Like what I’m writing? Reach out to me here if you want to grab coffee.

If you want to know the only VC worth caring about, my last article is right here:

In the last article, I shared a set of drivers that could be ‘pulled’ to create startup value. By being deliberate and pulling these drivers, founders can take a measured approach to value creation and allocate capital within their company to the initiatives that will drive the most value.

Here’s an easy lever you can pull as a founder: cut your customers.

Every one of your company’s customers will fall into a spectrum across these dimensions:

1. Customer Value: The amount of ARR this customer contributes to your overall ARR. Low ARR customers will have minimal or negligible impact on your overall ARR if they churn. Customers who fall within low ARR are candidates for cutting. High ARR customers are the ones you want to keep. Churning these logos is detrimental to your company and could hurt your ability to raise in future.

2. Expansion Opportunity: Is there an opportunity to expand within this logo? Some customers are 'land and expand’ opportunities, selling limited licenses, seats or products with the hopes of expanding ARR. Customers with low ARR and limited expansion opportunities are the prime candidates for customer cutting. Ways to identify Expansion Opportunities include assessing possible licenses / seats and comparing to contract terms and assessing products bought against your product suite.

3. Customer Success Effort: How much effort and resources does this customer take up? How much more effort will it take to execute on the expansion opportunity and keep them happy? High-effort customers with low ARR and limited expansion opportunities are an enormous opportunity cost for your company. Ways to identify Customer Success Effort includes training and implementation sessions, product adoption and usage and customer touch points.

Across these dimensions, we get four broad customer archetypes.

• White Whales - These are your dream customers. They are high-value customers with multiple power-users and internal champions who are driving usage and adoption. Ideally, you should be deeply embedded with these customers to understand other pain points and drive expansion and upsell.

• Cast Members - These are customers you can ignore. They are typically low-value and low-effort customers with limited expansion opportunities. They might have one power-user with limited adoption in their organisation. You can ignore these customers because they don’t require attention or training.

• Problem Students - These customers are deeply experiencing the pain you’re solving but are struggling to drive product usage and adoption. Instead of trying to drive upsell or expansion, you should be focused on educating and training these customers to get maximum value from the product. From there, you may be able to transition them into White Whales or Cast Members depending on their contract value.

• Teeth Pullers - These are the customers you want to cut. Teeth Pullers are low-value customers who are distracting your company and team. They take up resources which prevents you from servicing and focusing on high-value customers. Cut these customers or let them churn by reducing the service time and attention you give them.

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Case Study: Profitable Growth for B2B SaaS

Some time ago I helped a SaaS company think about profitability.

They had raised >$15m from VCs in their last round but had limited financial discipline as they scaled quickly. Their last raise was at a punchy >20x ARR which meant they had to find ways to grow profitably into their valuation (because of multiples compression, they were advised it would be difficult to raise another up round without significant growth).

The chart above shows the spread of their customers by ACV (customer value), the expansion opportunity and the effort they give each customer. I asked the Customer Success team to score each customer from 0 to 100 for each of these two dimensions.

From there, we found that one of their key problems was the quality of their customers. Given the focus on growth during 2020-2022, the company had signed many small customers to grow ARR and several large customers who had limited maturity.

A significant portion of their customers (and ARR) were Teeth Pullers or Problem Students which meant that their Customer Success team was a significant portion of their Employee Costs as they were responding to these customer requests or putting out fires.

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Using the Effort Scores for each customer, we mapped where the CS team spent their time and resources and found that Teeth Pullers and Problem Students took up 85% of the team’s resources, despite only being 56% of ARR. Shockingly, they spent 60% of their time managing 9% of ARR (Teeth Pullers).

Inversely, the CS team spent 5% of their efforts with White Whale customers, which meant they had limited opportunities to nurture expansion opportunities with the Sales team.

Cutting low-value customers enables companies to redirect resources towards White Whales and Problem Students - the customers with expansion opportunities. Ideally, this unlocks profitable growth as each interaction and touchpoint with these customers is building towards a return on investment through expansion opportunities.

Previously, each interaction with a Teeth Puller customer would only lead to a return on their ACV (i.e. preventing the logo from churning). However, focusing only on White Whales and Problem Students meant that each interaction with a customer could lead to expansion revenue (or at the very least, retention of the higher value existing revenue). Every dollar spent on Customer Success had a greater return than previously when the company was focused on Teeth Pullers.

This has other downstream implications for the company. You can refocus the Product roadmap on White Whales to create further expansion opportunities, you can tailor marketing and education efforts to Problem Students so that you can avoid Teeth Pullers in the future and you can realign incentives for the Sales and CS team to ensure they’re focused on the right customer segment.

Stopping the Problem Before it Starts

The last thing founders want is the same problem creeping again down the road, especially at Series C or later when the problem is generating significant opportunity cost.

This is where aligning this effort with Sales is necessary so that the company has sales pipeline discipline.

We screened the Opportunities in their CRM against two dimensions:

1. Pipeline Days - How long has this Opportunity been in the pipeline?

2. Customer Value - How much is this Opportunity worth?

By assessing these Opportunities, founders can identify indicative Teeth Pullers before they are signed as customers. These are low-value customers who had incredibly long sales cycles. By cutting these customers from the pipeline and incentivising the Sales team to refocus on potential White Whales (high ACV customers), you can start to build a GTM machine that acquires, retains and expands profitably.

I want to emphasise that this isn’t a blind exercise. Founders should do this only:

• When it makes sense for their company.

• In conjunction with Sales, Finance and CS.

• And with input from their investors.

There’s a cadence and nuance to a decision to trim customers or let them churn and it shouldn’t be done without alignment across your company.

Creating Long Term Customer Value

The goal of any startup should be to create long-term customer value. Jeff Bezos has a famous quote from an interview in 1999:

“In the long term, there is never any misalignment between customer interests and shareholder interests.”

The key nuance missing from this quote is choosing the right ‘customer’. If you want to grow long-term value, in a capital-constrained environment, you can’t do that by focusing and servicing all your customers.

By purposely curating and ‘cutting’ customers and refocusing on customers who have opportunities for long-term value creation, you can build a better company that maximises value to shareholders.

Did you like this article? It’s a different flavour to other things I’ve written. Let me know here.

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Pop Culture, Life, Reading and More

• On a four-hour train to Canberra last week, I binged both episodes of First Cheque by Cheryl Mack and Maxine Minter. Highly recommend and honestly way better than some of the other VC podcasts out there that talk about the same shit.

• My girlfriend and I just watched Past Lives (A24). Great film and honestly A24 can’t miss.

• Median SaaS multiples have now dropped to 5x. If you’re raising your Seed round, you better have a plan for value creation to get to Series A. If you want to chat, feel free to reach out.

Oop. It’s been a while!

Lots of things have happened in the past few months that have kept me from writing, reach out if you want to catch up and learn where my life is right now.

As a reminder, Rare Candy is a newsletter that aims to bring insightful and novel insights to help founders, investors and operators.

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Value Creation Through Growth or Profitability

This year, we’ve seen the pendulum swing from growth towards profitability for startups and technology companies. Startup value has shifted towards profitable growth as the bounty for topline growth disappears.

Guidance for ‘good’ profitable growth is often set using The Rule of 40. As a guardrail, the combination of your year-on-year growth rate and your profit margin should equal 40% or greater.

I like to think about this as ARR growth rather than GAAP Revenue growth to isolate the recurring portion of a company’s revenue. On the profit margin side, some people think about it as Operating Margin or EBITDA margin but FCF Margin is a better indicator given it more accurately represents a company’s ability to re-invest for growth.

