Mike Kwatinetz is a Founding General Partner at Azure Capital Partners and a Venture Capitalist investing in application software (SaaS), ecommerce, consumer web and infrastructure technology companies. Successful exits include: Bill Me Later, VMware, TripIt and Top Tier.
Applying Private Investment Analysis to the Rash of Mega-IPOs Occurring
first half of 2019 saw a steady stream of technology IPOs. First Lyft, then
Uber, then Zoom, all with different business models and revenue structures. As
an early investor in technology companies, I spend a lot of time evaluating
models for Venture Capital, but as a (recovering) investment analyst, I also
like to take a view around how to structure a probability weighted investment once
these companies have hit the public markets. The following post outlines a
recent approach that I took to manage the volatility and return in these growth
Question: Which of the Recent technology IPOs Stands out as a Winning
Investing in Lyft and Uber, post IPO, had
little interest for me. On the positive side, Lyft revenue growth was 95% in Q1,
2019, but it had a negative contribution margin in 2018 and Q1 2019. Uber’s growth was a much lower 20% in Q1, but it
appears to have slightly better contribution margin than Lyft, possibly even as
high as 5%. I expect Uber and Lyft to improve their contribution margin, but it
is difficult to see either of them delivering a reasonable level of
profitability in the near term as scaling revenue does not help profitability
until contribution margin improves. Zoom Video, on the other hand, had
contribution margin of roughly 25% coupled with over 100% revenue growth. It also
seems on the verge of moving to profitability, especially if the company is
willing to lower its growth target a bit.
Zoom has a Strong Combination of Winning Attributes
There is certainly risk in Zoom but based
on the momentum we’re seeing in its usage (including an increasing number of
startups who use Zoom for video pitches to Azure), the company looks to be in
the midst of a multi-year escalation of revenue. Users have said that it is the
easiest product to work with and I believe the quality of its video is best in
class. The reasons for Zoom’s high growth include:
Revenue retention of a cohort is currently 140% – meaning that the same set of customers (including those who churn) spend 40% more a year later. While this growth is probably not sustainable over the long term, its subscription model, based on plans that increase with usage, could keep the retention at over 100% for several years.
It is very efficient in acquiring customers – with a payback period of 7 months, which is highly unusual for a SaaS software company. This is partly because of the viral nature of the product – the host of the Zoom call invites various people to participate (who may not be previous Zoom users). When you participate, you download Zoom software and are now in their network at no cost to Zoom. They then offer you a free service while attempting to upgrade you to paid.
Gross Margins (GMs) are Software GMs – about 82% and increasing, making the long-term model likely to be quite profitable
Currently the product has the reputation of being best in class (see here) for a comparison to Webex.
Zoom’s compression technology is well ahead of any competitor according to my friend Mark Leslie (a superb technologist and former CEO of Veritas).
The Fly in the Ointment: My Valuation Technique shows it to be Over
My valuation technique, published in one of our blog posts, provides a method of valuing companies based on revenue growth and gross margin. It helps parse which sub-scale companies are likely to be good investments before they reach the revenue levels needed to achieve long term profitability. For Zoom Video, the method shows that it is currently ahead of itself on valuation, but if it grows close to 100% (in the January quarter it was up 108%) this year it will catch up to the valuation suggested by my method. What this means is that the revenue multiple of the company is likely to compress over time.
Forward Pricing: Constructing a Way of Winning Big on Appreciation of
So instead of just buying the stock, I constructed
a complex transaction on May 29. Using it, I only required the stock to
appreciate 10% in 20 months for me to earn 140% on my investment. I essentially
“pre-bought” the stock for January 2021 (or will have the stock called at a
large profit). Here is what I did:
Bought shares of stock at $76.92
Sold the same number of shares of call options at $85 strike price for $19.84/share
Sold the same number of shares of put options at $70 strike for $22.08/share
Both sets of options expire in Jan 2021 (20 months)
Net out of pocket was $35/share
Given the momentum I think there is a high
probability (75% or so) that the revenue run rate in January 2021 (when options
mature) will be over 2.5x where it was in Q1 2019. If that is the case, it seems
unlikely that the stock would be at a lower price per share than the day I made
the purchase despite a potential for substantial contraction of Price/Revenue.
In January 2021, when the options expire, I will either own the same shares, or double the number of shares or I will have had my shares “called” at $85/share.
The possibilities are:
If the stock is $85 or more at the call date, the stock would be called, and my profit would be roughly 140% of the net $35 invested
If the stock is between $70 and $85, I would net $42 from the options expiring worthless plus or minus the change in value from my purchase price of $76.92. The gain would exceed 100%
If the stock is below $70, I’ll own 2x shares at an average price of $52.50/share – which should be a reasonably good price to be at 20 months out.
Of course, the options can be repurchased, and new options sold during the time period resulting in different outcomes.
Break-Even Point for the Transaction Is a 32% Decline in Zoom Video Stock
Portfolio Managers that are “Value
Oriented” will undoubtedly have a problem with this, but I view this
transaction as the equivalent of a value stock purchase (of a high flyer) since
the break-even of $52/share should be a great buy in January 2021. Part of my
reasoning is the downside protection offered: where my being forced to honor
the put option would mean that in January 2021, I would own twice the number of
shares at an average price of $52.50/share. If I’m right about the likelihood
of 150% revenue growth during the period, it would mean price/revenue had
declined about 73% or more. Is there some flaw in my logic or are the premiums
on the options so high that the risk reward appears to favor this transaction?
I started writing this before Zoom reported
their April quarter earnings, which again showed over 100% revenue growth
year/year. As a result, the stock jumped and was about $100/share. I decided to
do a similar transaction where my upside is 130% of net dollars invested…but
that’s a story for another day.
Estimating the “Probabilistic” Return Using My Performance Estimates
Because I was uncomfortable with the
valuation, I created the transaction described above. I believe going almost 2
years out provides protection against volatility and lowers risk. This can
apply to other companies that are expected to grow at a high rate. As to my
guess at probabilities:
75% that revenue
run rate is 2.5x January 2019 (base) quarter in the quarter ending in January
2021. A 60% compound annual growth (CAG) for 2 years puts the revenue higher
(they grew over 100% in the January 2019 quarter to revenue of $105.8M)
95% that revenue
run rate is over 2.0X the base 2 years later (options expire in January of that
year). This requires revenue CAG of 42%. Given that the existing customer
revenue retention rate averaged 140% last year, this appears highly likely.
99% that revenue
is over 1.5X the base in the January 2021 quarter (requires slightly over 22% CAG)
1% that revenue is
less than 1.5X
Assuming the above is true, I believe that
when I did the initial transaction the probabilities for the stock were (they
are better today due to a strong April quarter):
50% that the stock
trades over 1.5X today by January 2021 (it is almost there today, but could hit
a speed bump)
80% that the stock
is over $85/share (up 10% from when I did the trade) in January 2021
10% that the stock
is between $70 and $85/share in January 2021
5% that the stock
is between $52 and $70 in January 2021
5% that the stock is
Obviously, probabilities are guesses since
they heavily depend on market sentiment, whereas my revenue estimates are more
solid as they are based upon analysis, I’m more comfortable with. Putting the
guesses on probability together this meant:
80% probability of
140% profit = 2.4X
10% probability of
100% profit = 2.0X
5% probability of
50% profit (this assumes the stock is in the middle at $61/share) = 1.5X
5% probability of
a loss assuming I don’t roll the options and don’t buy them back early. At
$35/share, loss would be 100% = (1.0X)
If I’m right on these estimates, then the
weighted probability is 120% profit. I’ve been doing something similar with Amazon
for almost 2 years and have had great results to date. I also did part of my DocuSign
buy this way in early January. Since then, the stock is up 27% and my trade is
ahead over 50%. Clearly if DocuSign (or Amazon or Zoom) stock runs I won’t make
the same money as a straight stock purchase would yield given that I’m capped
out on those DocuSign shares at slightly under 100% profit, but the trade also
provides substantial downside protection.
Conclusion: Investing in Newly Minted IPOs of High Growth Companies with
Solid Contribution Margins Can be Done in a “Value Oriented” Way
When deciding whether to invest in a
company that IPOs, first consider the business model:
Are they growing at a high rate
of at least 30%?
contribution margins already at 20% or more?
Is there visibility to profitability
without a landscape change?
Next, try to get the stock on the IPO if
possible. If you can’t, is there a way of pseudo buying it at a lower price? The
transaction I constructed may be to complex for you to try and carries the
additional risk that you might wind up owning twice the number of shares. If
you decide to do it make sure you are comfortable with the potential future
Why doesn’t Amazon produce more earnings given its dominance?
