS company you have here. Call me to discuss if it will scale!

About two years ago, Josh Hannah of Matrix Partners wrote an excellent article titled “That's a nice little $40M eCommerce company you have there. Call me when it scales.” In it he argues that an eCommerce business with $10 to $20 million in revenues is not that hard to build and also not very valuable. I would recommend that you read the full article, but one of the key points of the article was that if you fill a niche and have distinctive product/market fit with a set of customers, you can acquire customers very cheaply - up until a certain point, when you’ve maxed out the cheap customer acquisition channels and need to tap into more scalable channels. At that point it becomes a lot harder because the next set of customer acquisition channels will likely be much more expensive.

As a side note I’d add that the value of an eCommerce business with $10-20 million in revenue can be even more deceptive if a company has burned a lot of money to get to this level and has very low (or even negative) gross margins. The reason is that in most categories online shopping has become ultra-transparent (something which I’m not completely innocent of ;-) ) and that there’s a group of highly price-sensitive customers which always goes for the lowest price. So if you start an online shop, offer products at a loss, get listed on some of the biggest comparison shopping sites and do some affiliate marketing, you can easily get to tens of millions in revenue.

Now let’s talk about SaaS. In the last few years I’ve come to the realization that Josh’s observation can also be applied to the SaaS world: Building a SaaS business with $1-2 million in ARR is not that hard and not that valuable. Let me rephrase that. Starting a new company is always hard and most SaaS startups never get to $1-2 million in ARR. Every founder who accomplishes this deserves a huge amount of respect. The point is that getting to $1-2 million in ARR probably has less predictive value concerning a company’s ability to get to true scale than most people think – or at least thought some years ago.

The reason, I think, is that over the last 5-10 years it has become much easier to build a SaaS product and get initial traction:

• Building a web application has become much easier, faster and cheaper. Whether starting an Internet startup has really become 10x cheaper depends on how exactly you phrase the question and is debatable. But creating and launching a SaaS product has without a doubt become much cheaper in the last ten years. Moore’s Law, cheaper hardware and more bandwidth are one factor, but the even more important factor is that today there are great products for so many of the issues which the previous generation of SaaS founders had to worry about (billing, analytics, server monitoring, application performance, live chat, to name just a few … even AWS didn’t exist 10 years ago!).
• Ten years ago, there was nobody who SaaS founders could ask in order to learn how to do, for example, inbound marketing, low-touch sales or customer success. Many of the tactics that everybody is using today hadn’t been invented yet. In the last ten years the playbook has been written and subsequently published. As I wrote in my post about the rising table stakes in SaaS, today an abundance of knowledge about any imaginable SaaS topic is readily available online and events like the fantastic SaaStr conference last week allow founders to learn from people who’ve done it before.
• As SaaS is quickly becoming the norm, it’s now much easier to get initial traction. In any given category, the number of potential customers who considers (and in most cases prefers) a SaaS solution is much higher than it was some years ago. This and the fact that almost everybody owns a smartphone today has given rise to new categories which previously weren’t software categories at all because people used pen and paper to get the job done.

So – it has become much easier to develop and launch a SaaS application and get initial traction, but if you have product/market fit in a small niche, which many SaaS companies do, it may be very hard to expand beyond that niche. And even if your market is large in principle, keeping growth up after you’ve picked the low-hanging fruits and reached a few million dollars in ARR will become increasingly difficult. In order to go from a $1-2 million in ARR to $10 million and eventually $100 million, you’ll have to find highly repeatable and reasonably profitable ways to acquire customers at huge scale. With few exceptions that means you either need to have a viral product (a.k.a. as hunting mice) or you have to go upmarket and dramatically increase your ACV over time.

Some SaaS businesses manage to do this and have a shot at building a $100 million ARR company, but for the majority of SaaS companies growth will taper off once they’ve reached a few million dollars in ARR, making it hard to ever grow significantly beyond $10-20 million. In a way, this isn’t surprising – not everyone can become a unicorn. :-) The non-trivial part of what I’m saying is that 5-10 years ago, many of these companies wouldn’t have gotten to a few million dollars in ARR. Put differently, there are more $100 million ARR SaaS companies today, but the number of companies in the $1-10 million ARR range has grown disproportionately faster. That’s my theory at least, it’s not scientifically proven.

If my theory is true, will this be bad news for people in the SaaS industry? It’ll depend on who you ask. It could make seed and Series A investing harder because the percentage of seed and Series A funded SaaS startups that becomes really big would decrease - and VCs need large outcomes in order to make their business model work. But it would also lead to the generation of a large number of small-ish but still very viable SaaS businesses, many of which could generate very decent profits for their founders. From that point of view, there’s never been a better time to start a SaaS company.

