A KPI dashboard for early-stage SaaS startups – new and improved!

[Update 01/17/2015: There's a new company called ChartMogul (which we invested in) which makes it easy to get a real-time dashboard similar to the template below. Check it out!]

[Note: This post first appeared as a guest post on the blog of Totango. In case you don't know Totango, it is a powerful analytics product which gives online services the information they need to increase user engagement, conversion and retention. If you're a SaaS company you should check it out. Thanks to Guy Nirpaz and his team for publishing my post, which I am republishing here.]

In talking to a pretty large number of SaaS entrepreneurs in the last few years I've observed that there's a considerable amount of uncertainty around metrics: Which KPIs are the most important ones, what's the right way to calculate churn, CACs, MRR and other key metrics, how can I estimate customer lifetime value – these and other questions come up all the time, and the answers aren’t always obvious.

I've tried to address some of these questions in a couple of blog posts:

• 9 Worst Practices in SaaS Metrics
• Excel template for cohort analyses in SaaS
• The 8th DO for SaaS startups - Stay on top of your KPIs

I also put together a template which I thought SaaS startups could find useful and which also makes it easier for us as a VC to communicate what KPIs we're looking for when we talk to SaaS entrepreneurs. Needless to say a template can only be a starting point, as every SaaS startup is different and needs to build its own, customized dashboard. Nonetheless it seems like the template, first published in April of this year, struck a chord with many SaaS founders and investors: The blog post got more than 60,000 page views (which I assume is quite a lot for a niche topic on a VC blog, at least if you’re not Fred Wilson :-) ) and I get requests for the Excel file every day.

In the meantime I’ve put some more work into the dashboard. You can download it here. (And if you like it, tweet it!)

Here’s how the charts look like with some sample data in it:

Click for a larger version

The main improvement of this version is that it now includes different pricing tiers and annual plans. This makes the spreadsheet considerably larger, but I feel it's necessary if you have multiple pricing tiers and contract lengths, and you can collapse a lot of the rows to get a concise view of the top KPIs.

I hope you find it useful! If you have any questions, comments or suggestions, please feel free to email me at christoph@pointninecap.com.

OKRs – objectives and key results

Last night I returned from a 2-day offsite with the Point Nine team (in Schlepzig, of all places). Our (small) full-time team more than doubled in the last six months, and this was the first time for all of us to spend some time together away from the daily bustle. We had a long list of topics that we wanted to discuss, ranging from investment theses to portfolio companies and to a number of projects that we're working on.

I wanted to kick off things with a session about our OKRs (objective and key results), and we had scheduled two hours for this agenda item. If you haven't heard about OKRs before, it's a methodology invented by Intel and popularized by John Doerr, the famous VC who invested in Netscape, Amazon and Google. The idea is (simply put) that a company needs to have clear objectives and that every department, team and person in a company needs to have objectives – and a set of key results for hitting those objectives – which are aligned with the company-wide OKRs.

We ended up spending the entire first day and some more time of the second day on this topic. This is particularly funny because I wasn't even sure if it's worth talking about our OKRs since I was wondering if they aren't obvious anyway.

Now, to be precise we didn't spend ten hours talking about our high-level long-term objectives. At a high level our goals are pretty obvious and I've written about them here. But diving in deeper and deeper brought us from one question to the next question, and by the time we were finished with the OKR session we've covered most of the topics which we had planned to discuss in other sessions. So on the one hand we completely screwed up the schedule that we had put together, on the other hand we covered most of the stuff that we wanted to get done in the end.

After this experience I am now even more convinced than before that every startup should use OKRs or a similar methodology to ensure that everyone in the company is on the same page and that there are clear and measurable goals. Scott Allison, founder & CEO of Teamly, wrote a great summary of the benefits:

• It disciplines thinking (the major goals will surface)
• Communicates accurately (lets everyone know what is important)
• Establishes indicators for measuring progress (shows how far along we are)
• Focuses effort (keeps organization in step with each other)

But isn't this a no-brainer, don't all companies have a plan for the company as well as targets for most employees? Yes and no. All bigger company presumably have a budget and plan in place which is aligned with the company's objectives, but my guess is that what's often missing is linking that high-level plan to every employee's targets and communicating it throughout the entire organization. I'm pretty sure that if you randomly picked 100 employees of any Fortune 5000 company and asked them about the objectives of their companies you'd get lots of different answers. And in a fast-growing startup which doubles headcount every year and where each individual employee can have a much bigger impact than in a large enterprise, it's even more important that everyone is on the same page.

If you want to learn how Google (where John Doerr helped introduce OKRs) sets goals, watch this video from Google Venture's startup lab.

The 8th DO for SaaS startups - Stay on top of your KPIs

“What gets measured gets done” – it seems like the source of this quote, often attributed to management expert Peter Drucker, isn’t certain, but its meaning is clear and very relevant for every SaaS founder. If you want to make sure that you make best use of your scarce resources, you need to have a clear understanding of your objectives and the KPIs that measure your progress towards those objectives.

Depending on the stage that you’re in you’ll want to focus on different metrics. I’ve tried to illustrate this in the following diagram:

(click image for larger version)

As you can see, I segmented the company lifecycle into three major phases: pre product/market fit, post product/market fit but pre-scale, and post-scale (being fully aware that there is no distinct definition of “product/market fit” and “scale” and that the transition from one phase to the next one is a gradual one). At the bottom I noted what these phases usually mean in terms of the stage of your product and company and which funding level it typically corresponds with. Note that the x-axis is not a true-to-scale representation of time elapsed. For a true-to-scale representation I would have to add much more space between the Series A and the Series B and between the Series B and the Series C.

The key message of the chart is that in the beginning you can focus on a small set of metrics, but as time goes by and you’re making progress you need to add additional KPIs to your cockpit.

Let’s have a closer look at each of the three phases.

Pre product/market fit

I’ve written about it before in my posts about sales and unscalable hacks: In the very beginning, when you’re in the process of finishing the first version of your product and trying to get the first customers, you shouldn’t worry too much about metrics. Firstly there just aren’t many metrics to keep an eye on yet. Secondly you should be obsessively focused on getting to product/market fit (Marc Andreessen’s words), and that means you should spend your time talking to customers and developing the product.

