Toward Open Benchmarks for Philippine Startups

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Ever wondered how your team is doing versus the best Philippine startups? I always have.

Finally, we have some answers. Fortune just published revenues and profits of 46 top startups in the Philippines. I played around with the data and ended up with the benchmarks below.

I’m really pumped about these metrics. Few things motivate me more than a scoreboard, haha. I hope you find useful as well, and I hope this could be the start of open benchmarks for StartupPH.

In this post, I also share some thoughts on how we could have better benchmarks. For the nerds, I dive deeper into the data and share graphs galore.

Here are the benchmarks:

  • If self-funded, exceed PhP2M in annual revenue in the first couple of years after incorporation
  • If externally-funded, exceed PhP40M to PhP80M in annual revenue in year 3 to 4, while not burning more than PhP20M a year.
  • Grow revenue 2x (100%) to 3x (200%) YoY in the first few years
  • Consistently grow revenue 40% YoY as a mature company
  • Exceed USD1M in annual revenue in year 6–8
  • Exceed PhP100M in annual revenue in year 9–11
  • Exceed PhP1B in annual revenue in year 16–17

This is just for revenue targets. I don’t see any other useful benchmark in this data set. If we are to have better benchmarks in the future, we need two things:

  1. More data
  2. Someone with the economic incentive or alignment to mission to lead this

1. More data

“All aggregate data is BS.” In an ideal world, we would have separate data for different kinds of endeavors. In the past couple of years, I have been hanging out more with entrepreneurs beyond the Startup Weekend crowd. I have now have a better appreciation of more diverse kinds of entrepreneurship:

By founder intent

  • Minimum work for maximum life. The Philippine counterpart of 4 hour Workweek crowd.
  • Maximum growth from profit. The Philippine equivalent of the self-funded and bootstrapped MicroConf crowd.
  • Growth at all cost. The Philippine version of the Techcrunch crowd.
  • Megafunded expansionists. Well-funded companies with business models proven in other countries executing in the Philippines (eg, Zalora, Uber, Grab).
  • Classical entrepreneurs. Folks starting and running classical business models (eg, manufacturing, financing, trading, retail, professional services).

These are different crafts with different playbooks. They should not be lumped together.

By business model

Margins of services businesses are at ~20%. Business software with recurring revenue could have margins >80%. eCommerce, marketplaces, intermediation platforms, etc, have their own economics. They should not be lumped together.

For now however we don’t have a choice. I tried looking at the Forbes data by business model and the data becomes too thin to mean anything.

More kinds of data

On top of revenue, profits and growth rates, it would be nice to also get benchmarks on cost of acquiring a customer, annual contract value, customer lifetime, churn rates, lead-to-sale conversion rates, cost per lead, founder salaries, and number of employees. Plus salaries, shares, options, commissions of different roles. Some sort of Philippine version of this:

2. Someone with the economic incentive or alignment to mission to lead this

As much as I enjoy playing around with data, this is not my job. My job is to hit these benchmarks, not to make them.

Ideally, this should be led by companies who have startups as customers, or founders who have already gone through the journey from lower-left to upper-right of the chart.

Let me publicly challenge the first generation of Philippine startups and the accelerators/incubators/orgs: Jay Fajardo, The Chikka Guys, Nix Nolledo, VJ of iRipple/eMongo, Endeavor.org, Kickstart.ph, Techtalks.ph, Ideaspace, JFDI, PSIA, etc.

If one of your goals is to help the next generations of startups, there are few things more scalable than words in the the interwebs. Could you please be our local Jason M. Lemkin?

Since we are talking about benchmarks, perhaps the Philippine version of Tom Tunguz or David Skok (linked above)?

I invite you to publish or republish in StartupPh Chronicles:

Okay, that’s the end of my dreaming and pleading. Let’s get back to the data.

How these sausages were made

Let me share how the benchmarks above came about, so you can check if I made any mistakes in computation or in logic.

First, let’s plot the data with the following axes:

  • Years since incorporation
  • Revenue

Since Fortune included the revenue growth from the previous year for most of the companies, we could almost double our data set. Here’s the data:

Here’s the resulting graph:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

Let’s remove the outliers, the megafunded Lazada, Zalora, Uber and Grab, and the laid back guys at the bottom right.

