Tuesday, December 05, 2017

We’re looking for an Associate

I’m very excited to announce that we’re looking for a new Associate. In all modesty, I think that for a young, smart person who’s passionate about startups and technology, an Associate role at Point Nine is one of the fastest ways to learn, build your network, and advance your career. Case in point: Rodrigo, who started as an Associate four years ago, is now a Partner at Point Nine; Fabian is running his own fund; Nicolas became a “30 under 30” and is now VP at Insight; and Mathias is now GM Germany at Uniplaces.

As I wrote last time when we were adding an Associate to our team, 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, here are all the details. If you know somebody who could be a great fit, please pass on the link or let me know. Thank you very much in advance!

PS: As you may or may not know, the Associate role at Point Nine has historically been called “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 still kind of the like that analogy, but all good things must come to an end. For now, we’ll just call the new position “Associate” but if you have a creative idea for something funnier I’m all ears!


Friday, December 01, 2017

How public SaaS companies report churn, and what you can learn from them

While doing some research for another post I just stumbled on this excellent overview from Pacific Crest on the churn rates of publicly listed SaaS companies. I’ve seen posts with churn benchmarks of public SaaS companies before, but this one is by far the most comprehensive collection I’ve seen and I think it’s very useful.

What’s maybe even more interesting than taking a look at the numbers themselves is to see how different companies define churn (or the inverse, retention). Since there is no official US-GAAP definition of churn or retention, different companies use different ways to measure and report these metrics. And because public companies are under the scrutiny by the SEC, any non-GAAP metric they report must be accompanied by a razor-sharp definition.

Most public SaaS companies report churn in the form of their dollar-based net retention rate, i.e. the inverse of net MRR/ARR churn (as opposed to account/logo churn), which compares the recurring revenue from a set of customers across comparable periods. Here’s a particularly nice description of this metric, coming from AppDynamics:

“To calculate our dollar-based net retention rate for a particular trailing 12-month period, we first establish the recurring contract value for the previous trailing 12-month period. This effectively represents recurring dollars that we should expect in the current trailing 12-month period from the cohort of customers from the previous trailing 12-month period without any expansion or contraction. We subsequently measure the recurring contract value in the current trailing 12-month period from the cohort of customers from the previous trailing 12-month period. Dollar-based net retention rate is then calculated by dividing the aggregate recurring contract value in the current trailing 12-month period by the previous trailing 12-month period.”

If you take a look at the data assembled by Pacific Crest you’ll see that many companies use the same logic with minor variations. For example, some companies look at the trailing 12 month period, while others look at calendar years, quarters, or months.

Some companies exclude customers that do not meet certain criteria, for example:

  • Box includes only customers with $5k+ ACV and annual contracts
  • Alteryx considers only customers which have been paying customers for at least one quarter.
  • AppDynamics includes only customers who have been paying customers for at least one year.
  • Zendesk excludes customers on the starter plan.

This makes perfect sense: It tells you what type of customer the company is focused on, and you can see the retention metrics in regards to this type of customer.

Other companies use variations that I think are questionable. Some companies report customer count-based retention, which I think is much less interesting than dollar-based retention. Some report renewal based on the number of seats; one company, Fleetmatics, reports churn based on the number of vehicles under subscription. But the majority of companies does report dollar-based net retention rate in a way that allows for an apples-to-apples comparison across companies.

What can you learn from this?

(1) There is not one perfect definition of churn that is right for every SaaS company. Depending on the specifics of your business you might want to:

  • focus on monthly, quarterly or annual retention
  • exclude customers that churned within the first, say, two months
  • include only customers that represent the core of your business, e.g. customers above a certain ACV

(2) Having said that, dollar-based net retention is the way to go. You should stay close to the definition above and tweak it with care.

(3) There may not be one perfect way to define and measure churn, but there sure are lots of ways to get it wrong. :) One classic example is to calculate a monthly churn rate and to mix in annual plans with monthly plans. By including customers on annual plans who aren’t up for renewal in the period you’re measuring you’re underestimating your true churn rate.

