Cap Table Modeling: Understanding the Mechanics of Equity vs. Convertible Debt

Cap tables are an important concept for entrepreneurs to grasp when taking outside financing. A cap table is a schedule that lays out the ownership stakes in an early stage company. They typically take the form of a spreadsheet that changes over time as more capital is raised and more investors become involved in the growth of a company. Cap tables can also vary based on whether the capital is raised through equity or through convertible debt (debt that converts to equity at a future point in time).

Much has been written on the merits and challenges of both equity and convertible debt. There are a number of great posts that explain each at a high level and then go on to take a stance on which method is preferred and when. A number of notable investors have weighed in on the topic through a variety of posts including: Fred Wilson, Mark Suster and Josh Kopelman. All of these posts do a great job of explaining the mechanics of each financing option and provide sound reasoning around when (and when not) to use convertible debt vs. equity.

The problem with these sources, is that rarely do they actually dive into the mechanics of building a cap table from scratch and modeling out the differences over time of equity vs. convertible debt. Of course, there are courses taught by organizations such as Wall Street Prep that do extensive training around cap table modeling. While these courses are great, they tend to be a) very expensive b) time-consuming and c) highly detailed-oriented (too detailed for what most entrepreneurs are looking for). So what do you do if you’re an entrepreneur who wants more than just a high level understanding of the pros and cons of various financing options but doesn’t want to pay a premium for a time-consuming, detail-heavy course?

I recently came across a great resource put together by my Professor at CBS and 37 Angels founder, Angela Lee. Professor Lee has built a step-by-step guide to modeling out cap tables for equity and convertible debt deals (both when the discount or cap come into play). The guide, which is posted below, provides detailed instructions on how to calculate the various components of a cap table (shares owned, share price, % owned, etc.,) across various rounds of fundraising. Although the tool is simplified, it provides an intuitive way to model various financing scenarios and their implications for your ownership over time. Hopefully this sheds a bit more light on the mechanics of how cap tables are put together. Big thanks again to Professor Lee!

37 Angels Cap Table Template

The Age of the Unicorn: Traits of Today’s Unicorns & Their Marriage to the IPO Market

A few days ago, Dan Primack and Erin Griffith from Fortune put out an article entitled “The Age of the Unicorn” along with a nice list of the 80+ unicorns currently in business. In addition to providing a working definition of the “unicorn” (essentially a pre-IPO tech startup that has reached a $1B market value), Primack and Griffith go on to describe some of the characteristics of today’s post-bubble unicorns and why these companies have become much more commonplace. I decided to spend a little time looking at their list and gathering a little bit more information on these companies.

The first trait worth noting about today’s unicorns has to do with their actual valuations. While the mean valuation of these companies is nearly ~4B, this average is heavily affected by a few of the upper outliers—companies like Xiaomi ($46B), Uber ($41B) and Palantir ($15B). There are only 8 “decacorns” (companies with a $10B+ valuation); the majority of these companies fall in the $1-2B range. In other works, the collection has a long tail of companies that are “just barely” above the unicorn threshold. Importantly, these valuations are all on paper. For the founders and investors involved, these numbers are largely irrelevant until there is an exit to provide liquidity to these valuations (more on this towards the end of the post.)

Another characteristic worth noting is when these companies were founded. The average company life of these unicorns is 8 years—not all that surprising until you consider the fact that many of these companies have been unicorns for several years before Fortune published this list. In fact, the speed with which some of these companies have reached unicorn status is unparalleled. 7 of the companies (~9%) were founded in the last 2 years and 31 (~40%) were founded in the 6 years since the financial crisis. A mere 12 unicorns (15%), are dot-com survivors (founded in 2001 or earlier).

A final characteristic of the unicorn list worth noting is where they were founded. The chart below shows a story that is not all surprising—namely that the Bay Area is still King when it comes to producing fast-growing tech startups. That being said, the Bay Area’s “share” of unicorns, at 44%, is certainly not what it used to be. China is clearly a major force in the production of unicorns as is NYC and Europe. The surprise from a geographic perspective appears to be Southern California in 4th place—bolstered by the likes of SnapChat, SpaceX and JustFab. While not shown in the chart below, Boston and India are both tied for a close 6th with 3 unicorns each. Interestingly, each of India’s 3 unicorns are in the online retail/commerce space: FlibKart, SnapDeal and InstaCart.

unicorn location

There has been much debate on the drivers behind the growth in the number of unicorns, the macroeconomic implications of more privately held $1B+ companies and the possibility of a growing bubble. Griffith and Primack’s article provides a great overview of these debates and other related issues. One implication that is pretty evident, however, is that the IPO markets need to continue to stay strong in the next few years or venture investors are going to face disappointment. A quick example will help illustrate this point.