That said, the following metrics are relevant in the pre product/market fit phase:

• User feedback: Most of the user feedback that you collect in this phase is qualitative rather than quantitative, but if you talk to a larger number of potential users you might also be able to add some quantitative elements. For example, you could ask users to rate your prototype and see if that rating goes up over time.
• Development velocity: I don’t know if (or how strictly) you should use a software development methodology like Scrum, which allows you to nicely visualize your development velocity, in the very early days, when you’re maybe just two developers – I would be very interested in your thoughts on that question. At any rate, however, I think it’s a good idea to break down your project into a larger number of smaller pieces, features or “story points” early on. This will help you in getting an understanding of your development speed, which later on will become more and more important.
• Waiting list signups: When you put up a landing page to collect email addresses for your waiting list, track how many signups you’re getting. Driving signups probably isn’t a key priority for you at this stage but it’s an indication of interest in your product and hey, you’ll still have some space on your Geckoboard which you can fill with a nice chart! :)

Once you let potential customers try your product, the real fun begins. At that point, you should track signups and some indicators for activation and usage, which, for obvious reasons, are precursors to your ultimate goal, paying customers. What the right indicators for activation are depends on the type of your product. It could be a profile completion and the setup of a customized pipeline in case of a CRM application, the installation of a tracking snippet for a Web analytics product or… you get the idea. Similarly, usage metrics are highly specific to your application, so think about what the right events and parameters are in your particular case and make sure that you instrument your application accordingly. If your solution is a little more enterprisey and you’re working with a higher-touch sales model you may also want to track qualified leads along with trial signups.

In order to succeed you need happy customers who do free marketing for you, otherwise customer acquisition will always be an uphill battle. Therefore you should also consider regular Net Promoter Score (NPS) surveys. If you’re looking for the best survey tool, I have a tip for you.

Post product/market fit, pre scale

As you’re slowly but surely getting to product/market fit and starting to get the first paying customers (yay!), your trial-to-paid conversion rate becomes one of the most vital metrics. It’s hard to give you a benchmark, since your conversion rate not only depends on the quality of your product and the onboarding experience but also on many other things such as leads quality, pricing and many other factors. With that caveat in mind, the typical range that we’re seeing is between 5% and 25%.

Equally important is your retention, usually tracked by measuring churn (the inverse of retention), since your CLTV (customer lifetime value) is a direct function of how much you charge your customers and how long they stay on board. As a very rough rule of thumb you should try to get your churn rate to 1.5-3% per month.

Make sure to track churn not only on an account basis but also on an MRR basis. Your MRR-based churn rate will hopefully be significantly lower than your account-based churn rate, since smaller customers tend to have a higher churn rate and because your loyal customers will hopefully pay you more and more over time. Also, make sure that you avoid SaaS Metrics Worst Practice #8, mixing up monthly and yearly plans. Finally, if you want to get a good estimate of your customer lifetime, take a look at retention on a cohort basis.

If you don’t have a KPI dashboard yet that gives you an at-a-glance look at your key metrics, now is the time to build one. Here’s a template that I’ve created, along with some additional notes.

As you’re moving on, arguably the most important metric becomes MRR, and specifically net new MRR that you’re adding each month. Net new MRR is calculated using this simple formula:

Also keep an eye on your ARPA (average revenue per account). It’s an important metric at all times for obvious reasons, but as you’re nearing the next phase it’s becoming even more important.

Post scale

When you’ve reached a certain level of success, say you’re at around $500k MRR, the biggest challenge (besides growing a bigger organization and mastering all kinds of growing pains of course) is to find ways to profitably acquire customers at a much higher scale. By this time you’ve picked all the low-hanging fruits, and you may have maxed out what you can reasonably spend on AdWords to buy traffic and leads.

Therefore you’ll have to focus on the relationship between your CLTV and your CACs (customer acquisition costs), your CLTV/CAC ratio, which measures the ROI on your sales and marketing investments. Another way to look at it is your CACs payback time, which tells you how many months of subscription revenue it takes to recoup customer acquisition costs. If I had to choose I’d pick this one, since CLTV is always an estimate which can be more or less accurate.

A few last points:

• Many startups struggle to get all these numbers together because different numbers are collected in different systems (e.g. Web analytics software, billing systems, self-made databases,...), which often leads to inconsistencies. I don’t have a simple and general advice for this issue, I might address it in another post.
• If you’re not sure which metrics to track, e.g. which events in your application, err on the side of tracking too much data even if you have no immediate use for it. You never know if it becomes useful in the future, and the costs for tracking large amounts of data are no longer very high nowadays.
• If you want to read more about SaaS metrics, I highly recommend David Skok’s blog and Joel York’s blog, as well as Jason M. Lemkin and Tomasz Tunguz.

That was it for the 8th DO for SaaS startups – questions, comments and suggestions are as always very welcome!

[Update 01/17/2015: There's a new company called ChartMogul (which we invested in) which makes it easy to get a real-time dashboard of your SaaS metrics. Check it out!]

Impressions from the PNC SaaS Founder Meetup 2013

A little more than a week ago we did the second PNC SaaS Founder Meetup. Around the same time a year ago we organized our first SaaS Founder Meetup in San Francisco, this time we did it in Berlin.

Thanks to the incredible speakers and guests who came to the event it's been a truly amazing day, and I think all of the SaaS founders returned with a number of actionable insights which they can't wait to implement.

I was going to write a longer post about the event but decided to create some slides instead which hopefully capture a little bit of the great spirit of the meetup. Here you go:



If you want to view the presentation on SlideShare, here's the link.

Excel template for cohort analyses in SaaS

[Note: This post first appeared as a guest post on Andrew Chen's blog. Andrew is a writer and entrepreneur and has written a large number of must-read essays on topics such as viral marketing, growth hacking and monetization. He was kind enough to publish my post on his blog, and I am republishing it here.]

If you’re a long-time reader of my blog (or if you know me personally) you’ll know that cohort analyses are one of my favorite tools for getting a deeper understanding of a product’s usage. Cohort analyses are also essential if you operate a SaaS business and want to know how you’re doing in terms of churn, customer lifetime and customer lifetime value. I’ve blogged about it before and have included “Ignore your cohorts” in my “9 Worst Practices in SaaS Metrics” slides.

My feeling is that over the last 12 months the awareness for the importance of cohort analyses has grown among startup founders. One reason may be that thought leaders like David Skok have been writing about the topic, another reason are web analytic tools like MixPanel and KissMetrics that make it simple to create cohort analyses.

And yet, many founders are still having difficulties with cohort analyses, be it with the collection of the data or the interpretation of the results. With that in mind I wanted to create a simple cohort analysis template for early-stage SaaS startups.

You can download the Excel file here.

