Why Contribution Margin is a Strong Predictor of Success for Companies

In the last post I concluded with a brief discussion of Contribution Margin as a key KPI. Recall:

Contribution Margin = Variable Profits – Sales and Marketing Cost

The higher the contribution margin, the more dollars available towards covering G&A. Once contribution margin exceeds G&A, a company reaches operating profits. For simplicity in this post, I’ll use gross margin (GM) as the definition of variable profits even though there may be other costs that vary directly with revenue.

The Drivers of Contribution Margin (CM)

There is an absolute correlation between GM percent and CM. Very high gross margin companies will, in general, get to strong contribution margins and low gross margin companies will struggle to get there. But the sales and marketing needed to drive growth is just as important. There are several underlying factors in how much needs to be spent on sales and marketing to drive growth:

  1. The profits on a new customer relative to the cost of acquiring her (or him). That is, the CAC (customer acquisition cost) for customers derived from paid advertising compared to the profits on those customers’ first purchase
  2. The portion of new traffic that is “free” from SEO (search engine optimization), PR, existing customers recommending your products, etc.
  3. The portion of revenue that comes from repeat customers

The Relationship Between CAC and First Purchase Profits Has a Dramatic Impact on CM

Suppose Company A spends $60 to acquire a customer and has GM of $90 on the initial purchase by that customer. The contribution margin will already be positive $30 without accounting for customers that are organic or those that are repeat customers; in other words, this tends to be extremely positive! Of course, the startups I see in eCommerce are rarely in this situation but those that are can get to profitability fairly quickly if this relationship holds as they scale.

It would be more typical for companies to find that the initial purchase GM only covers a portion of CAC but that subsequent purchases lead to a positive relationship between the LTV (life time value) of the customer and CAC. If I assume the spend to acquire a customer is $60 and the GM is $30 then the CM on the first purchase would be negative (-$30), and it would take a second purchase with the same GM dollars to cover that initial cost. Most startups require several purchases before recovering CAC which in turn means requiring investment dollars to cover the outlay.

Free Traffic and Contribution Margin

If a company can generate a high proportion of free/organic traffic, there is a benefit to contribution margin. CAC is defined as the marketing spend divided by the number of new customers derived from this spend. Blended CAC is defined as the marketing spend divided by all customers who purchased in the period. The more organically generated and return customers, the lower the “blended CAC”. Using the above example, suppose 50% of the new customers for Company A come from organic (free) traffic. Then the “blended CAC“ would be 50% of the paid CAC. In the above example that would be $30 instead of $60 and if the GM was only $30 the initial purchase would cover blended CAC.

Of course, in addition to obtaining customers for free from organic traffic, companies, as they build their customer base, have an increasing opportunity to obtain free traffic by getting existing customers to buy again. So, a company should never forget that maintaining a persistent relationship with customers leads to improved Contribution Margin.

Spending to Drive Higher Growth Can Mean Lower Contribution Margin

Unless the GM on the first purchase a new customer makes exceeds their CAC, there is an inverse relationship between expanding growth and achieving high contribution margin. Think of it this way: suppose that going into a month the likely organic traffic and repeat buyers are somewhat set. Boosting that month’s growth means increasing the number of new paid customers, which in turn makes paid customers a higher proportion of blended CAC and therefore increases CAC. For an example consider the following assumptions for Company B:

  • The GM is $60 on an average order of $100
  • Paid CAC is $150
  • The company will have 1,000 new customers through organic means and 2,000 repeat buyers or $300,000 in revenue with 60% GM ($180,000) from these customers before spending on paid customers
  • G&A besides marketing for the month will be $150,000
  • Last year Company B had $400,000 in revenue in the same month
  • The company is considering the ramifications of targeting 25%, 50% or 100% year-over-year growth

Table 1: The Relationship Between Contribution Margin & Growth

Since the paid CAC is $150 while Gross Margin is only $60 per new customer, each acquired customer generates negative $90 in contribution margin in the period. As can be seen in Table 1, the company would shrink 25% if there is no acquisition spend but would have $180,000 in contribution margin and positive operating profit. On the other end of the spectrum, driving 100% growth requires spending $750,000 to acquire 5,000 new customers and results in a negative $270,000 in contribution margin and an Operating Loss of $420,000 in the period. Of course, if new customers are expected to make multiple future purchases than the number of repeat customers would rise in future periods.

