Tag: Software

The Return of Capital Efficiency

Capital efficiency has long been a desirable trait in early/growth stage businesses. But over the last few years, an abundance of capital combined with a “growth at all cost” mindset, allowed founders to deprioritize efficiency. Ignoring efficiency, however, can lead to making cardinal mistakes like misreading true product-market-fit, over-hiring for the stage you are in and burning through too much money too quickly. Furthermore, growth rate and top-line progress are a function of how much capital a business has consumed to get to that point (i.e. getting to $10M in revenue is less impressive if you spent $50M to get there vs spending $5M to get there.)

In a post-covid world, capital efficiency has returned as king. This is especially true in SaaS (which, as a category, has outperformed almost every other category.) Many of the companies that have outperformed during this time frame have been very efficient businesses (e.g. Twilio, Zoom, Shopify, Datadog, etc.) As the fundraising markets dry up a bit and sales cycles lengthen, founders will increasingly be forced to think more about efficiency and investors will pay a premium for efficient businesses.

But how should SaaS founders think about efficiency? Several years ago, Bessemer put out a simple, but helpful rule-of-thumb called the BVP efficiency score. The efficiency score shows a “good-better-best” framework for thinking about capital efficiency (defined as Net New ARR / Net Burn.) They advised founders (under $30M ARR) to think about good-better-best using the table below:

1

While this is a great high-level framework, efficiency among SaaS businesses is a bit more nuanced depending on stage. In the formative days, finding product-market-fit can take time and money. In the early days of growth, building a scalable and repeatable playbook can require significant up-front investment. As the company moves into expansion-mode, the business benefits from clear economies of scale and an improved gtm playbook. In the later stages, the business should be humming and efficiency ought to be at an all-time high.

The point is: benchmarking efficiency in a meaningful way requires looking more closely at stage/ revenue profile. What we really need is an efficiency score for each stage. Or, put differently, a rubric showing how much capital ought to be consumed (and, yes, there is a difference between “raised” and “consumed”) to achieve various ARR milestones along the journey from $0M to $100M in ARR.

Below are two frameworks for founders to use to help answer this question. These tables were developed based on what I’ve seen in the field over the years and have been triangulated with what several other SaaS investors have also seen. The first table is simply a good-better-best framework for total capital consumed to get to different ARR thresholds. The second is a “stage-adjusted” efficiency score. These two tables are, of course, two sides of the same coin.

2

3

Bear in mind these are simple guidelines / “rules of thumb” and anecdotal in nature. Every business has its own set of nuances and unique circumstances. And there is definitely more variability earlier on depending on the nature of the product (i.e. some companies have to invest a lot more in R&D to get the product to market.) Where you land on the grid is less important than what the trend-line looks like and whether you have managed cash wisely (i.e. been a “good steward of capital.”)

To bring this to life a bit, here are a few “hall-of-fame” worthy examples of companies that scaled past 100M in ARR with record breaking efficiency. Note that we are listing capital raised here as a close proxy in the absence of public data on capital consumed:

  • Veeva raised a total of $7M pre-IPO. Current market cap: $33B
  • Appfolio raised a total of $30M pre-IPO. Current market cap: $5B
  • Ringcentral raised a total of $44M pre-IPO. Current market cap: $24B
  • Wix raised a total of $59M pre-IPO. Current market cap: $11B
  • Salesforce raised a total of $65M pre-IPO. Current market cap: $162B
  • Zendesk raised a total of $86M pre-IPO. Current market cap: $9B
  • Realpage raised a total of $86M pre-IPO. Current market cap: $7B

It is no surprise that almost all of the above examples got going in the “good old days” of the 2000s, when capital was less plentiful, and efficiency much more in vogue. Much of this changed in the 2010s, but I suspect we will see the pendulum swing back to some degree in the decade ahead. Hopefully, this helps provide some useful data points in this return-to-efficiency world we now find ourselves in!