Companies generally achieve this in one of three ways:

• Superior growth rates but with lower FCF margins (rocketships).

• Lower growth rates but with higher FCF margins (cash cows).

• Balancing both and reinvesting for ‘profitable growth’ (dragons).

And companies who score above the benchmark are handsomely rewarded. Currently, the median revenue multiple for public SaaS companies is 6.4x LTM. However, companies above 40% on the Rule of 40 are valued at 10.2x and companies below 40% are valued at 4.6x.

If you’re a public SaaS company, You can effectively double your valuation if you’re above 40% on the Rule of 40. Looks like multiples expansion is back on the table!

Achieving the Rule of 40

Let’s walk through the three ways you can achieve the Rule of 40.

1. Value Creation Through Growth

Growing 100% YoY is the benchmark for any sub-scale startup. This often involves front-loading costs and burning cash until sizeable scale, after which your company grows into its cost structure and begins to hit profitability. I’m sure if you charted YoY revenue growth and profitability for Salesforce or Microsoft, that trend would be quite apparent.

GitLab and Samsara are two companies that are creating shareholder value through strong growth and have yet to switch gears towards long-term profitability. While public companies, neither are even a decade long (2014 for GitLab and 2015 Samsara) and both are new entrants to the public markets (IPO in 2021).

Many startups will achieve the Rule of 40 through growth alone and if you’re venture-backed, you’ll likely be in this camp. However, GitLab and Samara ‘grew up’ in a completely different operating and macro environment where capital was cheap and freely available.

As a founder, to approach value creation through growth alone, especially unprofitable growth is neither sustainable nor advised in this climate.

For GitLab, they achieved their incredible growth in several ways. From their CFO, Brian Robins:

"In April of this year, we raised the price of our Premium SKU for the first time in 5 years.”

“At the end of the second quarter of FY24, we had 810 customers with ARR of at least $100,000, compared to 760 customers in Q1 of FY24.”

“Additionally, in Q2 we started enforcing user limits on our free SaaS tier. It’s early but we have seen additional free users upgrade to Premium.”

Firstly, they pulled the pricing lever to deliver an immediate increase in pricing. While price-sensitive customers may churn, the net effect has delivered (at least in the short term), positive value creation for GitLab. With a product like GitLab and its strong retention (124% net dollar retention), it makes obvious sense to pull this lever with limited risk and downside. Their CFO even states that customer behaviour was in line with their internal expectations.

Pulling the pricing lever is one founders rarely pull. Pricing for startups is rarely a science and can be opaque, with very few founders revising pricing as often as they should.

Secondly, they pulled the volume lever and drove strong customer acquisition. In 12 months, GitLab acquired 1,931 new customers (33% YoY increase). Although the majority of these customers are relatively low ACV (95% of customers pay >$5,000 ARR). I speculate that the majority of these customers are wildly unprofitable (GitLab spent >$300m in Sales & Marketing over the same period) but GitLab has shown it can expand further and further into these accounts.

Lastly, shifted a proportion of their free customers to paid customers. For both product-led and sales-led companies, this is one of the biggest levers you can pull to create value; particularly long-term value.

How many founders have diligently looked over their contract terms and enforced them with customers? Particularly on usage terms.

Lastly, as GitLab look towards FY25 and beyond, they’re looking to create value in another way - product expansion.

“The third drivers (sic: of revenue) is the launch of Dedicated. This allows us to address a new opportunity for companies with complex security and compliance 8 requirements. Finally, we plan to monetize our AI capabilities by launching an add-on that will include Code Suggestions functionality later this year.”

GitLab are moving through the traditional motions of value creation; charge your customers more for your product, acquire more customers and sell more things to your customers. This isn’t rocket science but paints a picture of how GitLab is managing to sustain its incredible growth, even at $500m ARR.

2. Value Creation Through Cash

Once a company has achieved over $500m in ARR, it’s pretty difficult to sustain 50% or more YoY growth. The sheer magnitude of that dollar value is incredibly difficult to acquire, which is why mature technology companies (i.e. Adobe, Salesforce, Microsoft) aren’t able to grow at the same pace as their less mature counterparts in public markets (and even private markets).

Thus, these companies are reliant on capturing profit and creating value for shareholders through the maximisation of profitability (of course, eventually profit pools are arbitraged away, so these companies still have to invest in some growth!).

For early-stage startups, creating long-term value through profitability and trading off growth isn’t a playbook often executed but one that is becoming in vogue as capital pools dry up.

Adobe’s CFO, Dan Durn discusses the key to maintaining profitability is the combination of prioritisation and execution (note that while Adobe grew 10% YoY, it’s the slowest growing company of any public SaaS company that is achieving the Rule of 40).

“Growth and profitability is not new for us, we have been delivering both for a very long time and it is at the core of our operating philosophy. It all starts with prioritization, innovation and a sharp focus on execution.

“We really have a fundamental operating philosophy that's been alive at the company for a long time… We're going to prioritize, we're going to innovate, and we're going to execute with rigor, and you see that coming through in all of the financial results of the company.”

This prioritisation and execution excellence shines through for Adobe. Their focus shifted towards Firefly, their generative AI product, which enabled them to reduce their marketing efforts given they were focused on one product. They cut back on non-core expenses including consultants and held tight on salary increases. Their ability to control their cost structure and align it to their operating priorities enabled Adobe to generate value with the performance of their bottom line.

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3. Value Creation Through Growth and Cash

Snowflake is one of those extraordinary companies in the public markets that is growing incredibly quickly and generating enormous cash. Between FY22-FY23 they grew 69% YoY to over $2 billion in revenue, adding over $800m in revenue in 12 months. Over this period, they expanded their Gross Margins, reduced their operating leverage and improved their FCF Margin.

Cheekily, they do load up their Stock-Based Compensation which does impact their financial metrics but putting that aside for now, we can dissect some of the other value-creation initiatives that Snowflake have pursued to sustain both incredible growth and operational excellence.

On balancing growth and profitability, Snowflake are highly focused on driving efficiency across their GTM as a lever for revenue. In Q4 2023, their CFO, Michael Scarpelli noted:

“We'll not grow our revenue faster unless we see productivity increase in the sales organization. And when we see that increase in productivity, we'll add more heads there”

In Q1, 2024, Michael followed this up and reiterated the need to focus the Sales organisation in order to drive results:

“Productivity is not where we want it to be … we are still not satisfied with our results. We will only invest in areas that yield returns. For that reason, we will prioritize existing sales resources to drive growth before we onboard new capacity.”

In their most recent earnings call (Q2 2024), Michael was once again asked about Sales - this time being asked to grade the Snowflake’s go-to-market sales execution in the quarter:

“Our execution in Q2 on the sales side was actually quite good, it improved. But there is still pockets, though, where there is room for improvement when you look in certain territories or geos.”

For many founders and management teams, there is a temptation to spend and over-invest when companies are highly capitalised, but Snowflake has deliberately been methodical and investing only to generate profitable growth. Even when asked by Equity Analysts covering Snowflake:

“How can you be sure you're striking the right balance of investment, especially when you're up against such well-capitalized competitors?”

Michael goes on to reiterate again the need to be measured in their investment:

“Given the opportunity, we are investing as fast as we think we need to invest.”

I'm not getting requests that people need more headcount in the engineering organization, sales and marketing. Until we see an increase in productivity, we're going to be very methodical about how we add resources into those areas. So, we're definitely not underinvesting in the business.