PS: You may have noticed that I’ve changed Josh’s “call me when it scales” to “call me to to discuss if it will scale”. Being a seed investor I’m trying to find SaaS companies that can scale before they have scaled.

PPS: If you’re wondering why Josh talks about revenues in the $10-40 million range when he refers to sub-scale companies while I talk about $1-2 million in ARR: The reason is that besides the fact that SaaS revenues are recurring, SaaS margins are almost an order of magnitude higher than eCommerce margins. $1 in SaaS revenues is much more valuable than $1 in eCommerce revenues (all revenue is not created equal!).

[Update 03/11/2016: I wrote a followup post to the post above.]

6 reasons to be bullish on SaaS

Yesterday I argued that SaaS founders and investors shouldn’t worry about short-term movements of SaaS stocks and said that there are a lot of reasons to be bullish about the Cloud. Here are some of them.

1) SaaS is quickly becoming the norm
In the last years there’s been a dramatic shift in deployment preferences of software buyers. According to a survey by technology evaluation business Software Advice, 88% of buyers with a deployment preference preferred on-premise solutions in 2008. Just six years later, the results were completely upside-down: In 2014, 87% of all buyers with a deployment preference preferred Cloud solutions.

2) Billions of dollars of on-premise revenues are still up for grabs
In spite of this tectonic shift of deployment preferences, IDC estimates that in 2015 the market share of on-premise deployments in the enterprise applications market is still almost 80%. That means that billions of dollars will move from on-premise to the Cloud in the next ten years.

3) Millennials will move up through the ranks
In the near future, more and more IT decision maker positions will be taken over by millennials. For this generation, which grew up with Facebook and Gmail, SaaS will be the default choice. In fact, most of them will laugh at the idea that software could not be Cloud-based.

4) The entire software market will continue to grow
It’s not only about increasing the Cloud’s piece at the expense of the on-premise piece, though. Pen & paper or Excel sheets are still used by myriads of people for all kinds of business processes, especially in SMBs. Building better, Cloud-based solutions for these use cases will significantly increase the size of the total software cake.

5) Mobile expands the market to non-desk workers
About ten years ago, the number of smartphone users was negligible. Today there are more than two billion smartphone users worldwide. This development, which I think is nothing short of amazing, has (almost) suddenly increased the number of target users for B2B software companies by tens of millions in the industrialized countries alone. People in industries like construction, landscaping, hospitality and many other areas of “non-desk work”, who previously weren’t using any software, are now getting mobile apps that help them become more efficient.

6) New technologies will catalyze adoption
SaaS has always been more than just a better deployment option. It has enabled the creation of new ecosystems (Salesforce.com), new business models (Zenefits), new distribution strategies (Zendesk) and much more. The next wave of enterprise software will likely be powered by machine learning (check out this TechCrunch post for a good primer) and continued consumerization (and in some cases, new hardware). These and other innovations will allow SaaS applications to get even wider adoption and to provide even more value to its customers.

This is by no means meant to be an exhaustive list, and there are many more reasons to be bullish on SaaS. Want to let me know what you’re most bullish about? Tweet it to me!

Is SaaS doomed?

If one looks at the stock price development of public SaaS companies in the last few weeks, one could come to the conclusion that SaaS is over the hill. Salesforce.com: 17% down from its 52 week high. Veeva: 30% down from its 52 week high. Workday is 29% down, Box 47%, Hubspot 22%. Everyone got hit, as you can see in Tomasz Tunguz' post about the topic.

There are several reasons why this conclusion (that SaaS is past its prime) is wrong. Firstly, it's not just SaaS stocks which took a dive. The NASDAQ and the Dow Jones are both down more than 13% from their 52 week highs, too. Secondly, as this chart of the BVP Cloud Computing Index shows, SaaS stocks have outperformed the market significantly in the last couple of years, and it's not surprising that when the market corrects, stocks that went up more strongly than others are going down more strongly as well.

More importantly though, while public markets are good at valuing companies in the very long run, short term movements are – if not random – the result of all kinds of factors, most importantly supply and demand for stocks as an asset class, which itself depend on all kinds of factors that are not related to a specific company's ability to generate profits in the long run. That's why long-term public markets investors – let alone SaaS founders or VCs – shouldn't worry about the short-term movements of SaaS stocks. 

Fundamentally, there are lot of reasons to be bullish about the Cloud. I'll follow-up on that with another post soon.

The evolution of the SaaS landing page

When you look at the landing pages (or homepages or marketing sites, however you want to call them) of today's SaaS companies, they usually look quite beautiful. They typically have a clean, simple and friendly look, with very little text and a lot of images or videos. In many cases, these websites could just as well advertise a consumer product. This doesn't come as a surprise, since the consumerizaton of enterprise software has been one of the most important driving forces in the software world in the last years. But B2B software websites haven't always looked like this and it's fascinating to see how much things have changed. Join me as I go back in time and take a look at how SaaS landing pages looked like some years ago.


