Monday, April 11, 2016

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!

Wednesday, April 06, 2016

Truffle pig reloaded – Point Nine is looking for an Associate

About three years ago, we were looking for an Associate to join Point Nine and put up this landing page:

We called the position "truffle pig", because just like a truffle pig is digging up the best truffles from the ground, we as an early-stage VC try to find the best startups among a large number of potential investments. I have to give full credit for the truffle pig analogy to Mathias Schilling and Thomas Gieselmann of, by the way. "Truffle pigs" is what they (young VC Associates at that time) called themselves when they approached my co-founder and me back in 1997 after having stumbled on this website. Fast-forward almost 20 years and we still haven't found a better way to describe the role. :)

Anyway, our search three years ago led to two fantastic truffle pigs, Rodrigo and Mathias, both of whom got promoted to Principals at Point Nine in the meantime. And today we're excited to kick-off the search for a new Associate. Here are all the details.

This is an incredible opportunity for a young, super-smart, super-driven person with outstanding analytical skills and a solid user interface. I'm pretty sure that it took me more than 10 years to get the expertise and network which you'll get during three years in this job. 

If you're interested, please take a look at our job ad. If you know somebody who could be great fit, please pass on the link. Thanks!

Tuesday, March 29, 2016

SaaS Financial Plan 2.0 - bug fixes

Since I published v2 of my SaaS Financial Plan a few days ago, two alert readers have kindly pointed out two formula errors in the Excel sheet. Sorry about that. 

Here's a corrected version. The Excel sheet that was linked from the original post has been corrected as well.

In case you've started to modify the template already and want to keep working with the previous version, here are the two bugs that you need to correct:

1) Cell U124 on the Costs tab, i.e. the costs for external recruiters in December 2016, contained:


The +X96 part has been added accidentally and needs to be removed. So the correct version is:


2) Row 55 on the Revenues tab, i.e. the CACs for the Pro plan, is completely wrong. It should be, for column I (with the other columns following analogously):


Once again, apologies for the inconvenience. If I or somebody else finds any other bugs, I will fix them ASAP and update the change log here.

PS: Before you ask – yes, I'm aware that it's ironic that I have to post an on-premise software style bug patch to a SaaS financial planning template. Ironic in an Alanis Morissette kind of way, that is, because "ironic" actually means something completely different. Google it if you don't believe me.

Wednesday, March 23, 2016

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.

Friday, March 11, 2016

Building any business is hard

Judging from the number of Facebook likes and retweets, as well as comments on Twitter and elsewhere, my last post resonated with quite a lot of people. Some people thought it was provocative though, and some chimed in with good feedback:

Therefore I thought it would be worth following up on the topic to make sure that my message is clear.

The provocative sentence, I think, was this one:
"Building a SaaS business with $1-2 million in ARR is not that hard and not that valuable."
It's important to point out that I took it back in the next sentence ...
"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."
... and tried to explain the real point I was trying to make in the next one:
"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."
As you can see, I don't disagree at all with Jonathan Abrams' s comment that building any business is hard. The reason why I wrote the sentence above, only to rephrase it in the following sentence, was that it was a reference to Josh Hannah's post about "nice little $40M eCommerce companies", which my post was inspired by.

To be as clear as possible about the subject, let me sum up my view again:

1) Building any business is hard. It requires a much broader skill set, more hard work and much more persistence than most normal jobs. (Let me refine that to "normal office jobs" - I don't want to get into an argument with heart surgeons or firefighters.) And since most businesses fail (at least when it comes to tech startups) it also requires a huge tolerance for risk.

2) Getting a SaaS company from 0 to $1-2M in ARR is hard. For the reasons mentioned in the original post, I think it has become significantly easier in the last 5-10 years but that doesn't mean that it isn't still very hard. Maybe a better way to put it would be "more likely" than "easier".

3) As hard as it is to get to $1-2M in ARR, getting to that level doesn't say much about a company's ability to get to $100M in ARR. For most companies which didn't raise venture capital this is completely irrelevant. If you're a bootstrapped company or raised only a small amount of outside funding and eventually get to a few million dollars in ARR that's an amazing outcome, and calling a company like this a "lifestyle business" is ignorant and stupid. If you're a VC-funded company, the prospects of getting to $100M matter, though – at least to some of your shareholders. :)

In case it's still not clear, maybe this funnel diagram helps to explain what I mean. :-)

Saturday, February 20, 2016

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.]

Saturday, December 12, 2015

A simple tool to improve your 2016 planning

In my last post I wrote about the problem with month-over-month growth rates. One of the issues I talked about was that when your revenue plan numbers are based on a constant m/m percentage growth figure (i.e. you're projecting to grow exponentially), your short-term objectives are likely too low relative to your longer-term goals.

As an example, I showed a (fictional) SaaS startup that wants to grow from $1,000 in MRR to ~ $85,000 in MRR within one year. If that company projects exponential growth, it will have to add less than $7,000 in net new MRR in the first half of the year in order to be on track ... but to stay on track, it needs to add more than 10x that amount in the second half of the year!

To follow-up on the topic, I've put together a very simple (Google Sheets based) calculator which startup founders might find useful when they work on their plan for 2016. The purpose of this simple sheet is not to replace a thorough bottom-up planning which is based on the key drivers of your business. Instead, the idea is that it might be a useful input or cross-check for a more detailed plan.

Click here to check out the tool.

Here's what it does:

  • You enter your start MRR in the orange field at the top left
  • You enter your target growth for the year in the orange field in the middle
  • The sheet will then calculate three alternative paths to your target MRR for the end of the year

The first one is based on linear growth. It just takes the total net new MRR that you want to add throughout the year and assumes that you're adding 1/12th of it each month.

The second one is based on an exponential growth assumption, i.e. it assumes that you're growing at a constant percentage growth rate every month.

The third alternative, which I've called "Happy Medium", has a growth curve that sits between the linear and the exponential option. You can see that well if you take a look at the charts below the numbers.

I think most early-stage startups should project a trajectory which, like the "Happy Medium" path", is somewhere between the linear and the exponential option. What do you think?