TOBI

After five years as a director at Vend, yesterday was my final meeting.

I’ve written here about a number of milestones in the Vend journey to date: from the bike ride where I first got the pitch, the announcement of our first investment round, Vaughan describing the early history in his own words, notes from our recent visits to San Francisco, watching the team expand, and more recently the search for a “real” board.

So, I thought one final post would be appropriate.

It’s been a privilege to be part of the team from the beginning. It doesn’t feel like that long ago we were putting together cheeky advertisements and videos and hoping that people would notice.

A billboard concept. Probably better this never saw the light of day…

POS Advert

Steve, the potty mouthed, bigoted and small minded, crappy old 1980s cash register, finally meets his fate…

An early recruitment video…

Thankfully, people did notice. Suddenly we had retailers from all around the world using our software to run their business. And more and more of them over time!

As the team expanded, it was great to be able to spend some time in Auckland, Melbourne, San Francisco and Toronto with the local people who are working hard to make Vend a success.

We have also been joined along the way by some of the very best SaaS investors – from here in New Zealand and from Germany, Australia and the United States.

When you look back on this sort of thing it always seems like time is short. So, it’s easy, generally, to be motivated by negative FOMO – the fear of missing out. But, in this case, my overwhelming memory will be TOBI – the thrill of being involved. Thanks to Vaughan and the team for having me along for the ride so far. And, especially to Miki, Barry and (too briefly) Claudia and Sarah for your support as part of the board over the last couple of years.

Vend is in an exciting period as the team works to put the business on the right track for the next phase of growth. To everybody involved now, I remain an enthusiastic investor and will watch with interest to see where you can take it from here. You have a huge opportunity to be part of something special, and I know you’ll make the most of it!

Xero visits Dr SaaS

A few weeks ago Xero released their latest interim report for the six months ended 30-Sept.

I thought it would be interesting to plug these results into Dr SaaS, to see what the diagnosis shows us about how they are tracking.

Most of the details we need are in the report which is available on the investor centre section of the Xero website.

Revenue

There were 371,000 subscribers at 30-Sept, and total operating revenue of $54.295m. They report average monthly customer churn of 1.3%.

Starting with 284,000 subscribers at 31-Mar (from the previous annual report) they added 87,000 new subscribers net. So, if we assume a churn rate of 1.3% that works out to be ~109,200 new acquisitions offset by churn of ~22,200 subscribers.

xero-revenue

Based on these values Dr SaaS calculates growth of 3.91% per month, and and ARPU of just over $27 per subscriber per month (which is slightly less than the $29 value they include in the report).

Dr SaaS also estimates the average tenure of a new subscriber to be approximately 53 months, or nearly 4.5 years, which is pretty sticky! If you’re interested there is more information available about how Dr SaaS estimates tenure.

Profit

Next, we split out the acquisition and service costs. This is all done for us in the report – the total “cost of revenue” was $18.016m and “sales and marketing” was $38.329m.

xero-profit

Based on these values Dr SaaS breaks that down as $165 per new subscriber and just over $19 per month to service each subscriber. The profit margin is calculated to be 17.86%, which is to be expected given the focus on investing in growth.

Runway

To calculate the runway we need to also include the other revenue and expenses that don’t relate directly to subscribers.

Again the report includes all of the details we need – “other income” was $1.48m (this is a combination of government grants and rent received), “interest” was $4.128m and “other expenses” were $27.35m (mostly the cost of software development etc). The cash balance at 30-Sept was $170.8m.

xero-runway

Based on these values Dr SaaS calculates the break-even point (based on the current burn rate) to be around 944,000 subscribers. The runway is just over 43 months (again, based on the current burn rate).

Diagnosis

Based on all of this Dr SaaS gives Xero a pretty good diagnosis:  “you’re bleeding a little, but you’ll survive”.

Overall the lifetime value per subscriber is positive – total revenue per subscriber of $1428 offset by acquisition costs of $165 and service costs of $1008, leaving a gross profit of $255 per subscriber.

xero-diagnosis

See the full summary

This is obviously a pretty rough and inaccurate analysis. To do this properly you’d want to understand a lot more detail about growth and performance in each of the different markets where Xero operates, as well as the trends in terms of ARPU, churn, and acquisition costs for different channels etc. However, as a quick exercise it’s useful to give a high level overview.

