Zirra SUN100’s Top VCs

The Top VCs With the Most Portfolio Companies in Start-Up Nation’s $100 Million Club

Carmel Ventures, Vintage Investment Partners, and Marker LLC are among the VCs with the highest concentration of highly valued Israeli startups, according to recent research by Zirra. In order to rank VCs according to their achievements, Zirra, a research firm, used its proprietary algorithm to value Israeli startups, extracting 163 companies that were found to be worth over $100 million. Zirra then ranked the VCs invested in these companies by the size of the portfolio, from highest to the lowest. VCs that were ranked higher have the largest number of startups that are valued above $100 million (without taking into account the exact valuation). Since 2016, Zirra has produced a ranking of Israel’s $100M+ startups in what they call the SUN100 (Start Up Nation $100M club).

VCs that are ranked lower on this list are still considered to have a relatively high concentration of highly valued startups. We mentioned only five or more portfolio companies and excluded all the rest, as most of the investors do have between one to four such companies in their portfolio.

Some major qualifications to the ranking list must be mentioned:

*Not everyone in this list are VCs: Some non-VC financial enterprises are involved in either investing or lending money to the SUN 100 club, including Silicon Valley Bank, which is a bank focused on tech companies, and Viola Credit (formerly Plenus), a lending fund. In addition, OurCrowd is a crowdfunding platform, and Mitsui is a corporate VC. Two VCs in the list have decided not to raise new funds and to focus on their existing portfolios: Gemini Israel Ventures and Genesis Partners.

*Incumbency advantage: Incumbent VCs have a natural advantage over younger VCs for the simple reason that they have been around longer. Most of the VCs listed here were established during the 90’s or the early 2000’s, such as Carmel Ventures which was founded in 2000, or Vintage Investment Partners, which was formed in 2002. Nevertheless, there are some nuances worth noticing: US-based VCs may exist longer than their Israeli counterparts, but their presence in the Israeli startups ecosystem is a newer phenomenon. Bessemer opened its Israeli office only in 2007, and since then has steadily increased its investment in the Israeli market.

*The list is by no means proportional to seniority. Older funds are not necessarily ranked higher, and vice versa.

*Having a lot of $100 million+ valued companies is not always as good as it sounds. A bird in the hand is worth two in the bush. Therefore VCs counts big exits more than large enterprises. After all, what’s the point in having ten companies of $100 million and above if none of them are about to be sold for a higher valuation or go public? Therefore, having four or ten large enterprises in a portfolio is only a part of the big picture, and exits should be taken into account too.

*On the other hand, having a lot of good companies says something about your investment capabilities. And VCs use their portfolio of high valuation companies to help them each time they are raising their next fund.

*More top rated VCs will not necessarily have higher returns. What counts is the share of each portfolio company the VC holds, and their portion of any exit. A significant proportion in a $300 million company that isn’t get bought for years but lacks the growth to go public can end up as a failure in the eyes of a VC.

How Do We Value Companies?

The output of the Zirra Valuation Process is by no means a company’s real valuation. What we do is estimate the real-time valuation, as if the company had a stock traded on the public market, taking into account market momentum and industry characteristics,  while excluding effects such as a tech bubble or PR and marketing campaigns.

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The valuation process involves both Intrinsic and Relative valuation algorithms. The Intrinsic data includes revenue and expense estimations, traffic trajectories, advertising campaigns measurements, investment history and velocity, based on aggregated sources.

In the Relative analysis, data is compared and benchmarked with a database of thousands of companies with correlation to stage, space, size and trajectory. This produces a preliminary set of company ratings and valuation metrics. For example, the algorithm concluded that teams of up to 3 co-founders, each specializing in his/her field of business, technology or marketing leads to growth, whereas teams of 4 or more co-founders carry a higher degree of risk. The machine learning algorithms track the growth of companies, arrive at conclusions independently and dynamically adapt for future analysis.

