Notes from the Okta S-1 IPO Filing

Okta, a SaaS identity management platform (software to manage which corporate applications people can use), just released their S-1 IPO filing to go public. You might wonder how big the market is to manage authentication and authorization in the cloud, and as we’ll see, it’s quite large.

Here are a few notes for the Okta S-1 IPO filing:

  • Founded in 2009 (pg. 1 – Note: founding to IPO in eight years is fast!)
  • 2 million people use Okta daily (pg. 1)
  • 2,900 customers (pg. 2)
  • Revenues (pg. 2)
    • 2015 – $41 million
    • 2016 – $86 million
    • Last nine months – $112 million
  • Losses (pg. 2)
    • 2015 – $59 million
    • 2016 – $76 million
    • Last nine months – $65.3 million
  • Estimated $18 billion global opportunity (pg. 3)
  • Over 5,000 integrations available (pg. 4 – Note: strong network effect)
  • Product modules (pg. 4)
    • Universal directory
    • Single sign-on
    • Multi-factor authentication
    • Lifecycle management
    • Mobility management
    • API access management
  • Original company name: Saasure (pg. 6)
  • 12% internation revenue (pg. 34)
  • Accumulated deficit of $270 million (pg. 51)
  • 11% of revenue from professional services (pg. 57)
  • Weighted-average contract duration of 2.4 years (pg. 62)
  • Define contribution margin as the annual contract value of subscription commitments, or ACV, from the customer cohort at the end of a period less the associated cost of subscription revenue and sales and marketing expenses (pg. 63 – Note: this is the SaaS Magic Number)
  • 443 customers with an annual contract value over $100,000 (pg. 65)
  • Deferred revenue of $100 million (pg. 78 – Note: this means customers pay their annual subscription upfront making for a significant amount of “free” working capital)
  • “Okta” is the unit of measure for cloud cover in meteorology (pg. 88)
  • Ownership (pg. 132)
    • Co-founder/CEO – 10.3%
    • Co-founder/COO – 6.2%
    • VCs – 65.7%

Okta is like a utility providing a core service that everyone needs but doesn’t get much attention. Identity management in the cloud is critical infrastructure with a massive market and Okta, as the leader, will have a successful IPO.

Congratulations to Todd and the team!

What else? What are some more thoughts on Okta’s S-1 IPO filing?

Quick Notes on Fast-Growing SaaS Startup Intercom

Intercom is a fast-growing SaaS startup that provides customer communication software for doing live chat, in-app customer messages, email triggers, helpdesk support, and knowledge base content. Their CEO recently published an interesting blog post titled Vanity metrics, the future, and 100,000 thank yous with a number of interesting metrics.

Here are a few notes on the blog post and Intercom:

  • Started in 2011 (source)
  • Took four months to raise $500k (source)
  • Raised $1M angel round in 2012 (source)
  • Raised $6M Series A in June 2013 (source)
  • Raised $23M Series B 30 months after starting the business (source)
  • 7,000 paying customers after four years (source)
  • 50% of the 280 employees are in product and engineering as of last year (source)
  • Raised $35M Series C four years to the day they started the company (source)
  • Raised $50M Series C-1 in mid 2016 for a total of $116M (source)
  • Took two years to hit $1M in annual recurring revenue
  • 300+ employees today
  • 100,000 monthly active users
  • 400,000,000 customer conversations per month
  • Educate, the knowledge base product, is at $1.5M ARR
  • 17,000 companies that are paying customers
  • Grew from $1-50M in ARR in three years ($2,941 average revenue per year per customer)
  • Revenue run rate at end of year:
    • 2013 – $1M
    • 2014 – $7M
    • 2015 – $22M
    • 2016 – $50M
  • 2016 operating margin of -36%

Impressive metrics all around and easily one of the fastest growing SaaS companies in the world. Congrats to Intercom on reimagining customer communication for the modern business and building an incredible company.

Notes from the MuleSoft S-1 IPO Filing

MuleSoft, a fast-growing data and application integration software provider, just released their S-1 IPO filing. As more companies move to the cloud, the demand for connecting these applications, and the legacy installed applications, has grown as well.