Subscription Models Create More Consistency but are not a Panacea

When a company’s customers are monthly subscribers, each month starts with the prior month’s base less churn. To put it another way, if churn from the prior month is modest (for example 5%) then that month already has 95% of the prior months revenue from repeat customers. Additionally, if the company increases the average invoice value from these customers, it might even have a starting point where return customers account for as much revenue as the prior month. For B-to-B companies, high revenue retention is the norm, where an average customer will pay them for 10 years or more.

Consumer ecommerce subscriptions typically have much more substantial churn, with an average life of two years being closer to the norm. Additionally, the highest level of churn (which can be as much as 30% or more) occurs in the second month, and the next highest, the third month before tapering off. What this means is that companies trying to drive high sequential growth will have a higher % churn rate than those that target more modest growth. Part of a company’s acquisition spend is needed just to stay even. For example, if we assume all new customers come from paid acquisition, the CAC is $200, and that 15% of 10,000 customers churn then the first $300,000 in marketing spend would just serve to replace the churned customers and additional spend would be needed to drive sequential growth.

Investing in Companies with High Contribution Margin

As a VC, I tend to appreciate strong business models and like to invest after some baseline proof points are in place.  In my last post I outlined a number of metrics that were important ways to track a company’s health with the ratio of LTV (life time value) to CAC being one of the most important. When a company has a high contribution margin they have the time to build that ratio by adding more products or establishing subscriptions without burning through a lot of capital. Further, companies that have a high LTV/CAC ratio should have a high contribution margin as they mature since this usually means customers buy many times – leading to an expansion in repeat business as part of each month’s total revenue.

This thought process also applies to public companies. One of the most extreme is Facebook, which I’ve owned and recommended for five years. Even after the recent pullback its stock price is about 7x what it was five years ago (or has appreciated at a compound rate of nearly 50% per year since I’ve been recommending it). Not a surprise as Facebook’s contribution margin runs over 70% and revenue was up year/year 42% in Q2. These are extraordinary numbers for a company its size.

To give the reader some idea of how this method can be used as one screen for public companies, Table 2 shows gross margin, contribution margin, revenue growth and this year’s stock market performance for seven public companies.

Table 2: Public Company Contribution Margin Analysis

Two of the seven companies shown stand out as having both high Contribution Margin and strong revenue growth: Etsy and Stitch Fix. Each had year/year revenue growth of around 30% in Q2 coupled with 44% and 29% contribution margins, respectively. This likely has been a factor in Stitch Fix stock appreciating 53% and Etsy 135% since the beginning of the year.

Three of the seven have weak models and are struggling to balance revenue growth and contribution margin: Blue Apron, Overstock, and Groupon. Both Blue Apron and Groupon have been attempting to reduce their losses by dropping their marketing spend. While this increased their CM by 10% and 20% respectively, it also meant that they both have negative growth while still losing money. The losses for Blue Apron were over 16% of revenue. This coupled with shrinking revenue feels like a lethal combination. Blue Apron stock is only down a marginal amount year-to-date but is 59% lower than one year ago. Groupon, because of much higher gross margins than Blue Apron (52% vs 35%), still seems to have a chance to turn things around, but does have a lot of work to do. Overstock went in the other direction, increasing marketing spend to drive modest revenue growth of 12%. But this led to a negative CM and substantially increased losses. That strategy did not seem to benefit shareholders as the stock has declined 53% since the beginning of the year.

eBay is a healthy company from a contribution margin point of view but has sub 10% revenue growth. I can’t tell if increasing their market spend by a substantial amount (at the cost of lower CM) would be a better balance for them.

For me, Spotify is the one anomaly in the table as its stock has appreciated 46% since the IPO despite weak contribution margins which was one reason for my negative view expressed in a prior post. I think that is driven by three reasons: its product is an iconic brand; there is not a lot of float in the stock creating some scarcity; and contribution margin has been improving giving bulls on the stock a belief that it can get to profitability eventually. I say it is an anomaly, as comparing it to Facebook, it is hard to justify the relative valuations. Facebook grew 42% in Q2, Spotify 26%; Facebook is trading at a P/E of 24 whereas even if we assume Spotify can eventually get to generating 6% net profit (it currently is at a 7% loss before finance charges and 31% loss after finance charges, so this feels optimistic) Spotify would be trading at 112 times this theoretic future earnings.