The SaaS Stone Age

Fast-backward about 16 years. This is how the website of Salesforce.com - the most innovative software company of that time – looked like in 1999:

Salesforce.com in 1999
(click for a larger version)

Interestingly, as horrible as the site looks by today's standards, it does have a bit of a consumer-ish feel and it actually became more enterprise-y over time (you can browse the history on the Internet Archive, which I've used to take these screenshots). So maybe in 1999 and the early 2000s the world wasn't ready for consumerization yet, or Salesforce.com didn't figure out the right approach or they just saw more success with a top-down enterprise sales approach.

The Beginnings of Modern (SaaS) Times

Not much happened on the SaaS design front in the following years. Until 2004, that is, when a small, Chicago-based web design agency called 37signals launched its project management tool called Basecamp:

Basecamp in 2004
(click for a larger version)

Basecamp looked radically different from any other piece of B2B software. If it's possible to pinpoint the beginning of modern SaaS to a specific company or product, I think this honor is due to Jason Fried and his colleagues at 37signals. As much as I disagree with Jason on many things he writes about how to build a business – kudos to 37signals for their focus on product, design and usability. No other SaaS company had a bigger influence on SaaS design.

It took a few years – which shows how much ahead of its time 37signals was – but eventually other SaaS companies redesigned their websites or rebuilt them from the ground up:

Campaign Monitor in 2008
(click for a larger version)

The trend was clear: Less and less text, bigger font sizes, larger images, videos. SaaS companies which were founded at that time had a stronger focus on design from the get-go:

Clio in early 2009
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Zendesk in 2010
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Contemporary SaaS Design

In the years that followed, the trend towards simplicity, focus on design and consumerization continued, and I'd say that since around 2012 or 2013, having a reasonably beautiful and conversion-optimized marketing website is more or less table stakes. Today you can buy a SaaS landing page template for $18. A $18 design which looks better than every B2B website that was built before 2004 – makes me wonder if Moore's law applies in design, too. ;-)

Since most people are trend-followers rather than trend-setters, SaaS landing pages started to look more and more alike in the last few years: A navigation bar at the top; 1-2 devices that were made in Cupertino, with product screenshots on them; a large headline and smaller sub-headline; 1-2 call-to-action buttons; some customer logos. This (plus a few other things) was the anatomy of almost every SaaS landing page in 2014. Not bad, don't get me wrong, but if everyone follows that recipe it gets harder and harder to stand out and build something memorable.

But just when things started to get boring, some cutting-edge design-led SaaS companies pushed the envelope further:

Geckoboard's current website
Go to www.geckoboard.com to see it live

Typeform's current website
Go to www.typeform.com to see it live

Another view of Typeform's current website
Go to www.typeform.com to see it live

Both examples make heavy use of video so the screenshots don't do them justice. Please go to Geckoboard and Typeform to see them in action. While still being focused on conversion, I think these websites are almost indistinguishable from art. Using high-quality video footage, very little text and beautiful typography, crafted with incredible attention to detail, these websites bring across a  value proposition in a fresh, unique and highly emotional way.

This little journey through time has shown that up until now, the evolution of the SaaS landing page has been a development towards ever more simplicity. It will be interesting to see if this trend continues in the coming years.


Disclosure: I'm an investor in Clio, Zendesk, Geckoboard and Typeform.

By the time you're at $2-3M in ARR, you need a VP of Sales who's done it before

For most SaaS startups, the VP of Sales (along with the VP of Marketing) is one of the most crucial hires they need to make. Unless you have a no/low touch sales model and you're growing virally (a.k.a. you're successfully hunting flies or mice), someone needs to build a scalable sales organization, whether it's an inside sales team (a.k.a. hunting rabbits or deer) or a field sales team (a.k.a. hunting elephants).

It's also one of the toughest hires. Jason M. Lemkin gave an epic talk about the subject at our 3rd annual SaaS Founder Meetup, last year in San Francisco. Jason also wrote extensively about the topic on SaaStr. If you haven't read his articles yet, make sure you read all of them.

As Jason explained in this post, one of the things that makes hiring the right VP of Sales so hard is the timing. If you try to hire your "Mr. Make it Repeatable" or your "Ms. Go Big" VP of Sales too early, say at $500k in ARR, you'll almost certainly not get a great one. The reason is that a great one will most likely not leave his or her current position at a successful, fast-growing, well-funded SaaS company, which pays him or her hundreds of thousands of dollars in salary and bonus/commission per year, to join your tiny little startup.