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I’d like to thank Alex Kurland (@atkurland), Brian Murray (@murr), Chetan Puttagunta (@chetanp), Logan Barlett (@loganbartlett), Murat Bicer (@itsbeecher) and Parsa Saljoughian (@parsa_s) for their feedback and help in triangulating the numbers here.

Hybrid B2B Revenue Models…and How to Value Them

Summary:

  • While the 2000s and 2010s gave birth to many B2B SaaS greats, the 2020s will usher in a new wave of winners that have far more heterogenous business models.

0. Josh Kopelman

As we begin to reach a certain level of maturity among cloud applications, it has become increasingly clear that we are now moving beyond the first wave of pure SaaS players that came to define the 2000s and 2010s and produced big B2B wins like Salesforce, Atlassian, Zoom, Hubspot and many others. In more recent times, we’ve migrated from this homogenous SaaS world to a more complex world of hybrid businesses, which generate different types of revenue in their quest to build enduring value. This, of course, has played out in many industries beyond software. Costco, for example, was one of the OGs here with its membership subscription fee + item price revenue model.

In some cases, hybrid models are an evolution over time: an early stage company starts with a wedge software product that customers love and then evolves in the growth stages to include additional features that drive new sources of revenue like lead gen fees, payment transaction revenue, lending revenue, etc. This is the story of Shopify, which originally generated subscription revenue for access to its ecommerce software tools before evolving to include additional revenue sources like payments, transaction fees from apps in its app marketplace and other “store-front fees” like domain registration.

In other cases, mixed revenue streams can happen right from the get-go. Our portfolio company, Sendoso, has operated as a SaaS + Transaction revenue-model from Day 1. Customers pay a subscription fee for access to the platform and a set of integrations into the sales, marketing and customer success stack. Additionally, they then pay a separate transaction fee for physical or virtual items sent through the platform to current customers or prospects.

Shopify and Sendoso are certainly not the first businesses with a hybrid model, nor will they be the last. As we enter a world where mixed-models become more common, the two questions then become:

(1) What will these mixed-models look like?

(2) How do founders think about valuation in the absence of less established rules of thumb?

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SaaS: Established Rules of Thumb

But before we get to answering these two questions, it’s helpful to review the basics behind the most successful B2B business model of the last 2 decades: pure SaaS. It is well understood that the two most important financial drivers impacting the valuations of public SaaS companies are, first and foremost, growth rate and second, to a lesser extent, gross margin (though the latter may increase in importance given the recent times.) Below is a view from a basket of SaaS businesses. For illustrative purposes, this is a snapshot taken from February, before the market volatility caused by coronavirus.

1. Growth Rate

2. Gross Margin

To sum: most public SaaS businesses north of 100M ARR that are growing 30–40% with 70–80% gross margins can command a multiple of ~10–12x on the public markets (or at least they could pre-coronavirus; we will know over the coming months whether the current deflation is temporary or here to stay.)

In the “earlier” venture to growth-stage world, this translates into a number of operating levers that are well understood. This post is not meant to be a review of the literature on SaaS metrics but there are some great resources for further reading on these topics, which I’ve included in an appendix at the end.

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Mixed Revenue Models: Forging into Newer Territory

In today’s world, we are seeing a notable uptick in mixed revenue models. B2B companies chasing additional growth opportunities are realizing that once they have achieved clear customer lock-in with one product, maintaining a high growth rate and expanding their TAM, can often be accomplished by cross selling other ancillary products — many times with different types of revenue. This has taken the shape and form of at least four playbooks:

(1) Software + Services

Selling services in addition to software is of course nothing new. In the on-prem/ perpetual license world, professional services were essential to the delivery and implementation of enterprise software. In the cloud application world, professional services typically play a similar role when selling to large enterprises (e.g. the customer base has a lot of F500 customers.) These customers typically require broad integrations, time-consuming security audits and a white-glove experience. While necessary and incremental to top line, services revenue is broadly viewed as less valuable than SaaS revenue.