The idea is that you have to enter only a small amount of data and everything else is calculated automatically. Specifically, what you’ll have to type in (or import from a data source) is the basic cohort data: How many customers did you acquire in each month and how many of them were retained in each subsequent month. If you also want to see your churn on an MRR basis and get a sense for your CLTV, you’ll also have to enter the corresponding revenue numbers.

If you’re not sure how to read a cohort analysis, here’s a quick explanation:

Here are some brief notes on each of the arrays in the sheet:

A1: This is where you enter the raw data. Start with January 2013 and enter the number of new customers that you’ve acquired in that month. Then move to the right and enter how many of those January 2013 customers were still customers in February, March, April and so on. Then move on to the next row. If your data goes further back than January 2013, extend the table accordingly.

A2 and A3: A2 takes the data from A1 and shows it in “left-aligned mode”, making it easier to compare different cohorts. As you can see the columns have changed from specific months to “lifetime months”. A3 shows the number of churned customers as opposed to the number of retained customers. Both A2 and A3 aren’t particularly insightful to look at per se, but the data is necessary for the calculations in B1, B2 and B3.

B1: Shows the percentage of retained customers, making it easy to see how retention develops over time as well as to compare different cohorts with each other. What you’ll want to see is that younger cohorts are getting better than older cohorts.

B2. This is kind of like the “inverse” of B1, showing the percentage of churned customers as opposed to the percentage of retained customers. In any given row, the sum of the percentages of churned customers plus the percentage of retained customers equals 100%.

B3: B3 is similar to B2, but the difference is that churn isn’t calculated relative to the original number of customers of the cohort but relative to the number of the cohort’s customers in the previous month. Let’s say you have a cohort with 100 customers and after 6 months the cohort has been reduced to 50 customers. If you lose 5 customers in month 7, this represents 5/100=5% churn in B2 but 5/50=10% churn in B3.

So what’s the correct number? There’s no right or wrong here, it depends on the question that you want to ask. If you want to know e.g. “How many customers do I lose within the first six months?”, B2 (in conjunction with B1) gives you the right answer. But if you want to know what percentage of customers you’re losing per month (important when you look at data across multiple cohorts and for lifetime estimates), take a look at B3.

What you’ll want to see in this table is that after a usually relatively high churn rate in the first lifetime months churn starts to stabilize (because the people who never really adopted the product in the first place are now gone).



C1-C3: Same as A1-A3, just for MRR instead of customer numbers.

D1-D3: Same as B1-B3, just for MRR instead of customer numbers. What you’ll want to see is that your MRR churn is lower than your customer churn due to account expansions.

E1 and E2: If you enter the CACs for each cohort, these tables show you when each cohort breaks even.

Also take a look at the second tab in the Excel sheet, which calculates/estimates customer lifetime and customer lifetime value on a cohort basis. Note that the data is highly speculative for younger cohorts for which there isn’t much data yet.

Further notes are included in the Excel sheets.

If you have any questions or comments, please feel free to reach out!

The 7th DO for SaaS startups – Build a repeatable, profitable sales process

The last post in my series on DOs and DON'Ts for early-stage startups was about lead generation. The next logical step is sales, and so I want to write about what you can do to convert as many of those leads into paying customers.

7th DO for SaaS startups

Build a repeatable, profitable sales process

Sales is a very different animal depending on the stage of your company, the market segment you're going after and on whether we're talking about inbound sales or outbound sales. For all the differences, though, the goal is always to create a scalable process which allows you to acquire customers for a small fraction of their CLTV. As a rule of thumb, you should aspire a payback time of 6-9 months, meaning that you spend 6-9 months' worth of subscription revenue to acquire a customer. It really is just a rule of thumb though, since depending on the customer lifetime and various other factors, you may want to accept a significantly longer payback period.

To achieve a payback period in that neighborhood you have three options:

1. If your ARPA is around $20-50 per customer per month, you need to be able to generate a large amount of leads for little money and convert them with little to no human interaction (self-service with no/low touch sales)
2. In order to support an inside sales force you need customers who pay you around $100 per month, preferably significantly more (often called "transactional sales").
3. If you need a field sales force to sell your product, assume that your ARPA needs to be at least $3000 per customer per month if not higher (enterprise sales).

Most people would argue that you need much higher prices to make inside sales work (including Jason M. Lemkin, who says you need at least $300/m), but several of our portfolio companies have shown that due to a combination of high conversion rates, fast sales cycles and sales people in countries where salary levels are 50-80% lower compared to Silicon Valley, you can use inside sales people to profitably acquire customers at much lower price points.

So – take the specific numbers with a grain of salt as they are highly dependent on a variety of individual factors. The important message is that your customer lifetime value defines what you can spend on customer acquisition. If you don't keep that in mind you'll end up in what Joel York, who created a nice visualization of the different models, calls the "startup graveyard".

In line with the theme of this series I'm going to focus primarily on the self-service and transactional models and want to break down my tips & tricks into three parts based on the stage of your company. I'm going to call them "pre product/market fit", "pre scale" and "post scale" (being well aware that the transitions between these phases are gradual). I'll focus on inbound sales in this post and will follow up with one on outbound sales shortly.

Pre product/market fit

• In the beginning, while you're still trying to figure out product/market fit, spend as much time with potential customers as possible. Don't consider the time spent with customers a sales expense – it's an essential investment that you need to make in order to solve a real problem of real people.
• Don't worry about scalability yet. In this phase it's perfectly fine to do things that are completely unscalable. As I wrote before, a good "unscalable hack" for SaaS startups is to spend huge amounts of time with early users.
• Don't worry about processes or tools, don't even worry about metrics (if you know me a bit you know that you won't hear me say this often!). Be "obsessively focused on getting to product/market fit", as Marc Andreessen put it.

Post product/market fit, pre scale

When you've found product/market fit and start to get more and more signups every month, some of the things that you did in the previous phase start to not work any more. As long as you get 50 signups a month you can still talk to every trial customer. Once that number gets into the hundreds or thousands, you need to hire people and put some processes and tools in place.