You can try Dr SaaS for yourself, using either your own numbers, or (if you just want to have a play) using the public details from one of many listed SaaS companies. Hopefully going through the process will teach you a little about the SaaS business model.

http://drsaas.md

We’d love to hear what you think.

Estimating Tenure

The key number that Dr SaaS needs to calculate in order to diagnose your SaaS business model is average tenure, or, if you prefer, the life expectancy of a new customer when they subscribe to your service.

To calculate the lifetime value of a customer (LTV) you just need to know how much you earn on average from them each month (ARPU), how much it costs you on average to acquire a new customer (CAC), how much it costs you on average to service a new customer (CTS) and how long you can expect them to remain a customer (Tenure). ARPU, CAC and CTS are all easily derived from your financial statements. But, tenure is not so straight forward.

The way this is typically calculated is using the current churn level, which is the rate at which existing customers currently cancel:

Churn = Cancelled Subscriptions / Total Subscribers

For example, if you have 500 subscribers and 12 cancel during the month, then your churn rate is 2.4% per month.

Then:

Tenure = 1 / Churn

For example, if your churn rate is 2.4% then your average tenure using this formula is just under 42 months (or 3.5 years).

This sort of makes sense: if you have 12 cancellations every month then after 42 months all 500 subscribers will have cancelled.

However, in practice this approach often ends up over estimating the actual tenure, as Jason Cohen (aka A Smart Bear) explains in his great blog post on this topic:

“It’s impossible to see ahead to timeframes beyond a few years for a young company and perhaps 4-6 years for a mature one. In those timescales you expect drastic changes in market conditions — a strong new competitor appears or dies, the economy slumps or soars, a disruptive technology changes the landscape, etc.

That in turn will cause material changes in pricing, retention rates, reorganized customer segmentation, usage levels, service levels, and so forth.

Computing expected months with the ad infinitum approach leads you to over-estimate the total revenue you can depend on.”

This skew is especially evident if your churn rate is low as the inverse value increases rapidly at this point:

Alternative Tenure Calculations

So, what to do about this? Jason suggests two alternative approaches – either capping the number of months or using a discount rate.

Tenure = 1 / (Churn + Discount)

This option does product lower estimates of churn when the churn rate is low (and as he points out who cares about what it does if the churn rate is very high, as in that case you likely have much greater problems to deal with than what tenure formula to use!)

Alternative Tenure Calculations

In Dr SaaS we use a third option which gives values somewhere between these two extremes when the churn rate is less than 2%, but lower values when the churn rate is higher.

Tenure = ln(0.5) / ln(1 – Churn)

While this looks complicated, it’s just using the churn rate to work out how many months it takes before half of the new customers in a given cohort have cancelled.

Consider the example above, where tenure is estimated to be 29 months (compared to 42 months for the simple formula):

Month 0: We start with 500 subscribers
Month 1: 500 * 2.4% = 12 cancellations, leaving 488 subscribers
Month 2: 488 * 2.4% = 12 cancellations, leaving 476 subscribers
Month 3: 476 * 2.4% = 11 cancellations, leaving 465 subscribers
Month 4: 465 * 2.4% = 11 cancellations, leaving 454 subscribers

Month 28: 259 * 2.4% = 6 cancellations, leaving 253 subscribers
Month 29: 253 * 2.4% = 6 cancellations, leaving 247 subscribers

At this point, 50% of our original 500 subscribers remain, so we take this as our average tenure.

You can see how this looks on the graph:

Alternative Tenure Calculations

If you want to try this out with your own subscriber numbers, check out Dr SaaS:

http://drsaas.md

What do you think?

How are you currently calculating tenure? How does it change your results if you use this formula instead?

We’re interested to hear any suggestions.

Track Record

Early-stage investment is a dark art.

Very few investors are forthcoming about their results, and so there is a lot of misunderstanding about what is “normal”.

The common belief seems to be that you just need to invest in ten companies and one of them will be a winner. I actually don’t think those sort of results are typical. My observation is that most investors have a selection bias which skews their returns significantly in one direction or another.

Either way, I thought it might be helpful to others to consider my own experience to date.