Snowflake are pulling a key lever that requires limited investment to drive growth: productivity. By focusing on productivity, particularly in GTM, Snowflake have been able to drive growth while simultaneously growing (albeit measured as per their CFO’s statements.

Over the 12-month period between Q2 FY23 and Q2 FY24, Snowflake grew revenue per employee by more than $1,600. While this is only a small increase, it can lead to significant growth over a long period of time if you instil this type of operating discipline within your organisation.

This discipline isn’t something unique to Snowflake. In fact, their CEO and CFO brought over this discipline from ServiceNow. They both took ServiceNow public and transformed it into one of the leading SaaS companies in the world (>$8bn LTM revenue, 50% Ro40).

They are executing on a tried and tested playbook for value creation.

All these companies are executing a value-creation playbook that their management team has created or stolen from other companies. They apply these tactics and calibrate their playbook according to the nuances of their company and the changes in their operating environment.

Introducing the Startup Value Creation Drivers

I’ve collated over 120 drivers that founders and operators can use to create value and drive growth and profitability within their startups.

I’m sharing this so that founders can be deliberate and tactical when it comes to creating value and instead, isn’t reliant on multiples expansion, growth through headcount and cutting burn by shedding employees.

I’m aware that many founders are doing many of these things already. Some deliberately but more often than not, most founders are being reactive and allocating capital without first being purposeful and measured.

If you’re a first-time founder, you might stumble upon one of these drivers through experimentation or hypothesis-led thinking. If you’re lucky, you might have a great investor in your pocket who can help you by ‘adding value’ and guiding you to one of the methods. You might have a network of senior operators and other founders who have created their own playbooks and sharing their knowledge about drivers to pull.

But with this, founders can take these drivers and adapt them to the intricacies of their operating environment, much like GitLab, Adobe and Snowflake have in the public markets.

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Canva is an incredible business. I’ve taken their mission statement and highlighted how you can use these playbooks as a way to execute your company’s mission. For example, Canva’s mission is to empower everyone in the world to design anything and publish anywhere. As part of that, they need to make their product cheap or free to use, otherwise ‘everyone’ will never be achieved. This means one of the levers they need to pull is to convert free users to paid users. Strategically, Canva can make choices and trade-offs as they pull this lever by asking questions like:

• What is the right price?

• Why do people pay?

• Which features do we gate vs which features are free?

• How do we incentivise users to upgrade?

• Is this applied consistently in every market and segment?

• How do we incentivise our team to drive growth in paid users?

• What is the timeframe for this? How quickly should a user upgrade?

By proactively pulling levers, founders and operators can allocate capital, plan initiatives and priorities, set KPIs and experiment across their business instead of being reactive to growth or changes in their environment.

Conclusion

I’ve let this newsletter lie dormant for a while as I’ve spent a long time this year thinking about startups and venture. I’m charting my own course on what startup value creation looks like and I’ll be using this newsletter to keep writing, sharing, interviewing founders, investors and operators and analysing startup value creation.

Want access to the high-resolution version of the Startup Value Creation Drivers? You can find it here.

Better get sharing because I’m back.

Reach out to me here if you want to grab coffee.

Pop Culture, Life, Reading and More

• This set from Flight Facilities in 2010 is the perfect due diligence playlist.

• The best pasta I’ve had recently is at Acqua E Farina in Potts Point, get the ragu.

• I bought sheets from Bed Threads recently and they are worth every dollar.

Welcome to Rare Candy #3

Happy New Year and welcome back to another edition of Rare Candy.

Apologies for not releasing a newsletter in December 2022. Unfortunately I had a family member pass away early December and had to fly overseas for a few weeks. I had promised a bottle (or two!) of champagne for the 'team' who had the most subscribers, but it made sense at the time given it was the festive season. I might hold off on that until Easter or when it makes sense to celebrate (I know it's a cop out).

If you’re new here, Rare Candy is a newsletter that aims to provide deep and insightful analysis on venture capital. You’ll want to read my first piece here and my second piece before this one.

If you’re interested in collaborating, please reach out to me here. I’d love to share some ideas and see how we can work together.

Summary

• Smaller venture funds (<$100m) are likely to return their fund with a median-size SaaS exit.

• To return larger funds, patient capital is required, and funds should consider long-term valuation creation post-IPO.

• Cross-over funds (private and public market funds) are becoming common and may be a potential model for 'patient capital' in the future.

I love investing. I’m addicted. I love ‘levelling up’ and learning about interesting asset classes like vinyls, whiskey, Pokemon cards and more. That's why I've been reading Alts. Stefan and Wyatt write deep analysis on alternative assets and you get to reap the rewards.

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Introduction

I read this article over the summer break (a riveting way to spend my holidays, I know). It makes a bold assertion that a venture fund should be no larger than 1-1.5x the average exit value in a domain or sector. This was from 2011, and I wanted to understand:

• How large do exits need to be if fund size keeps increasing?

• Do those exits exist?

Returning a Venture Fund

The threshold for a ‘good’ fund is to return 2-3x cash-on-cash or more. Top performing funds can return substantially more. For example, Union Square Ventures has generated returns ranging from 3.9x cash-on-cash to 7.3x cash-on-cash.

Working backwards from 3x cash-on-cash as a baseline, you can solve for the exit value of one company that would achieve this return, assuming an ownership stake and a fund size:

We know that returns are power law distributed. Therefore if you assume that only one company is successful at returning capital then:

• For a small fund to return 3x, it would need an exit valuation between $1.5b - $37bn. I've assumed that their ownership stake is between 1-5% (shows you how sensitive fund returns are to ownership). This is relatively small, but smaller funds don't have the capital to continuously exercise pro-rata (or lead future rounds in their successful portfolio companies), which means they are likely to be diluted down to lower ownership stakes.

  • Additionally, it could be argued that in a competitive venture ecosystem, smaller funds may be 'competed out’ of leading rounds and can only take smaller ownership stakes to fill remaining allocation.

• On the other hand, for a large fund to return 3x, it would need an exit valuation between $15 billion and $60 billion. I've assumed that a larger fund can continuously exercise pro-rata and lead future rounds in their portfolio companies, meaning it's likely they'll hold 10-20% of a company.

It's important to note that portfolio companies aren't ‘return or nothing’. There are mid-range exits, secondaries, and downside protection through preference stacks, etc. which means funds do have a spread of exits rather than 'all or nothing.'

Even if you assume a 2x return (cash-on-cash) because the other 1x is covered through other means, larger funds are still looking for outcomes of over $10b.

By working backwards, we have determined the scale of exit required to return a venture fund.

However, do exits of that scale exist?

Drinking a coffee? Would love one!

The Power Law Within the Power Law

Large funds require at least a $10b valuation at exit (~$14bn AUD).

• However, there are currently over 1,200 unicorns, and only 54 (~5%) of these are valued at over $10 billion USD (and 97 at $10bn AUD). Furthermore, only one of these companies is Australian (Canva). This means the probability of a large portfolio company is very low, these are the outliers of outliers.

For smaller funds, they need to be at least unicorn status at exit, depending on their ownership.

• The median unicorn valuation right now is $1.6b USD (realistically lower because the data is from October ‘22 but let’s roll with this as this is readily available data). That’s $2.2b AUD.

• On this valuation, this would return 2x of a fund less than $50m, assuming they owned ~4-5% of the company (very probable to own this stake if you led one of their first rounds of financing).