Let’s say you’re a VC who recently invested $100M into the latest round of a fast growing startup at a $900M pre thus providing the company with unicorn status based on its $1B post. As a VC, you’re looking for at least a 3x cash-on-cash return on this investment. In order for you to realize that type of return, the company you invested in needs to exit for at least $3B. Very few companies in the F500 can afford an acquisition of that size. Thus, in order to realize that kind of return, you will push the company (and its management team) to go for the IPO. This push for an IPO may be aligned with the founder’s goals but it may also come despite the attractiveness of an acquisition from the founder’s perspective. Even if there is full alignment on exit strategy, the whole thing will unravel if the IPO markets cool and there is no demand for these assets. Thus, the Age of the Unicorn is strongly tied to the strength of the IPO market. In the coming months, I think we’re going to hear a lot more speculation from the venture community on this very topic.


Increasing Conversion along the mCommerce Customer Journey

Increasing sales on a mobile commerce (mCommerce) platform is often seen as synonymous with driving more traffic through mobile channels—whether through the mobile app, tablet or mobile site. Yet there are other ways for mCommerce startups to increase sales besides increasing app downloads. Chief among these methods is increasing conversion in the customer journey to levels that are on par or better than desktop conversion rates or any other benchmark a company is using.

Typically mCommerce platforms have customer journeys roughly similar to the desktop customer journey. Give or take a few steps depending on the product, industry, stored preferences, member vs. guest, etc. These customer journeys almost always (roughly) look something like this:


When scaled up to thousands if not millions of customers all going through this process, the customer journey in aggregate looks like a funnel. In early stages of the journey, the funnel is broad—there are many customers. Yet by the time the journey is at the “Confirmation” stage the funnel has narrowed, and there are very few customers remaining who actually convert into buyers. An example using Airbnb will help illustrate the concept of the funnel. All numbers are completely made up and used simply for illustrative purposes.

Let’s say there are 100 potentials customers who login to Airbnb’s iPhone app on Friday at noon. Of those 100, let’s say 80 proceed from the Login page to actually browsing the listings of sublets in the destination of their choice. Of those 80 who browse the listings, only 30 actually select a sublet that they are interested in. Of those 30 who select a sublet of interest, only 10 make it to the “Review” page where they review their listings and perhaps add any extra features they want. Of those 10, only 5 actually enter in their payment information. And of the 5 who enter their payment information, only 2 click submit and reach the “Confirmation” page. Thus of the original 100 who logged into the app, only 2 actually purchased, resulting in a final conversion rate of 2%.

There is clearly a big opportunity to increase conversion—particularly if Airbnb’s desktop conversion is higher than 2% or if their competition has superior conversion rates. Startups looking to increase conversion in the customer journey can target 2 different methods:

(1) The first method is to simply make it easier for customers by eliminating steps in the customer journey. A great example of this is how Uber has dealt with payments. By taking a photo of your credit card the first time a customer opens the app and then storing that information, they have effectively eliminated the payment step in the customer journey. Fewer steps in the journey, mean less opportunities to fall out and, ultimately, higher conversion rates.

(2) The second method is to simplify painpoints in the customer journey. In other words, increase the conversion rate of steps in the customer journey where customer fallout is particularly high. So if the conversion rate from “Browse Listings” to “Select Product” at Airbnb is currently 37.5% (30%/80%), focus on increasing that step’s conversion rate to 50% or 60%. This particular step in the journey has been mastered by many of the airlines and hotel companies (SPG and United in particular) with their unique mapping features, simplified browsing/sorting capabilities and sharp focus on UX. As can be imagined, increasing conversion early in the customer journey (when the funnel is still wide), should be prioritized as it has the potential to have the biggest impact on final conversion.