(4) Whatever metric you choose, make sure that you use it consistently and that you have a razor-sharp definition.

Bonus tip: Whenever you report numbers, be it in monthly updates or in a Board deck, include footnotes or an appendix with definitions of every metric that you’re reporting. I can almost guarantee you that this will save you ten minutes of discussion with your VC Board member(s) who (understandably) want to make sure that they understand the numbers you’re showing them. :)


Tuesday, November 21, 2017

Getting feedback from your Board

After a Clio Board Meeting last week I received the following email from Jack Newton, the company's amazing co-founder & CEO.

Hi everyone,

I'd like to experiment with requesting some 1:1 feedback on our board meetings. Please take 5 minutes and provide feedback through this Typeform:

https://xxx.typeform.com/xxx...

Cheers,

Jack


I thought this was a really great idea and worth sharing here. I removed the URL from Jack's Typeform but rebuilt it quickly so that you can check it out:


powered by Typeform

If you're not getting feedback from your Board members you're missing out on something. Preparing and holding Board meetings is a big time investment, and making them really effective isn't easy. So you should try to get as much value out of them as possible.

Sending out a post-meeting Typeform is, of course, not the only way to get feedback: In some Boards that I'm a member of we sometimes do an executive session between the CEO and the directors. Sometimes I try to summarize my thoughts at the end of the meeting, sometimes I do it in a followup email after the meeting.

But doing it with a Typeform might help you ensure that you'll be getting feedback more consistently: after each Board meeting, from each director. I think this format might also help you get more candid feedback because not everyone is good at delivering honest feedback in a meeting. As a side benefit, you'll start building an archive of feedback that you can revisit later. No rocket science, but sometimes little things can make a difference, and I'm curious to see how this one will pan out.

Thanks to Jack for giving me permission to share this here (and thanks Fred Wilson, who, as I've learned from Jack, inspired Jack on this topic).



Saturday, November 18, 2017

Unsure how much you should pay yourself? Check out this Founder Salary Calculator.

Founder salaries are not a topic I’ve had to spend a lot of time with so far. I usually just “OK” them, since the founders we are working with are all super reasonable people who carefully weigh how much they need against the interests of the company – their company. But sometimes founders ask me for a suggestion or some guidance because they are uncertain as to what is fair, and so I thought it might be useful to create a simple model.

Here it is.

The model calculates the founder salary based on three drivers: stage, family situation, and location.

Stage

Unless you’re in the fortunate position to generate revenues almost from day 1 or to raise a sizable seed round right at the start you’ll probably not be able to pay yourself any salary at all, at least in the first few months, for the simple fact that the company doesn’t have any money to spend. If you raise a small angel or friends & family round, you’ll probably want to spend it on other things than founder salaries. Once you’ve raised a bigger seed round and/or you start to generate revenues, that changes and you can pay yourself a modest salary.

In the calculator, I’ve assumed that the “entry salary” for a Berlin-based founder who doesn’t have kids is $50,000. I’ve then assumed that that amount increases to $75,000, $95,000 and $115,000 when you reach funding and revenue milestones that roughly correspond with a Series A, Series B and Series C round, respectively. I don’t think founders should get salaries that make them rich, but as soon as the company can afford it the founders should get enough so that they don’t have to be worried about how to make ends meet all the time. And if a little more allows them to outsource some errands and chores after a 100-hour-work-week I’m all for it!

Family

It might surprise you to hear this from a venture capitalist, but my approach to founder salaries is a little communistic: I think founder salaries should not be based on performance alone but should also take into account what the founder needs. If that means that one founder gets more cash than the others because in contrast to them he or she has a family to take care of, that’s fine with me. A founder’s cash compensation doesn’t reflect the value which she contributes to the company anyway, so who cares if one of them gets a little more than the others.

My model, therefore, assumes that for each kid you add $10,000 (multiplied by the location factor, more on that soon). Whether this is the right amount is of course debatable, and there can be other aspects besides having children that need to be taken into account.