We then produce a map of competitors based on the data set, rated by the degree of direct competition, its size, threat, and proximity of the shared customer and partner base. Results are sent to relevant experts that comment on both quantitative analytics (scores and metrics) and qualitative analytics (risks, opportunities, competitors).

Where do we get the data from?

Data is extracted from 85 different data sources, regularly updated (daily to weekly). Sources include both open and licensed directories such as the company website, Bloomberg, Linkedin, SimilarWeb and Adwords; It can be “derived data” such as Glassdoor reviews, consumer reviews, sentiment analysis from open web articles; or other data points such as academic researches, stock indexes, and macro-economic parameters.

Companies With Significant Milestones in This Quarter’s list

Gett

Taxi ride-hailing app Gett is still Israel’s highest valued private tech company. The company’s status got even better this quarter, as the Israeli automotive ecosystem was upgraded with the acquisition of Mobileye by Intel for $15 billion and the decision by Intel to make Israel its automotive powerhouse. A little less than a year since the $300 million that car maker Volkswagen had put into Gett, there is still no sign of a significant cooperation between the two on a service or a product.

Still, Gett continues to grow in European markets such as Russia and the UK. Gett’s acquisition of Mountainview House Group in the UK gives them control over black cab brands Radio Taxis and Xeta as well as corporate transport platform One Transport. As a result of this acquisition Gett is the biggest taxi app in the UK, with over 11,500, taxis in London alone.

Gett claims to be the market leader in Europe in terms of volume of rides, revenues, and profits. Within Europe the service is currently live only in Russia and the UK, indicating much more room for growth and building on their market lead. Despite talk over five years ago of launching in France and Germany, Gett has not yet entered those markets.

In France, Uber has taken a leading role but met with serious resistance from Taxi drivers and from the French government. German companies MyTaxi and Taxi.eu lead in Germany, where Uber has run into issues and been forced to leave all but Berlin and Munich.

According to Zirra research, Russia is Gett’s fastest growing market, in terms of growth in Android and Apple’s app stores, and in terms of web traffic. Still, Gett is not the biggest taxi app in the country. It is overshadowed by Yandex, which accounts for 55% of all taxi rides in Moscow, with Uber and Gett handling about half of the remaining 45% of rides in the city.

In the US, Gett’s initial attempt at penetrating the market has not been as successful as they hoped. Despite strong marketing efforts, attractive fixed fares, and CEO Shahar Waiser moving to New York, the company’s business in the city is not yet profitable and trails behind
competitors.

In recent months, Gett has been expanding its offerings into delivery, allowing businesses to call for couriers. According to a Zirra survey, a significant number of respondents were open to trying Gett’s delivery service if prices are low enough.

Trax Imaging

Raising $19 million about 2 months ago, Trax imaging joins Amazon in the race to commercialize in-store computer vision tech. Trax allows grocery store employees to capture images of the current retail situation in stores and through deep analytics in Trax’s cloud, insights and reports are delivered to management teams for the purposes of optimizing stocking cycles and tracking products and promotions. Now Trax is arriving to consumers as well, allowing them to find desired products in real time or suggest alternatives. Soon, Trax will be able to compete with Amazon Go’s cashier-less stores. But Trax is not alone in the market, as many established companies are already developing computer vision-based solutions to retail such as IBM, Oracle, SAP, Microsoft, and smaller companies such as Planorama, RetailNext and Symphony Gold. [Read here for Zirra’s full spotlight report on Trax Imaging]

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Kaminario

Kaminario, a developer of a high performance all-flash array storage system, passed the $1 billion valuation this quarter, thanks to a $75 million financial round earlier this year. After a couple of years trying to convince enterprises to deploy more SSD-based storage, EMC started to sell a competing system, ExtremeIO, thus educating the market, and making it large enough for Kaminario’s flash-based product. In 2014 the company achieved a world record in speed of storage and a very high reliability, making it a valid competitor to EMC. 2015 and 2016 were excellent in sales, bringing the company toward $100 million in annual revenue run rate. The company also grew in terms of size, 111% in two years, not bad for a company that was founded in 2008. [Read here for Zirra’s full spotlight report on Kaminario]