My first early-stage investment post Trade Me was Xero, in March 2007. It was a relatively easy decision, as I was also joining the team ahead of the IPO later that year. With the benefit of hindsight, I probably should have stopped after that, and I could now claim a 100% hit rate!

Instead, in the seven years since then I’ve made fifteen further direct investments. I’ve also made follow-on investments in six of these.

In total I have invested just over $4m so far.

This is the list in chronological order 1:

Sonar6 is the only real exit to date, after they were acquired by Cornerstone On Demand in April 2012. As an investor in their later rounds, that represented a ~2x return for me.

Four are sold or confirmed dead (in a couple of those cases there were very small amounts returned to investors, but only cents on the dollar so more of a gesture than something that should be considered a return) and one other is missing presumed dead, so 31% by count or circa 16% by value invested have resulted in a loss of the money I invested. That compares favourably with the 40% figure that Fred Wilson has written about although, as he says, that’s maybe just a signal that I’m not taking enough risks.

Thankfully, I’ve invested larger amounts in the companies which have been successful thus far. This is partly good luck and partly, I think, a function of the approach I take – typically investing a small amount at a reasonable valuation initially and then more later, once the company has proven they can execute and start to scale and as a result have significantly reduced the risk.

Xero is clearly the biggest success on that list at this point. The small portion I’ve sold has repaid my initial investment several times over, and the majority that I retain is worth more than all of the others combined, even after the recent share price correction. I remain very long and patient.

I’m also very optimistic about Vend and Timely, which take a large chunk of my time today. I am chairman at Vend and a director at Timely.

Atomic, Revert and Respondly are three recent investments, so far too soon to tell, but I’m very excited to be working with all of them too.

And, the jury is out on a few of the others – I’m hopeful there may be a couple more winners in that list too.

Overall, the portfolio doesn’t owe me anything at this point.

On top of that I’ve also gained some useful scars from the early failures. This is what I mean when I say get started and be prepared to suck for a bit. I suspect that is actually the only option, if this is something you’d like to be good at.

Some of the biggest lessons, so far:

I’ve learned it’s better to invest in the best companies, not the most companies. As the list gets longer I feel less and less inclined to do more and more.

I’ve learned that investing passively from the sidelines doesn’t provide much personal satisfaction, even if it goes well for the company, so my recent investments have been in ventures where there is an opportunity to get involved in some capacity in addition to investing cash 2. The downside with this approach is that time is finite. At the moment I have my hands full to overflowing with the things I’m already invested in and working on, so I’m focussed on those rather than looking to add anything new into the mix (and, as I have to constantly remind myself, focus means saying no or, aspirationally, having an assistant to say no on your behalf).

I’ve learned that you can achieve a lot more if you’re not worried all the time about who gets the credit, but if you take that approach you have to assume that you won’t get the credit and be comfortable with that.

I’ve learned that as a potential investor aimless networking, coffee meetings and events are a black hole, and you can spend all your time there, but it doesn’t really help you to find the best investments or contribute much of value to the companies you’re already working with.

Time will tell how this goes.

It will be interesting to look back at this list in another seven years and see whether the companies that I think are the possible winners now actually worked out that way, or if there were any surprises. And, who knows if there will be more names to add to the list which at the moment are nothing more than an idea.

I continue to make it up as I go. No doubt there are many more lessons to come.

Perhaps this post will prompt other local early-stage investors to talk more openly about their own results and experiences too. If so, please add a link in the comments below.


 

Notes:

  1. There are a few things excluded from this list, where my investment was a token amount. I have excluded the projects I’ve worked on with the team at Southgate Labs, such as Triage. They are not material to the calculation because my investment there has been predominantly time rather than cash. I’m also a small investor in the latest Movac fund, however it would be generous to count any of their investments as mine in this context so they are also excluded.
  2. In practical terms this means spending a day or so each month working with the founders on whatever they need help with, and being available in between those times via video or email to answer questions or be a sounding board – usually for things like strategy, planning, finance, legal and recruitment (or the opposite!) Ironically, these days, less and less of my time is spent on product or software development, even though being good at that was what earned me the right to be in this position in the first place, although I’ve typically invested in ventures where those skills are well represented in the team already.