Amazon just reported earnings and, as was the case in 2017 and 2016, emphasized that 2019 will be an investment year, so the strong operating margin expansion of 2018 would be capped in 2019. This, of course, is great fodder for bears on the stock as Amazon gave sceptics renewed opportunity to point out that it is a company that has a flawed business model and would find it difficult to ever earn a reasonable return on revenue.
In contrast, I believe that Amazon continues to transform itself into a potential strong profit performer. For example, taking the longer perspective, Amazon’s gross margins are now over 40% up from 27.2% five years ago (2013). So why doesn’t Amazon deliver higher operating margin than the slightly over 6% it reported in 2018? Amazon’s dirty little secret is that it continues to invest heavily in creating future dominance through R&D. Had it spent a similar amount in R&D to its long time competitor, Walmart, EBITDA would have nearly tripled… to over 17% of revenue! I must confess that in the past I haven’t paid enough attention to how much Amazon spends on R&D. As a result, I was surprised that Apple and Microsoft trailed it in voice recognition technology and that Amazon could lead IBM and Microsoft in cloud technology. The reason this occurred is not a surprising one: Amazon outspends Apple, Microsoft and IBM in R&D.
In fact, Amazon now outspends every company in the world (see Table 1) and have been dedicating a larger portion of available dollars to R&D (as measured by the % of gross margin dollars spent on R&D) than any other large technology company, except Qualcomm, for more than 10 years. Even though Amazon had less than 50% of Apple’s revenue and less than 1/3 of its gross margin dollars 5 years ago (2013) Amazon spent nearly 50% more than Apple on R&D that year… by 2018 the gap had increased to close to 100% more.
Table 1: Top 10 (and a few more) U.S. R&D Spenders in 2018 ($Bn)
Note 1: Ford and GM may be in the top 10 but so far have not reported R&D in 2018. If they report it at year end the table could change. Walmart does not report R&D and their spend is generally unavailable, but I found a reference that said they expected to spend $1.1M in 2017.
Note 2: A 2018 global list would include auto makers VW and Toyota (with R&D of $15.8B and about 10.0B), drug company Roche (&10.8B) and tech company Samsung at $15.3B in place of the lowest 4 in Table 1.
The Innovators Financial Dilemma: Increasing Future Prospects can lower Current Earnings
When I was on Wall Street covering Microsoft (and others) Bill Gates would often point out that the company was going to make large investments the following year so they could stay ahead of competition. He said he was less concerned with what that meant for earnings. That investment helped drive Microsoft to dominance by the late 1990s. Companies are often confronted with the dilemma of whether to increase spending to drive future growth or to maximize current earnings. I believe that investment in R&D, when effective, is correlated to future success.
It is interesting to see how leaders in R&D spending have transitioned over the past 10 years. In 2008 the global leaders in R&D spending included 5 pharma companies, 3 auto makers and only 2 tech companies (Nokia and Microsoft which subsequently merged). In 2018, 6 of the top 7 spenders (Samsung plus the 5 shown in Table 1) were technology companies.
Table 2 – 2008 global R&D leaders ($Bn)
Note: *Facebook data from 2009, first available financials from S-1 filing
It’s hard to change without tanking one’s stock
When a company has a business model that allocates 1% of gross margin dollars to R&D, it is not easy to turn on the dime. If Walmart had decided to invest half as much as Amazon in R&D in 2018, its earnings would have decreased by 80% – 90% and its stock would have depreciated substantially. So, instead it began a buying binge several years ago to try to close the technology gap through acquisitions (which has a much smaller impact on operating margins). It remains to be seen if this strategy will succeed going forward but in the past 5 years Walmart revenue (including acquisitions) increased only 5% while Amazon’s was up 130% in the same period (also including acquisitions).
Whatever Happened to IBM?
When I was growing up, I thought of IBM as the king of tech. In the early 1990s it still seemed to rule the roost. The biggest fear for Microsoft was that IBM could overwhelm it, yet now it appears to be an also ran in technology. From 2014 to 2018, a heyday era for tech companies, its revenue shrank from $93 billion in 2014 to $80 billion in 2018. I can’t tell how much of the problem stems from under investing in R&D versus poor execution, but for the past 5 years it has spent an average of about 13% of GM on R&D, while the 6 tech companies in Table 1 have averaged about 24% of GM dollars with Apple the only one under 20%.
Soundbyte I: Tesla
I recently had a long dialogue with a very smart fund manager and was struck by what I believe to be misinformation he had read regarding Tesla. There were 3 major points that he had heard:
The quality of Tesla cars was shoddy
Tesla could not maintain reasonable margins as it began producing lower priced Model 3s
The upcoming influx of electric cars from companies like Porsche, Jaguar and Audi would take substantial market share away from Tesla
I decided to do a bit of research to determine how valid each of these issues might be.
Tesla Quality: I found it hard to believe that the majority of Tesla owners thought the car was of poor quality since every one of the 15 or so people I knew who had bought one had already bought another or were planning to for their next car. So, I found a report on customer satisfaction from Consumer Reports, and I was not surprised to find that Tesla was the number 1 ranked car by customer satisfaction.
Tesla margins: this is much harder to predict. Since Tesla is relatively young as a manufacturer it has had numerous issues with production. Yet it is probably ahead of many others when it comes to automating its facilities. This tends to cause gross margins to be lower while volume ramps and higher subsequently. The combination of that, plus moving up the learning curve, should mean that Tesla lowers the cost of producing its products. However, Tesla charges more for cars with higher capacity for distance, but as I understand it uses software to limit battery capacity for lower priced cars. This would mean that a portion of the difference between a lower priced Model 3 and a higher priced one (the battery capacity) would be minimal change in cost, putting pressure on margins. The question becomes whether Tesla’s improving cost efficiencies offset the average price decline of a Model 3 as Tesla begins fulfilling demand for lower priced versions.
March 1 Update: After this post was complete (Thursday February 28) the company announced it was closing many showrooms to reduce costs. Then late today (Friday) announced that the $35,000 version of the model 3 is now available. So, we shall soon see the impact. I believe that if Tesla has increased capacity there will be very strong sales. It also likely will experience lower gross margin percentages as it climbs the learning curve and ramps production.
Will the influx of electric cars from others impact Tesla market share?
Porsche is an electric sports car starting at $90K – at that price point it is competitive with model S not model 3. In competing with the S it comes down to whether one prefers a sports car to a sedan. I have owned a Porsche in the past and would only consider it if I wanted a sports car with limited seating capacity (but very cool). I loved my Porsche but decided to switch to sedans going forward. Since then I’ve owned only sedans for the past 10+ years. It also appears that early production is almost a year away, so it is unlikely to be competitive for 2019.
Audi is at price points that do compete with the Model 3 and expects to start delivering cars in March. However, I think that is mainly in Europe where Tesla is an emerging brand so it might not impact them at all. When I look at the Audi models I don’t think they will appeal to Tesla buyers as they are very old-line designs (I would call them ugly). The range of the cars on a charge is not yet official but seems likely to be much lower than Tesla which has a big lead in battery technology.
The Jaguar competes with the Tesla Model X but while cheaper, appears a weak competitor.
I don’t want to dismiss the fact that traditional players will be introducing a large number of electronic vehicles. The question really is whether the market size for electric cars is a fixed portion of all cars or whether it will become a much larger part of the entire market over time. I would compare this to fears that analysts had when Lotus and Wordperfect created Windows versions. They felt that Microsoft would lose share of windows spreadsheets and word processors. I agreed but pointed out that Windows was 10% of the entire market for spreadsheets, so having a 90% share gave Microsoft 9% of the overall spreadsheet market. I also predicted Microsoft would have over a 45% share when Windows was 100% of the market. So, while this would decrease Microsoft’s share of Windows spreadsheets, it would grow its total share of the market by 5X Of course we all were proven wrong as Microsoft eventually reached over 90% of the entire market.
For Tesla, the question becomes whether these rivals are helping accelerate the share electric cars will have of the overall market, rather than eroding Tesla volumes. I’m thinking that it’s the former, and that Tesla will have a great volume year in 2019 and that its biggest competitive issue will be whether the Model 3 is so strong that it will get people to buy it over the Model S. Of course, I could be wrong, but believe the odds favor Tesla in 2019, especially the first half of the year where the competitors are not that strong.
The 2018 December selloff provides buying opportunity
One person’s loss is another’s gain. The market contraction in the last quarter of the year means that most stocks are at much lower prices than they were in Q3 of 2018. The 5 stocks that I’m recommending (and already own) were down considerably from their Q3 2018 highs. While this may be wishful thinking, returning to those highs by the end of 2019 would provide an average gain of 78%. Each of the 5 had revenue growth of 25% or more last year (and 3 were over 35%) and each is poised for another strong year in 2019.