So the goal of this phase is to maximize the conversion rate of a large and ever-increasing trial volume while keeping customer acquisition at an acceptable level and starting to get a sense for the scalability of various sales and marketing channels. With that in mind, here are some tips:

• Set up an automated lifecycle email program to welcome new users, reach out to inactive users and follow-up with users towards the end of their free trial. Solutions like userfox (a portfolio company of ours) or Intercom make it easy.
• Send personalized messages to as many trial users as possible. Use any piece of information that you can easily get e.g. by looking at the trial customer's website or the way he uses your software to add some personal touch. This job can be done by junior customer support or sales people. The idea is to make every trial customer feel important and show him that you care, but do it in a highly scalable way. 
• Segment your trial users based on factors like potential account size, activity and brand and use this information to prioritize the queue for your inside sales people. A lot of this can be automated e.g. by checking a trial customer's Alexa rank or Google Page Rank to get an indication of the company's size. Also take a look at Totango, which can help you identify your most valuable prospects. You can also use this information to assign different types of potential customers to different types of sales people (e.g. small businesses are assigned to junior customer care people, bigger ones are assigned to more senior Account Executives).
• Set up a lead nurturing program for trial users who are only moderately interested in your product or don't have an immediate need for your product yet. Send them a newsletter, offer webinars, organize events... The goal is to provide them with valuable content and stay top of mind, so that when they eventually need a solution they'll think of  you.
• Track everything and do lots and lots of tests. A/B test different messages, find out the best moments and triggers for your lifecycle emails, test in-app messaging... In short: Try lots of different things and measure what works best.
• Avoid SaaS Metrics Worst Practice #3, which is to attribute all conversions to your sales team. To calculate the effectiveness and the ROI of your sales team you have to measure the conversion uplift relative to your unaided baseline conversion.  
• You can still do things that you know won't scale, but you should know what these things are and leave this phase with an excellent understanding of your CACs at scale.

Post scale

In this phase you're going to double down on what you've found to be working in the previous phase. Sounds easy, but it of course comes with its own challenges: Hiring, onboarding and retaining the right people; continuing to fill the funnel with enough leads to keep your sales team busy; adapting processes  and tools for a much larger sales team. At this point it's primarily a management challenge, and if you've come this far without hiring a seasoned VP of Sales, now is the time to hire one. And since this series is geared towards early-stage SaaS startups I'll leave it with this. :)

Failure IS an option

Failure may not have been an option for the Apollo 13 mission, but it certainly is an option for startups. In fact, since statistically the majority of startups fail, you could argue that it's the default option.

Most successful entrepreneurs have a few failures under their belt, and most "overnight" successes are the result of years' of hard work – and in many cases years' of trial and error. Before writing history with Angry Birds, Rovio had already launched 51 games that you've probably never heard. Brian Chesky described AirBnB as a an "'overnight' success that took 1,000 days".

I've had my fair shares of failures as well. It took me a text adventure for the C64 (never completed), a mail-order business for Amiga shareware (a decent success for a student business, but discontinued when the Amiga died), a PC real-time simulation game (nice game, but didn't manage to get it properly distributed) and several other attempts before I had a decent success with DealPilot.com, which I co-founded in 1997. Likewise, as an investor I've made several investments that didn't work out before landing my first big hit with Zendesk.

Considering how normal and necessary failure is in the startup world, it's surprising how many VCs are afraid of admitting failure when it happens: Logos are quietly removed from portfolio pages^*, asset deals are arranged to make it look like a successful exit, PR stories are written. What's even worse is if the death of a dying startup is delayed by putting more money into it, all out of fear of admitting failure.

If you invest in early-stage startups, you know that a large part of them, maybe more than half, won't make it. The rest of the world knows it too. So why not be open about it?



* We're guilty of this too, but we're thinking that we should keep all logos on the page and add a "R.I.P." badge when a startup died. What do you think?

I'm selling my SaaS dashboard and all it costs is a tweet

My financial planning sheet for SaaS startups, my KPI dashboard for SaaS startups and my "9 Horror Worst Practices in SaaS Metrics" slides got a fair bit of popularity lately and two hundred or so people emailed me and requested one of the original Excel files.

That brought me to the idea of selling them. But fear not, I don't want your money, all I want is a tweet. Or a Facebook post. (And if you really want to get one of the files without tweeting, drop me an email and I'll send it to you, although I can't guarantee that it's not bad for your karma.)

So...here are the "pay with a tweet" links:

Financial planning

Dashboard

Worst Practices

9 Worst Practices in SaaS Metrics

9 Horror Worst Practices in SaaS Metrics

As mentioned in my last post, I recently did a talk about SaaS metrics and I said I'm going to upload the slides. The slides don't contain a lot of text as they were not meant to stand on their own, but I've added a few additional notes to make them a bit more useful. 

You can view the presentation on SlideShare.

PS: Last week I held a session about the same topic at Seedcamp in London – thanks Philip and team for inviting me!

KPIs for VCs

Example for a Geckoboard KPI dashboard

Last week I spent a day in Stockholm to attend a metrics seminar organized by our friends at Creandum. It was a great event with talks from people of some of the best Internet companies from the Nordic region such as Spotify or Wrapp. Thanks Johan, Joel, Daniel, Frederic and everyone at Creandum for setting it up and inviting me!

I did a talk about SaaS metrics (I'll post the slides shortly), and in the Q&A session Andreas Ehn asked a really good question:

"As a VC, what are the most important KPIs for yourself?" 

Ultimately our #1 KPI is the return that we deliver to our LPs. If you're new to the world of venture capital, LP is short for "Limited Partner" and means the people and funds which have invested in our fund. That return is expressed as a return multiple or as the internal rate of return (IRR). As it obviously takes a lot of time to build (and eventually sell or IPO) great companies it will of course take many years until we know our final performance. Like most VCs our fund is set up for a lifetime of ten years.

In the meantime we (and other VCs) track our performance by:

1) Adjusting the value of our portfolio whenever a portfolio company raises a new round of financing from a new investor at a new (hopefully higher) valuation. While there's no guarantee that we will ever sell our shares at these "Fair Market Valuations" (FMVs), the assessment of the portfolio based on current FMVs is usually the best way to measure success. Valuations are usually marked up on an ad hoc basis internally (i.e. when a new round closes) and reported to LPs on a quarterly basis.

2) Monitoring our portfolio companies' key financial data, KPIs and operational performance. This is the best near-time proxy to long-term success, and so we're constantly looking at these things. We usually get either access to live dashboards or monthly reports and I'm hoping that we'll soon find the time to create a beautiful Geckoboard dashboard with the top KPIs across the entire portfolio (requires some work because we get data from portfolio companies in a variety of different forms and shapes).

Besides these pretty obvious ones there are a few other KPIs that we're looking at:

Number of deals that we're evaluating

It's not a KPI in the sense that there's a direct "the higher the number, the better it is" correlation, as quality of deal-flow is of course more important than quantity. But there is a connection between quantity and quality, and since we're using Zendesk to track each potential investment it's easy to monitor this number (for what it's worth, we're currently at deal #3,773 since we started using Zendesk about two years ago, and in the last 30 days 148 new ones have been added). 