The “need-based” approach can, of course, go both ways: if a founder had a sizable exit already, he may want to forgo his salary or reduce it to a symbolic amount, at least in the first few years. I did that at my last startup, Pageflakes, and thought that besides saving the company some money it can also have a positive impact on the company culture if people know that the founder’s interests are 100% tied to the company’s success.

Location

The third factor that I’ve included is location. I’ve defined Berlin as 1.0x and have assumed that in Paris, London and San Francisco, you’ll have to pay yourself 1.3x, 1.5x and 1.8x as much in order to have a similar standard of living. These ratios are roughly in line with the data published on this website. If you want to find out the ratios for other cities, take a look.

Notes

  • The numbers in the model reflect what I think is market and fair based on the data points that we have and some industry benchmarks that we were able to get. However, our data set is quite limited and the numbers produced by the calculator should by no means be taken as the ultimate truth. If you disagree with my assumptions or have seen different numbers in the market I’d love to hear from you!
  • I saw a study according to which founder salaries are much lower. According to this data source, 75% of Silicon Valley based founders pay themselves less than $75,000, with 66% paying themselves less than $50,000. Based on these numbers, even for companies that have raised more than $10M the average salary is only $81,700. This looked odd to me, and maybe the difference is due to the fact that the study is three years old. I ignored this data source for now, but again, suggestions and input are very much appreciated.
  • The model assumes that the founder gets a fixed salary with no bonus. I’m not strongly against including a bonus component in a founder’s package, but I think it’s usually not necessary. If you own a big chunk of equity, I don’t think you’ll need a performance bonus to be motivated and rewarded.
  • The model doesn’t differentiate between the founding CEO, tech founder and other roles. In the first couple of years it’s usually not necessary to differentiate based on the founder’s role because everyone in the founder team carries a similar load. At a later stage, when the company has a bigger leadership team, it makes sense that the CEO gets more than the other founders. The numbers in the model are calibrated for founder CEOs, so you may want to reduce the amounts for other founders at the Series B or C stage.
  • The calculator shows the results for the various stages and locations simultaneously, so you can easily compare the numbers side-by-side. The number of kids, however, needs to be entered (column I). If you enter a different value here, the numbers in column K and column P will be updated accordingly. Showing the results for various numbers of kids simultaneously would have added a lot of additional permutations and would have made the sheet very large.
  • The blue numbers are input variables and you can change them if you’d like to adjust the model. The brown numbers can be changed, too, but aren’t used as inputs for the calculation. To play around with the numbers please make a copy (File > Make a copy).

Wednesday, October 04, 2017

Knowing when to scale (and how to prove that you can do it)

When you’re talking to investors about a Series B, Series C or later round, one of the questions that will inevitably come up is “What are your CACs?”. It sounds like a simple question, but from the question of what costs to include and the right way to account for organic traffic to the pandora box of multi-touch attribution, there are lots of devils in the details.

What's more, the real question is not "What are your CACs?" but "What will your CACs be if you invest $10-20 million in sales & marketing?". It’s hard enough to calculate historic CACs for different acquisition channels with a high degree of accuracy. It’s much harder to predict future CACs at bigger scale.

And yet it shouldn’t come as a surprise that later-stage investors are so focused on this question. When you’re raising a Series B or later round, you’ve achieved Product/Market Fit (which is hard to define, see me attempt here) and you’ve got what Jason M. Lemkin calls “Initial Traction” and “Initial Scale”. At that point, the biggest thing standing between you and building a $100M+ business is finding scalable and profitable customer acquisition channels. Obviously you still have to overcome lots of other challenges along the way, but if you’re at $5-10M in ARR and you are confident that you’ve found scalable sales and marketing channels you are in an excellent (and rare) spot.

So how do you know if your customer acquisition channels will scale, that is, if a 10x increase of your sales and marketing spend will lead to a 10x increase in new customers? Consumer Internet startups are sometimes in the fortunate position to have found a profitable customer acquisition channel that offers huge potential for expansion. If ads on TV, YouTube or Facebook work for you, you might be able to increase your spending by 10x (and maybe much more) because these platforms have such a gigantic reach. In the B2B SaaS world this is very rare. Mass-market advertising won’t work because there’s way too much ad wastage, and targeted ads usually don’t give you the volume to easily 10x your spend.