For the 4 continued recommendations (all of which I mentioned I would recommend again in my last post), I’ll compare closing price on December 31, 2019 to the close on December 31, 2018 for calculating performance. For the new add to my list, I’ll use the stock price as I write this post. I won’t attempt to predict the overall market again (I’m just not that good at it) but feel that the 14% drop in Q4 means there is a better chance that it won’t take a nosedive. However, since stock picks are always relative to the market, success is based on whether my picks, on average, outperform the market.
I’ll start the post with stock picks and then follow with the remaining 5 predictions.
Tesla stock will outpace the market (it closed last year at $333/share and is essentially the same as I write this)
In Q3, 2018 the Tesla model 3 was the bestselling car in the U.S. in terms of revenue and 5th highest by volume. This drove a 129% revenue increase versus a year earlier and $1.75 in earnings per share versus a loss of $4.22 in the prior quarter. I expect Q4 revenue to increase sequentially and growth year/year to exceed 100%. In Q3, Tesla reported that nearly half of vehicles traded in for the Model 3 were originally priced below $35,000. As Tesla begins offering sub-$40,000 versions of it, demand should include many buyers from this high-volume price range. Since the backlog for the Model 3 is about 300,000 units I expect 2019 sales to remain supply constrained if Tesla can offer lower price points (it already has announced a $2,000 price reduction). The important caveat to demand is that tax credits will be cut in H1 2019, from $7500 to $3750 and then cut again to $1875 in the second half of the year. Part of Tesla’s rationale for a $2000 price drop is to substantially offset the initial reduction of these tax credits.
Tesla began taking orders for its Q1 launch in Europe where demand over time could replicate that in the U.S. The average price of a Model 3 will initially be about $10,000 higher than in the U.S. Tesla is also building a major manufacturing facility in China (where Model 3 prices are currently over $20,000 higher than the U.S.). This Giga-Factory is expected to begin production in the latter half of 2019. While moving production to China for vehicles sold there should eliminate trade war issues, Tesla still expects to begin delivering Model 3s to Chinese customers in March.
The combination of a large backlog, reducing prices within the U.S. and launches in Europe and China should generate strong growth in 2019. Some investors fear price reductions might lead to lower gross margins. When I followed PC stocks on Wall Street, this was a constant question. My answer is the same as what proved true there: strong opportunity for continuous cost reduction should enable gross margins to remain in the 20-25% range in any location that is at volume production. So, perhaps the Chinese Giga-Factory and a future European factory will start at lower margins while volume ramps but expect margins in the U.S. (the bulk of revenue in 2019) to remain in the targeted range. Higher prices in Europe and China due to massive initial demand allows premium pricing which may keep margins close to 20%+ in each.
Facebook stock will outpace the market (it closed last year at $131/share).
Facebook underperformed in 2018, closing the year down 28% despite revenue growth that should be 35% to 40% and EPS tracking to about 36% growth (despite a massive increase in SG&A to spur future results). The stock reacted to the plethora of criticism regarding privacy of user information coupled with the continuing charges of Russian use of Facebook to impact the election. Before the wave of negative publicity, Facebook reached a high of $218/share in July. Facebook is likely to continue to increase its spending to address privacy issues and to burnish its image. However, scaling revenue could mean it keeps operating margins at a comparable level to 2018 rather than increasing them. Rumors of Facebook’s demise seem highly exaggerated! According to a December 2018 JP Morgan survey of U.S. Internet users, the three most used social media products were Facebook (88% of participants), Facebook Messenger (61%) and Instagram (47%). Also, 82% of those surveyed picked a Facebook-owned platform as being the most important to them. Finally, the average Facebook user reported checking Facebook roughly 5 times per day with 56% of users spending 15 minutes to an hour or more on the platform on an average day. While Facebook has experienced a minor decrease in overall usage, Instagram usage has increased dramatically. Facebook, Instagram, and WhatsApp together give the company a growing and dominant position.
At the beginning of 2018 Facebook stock was trading at 34 times trailing EPS. By the end of the year the multiple of trailing EPS was below 18. If I assume EPS can grow 20%+ in 2019 (which is below my expectation but higher than the consensus forecast) than a multiple of 20 would put the stock at about $180/share by December 31. If it grew EPS, more in line with revenue and/or returned to a multiple closer to 34 it could reach well over 200.
Two key factors:
A 20% increase in revenue (I expect the increase to be about 30%) adds over $11 billion in revenue. A comparable 20% increase in SG&A would provide over $4 billion in additional money to spend, affording the company ample dollars to devote to incremental marketing without impacting operating margins.
Given the “low” stock price, Facebook increased its buyback program by $9 billion to $15 billion. Since it generates $6B – $7B in cash per quarter from operations (before capex) and has roughly $40 billion in cash and equivalents it could easily increase this further if the stock remains weak. The $15 billion could reduce the share count by as much as 3% in turn increasing EPS by a similar amount.
Amazon stock will outpace the market (it closed last year at $1502/share).
While its stock dropped from its September high of $2050, Amazon remained one of the best market performers in 2018 closing the year at $1502/share. At its 2018 high of $2050, It may have gotten ahead of itself, but at year end it was up less than 2018 revenue growth. Leveraging increased scale meant net income grew faster than revenue and is likely to triple from 2017. Growth will be lower in Q4 then Q3 as Q4 2017 was the first quarter that included all revenue from Whole Foods. Still, I would not be surprised if Amazon beat expectations in Q4 since this is already factored into analyst forecasts. Amazon trades on revenue coupled with the prospect of increasingly mining the revenue into higher profits. But the company will always prioritize making long term investments over maximizing near term earnings. Growth in the core ecommerce business is likely to gradually slow, but Amazon has created numerous revenue streams like its cloud and echo/Alexa businesses that I expect to result in maintaining revenue growth in the 20% plus range in 2019. The prospect of competing with an efficient new brick and mortar offering (see prediction 6 in this post) could drive new excitement around the stock.
Profitability in 2019 could be reduced by: announced salary increases to low end workers; increasing the number of physical store locations; and greater marketing incentives for customers. Offsets to this include higher growth in stronger margin businesses like AWS and subscription services. The stock may gyrate a bit, but I expect it to continue to outperform.
Stitch Fix stock will outpace the market (it closed last year at $17/share).
In my 2018 forecast I called this my riskiest pick and it was the most volatile which is saying a lot given the turbulence experience by Facebook, Tesla, and Amazon. I was feeling pretty smug when the stock reached a high of $52/share in September! I’m not sure how much of the subsequent drop was due to VCs and other early investors reducing their positions but this can have an impact on newly minted public companies. Whatever the case, the stock dropped from September’s high to a low point of $17.09 by year’s end. The drop was despite the company doing a good job balancing growth and profitability with October quarter revenue up 24% and earnings at $10.7 million up from $1.3 million in the prior year. Both beat analyst expectations. The stock was impacted because the number of users grew 22% (1-2% less than expected) despite revenue exceeding expectations at 24% growth. I’m not sure why this was an issue.
Stitch Fix continues to add higher-end brands and to increase its reach into men, plus sizes and kids. Its algorithms to personalize each box of clothes it ships keeps improving. Therefore, the company can spend less on acquiring new customers as it has increased its ability to get existing customers to spend more and come back more often. I believe the company can grow by roughly 20% or more in 2019. If it does and achieves anything close to the revenue multiple that it started with in 2018 (before the multiple doubled in mid-year), there would be a sizeable stock gain this year. But it is a thinly traded stock and likely to be quite volatile.
Docusign Stock will outpace the market in 2019 (it is currently at $43/share).
Docusign is a new recommendation. Like Stitch Fix, it is a recent IPO and could be volatile. Docusign is the runaway leader in e-signatures, facilitating multiple parties signing documents in a secure, reliable way on board resolutions, mortgages, investment documents, etc. Strong positives include:
A high value for a reasonable price – I am increasingly annoyed when I need to deal with manual signatures for documents.
As of October 31, 2018, Docusign had over 450,000 customers up from 350,000 customers one year earlier. Of which 50,000 are Enterprise/Commercial accounts;
There are hundreds of millions of users whose e-signatures are stored by the company making the network effect quite large;
Roughly 95% of revenue is from its SaaS product which has 80% gross margin with the rest from services where margins have improved and are now positive;
As a SaaS company with a stable revenue base growth is more predictable. The company exceeded revenue guidance each quarter with the October 31, 2018 quarter revenue up 37%;
Most customers pay annually in advance. This means cash flow from operations is positive despite the company recording an operating loss;
Customers expand their use resulting in retained customers growing revenue faster than decreases from churned customers making net revenue retention over 100%;
International expansion remains a large opportunity as international is only 18% of revenue.