This is pretty interesting to think about!

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Unicorn companies are already in the top 1% of their class and even for small venture fund, you would need a median company within that top 1% cohort to return 2x of the fund. No wonder many venture funds don’t succeed!

I want to illustrate an example of how this plays out. Assume that private market and public valuation multiples are at parity at later stages. If you had a $100m venture fund, in order to return 3x cash-on-cash, you would need:

• Between three to five exits of a company valued at $2-3b (assuming lower levels of ownership). HARD. Remember, the median unicorn valuation right now is $2.2b AUD and now you need at least three of these. Go look at the portfolio of any venture fund and tell me how many have three unicorns or more within a specific fund.

• One or two exits of a company valued at $5b. In Australia, only Canva has hit this milestone. And don’t forget you have to compete against the Blackbirds, the AirTrees and the Square Pegs of the world, as well as the highly differentiated funds like AfterWork and EVP to win deals or get allocation. DOUBLE HARD.

• One exit for a company valued at $10b or more depending on ownership. Venture is already an asset class of outliers and now you’re looking for the most extreme of outliers. Remember, right now there are only 54 companies with a valuation of $10b USD or more, putting them in the top 5% of all unicorns. TRIPLE HARD!

I’m using unicorn valuations as a proxy for exit valuations, given that multiples should regress to public market multiples when they approach this size and scale. At the moment, very few private companies could return even 2x of a $1b fund, let alone the $5b growth fund that a16z raised in 2022 (part of a cohort of funds totalling $9b).

IPOs and M&A

Portfolio exits occur at all sorts of valuations and they often differ from their last private market valuation.

• IPOs would need to be at a higher valuation than their last private market financing in order to return capital to investors at that stage. For example, Uber’s last financing round was at a valuation of $76b and it went public at a valuation of $82b.

• Corporate development teams are likely to overpay for large acquisitions as a defensive mechanism to maintain incumbency. Figma was valued by Adobe at $20b at the time of the acquisition offer - twice the valuation of the company at its last financing round.

Knowing there’s variability between last funding round valuations and exit valuations, we can look at recent data to tell us what these valuations look like at IPO (acquisitions are harder to look at because there are fewer large scale benchmarks!).

If you zoom in on this beautiful bar chart, you’ll see that enterprise SaaS has a median IPO valuation of $2.8b (~$4b AUD). At this valuation, you could return 3x your $100m fund if you can own around 7.5% of a company that made it to this size and scale. This seems pretty reasonable assuming you start at around 20% ownership when you first invest. However, this is US centric data.

The Australian perspective is harder to infer given the limited data available and immaturity of technology listing on the ASX but as a single data point, Siteminder went public in late 2021 at a market cap of $1.36b.

To summarise, if you want to return a small-ish VC fund of $100m, you’d just need a median US-enterprise SaaS exit or three Siteminder-level Australian IPOs.

As fund size increases, funds can’t settle for a median sized enterprise SaaS exit, which means they can’t just be investing in SaaS.

If you have a $500m-$1b fund, it would be nearly impossible to return a 3x the fund on SaaS exits alone.

If the median SaaS IPO was valued at $4b AUD (~$2.8b USD), you’d need three or four to return 3x the fund (assuming 10-20% ownership). There’s not four startups of that scale in Australia at the moment!

One of the largest cloud/software IPOs was Snowflake (~$34b) and even Snowflake pales in comparison to some of these consumer companies like Meta and Uber.

Given the scarcity of these exits, investors may have to become post IPO owners of companies if they’re managing larger amounts of capital.

Long Term Capital and Public Markets

There are 580+ US listed companies that currently have a market cap of >$10b. This number would be much larger if you include other regions. Some of these were once venture backed companies. That’s 10x the amount of private market companies valued at the same level.

Some of these companies have created this value long after they went public. The ‘legacy’ examples of this are Microsoft, Apple and Alphabet but you can look at more recent examples including Atlassian, Salesforce, Uber and Airbnb.

Throughout this edition, I’ve assumed that funds divest at IPO. This is a false assumption. Some funds continue to hold their ownership in companies long after their IPO.

Some funds already do consider themselves as ‘long term capital’, rather than venture capital.

If you’re looking for founders who can create long term and sustainable value and truly believe in those founders to do this, it doesn’t make sense to divest at IPO (or maybe just a little so you can return capital and raise another fund).

• They’ve already built and shown they can create value and build an enduring company;

• There’s greater availability of capital in public markets. Companies can utilise this capital and invest in greater volumes to continuously innovate, build new products, acquire adjacent players and expand across value chains;

• At times, the discipline and rigour of public markets and public market participants can act as a forcing function to ensure long term value creation (Elon Musk, activist investors etc).

In 2015, Altimeter Capital led Snowflake’s Series C at $2.29 per share and continued to invest in every round after. Unlike many of the earlier investors in Snowflake, Altimeter still remains of one of the largest investors in the company and the Partner who led the deal within Altimeter, Brad Gerstner believes Snowflake will continue to create long-term value.

Imagine if you had sold at IPO (which was priced at $120) only to see multiple expansion driving the share price to $390+. That is more than a 3x return, which would put your fund in top 5% of venture funds. I’ve outlined above at the difficulty in returning 3x in the asset class, but here’s one in the public markets! But imagine if you were Sutter Hill, they invested in Snowflake’s Seed and Series A. That’s an incredible return if they held past IPO.

Of course, this situation was a unique outlier given the extreme multiple expansion that occurred in the public markets between 2020 and 2021. You can look at the share price history and the evolution of companies like Adobe, Alphabet, Microsoft and Amazon as comparable companies who have existed for decades. These companies have shown the ability to create value and reinvent themselves in public markets.

The power law isn’t unique to venture and does manifest in public markets and this is where the outliers of outliers emerge. And larger funds like Altimeter and Tiger know this, which is why they’ve structured themselves as cross-over funds.

In time, I think we’ll see more cross-over funds emerge as patient capital and play earlier, which will paint a gloss over their ‘hedge fund’ status. These funds have ‘proper villains’ who have strong finance and investment backgrounds which, when applied correctly, can translate to early stage diligence.

In my first job, I spent months crawling through S1s and 10Ks to benchmark SaaS company margins and OPEX for a project I was working on as a consultant. It would be a lie to say looking at annual reports of mature technology companies isn’t useful to my job right now working with early stage startups.

There is definitely a challenge for venture funds who become cross-over funds in building this capability internally!

Concluding Thoughts and What’s Next

I concede that the immaturity of the technology ecosystem in Australia plays a role in this as well. Do I believe in the next 10 years that we’d see more unicorns and greater value creation or do I believe that it will remain at these volumes (or lower)? Absolutely, I believe that there’s more value to be created and that we'll see many more Australia companies reach >$10bn and more.

I want to meet some LPs and learn how they think about venture allocation. There’s lots of VC / startup hang outs, but where do LPs hang out?

I’m going to do some cold outreach, but if you’re an LP in a venture fund, please reach out. I promise I won’t ask for your money. I’d love to write an article about venture allocation from the perspective of LPs.

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Pop Culture, Life, Reading and More

• I won my Fantasy Football (NFL) league, Superbowl is coming up and would love to organise a watch party if anyone is interested!

• The day this drops, ‘The Last of Us’ by HBO will have been released. Worth a watch, even if you’ve never played the game (the game is unreal!).

• I’ve started reading ‘The World in a Grain: The Story of Sand and How it Transformed Civilisation’ after a friend recommended it. It’s excellent so far!