M&A Activity of Major Tech Companies

In the venture world, there are typically two ways VCs successfully exit the companies they invest in: (1) via IPO or (2) through acquisition by a larger tech company (think Google, Microsoft, etc.,). Of these two methods, an M&A exit has historically been more common. Nonetheless the literature within the venture community about why large tech firms acquire the specific targets they snap up is sparse. It seems odd that while ‘the acquisition’ is the main goal for most of the venture community, many VCs spend little to no time thinking about investing from the perspective of the firms doing all the acquiring.

This semester, I took Columbia Business School Professor Raul Katz‘s course on Developing Strategies for High Tech firms. In the process, I wrote my final paper on this very subject. The focus of the paper was to understand the recent (last 3 years) M&A activity of four of the largest global tech companies: Apple, Facebook, Google and Microsoft. Specifically the paper analyzed the implications the M&A activity of these four companies (and others like them) has for early stage VCs focused on investing in tech companies.

In building towards a hypothesis around the motivations for M&A activity, I examined the 7 motivational variables displayed in the table below. I focused solely on operational motivators and excluded non-value maximizing motivators such as management hubris or financial synergies like the desire to reduce the weighted average cost of capital (WACC). The rationale behind this focus is that operational synergies are the most relevant and identifiable variables for VCs to focus on as they think about M&A as an exit option. Operational synergies are also: specific, repetitive (allowing for pattern recognition), have predictive power and can be used to build an investment thesis.

The shaded rows represent new variables previously not looked at in the existing literature. I used S&P Capital IQ as well as a variety of analyst reports and news articles (VentureBeat, TechCrunch, etc.,) to populate the data used in the regression model.


The results of the regression analysis are displayed below:

Premium Paid = -$5,500 + $2,950(β1) + $324(β2) + $3,780(β3) + $109(β4) + $2,168(β5) + $4,193(β6) + $1301(β7)


There are several characteristics of the regression worth pointing out. First, the intercept (β0) is negative, which limits the full application of the regression equation. This is likely due to a small sample size and data that is not normally distributed. Because of this negative intercept, we cannot make a direct dollar connection between each M&A motivation variable and the premium paid by the acquiring firm. That being said, we can make some relative observations based on the size of each beta coefficient. Additionally we can make some important observations regarding statistical significance. As seen in the exhibit above the four M&A motivation variables that were statistically significant include: economies of scale, value chain integration, growth in new and existing markets and large network effects. The remaining three variables are not statistically significant according to our model.

The results can be broadly bucketed into B2C variables and B2B variables—although there is certainly some overlap. On the B2C front, unsurprisingly, tech firms like Apple, Facebook, Google and Microsoft place the largest premiums on startups with large network effects. Acquiring companies like Instagram, WhatsApp and Skype allows these firms to essentially acquire a massive customer base with a large customer life-time value. Because of the large network effects, these customers are unlikely to switch to substitutes. Big tech firms can then monetize these acquired customers over a long period of time as well as cross-sell products and services on their existing platforms.

According to our regression output, these big tech firms also place an important (though not nearly as large) premium on B2C companies that allow them to grow in new and existing markets. B2C companies like Snaptu (a mobile platform for feature phones in developing nations acquired for $70 million) and Oculus VR (a virtual reality and gaming device company acquired for $2.3 billion) allow big companies like Facebook to enter new markets—whether geographic, customer-segment specific or newly emerging industries.

When it comes to B2B acquisitions, the M&A model provides evidence that large tech companies place a heavy premium on value chain integration and economies of scale—both means to maintain a competitive advantage. Apple’s acquisition of semiconductor company Anobit Technologies for $400 million is a great example of value chain integration. Apple has slowly been moving away from hard drives to flash memory beginning with the iPod and most recently its MacBook Air. Flash memory allows Apple’s products to be thinner and run on less power. Acquiring Anobit allowed the firm to acquire the hardware component needed to complete value chain integration and transition fully from hard drives to flash memory chips.

Though not as important as value chain integration from a relative perspective, large tech companies also consider economies of scale when acquiring B2B companies. Within that realm, companies that provide a service or toolkit that enable a bigger tech company to take advantage of scale economies are also often worth acquiring. Microsoft’s acquisition of Pando, a file-sharing technology that works peer-to-peer like bit-torrent, is a great example of this. Pando’s technology can be applied to Microsoft products like Xbox and Windows Phone App Store, to reduce costs in these divisions and enable Microsoft to take advantage of its economies of scale.