Picks 6 – 10: Major Trends that will surface in 2019
I developed my primary method of stock picking at my first Wall Street firm, Stanford Bernstein. The head of research there, Chuck Cahn, emphasized that you could get small wins by correctly determining that a stock would trade up on certain news like a new product, a big customer win, and beating consensus forecasts. But larger and more predictable wins of 5X or more were possible if one identified a long-term winner riding a major trend and stuck with it for multiple years. All 5 of my stock picks fall into the latter category. I’ve been recommending Facebook, Tesla, and Amazon for 4 years or more. All 3 are now over 5X from when I first targeted them as I bought Tesla at $46 and Facebook at $24 in 2013 (before this blog) and they have been in my top 10 since. Amazon was first included in 2015 when it was at $288/share. Stitch Fix and DocuSign are riskier but if successful have substantial upside since both are early in their run of leveraging their key trends.
The next 4 picks are in early stages of trends that could lead to current and next generation companies experiencing benefits for many years. The first two go hand in hand as each describes transformation of physical retail/restaurants, namely, replacing staff with technology in a way that improves the customer experience. This is possible because we are getting closer to the tipping point where the front-end investment in technology can have a solid ROI from subsequent cost savings.
Replacing Cashiers with technology will be proven out in 2019
In October 2015 I predicted that Amazon (and others like Warby Parker) would move into physical retail between then and 2020. This has occurred with Amazon first opening bookstores and then buying Whole Foods, and Warby Parker expanding its number of physical locations to about 100 by the end of 2018. My reasoning then was simple: over 92% of purchases in the U.S. were made offline. Since Amazon had substantial share of e-commerce it would begin to have its growth limited if it didn’t create an off-line presence.
Now, for Amazon to maintain a 20% or greater revenue growth rate it’s even more important for it to increase its attack on offline commerce (now about 90% of U.S. retail) I’m not saying it won’t continue to try to increase its 50% share of online but at its current size offline offers a greater opportunity for growth.
A key to Amazon’s success has been its ability to attack new markets in ways that give it a competitive advantage. Examples of this are numerous but three of the most striking are Amazon Cloud Services (where it is the industry leader), the Kindle (allowing it to own 70% share of eBook sales) and Prime (converting millions of customers to a subscription which in turn incentivized buying more from Amazon due to free shipping).
Now the company is testing an effort to transform brick and mortar retail by replacing staff with technology and in doing so improving the buying experience. The format is called Go stores and there are currently 5 test locations. Downloading the Amazon Go App enables the user to use it to open the automated doors. The store is stocked (I think by actual people) with many of the same categories of products as a 7-Eleven, in a more modern way. Food items include La Boulangerie pastries, sushi, salads, an assortment of sandwiches and even meal kits. Like a 7-Eleven, it also has convenience items like cold medicine, aspirins, etc. The store uses cameras and sensors to track your movements, items you remove from the shelves and even whether you put an item back. When you leave, the app provides you with a digital receipt. Not only does the removal of cashiers save Amazon money but the system improves customer service by eliminating any need to wait in line. I expect Amazon to open thousands of these stores over the next 3-5 years as it perfects the concept. In the future I believe it will have locations that offer different types of inventory. While Amazon may be an early experimenter here, there is opportunity for others to offer similar locations relying on third party technology.
Replacing Cooks, Baristas and Waitstaff with robots will begin to be proven in 2019
The second step in reducing physical location staff will accelerate in 2019. There are already:
Robotic coffee bars: CafeX opened in San Francisco last year, and in them one orders drip coffee, cappuccino, latte, or hot chocolate using an app on your phone or an iPad available at a kiosk. The coffee is made and served by a robot “barista” with the charge automatically put on your credit card. Ordering, billing, and preparation are automatic, but there is still one staff member in the shop to make sure things go smoothly.
The first robotic burger restaurant: Creator opened in San Francisco last June. It was in beta mode through September before opening to the general public. While a “robot” makes the burgers, Creator is not as automated as CafeX as humans prepare the sauces and prep the items that go into the machine. Creator also hasn’t automated ordering/payment. Startup Momentum Machines expects to open a robotic burger restaurant and has gotten substantial backing from well-known VCs.
Robots replacing waitstaff: For example, at Robo Sushi in Toronto, a “Butlertron” escorts you to your table, you order via an iPad and a second robot delivers your meal. Unlike the robots in the coffee bar and burger restaurant these are made into cute characters rather than a machine. Several Japanese companies are investing in robotic machines that make several of the items offered at a sushi restaurant.
Robotic Pizza restaurants: The furthest along in automation is the Pizza industry. Zume Pizza, a startup that uses robots to make pizzas, has recently received a $375 million investment from Softbank. Zume currently uses a mix of humans and robots to create and deliver their pizzas and is operational in the Bay Area. Pizza Hut and Dominos are working on drones and/or self-driving vehicles to deliver pizzas. And Little Caesars was just issued a patent for a robotic arm and other automated mechanisms used to create a pizza.
At CES, a robot that makes breads was announced. What all these have in common is replacing low end high turnover employees with technology for repetitive tasks. The cost of labor continues to rise while the cost of technology shrinks a la Moore’s Law. It is just a matter of time before these early experiments turn into a flood of change. I expect many of these experiments will turn into “proof points” in 2019. Successful experiments will generate substantial adoption in subsequent years. Opportunities exist to invest in both suppliers and users of many robotic technologies.
“Influencers” will be increasingly utilized to directly drive Commerce
Companies have long employed Influencers as spokespersons for products and in some cases even as brands (a la Michael Jordon and Stephan Curry basketball shoes or George Forman Grills). They appear on TV ads for products and sometimes used their social reach to tout them. Blogger, a prior Azure investment, understood how to use popular bloggers in advertising campaigns. But Blogger ads, like most TV ads did not directly offer the products to potential customers. Now we are on the verge of two major changes: tech players creating structured ways to enable fans of major influencers (with millions of followers) to use one-click to directly buy products; and technology companies that can economically harness the cumulative power of hundreds of micro-influencers (tens of thousands of fans) to replicate the reach of a major influencer. I expect to see strong growth in this method of Social Commerce this year.
The Cannabis Sector should show substantial gains in 2019
In my last post I said about the Cannabis Sector: “The industry remains at a very early stage, but numerous companies are now public, and the recent market correction has the shares of most of these at more reasonable levels. While I urge great care in stock selection, it appears that the industry has emerged as one to consider investing in.” Earlier in this post, I mentioned that riding a multi-year wave with a winning company in that segment is a way to have strong returns. I’m not knowledgeable enough regarding public Cannabis companies, so I haven’t included any among my stock recommendations. However, I expect industry wide revenue to grow exponentially. The 12 largest public Cannabis companies by descending market cap are: Canopy Growth Corp (the largest at over $11B), Tilray, Aurora Cannabis, GW Pharmaceuticals, Curealeaf Holdings, Aphria, Green Thumb Industries, Cronos Group, Medmen Enterprises, Acreage Holdings, Charlotte’s Web Holdings and Trulieve Cannabis.
I believe one or more of these will deliver major returns over the next 5 years. Last year I felt we would see good fundamentals from the industry but that stocks were inflated. Given that the North American Cannabis Index opened this year at 208 well down from its 2018 high of 386 investing now seems timely. I’ll use this index as the measure of performance of this pick.
2019 will be the Year of the Unicorn IPO
Many Unicorns went public in 2018, but this year is poised to be considerably larger and could drive the largest IPO market fund raising in at least 5 years. Disbelievers will say: “the market is way down so companies should wait longer.” The reality is the Nasdaq is off from its all-time high in August by about 15% but is higher than its highest level at any time before 2018. Investment funds are looking for new high growth companies to invest in. It appears very likely that as many as 5 mega-players will go public this year if the market doesn’t trade off from here. Each of them is a huge brand that should have very strong individual support. Institutional investors may not be as optimistic if they are priced too high due to the prices private investors have previously paid. They are: Uber, Lyft, Airbnb, Pinterest, and Slack. Each is one of the dominant participants in a major wave, foreshadowing substantial future revenue growth. Because information has been relatively private, I have less knowledge of their business models so can’t comment on whether I would be a buyer. Assuming several of these have successful IPOs many of the other 300 or so Unicorns may rush to follow.
In working with early stage businesses, I often get the question as to what metrics should management and the board use to help understand a company’s progress. It is important for every company to establish a set of consistent KPIs that are used to objectively track progress. While these need to be a part of each board package, it is even more important for the executive team to utilize this for managing their company. While this post focuses on SaaS/Subscription companies, the majority of it applies to most other types of businesses.
Areas KPIs Should Cover
MRR (Monthly Recurring Revenue) and LTR (Lifetime Revenue)
CAC (Cost of Customer Acquisition)
Marketing to create leads
Customers acquired electronically
Customers acquired using sales professionals
Gross Margin and LTV (Life Time Value of a customer)
Many companies will also need KPIs regarding inventory in addition to the ones above.