• Mark, a mentor of mine and fellow VC has started a newsletter. He’s a genius so I would recommend it.

• We’ve (Astral Ventures) built a VC leaderboard that lets AU/NZ founder rank their VCs. Would love for you to share it!

  VC Leaderboard

Welcome to Rare Candy #2

I’m humbled and grateful for the support I’ve received for Rare Candy since launching last month. If you’re new here, Rare Candy is a newsletter that aims to provide deep and insightful analysis on venture capital.

Thank you to the 300+ subscribers who have joined me on this journey. The majority of which are investors from VC and startups. I know you’re a competitive bunch, so each edition I’m going to post a ‘podium’ of my top VC or startup supporters.

Here’s the current leader board:

To be completely transparent, this is how I’m assessing the podium.

I’ll send two bottles of champagne to the fund or company who makes it to the #1 spot next month. If AirTree takes the top spot, I’ll even send it via Milkrun.

If you’re interested in collaborating, please reach out to me here. I’d love to share some ideas and see how we can work together.

Shout Me a Coffee

Summary

Key Insights

Just here for the takeaway? Here is what you need to know:

1. Portfolio strategy and construction differs between funds - all these funds are playing the Power Law game but some play it very differently.

2. If you can’t source, assess and win the absolute best founders maybe ‘spray and pray’ is the right decision - If you can’t pick the right players to score a goal, getting as many players on the field as possible may also be a winning strategy.

   ---

   

   I love investing. I’m addicted. I love ‘leveling up’ and learning about interesting asset classes like vinyls, whiskey, Pokemon cards and more.

   That's why I've been reading Alts. Stefan and Wyatt write deep analysis on alternative assets and you get to reap the rewards.

   Join 50,000 others and see what you’ve been missing.

   Subscribe to Alts for free.

   ---

   Subscribe now

Primer on the Power Law

The startup ecosystem thrives beacuse of a rule called The Power Law which defines the return profile of early stage VC investments. Simply put, given a incredible large enough cohort of startups, only a handful of of those will product expotential returns. Returns which are greater than the returns of all other companies combined.

This is nicely summarised by Peter Thiel in his book Zero to One:

‘… the biggest secret in venture capital is that the best investment in a successful fund equals or outperforms the entire rest of the fund combined.

If you believe this statement, this means success can be determined on whether a startup can return a fund, or multiples of a fund.

And if you’re a VC and you’ve found a company that has the potential to do that, they want to optimise ownership in that company in order to maximise their return (in reality there’s other factors including portfolio concentration and so forth but let’s keep it simple).

This makes VC sound really easy when you reduce it to this process:

Unfortunately, we know (from the Power Law) that only a few companies can generate outsized returns. We also know that ownership of these companies is a zero-sum game (the more ownership you own, the less anyone else owns). This means VCs need to find and invest in the best founders and companies and these companies need to create enough value such that the VC’s stake in the company is worth the original value of the fund, or more.

VC Decision Making and Shot Selection

This is where we all get to nerd out.

Warning: this will get a tiny bit technical. Here’s a quick primer to help frame the technical aspects that follow below.

• The purpose of venture capital is to score a goal (a return).

• Imagine if every player had a ball, then there are two ways to do this:

  1. You get as many players onto your team as possible. The more players and balls on the field, the more goal attempts.

  2. You pick only the best players for the team. This means you have a smaller team but better players might maximise the probability of a goal.

• Technically, you could do both (i.e. aggregate all the best players) but this is hard to do given some players might choose to go to other teams (other funds).

Now for the technical part.

Venture capital could be described an extensive-form game depicted as a game tree. For those unfamiliar with extensive form games, it’s a sequential game that where the players makes a set of probability based decisions (with complete or incomplete information), with an inevitable pay-off at the end.

Put simply:

• Each turn, a player (VC fund) will make a decision to invest in a company on the basis of complete or incomplete information (diligence)

• At the end of the turn, the company will be successful or unsuccessful (determined by probability)

• And then the players can choose to invest again (follow on investment)

• This repeats until there’s a payoff (liquidity event)

We’re able to depict this here using a variation of a game tree that I’ve adapted from Ewens et al. (2017):

This game tree outlines the return ($V) for an investor on a two-stage investment process. The aim of venture capital is to maximise $V.

• At the first step, investors have to source deals and make a decision whether to invest or not invest. If an investor chooses not to invest in the company, they keep $X and $Y but don't get the returns. If they choose to invest, then $X is invested into the startup, reducing their total pool of funds

• The startup then uses that money and runs experiments within their business to validate their hypothesis. After they’ve taken this money, the startup has two probabilistic outcomes of their experiementation (the probability of success is P1, and the probability of failure is 1-P1. The assumption here is after their first experiment, if the founders, choose then to ask for more money

• Based on the outcome (success or failure), the investor can then choose to invest again and give the founders more money. In which case the startup has more cash to run experiments and further validate their additional hypotheses or the investor can keep $Y (the money used for follow on investments).

• With a follow-on investment, there’s conditional success:

  • PS - the probability of success after the first success, and

  • PF - the probability of success after the first failure.

We can assume that PS > PF (this means two successful outcomes in a row is likely to lead to a greater probability of $V than one failure and then one success). Ultimately, success is a function of the probability that a startup can be successful across multiple stages of their business (success = validating a hypothesis at each stage of the company).

This means that the probability of $V (the probability of a return) can be mathematically described as:

For those who aren’t mathematically inclined, this means the probability of a return (success) is the sum of both avenues for success (probability two successes in a row (P1 x PS) plus the probability of a failure and a success (1-P1 x PF).

If you want to take it even further, that means the expected return (denoted as E(V)) is just the probability of a return, multiplied by the magnitude of a return:

Recalling that VCs want to maximise the value of the eventual payoff $V this means they have two ways to do this (given that PS > PF):

1. Maximise the magnitude of $V - This is why VCs are obsessed with founder ambition and vision. Naturally, the founders with the grandest ambitions have the most room to run and when there’s lots of room the run, the value of $V can get very large, and large enough for exponential returns such that the Power Law comes into play. Some investors think about this value ($V) as TAM, but if you believe in a founder’s ability to create value, particularly in new markets they have created, then the focus should be on ambition and aspiration rather than TAM. This means trying to quantifying $E(V) (i.e. the total potential return) at the early stage is more of an abstract exercise

2. Maximise the probability value of P(V) - choosing the subset of founders with the greatest probability of success. Obviously it goes without saying that these founders also need to have large potential $V values such that you can realise venture scale returns, but really the optimisation here is founders with the highest possible P1 values, or PS or PF values. This means in order to maximise P(V), investors should invest in founders that will have either (or both):

   1. The highest probability of success at the first stage of experimentation; or

   2. Incredible resilience - founders who can maximise the probability of success after failure

Unfortunately for all the VCs reading this, there’s not a magic, endless supply of ambitious, resilient and high probability founders in market. And even if there was, trying to assess and quantify these values is incredibly difficult given the broad and variable that which founders come from. Assessment of success is also rife with bias adding to the difficulty, and there are VCs who admittedly have no idea how to make assessments in particular domains, which restricts the pool of high probability founders they can draw upon.

Now here lies the two diverging schools of thought in VC:

1. VCs who believe that P1 (and subsequently PS and PF) can be quantified accurately and maximised and only invest in founders and companies they believe have maximum P1. Conventionally, you could call this ‘high conviction’ investing. These VCs optimise for ownership in these companies at first cheque and continue to follow on in subsequent rounds.