OrCam

Taking advantage of the momentum he has created with selling Mobileye to Intel for $15 billion last month, computer vision scientist Amnon Shashua announced a new $41 million round from unknown investors for another tech company he had founded: OrCam. According to Reuters, the new round that was announced only this weekend values OrCam an $600 million, while Zirra’s valuation algorithm estimates OrCam’s valuation at $569 million. This puts Orcam straight as the 18th highly valued private tech company in Israel, according to Zirra.

OrCam takes the computer vision abilities of a company such as Mobileye’s obstacles detection on the roads to help blind or visually impaired people to “see” better by reading them in headphones what is in front of their eyes. A tiny computer that is attached to the side of a pair of glasses read today’s news or a sign, recognize faces and facial expressions, and helps them to function almost as anyone. All they need to do is activate the visual engine by pointing to the object.

The device has just launched to market in 2016, and according to Shashua will become profitable in 2018 and then will consider a listing in New York.

How Do We Valuate a Startup?

The highlight of the meeting with Prof. Aswath Damodaran was about fifteen minutes after we had taken our seats. We were sitting in his office, in front of (probably) the most popular professor at NYU, when he was suddenly giggling: “Every company and investor has their Bar-Mitzvah moment,” he said. “The moment in which laws and principles are binding and twisting without notice. Then comes the moment in which a kid, measured by his future potential, turns to be an adult, measured by performance.”

It’s easy to misinterpret Prof. Damodaran. He is open-minded, lighthearted, fluent, but you know you can’t blink. By doing so you might lose an extremely important insight that comes out of his mouth. “The smart thing to do is not to realize this at your Bar-Mitzvah ceremony, but much before that,” he continues. “This feeling, that comes way ahead, is the principle that distinguishes Facebook from Twitter. The latter will stay 13 forever because it didn’t realize the sudden transformation to a market that measures each user by financial standards.”

Prof. Aswath Damodaran, NYU

Later on, we discussed other companies and markets’ Bar-Mitzvahs, figuring out precursors (“a migration of employees and customers”), seminal events during companies’ lifecycle (“Lawsuits in progress and other stuff swept under the rug”), and how to frame all of it into a general and a valuable model.

In Damodaran’s eyes, we saw the same curiosity that brought us to establish Zirra. And his voice made us realize that not only is the industry experiencing a Bar Mitzvah, but we are as well. This is a great feeling, despite the changing voice and the hair that suddenly appears on the face.

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The Age of Transparency

The private tech industry is one of the most secretive and mysterious – yet it is rich and growing rapidly. It is one big black box for most of us, but not only to us; those who are working in the startup ecosystem themselves, entrepreneurs, venture capitalists, reporters, lawyers, and accountants, are suffering from serious disinformation regarding the economy that surrounds them.

The black box of the private tech business

On the face of it, the startup ecosystem is quite noisy. You hear daily about new financing rounds, sometimes four of five a day, and about an unending array of product launches. Each day tech growth companies raise dozen of millions of dollars, echoing their funding achievements throughout the press and on social networks. But you can rarely guess the price tag a company gets as a byproduct of the round. And you will never have a clue about how much the company is making or how much it is going to spend in the years to follow.

This is quite understandable from the point of view of the entrepreneur. It seems that no one wants to reveal his company’s losses or discuss the fact that its first revenue is going to be five years from now.

Also, exposing one company’s valuation will anchor the market to a number that might go down in the future if something goes wrong. Wishing to prevent such an embarrassment, entrepreneurs prefer not to talk about valuation at all unless the company they run is too big for the number to stay a secret (e.g. Uber, Airbnb, Snap). In that case, analysts and investors disclose that number willingly, although off-record.

Discussing the cap table is also a taboo. Investors and entrepreneurs like to keep the cards close to their chest. But, imagine a world in which the cap table is transparent, allowing everyone to tell the difference between abusive and fair investors.