For full analysis of the results of this study as well as a discussion of the implications for VCs, please email the author.

Google Glass Investment Thesis

About a year ago, I wrote a post about Google Glass and the possibility that Glass (and other wearable tech hardware platforms) would eventually give rise to the next generation of startups. It seems like the jury is still out on whether Glass will be the next iPhone, but it is certainly an area worth exploring further. This semester while interning with DFJ Gotham Ventures, I was charged with building out an investment thesis around the Glass ecosystem.

As a result, I did a deep dive analysis on the eyeware itself, the wearable tech industry more broadly speaking and the opportunities and challenges that currently exist for venture investors. In the process, I went as granular as focusing on specific industries and identifying companies within those industries. I was fortunate to speak with a wide range of VCs, entrepreneurs and industry experts – all of whom greatly contributed to the end product. Special thanks to Zak and Lucas on the Gotham team and Professor R.A. Farrokhnia for their guidance. Enjoy and feel free to drop me a line if you have any comments or suggestions. 

CareCloud: A Good Investment?

This past week, while applying for the InSITE Fellows program, I had to prepare a quick analysis of CareCloud (a healthcare IT company) based on a venture beat article that can be found here. Now that the application cycle is over, I thought I’d share my response and some general thoughts on the company. Admittedly, I know very little about healthcare companies but the industry is intriguing and very much ripe for disruption. Here is a first attempt at evaluating the company from an investment perspective.

In assessing CareCloud as a potential investment, I examined three core areas: the market, the technology and the team. While the technology is very sound and the team is promising, I would likely not invest in the company due to several significant issues in the electronic medical record (EMR) market.

The Technology

CareCloud’s medical practice management software is a great solution to a clear pain point in the market—namely that legacy vendor’s provide systems that are too bulky, inefficient and costly. Built on a nimble Ruby on Rails platform, CareCloud’s elegant design and user-friendly interface has been well received by physicians and other users. The product is completely cloud based making it easy for physicians to update and stay on top of complex regulations and compliance mandates. It also focuses on providing users with the flexibility to pick and choose components of the software rather than being forced to adopt an entire platform and abandon existing software. All these features result in a lowered cost to the physician and a better way to manage their practices.

The Team

The management team at CareCloud is also very strong—comprised of industry veterans and individuals who are experts at the given function they lead. This of course starts at the top with Albert Santalo—the founder and CEO of the company. Santalo has spent the last 12 years working in healthcare. He is a successful serial entrepreneur having co-founded and grown Avisena into one of the largest providers of revenue cycle management software and services for physician practices in the world. The rest of the team is likewise very strong and experienced. This is a team that has experienced a lot of success prior to starting CareCloud and in the first 4 years of the company have continued to be successful.

The Market

The biggest challenge with CareCloud is the market. At a high level, things look pretty good. Healthcare is the largest sector in the U.S. economy and set to grow from a $2 trillion dollar market to a $4 trillion dollar market in the next 10 years. In particular there are mounting cost pressures stemming from an aging U.S. population that will grow from 12% who are 65+ to 17% who are 65+ in the next 10 years. Those over the age of 65 tend to spend 4X as much on healthcare as the rest of the population. Against this backdrop, the EMR market is estimated to be a $6-10 billion dollar market—which would appear to be large enough to invest in.

However, the big problems with the market are the regulatory environment in the industry and the plethora of competition CareCloud faces. Regulations and mandates imposed by the federal government could easily destroy the industry and put CareCloud out of business—particularly since so much data is stored in the cloud where it is more susceptible to compromise. In terms of the competition, legacy vendors like Allscripts, Epic, GE and Siemens already control at least 75% of the market and almost all large hospitals use them because of the subsidies from the government—CareCloud is unlikely to take any of this market share away. The remaining niche of 25% or $1.5-2.5 billion of the original market is comprised of pysichians operating in small clinics with over 300 electronic vendors, including well established companies like Practice Fusion and AthenaHealth, competing for their business. Even if we assumed that CareCloud could capture 25% of that market (which it almost assuredly won’t), that would only be a total share of $375-$625m, which is too small to invest in especially since the company has already taken in $54 million in total venture funding and we are only at the Series B level. There is a lot of pressure to have a very high exit in situations like this. Because of these challenges in the market, I would be very hesitant to invest in CareCloud.