While there may be very complex analysis behind some of these numbers, it’s important to try to keep KPIs to 2-5 pages of a board package. Use of the right KPIs will give a solid, objective, consistent top-down view of the company’s progress. The P&L portion of the package is obviously critical, but I have a possibly unique view on how this should be included in the body of a board package.
P&L Trends: Less is More
One mistake many companies make is confusing detail with better analysis. I often see models that have 50-100 line items for expenses and show this by month for 3 or more years out… but show one or no years of history. What this does is waste a great deal of time on predicting things that are inconsequential and controllable (by month), while eliminating all perspective. Things like seasonality are lost if one is unable to view 3 years of revenue at a time without scrolling from page to page. Of course, for the current year’s budget it is appropriate for management to establish monthly expectations in detail, but for any long-term planning, success revolves around revenue, gross margins, marketing/sales spend and the number of employees. For some companies that are deep technology players there may be significant costs in R&D other than payroll, but this is the exception. By using a simple formula for G&A based on the number of employees, the board can apply a sanity check on whether cost estimates in the long-term model will be on target assuming revenue is on target. So why spend excessive time on nits? Aggregating cost frees up time for better understanding how and why revenue will ramp, the relationship between revenue types and gross margin, the cost of acquiring a customer, the lifetime value of a customer and the average spend per employee.
In a similar way, the board is well served by viewing a simple P&L by quarter for 2 prior years plus the current one (with a forecast of remaining quarters). The lines could be:
Table1: P&L by Quarter
A second version of the P&L should be produced for budget comparison purposes. It should have the same rows but have the columns be current period actual, current period budget, year to date (YTD) actual, year to date budget, current full year forecast, budget for the full year.
Table 2: P&L Actual / Budget Comparison
Tracking MRR and LTR
For any SaaS/Subscription company (I’ll simply refer to this as SaaS going forward) MRR growth is the lifeblood of the company with two caveats: excessive churn makes MRR less valuable and excessive cost in growing MRR also leads to deceptive prosperity. More about that further on. MRR should be viewed on a rolling basis. It can be done by quarter for the board but by month for the management team. Doing it by quarter for the board enables seeing a 3-year trend on one page and gives the board sufficient perspective for oversight. Management needs to track this monthly to better manage the business. A relatively simple set of KPIs for each of 12 quarterly periods would be:
Table 3: MRR and Retention
Calculating Life Time Revenue through Cohort Analysis
The detailed method of calculating LTR does not need to be shown in every board package but should be included at least once per year, but calculated monthly for management.
The LTR calculation uses a grid where the columns would be the various Quarterly cohorts, that is all customers that first purchased that quarter (management might also do this using monthly instead of quarterly). This analysis can be applied to non-SaaS companies as well as SaaS entities. The first row would be the number of customers in the cohort. The next row would be the first month’s revenue for the cohort, the next the second months revenue, and so on until reaching 36 months (or whatever number the board prefers for B2B…I prefer 60 months). The next row would be the total for the full period and the final row would be the average Lifetime Revenue, LTR, per member of the cohort.
Table 4: Customer Lifetime Revenue
A second table would replicate the grid but show average per member of the cohort for each month (row). That table allows comparisons of cohorts to see if the average revenue of a newer cohort is getting better or worse than older ones for month 2 or month 6 or month 36, etc.
Table 5: Average Revenue per Cohort
Cohorts that have a full 36 months of data need to be at least 36 months old. What this means is that more recent cohorts will not have a full set of information but still can be used to see what trends have occurred. For example, is the second months average revenue for a current cohort much less than it was for a cohort one year ago? While newer cohorts do not have full sets of monthly revenue data, they still are very relevant in calculating more recent LTR. This can be done by using average monthly declines in sequential months and applying them to cohorts with fewer months of data.
Customer Acquisition Cost (CAC)
Calculating CAC is done in a variety of ways and is quite different for customers acquired electronically versus those obtained by a sales force. Many companies I’ve seen have a combination of the two.
Marketing used to generate leads should always be considered part of CAC. The marketing cost in a month first is divided by the number of leads to generate a cost/lead. The next step is to estimate the conversion rate of leads to customers. A simple table would be as follows:
Table 6: Customer Acquisition Costs
For an eCommerce company, the additional cost to convert might be one free month of product or a heavily subsidized price for the first month. If the customer is getting the item before becoming a regular paying customer than the CAC would be:
CAC = MCTC / the percent that converts from the promotional trial to a paying customer.
CAC when a Sales Force is Involved
For many eCommerce companies and B2B companies that sell electronically, marketing is the primary cost involved in acquiring a paying customer. For those utilizing a sales force, the marketing expense plus the sales expense must be accumulated to determine CAC.
Typically, what this means is steps 1 through 3 above would still be used to determine CPL, but step 1 above might include marketing personnel used to generate leads plus external marketing spend:
CPL (cost per lead) as above
Sales Cost = current month’s cost of the sales force including T&E
New Customers in the month = NC
Conversion Rate to Customer = NC/number of leads= Y%
CAC = CPL/Y% + (Sales Cost)/NC
There are many nuances ignored in the simple method shown. For example, some leads may take many months to close. Some may go through a pilot before closing. Therefore, there are more sophisticated methods of calculating CAC but using this method would begin the process of understanding an important indicator of efficiency of customer acquisition.
Gross Margin (GM) is a Critical Part of the Equation
While revenue is obviously an important measure of success, not all revenue is the same. Revenue that generates 90% gross margin is a lot more valuable per dollar than revenue that generates 15% gross margin. When measuring a company’s potential for future success it’s important to understand what level of revenue is required to reach profitability. A first step is understanding how gross margin may evolve. When a business scales there are many opportunities to improve margins:
Larger volumes may lead to larger discounts from suppliers
Larger volumes for products that are software/content may lower the hosting cost as a percent of revenue
Shipping to a larger number of customers may allow opening additional distribution centers (DCs) to facilitate serving customers from a DC closer to their location lowering shipping cost
Larger volumes may mean improved efficiency in the warehouse. For example, it may make more automation cost effective
When forecasting gross margin, it is important to be cautious in predicting some of these savings. The board should question radical changes in GM in the forecast. Certain efficiencies should be seen in a quarterly trend, and a marked improvement from the trend needs to be justified. The more significant jump in GM from a second DC can be calculated by looking at the change in shipping rates for customers that will be serviced from the new DC vs what rates are for these customers from the existing one.
Calculating LTV (Lifetime Value)
Gross Margin, by itself may be off as a measure of variable profits of a customer. If payment is by credit card, then the credit card cost per customer is part of variable costs. Some companies do not include shipping charges as part of cost of goods, but they should always be part of variable cost. Customer service cost is typically another cost that rises in proportion to the number of customers. So:
Variable cost = Cost of Goods sold plus any cost that varies directly with sales
The calculation of VP% should be based on current numbers as they will apply going forward. Determining a company’s marketing efficiency requires comparing LTV to the cost of customer acquisition. As mentioned earlier in the post, if the CAC is too large a proportion of LTV, a company may be showing deceptive (profitless) growth. So, the next set of KPIs address marketing efficiency.
It does not make sense to invest in an inefficient company as they will burn through capital at a rapid rate and will find it difficult to become profitable. A key measure of efficiency is the relationship between LTV and CAC or LTV/CAC. Essentially this is how many dollars of variable profit the company will make for every dollar it spends on marketing and sales. A ratio of 5 or more usually means the company is efficient. The period used for calculating LTR will influence this number. Since churn tends to be much lower for B2B companies, 5 years is often used to calculate LTR and LTV. But, using 5 years means waiting longer to receive resulting profits and can obscure cash flow implications of slower recovery of CAC. So, a second metric important to understand burn is how long it takes to recover CAC:
CAC Recovery Time = number of months until variable profit equals the CAC
The longer the CAC recovery time, the more capital required to finance growth. Of course, existing customers are also contributing to the month’s revenue alongside new customers. So, another interesting KPI is contribution margin which measures the current state of balance between marketing/sales and Variable Profits:
Contribution Margin = Variable Profits – Sales and Marketing Cost
Early on this number will be negative as there aren’t enough older customers to cover the investment in new ones. But eventually the contribution margin in a month needs to turn positive. To reach profitability it needs to exceed all other costs of the business (G&A, R&D, etc.). By reducing a month’s marketing cost, a company can improve contribution margin that month at the expense of sequential growth… which is why this is a balancing act.
I realize this post is long but wanted to include a substantial portion of KPIs in one post. However, I’ll leave more detailed measurement of sales force productivity and deeper analysis of several of the KPIs discussed here for one or more future posts.