Workday and Veeva are two great examples of companies that have continued to excel at growing both SaaS and Services revenue. To this day both companies still have a very significant (and growing) services revenue stream (i.e. hundreds of millions of revenues annually) in addition to the SaaS revenue.

3. WDAY and VEEV

(2) Bundled Financial Services

A common theme we are seeing, especially within FinTech is the bundling of financial services. Typically, a business will find initial PMF around a single product with a single source of revenue — for example payments. Overtime, the business will offer its customers additional financial products generating additional revenue from things like lending, referrals to 3rd parties, % of AUM, interchange and a range of other revenue models.

Stripe is a great example of a company that has executed very well on this playbook. In “Act One,” Stripe created tremendous lock-in around it’s payments platform by enabling companies to process card charges on a 2.9% + $0.30 per transaction basis. But as the company evolved over time they built new products with different revenue models (see here for more info):

(3) Software + Bundled Financial Services

But FinTechs are not the only players to bundle financial services. We have begun to see a number of SaaS businesses use application software as an entry point, create lock-in with recurring revenue and then embed a host of other financial services directly into the platform. In doing so, these businesses can generate incredible momentum, widen their TAMs while also maintaining a broad base of stable recurring revenue.

No one has executed better on this playbook than Shopify, which has grown to over $70B in market cap (accelerating through covid-19 no less) and has commanded a revenue multiple of over 30x at certain times. Shopify’s SaaS business gives merchants access to its ecommerce platform + tools to build storefronts; while it’s Merchant Solutions business (i.e. bundled financial services) generates revenue from customers via lending, payments, shipping and referral fees. In the early days, software was the main driver of revenue growth, but over time the financial services have accelerated in a very impressive way.

4. Shopify

(4) Software + Bundled Financial Services + Hardware

The final hybrid model we have seen is effectively #3 above with the addition of hardware. Hardware stand-alone businesses, of course, are notoriously difficult and very hard to operate successfully at scale. But hardware combined with the margins of SaaS and the extended reach of bundled financial services can be a very powerful business. Toast is a great example of a company that has successfully leveraged all three revenue sources to build a very effective business in the restaurant vertical (see here for more info):

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Hybrids: A Weighted Average Approach to Valuation

Mix-model business are thriving and clearly here to say. But valuing high-growth hybrids is more challenging in the absence of the simple heuristics developed for the SaaS world. My suggestion on how to value these companies in the early/growth stages (~$2-$20M in revenue) is to use a weighted average revenue multiple approach. In other words:

1. Break down the business into its various components based on where it is today from a net revenue perspective

2. Apply specific multiples to each of the distinct parts of the business based on general heuristics associated with underlying characteristics like growth rate, margin profile, usage frequency, etc

3. Add in a “boost” or “mute” for external factors like TAM, LTV, retention, depth of competition, customer profile, how the revenue mix may shift over time, etc. This is a big part of the “magic”

4. Use a Sum-Product function across revenue and revenue multiple

Below is a table that illustrates the valuation equation and some general “rules of thumb” as guidance:

5. Valuation

Example One

SMB SaaS business that helps its customers make payments to vendors and also generates a lead gen fee for referring its customers to new vendors. On the SaaS side (SMB so self-serve and no services), the business seems to be in the early innings of a strong growth trajectory (3x.3x.2x.2x.2x) having grown from 2M ARR to 6M ARR in the last year ($4M in revenue associated with the SaaS ARR.) The business did an additional $4M in payments revenue and $2M in lead gen revenue; for a total of $10M in revenue. The company operates in a large, mostly greenfield TAM and, over time, the payments revenue will grow to be the clear leading driver of revenue while the lead gen revenue becomes less relevant.