Additional Questions

Some additional questions I have that would be useful to know when investing include:

  • What was the pre-money valuation before the Series B round of financing?
  • What do the actual revenue and customer acquisition numbers look like?
  • What are the terms of the deal—what sort of exit size do we need to make a good return?


Market Sizing: How big is online video advertising?

Television advertising still dominates the scene when it comes to advertising revenue. Yet in the last 5 years, Internet advertising has nearly doubled proving that there is little doubt that advertising is increasingly going online. Within Internet advertising, the video advertising component, while still relatively small, has been growing steadily resulting in a tremendous opportunity for innovative entrepreneurs disrupting this emerging market.

But exactly how big is the online video advertising market? Applying a bottoms-up approach yields the following results:

Total # of Video Ad Views = U.S. Pop. X Average # of Video Ads viewed per person
Total # of Unique Video Ad Views = 315mm X *840
Total # of Unique Video Ad Views = 265B

Average Price per View =  CPM / 1000
Average Price per View =  $15 / 1000
Average Price per View = .015

Central Equation
Video Ad Market Size = Total # of Unique Video Ad Views X Average $ per View
Video Ad Market Size = 265,000,000,000 X .015
Video Ad Market Size = $4B

U.S. Market Size = ~$4B
**Global Market Size = ~$16B

*Based on ComScore 2012 U.S. data, market sizing estimates
**Applied a multiplier of 4 to get the global market size.

Doing a quick search through the Wall Street Journal – it appears that they agree with this market size of $4B for the U.S. market.

Picture 1

It is important to note two trends in the video ad market that matter and will significantly impact the size of the market.

1)   Contraction Force: The average price per video ad is decreasing. In 2011 at top tier sites ads were in the $17-$25 range. In 2012 that range fell to $15-$20. The WSJ argued that this price will only decrease further from here.

2)   Expansion Force: Video advertising may only be a $4B market as of 2012, but it is an increasing segment of the overall $42.5B digital media market—a market which is growing in size itself.

The net effect of these two forces is hard to determine as they act in opposite directions, but the overall affect will likely be an increase in the market size in the next 5 years, especially as the internet plays an increasingly important role vis a vis the television.

Google Glass

Since the beginning of the computing industry, it has been the case that hardware platforms produce software innovation. A single innovation in hardware can provide the base for a multitude of software applications. In the process, thousands of companies are created, millions of customers are acquired and billions of dollars in revenues are generated.

Hardware innovation in the 1970s and 1980s by IBM around the personal computer led to software innovation by now Fortune 500 companies like Microsoft, Oracle, Adobe, Symantec and SAP. In the mid 2000s, hardware innovation by Apple on the iPhone led to many of today’s rising stars: Twitter, Instagram, Flipboard and Waze are all built on mobile platforms.


It is still too early to tell whether Google Glass will be the next ubiquitously used hardware platform spurring software innovation. It looks like the product development teams have a ways to go to iron out some of the kinks and lower production costs to get the price down to what consumers would be willing to pay In fact, last week Forrester Report published survey results showing that only 12% or approximately 21.6 million U.S. online consumer would use Google Glass on an everyday basis.

Yet, if we looked back in time, I don’t think the early adoption numbers for the personal computer or iPhone would be all that different, especially pre-launch. Nonetheless here we are in 2013 and I can count on one hand how many people I know who don’t have a smartphone or a personal computer.

If Glass is able to capture broad consumer appeal, you can count on another big wave of software innovation. Already, Google has released parts of its developer API and the applications are limitless—everything from education to health to advertising. Smart entrepreneurs and VCs will already start thinking about software applications Glass could enable. It’s a great time for innovation.

Metamorphic Ventures

This past week, I started a pre-MBA internship at Metamorphic Ventures—an early stage venture capital firm that focuses on investing in transactional media companies. More specifically MV likes to invest in companies with the potential to disrupt the digital media and commerce space.

The full list of portfolio companies, which includes companies as diverse as IndieGoGo, Songza, Tapad and Moveable Ink, can be found here. But broadly speaking, MV is looking for companies that are going for a seed or Series A round, focused on B2B products/services and have the ability to use a small injection of capital to scale quickly.