Response time for investment inquiries

For founders it's important to get fast responses, even if the answer is "no". Depending on our workload sometimes we're fast and sometimes we're slow. There's still a lot of room for improvement, so this is a KPI that we're going to keep a closer eye on in the future.

"Rating" of our responses

Zendesk allows you to let your end users rate the customer support experience for every support ticket. We're not using this feature yet, but I'm wondering if we should do it in order to keep track of how successful we are in leaving positive impressions with the entrepreneurs that are pitching to us.

How well are we at picking the right investments?

Of all the potential investments that we look at, how well are we at picking the winners and avoiding the losers? And how well are we doing when it comes to allocating follow-on investments among our portfolio companies? We're not yet using a simple set of KPIs to track this, but we're regularly reviewing our past deal flow, trying to understand when we were right and when we were wrong and what we can learn from it.

Finally, there's one other KPI, and while it's again not something you can quantify on a short-term basis, it's just as important or even more important than our fund performance in the long run: It's the concept of Net Promoter Score applied to us. What it means is that when we ask our portfolio founders two simple questions – "Would you raise money from Point Nine in your next startup?" and "Would you recommend Point Nine to other founders?" – we want to hear two wholehearted YESes.

PS: Just like Web startups have their vanity metrics, you can also hear VC talk about vanity metrics – i.e. metrics which sound good but don't mean much. I'll leave that for another post.

Ideas we'd like to invest in: Mobile-first SaaS

Following my posts about electronic signing and vertical SaaS, here's another area that we're very interested in:

SaaS solutions with a mobile-first approach

While my first two posts of this series were fairly specific, this one is pretty fuzzy as I don't have a good sense for what I'm looking for. I just have a feeling that there are huge opportunities ahead for startups which rethink how people will use business applications in the future. This feeling is based on a couple of factors:

• The incredible rise of smartphones and tablet computers, combined with ubiquitous Internet connectivity. Global mobile traffic as a percentage of total Internet traffic has grown from 1% less than three years ago to more than 13% today. In India and other countries, mobile traffic has surpassed desktop Internet usage already, and very very soon there will be more smartphones and tablets than desktop PCs and notebooks. (Taken from Mary Meeker's Internet Trends report – always a good read.)
• In sectors or jobs in which people are on the road almost all the time, people spend much more time with their mobile device than with their desktop computer already. But since the leading SaaS companies have been started before the mobile revolution took off, even if they have developed mobile apps in the meantime their products have not been built with a mobile use case in mind from the ground up. Makes me wonder if there's an opportunity to become to Salesforce.com what Instagram is to Flickr. And field sales people are just one example of course – think about places like hospitals, construction sites or factories where using tablets makes a lot of sense as well.
• The unique capabilities of mobile devices – location-awareness, built-in cameras, touchscreens to name just a few examples – allow the creation of entirely new features, products and user experiences. There are lots of examples for amazingly innovative mobile apps which take advantage of these capabilities in the consumer world, but business apps seem to be lagging behind in this respect.

So...if you're working on a mobile-first SaaS startup, let me know!

Ideas we'd like to invest in: Industry-specific SaaS solutions

Following my post about electronic signing I'd like to describe another area that we'd like to invest in. It's not a specific idea this time, rather a category of startups that we're very interested in:

Industry-specific SaaS solutions

I talked about the topic before when I wrote about "The land of a thousand niches" and touched on it in my "1st DO for SaaS startups". There are several reasons why we're so excited about vertical SaaS solutions. *

• Focusing on a specific vertical simply allows you to build a better product for the industry that you're after. Whereas a generic product needs to be the lowest common denominator for different types of customers, a vertical solution can be tailored exclusively to the needs of your specific target audience.
• By the same token, a vertical focus also allows you to tailor your messaging to one target group. Take our portfolio company Clio as an example. Look at their website and think about how much weaker their proposition would be if they had to keep it generic to address a broader target audience.
• Knowing exactly who your target group is also makes sales and marketing much more straightforward. It means you'll know which publications your target customers read, which conferences they attend, which other products they use, and so on. You can even get their names and addresses from the yellow pages or other directories. And because people in an industry usually talk to each other a lot, it's easier to get a critical mass of mindshare which is so important for organic growth.
• Competition tends to be less intense in verticals. Maybe because building a SaaS solution for field-service businesses like landscapers and snow removers doesn't appear like the sexiest thing on Earth, maybe because opportunities in verticals don't seem large enough for big enterprises. This gives you a chance to dominate a category and achieve extraordinarily high market share.

Boris Wertz, a good friend and co-investor in two vertical SaaS solutions, Clio and Jobber, recently wrote about the topic as well and has some additional points.

I have one caveat regarding vertical SaaS solutions: Make sure that the vertical that you're going after is big enough, i.e. aligned with your ambition with respect to the size of the company that you want to build. Expanding from one vertical into another one isn't easy. Maybe you won't have to start from zero, but the very reasons which make a vertical strategy attractive in the first place can also mean that most of the value that you've built in one category (domain expertise, product/market fit, mindshare,...) can't be easily transferred into another category.

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* This doesn't mean that we're not excited about SaaS startups which don't have a vertical approach. If you focus on a specific part of the value chain (e.g. accounting, marketing, sales) it makes perfect sense to go horizontal. It's the "practice management" type product, which encompasses a large part of the value chain, for which I recommend the vertical approach.

A KPI dashboard for early-stage SaaS startups

[Update 12/20/2013: I have extended the dashboard to include multiple pricing tiers and annual subscription plans. Check it out here.]

[Update 01/17/2015: There's a new company called ChartMogul (which we invested in) which makes it easy to get a real-time dashboard similar to the template below. Check it out!]

Over the last few years I've helped quite a lot of SaaS startups to create or fine-tune their KPI dashboards. While every situation is a bit different there's also a lot of overlap, which made me think that it would make sense to publish my template (not without polishing it a bit). I hope other SaaS startups will find it useful, and it will also make it easier for us to communicate what KPIs we're looking for when we talk to SaaS entrepreneurs.

Not surprisingly the dashboard looks quite similar to the financial planning sheet that I've posted some time ago. Below are two Excel screenshots, and 

here is the Google Docs version.

If you prefer the Excel version, which looks a bit nicer, click here to download it. (And if you like it, tweet it!)