The result of this panoply of secrets, taboos, and mysteries is enormous disinformation surrounding the startups market. The only information that is already outside is the PR: which company raised money and when did they launch their products.

That is not enough if you’d like to make your way in the industry. If you’d like to invest wisely as a VC investor, to know better your competitors as an entrepreneur, to choose wisely your next job, or even to produce a better coverage as a journalist or an analyst, it is simply not enough.

How to Valuate a Startup

Here at Zirra, we decided to do something about that. We have made it our mission to bring transparency to the private tech market.

First, we set out to valuate tech companies. But how do you assign a value to a startup company? As the valuation guru, Prof. Aswath Damodaran, would say you should take into account the company’s discounted cash flow, growth, and risk. This is intrinsic valuation. Then, you’re allowed to use a relative valuation based on other companies in the field, using standardized metrics and multiples.

But what happens when you don’t have the intrinsic data on the company? This is commonly the case. Entrepreneurs are not going to start disclosing revenue data or their discounted cash flow in the next few years.

Usually, a startup in its first year doesn’t make any revenue, and it invests most of its capital in future growth. This could mean hiring new engineers, building new products or growing their marketing team. The cash flow, then, is an imaginary number predicted by the management, and it stays that way until the company is significantly growing. And, there is nothing wrong with that, says Damodaran. The investors expect the company to lose money – even in areas that hadn’t been thought of.

That’s why, according to Damodaran, that in the new digital economy companies are usually evaluated by the number of users.

In the startup economy growth in users, engagement, or momentum might say a lot more about the company than its current cash flow. But it may also have some implications for the future of company’s revenue.

We at Zirra took the challenge to break the taboo and tell how much a private company is worth. We do that because we cherish the same factors cherished by investors: growth, product adoption, engagement, momentum, brand power, funding, and a healthy team. We do that because we also take into account external risks like fierce competition, a non-existing or too-early market, a lack of funding or an inexperienced team.

We assume we don’t know everything, but we built a good-enough model that helps us manage both intrinsic and relative valuations, based on public data. By doing so we try to challenge the valuation of the company as it appears in the financial books. We don’t claim that our estimated valuation is the ultimate true valuation of the company, but we do try to make it as close as possible.

Is the valuation of the company written in financial books locked deep inside an accountant’s safe the real valuation? Not necessarily. A few factors such as preferred stocks and a hot investment market can inflate the company’s valuation in an artificial way. And that’s exactly what made us develop our own algorithms: We’d like to put a solid mirror in front of those numbers and to pull away from the bubble effect.

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Zirra’s Estimation Process

Zirra has developed AI and machine learning technology to effectively analyze the private tech market. It provides insights on startup companies, including estimated valuations, competitor lists, estimated time to exit, risk and success factors, as well as ratings of the team, product, momentum, and execution. Based on its technology, Zirra serves investors, entrepreneurs, and job-seekers with spotlight reports on companies that help them learn more about the companies they are engaging or competing with.

The Zirra valuation process involves both intrinsic and relative valuation algorithms. The intrinsic data includes revenue and expense estimations, traffic trajectories, investment history, and velocity, based on aggregated sources.

In the relative analysis, data is compared and benchmarked with a database of 1,200 companies with correlation to stage, space, size, and trajectory. This produces a preliminary set of company ratings and valuation metrics. For example, the algorithm concluded that teams of up to 3 co-founders, each specializing in his/her field of business, technology or marketing leads to growth, whereas teams of 4 or more co-founders carry a higher degree of risk. The machine learning algorithms track the growth of companies, arrive at conclusions independently, and dynamically adapt for future analysis.

We then produce a map of competitors based on the data set, rated in accordance with the degree of direct competition, its size, threat, and proximity of the shared customer and partner base. Results are sent to relevant experts in our expert community, which is already over 450 experts strong. Experts comment on both quantitative analytics (scores and metrics) and qualitative analytics (risks, opportunities, competitors).