Starting to look for your VP of Sales too late is equally dangerous, though. If you want to grow roughly in line with the T2D3 formula, which most venture-funded SaaS startups should shoot for, you need to hire a lot of sales people in year 3. An exception are SaaS startups with a no/low-touch sales model and viral growth (see above) and potentially companies which have a massively negative net MRR churn rate and therefore don't have to acquire as many new customers. If you're fortunate to be in one of these categories, you may not need a big sales team, but most SaaS companies aren't.

That's why I think most SaaS companies that don't have sales management experience in the founder team need to start looking for a VP of Sales by the time they're at around $1.5-2M in ARR so that by the time they're at around $2-3M, they've recruited a VP of Sales who can take them to $10M and beyond. My thinking becomes clearer if you take a look at this model, which calculates how many sales people you need to get from, say, $1M in ARR to $10M. Note that a big and productive sales team may be necessary to achieve that goal, but it's obviously not sufficient. You also need a great product, great marketing, etc. – otherwise your sales team won't have enough warm leads and closing them will be too hard.

(click for a larger version)

Click here to download the Excel sheet.

Here's how the model works:

• Enter your current ARR in cell D10. You can of course also enter your ARR target for a future date, depending on what you want to calculate. In the template, I'm assuming that you're at or close to the end of year 1 and want to work out your hiring plan for year 2 and year 3.
• Enter the monthly growth rate that you're targeting for year 2 and year 3 in cells D11 and D12, respectively. Note that this should be your "net MRR/ARR growth rate", which takes into account all MRR movements like churn, expansion or contraction. The sample data that I've put in reflects the T2D3 formula (grow to $1M in ARR in year 1, triple in year 2 and triple again in year 3).
• Input your monthly net MRR churn rate (i.e. [churn MRR plus contraction MRR] minus [expansion MRR plus reactivation MRR]) in cell D13.

Using these inputs, the spreadsheet will calculate the new ARR from new customers that you have to acquire in order to meet your growth targets. See row 25.

Now ... how many sales people do you need to achieve these target numbers? This depends on the following inputs:

• Your AEs' quota, i.e. how much new ARR you expect each AE to bring per month. The model assumes that your AEs will on average meet their quota. In reality, some of your sales people won't meet their quota and some will exceed it, so this number really is just the average which you expect to achieve.
• Ramp-up time, i.e. the time it takes your AEs to reach full productivity. The model assumes that they're 100% productive in month 4. For months 1-3, you can enter different percentages in cells G10-12.
• The size of your sales support team. In cells K10-14 you can enter how many Sales Directors, SDRs and SDR Directors you expect you'll need in proportion to the number of AEs.

The sample numbers that I'm using in the template are broadly in line with the results of this benchmarking survey. As you can see in the spreadsheet and in the chart, based on these assumptions your total sales headcount increases from 2 to 9 in year 2 and from 9 to 30 in year 3. So in year 3 you'll have to hire and train 21 new sales people (plus replacements for people that leave or are let go). 

Without a VP of Sales who has built and scaled a sales team before, that's tough. 

PS: As you can see in the chart below, there's a 1:1 correlation (approximately) between ARR and sales headcount. That's OK in the $1-10M ARR stage, but in the longer term the best SaaS companies manage to grow revenues faster than sales spendings, primarily by focusing on account expansions to achieve an ever-increasing negative MRR churn rate and by continuously getting up sales efficiency.

(click for a larger version)

A closer look at the 6 things to pre-empt 90% of Due Diligence

Since last week's post about 6-7 things to pre-empt 90% of Due Diligence was liked/shared/retweeted quite a bit, I'd like to follow up with some additional details on what exactly SaaS Series A/B investors will look for when you supply them with the data and material that I've mentioned. In my post I suggested that you should prepare a key metrics spreadsheet, a chart with your MRR movements, a cohort analysis, a financial plan, an analysis of your customer acquisition channels and, if you're selling to bigger customers, information about your sales pipeline and details about your largest customers. Let's go through these items one by one and try to anticipate some of the questions potential investors will think about.

As a caveat, I'm going to mention some benchmark numbers but it's very important to note that none of these numbers can be viewed in isolation. There is not one number which will determine if investors want to invest. It's always about many puzzle pieces which together form a picture of the strength of your company.