 

SoundBytes

I found the recent controversy over Elon Musk’s sharing his thoughts on taking Tesla private interesting. On the one hand, people want transparency from companies and Elon certainly provides that! On the other hand, it clearly impacted the stock price for a few days and the SEC abhors anything that can be construed as stock manipulation. Of course, Elon may not have been as careful as he should have been when he sent out his tweet regarding whether financing was lined up…but like most entrepreneurs he was optimistic.

Interesting KPIs (Key Performance Indicators) for a Subscription Company

what-are-key-performance-indicators-kpis

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

  1. P&L Trends
  2. MRR (Monthly Recurring Revenue) and LTR (Lifetime Revenue)
  3. CAC (Cost of Customer Acquisition)
    1. Marketing to create leads
    2. Customers acquired electronically
    3. Customers acquired using sales professionals
  4. Gross Margin and LTV (Life Time Value of a customer)
  5. Marketing Efficiency

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

table 6.1

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:

  1. CPL (cost per lead) as above
  2. Sales Cost = current month’s cost of the sales force including T&E
  3. New Customers in the month = NC
  4. Conversion Rate to Customer = NC/number of leads= Y%
  5. 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

Variable Profit = Revenue – Variable Cost

Variable Profit% (VP%) = (Variable Profit)/Revenue

LTV = LTR x VP%

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.

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.

Soundbytes

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.

Highlights From the 2018 Azure CEO Summit

It’s All About the Network

On June 13th, 2018, Azure held our 12th Annual CEO Summit, hosted at the Citrix Templeton Conference Center. Success for our companies is typically predicated on the breadth and depth of their networks in Silicon Valley and beyond. This event is a cornerstone of how we support this, providing a highly curated, facilitated opportunity to expand connections for business development, fund-raising, and strategic partner dialogue. It is also an opportunity for our portfolio companies to develop strong relationships with our investors, networks, and among each other, which provides business partnership opportunities, potential future investors and is a first step towards engaging with future acquirers. An incidental benefit to Azure is that the appeal of the event also leads to expansion of our own network.

Throughout the day, we had participation of nearly 70 corporate entities, venture funds and financial institutions, including Amazon, Google, Apple, P&G, Citrix, Ericsson, Intel, Microsoft, Oracle, Trinet, Arcserv, Citibank, SVB, and UBS, in addition to 28 of Azure’s portfolio companies, and six Canadian startups which were invited as part of Azure’s Canada-Bridge initiative. The Canadian companies were selected from a group of about 100 nominated by Canadian VCs. At the event, the six winners gained access to Azure’s Silicon Valley network not only through participation along with our portfolio CEOs in the approximately 370 one-on-one meetings we arranged but also through networking opportunities throughout the rest of the day and into the evening.

Nearly all the Azure portfolio companies participating gave demo-day style presentations to the full audience, which expanded the reach of their message beyond the more intimate one-on-one meetings.

Visionary Keynote Speakers

Azure was quite fortunate in once again having several visionary keynote speakers who provided inspiration and thought-provoking inputs from their experiences as highly successful entrepreneurs and investors.

The first was David Ko, currently President and COO, Rally Health, and formerly SVP, Yahoo and COO, Zynga (famous for Farmville which peaked at 34.5 million daily active users). David provided his vision for the consumer-focused future for managing health and shared lessons learned from his journeys both in taking Zynga public and in leading Rally Health as it has grown in eight years from a company with low single-digit millions in revenue to more than a billion in revenue. Rally works with more than 200,000 employers to help drive employee engagement in their health. Accessible to more than 35 million people, Rally’s digital platform and solutions help people adopt healthier lifestyles, select health benefits, and choose the best doctor at the right price for their needs. The company’s wellness solution focuses on four key areas to improve health: nutrition, exercise, stress reduction and preventive health. Given the astronomical increase in the portion of U.S. GDP spent on healthcare, David pointed out how critical it is to help individuals improve their “wellness” tactics. He believes this is one of the waves of the future to curb further acceleration of healthcare cost.