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As illustrated above, this is a SaaS + Bundled Financial Services model consisting of subscription revenue, payments revenue and lead-gen revenue. In addition, we applied a relatively high Boost of 0.75 to account for the strong growth profile and large/greenfield TAM; somewhat muted by the lower-multiple payments revenue being the predominant driver of long-term growth. The weighted multiple is ~9x.

Example Two

The second example, a POS terminal business that operates in corporate cafeterias, is also doing $10M in revenue. In addition to charging for the terminals, the company charges an installation fee for set up, generates payments revenue from processed transactions and takes a cut of revenue from any 3rd party apps installed on its devices. However, this business is slower growth due to longer sales cycles (grew < 40% last year.) The company also faces fierce competitors like Square, Toast and Revel.

2

As noted above, this is a Software + Bundled Financial Services + Hardware company. In addition to being comprised of different components than the company in example 1, this is also a lower growth business with 2–3 dominant competitors in market. As such, we added a lower boost scale and the weighted multiple ends up being ~4x.

Template: If you’d like to access these examples, and maybe run a few scenarios yourself, I’ve included a google sheet (here) where you can give it a try. Always open to suggestions on how to improve this so feel free to send my way.

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Final Thoughts

We’re moving into a more heterogenous world, where mixed-model revenue businesses will continue to emerge and thrive. As this new class of companies grow and thrive, founders and investors will need to better understand how to operate, grow and (ultimately) value these businesses. In some cases, it may make a lot of sense to start by valuing a company with one approach (e.g. SaaS) and then layer in other approaches over time as the company evolves. But taking a weighted average approach to valuation in conjunction with a bit of good judgement is a great way to understand valuation for these hybrids.

Appendix: Further Resources on SaaS

Overall SaaS Frameworks:

Growth Rate:

Retention

Sales Productivity / Efficiency

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If you have a different approach, I’d love to hear about it (@MrAllenMiller!) I’d also like to thank Kris (@rudeegraap), Dimitri (@dadiomov), Ian (@iankar_) and Sheel (@pitdesi) for their contributions to this piece.

Cyber-security: a renewed sense of urgency for enterprises

Security has been a chief concern for enterprises since the early days of computing. As software has evolved to enable businesses to be more productive, hackers have also evolved to take advantage of vulnerabilities in the tech stack. The DDoS attack on Dyn last October, which resulted in much of the American internet being unavailable for the majority of the day, unveiled a pretty scary weapon available to hackers called the Mirai botnet. And while the malware was eventually contained, cyber attacks remain a very real threat to enterprises.

I’ve noticed at McKinsey, where we pride ourselves on client confidentiality, that we have begun to approach enterprise security with a renewed sense of urgency. The firm has conducted a massive cyber security campaign including: mandatory courses for new hires, periodic phishing tests (unfortunately, yours truly has failed a few!) and the addition of a new cyber solutions group to support the firm internally as well as engage with many of our enterprise clients. All this is encouraging and I’m glad the firm is investing in this area. But still it’s tough to feel at ease if for no other reason than the fact that it’s tough to deciphere the world of cyber security jargon.

So what exactly is shaping the nebulous world of cyber security and what can we expect in the near term? There’s a lot of literature on the various types of attacks and the underlying technology being used in these attacks. In layman’s terms, however, it boils down to two (almost opposing) trends:

  • (1) Commodification and automation of basic attacks: Known vulnerabilities are being included in attack scripts and being made available to less skilled attackers. In addition, networks of attack robots are running attack scripts against any device connected to a network.
  • (2) Professionalization and specialization of attackers: Attackers are acquiring the skills to plan and launch long-term campaigns and advanced persistent threats (APTs). In addition, electronic platforms, e.g., “ExploitHub”, connect attack experts globally and allow for trading specific skills. Finally, better educated attackers are entering the scene, e.g. secret services building up cyber security capabilities.

While the development of these themes (particularly the second one) is alarming, the good news is that there are a number of industry stalwarts who have long been building and re-building software to fight these attacks. In addition, there are a range of emerging players who are also building meaningful security products.