Key metrics spreadsheet

• What's your visitor-to-signup conversion rate? Typically this metric is in the 1-5% range. If you're significantly below that, that doesn't have to be a red flag – there can be good reasons for a lower rate – but it may raise questions.
• What's your signup-to-paying conversion rate? In my experience, most good SaaS companies convert 5-20% of their trial signups into paying customers (but again, there can be exceptions).
• What's your lead velocity? Are you getting more and more new trials/leads every month?
• What's your account churn rate and more importantly your MRR churn rate? The best SaaS companies have an account churn rate of less than 1.5% per month and a negative MRR churn rate (which doesn't mean that you can't have a great company with somewhat higher churn or that you have to be at negative MRR churn at the time of your Series A/B).
• How fast and how consistently have you been growing MRR? Have you been adding an ever-increasing amount of net new MRR month over month?
• How has your ARPA developed? Have you been able to increase it?
• Are you able to sell annual plans?
• How long did it take you to get to $1M ARR? The best SaaS companies get there within 12-15 months after launch (but again, lots of exceptions ... there are companies that start slowly and skyrocket later).
• How much have you been spending on customer acquisition? As a rule of thumb, most SaaS companies should target a CAC payback time of 6-12 months, although in some cases there can be good reasons to spend significantly more.
• What are your CoGS and what's your Gross Profit Margin? As a pre Series A startup you're probably not great at tracking/attributing CoGS ... which I think is OK.

MRR movements

• How much MRR have you been gaining by acquiring new customers? Have you been able to add MRR by expanding existing accounts as well? 
• How much MRR have you been losing due to churn or downgrades?
• Mamoon Hamid of Social+Capital has coined the term "Quick Ratio" for the ratio between added MRR and lost MRR, and he's looking for companies with a Quick Ratio of > 4. If your Quick Ratio is significantly below that, is it trending in the right direction?

Cohort analysis

• How does your account and MRR retention look like for some of your older customer cohorts? Do you have low or even negative MRR churn?
• Taking a "vertical" look at the cohort analysis, are you getting better and better over time, i.e. do your younger cohorts look better than older ones?
• What's your estimated CLTV based on this cohort data?
• How does usage activity look like on a cohort basis? Is there a lot of "hidden churn" (customers who got inactive and are likely to cancel soon)?

Financial plan

• Is your plan both ambitious and realistic? Most investors are looking for T2D3 type growth, i.e. once you've reached around $1M in ARR you should try to grow 3x y/y for two years.
• Is your plan a coherent continuation of your historic/present numbers, both methodically and with respect to your key assumptions? Projecting a sudden, drastic improvement of your key drivers is understandably much harder to sell to investors.
• Are your key assumptions plausible, and what's the impact of somewhat more pessimistic assumptions?
• Did you sanity check the outcome of your model? If the result of your model is that you'll be a money printing machine within two years, that's usually a sign that you're underestimating future costs. :)

Customer acquisition channels

• How did your customers find you? Organic, paid, both? Ideally you have strong organic growth (which is strong proof of product/market fit) as well as some success with paid customer acquisition channels (which can be scaled more easily).
• How does your conversion funnel look like for different sources of traffic? What are your costs per lead and per customer for different marketing channels?
• How close are you to building a (somewhat) predictable and repeatable sales and marketing machine? Do you have a sense for the scalability of your customer acquisition channels? 

Sales pipeline

• How does your current pipeline look like? Do your short-term targets look realistic based on your "in closing" pipeline? Does your overall pipeline support your mid-term targets?
• How has your pipeline developed? Has it become stronger and stronger over time?
• Are you starting to get a handle on closing probabilities and closing timelines?

In the original post I said as a bonus tip that if you're an enterprise SaaS company, you should put together some additional information about your largest customers. Here's another bonus tip: Include information about your NPS (which is hopefully very high) and how it has developed over time.

Ideally, all these puzzle pieces together, along with the size and attractiveness of the opportunity you're going after and the strength of you and your team, will form the picture of a SaaS startup which has clear product/market fit, enthusiastic customers, strong initial traction, continuously improving metrics and which is on its way to building a repeatable, scalable and profitable customer acquisition engine.

6 things to pre-empt 90% of Due Diligence

The founder of a portfolio company recently asked me what kind of numbers and other material he'll need when he goes into his next round of fundraising. He wanted to make sure that when he starts talking to new potential investors, he'll have answers ready to most of the questions he'll be asked.

That was a great question. By putting together a comprehensive set of data you can pre-empt 90% of the questions which investors will ask you when they assess a potential investment. This has a number of important advantages:

• It saves you time because you'll have to answer fewer individual questions and requests in a piecemeal fashion.
• It can speed up the fundraising process dramatically if investors get almost everything they need at once (or almost immediately upon request).
• It makes you look better, because it shows that you're on top of things.
• Almost all of the numbers (good) investors ask for are things that you should be highly interested in anyway, since they are important for understanding and running your business.