Shai Agassi, Former President, Product and Technology Group, SAP, and former CEO, Better Place responded to questions posed by me and the audience during a fireside chat.  Shai first shared his experience of building a business that successfully became integrated into SAP, but the heart of his session revolved around his perspectives on the evolution of the electric car and the future emergence of (safe) automated vehicles. He painted a vivid picture of what the oncoming transition to a new generation of vehicles means for the future, where automated, electric cars will become the norm (in 5-10 years). As a result, he believes people will reduce their use of their own cars and instead, use an “automated Uber-like service” for much of their transportation. In such a world, many people won’t own a car and for those that do, their autos will have much longer useful lives thereby reducing the need to replace cars with the same frequency. If he proves correct, this would clearly have major ramifications for auto manufacturers and the oil industry.

Our final keynote speaker was Ron Suber, President Emeritus, Prosper Marketplace, who is referred to as “The Godfather of Fintech”.  Ron shared with us his perspective that we’re at the beginning stages of the ‘Golden Age of Fintech’ which he believes will be a 20-year cycle. He expects to continue to see a migration to digital, accessible platforms driven by innovation by existing players and new entrants to the market that will disrupt the incumbents. What must be scary to incumbents is that the new entrants in fintech include tech behemoths like Paypal, Google, Amazon, Tencent (owner of WeChat), Facebook and Apple.  While traditional banks may have access to several hundred million customers, these players can leverage their existing reach into relationships with billions of potential customers. For example,  WeChat and Instagram have both recently surpassed one billion users. With digital/mobile purchasing continuing to gain market share, a player like Apple can nearly force its users to include Apple Pay as one of their apps giving Apple some unique competitive advantages. Amazon and WeChat (in China) are in a strong position to leverage their user bases.

All That Plus a Great Dinner

After an action packed daytime agenda, the Summit concluded with a casual cocktail hour and outdoor dinner in Atherton. Most attendees joined, and additional members of the Azure network were invited as well. The dinner enabled significant networking to continue and provided an additional forum for some who were not able to be at the daytime event to meet some of our portfolio executives.

The Bottom Line – It’s About Results

How do we measure the success of the Summit? We consider it successful if several of our companies garner potential investors, strike business development deals, etc.  As I write this, only nine days after the event, we already know of a number of investment follow-ups, more than ten business-development deals being discussed, and multiple debt financing conversations. Investment banks and corporate players have increased awareness of the quality of numerous companies who presented. Needless to say, Azure is pleased with the bottom line.

Company Valuations Implied by my Valuations Bible: Are Snap, Netflix, Square and Twitter Grossly Overvalued?

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:

  1. The method is inaccurate
  2. The method is a valid screen but I’m missing some adjustment for these companies
  3. 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

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

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.

Netflix

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

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.

Blue Apron

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.

The Valuation Bible – Part 2: Applying the Rules to Tesla and Creating an Adjusted Valuation Method for Startups

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).

Calculating TPE

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.

Estimated TPE

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:

  1. 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
  2. It has consistently lost money so some say it will never reach the mature case I have outlined
  3. As others produce better electric cars Tesla’s market share of electric vehicles will decline so high revenue growth is not sustainable
  4. 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.

The Valuation Bible

Facebook valuation image

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

graph

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.

 

SoundBytes

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

table

*Note: Bolded players denote those in the top 10 in Points per Game

Ten Predictions for 2018

In my recap of 2017 predictions I pointed out how boring my stock predictions have been with Tesla and Facebook on my list every year since 2013 and Amazon on for two of the past three years. But what I learned on Wall Street is that sticking with companies that have strong competitive advantages in a potentially mega-sized market can create great performance over time (assuming one is correct)! So here we go again, because as stated in my January 5 post, I am again including Tesla, Facebook and Amazon in my Top ten list for 2018. I believe they each continue to offer strong upside, as explained below. I’m also adding a younger company, with a modest market cap, thus more potential upside coupled with more risk. The company is Stitch Fix, an early leader in providing women with the ability to shop for fashion-forward clothes at home. My belief in the four companies is backed up by my having an equity position in each of them.

I’m expecting the four stocks to outperform the market. So, in a steeply declining market, out-performance might occur with the stock itself being down (but less than the market). Having mentioned the possibility of a down market, I’m predicting the market will rise this year. This is a bit scary for me, as predicting the market as a whole is not my specialty.