I’ll begin by apologizing for a midyear brag, but I always tell others to enjoy success and therefore am about to do that myself. In my top ten predictions for 2018 I included a market prediction and 4 stock predictions. I was feeling pretty good that they were all working well when I started to create this post. However, the stock prices for high growth stocks can experience serious shifts in very short periods. Facebook and Tesla both had (what I consider) minor shortfalls against expectations in the 10 days since and have subsequently declined quite a bit in that period. But given the strength of my other two recommendations, Amazon and Stitchfix, the four still have an average gain of 15% as of July 27. Since I’ve only felt comfortable predicting the market when it was easy (after 9/11 and after the 2008 mortgage blowup), I was nervous about predicting the S&P would be up this year as it was a closer call and was somewhat controversial given the length of the bull market prior to this year. But it seemed obvious that the new tax law would be very positive for corporate earnings. So, I thought the S&P would be up despite the likelihood of rising interest rates. So far, it is ahead 4.4% year to date driven by stronger earnings. Since I always fear that my record of annual wins can’t continue I wanted to take a midyear victory lap just in case everything collapses in the second half of the year (which I don’t expect but always fear). So I continue to hold all 4 stocks and in fact bought a bit more Facebook today.
Applying the Gross Margin Multiple Method to Public Company Valuation
In my last two posts I’ve laid out a method to value companies not yet at their mature business models. The method provides a way to value unprofitable growth companies and those that are profitable but not yet at what could be their mature business model. This often occurs when a company is heavily investing in growth at the expense of near-term profits. In the last post, I showed how I would estimate what I believed the long-term model would be for Tesla, calling the result “Potential Earnings” or “PE”. Since this method requires multiple assumptions, some of which might not find agreement among investors, I provided a second, simplified method that only involved gross margin and revenue growth.
The first step was taking about 20 public companies and calculating how they were valued as a multiple of gross margin (GM) dollars. The second step was to determine a “least square line” and formula based on revenue growth and the gross margin multiple for these companies. The coefficient of 0.62 shows that there is a good correlation between Gross Margin and Revenue Growth, and one significantly better than the one between Revenue Growth and a company’s Revenue Multiple (that had a coefficient of 0.36 which is considered very modest).
Where’s the Beef?
The least square formula derived in my post for relating revenue growth to an implied multiple of Gross Margin dollars is:
GM Multiple = (24.773 x Revenue growth percent) + 4.1083
Implied Company Market Value = GM Multiple x GM Dollars
Now comes the controversial part. I am going to apply this formula to 10 companies using their data (with small adjustments) and compare the Implied Market Value (Implied MKT Cap) to their existing market Cap as of several days ago. I’ll than calculate the Implied Over (under) Valuation based on the comparison. If the two values are within 20% I view it as normal statistical variation.
Table 1: Valuation Analysis of 10 Tech Companies
* Includes net cash included in expected market cap
** Uses adjusted GM%
*** Uses 1/31/18 year end
**** Growth rate used in the model is q4 2017 vs q4 2016. See text
This method suggests that 5 companies are over-valued by 100% or more and a fifth, Workday, by 25%. Since Workday is close to a normal variation, I won’t discuss it further. I have added net cash for Facebook, Snap, Workday and Twitter to the implied market cap as it was material in each case but did not do so for the six others as the impact was not as material.
I decided to include the four companies I recommended, in this year’s top ten list, Amazon, Facebook, Tesla and Stitchfix, in the analysis. To my relief, they all show as under-valued with Stitchfix, (the only one below the Jan 2 price) having an implied valuation more than 100% above where it currently trades. The other three are up year to date, and while trading below what is suggested by this method, are within a normal range. For additional discussion of these four see our 2018 top Ten List.
Digging into the “Overvalued” Five
Why is there such a large discrepancy between actual market cap and that implied by this method for 5 companies? There are three possibilities:
The method is inaccurate
The method is a valid screen but I’m missing some adjustment for these companies
The companies are over-valued and at some point, will adjust, making them risky investments
While the method is a good screen on valuation, it can be off for any given company for three reasons: the revenue growth rate I’m using will radically change; a particular company has an ability to dramatically increase gross margins, and/or a particular company can generate much higher profit margins than their gross margin suggests. Each of these may be reflected in the company’s actual valuation but isn’t captured by this method.
To help understand what might make the stock attractive to an advocate, I’ll go into a lot of detail in analyzing Snap. Since similar arguments apply to the other 4, I’ll go into less detail for each but still point out what is implicit in their valuations.
Snap’s gross margin (GM) is well below its peers and hurts its potential profitability and implied valuation. Last year, GM was about 15%, excluding depreciation and amortization, but it was much higher in the seasonally strong Q4. It’s most direct competitor, Facebook, has a gross margin of 87%. The difference is that Facebook monetizes its users at a much higher level and has invested billions of dollars and executed quite well in creating its own low-cost infrastructure, while Snap has outsourced its backend to cloud providers Google and Amazon. Snap has recently signed 5-year contracts with each of them to extend the relationships. Committing to lengthy contracts will likely lower the cost of goods sold. Additionally, increasing revenue per user should also improve GM. But, continuing to outsource puts a cap on how high margins can reach. Using our model, Snap would need 79% gross margin to justify its current valuation. If I assume that scale and the longer-term contracts will enable Snap to double its gross margins to 30%, the model still shows it as being over-valued by 128% (as opposed to the 276% shown in our table). The other reason bulls on Snap may justify its high valuation is that they expect it to continue to grow revenue at 100% or more in 2018 and beyond. What is built into most forecasts is an assumed decline in revenue growth rates over time… as that is what typically occurs. The model shows that growing revenue 100% a year for two more years without burning cash would leave it only 32% over-valued in 2 years. But as a company scales, keeping revenue growth at that high a level is a daunting task. In fact, Snap already saw revenue growth decline to 75% in Q4 of 2017.
Twitter is not profitable. Revenue declined in 2017 after growing a modest 15% in 2016, and yet it trades at a valuation that implies that it is a growth company of about 50%. While it has achieved such levels in the past, it may be difficult to even get back to 15% growth in the future given increased competition for advertising.
I recommended Netflix in January 2015 as one of my stock picks for the year, and it proved a strong recommendation as the stock went up about 140% that year. However, between January 2015 and January 2018, the stock was up over 550% while trailing revenue only increased 112%. I continue to like the fundamentals of Netflix, but my GM model indicates that the stock may have gotten ahead of itself by a fair amount, and it is unlikely to dramatically increase revenue growth rates from last year’s 32%.
Square has followed what I believe to be the average pattern of revenue growth rate decline as it went from 49% growth in 2015, down to 35% growth in 2016, to under 30% growth in 2017. There is no reason to think this will radically change, but the stock is trading as if its revenue is expected to grow at a nearly 90% rate. On the GM side, Square has been improving GM each year and advocates will point out that it could go higher than the 38% it was in 2017. But, even if I use 45% for GM, assuming it can reach that, the model still implies it is 90% over-valued.
I don’t want to beat up on a struggling Blue Apron and thought it might have reached its nadir, but the model still implies it is considerably over-valued. One problem that the company is facing is that investors are negative when a company has slow growth and keeps losing money. Such companies find it difficult to raise additional capital. So, before running out of cash, Blue Apron began cutting expenses to try to reach profitability. Unfortunately, given their customer churn, cutting marketing spend resulted in shrinking revenue in each sequential quarter of 2017. In Q4 the burn was down to $30 million but the company was now at a 13% decline in revenue versus Q4 of 2016 (which is what we used in our model). I assume the solution probably needs to be a sale of the company. There could be buyers who would like to acquire the customer base, supplier relationships and Blue Apron’s understanding of process. But given that it has very thin technology, considerable churn and strong competition, I’m not sure if a buyer would be willing to pay a substantial premium to its market cap.
An Alternative Theory on the Over Valued Five
I have to emphasize that I am no longer a Wall Street analyst and don’t have detailed knowledge of the companies discussed in this post, so I easily could be missing some important factors that drive their valuation. However, if the GM multiple model is an accurate way of determining valuation, then why are they trading at such lofty premiums to implied value? One very noticeable common characteristic of all 5 companies in question is that they are well known brands used by millions (or even tens of millions) of people. Years ago, one of the most successful fund managers ever wrote a book where he told readers to rely on their judgement of what products they thought were great in deciding what stocks to own. I believe there is some large subset of personal and professional investors who do exactly that. So, the stories go:
“The younger generation is using Snap instead of Facebook and my son or daughter loves it”
“I use Twitter every day and really depend on it”
“Netflix is my go-to provider for video content and I’m even thinking of getting rid of my cable subscription”
Once investors substitute such inclinations for hard analysis, valuations can vary widely from those suggested by analytics. I’m not saying that such thoughts can’t prove correct, but I believe that investors need to be very wary of relying on such intuition in the face of evidence that contradicts it.