What kind of numbers you should prepare of course depends on the industry and stage you're in. I'm going to assume that you're a SaaS company and that you're going for a Series A or a Series B round. In this case, the following things will help you pre-empt a lot of DD questions:

1) A spreadsheet with your key metrics, since launch, on a monthly basis. It should include funnel metrics (visitors, signups, conversions etc.) as well as key financial metrics (MRR, CoGS, CACs etc.). If you haven't seen it yet, I put together a template for a KPI dashboard some time ago, which should serve as a good start.

You are probably tracking most of these numbers already anyway, so you can use a copy of your internal dashboard, but make sure that it's clean, comprehensible and that you're using the right terms.  If your dashboard contains any ambiguous metrics, add footnotes with precise definitions to make sure that an outsider understands exactly what he's looking at.

2) A chart with your MRR movements, since launch, on a monthly basis. That is, a chart that shows your new MRR, expansion MRR, contraction MRR, churn MRR and reactivation MRR for each month since launch.

MRR movements in ChartMogul

If you have a very wide range of customer size, consider breaking down the MRR movement analysis by your customer segments, because in that case the aggregate numbers across all customers may not tell the full story. So if you're selling to both SMBs and bigger enterprises, consider showing one MRR movement chart for the SMB customer segment and another one for the enterprise customer segment.

Make sure to provide the raw data along with these charts (and any other charts you provide) to allow the viewer to do his or her own calculations.

3) A cohort analysis, showing each monthly customer cohort since launch and how the cohort’s MRR has developed over time. I created a template for that, too. If you're selling to both SMBs and enterprise customers, you should again consider doing a separate analysis for each of the two segments.

Also consider adding a cohort analysis which is based on an activity metric. Think about what your key usage indicator is, then run a cohort analysis that shows the development of that number over time.

4) A financial plan for the next three years. The plan should follow the same logic as your historic KPI dashboard and should be relatively simple. Don't hard-code many numbers and make it easy to understand which assumptions the model is based on. Here are a few additional tips, and here's a template for a financial plan I built some time ago.

5) An overview of your customer acquisition channels. That is, a breakdown of your website visitors, leads and customers by source and data about your customer acquisition costs. 

Try to add some data points or estimates on the scalability of your customer acquisition channels. I know this is very hard and sometimes impossible, especially for inbound marketing driven companies, but some projections are probably better than having none at all.

6) If you're selling bigger deals, detailed information about your current sales pipeline. This should include a list of all qualified opportunities, and for each opportunity the potential deal size (in terms of MRR or ARR), pipeline stage and, if you have enough historic data to make a solid guess, closing probability and timeline. If you're a low-touch sales, high-velocity, low ARPA SaaS company you can leave this out.

Bonus tip: If you're an enterprise SaaS company, put together some additional information about your largest customers. Think of it as a little case study, with some information about how the customer found you, how the sales process looked like and how the account has developed over time.

What do you think? Does this capture most of the data Series A/B investors want to know?

[Update 5/8/2015]: I wrote a follow-up post with some additional details on what exactly SaaS Series A/B investors will look for when you supply them with the data and material mentioned above.]

Key Revenue Metrics for SaaS companies

Thanks to Nick Franklin for reviewing a draft of this post!

When I talk to SaaS startups and take a look at their metrics, it still happens quite often that some of the numbers aren’t quite clear to me and it takes some time to clarify things. I’m not referring to sophisticated reports or analyses but to the much more mundane question of what exactly people mean when they use a term like “revenues”.

It’s maybe not surprising that there’s sometimes confusion, given that there are several different ways to express revenues of a SaaS company and even more ways to label them: revenues, sales, turnover, MRR, CMRR, ARR, cash inflow, cash-in, billings, bookings, GAAP revenues, income and so on. That said, I believe most SaaS companies can focus on a small number of revenue metrics which aren’t overly complicated.

If everyone in the SaaS world can agree on the same nomenclature, I think that will make communication between founders and investors more efficient and will save all of us some time. So let’s take a look at the most important revenue metrics in SaaS.


MRR

Monthly Recurring Revenue (MRR) is, as the name suggests, revenue that you anticipate to recur on a monthly basis. If you’re selling monthly subscriptions, MRR is simply the price paid each month for the subscription. If your customers are paying you for more than one month upfront, you simply divide the amount you received by the number of months in the subscription period.

Say you’ve acquired two new customers. Customer A has signed up for a monthly subscription at $100 per month and Customer B has signed up for an annual subscription of $1100 per year. In this scenario, customer A increases your MRR by $100 whereas customer B increases your MRR by $91.67 ($1100/12).

This simple metric is the most important metric a subscription business needs to calculate, which is why ChartMogul (which for disclosure we’re an investor in) is highly centered on MRR. If you focus completely on MRR and calculate it correctly you’re in pretty good shape, so feel free to stop here and ignore the rest of this post. :-)


ARR

Annual Recurring Revenue (ARR) follows exactly the same concept. The only difference is that it measures your annually recurring revenue as opposed to your monthly recurring revenue, so your ARR is 12x your MRR.