We’ll start with the stock picks (with January 2 opening prices of stocks shown in parenthesis) and then move on to the remainder of my 10 predictions.

1. Tesla stock appreciation will continue to outpace the market (it opened the year at $312/share).

The good news and bad news on Tesla is the delays in production of the Model 3. The good part is that we can still look forward to massive increases in the number of cars the company sells once Tesla gets production ramping (I estimate the Model 3 backlog is well in excess of 500,000 units going into 2018 and demand appears to be growing). In 2017, Tesla shipped between 80,000 and 100,000 vehicles with revenue up 30% in Q3 without help from the model 3. If the company is successful at ramping capacity (and acquiring needed parts), it expects to reach a production rate of 5,000 cars per week by the end of Q1 and 10,000 by the end of the year. That could mean that the number of units produced in Q4 2018 will be more than four times that sold in Q4 2017 (with revenue about 2.0-2.5x due to the Model 3 being a lower priced car). Additionally, while it is modest compared to revenue from selling autos, the company appears to be the leader in battery production. It recently announced the largest battery deal ever, a $50 million contract (now completed on time) to supply what is essentially a massive backup battery complex for energy to Southern Australia. While this type of project is unlikely to be a major portion of revenue in the near term, it can add to Tesla’s growth rate and profitability.

2. Facebook stock appreciation will continue to outpace the market (it opened the year at $182/share).

The core Facebook user base growth has slowed considerably but Facebook has a product portfolio that includes Instagram, WhatsApp and Oculus. This gives Facebook multiple opportunities for revenue growth: Improve the revenue per DAU (daily active user) on Facebook itself; increase efforts to monetize Instagram and WhatsApp in more meaningful ways; and build the install base of Oculus. Facebook advertising rates have been increasing steadily as more mainstream companies shift budget from traditional advertising to Facebook, especially in view of declining TV viewership coupled with increased use of DVRs (allowing viewers to skip ads). Higher advertising rates, combined with modest growth in DAUs, should lead to continued strong revenue growth. And while the Oculus product did not get out of the gate as fast as expected, it began picking up steam in Q3 2017 after Facebook reduced prices. At 210,000 units for the quarter it may have contributed up to 5% of Q3 revenue. The wild card here is if a “killer app” (a software application that becomes a must have) launches that is only available on the Oculus, sales of Oculus could jump substantially in a short time.

3. Amazon stock appreciation will outpace the market (it opened the year at $1188/share).

Amazon, remarkably, increased its revenue growth rate in 2017 as compared to 2016. This is unusual for companies of this size. In 2018, we expect online to continue to pick up share in retail and Amazon to gain more share of online. The acquisition of Whole Foods will add approximately $4B per quarter in revenue, boosting year/year revenue growth of Amazon an additional 9%-11% per quarter, if Whole Foods revenue remains flattish. If Amazon achieves organic growth of 25% (in Q3 it was 29% so that would be a drop) in 2018, this would put the 3 quarters starting in Q4 2017 at about 35% growth. While we do expect Amazon to boost Whole Foods revenue, that is not required to reach those levels. In Q4 2018, reported revenue will return to organic growth levels. The Amazon story also features two other important growth drivers. First, I expect the Echo to have another substantial growth year and continue to emerge as a new platform in the home. Additionally, Amazon appears poised to benefit from continued business migration to the cloud coupled with increased market share and higher average revenue per cloud customer. This will be driven by modest price increases and introduction of more services as part of its cloud offering. The success of the Amazon Echo with industry leading voice technology should continue to provide another boost to Amazon’s revenue. Additionally, having a large footprint of physical stores will allow Amazon to increase distribution of many products.

4. Stitch Fix stock appreciation will outpace the market (it opened the year at $25/share and is at the same level as I write this post).

Stitch Fix is my riskiest stock forecast. As a new public company, it has yet to establish a track record of performance that one can depend upon. On the other hand, it’s the early leader in a massive market that will increasingly move online, at-home shopping for fashion forward clothes. The number of people who prefer shopping at home to going to a physical store is on the increase. The type of goods they wish to buy expands every year. Now, clothing is becoming a new category on the rapid rise (it grew from 11% of overall clothing retail sales in 2011 to 19% in 2016). It is important for women buying this way to feel that the provider understands what they want and facilitates making it easy to obtain clothes they prefer. Stitch Fix uses substantial data analysis to personalize each box it sends a customer. The woman can try them on, keep (and pay for) those they like, and return the rest very easily.