This post is part 2 of our valuation discussion (see this post for part 1). As I write this post Tesla’s market cap is about $56 billion. I thought it would be interesting to show how the rules discussed in the first post apply to Tesla, and then to take it a step further for startups.
Revenue and Revenue Growth
Revenue for Tesla in 2017 was $11.8 billion, about 68% higher than 2016, and it is likely to grow faster this year given the over $20 billion in pre-orders (and growing) for the model 3 coupled with continued strong demand for the model S and model X. Since it is unclear when the new sports car or truck will ship, I assume no revenue in those categories. As long as Tesla can increase production at the pace they expect, I estimate 2018 revenue will be up 80% – 120% over 2017, with Q4 year over year growth at or above 120%.
If I’m correct on Tesla revenue growth, its 2018 revenue will exceed $20 billion. So, Rule Number 1 from the prior post indicates that Tesla’s high growth rates should merit a higher “theoretical PE” than the S&P (by at least 4X if one believes that growth will continue at elevated rates).
Tesla gross margins have varied a bit while ramping production for each new model, but in the 16 quarters from Q1, 2014 to Q4, 2017 gross margin averaged 23% and was above 25%, 6 of the 16 quarters. Given that Tesla is still a relatively young company it appears likely margins will increase with scale, leading me to believe that long term gross margins are very likely to be above 25%. While it will dip during the early production ramp of the model 3, 25% seems like the lowest percent to use for long term modeling and I expect it to rise to between 27% and 30% with higher production volumes and newer factory technology.
Tesla recognizes substantial cost based on stock-based compensation (which partly occurs due to the steep rise in the stock). Most professional investors ignore artificial expenses like stock-based compensation, as I will for modeling purposes, and refer to the actual cost as net SG&A and net R&D. Given that Tesla does not pay commissions and has increased its sales footprint substantially in advance of the roll-out of the model 3, I believe Net SG&A and Net R&D will each increase at a much slower pace than revenue. If they each rise 20% by Q4 of this year and revenue is at or exceeds $20 billion, this would put their total at below 20% of revenue by Q4. Since they should decline further as a percent of revenue as the company matures, I am assuming 27% gross margin and 18% operating cost as the base case for long term operating profit. While this gross margin level is well above traditional auto manufacturers, it seems in line as Tesla does not have independent dealerships (who buy vehicles at a discount) and does not discount its cars at the end of each model year.
Table 1 provides the above as the base case for long term operating profit. To provide perspective on the Tesla opportunity, Table 1 also shows a low-end case (25% GM and 20% operating cost) and a high-end profit case (30% GM and 16% operating cost). Recall, theoretic earnings are derived from applying the mature operating profit level to trailing and to forward revenue. For calculating theoretic earnings, I will ignore interest payments and net tax loss carry forwards as they appear to be a wash over the next 5 years. Finally, to derive the Theoretic Net Earnings Percent a potential mature tax rate needs to be applied. I am using 20% for each model case which gives little credit for tax optimization techniques that could be deployed. That would make theoretic earnings for 2017 and 2018 $0.85 billion and $1.51 billion, respectively and leads to:
2017 TPE=$ 56.1 billion/$0.85 = 66.0
2018 TPE= $ 56.1 billion/1.51 = 37.1
The S&P trailing P/E is 25.5 and forward P/E is about 19X. Based on our analysis of the correlation between growth and P/E provided in the prior post, Tesla should be trading at a minimum of 4X the trailing S&P ratio (or 102 TP/E) and at least 3.5X S&P forward P/E (or 66.5 TP/E). To me that shows that the current valuation of Tesla does not appear out of market. If the market stays at current P/E levels and Tesla reaches $21B in revenue in 2018 this indicates that there is strong upside for the stock.
Table 1: Tesla TPE 2017 & 2018
The question is whether Tesla can continue to grow revenue at high rates for several years. Currently Tesla has about 2.4% share of the luxury car market giving it ample room to grow that share. At the same time, it is entering the much larger medium-priced market with the launch of the Model 3 and expects to produce vehicles in other categories over the next few years. Worldwide sales of new cars for the auto market is about 90 million in 2017 and growing about 5% a year. Tesla is the leader in several forward trends: electric vehicles, automated vehicles and technology within a car. Plus, it has a superior business model as well. If it reaches $21 billion in revenue in 2018, its share of the worldwide market would be about 0.3%. It appears poised to continue to gain share over the next 3-5 years, especially as it fills out its line of product. Given that it has achieved a 2.4% share of the market it currently plays in, one could speculate that it could get to a similar share in other categories. Even achieving a 1% share of the worldwide market in 5 years would mean about 40% compound growth between 2018 and 2022 and imply a 75X-90X TP/E at the end of this year.
The Bear Case
I would be remiss if I omitted the risks that those negative on the stock point out. Tesla is a very controversial stock for a variety of reasons:
Gross Margin has been volatile as it adds new production facilities so ‘Bears’ argue that even my 25% low case is optimistic, especially as tax rebate subsidies go away
It has consistently lost money so some say it will never reach the mature case I have outlined
As others produce better electric cars Tesla’s market share of electric vehicles will decline so high revenue growth is not sustainable
Companies like Google have better automated technology that they will license to other manufacturers leading to a leap frog of Tesla
As they say, “beauty is in the eyes of the beholder” and I believe my base case is realistic…but not without risk. In response to the bear case that Tesla revenue growth can’t continue, it is important to recognize that Tesla already has the backlog and order momentum to drive very high growth for the next two years. Past that, growing market share over the 4 subsequent years to 1% (a fraction of their current share of the luxury market) would generate compound annual growth of 40% for that 4-year period. In my opinion, the biggest risk is Tesla’s own execution in ramping production. Bears will also argue that Tesla will never reach the operating margins of my base case for a variety of reasons. This is the weakness of the TPE approach: it depends on assumptions that have yet to be proven. I’m comfortable when my assumptions depend on momentum that is already there, gross margin proof points and likelihood that scale will drive operating margin improvements without any radical change to the business model.
Applying the rules to Startups
As a VC I am often in the position of helping advise companies regarding valuation. This occurs when they are negotiating a round of financing or in an M&A situation. Because the companies are even earlier than Tesla, theoretic earnings are a bit more difficult to establish. Some investors ignore the growth rates of companies and look for comps in the same business. The problem with the comparable approach is that by selecting companies in the same business, the comps are often very slow growth companies that do not merit a high multiple. For example, comparing Tesla to GM or Ford to me seems a bit ludicrous when Tesla’s revenue grew 68% last year and is expected to grow even faster this year while Ford and GM are growing their revenue at rates below 5%. It would be similar if investors compared Apple (in the early days of the iPhone) to Nokia, a company it was obsoleting.
Investors look for proxies to use that best correlate to what future earnings will be and often settle on a multiple of revenue. As Table 2 shows, there is a correlation between valuation as a multiple of revenue and revenue growth regardless of what industry the companies are in. This correlation is closer than one would find by comparing high growth companies to their older industry peers.
Table 2: Multiple of Revenue and Revenue Growth
However, using revenue as the proxy for future earnings suffers from a wide variety of issues. Some companies have 90% or greater gross margins like our portfolio company Education.com, while others have very low gross margins of 10% – 20%, like Spotify. It is very likely that the former will generate much higher earnings as a percent of revenue than the latter. In fact, Education.com is already cash flow positive at a relatively modest revenue level (in the low double-digit millions) while Spotify continues to lose a considerable amount of money at billions of dollars in revenue. Notice, this method also implies that Tesla should be valued about 60% higher than its current market price.
This leads me to believe a better proxy for earnings is gross margin as it is more closely correlated with earnings levels. It also removes the issue of how revenue is recognized and is much easier to analyze than TPE. For example, Uber recognizing gross revenue or net revenue has no impact on gross margin dollars but would radically change its price to revenue. Table 3 uses the same companies as Table 2 but shows their multiple of gross margin dollars relative to revenue growth. Looking at the two graphs, one can see how much more closely this correlates to the valuation of public companies. The correlation coefficient improves from 0.36 for the revenue multiple to 0.62 for the gross margin multiple.
Table 3: Multiple of Gross Margin vs. Revenue Growth
So, when evaluating a round of financing for a pre-profit company the gross margin multiple as it relates to growth should be considered. For example, while there are many other factors to consider, the formula implies that a 40% revenue growth company should have a valuation of about 14X trailing gross margin dollars. Typically, I would expect that an earlier stage company’s mature gross margin percent would likely increase. But they also should receive some discount from this analysis as its risk profile is higher than the public companies shown here.