The sheet contains some notes on the right side. I was going to note a few additional things here but it's gotten really late here in Europe so I'll leave that for another day. If you find any bugs, let me know and I'll fix them tomorrow morning. :)

One comment, though. Although I've developed this sheet on my own, I've learned a lot about SaaS metrics from David Skok, who I am very thankful for. David created a SaaS dashboard as well, it's a bit more sophisticated and has a slightly different focus, but it's quite similar. Check it out, and if you have not read his brilliant articles about SaaS yet I highly recommend that you do so. They are an absolute must-read for every SaaS entrepreneur.

Like this post? Follow me on Twitter.

Ideas we'd like to invest in

Inspired by Paul Graham’s “Startup Ideas We’d Like to Fund” post of a few years ago I’d like to start a series of posts about ideas that I find exciting and that we at Point Nine would be very interested in investing in. Here's the first one.

Electronic signing

I’m a huge, huge fan of electronic signing. Whenever I have to sign a document and I’m getting a “Please eSign...” email I rejoice because it saves me the hassle of printing, completing, signing, scanning and emailing the signature pages (don’t get me started on snail-mailing paper copies with original signatures!). This is of course especially true if you’re traveling and don’t have access to printers constantly. Apps like SignEasy and SignNow, which target the “signer” and let you e-sign PDF documents from your iPhone, are a pretty good solution and can be a live-safer if you’re sitting in a cab and have to sign an important document. Products like EchoSign, DocuSign, RightSignature and HelloSign, which are geared towards the signature-collecting parties, are even better in that they take care of the entire e-signing process from creating documents to collecting signatures and archiving signed contracts.

There are a couple of reasons why I think e-signing is not just a great product but also a great business:

• The product is inherently viral. Very rare for SaaS solutions. That means low customer acquisition costs which, combined with a good revenue model, are a killer.
• The product is valuable for individual users but becomes even more valuable if it’s used by an entire department or an entire company, which means you can use a Yammer-like land-and-expand strategy to get into bigger accounts. 
• It seems easy to find a good pricing structure which lets you combine an affordable entry-level plan for small customers (or even a free plan) with expensive plans for large customers, since the value delivered to customers (and hence willingness to pay) should correlate strongly with the number of contracts and number of users.

Now – there are a couple of well-funded players already, and EchoSign, following its acquisition by Adobe, has been integrated into Acrobat Reader, giving the product massive distribution as well as an entry product that is geared to the “signer side”. So the big question is if there’s still room for a new entrant.

I don’t have a clear answer, but given that the vast majority of signatures are still done on paper and that the US players seem to have very low penetration in Europe I’m wondering if there could still be an opportunity – maybe for a European champion, maybe with a vertical approach, maybe with a mobile-first strategy or another special twist?

The 6th DO for SaaS startups – Fill the funnel

Here's another post in my series on DOs and DON'Ts for early-stage SaaS startups:

6th DO for SaaS startups

Fill the funnel
Or: Focus on inbound marketing, but
 try lots of things and double-down on what works

In this post I'm going to write about lead generation for SaaS startups. When I edit the series later on I might merge it into my 4th DO (Make your website your best marketing person) to have one post on marketing. Let's see.

To make it clear right away, unfortunately I can't tell you what's going to work for you in terms of getting a large number of potential customers to your site. In fact, my key message is that there is no magic bullet when it comes to lead generation and that you'll have to try lots of things, put in lots of time and effort, double down on what works and execute extremely well. I haven't seen a SaaS company yet which gets more than 50% of its leads from one particular distribution partnership or marketing channel (except maybe word of mouth if you want to count that as a lead source).

Compared to that, marketing for consumer Web startups can be relatively straightforward. If you are a travel startup or an online shop, for example, millions of people search for your products or services online so you can use SEM, affiliate marketing, banner ads and other proven tactics to acquire large numbers of customers. In addition you can do TV advertising as your products are interesting for a relatively large percentage of the population. Getting the economics right and making it work at scale is of course a huge task and a science of its own, don't get me wrong on that.

But the particular challenge in SaaS marketing is that in many cases there isn't a huge amount of demand (a.k.a. search volume on Google), so the number of customers that you can acquire via AdWords is often quite limited. And things like TV advertising obviously don't work because of the huge waste circulation ("waste circulation" was the best translation I could find for the German word "Streuverlust" – does anyone know a better one?).

Just because you have a great solution doesn't mean that people are actively looking for it. That's not to say that you have a solution in search for a problem, but people may not be aware that there is a better way of doing things. What that means is that you need to find – and be found by – the people who your product is geared towards, often at a stage when they are loosely interested but are not yet ready to try (let alone buy) your product. Give them something that is useful to them. Write about the topics that your target group is interested in and provide lots of useful high-quality content and tips and tricks in a variety of formats, e.g. blog posts, white papers, case studies, videos, webinars, infographics or podcasts. Make sure that you don't talk too much about your product and that what you're publishing is really interesting to your target group. Sooner or later, some of these people will try and eventually buy. That's the whole idea of inbound marketing and lead nurturing. If you're not yet familiar with those concepts you should start learning more about them. A good starting point is Hubspot.

Zendesk is of course a great example for excellent inbound marketing. On its site the company provides a wealth of resources that are valuable for anyone who's interested in customer service, everything from tips for hiring customer service reps, to a guide to multi-channel customer support to numerous case studies and much more (including funny videos like this one). All of this helps to establish Zendesk as the go-to site for the help desk industry.

As for other ways to fill the funnel, here are some thoughts on things that you can do (in no particular order and of course by no means exhaustive):

• PR: Very important, and can get you off the ground in the beginning. Build relationships with the important bloggers, journalists and opinion leaders in your space and supply them with news. In the long term try to become an opinion leader yourself. Use Facebook, Twitter, Quora, conferences and events to reach out to the important people in your space.
• Most products are not inherently viral, but think about whether there are (sensible) ways to build virality into the product. If you can't find any you can still launch a referral program and reward users for recommendations to increase referral rates at least a little bit.
• Marketplaces, app stores, API partnerships, integrations, partnerships with hosters and the like: Don't expect huge volumes of leads from them, but they can be a meaningful lead source (and add value to your product).
• SEM & SEO: While you shouldn't bet on it alone, this is a very significant lead source for almost all SaaS startups that I know, so it's worth spending time and money on it.
• Ads on Facebook and LinkedIn: Personally I haven't seen great results with Facebook or LinkedIn ads for SaaS companies, but given the vast targeting options that you have there I think it's worth trying. If you've made it work I'd love to learn more.
• Display ads: Similar story, most of the time it doesn't work very well, but if there are suitable industry sites or blogs you may want to try it. 
• Retargeting: Can work very well. Obviously rather a nice supplement than a real needle-mover since the amount of visitors that you can target is limited by the amount of visitors who you've attracted in the first place.
• Promoted tweets: I don't have a lot of experience with advertising on Twitter, but I think it's worth a try, too.
• Distributors, VARs and similar channels: Tends to work better for traditional software with high license fees, setup and training requirements etc., but I've seen some good success in SaaS as well. Usually better for satisfying existing demand than for generating the demand in the first place, i.e. don't expect your channel partners to create the awareness for you.
• Local meetups: Once you have a number of customers in a region, organize local meetups. Nothing beats putting a bunch of happy customers and prospective customers into one room!
• Telesales/telemarketing: Hard to make it work, but if you can pull it off it can scale extremely well.