2. VCs who have a P1 benchmark threshold and invest in any founder or company who meets the minimum threshold P1 value. Inverse to the above, this is optionality investing and if you take this to the extreme at lower P1 values, this could be described colloquially as ‘spray and pray’ investing. These VCs will write smaller cheques intially and then take larger, more meaningful stakes in later rounds or in the case of ‘spray and pray', not follow on at all and simply invest only once in a company (at the earliest cheque, entry points at low so you can still achieve sizeable ownership)

Sourcing the best companies and most ambitious founders is a difficult exercise and even if you can source these founders, given there’s a finite amount of these companies and finite ownership of these companies, it makes venture competitive for top companies, which then increases the entry point for investments and potentially eroding away return multiples.

You can effectively distill venture capital as a function of several things:

• VC Sourcing Efficiency - finding P1 founders. These are the founders who have the highest probability; and

• VC Assessment Ability - assessing that they are truly P1 startups and subsequently assessing for PS and PF; and

• VC Value Add - the ability of support and infuence the success of a startup (i.e. PS/PF and subsequent probability rounds) such that you can increase the overall probability of P($V). No jokes and cliches here, this is actually a real thing that can influence the success of a company.

Drinking a coffee? I'd love one, thanks!

Venture Probability in the US

I’ve chosen a selection of US based VC funds to illustrate differences in early stage VC portfolio strategy. These funds to invest across a range of stages but I’ve only accounted for their early stage investments (Pre-Seed and Seed) where arguably the probability of success at the first experiment (P1) is very low.

My starting point is that I’m assuming that a VC will ‘follow on’ in investment regardless if the initial experiment was a success or not. This means they believe the founders can still generate a return from subsequent, successful experiments.

The inverse to this is VCs who will only invest in a ‘follow on’ round if the initial experiment was successful. The implication here (flicking back to the logic tree above) is that a VC will not invest if an initial experiment fails because the opportunity cost outweighs PF (the probability of success after failure).

• In truth, there’s actually a lot of reasons why a VC doesn’t follow on. Sometimes they’ve run out of funds or don’t have the funds to deploy at later stages. Maybe their LP mandate has restricted them from investing in later rounds. But if you believe that VC’s want to optimise for ownership in the top performing companies, it’s more than likely they will continue to invest in their ‘winners’ at least one more time after their first investment.

Let’s dive into this table.

Union Square Ventures is one of the best performing VC funds in the world.

• USV has a small and highly concentrated portfolio (they mention their 2016 fund aimed to invest in 20-23 companies), which means they invest a larger proportion of their fund into each company. This outlines that USV is a ‘high conviction’ investor

• This shines through because a large number of their investments receive follow on investments, meaning they had strong belief in the initial investment such that they are going to continue to support the founder and invest to maintain (or grow) their stake, regardless of whether the first experiment was a success or not

• You could also assume the initial experiment failed and that USV only invested in the successful companies. But given their high follow on percentage (>50%), this means USV believes they have high skill at picking the right founders to back (P1 founders)

• USV has had 48 exits and a number of their portfolio companies have graduated to the public markets including Twilio, Cloudflare, Etsy and Twitter (none of these were Pre-Seed or Seed investments however!). This puts their exit rate at around 25% across their entire portfolio which is an impressive goal rate

The complete inverse of USV is 500 Global. Their website boasts they have invested in over 2,600 companies. I’ve got data for 2,200 and of that list, 1,823 of these companies where invested for the first time at Pre-Seed or Seed.

• 500 Global could be described as an optionality investor with a portfolio of early stage companies of this size. They invest all around the world in a broad set of domains and verticals so it’s likely that they have a P1 threshold and they’re optimising for shots on goal instead of trying to build the absolute best team

• The majority of their investments don’t receive follow on investments - only a quarter of their investments receive follow on. There’s some nuance here but I don’t necessarily think it’s for lack of funds. For example, they invested in African unicorn ChipperCash at their Seed round and continued to invest until their Series C (their latest round)

• I’m sensing that 500 Global invests a small amount initially (smaller $X) and then follows on in their successful companies (larger $Y). And this strategy is actually working for them! They boast that their portfolio has 49 unicorns and 150+ companies with a valuation greater than $100m

• This is almost like a development squad. By choosing to invest in a large amount of players, they get access to information that helps them make future decisions, and then they can create a new team of players who are more likely to score goals (follow on investments)

• As a side note - if you’re a high conviction fund, consider seeding an earlier stage with a larger and more diversified portfolio for access to companies and information without impact to your own brand

These two funds showcase how the game-tree above plays out in reality. If you’re a VC who can assess for P1 at incredibly high accuracy and fidelity, then it’s worth maintaining a small, concentrated portfolio. This also means you can work closely with founders to influence PS or PF values and improving the probability of a return.

If you’re VC who would prefer to instead maintain a highly diversified and large portfolio, you should set a benchmark for P1 and write optionality cheques that give you the ability to invest again for greater ownership if the initial experiment was successful. This would lead to much larger portfolios, reducing the time you can spend with founders, but gives you more time to source new founders and deploying at faster rates.

Some VCs do both and perhaps Khosla and a16z are two examples of this given they sit between the spectrum of USV and 500 Global. My personal take is that it can be difficult to execute on this unless you have the right infrastructure internally to support a growing portfolio, otherwise you risk not being able to support founders. And this has ramifications on your ability to win future deals if you’re unable to provide the support to founders you’ve otherwise said you can. There is a very real trade-off between fund portfolio size and success and only the best VCs can navigate this trade-off effectively.

This is another reason why it could be worth seeding other funds as you won’t have to make that trade-off.

Final Thoughts on VC Decision Making

This was actually very interesting to write and think about. Playing the thought experiment, if I was running my own fund:

• Would I be a high conviction investor with a highly concentrated portfolio or would I run an optionality fund with a much larger portfolio?

There’s overlays to this as well. With a smaller fund (<$20m), it might be difficult to execute a portfolio strategy that requires me to invest in 50-100 companies. There’s the funnel overlay - if only 1% of companies are VC backable, then you would need to see 10,000 companies to back 100. This would require someone to be across multiple domains and verticals and the market in Australia may not be large enough for that.

Additional Reading

I highly recommend these two papers both of which I have used extensively for this article:

• We Have Met the Enemy…and He is Us from the Kauffman Foundation

• Predicting Success in Early Stage Venture Capital by Hans Jacques Lindahl Falck

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What’s Next?

I have something incredibly spicy but I’ll only release when this hits 1,000 subscribers. If you want some real and deep inside baseball, better get sharing.

I’d love to hear from you if there was something that reasonated in this article or if you have feedback for me. Shoot me a message, DM me on Twitter, add me on Linkedin, or even UberEats me some pizza (rip Deliveroo).

If you’re interested in collaborating, please reach out to me here.

Pop Culture, Dating and More

As promised:

• I was in Canberra last weekend for Dad’s birthday. Every time I’m back in Canberra, I can’t help notice the incremental things that make it even cooler. There’s some pretty impressive founders in Canberra too, maybe it’s an untapped bastion of alpha

• I went on a first date this week - seemed promising with a second one lined up! More on this later!

• I’m surprised Pokemon hasn’t gotten into NFTs. Seems like a great use case. You could make them interoperable across games and there’s rarity in Pokemon so naturally lends itself to exclusivitiy. And people are already obsessed with catching them all.