Here are a few notes on the MuleSoft S-1 IPO filing:

  • Key metrics as of December 31, 2016 (pg. 1)
    • > 1,000 customers
    • 117% dollar-based net retention
    • 70% revenue growth
    • $188 million in revenue
    • -1.4% operating cash flow margin
  • Customers use the Anypoint Platform to connect their applications, data, and devices into an “application network” in which these IT assets are pluggable using application programming interfaces, or APIs, instead of glued together with custom integration code. (pg. 1)
  • Estimate the current market opportunity to be $29 billion. (pg. 3)
  • 30 customers with over $1.0 million in annual contract value of subscription and support contracts. (pg. 3)
  • Revenue (pg. 3)
    • 2014 – $57.6 million
    • 2015 – $110.3 million
    • 2016 – $187.7 million
  • Net losses (pg. 3)
    • 2014 – $47.8 million
    • 2015 – $65.4 million,
    • 2016 – $49.6 million
  • Professional services revenue (pg. 8)
    • 2014 – $9.1 million
    • 2015 – $22.2 million
    • 2016 – $34.9 million
  • Accumulated deficit of $236.2 million as of December 31, 2016 (pg. 12)
  • In 2014, 2015, and 2016, total sales and marketing expense represented 102%, 84%, and 65% of revenue (pg. 15)
  • Outsource the cloud infrastructure to Amazon Web Services, or AWS, which hosts the platform (pg. 16)
  • Platform is deployed in a wide variety of technology environments, both on-premises and in the cloud (pg. 16)
  • 38% of the revenue from customers located outside the United States in 2016 (pg. 27)
  • 156 employees located in Argentina at the end of 2016 (pg. 29)
  • Ross Mason created Mule in 2006 to address the frustrations of manually connecting disparate systems and applications. Mule took its name from Ross’s desire to take the “donkey work” out of legacy approaches to technology integration. (pg. 57)
  • Annual contract value of $169,000 in 2016 (pg. 58)
  • Subscription pricing is based primarily on the amount of computing capacity on which the customers run the software (pg. 58)
  • Founder owns 5.9% (pg. 134)
  • VCs own 67.8% (pg. 134)

MuleSoft is a hybrid cloud and on-premise software provider with a pricing model that bills everything like SaaS. Data and application integration is a massive market and MuleSoft is well positioned to grow for many years and have a strong IPO. Like AppDynamics, look for large strategics to take an interest in MuleSoft as well.

Think Gross Margin When Considering Metrics

Earlier today I was talking to a growth stage startup in town and was reminded of the importance of gross margin when considering metrics. From Wikipedia:

Gross margin is the difference between revenue and cost of goods sold, or COGS, divided by revenue, expressed as a percentage.

In the SaaS world, gross margins are assumed to be in the 75-85% range such that the heuristics, like The Golden Metric for SaaS – $1 Burned for $1 of Recurring Revenue is consistent from company to company. Yet, most companies don’t have SaaS gross margins (and different cost of goods sold), such that when thinking about metrics and best practices, they should be recalibrated for the gross margins of the specific company. Meaning, if the Golden Metric for SaaS is $1 of cash burned for $1 of net new annual recurring revenue, that assumes 80% gross margins. If the company has 40% gross margins, the Golden Metric would be $1 of cash burned for $2 of net new annual recurring revenue (half the margin so need twice the revenue).

Whenever you hear metrics and best practices mentioned, factor in the gross margin.

What else? What are some more thoughts on considering gross margin when thinking about metrics?

The Golden Metric for SaaS – $1 Burned for $1 of Recurring Revenue

Thinking more about the post from a couple weeks ago titled Evaluating a Startup Based on Cash Burned vs Recurring Revenue and how the same idea was brought up again two days ago in Bessemer’s 2017 State of the Cloud Report, I’ve come to believe that $1 of cash burned for $1 of net new recurring revenue is the Golden Metric for SaaS.

As an idea, it’s easy to understand.

As a metric, it’s easy to track.

As a way to create value, it’s excellent.

As a benchmark for entrepreneurs to measure against, it’s perfect.