Cyber security companies can be grouped into 5 categories: (1) endpoint security, (2) network security, (3) web/ messaging security, (4) identity and access management (IAM) and (5) security and vulnerability management (SVM). Below I have provided a view by category of each of these categories and some of the existing and emerging players:

Capture

So where’s the opportunity for new entrants? All five of these categories have real opportunity and one could credibly build a company around each. But right now IAM and SVM are particularly relevant to large enterprises, many of which have little institutional knowledge of these categories. IAM is crucial because corporate data, and especially customer data, is often an enterprise’s most valuable asset – to suffer identity fraud could be catastrophic. SVM is important as well becasue most large enterprises don’t have a clear sense of their risk levels or ways to track vulnerability. Diagnosing and then monitoring risk levels helps enterprises understand where they are vulnerable and what they can do to shield themselves from attack.

I hope we see more companies built around these two areas because we’re going to need high quality software tools to protect against the attacks we are seeing from a new, and very sophisticated, generation of hackers.

Metrics that Matter in SaaS

Today, software entrepreneurs are very fortunate to have a wealth of information available on the indicators and metrics to focus on when running a SaaS business. There is so much out there that it can be a bit overwhelming to absorb. With that in mind, I’ve put together a one page summary of the core areas every SaaS founder should focus on when first starting and running a SaaS business.

This is not meant to be an exhaustive list of every KPI but rather an 80/20 “boil-it-down-to-what-matters-most” view of the qualitative and quantitative indicators of the overall health of a SaaS business. This also doubles as a checklist when going out to raise an institutional round of capital (most VCs will ask for these metrics as part of their diligence process.)

capture

The way to think about it is in 4 categories.

  • (1) Qualitative: Indicators in this category, while not as quantitative as the rest on this list, are likely to be the most important for early stage companies. They include a sharp focus on the team and the founder(s). The product/ service itself and early customer feedback are likewise very important.
  • (2) Market Metrics: Venture investors care a lot about the market in which a business is focused on (and entrepreneurs should as well to ensure they are solving a worthy problem!) Key metrics here include the overall TAM and growth (or stagnation/decline) of the industry. In addition the competitive landscape, both the number of competitors and share of each competitor, is key.
  • (3) Financial Metrics: Metrics in this category tend to be a bit more objective – but even here much is dependent on the idiosyncrasies of a particular business, what stage it is in and the market opportunity ahead of it. Here, most financial metrics boil down to 3 things:
    • Top-line revenue and growth: CMRR/CARR is the most accurate predictor here
    • Margin profile: some combination of gross and operating margin
    • Cash position:both burn rate and runway
  • (4) Operating Metrics: Operating metrics tend to be a bit more unique in SaaS than in other business models. A good way to think about operating metrics is through three sub-categories:
    • Customer willingness to pay: a combination of ACV, NPS, expansion revenue, etc. combined with the pricing model employed can help determine overall WTP
    • Sales efficiency: magic number (developed by Scale Venture Partners) is a great metric as are payback period and sales cycle length
    • Churn: gross revenue churn is closely tied to growth but cohort analysis and the quick ratio (developed by Social Capital) are also good metrics to track

As mentioned earlier, there is a wealth of information on all of 4 of these areas as well as best-in-class metrics based on revenue, stage, etc. Some of the best material out there for further reading includes: Byron Deeter’s State of the Cloud report, David Skok’s For Entrepreneurs blog and Jason Lemkin’s content on SaaStr.

Grow fast or die slow: Why unicorns are staying private

In today’s world, technology companies worth more than $1 billion—and many worth $10 billion—have fewer reasons to go public than they did in the past. It’s a new paradigm shift that has really changed many of the dynamics in the startup community. A few of us in McKinsey’s High-Tech practice put together an article on the software IPO environment and the implications for founders and VCs. We hope it’s an insightful read.

The full article is available here.