Without a careful keyword volume analysis, being able to profitably spend $10k a month on AdWords doesn’t mean much in regards to your ability to spend $100k a month. If you spend small amounts on AdWords you will by definition (AKA by algorithm) capture the lowest-hanging fruits. As you’re trying to spend more, prices will go up. You might be able to offset the price increase by optimizing your campaigns, landing pages, onboarding, etc, but don’t take it as a given.

The underlying problem is that the existing “hot demand” for your product – people who are actively looking for a solution – is usually quite limited. The good news is that the amount of “lukewarm demand” – companies that would benefit from your product but aren’t aware of it yet – is usually much larger. That’s why content marketing is so critical in SaaS: it allows you to capture leads at a much earlier stage of the discovery process. But scaling up your content marketing by 10x is not as straightforward as simply 10x-ing your ad budget.

So how do you know, in B2B SaaS, if you’ve found scalable acquisition channels?

Nothing is completely certain here, but one great sign that should give you a lot of confidence is if you can hire new salespeople and the new hires (once they’re ramped up) are hitting their quota. If you add two AEs, add another two, and then another two, and most of them are hitting quota it shows that you’re able to increase the amount of high-quality leads. If that wasn’t the case, your growing sales team would quickly start fighting for the best leads and some of your salespeople wouldn’t be able to hit their quota any longer. Equally important, it also shows that you’ve managed to industrialize the sales process to a certain extent. Firstly, it doesn’t take the founders or superstar salespeople to sell your product, it can be sold by “normal” people. And second, you’ve managed to attract the right people, to set up the right processes and infrastructure and to create the right incentive structure and culture that is required to make a sales team successful.

Besides a growing, successful sales team, there are a few other factors that you can look at when you’re trying to decide if it’s time to put the pedal to the metal:

1. Are you able to make outbound sales work?
Doing outbound at reasonable CACs is usually very hard because you’re dealing with lots of unqualified leads. It requires lots of persistence from every AE and your sales leader as well as a strong commitment from the founders, since a serious attempt to make outbound work can cost a lot of money and time. The beauty of outbound sales is that if it works for you, you may have found a highly scalable customer acquisition channel: emailing or calling every single target customer in the world will keep your sales team busy for a while. :)

2. Have you managed to increase your SEM budget consistently and significantly without negative effect on CACs? What is your impression share, and how large is the search volume that you can still tap into?
As mentioned above, past performance in scaling an SEM budget from A to B alone is not a reliable indicator of future performance to scale from B to C. But in combination with a thorough analysis of the relevant search volume it can be a relevant data point.

3. Have you built a content marketing “machine” that consistently generates more leads month-over-month? 
If you can consistently increase inbound/content leads for some time, it means that you’ve found your narrative, or “North Star”; started to build content distribution channels; and managed to attract the right marketing people and make them effective. (Check out this great post from my colleague Clément for much more about this.)

If there are other aspects that you’re looking at to decide if you’re ready to scale, I’d love to hear about them in the comments below!

Thank you Rodrigo and Janis for reviewing a draft of this post and the valuable feedback.


Friday, August 25, 2017

A sneak peek into Point Nine's investment thesis

Over the last couple of weeks and months we spent some time putting our investment thesis on paper. The purpose of this exercise was to challenge and discuss our implicit assumptions and to get everyone on our team aligned on what kind of investments we seek.

One of the things that being very clear about our investment focus helps with is getting to “no” faster. If that sounds pessimistic, remember that we see thousands of potential investments every year but can only do 10-15 of them. Just like it’s crucial for sales teams to have clear qualification and disqualification criteria, it’s important for us to focus our time on “higher probability deals”. That means we’ll have to be able to quickly pass on a large number of deals that are likely not a good fit for us. Our “filter” is of course not perfect, so we’ll inevitably pass on lots of great companies, some of which will end up in our growing anti-portfolio – but there aren’t enough hours in the day to take a close look at each company that we see.