Here’s how it looks like:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

If we we trace the maximum, average and median of this graph, it will give us this:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

We want to smoothen these to get the numbers in between the highs and lows. Let’s not forget though that these are the highs and low of the top startups in the country; the average still represent the top. Let’s get their trendlines using an exponential curve:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

We can get the formulas of these trendlines so that we can plot them out the numbers in a table.

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

The average and the median look pretty similar, so I’ll just use one of them.

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

Here’s the resulting table:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=1959859549

What’s the revenue benchmark for startups in their first few years? Our set only gives us 3 data point for the first year (those incorporated in 2013 and reported YoY revenue growth numbers in our 2014 data set):

  • Synapse | Cogito 2013: PhP 1.92M (the data in the magazine mistakenly had this as 19.2)
  • Galleon.ph 2013: PhP 2.02M
  • Timeframe Innovations 2013: PhP 2.52M

We have more figures from startups in their second year:

  • Kalibrr 2013: 17.28
  • Myproperty.ph 2013: 14.18
  • Tripmoba 2013: 0.57
  • Zipmatch 2013: 6
  • Lifetrack Medical Systems 2013: 0.25
  • Physics Research 2013: 2.59
  • Ava.ph 2013: 5.53
  • Perxclub 2013: 1.30
  • Synapse | Cogito 2014: 6.5
  • Engagespark 2014: 6
  • Galleon.ph 2014: 4.9
  • Timefree Innovations 2014: 3.4

Similarly, we have a substantial number of revenue figures from startups in their third year:

  • Rappler 2013: 57.48
  • Metrodeal 2013: 123.88
  • Lenddo 2013: 18.29
  • IT.Corea 2013: 2.31
  • Kalibrr 2014: 21.6
  • Myproperty.ph 2014: 13.9
  • Tripmoba 2014: 9.9
  • Zipmatch 2014: 5.7
  • Lifetrack Medical Systems 2014: 5.6
  • Physics Research 2014: 4.5
  • Ava.ph 2014: 2.6
  • Perxclub 2014: 1.3

My personal interest is to benchmark with self-funded startups by local entrepreneurs. I’ve worked with Jeff Siy of Galleon.ph (in starting The Science of Sales) and with Gian de la Rama of Cogito (since our HP days), and they are both awesome fellows. Now, I can also look at their numbers as benchmarks. Galleon.ph and Cogito were both self-funded during these years we are looking at (Kickstart invested in Cogito in 2015).

This sounds like a good benchmark for self-funded startups: Exceed PhP2M in revenue in the first couple of years after incorporation.

The more important metric though is the growth rate. Founders take extraordinary risks creating companies with a new product or a new business model. The math makes sense only with extraordinarily high growth rates. Otherwise, it makes better financial sense to do a classical business. But then again, I have yet to meet a startup founder whose primary motive is a secure way to make money.

Revenues for Galleon.ph grew more than 2x (143%) and for Cogito more than 3x (239%) from 2013 to 2014. Gian told me that Cogito grew 2x from 2014 to 2015. If this is achievable for self-funded startups, it should be more so for externally-funded startups.

First-time founders should take note that Galleon.ph is not the first startup of Jeff. Nor is Cogito the first of Gian. A top startup that Forbes missed is Loansolutions.ph. They made USD 100k (PhP4M+) in revenue in their first 12 months or so. The founder, JP Bisson, and his team, also built several products before Loansolutions. I wrote about Galleon.ph, Cogito, Loansolutions and other startups here:

The numbers we have for externally funded startups are in year 2 to year 4. We’re actually looking at the top-performing startups that got started during the first rumblings (circa 2011) of the current global wave of startup entrepreneurship.

What should your benchmarks be if you receive external funding? Let’s look at their charts. Since externally funded startups can afford to be in the red for years in pursuit of growth, let’s also look at their profits. This is our excuse to create some bubble charts.

Here’s our entire data set. I divided into 3 generations plus the megafunded expansionists.

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=797741995

Let’s zoom in each generation.

Gen 1
Gen 2
Gen 3
Megafunded

Let’s isolate the funded in Gen 3. I include here the companies in the list that have received funding from professional investors in my knowledge, and those that are owned by large companies (eg, Myproperty and Metrodeal).