Where do we get the data from? The data is extracted from 85 different data sources, and is updated regularly (daily to weekly). Sources include both open and licensed directories such as the company’s website, Bloomberg, LinkedIn, SimilarWeb, and Adwords. It can be “derived data” such as Glassdoor reviews, consumer reviews, sentiment analysis from open web articles; or other data points such as academic researches, stock indexes, and macro-economic parameters.

Zirra’s Full Valuation Process

A. Data Collection – The data fetched from 85 different data sources such as:

  • Information derived from open and licensed directories (e.g. CrunchBase, Bloomberg), LinkedIn, the Company Website, SimilarWeb, Google Adwords research.
  • Sentiment analyzed from open web articles, consumer reviews, business reviews or Glassdoor.
  • Other data points such as academic researchers, macro economic parameter or stock indexes.

B. Analysis:

  • Relative Analysis – The data is compared and benchmarked with a database of 1,200 companies with correlation to stage, space, size, and trajectory. This produces a preliminary set of company ratings (comparative scores) and valuation metrics.
  • Intrinsic Analysis – Revenue and expense estimations, traffic trajectories, investment history, and velocity. The intrinsic valuation fine tunes the relative valuation based on intrinsic (DCF) and averaging algorithms.

C. Expert curation – results are sent to relevant experts from our community of over 450 experts. Experts comment on both quantitative analytics (scores and metrics) and qualitative analytics (risks, opportunities, competitors).

D. Output:

  • Metrics:

Valuation – Estimated company valuation assuming it was traded today in the open market.

Exit Valuation – Estimated company valuation at time of M&A or IPO.

Chances of Exit – Chances of successful M&A or IPO, at a value higher than current valuation.

Time to Exit – Expected average time between today and a successful exit.

  • Qualitative Sets:

Risk & Opportunity Analysis – The data is scanned with 300 business rules which produce risks and opportunities the company is facing based on the data set.

Competition Analysis – Competitors are collated based on the data set and rated in accordance with the level of direct competition, the size of the threat, and proximity to the shared customer and partner base.

  • Ratings:

Product Rating– Product rating is a factor of customer reviews, analysis of product sentiment on the media, current hirings, Google trends analysis of product searches, IP search, usage metrics (downloads, Similar Web), and others.

Team Rating– Team rating is a factor of the LinkedIn recommendations, record evaluation, social sentiment analysis, success and seniority track record, social media feedback, success as previous entrepreneurs, managers, investors, and more.

Momentum Rating– Momentum rating will rate the company’s progress, pace, and acceleration of translating their vision with execution.

Momentum will be rated by Alexa and Similar Web trajectories, funding history, frequency, and sentiment of media & news analysis, usage history of the product, and others.

Opportunity Rating– Opportunity Rating will encompass the potential opportunity the company is facing should it execute successfully. This will include the potential market size and addressable market audience, the competitive situation – direct and indirect, and how they all translate to ROI potential.

Opportunity will be rated based on Google Trends analysis of the sector to validate growth, general sentiment analysis towards the sector,and a competition or a lack of a competition within a sector.

Vision Rating– Vision rating will rate the company’s ability to effectively align, arrange, and strategize. This will include their clear understanding of the market, translating that to a marketing and sales strategy, business model, required innovation, end-to-end solution providing and setting the stage for market leadership years down the road.

Vision will be rated based on social media and media sentiment analysis, a rating of the visionary capabilities of the founders, by a combination of the product ranking as well as team ranking and more.

Ability to Execute Rating– Ability to execute rating will rate the company’s ability to deliver on its vision effectively. Can the company translate their vision to independent operations, intellectual property, regulatory and compliance issues, eco system support, and required financial depth.

Ability to execute will be rated based on the combination of team ranking, product ranking, ratio of existing funding to remaining funding needs, as well as external factors such as the state of regulatory clearances and other external dependencies that can impact the company’s ability to execute.