Since both metrics are interchangeable, it doesn’t matter if you’re tracking MRR or ARR. I personally prefer MRR, but I can’t tell you why. Probably just out of habit.


Cash inflow

Cash inflow or “Cash In” is the amount of money that you’ve received in your bank account. In the example above, it’s $100 for customer A and $1100 for customer B. A related term from the accounting world is “Accounts Receivable” and refers to cash that is legally owed to you but which you haven’t received yet. Since SaaS companies are typically paid upfront, at least for a month of subscription if not a year, you usually don’t have to worry too much about this and can focus on cash inflow.


Revenues

Revenue means MRR plus any non-recurring revenue such as implementation fees, setup fees or charges for professional services. Let’s say you’re charging a customer $1000 for a data migration project that takes one month to complete, plus another $3000 for onboarding consulting in the customer’s first three months. In that case, the customer will increase your revenue by $2000 in the first month ($1000 for the data migration and $1000 for consulting) and another $1000 in month two and three each. But since these revenues aren’t recurring, don’t include them in your MRR.

Note that this definition of “revenues” is what I believe is usually the right way to look at revenues at the management and board level whereas the numbers which your accountant will produce for your financial statements will likely look slightly different. The reasons are a couple of subtleties in the way software revenues are recognized based on US GAAP and other accounting standards, which brings me to...


US GAAP Revenues

Since I’m not an accountant and don’t even have an MBA we’re now entering territory which I’m not very familiar with, so proceed at your own risk. :) US GAAP Revenues means revenues in accordance with the “Generally Accepted Accounting Principles” adopted by the SEC. Your US GAAP revenues will usually be close to your revenues based on the definition I outlined above, but there can be some differences. For example, US GAAP revenue is typically calculated using a daily recognition model as opposed to the more practical monthly model. That means that if a customer signs up for a subscription at $100 per month on January 15th, according to US GAAP you should only recognize $50 of those $100 in January, despite the fact that that customer is adding $100 to your January MRR. Another difference is that as I’ve learned when doing some research for this article, apparently you may have to recognize things like implementation fees over the subscription period as opposed to the period in which the implementation service is being provided.

This topic is a science of its own, and if you’re interested you can read this 150 page manual from Deloitte about software revenue recognition, but the good news is that you don’t have to worry too much about it. Find a good accountant who understands SaaS and let him figure it out.


Bookings

I’ve seen several definitions of the term “bookings”. Broadly speaking, bookings are the total dollar value of all new contracts signed, but it’s not clear if the number should be annualized for contracts that are larger than one year, nor if non-recurring revenues should be included. Even worse, if your contracts have different subscription periods (e.g. one month and one year), the bookings number can be very ambiguous and misleading. I would therefore recommend to not use this metric and largely agree with the Bessemer Cloud Computing Law #2 which famously stated that “booking is for suckers”.


Billings

The term “billings” refers to the amount that you have invoiced and that is due for payment soon. If your ARPA is low and most customers pay you via credit card and/or your bigger customers usually pay you on or about the time of subscription or renewal, this metric isn’t important. If you agree on longer terms of payments with your customers, it can become important for cash flow planning purposes.


Committed MRR

Committed MRR or CMRR is a projection of your MRR in the next month or future months based on your current MRR, adjusted by guaranteed expansion MRR and anticipated churn MRR. SaaS companies sometimes have customers that start with a low price but have already agreed to a price increase in the future. CMRR is a great way to track and show this type of guaranteed expansion MRR. If you adopt the CMRR metric to show guaranteed expansion MRR, make sure that you also take into account “guaranteed churn” in order to make it consistent. That is, subtract MRR which you expect to lose from customers that you expect to stop using your software in the near future.


Closing thoughts

I believe that most SaaS companies do well by focusing on MRR and Cash Inflow plus, depending on the nature of the business, revenues and CMRR. The only thing I’d add is that if you’re selling annual subscriptions but you don’t get the full payment upfront (or similarly, if you’re for example selling 2-year-subscriptions but get only one year upfront), you should monitor your MRR broken down by contract length. That’s because there’s obviously value in selling longer subscriptions vs. shorter ones but that difference won’t show up in your MRR nor in your Cash Inflow in these cases. If you think there are any other revenue metrics that I’ve missed, please let me know.

Finally, I’m well aware that while all of these metrics are easy to understand conceptually, there are still a lot of devils in the details. The purpose of this post is to come to a common understanding of the key revenue metrics – how to deal with some of the many special cases that you’ll inevitably see (discounts, refunds, currency fluctuations, metered charges, etc) might be the topic of another post.

How fast is fast enough?