The only thing this graph says is that externally funded startups tend to grow fast and burn a lot of cash. Which we already know. Let’s put them in a table.

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=1916983537

Let’s graph the max, min, ave and median values.

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=1916983537
https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=1916983537

If I raise funding early on, I’d give myself this benchmark based on these graphs: Exceed PhP40M to PhP80M in annual revenue in year 3 to 4, while not burning more than PhP20M a year.

But these rockets don’t carry the same volume of rocket fuel. It would be interesting to see the relationship between amounts raised, annual revenue and the years since raising the amount. Among startups in this list, only Zipmatch, Kalibrr and Lenddo have shared their numbers in Crunchbase. Lenddo is not headquartered in the Philippines, so the revenues published by Forbes is only a fraction of the total revenues of the company.

Once again, we have to base our benchmark only on a couple of companies. If we put the numbers of Zipmatch and Kalibrr in a table we get this:

If we put the three right-most columns in a chart, we get this:

R = annual revenue

This tells me that if I raise seed capital, my annual revenue should be between 20% to 60% of the raised amount within a couple of years. At least to be as good as Zipmatch or Kalibrr.

Let’s compare that to a global standard. One global accelerator told me that they have a cutoff of $10k MRR for early revenue startups. They said they normally invest around $100k. That means annual revenue is at 120% of seed at the time of investment.

I’d love to create this chart again once we have a more substantial volume of data.

Another interesting angle would be FTE efficiency. Divide the annual revenue with the headcount. That would give an indication of the amount of value created (output) with the amount of talent in the company (input). We simply don’t have the figures to look at this now.

Data science folks joke that “if you torture data long enough, it will confess to anything.” This exercise shows that there is a point where the data just dies from torture.

Growth rate

According to Paul Graham, what makes a startup a startup is growth rate. So let’s take a look at the growth rates of the top Philippine startups. Collectively, here’s how it looks like:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459 (scroll down)

Let’s remove the outliers, so that we could see the rest clearly (outliers = those who grew > 500% YoY).

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

Here’s how it looks like with trendlines:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

Looking closer:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=348306459

Another way to look at this is to use our expected revenue per year table above and add the growth rate:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=1959859549

Here’s how that looks like charted out:

https://docs.google.com/spreadsheets/d/1sOBdjKxyHSKmjaD3tXec7d-UUszNheR9ZrCpTPP6khc/edit#gid=1959859549

It should help to look at US companies. Although their revenues should be higher (perhaps proportional to market size?), I imagine growth rates to be similar for top companies in any environment.

Here’s a graph from Tom Tunguz for US SaaS startups that eventually IPO’d:

http://tomtunguz.com/growth-rates-of-public-saas-companies/

Here’s a similar graph from TechCrunch:

https://techcrunch.com/2013/08/24/how-fast-should-you-be-growing/

They essentially say the same thing. Grow 2x-3x when you’re young/small. Grow ~40% YoY when you are mature/big.

To recap

  • If self-funded, exceed PhP2M in annual revenue in the first couple of years after incorporation
  • If externally-funded, exceed PhP40M to PhP80M in annual revenue in year 3 to 4, while not burning more than PhP20M a year.
  • Grow revenue 2x (100%) to 3x (200%) YoY in the first few years
  • Consistently grow revenue 40% YoY as a mature company
  • Exceed USD1M in annual revenue in year 6–8
  • Exceed PhP100M in annual revenue in year 9–11
  • Exceed PhP1B in annual revenue in year 16–17

You only need one benchmark

When I do laps, I notice I swim faster and push myself harder when there are swimmers in the other lanes.

I think this is the main benefit of having open benchmarks. Each startup journey is different, but looking at the metrics of our peers might be a good psychological hack to help us push harder and aim higher.

Along with this data from top Philippine startups, the same issue of Forbes gives us some numbers from the current poster boy of Philippine tech startups, Xurpas:

  • Capital: 62,500 in 2001 Pesos
  • 2003 (year 2) revenue: PhP10.3 million
  • 2005 (year 4) revenue: PhP104.15 million
  • 2013 (year 12) revenue: PhP251.8 million

Here’s the chart of their annual revenue and profit. Any startup founder in the Philippines would appreciate this masterpiece.

You have no choice but to give your all when an Olympic-level athlete is in the next lane.

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