We Are Updating Mattermark’s Company Ranking Algorithm & Introducing the Growth Score

Published on in Product Updates , by

Today we are excited to introduce our first official update to the company rankings in Mattermark. The “Mattermark Score” has been split into two new indicators, each with more descriptive names: the Growth Score and the Mindshare Score. Our job is to help dealmakers find the most promising prospects, and these scores are algorithms we’ve created to filter out the signal from the noise. We weigh billions of data points to return a useful ranked list organizing the 800,000+ companies in Mattermark.

The Growth Score is now the default ranking for all companies in Mattermark. It works by counting a company’s website visitors, mobile downloads, social media metrics, employees, and publicly announced funding, all tracking how these numbers change over time. The underlying assumption is that companies who see growth across these signals are shipping product and talking to customers, and are more likely to continue to grow as a result.

The Mindshare Score is the original Mattermark Score with a new name. It combines web, mobile and social traction to summarize a company’s growth of online attention. Think of it as a subset of the Growth Score that accounts for social signals and the company’s ability to gain and retain attention online.

To get a sense of how today’s update changes the default list of companies you’ll discover on the first page of results in Mattermark, take a look at the different between the results when sorted by highest Mindshare Score (the old Mattermark Score) versus the new Growth Score:

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As you can see, these new rankings move several unicorn startups to their rightful spots in top positions, and reveals many of the fastest growing and most valuable private companies. Applying additional filtering such as stage and geography helps bubble up opportunities that fit with specific prospecting criteria.

For example, take a look at the top ranked Series C stage companies in the Bay Area:

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How Are These Scores Calculated?

Our original rankings began with the Mattermark Score, which is an algorithm created by Danielle Morrill, Kevin Morrill and Andy Sparks — the founders of Mattermark. The Mattermark Score is still in use today, but as we continue to collect more data and learn more about the problems we are solving it has become part of a larger set of algorithms that power scoring and ranking of companies.

These algorithms are extremely valuable to our business, and will remain “black box.” The exact formulas for calculating these scores, which will continue to evolve over time, are not going to be revealed. Users can observe the inputs (the same raw data you can view in Mattermark) and benefit from the output (the company rankings) but what happens in the middle is the secret sauce we’re developing. Instead of agonizing about how we’ve built our scoring system, we encourage customers to use our data to build their own models and deepen their analysis to get an edge beyond what we provide.

Mattermark customers also can also build their own scoring algorithms by applying custom weights to the dataset through our web-based interface. Any Mattermark customer can run ad-hoc models against our entire set of companies, returning the results of their Custom Score in seconds. To give you some sense of how powerful this can be, just try doing the same thing with a 800,000 row spreadsheet in Excel.

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Garbage In, Garbage Out

A model is only as good as the data put into it, and that’s why we’re on a mission to deliver the most comprehensive historical dataset of business growth signals. The universe of companies we currently cover includes more than 800,000 startups, technology enabled service businesses, and other businesses with rapidly growing online presences.

Beyond broadening company coverage, we are doing groundbreaking work in cleaning and organizing business information using machine learning (and we’re hiring!). Mattermark is your outsourced data science team, building the data collection, machine learning, and analysis processes to give you deal prospecting superpowers at a fraction of the cost. Our customers’ expectations for the kinds of questions they should be able to answer, and data we should make available, will continue to climb as we open up new lines of questioning.

Udi Manber of Google said it well in a 2010 blog post:

“One of the key things about search is that users’ expectations grow rapidly. Tomorrow’s queries will be much harder than today’s queries. Just as Moore’s law governs the doubling of computing speed every 18 months, there is a hidden unwritten law that doubles the complexity of our most difficult queries in a short time. This is impossible to measure precisely, but we all feel it. We know we cannot rest on our laurels, we have to work hard to meet the challenge.”