Notice that the price to sales graph indicates Tesla should be selling at 60% more than its multiple of 5X revenue. On the other hand, our low-end case for Tesla Gross Margin, 25%, puts Tesla at 20X Gross Margin dollars, just slightly undervalued based on where the least square line in Table 3 indicates it should be valued.
After many years of successfully picking public and private companies to invest in, I thought I’d share some of the core fundamentals I use to think about how a company should be valued. Let me start by saying numerous companies defy the logic that I will lay out in this post, often for good reasons, sometimes for poor ones. However, eventually most companies will likely approach this method, so it should at least be used as a sanity check against valuations.
When a company is young, it may not have any earnings at all, or it may be at an earnings level (relative to revenue) that is expected to rise. In this post, I’ll start by considering more mature companies that are approaching their long-term model for earnings to establish a framework, before addressing how this framework applies to less mature companies. The post will be followed by another one where I apply the rules to Tesla and discuss how it carries over into private companies.
Growth and Earnings are the Starting Points for Valuing Mature Companies
When a company is public, the most frequently cited metric for valuation is its price to earnings ratio (PE). This may be done based on either a trailing 12 months or a forward 12 months. In classic finance theory a company should be valued based on the present value of future cash flows. What this leads to is our first rule:
Rule 1: Higher Growth Rates should result in a higher PE ratio.
When I was on Wall Street, I studied hundreds of growth companies (this analysis does not apply to cyclical companies) over the prior 10-year period and found that there was a very strong correlation between a given year’s revenue growth rate and the next year’s revenue growth rate. While the growth rate usually declined year over year if it was over 10%, on average this decline was less than 20% of the prior year’s growth rate. What this means is that if we took a group of companies with a revenue growth rate of 40% this year, the average organic growth for the group would likely be about 33%-38% the next year. Of course, things like recessions, major new product releases, tax changes, and more could impact this, but over a lengthy period of time this tended to be a good sanity test. As of January 2, 2018, the average S&P company had a PE ratio of 25 on trailing earnings and was growing revenue at 5% per year. Rule 1 implies that companies growing faster should have higher PEs and those growing slower, lower PEs than the average.
Graph 1: Growth Rates vs. Price Earnings Ratios
The graph shows the correlation between growth and PE based on the valuations of 21 public companies. Based on Rule 1, those above the line may be relatively under-priced and those below relatively over-priced. I say ‘may be’ as there are many other factors to consider, and the above is only one of several ways to value companies. Notice that most of the theoretically over-priced companies with growth rates of under 5% are traditional companies that have long histories of success and pay a dividend. What may be the case is that it takes several years for the market to adjust to their changed circumstances or they may be valued based on the return from the dividend. For example, is Coca Cola trading on: past glory, its 3.5% dividend, or is there something about current earnings that is deceptive (revenue growth has been a problem for several years as people switch from soda to healthier drinks)? I am not up to speed enough to know the answer. Those above the line may be buys despite appearing to be highly valued by other measures.
Relatively early in my career (in 1993-1995) I applied this theory to make one of my best calls on Wall Street: “Buy Dell sell Kellogg”. At the time Dell was growing revenue over 50% per year and Kellogg was struggling to grow it over 4% annually (its compounded growth from 1992 to 1995, this was partly based on price increases). Yet Dell’s PE was about half that of Kellogg and well below the S&P average. So, the call, while radical at the time, was an obvious consequence of Rule 1. Fortunately for me, Dell’s stock appreciated over 65X from January 1993 to January 2000 (and well over 100X while I had it as a top pick) while Kellogg, despite large appreciation in the overall stock market, saw its stock decline slightly over the same 7-year period (but holders did receive annual dividends).
Rule 2: Predictability of Revenue and Earnings Growth should drive a higher trailing PE
Investors place a great deal of value on predictability of growth and earnings, which is why companies with subscription/SaaS models tend to get higher multiples than those with regular sales models. It is also why companies with large sales backlogs usually get additional value. In both cases, investors can more readily value the companies on forward earnings since they are more predictable.
Rule 3: Market Opportunity should impact the Valuation of Emerging Leaders
When one considers why high growth rates might persist, the size of the market opportunity should be viewed as a major factor. The trick here is to make sure the market being considered is really the appropriate one for that company. In the early 1990s, Dell had a relatively small share of a rapidly growing PC market. Given its competitive advantages, I expected Dell to gain share in this mushrooming market. At the same time, Kellogg had a stable share of a relatively flat cereal market, hardly a formula for growth. In recent times, I have consistently recommended Facebook in this blog for the very same reasons I had recommended Dell: in 2013, Facebook had a modest share of the online advertising, a market expected to grow rapidly. Given the advantages Facebook had (and they were apparent as I saw every Azure ecommerce portfolio company moving a large portion of marketing spend to Facebook), it was relatively easy for me to realize that Facebook would rapidly gain share. During the time I’ve owned it and recommended it, this has worked out well as the share price is up over 8X.
How the rules can be applied to companies that are pre-profit
As a VC, it is important to evaluate what companies should be valued at well before they are profitable. While this is nearly impossible to do when we first invest (and won’t be covered in this post), it is feasible to get a realistic range when an offer comes in to acquire a portfolio company that has started to mature. Since they are not profitable, how can I apply a PE ratio?
What needs to be done is to try to forecast eventual profitability when the company matures. A first step is to see where current gross margins are and to understand whether they can realistically increase. The word realistic is the key one here. For example, if a young ecommerce company currently has one distribution center on the west coast, like our portfolio company Le Tote, the impact on shipping costs of adding a second eastern distribution center can be modeled based on current customer locations and known shipping rates from each distribution center. Such modeling, in the case of Le Tote, shows that gross margins will increase 5%-7% once the second distribution center is fully functional. On the other hand, a company that builds revenue city by city, like food service providers, may have little opportunity to save on shipping.
Calculating variable Profit Margin
Once the forecast range for “mature” gross margin is estimated, the next step is to identify other costs that will increase in some proportion to revenue. For example, if a company is an ecommerce company that acquires most of its new customers through Facebook, Google and other advertising and has high churn, the spend on customer acquisition may continue to increase in direct proportion to revenue. Similarly, if customer service needs to be labor intensive, this can also be a variable cost. So, the next step in the process is to access where one expects the “variable profit margin” to wind up. While I don’t know the company well, this appears to be a significant issue for Blue Apron: marketing and cost of goods add up to about 90% of revenue. I suspect that customer support probably eats up (no pun intended) 5-10% of what is left, putting variable margins very close to zero. If I assume that the company can eventually generate 10% variable profit margin (which is giving it credit for strong execution), it would need to reach about $4 billion in annual revenue to reach break-even if other costs (product, technology and G&A) do not increase. That means increasing revenue nearly 5-fold. At their current YTD growth rate this would take 9 years and explains why the stock has a low valuation.
Estimating Long Term Net Margin
Once the variable profit margin is determined, the next step would be to estimate what the long-term ratio of all other operating cost might be as a percent of revenue. Using this estimate I can determine a Theoretic Net Earnings Percent. Applying this percent to current (or next years) revenue yields a Theoretic Earnings and a Theoretic PE (TPE):
TPE= Market Cap/Theoretic Earnings
To give you a sense of how I successfully use this, review my recap of the Top Ten Predictions from 2017 where I correctly predicted that Spotify would not go public last year despite strong top line growth as it was hard to see how its business model could support more than 2% or so positive operating margin, and that required renegotiating royalty deals with record labels. Now that Spotify has successfully negotiated a 3% lower royalty rate from several of the labels, it appears that the 16% gross margins in 2016 could rise to 19% or more by the end of 2018. This means that variable margins (after marketing cost) might be 6%. This would narrow its losses, but still means it might be several years before the company achieves the 2% operating margins discussed in that post. As a result, Spotify appears headed for a non-traditional IPO, clearly fearing that portfolio managers would not be likely to value it at its private valuation price since that would lead to a TPE of over 200. Since Spotify is loved by many consumers, individuals might be willing to overpay relative to my valuation analysis.
Our next post will pick up this theme by walking through why this leads me to believe Tesla continues to have upside, and then discussing how entrepreneurs should view exit opportunities.
I’ve often written about effective shooting percentage relative to Stephen Curry, and once again he leads the league among players who average 15 points or more per game. What also accounts for the Warriors success is the effective shooting of Klay Thompson, who is 3rd in the league, and Kevin Durant who is 6th. Not surprisingly, Lebron is also in the top 10 (4th). The table below shows the top ten among players averaging 15 points or more per game. Of the top ten scorers in the league, 6 are among the top 10 effective shooters with James Harden only slightly behind at 54.8%. The remaining 3 are Cousins (53.0%), Lillard (52.2%), and Westbrook, the only one below the league average of 52.1% at 47.4%.
Table: Top Ten Effective Shooters in the League
*Note: Bolded players denote those in the top 10 in Points per Game