Some startups will choose to burn more than $1 for each $1 of new new recurring revenue, but most won’t have that luxury. Startups that achieve scale, and burn $1 (or less!) for every $1 of net new recurring revenue, will do well for all stakeholders involved.

What else? What are some more thoughts on the Golden Metric for SaaS being $1 of cash burned for $1 of net new recurring revenue?

Bessemer’s 2017 State of the Cloud Report

There was so much good content at the SaaStr Annual that it’s going to time to get through it all. Next of the list is Bessemer’s 2017 State of the Cloud Report.

Here are a few notes from the Bessemer slide deck:

  • 40% of the market cap of publicly traded SaaS companies has already been acquired representing greater than $300 billion in value
  • Key questions from top CEOs:
    • How fast should I be growing?
    • How much should I burn?
    • How do I scale?
  • How fast should I be growing?
    • Dropbox is the fastest SaaS company ever to hit $1B in run rate (did it in eight years)
    • The pace is quickening for SaaS companies going from $1M – $100M in recurring revenue (5.3 years for top 25%, 7.3 years median, 10.6 years bottom 25%)
    • BVP Growth Benchmark for ARR
      • Good
        • $1 – $10M in four years
        • $1 – $100M in 10 years
      • Better
        • $1 – $10M in three years
        • $1 – $100M in 7 years
      • Best
        • $1 – $10M in two years
        • $1 – $100M in five years
  • How much should I burn?
    • Rule of 40 = % Annual Revenue Growth + % Profit Margins
    • Efficiency Score = % Annual CARR Growth + % Burn
    • BVP Efficiency Rule (> $30M ARR)
      • Expansion ($30 – $60M ARR) – 70% efficiency score
      • IPO (~$100M ARR) – 50% efficiency score
      • Public (>$150M ARR) – 30% efficiency score
    • BVP Efficiency Rule (< $30M ARR)
      • Net New ARR / Net Cash Burn > 1
      • Meaning, for every dollar burned, company needs $1 or more net new dollars of ARR
  • How do I scale?
    • Customer Acquisition Cost (CAC) Payback = Total Sales and Marketing Costs Last Quarter / New CMRR Added Last Quarter * % Gross Margin
    • Understanding Your Sales Model
      • SMB
        • CAC Payback 3-6 months
        • AVG ACV < $12k
        • Churn/Upsell < 3% monthly
      • Midmarket
        • CAC Payback 12 months
        • AVG ACV $12 – $50k
        • Churn/Upsell 1% monthly
      • Enterprise
        • CAC Payback 3-6 months
        • AVG ACV $50k+
        • Churn/Upsell < 1% monthly, upsell

Thanks to the team at Bessemer for putting together the great information. Every SaaS entrepreneur should read Bessemer’s 2017 State of the Cloud Report.

SaaS Numbers that Actually Matter

Continuing with 12 Key Levers of SaaS Success from David Skok at SaaStr, Mamoon Hamid gave an excellent presentation Numbers that Actually Matter. Finding Your North Star.

Here are a few notes from the presentation:

  • Quick Ratio (QR) = New MRR + Expansion MRR / Churned MRR + Contraction MRR
  • Goal is a Quick Ratio greater than 4
  • Product-market fit happens one customer at a time one month at a time
    • Mostly ignored any product-market fit metrics
  • Churn/Expansion/Contraction MRR is a lagging indicator of product-market fit
  • MRR is the price that the customer pays, the North Star is the value that they get
  • Focus on a leading indicator of the MRR decision
  • Your North Star measures the value you deliver
  • Bad: Mostly measuring price paid as opposed to value delivered
    • MRR, paid seats
  • Good: Measures value delivered in bulk
    • MAU, DAU, messages sent
  • Better: Unquestionably indicates Product Market fit has been reached with the customer
    • Number of users with L28 >= 16
    • Messages sent w/in 30 days in signup

Read the presentation Numbers that Actually Matter. Finding Your North Star. and figure out the North Star for your product.