5. The stock market will rise in 2018 (the S&P opened the year at 2,696 on January 2).

While I have been accurate on recommending individual stocks over a long period, I rarely believe that I understand what will happen to the overall market. Two prior exceptions were after 9/11 and after the 2008 mortgage crisis generated meltdown. I was correct both times but those seemed like easy calls. So, it is with great trepidation that I’m including this prediction as it is based on logic and I know the market does not always follow logic! To put it simply, the new tax bill is quite favorable to corporations and therefore should boost after-tax earnings. What larger corporations pay is often a blend of taxes on U.S. earnings and those on earnings in various countries outside the U.S. There can be numerous other factors as well. Companies like Microsoft have lower blended tax rates because much of R&D and corporate overhead is in the United States and several of its key products are sold out of a subsidiary in a low tax location, thereby lowering the portion of pre-tax earnings here. This and other factors (like tax benefits in fiscal 2017 from previous phone business losses) led to blended tax rates in fiscal 2015, 2016 and 2017 of 34%, 15% and 8%, respectively. Walmart, on the other hand, generated over 75% of its pre-tax earnings in the United States over the past three fiscal years, so their blended rate was over 30% in each of those years

Table 1: Walmart Blended Tax Rates 2015-2017

The degree to which any specific company’s pre-tax earnings mix changes between the United States and other countries is unpredictable to me, so I’m providing a table showing the impact on after-tax earnings growth for theoretical companies instead. Table 2 shows the impact of lowering the U.S. corporate from 35% to 21% on four example companies. To provide context, I show two companies growing pre-tax earnings by 10% and two companies by 30%. If blended tax rates didn’t change, EPS would grow by the same amount as pre-tax earnings. For Companies 1 and 3, Table 2 shows what the increase in earnings would be if their blended 2017 tax rate was 35% and 2018 shifts to 21%. For companies 2 and 4, Table 2 shows what the increase in earnings would be if the 2017 rate was 30% (Walmart’s blended rate the past three years) and the 2018 blended rate is 20%.

Table 2: Impact on After-Tax Earnings Growth

As you can see, companies that have the majority of 2018 pre-tax earnings subject to the full U.S. tax rate could experience EPS growth 15%-30% above their pre-tax earnings growth. On the other hand, if a company has a minimal amount of earnings in the U.S. (like the 5% of earnings Microsoft had in fiscal 2017), the benefit will be minimal. Whatever benefits do accrue will also boost cash, leading to potential investments that could help future earnings.  If companies that have maximum benefits from this have no decline in their P/E ratio, this would mean a substantial increase in their share price, thus the forecast of an up market. But as I learned on Wall Street, it’s important to sight risk. The biggest risks to this forecast are the expected rise in interest rates this year (which usually is negative for the market) and the fact that the market is already at all-time highs.

6. Battles between the federal government and states will continue over marijuana use but the cannabis industry will emerge as one to invest in.

The battle over legalization of Marijuana reached a turning point in 2017 as polls showed that over 60% of Americans now favor full legalization (as compared to 12% in 1969). Prior to 2000, only three states (California, Oregon and Maine) had made medical cannabis legal. Now 29 states have made it legal for medical use and six have legalized sale for recreational use. Given the swing in voter sentiment (and a need for additional sources of tax revenue), more states are moving towards legalization for recreational and medical purposes. This has put the “legal” marijuana industry on a torrid growth curve. In Colorado, one of the first states to broadly legalize use, revenue is over $1 billion per year and overall 2017 industry revenue is estimated at nearly $8 billion, up 20% year/year. Given expected legalization by more states and the ability to market product openly once it is legal, New Frontier Data predicts that industry revenue will more than triple by 2025. The industry is making a strong case that medical use has compelling results for a wide variety of illnesses and high margin, medical use is forecast to generate over 50% of the 2025 revenue. Given this backdrop, public cannabis companies have had very strong performance. Despite this, in 2016, VCs only invested about $49 million in the sector. We expect that number to escalate dramatically in 2017 through 2019. While public cannabis stocks are trading at nosebleed valuations, they could have continued strong performance as market share consolidates and more states (and Canada) head towards legalization. One caveat to this is that Federal law still makes marijuana use illegal and the Trump administration is adopting a more aggressive policy towards pursuing producers, even in states that have made use legal. The states that have legalized marijuana use are gearing up to battle the federal government.