A fast decision process is also important for founders. As we’ve learned from this survey, being left in the dark is the single most important reason why fundraising often sucks for founders. We will obviously never be able to make decisions based on a simple algorithm, if only for the fact that the founding team remains the most important of all criteria. But anything that helps us streamline our decision making process is welcome.

Once the document is in a publishable form we will post it. Bear with us for a little while as we’re polishing the document a bit to make it more self-explanatory and to remove the worst typos. ;-) In the meantime, here’s a sneak preview.

We will continue to focus on two business models: SaaS and marketplaces


SaaS

  • We use a broad definition of SaaS. Usually the first “S” stands for “software”, but sometimes it stands for “something”, e.g. a combination of software and hardware or software and data.
  • We’re interested in horizontal and vertical SaaS. What counts is that the startup is aiming to solve a big enough problem for a large enough number of potential customers in order to build a big business. As a rule of thumb, we’re looking for markets that consist of at least 3,000 whales ($1M ACV), 30,000 elephants ($100k ACV), 300,000 deer ($10k ACV) or 3M rabbits ($1k ACV). 1
  • We’re equally interested in companies targeting SMBs (AKA rabbit and deer hunters) and companies targeting enterprises (AKA elephant and whale hunters). What’s important is the right founder/market fit. For companies targeting very small businesses (AKA mice and rabbit hunters) we want to see the potential for viral distribution.
  • We’re looking for companies that we think can build a 10x better product and/or drive a paradigm shift in the industry. 2
  • We want to invest in companies that can eventually build moat e.g. by becoming a system of record or a system of intelligence”; by building a large data set that in combination with machine learning translates into a superior product; by building a platform; or by becoming a SaaS-enabled marketplace.
  • With very few exceptions in areas like accounting, we’re looking for companies that have the potential to win the US market.
  • We’re looking for SaaS companies that have the potential to get to $100M in ARR within 7-8 years and to $250-300M ARR within another 2-3 years.

Marketplaces

  • Like in the case of SaaS, we use a broad definition for marketplaces. For us, a marketplace is a digital platform that brings two or more parties together and enables them to “transact”. The object of the transaction can be a physical product, a digital product, a service, or in some cases a piece of information or knowledge.
  • We look for startups that leverage marketplace dynamics to create unique user experiences in fragmented markets, with the potential to develop a moat through network effects.
  • We believe that marketplace platforms will continue to emerge in the most unexpected of places and in the most unexpected of forms. They will continue to transform entire industries.
  • We are open to all of C2C, B2C, B2BC and other types of marketplaces. We are particularly excited about B2B marketplaces andSaaS enabled marketplaces.
  • We are trying to identify platforms able to become international leaders. Thus, we will typically look for early proof of ability to operate in more than one country or globally.
  • We are looking for early signs of liquidity. 3
  • We look for founding teams with strong commercial sense.
  • We think that blockchain technologies have the the potential to disrupt many marketplace models as we know them today; we will be exploring them in depth.
  • We look for marketplaces that can become truly significant. In monetary terms, this means the potential to ultimately generate hundreds of millions of dollars in annual net revenues and billions in GMV.

Thanks for contributing this section, Pawel. Expect a follow-up post with more details from Pawel (who’s leading most of our marketplace investments) soon.


We will continue to invest in new areas and technologies that we like to dub “Frontier Tech”


  • While we’re focused on two business models – SaaS and marketplaces – we’ll continue to keep our eyes wide open with respect to new technologies.
  • We’re extremely interested in new opportunities in areas such as AI/ML, blockchain and cryptocurrencies, IoT and hardware-as-a-service, drones, or AR/VR. We have already made investments in most of these areas and will continue to do so.
  • In many of these cases there are complex tech problems that must be solved. We’re happy take a certain level of technology risk, but at the same time we’re looking for founders who find ways to bring a product to the market quickly and cheaply.
  • While a superior technology will usually be key to entering the market and have some early wins, most technologies will eventually be commoditized. Therefore we’re looking for additional sources of long-term defensibility such as high switching costs and large data sets (see the section on SaaS above) or network effects (see the section on marketplaces above).