Growth is the single biggest determinant of startup valuations at IPO, as my fellow SaaS investor Tomasz Tunguz concluded based on an analysis of 25 IPOs in 2013. Growth (a.k.a. traction) is also the most important factor that attracts VCs and drives valuations in private financing rounds. Of course your team, product, technology, business model and market matter too, but when you’re past the seed stage the expectation is that these factors will have resulted in excellent growth. At the seed stage you can sell your story and vision. At the Series A and later stages, you have to back it up with numbers.

This isn’t surprising. Past growth tends to correlate with future growth, and since tech markets are winner-takes-all (or "winner-takes-most") markets, investors are obsessed about finding the fastest-growing player that has the biggest chance of dominating the market.

If growth is so crucial, how fast do you have to grow?

The answer depends on the market you’re in and the type of company that you want to build. If you’re in a small niche market – let’s say a business solution for a small vertical, localized to one country – maybe you don’t have aggressive, well-funded competitors. In that case it may be sufficient if you’re the fastest-growing player in that market, even if that means you’re growing only 20% year-over-year. There’s absolutely nothing wrong building a company like this, and you could end up with a highly profitable small business (or Mittelstand company). This is not the type of company VCs look for though, and the rest of this post is written based on the premise that you’re a SaaS startup that wants to grow to $100M in Annual Recurring Revenue (ARR).

So how fast do you have to grow in order to become a $100M company? Again using data compiled by Tomasz “Mr. SaaS Benchmarking” Tunguz we can see that the 18 publicly traded SaaS companies that were founded within the last ten years took five to eight years to reach $50M in revenues, with 14 out of the 18 being in the six to seven years range. ⁽¹⁾ Add another one or two years for getting from $50M to $100M, and we can assume that most of these companies took seven to nine years to get to $100M.

$1M, T2D3, 50%?

If you want to get from 0 to $100M in revenues in seven years, your growth curve will likely look very roughly like this: Get to $1M in ARR by the end of the first year, triple to $3M in the next year, followed by another triple to $9M by the end of year three. Double your revenues in the next three years, so that you’ll reach $18M, $36M and $72M by the end of year four, five and six, respectively. Grow by another 50% in the next year and reach $108M in ARR by the end of year seven:

This is very much in line with the “T2D3” formula described by Battery Ventures in this TechCrunch post. If you want to give yourself nine years to get to $100M, your numbers will probably look roughly like this:

Could you also take the slow track?

The big question is now if this strong pattern is merely the result of investment bankers’ and public market investors’ preference for fast-growing companies or if something more fundamental is going on here. If there was a “law” which said that if you haven’t reached something close to $5M after three years, $10M after four years, and so on, you’ll likely never get to $100M, this would obviously have important implications for founders as well as investors.

My opinion is that there’s no hard law – in business you’ll find exceptions for every rule, and I think it’s definitely possible that software companies that grow slowly and eventually reach $100M exist. But I do think that the probability of ever getting to $100M does go down very significantly if you’re growing much slower than pictured above. This is because:

• As companies get bigger, growth rates tend to go down, not up. So if your growth rate in year three is only, say, 50%, it’s unlikely that it will be 200% in the following year. It can happen and does happen, of course, but only if there’s a dramatic improvement in the business - a new product, a new distribution channel, a new business model or the like.
• It’s hard for a slow-growing company to attract the best people. It’s not only about being “hot” as an employer (although that’s part of it, too). If you’re not growing fast, you’ll also have a hard time making compensation packages competitive with those of fast-growing companies. The positive feedback loop that is taking place here is very powerful: Momentum attracts talent and money, which you can turn into more momentum, and so on.
• Not so many founders have the stamina and patience to stick to their company for 10, 12, 15 years - after so many years, many people understandably need a change. And while a company can of course survive its founders, it’s still a loss that doesn’t make things easier in the future.
• Lastly, but maybe most importantly, if you can’t figure out a way to grow fast and you’re in a large market, chances are that someone else will. It also increases the chance of a new, innovative, fast-growing startup entering and possibly disrupting the market before you’ve reached significant scale.

Coming back to the original question, how fast is fast enough? If your goal is to eventually get to $100M in ARR, I think you should try to get there as fast as possible, and getting there by the end of year seven after public launch feels about right to me. This may seem like a very ambitious goal, but it would be boring if it was easy, wouldn’t it?

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(1) Note that there’s somewhat of an outcome bias in these results, as companies that were founded in the last ten years but take more than ten years to go public haven’t been included. So it’s possible that a few companies with slower growth will be added in the future, but that’s unlikely to change the picture significantly, especially if you keep in mind the trend which Tomasz has described in his post: SaaS startups are growing faster than ever before, and it’s taking them less and less time to get to $50M.