Evaluating a Startup Based on Cash Burned vs Recurring Revenue

In the SaaS world, one of the common best practices is to have the cost of customer acquisition be equal to or less than the first year’s revenue (or even better would be gross margin). So, if on average it costs $5,000 in fully loaded sales and marketing expense to acquire a customer that pays $5,000 per year, things are going well. After learning that heuristic, and working with a number of entrepreneurs, I’ve come to take it one step further and judge the success-to-date of a startup based on the amount of money burned all-time vs the annual recurring run-rate today, especially if it’s one to one.

While burning $1 to get $1 of recurring revenue might not sound like much, it’s actually really good. Think of a company that’s growing fast at $5 million recurring on $5 million burned all-time. In today’s market, that company is likely valued at $30M .- $40M (6-8x run-rate). Spending $5M to build a company worth that much is likely a good scenario for everyone involved including founders, employees, and investors. A common phrase in the startup world is “if the company sells for 10x the amount of money raised, everyone does well.” While a valuation of 10x the capital raised is excellent, consider the ratio of capital burned all-time to current recurring revenue as another metric to evaluate the success of a startup.

What else? What are some more thoughts on evaluating a startup based on cash burned vs recurring revenue?

The SaaS Metrics Framework

Updata Partners released their new SaaS Metrics Framework and it’s excellent. SaaS companies have a number of business model elements that are consistent from one company to another such that it’s possible to run them through a process and see how they stack up fairly quickly. Updata’s framework is one such model.

Here are a few notes from the SaaS Metrics Framework:

  • Two SaaS metrics that matter most: Gross Margin Payback Period (GMPP) and Return on Customer Acquisition Cost (rCAC)
  • GMPP is the number of months required to break even on the cost of acquiring a customer
  • rCAC incorporates the element of customer churn/retention into the equation and calculates the multiple of the acquisition cost provided by the lifetime gross profit of a customer
  • Good is GMPP under 18 months and rCAC above 3x
  • Great is GMPP under 12 months and rCAC above 5x
  • Cohort level analysis is necessary and must be run across at least three critical dimensions: Vintage, Product, and Channel
  • Metrics and sequence of analysis
    1. MRR – Monthly Recurring Revenue
    2. tCAC – Total Customer Acquisition Cost
    3. RGP – Recurring Gross Profit
    4. GMPP – Gross Margin Payback Period
    5. eLT – Expected Lifetime
    6. LTF – Lifetime Value
    7. rCAC – Return on Total Customer Acquisition Cost

One big takeaway: SaaS companies need to be thinking about many of the popular metrics like the SaaS Magic Number in the context of gross margin, not revenue. And, thankfully, gross margin should improve with scale. Want to understand SaaS unit economics better? Head over to SaaS Metrics Framework.

What else? What are some more thoughts on Updata’s SaaS Metrics Framework?

Measuring SaaS Churn Rates 2.0

Dave Kellog published a new post recently titled A Fresh Look at How to Measure SaaS Churn Rates in which he introduces several new concepts related to SaaS churn. On the surface, SaaS churn seems pretty straightforward — take the number of customers that were up for renewal at the start of the time period, take the number that left during the time period, and divide the second into the first — but it’s much more nuanced than that. What about logo vs revenue churn, by cohort, by product, by account, or by any of a number of other measures? It gets more complicated, quickly.

Here are a few notes from the article:

  • Leaky Bucket Equation: Starting ARR + new ARR – churn ARR = ending ARR
  • Tracking it as churn is more common that tracking it as renewals
  • Shrinkage (anything that shrinks ARR) and expansion (anything that expands ARR) need to be factored in
  • Two most important churn rates: logos (by customer count) and ARR (by recurring revenue)
  • 5 churn rate formulas:
    • Simple churn = net churn / starting period ARR * 4
    • Logo churn = number of discontinuing logos / number of ATR+ logos.
    • Retention = current ARR [time cohort] / time-ago ARR [time cohort]
    • Net churn = account-level churn / ATR+
    • Gross churn = shrinkage / ATR+

Want to better understand churn in the context of SaaS? Head over to A Fresh Look at How to Measure SaaS Churn Rates and take a deep dive.

What else? What are some other good resources on SaaS churn?