Introduction to Rare Candy

Welcome to the inaugural edition of Rare Candy. I’m pretty excited to be writing this (and for you to be reading!).

I’ll keep this introduction short, because I know why you’re here.

Rare Candy is a monthly newsletter providing you with deep, insightful analysis about investing, venture capital and technology. It will almost certainly be quantitative and data-driven and hopefully, it will be novel analysis.

At times, it may also be about other things I’m interested in such as sports, cooking, pop culture, millennial dating, books, memes and more. But I’ll keep it relevant to venture and investing where I can.

If you’re interested in collaborating, please reach out to me here. I’d love to share some ideas and see how we can work together.

Like what you’ve read today? Coffee is getting expensive and I need it to keep writing.

Shout Me a Coffee

Summary

Key Insights and Ask

Just here for the chart? Here is what you need to know:

1. The ‘Big 3’ VC funds are in a league of their own - Square Peg, AirTree and Blackbird have incredible efficiency at both sourcing deals and deploying capital.

2. Differentiation in approach is working - Funds like AfterWork, EVP and Galileo are showing they can compete by differentiating their focus and their approach. More on this below.

3. Capital allocation strategy differs across funds - It’s still a power law game, but the game is played differently by funds.

My Ask: Reach out to me and provide me with updated data for my charts. This data won’t be shared with anyone else and it won’t be made public on this newsletter.

Note: Not every VC fund is included. This data requires a lot of manual input so I focused on a selection. Want to help with future analysis? Reach out!

I love investing. I’m addicted. I love ‘leveling up’ and learning about interesting asset classes like vinyls, whiskey, Pokemon cards and more. That's why I've been reading Alts. Stefan and Wyatt write deep analysis on alternative assets and you get to reap the rewards.

Join 50,000 others and see what you’ve been missing. Subscribe to Alts for free.

Introduction to Leverage Models

Leverage models are a way to understand how work gets delivered by organisations. Commonly used in professional services firms (law, consulting, banking etc), they help you understand the mix of ‘grinders’ (the analysts / associates like yours truly who ‘do’ the work), the ‘minders’ who babysit the grinders and the ‘finders’ who win work for the minders and grinders to deliver.

I’ve applied this to understand three ratios across a selection of Australian VC funds to understand how work (or capital) gets delivered:

• Investment Team Leverage - Ratio of Partners to other investors (analysts, associates, managers, principals and directors). As leverage increases, Partners are freed to do other things like fundraise and meet LPs, thesis development, advise Boards and founders and grow their twitter following and less time ‘grinding’.

• Deployment Availability - Ratio of funds available to deploy (or funds being raised to deploy) per investors at a fund. This doesn’t mean every investors get free reign to deploy that capital (although some funds do operate this way) but provides an indicative and directional view of how funds staff and structure their investment teams based on their fund size.

• Deal Leverage - Ratio of the investments closed this calendar year per investors at a fund. You could say it’s an indicative and directional view of the number of deals each investor makes. While in practice this isn’t really true as funds have their own decision making processes and governance structures, it’s a binary way to think about investments and investment teams. If you assume that 1 in every 100 startup gets venture backed, you could even use it as a proxy for deal sourcing and coverage - more deals you see, the more deals get done.

Why is this important?

If you’re an investor at a VC fund, I’d be shocked if you hadn’t done this analysis internally already on your own fund, or another fund. Understanding these ratios provides investors with foresight on internal budgeting, fund and investor performance. Understanding the staffing requirement to deploy the fund you’ve raised by using these ratios is particularly useful, but even more useful is understanding the staffing requirement required to source and see the right deals (some funds have found a cheat code to sourcing and have seeded other funds for coverage and flow. If you want to seed a fund, reach out to me 💰).

These ratio help with answering two key questions for investors: Based on our investment team size, are we:

1. Investing at the right rate (amount, quantity of capital etc)?

1. Seeing the right volume of deals?

Why am I doing this analysis?

The short answer is that I love doing this type analysis, I love uncovering this insight and I really love bubble charts. Maybe it’s Stockholm Syndrome from being an ex-strategy consultant?

The serious answer is that I aspire to become a great venture investor and part of this journey for me is truly understanding this industry and its opaque nuances. Aptly named, this newsletter is about my journey to the Elite Four, and by learning what I can about the other ‘Trainers’ and ‘Gyms’ in this industry, it’ll help me get better at the craft of venture.

Investment Team Leverage

This is what the current investment team leverage looks like across the VC landscape. Higher leverage implies a greater ratio of non-Partner investors to Partners in a fund. As a side note - I don’t buy the notion that founders need to be speaking to a Partner straight away. Analysts and associates can become incredible advocates for founders (they’re generally young and hungry to prove themselves).

As funds scale and grow in size, they build higher leverage models to support growth. Blackbird are looking to raise a fund could range in the $1-1.3bn+ range and their leverage model likely reflects that. Smaller funds are naturally top heavy given they have smaller (in aggregate) dollars to pay for salaries, leading to leaner teams that are mainly Partners.

The outlier here is Square Peg which has the lowest leverage of any of the Big 3 and almost lower than most funds on this chart.

There is a lot of you can imply or speculate on regarding this chart - it’s not that interesting to me in isolation so let’s move onto the meatier analysis.

(Maybe a fund with higher leverage will see this chart and promote someone to Partner just to reduce leverage the next time I publish it).

Analysing VC Leverage Ratios

Across these funds, there is $3.7bn in funds raised (or to be raised) and ~120 investors.

Square Peg, AirTree and Blackbird are truly in a league of their own when it comes to venture in Australia. These funds have shown strong ability to get deals across the line and haven’t slowed activity despite the market conditions. It’s worth calling out that these funds also have 2-3x the size of investment team than other funds and have managed to close more deals per investor than the other funds on this chart. They’ve grown in scale and efficiency, which was a surprise to me as my initial hypothesis was the inverse but it shows the strength of these funds.

Up and to the right is Blackbird. If you believe the hypothesis that funds increase their deal leverage as they scale (i.e. more people = more deals), it makes sense that they’re firmly in the top quadrant. I’ve even cut this chart with axis breaks because they were skewing it too far to the right. They’re raising their latest fund at the moment and I’m unsure whether they’ll hire another crop of investors so I’m sure this positioning could change, but again, if you believe in the above hypothesis, they might continue to shoot off to the right.

AirTree and Square Peg are closer in positioning - they have similar fund sizes, investment team sizes and have closed a similar amount of investments this calendar year. Two calls outs on this:

• AirTree have recently hired two new investors (and an investment research manager), all three of which are included as part of this analysis. If we take them out, AirTree move further to the right and much more closely aligned to Blackbird. I’d be suprised if these investors have closed deals in between the time they joined AirTree and this article being written seeing as it’s relatively recent but only AirTree can tell me that.

• Square Peg only has 5 investors who are focused on Australia. This puts their AU presence at half the size of these other funds. If you assume they’re sourcing deals at the same volume in aggregate as both AirTree and Blackbird, this implies incredible sourcing coverage and efficency.

There’s more I want to write on these three but they’re better placed below in the Geographical Coverage and Domain Coverage write-up. And besides, I have to keep you reading.

Let’s take them out for now, because they're skewing the chart…

We start to get some really interesting insights. In the orange quadrant, there are a few interesting funds that I want to call out specifically because they’ve all differentiated themselves outside of the normal ‘early stage investor’.