7. At least one city will announce a new approach to Urban transport

Traffic congestion in cities continues to worsen. Our post on December 14, 2017 discussed a new approach to urban transportation, utilizing small footprint automated cars (one to two passengers, no trunk, no driver) in a dedicated corridor. This appears much more cost effective than a Rapid Bus Transit solution and far more affordable than new subway lines. As discussed in that post, Uber and other ride services increase traffic and don’t appear to be a solution. The thought that automating these vehicles will relieve pressure is overly optimistic. I expect at least one city to commit to testing the method discussed in the December post before the end of this year – it is unlikely to be a U.S. city. The approach outlined in that post is one of several that is likely to be tried over the coming years as new thinking is clearly needed to prevent the traffic congestion that makes cities less livable.

8. Offline retailers will increase the velocity of moving towards omnichannel.

Retailers will adopt more of a multi-pronged approach to increasing their participation in e-commerce. I expect this to include:

  • An increased pace of acquisition of e-commerce companies, technologies and brands with Walmart leading the way. Walmart and others need to participate more heavily in online as their core offline business continues to lose share to online. In 2017, Walmart made several large acquisitions and has emerged as the leader among large retailers in moving online. This, in turn, has helped its stock performance. After a stellar 12 months in which the stock was up over 40%, it finally exceeded its January 2015 high of $89 per share (it reached $101/share as we are finalizing the post). I expect Walmart and others in physical retail to make acquisitions that are meaningful in 2018 so as to speed up the transformation of their businesses to an omnichannel approach.
  • Collaborating to introduce more online/technology into their physical stores (which Amazon is likely to do in Whole Foods stores). This can take the form of screens in the stores to order online (a la William Sonoma), having online purchases shipped to your local store (already done by Nordstrom) and adding substantial ability to use technology to create personalized items right at the store, which would subsequently be produced and shipped by a partner.

9. Social commerce will begin to emerge as a new category.

Many e-commerce sites have added elements of social, and many social sites have begun trying to sell various products. But few of these have a fully integrated social approach to e-commerce. The elements of a social approach to e-commerce include:

  • A feed-based user experience
  • Friends’ actions impact your feed
  • Following trend setters to see what they are buying, wearing, and favoring
  • Notifications based on your likes and tastes
  • One click to buy
  • Following particular stores and/or friends

I expect to see existing e-commerce players adding more elements of social, existing social players improving their approach to commerce and a rising trend of emerging companies focused on fully integrated social commerce.

10. “The Empire Strikes Back”: automobile manufacturers will begin to take steps to reclaim use of its GPS.

It is almost shameful that automobile manufacturers, other than Tesla, have lost substantial usage of their onboard GPS systems as many people use their cell phones or a small device to run Google, Waze (owned by Google) or Garmin instead of the larger screen in their car. In the hundreds of times I’ve taken an Uber or Lyft, I’ve never seen the driver use their car’s system. To modernize their existing systems, manufacturers may need to license software from a third party. Several companies are offering next generation products that claim to replicate the optimization offered by Waze but also add new features that go beyond it like offering to order coffee and other items to enable the driver to stop at a nearby location and have the product prepaid and waiting for them. In addition to adding value to the user, this also leads to a lead-gen revenue opportunity. In 2018, I expect one or more auto manufacturers to commit to including a third-party product in one or more of their models.

Soundbytes

Tesla model 3 sample car generates huge buzz at Stanford Mall in Menlo Park California. This past weekend my wife and I experienced something we had not seen before – a substantial line of people waiting to check out a car, one of the first Model 3 cars seen live. We were walking through the Stanford Mall where Tesla has a “Guide Store” and came upon a line of about 60 people willing to wait a few hours to get to check out one of the two Model 3’s available for perusal in California (the other was in L.A.). An hour later we came back, and the line had grown to 80 people. To be clear, the car was not available for a test drive, only for seeing it, sitting in it, finding out more info, etc. Given the buzz involved, it seems to me that as other locations are given Model 3 cars to look at, the number of people ordering a Model 3 each week might increase faster than Tesla’s capacity to fulfill.