Thanks to Mr. Frontier Tech Rodrigo for your help with this section, and looking forward to your follow-up post as well.

We will continue to focus on early-stage investments


  • We’ll continue to focus on seed investments, investing anything from a few hundred thousand dollars up to around $2M in “seed” and “late seed” rounds, typically in companies that have strong indications of Product/Market Fit and promising early traction.
  • We will continue to make what we call „founder bets“: Idea-stage investments into proven entrepreneurs from our close network. In these cases most of our „rules“ don’t apply. When people like Doreen Huber, Fabian Siegel, Iñigo Juantegui, Pan Katsukis, Sebastian Diemer or Stefan Smalla start something new, we want to be part of it. 4

We will continue to invest internationally


  • Europe is our home market – we’ve made investments in most European countries and we’ll continue to invest all over Europe.
  • Especially in SaaS we will continue to invest outside of Europe as well – e.g. in the US, Canada, Australia, New Zealand and other countries.
  • In SaaS, our assumption is that you can start almost anywhere but you have to win globally (which requires winning the US). In marketplaces we want to find companies that can win several large markets.

We continue to aspire to be a “Good VC”


  • We don’t pretend to be the right investor for every startup. But our aspiration is that if we do invest in a company, we’re the absolute best partner the founders can dream of and that we’ll play a significant role in helping the company get to the next stages.
  • We’re optimizing for the long run in everything we do. You “always meet twice in life”, as the German saying goes.


_________________________

1 Check out this post if you have no idea what I’m talking about. Then, get your poster.
2 See Sarah Tavel’s post about “10x better and cheaper products” for a similar concept from the consumer Internet world.
3 Defining liquidity is tricky – a topic for another post!
4 True story – these are all guys who we backed or worked with closely before and who subsequently founded Lemoncat, Marley Spoon, OnTruck, Remerge, Finiata and Westwing, respectively.

Wednesday, July 05, 2017

WTF is PMF? (part 2 of 2)

In the first part of this post, I looked at what some of the most knowledgeable people in the industry said about Product/Market Fit (PMF) and how they try to define and measure it. While everybody seems to agree on the broad concept of PMF there is (unsurprisingly) no consensus on how exactly it can be defined and measured, and some people set the bar much higher than others. For example, according to Brad Feld you find PMF somewhere between $100k and $1M in MRR, while others argue that you can have PMF with much lower revenues.

In this part I’d like to talk a bit about my view on PMF and how we try to detect it when we look at SaaS startups at Point Nine. Here’s my favorite definition of PMF, inspired by many of the people mentioned in the first part of the post:

Product/Market Fit means having a product that solves a problem for a significant number of independent customers.

Note that this definition intentionally doesn’t say anything about market size. Lots of companies have PMF for a very small market, but addressing a small market is not a reason to deny a company its PMF.

If we talk about PMF for “VC cases”, i.e. the type of company venture capital investors are looking for, I would adjust the definition as follows:

Product/Market Fit means having a product that solves an important problem – without custom work and better than existing solutions – for a significant number of independent customers in a large market.

The next step in getting to a solid definition would be to define the pieces that this definition includes: How “important” is important enough, and how can it be measured? How much “better” is better enough, and how can it be measured? And so on.

There are no clear answers to these questions and – sorry – I don’t think there is a razor-sharp way of defining and measuring PMF. Some companies clearly have PMF, some clearly don’t. Others are somewhere in the middle – they have indications of PMF but it’s not clear if they will ever get to strong PMF. Most seed investments that we’re considering fall into the last bucket.

Here’s an overview of the most important factors that we’re looking at when we try to assess the degree of PMF of a SaaS company. In isolation, none of these factors can tell you if you have PMF or not. But taken together, it can hopefully give you at least a good indication:





This concludes my mini-series on Product/Market Fit (at least for now). Let me know if you have any feedback!

___________________________

1) For more background on the concept of rabbit/deer/elephant hunters, check out this post.
2) Take a look at this post to read more about "expected usage frequency".
3) This is from Sean Ellis’ test for PMF. More on this here.