• AfterWork Ventures has differentiated itself from other funds and leverages (see what I did there?) a community-powered approach to investing.a AfterWork is proving that this model is working - if you believe that deal leverage could be used as a proxy for deal coverage (the hypothesis above), then it’s apparent that their community-powered approach is a unique superpower that gives them similar deal leverage as the Big 3 but without the team size.

• OIF and Carthona are interesting funds too and differentiated in a different way. Both are funds that don’t have ‘investing-adjacent’ pursuits in the way some other funds do but both funds boast high deal leverage and their investment teams are below the average size of VC funds in the country.

• Investible is an interesting fund because they have broad geographical coverage and broad domain coverage. They play across SEA and have multiple fund types (i.e. early stage fund, climate focused fund) and I think this lends itself to getting more deals done, partly due to the fact they’re probably just seeing a greater volume of deals. More on this below.

• EVP is another really interesting fund because they predominately invest in B2B SaaS (btw EVP if you’re reading this, I’ve invested in two B2B SaaS companies that you should definitely mark up for me, reach out!). They’re likely seeing almost every B2B SaaS business in AU and NZ and can win those deals given their status and expertise in the space.

• Lastly, Galileo is a new fund that invests only in first-time founders and they aim to be the first cheque in those companies. This proposition is proving to be attractive for founders and they’ve co-invested alongside some great US funds including a16z and Insight Venture Partners.

Thematically, these funds have differentiated themselves either through their approach to sourcing, investing activities, or which segments of the market they invest in and it’s proving very well. As the VC space becomes more saturated, this differentiation will continue to be the key to their success and the success of new funds.

Lastly, the blue quadrant is really interesting to me. Main Sequence Ventures is a deep-tech investor and there’s very few deep tech start-ups in Australia (watch this space because I’m sizing this market and will publish my results in the coming months). Given that the ‘top of funnel’ is smaller in aggregate for MSV, their positioning makes sense here. It would be interesting to do this analysis but for deep tech focused funds only!

Drinking a coffee? I'd love one, thanks!

Geographical Leverage

Geographical leverage (or coverage) is an interesting overlay on this analysis. The majority of VC funds in Australia invest in AU / NZ founders and by nature of this, the majority of those founders are located in AU or NZ. This isn’t really insight at all.

The real insight (in my mind) is thinking about these investment teams, their coverage and comparing how these teams are structured.

Square Peg has 5 investors who cover Australia and the rest of their team covers South-East Asia (SEA) and Israel. Most VC funds have 5+ investors covering Australia, some even more so. To me, this implies that Square Peg are exceptional at sourcing because they can cover the same landmass as other funds but with fewer people. This isn’t necessarily true though because I don’t know if they see every deal in the country but it leads me to think about diminishing returns regarding sourcing effectiveness as you add new investors to an investment team unless you can tap into ‘alpha’ in some way. Something that could be true though - if you increase the diversity of your investment team as you increase size, you’re likely to see more deals. People of the same background will undoubtedly end up sourcing the same deals.

Aura is another interesting call out here - they have 6 investors who cover AU, NZ and SEA. Once again, this implies that Aura is exceptional at sourcing if they can effectively cover the region with this size of an investment team. They’re an early stage investor so their ‘market size’ is as large as it gets in venture.

Lastly, Investible has a presence in SEA with an office in Singapore but it looks like they have one dedicated investor in the region, supported by two investors based in Australia. They’ve investing across the region including Singapore, Indonesia and the Philippines which shows that they’ve got the ability to source across borders and even if it’s a lean team.

One last thing on this point - don’t read this as the AU based funds only invest in AU or NZ. Tidal Ventures has a presence in NYC and has invested in US companies. AfterWork just announced an investment in a SEA based company. Someone I lived with at college just got backed by a Big 3 fund and they weren’t even in the country (or had any connections with Australian VCs).

Domain Leverage

The last topic I want to cover in this article is Domain Leverage. I’ll be short here because this newsletter is already getting too long.

VCs invest in a range of segments and industries which means they need to effectively source and diligence these opportunities. This is hard. Diligence on a B2B SaaS startup is very different to a regulated MedTech startup and this again is very different to a Web3 startup. Sourcing is the same.

As funds grow in size, they need to find new areas of investment to deploy their cash into and part of their leverage models needs to account for these domains. Some examples here to show how domain leverage is playing out in practice. AirTree has a dedicated Web3 investor and Blackbird has a Scientist-in-Residence.

As we discussed above, some funds have specific domain mandates. EVP invests predominantly in SaaS. Main Sequences invests only in deep tech.

You can take this model to an extreme at generalist funds too - a16z has Partners who only focus on one segment or vertical. This enables them to source effectively and diligence effectively as they have domain experts who have cultivated a ‘halo’ effect in these verticals.

Will we get to that extreme in Australia? I’m not sure - the market might be too small for funds to be doing this consistently across the board, but differentiation is key to playing and winning in this game. I don’t think any new funds can be a ‘generalist early stage investor’ without genuinely having a differentiator, the landscape is becoming too competitive.

Limitations

This is point in time analysis made with unverified data points. You’ve probably noticed I’ve made assertions and conclusions and then followed up with ‘this isn’t necessarily true’. The difficulty of private markets is that data is scarce and fragmented, meaning analysis like this is hard to do without verified data.

Final Thoughts on Leverage Models

Leverage models in this space are super interesting because it exposes differences in fund structure and capital allocation strategy. a16z in the US fuctions almost like a consulting firm with its leverage model and the full-stack of services it offers to portfolio companies. Only bigger funds can compete in this way so for smaller funds, they’ll need to shift the other direction and continue to differentiate in novel and exciting ways in order to compete in this ecosystem.

This was a lengthy article, thank you for reading if you’ve made it this far. Did you find it useful? Let me know by sending me a message or sliding into my Twitter DMs.

What’s Next?

I’ll be releasing interesting analysis every month on investing, venture capital and technology.

I’d love to hear from you if there was something that reasonated in this article or if you have feedback for me. Shoot me a message, DM me on Twitter, add me on Linkedin, or even UberEats me some pizza.

If you’re interested in collaborating, please reach out to me here.

Reading, Cooking, Sports and More

As promised:

• Reading - I finished reading Before the Coffee Gets Cold by Toshikazu Kawaguchi. If you’re into magical realism, I highly recommend it.

• Cooking - Carbonara with speck is a game-changer, it crisps better than guanciale and has a more intense flavour.

• Sports - I’m 4-1 (3rd of 12) in my Fantasy NFL league, taking a real money ball approach and barely watching game, only stats.

• Life - After almost 5 years of living with one of my best friends, I’ve moved into my own place. It’s also right next to the office of a VC fund. Classic.

About Me

I’m Albert, I’m a technology investor and strategist. I grew up in Darwin, studied Chemistry and Law at the ANU in Canberra (with a brief stint in North Carolina at Chapel Hill), and moved to Sydney in 2018.

I started my career as a strategy consultant and left consulting to become an early employee at a venture-backed SaaS startup.

Now you can find me at Astral Ventures, on Twitter and on a tennis court or at a bouldering gym. In my free time, I co-host an investing podcast called Fresh Capital and now I write this newsletter.

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Rare Candy is a newsletter providing deep analysis on startups, venture capital and investing. At times, it may also be about pop culture, sports, gaming, internet sub-culture and millennial dating.

Who are you?

I’m a technology investor and strategist. I’ve spent 5+ years working in across strategy consulting, startups and VC.

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Yes.

This is Rare Candy by Albert Patajo, a newsletter about leveling up on the way to Victory Road.

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