In my first week as a Summer Associate with the firm I have been able to get a quick glimpse of the world of VC. Admittedly I haven’t even scratched the surface here, but what I have seen has impressed upon me the uniqueness of the business. It’s been said by many before that you really can’t learn about VC by reading a textbook or taking a class—not that those aren’t perfectly acceptable foundations from which to build. But in order to really learn the industry and get good at identifying promising companies, you need to view any junior level role as an apprenticeship. Find people who know what they’re doing, who have been in the business for a while and try to learn as much as possible from them.

My hope is that as the summer progresses, I’ll have the opportunity to write more about this experience and what I’ve learned about early stage tech investing from the leadership at MV. For now, however, here’s a glimpse at some of the projects I’m working on.

1)   Deal Flow: MV gets a large volume of deals each week coming through the pipeline. Part of what I’ve been working on is creating an internal system to best manage the deal flow and track companies that come our way. Along with this, I’ve been helping write initial memos of companies based on preliminary research, conversations the partners have had with the entrepreneurs and any company materials they’ve sent our way.

2)   Portfolio Company Support: Several of MV’s companies have projects that they would love to pursue but simply don’t have the time for this summer. One of my hopes is to get involved in more of an operational role with some of these companies. To start off with, I’ll be sitting down with Songza next week to discuss a competitor analysis project that they need some help with. More on that as the summer progresses.

3)   Internal Projects: There are a number of research projects and industry analysis reports that need to be done this summer. The goal here is to collect and analyze data that will help the firm make better investment decisions as well as grow the amount of shared knowledge for the MV community.

All in all, it’s shaping up to be a pretty interesting summer experience that will definitely provide valuable insight into the VC/Tech world. Looking forward to writing more soon.

Customer Acquisition Challenges for Location-based Startups

Location-based startups seem to be pretty popular these days. Some of the most successful location based startups (i.e. Foursquare, Shopkick, Yelp, etc.,) have received multiple rounds of funding, achieved nice exits and set a high bar for others to follow. Nonetheless, many location-based start-ups still face a number of challenges when it comes to growth – particularly in the area of customer acquisition. This post seeks to dig a little further into the issue of customer acquisition for location-based apps. Here are some steps startups can take to address challenges they face in acquiring new customers. 

  • Performance Measurement: It’s important to first take a step back and reflect on the existing product and existing customers. Some questions to ask include: Who are the customers? Are there different segments? How are the current customers using the product? Are there differences in the ways various segments use the product? How is the product performing among various customer segments? An understanding of these questions will allow the portfolio company to better target its strategy—whether that is to strengthen its position in a current market or pivot a little and go after a different set of customers.
  • Product Differentiation: Startups looking to acquire customers should differentiate their product from the competition and make the value-add very clear. That way, from a customer’s perspective, there is a clear reason for switching to the new product. Product differentiation can build customer loyalty and allow the startup to monetize its partnerships with advertisers or other 3rd party vendors. Mobile represents a huge opportunity to creatively differentiate across a range of platforms. Startups should find unique ways to combine location-based data with mobile platforms to provide users with useful information. Foursquare’s check-in rewards system seems to have championed this strategy.    
  • Personalization/Segmentation: Location-based startups should also focus on personalizing as much as possible when trying to acquire new customers. This means offering a different type of service for different customer segments. LinkedIn has done a great job of this. There is a free service for the 80% of customers who only use the platform a few times a year. Another 15% of the customer segment, who use the product monthly or weekly, pay for a slight business upgrade. The final 5% who use the service daily pay for the most expensive “executive” version—with expanded product features. But personalization should move beyond product lines to also include targeted marketing and sales campaigns so that potential users are finding out about the product through channels that appeal to them most.   
  • Focus on Branding: Location-based startups can also attract customers by building a really strong brand. Brand loyalty seems to be mostly based on three things: differentiation, relevance and emotion. Some examples: Apple has built an incredible brand around the concept of aesthetics and beautiful design. Etsy has built a brand around homemade/vintage goods.  Focusing on the above 3 keys to build a really strong brand can, in turn, attract customers.
  • Customer Service: One way to really attract customers (and to also differentiate from the competition) is to provide strong customer service. This entails providing a high quality service or product experience, showing support for customers during and after the sales process, developing customer loyalty programs and creating a customer service team with a 100% focus on customer satisfaction.