Finally...if you have trouble reaching your target group, try to put yourself in the shoes of the persons that you're trying to reach. Imagine how a typical day looks like for them. What websites do they visit, what might they be looking for on the Web? What magazines do they read, which industry associations might they be part of, what other products do they use, which people do they spend time with? Thinking about it this way will hopefully spark your creativity and let you come up with some fresh ideas.

Why I'm happy to be a micro VC

Last week we announced the closing of our new fund, Point Nine Capital II. The most important information about the new fund is included in our official press release, but I wanted to write a brief blog post to give you some additional background and share some personal thoughts.

When we set out to create the new fund last year, the goal was to raise €30 million. Since we're quite new to the VC game and didn't have any relationships with institutional investors, raising the fund took us quite a while. We're all the more happy with the result – not only did we end up raising €40 million, we also managed to get leading private equity fund-of-funds like Horsley Bridge Partners on board. Ironically, while it took us quite some time to raise the first €15 million, in the end we could have raised more than what we did if we had wanted to. I'm sure this will sound very familiar to many startups.

While the fund size means we are a "micro VC", at least by US standards, we feel it's a pretty sizable fund for early-stage Internet investments in Europe. The fund size will allow us to invest in around 40 companies over the course of the next few years, while keeping significant reserves for follow-on investments into our portfolio companies. It will also allow us to hire some people to help us with administrative and other tasks so that Pawel, Nicolas and I (plus the new truffle pig that we're looking for at the moment) can focus most of our time on what we like best – finding new investments and helping our portfolio companies.

The importance of follow-on capacity is one of the things that I've learned as an angel investor. As an angel investor who invests his own money it's hard to keep a lot of reserves. That can be problematic not only for the angel investor (who sees himself getting diluted starting with the A round) but also for the portfolio company if it needs to go back to the market to raise more money from new investors too quickly. I wouldn't say that I've learned this the hard way, but having a fund is definitely a big plus in this respect.

While we have more firepower than private investors, we're still small enough to not have to deal with the challenges faced by large VC funds. If you have a €300-500 million fund it's really hard to find investments which can move the needle or "return the fund", in VC lingo. There just aren't many companies that can put something like €20 million to work and turn it into €200 million. And if you look as the market as a whole, there just aren't enough €1B+ exits to allow a bigger number of large funds to deliver great returns to their LPs. The micro VC fund size also works well with our "angel VC" approach (which means fast decisions, no big committees, founder-friendly terms, simple term sheets, hands-on support and generally a no-bullshit attitude). 

Don't get me wrong, I loved being an angel investor and if I didn't do Point Nine I'd still be one (and needless to say, angel investors fulfill an incredibly important role in the startup ecosystem). As for the other end of the spectrum, I genuinely admire VCs who manage to deliver great returns on large funds. But it's a different game, and not the one I want to play.

That is why I'm happy to be a micro VC.

Do you have what it takes to become a truffle pig?

A few weeks ago, Fabian, who worked as Point Nine's associate from the very beginning, has left to create his own startup, Wunsch Brautkleid. Hence we're now looking for a new Investment Associate to complement our investment team.

Here are all the details.

Please check it out and help us spread the word!

The 5th DO for SaaS startups – Get your pricing right

Following some advice on choosing the right market (here and here), building a team with product/tech DNA and the importance of an awesome product and an awesome marketing website I would now like to turn to the topic of getting your pricing right:

5th DO for SaaS startups

Get your pricing right

If you're following this blog for a little while, a part of this post won't be new for you because I wrote about the topic before and will repost a large part of it here. But I'm going to add a few new thoughts as well, especially about Freemium.

As you're getting close to the launch of your product you'll have to make a number of decisions around pricing:

1. Will there be a free plan?
2. What pricing model am I going to use?
3. How much am I going to charge?

Pros and cons of Freemium

Starting with the first question, there is no general answer on whether you should or should not adopt the Freemium model. Having a free plan can be extremely powerful in getting large numbers of users quickly but there are costs to it. Here are some of the factors that you should consider:

• How much does it cost you to serve a customer? While the marginal costs for hardware and bandwidth to serve an additional customer are of course very low, keep in mind that when you offer a Freemium model you might very well end up with 95% free customers and 5% paying customers. So assuming your CoGS are the same for free and paying customers (which may not be true), the free plan might increase your costs for hardware and bandwidth by a factor of around 20. Also consider the burden on your support team when you think about the costs to serve free customers.
• Is there a natural upgrade path from free to paying? That is, do you think a free plan will allow you to attract users who will eventually upgrade to a paid plan e.g. because their business grows or because they need premium features? Or would a free plan primarily attract users who will never pay for your product and who you might not be interested in acquiring at all?
• How price sensitive is your target group?
• Do you have a good idea for defining the limitations of the free plan? Will you be able to offer compelling reasons for upgrading?
• Is there an opportunity to make money off the non-paying customer base using alternative revenue channels? Or are there network effects in your business that let you benefit from a large user base?
• Is there strong competition? Are you in a "land grab" situation?
• How well are you funded, can you afford to give low priority to short-term revenues?

A good example for a successful Freemium model is MailChimp, the popular email marketing solution. MailChimp offers a free plan that lets you send up to 12,000 emails per month to up to 2,000 subscribers. If you look at the questions above you'll notice that for an email marketing solution there's a strong case for Freemium. Most of the aspects are pretty obvious (costs to serve a free user can be calculated fairly precisely, smooth upgrade path, high price sensitivity due to strong competition). One maybe less obvious aspect is that its large base of free users allows MailChimp to process and analyze hundreds of thousands of email lists and billions of email addresses. This for sure gives MailChimp lots of valuable insights which small competitors don't have. For example, it allows MailChimp to build a database of invalid email addresses which they can use to reduce bounce rates for their customers and thus become a better emailer (from the perspective of spam detection), improving email deliverability rates.

By the way – if your product doesn't lend itself well to a Freemium offer, try to think of something else that you can give away for free to get users and make them aware of your paid product. This could be an add-on to your core product, a mobile app or a small separate product. Hubspot's website grader is a great example.


Using the right model, charging the right amount

Let's move on to the second and the third question from above – what pricing model am I going to use and what should I charge?

It’s obvious that getting pricing right is extremely important: If you’re too cheap you will leave money on the table and reduce your ability to invest in customer acquisition. You may also hinder adoption especially from bigger customers who think that your product can’t be good because it’s so cheap. If you’re too expensive you might be scaring away the majority of your potential customers.

Unless your target customers are all very similar (which is unlikely), the most important thing that your pricing model has to accomplish is to capture different amounts of money from different customers based on their willingness and ability to pay, which correlates with the value that they’re getting from your product. In the old enterprise software world this used to be the job of the sales people – talk to the customer, find out about his needs, get a sense for what he can pay, offer him a solution and negotiate a price. In the world of SaaS, customers (rightly) expect more transparency and will look for a price list on your website before they start a trial.

In many cases a per-user pricing (often also referred to as “per seat”) is an obvious choice, and some of the most successful SaaS companies including Salesforce.com are using that. Other successful examples include pricing based on:

• number of clients managed with the software (e.g. Freshbooks)
• number of newsletter emails sent (e.g. MailChimp)
• number of email recipients in the system (e.g. ConstantContact)
• amount of storage that is used (e.g. Dropbox)
• number of events tracked (e.g. KISSmetrics)

What these companies have in common is that they've found an "axis" that highly correlates with their customers' willingness to pay, which allows them to keep their service affordable (and in some cases free) for small customers while asking bigger customers for much more. It also allows them to benefit from the growth of their customers, since a growing company needs more seats/emails/MBs/events/etc over time. Ideally this can lead to what is known as "negative churn" – the wonderful situation when the MRR growth of some customers of a customer cohort more than offset the effect of terminations from that cohort.

Importantly, most successful SaaS companies differentiate their prices along more than one axis (David Skok wrote about this here). Secondary axes include the level of support, additional features or other usage parameters. For example, Freshbook's pricing is based on a combination of the number of clients that you can manage and the number of seats, plus two additional factors:

So what's the right pricing model for your SaaS startup? The right answer is of course "it depends", and all I can do is offer a few practical tips:

• Try to find one or more axes which correspond with the value that your customers are getting from your product and which correlate with your customers' willingness to pay. Talk to your customers and analyze how your early users are using the system to find out the ways in which larger customers are using your product differently from smaller customers.
• If you don't know how much to charge, take a look at the prices of other products in the market and try to get a sense for the value that customers get from your product. How much time and thus money can a customers save with your product? Does it allow your customer to increase revenues?
• In the beginning, err on the side of being too cheap rather than being too expensive. In the beginning the most important thing is to get customers. You can optimize your margins later.
• Later on, make sure you're not leaving too much money on the table. If not a single customer ever complains that you're too expensive that's a strong sign that you're too cheap. Also keep in mind that a higher ARPU means more money that you can reinvest in customer acquisition and that a higher ARPU can open up completely new ways of acquiring customers, so higher prices can also be a driver of customer growth.
• Accept the fact that it's very unlikely that you will get your pricing right at the first shot. Go out with something that you think makes sense, get feedback from the market and be prepared to make changes quickly.
• If you increase prices, try to do it along with new value-add features that help justify the price increase. And offer your existing customers extremely generous grandfathering terms.
• If your pricing is differentiated based on features, consider giving all users the high-end plan with all features during their trial so that they can play around with the full product.
• Maybe not necessary to mention since these are all known best practices, but just in case: Give users a self-service free trial. Offer monthly pay-as-you-go subscriptions that users can cancel at any time. Provide an option to pay in advance for a year (with a discount). Create a clean, beautiful pricing page. 

Unscalable hacks

Recently I stumbled on the term "unscalable hack", in a blog post by Chris Dixon. This really struck a chord with me because it's a very important concept for many startups but I didn't have a term for it until I read Chris' post.

What exactly is an "unscalable hack"? Google doesn't return a lot of useful results and neither does Quora, so let me try to explain it. In the context of programming, using an unscalable hack means programming something in such a way that it works under very specific, limiting conditions (e.g. with very few concurrent users) but won't work with a larger number of users. The advantage of a solution like this is that it doesn't take a lot of time to develop so it saves you money and time, but the disadvantage is that it, well, doesn't scale and that you're accumulating technical debt.

In a business context, unscalable hacks are actions that you use to dramatically decrease time-to-market, solve chicken-egg-problems or overtake competitors, all the while knowing that you can't operate like this forever. In some cases the success of these hacks can be a make-or-break factor for a startup.

Marketplaces and social networks are particularly prone to these tactics since these types of businesses require you to reach a certain critical mass in order to be successful. Take an auction site as an example: As long as there aren't many buyers on the site, it's not attractive for sellers to list their items on it. And as long as there aren't many sellers, the site is not very useful for buyers. It's a classic chicken-egg-problem, and unscalable hacks can help you solve it.

Here are some examples of unscalable hacks that I'm aware of:

• In the early days of PayPal, PayPal reportedly listed lots of products on eBay and made PayPal the only accepted payment option for these products. I don't know if it's a true story, but either way it's brilliant. :-)
• AirBnB offers people who want to list their apartment on the site professional photo shootings of their apartment for free (maybe this actually isn't unscalable, I don't know).
• Lead generation marketplaces which send free leads to the supply side in the beginning and generally invest a disproportionate amount of money and time into acquiring the first providers.
• Mobile app creators who hope to start a virtuous circle by buying their way into the app store top listings.
• In SaaS, a good unscalable hack is to spend huge amounts of time with your early users to turn them into happy users and evangelists.

Solving the chicken-egg problem that is inherent to marketplace-like models is so mission critical that it sometimes leads to unscalable hacks that are ethically highly questionable, for example dating sites that use faked profiles to attract people to their sites.
The oldest well-known unscalable hack, or maybe a close relative of it, is maybe to give away oil lamps and make money by selling the oil. :-) If you know any good ones from the more recent past I'd love to hear them!