It is not known exactly how many businesses there are globally, but estimates range from 250 to 300 Million and growing. Our goal is to track all of them with Mattermark, and if this first 18 months is anything to go by we definitely have our work cut out for us. Our data set is already growing a millions of rows per hour, and this is just the beginning.

I look forward to sharing many more improvements to our rankings and other tools as we go. If you haven’t yet, please sign up for a free trial and check us out.

Which VCs Have the Most Portfolio Companies with $100M+ of Funding?

Published on in Venture Capital , by

Bill Gurley of Benchmark Capital gave a fascinating interview to the Wall Street Journal, expressing a great deal of concern for the nine digit funding rounds being raised by later stage startups. Interestingly, he wasn’t laying blame at the feet of valuations — it was burn rate that was most worrying, and Fred Wilson chimed in later in the evening, echoing the same sentiment.

While VCs certainly have an obligation to deploy their LPs capital to generate returns, founders also have an obligation to deploy VC money to grow their businesses. Investors are not merely bystanders, they sit on the boards of these companies and are expected to help set their course. With all this in mind, I thought it would be interesting to take a look at which venture capital firms are most complicit in enabling high burn rates, based on the number* of portfolio companies with $100M or more in total funding to date.

VC Firms Ranked by Un-Exited Portfolio Companies with $100M+ in Funding

43 – Kleiner Perkins Caufield & Byers

35 – New Enterprise Associates

31 – Sequoia Capital, Goldman Sachs

27 – SV Angel, Accel Partners

24 – Intel Capital

22 – DAG Ventures

21 – Tiger Global Management

20 – Bessemer Venture Partners, Greylock Partners

19 – Lightspeed Venture Partners

17 – Benchmark, Founders Fund, Khosla Ventures, Silicon Valley Bank

16 – Insight Venture Partners

15 – Andreessen Horowitz, Google Ventures, Oak Investment Partners

14 – Redpoint

13 – General Catalyst, DFJ, Meritech Capital Partners

12 – Technology Crossover Ventures, Tenaya Capital, Venrock, Salesforce, Temasek Holdings

11 – Adams Street Partners, IDG Capital Partners

10 – SAP Ventures, Mayfield Fund, In-Q-Tel, Menlo Ventures, Canaan Partners, VantagePoint Capital Partners, QiMing Venture Partners, Investment AB Kinnevik

9 – First Round Capital, GGV Capital, Norwest Venture Capital, Matrix Partners, US Venture Partners, QED Investors

8 – GSV Capital, Battery Ventures, Shasta Ventures, Northgate Capital, Sigma Partners, Foundation Capital, North Bridge Venture Partners, Kreos Capital

7 – Felicis Ventures, DFJ Growth, Glynn Capital Management, Qualcomm Ventures, Morgenthaler Ventures, Polaris Partners, Mohr Davidow Ventures, InterWest Partners, Rho Capital Partners

6 – Silver Lake Partners, Scale Venture Partners, Spark Capital, Balderton, Samsung Ventures, DCM, Crosslink Capital, El Dorado Ventures, Bain Capital Ventures, Flagship Ventures, Sofinnova Ventures, Bezos Expeditions, Vulcan Capital, TPG Growth, Google Capital

5 – RRE Ventures, Ignition Partners, Great Oaks Venture Capital, Deutsche Telekom, Fidelity Ventures, General Atlantic, Focus Ventures, Western Technology Investment, Presidio Ventures, Investor Growth Capital, ARCH Venture Partners

4 – CrunchFund, Rocket Internet, Flybridge Capital Partners, Union Square Ventures, Hummer Winblad, Sutter Hill Ventures, Trident Capital, Canvas Venture Fund, Alloy Ventures, Wellington Partners, Atlas Venture, Wellington Partners, Star Ventures, BDC Venture Capital, Austin Ventures, Aisling Capital, Alta Partners, TA Associates, Aeris Capital, Versant Ventures, Columbia Capital, New Leaf Venture Partners

*For the sake of brevity, I cut the list off after 4.

Curious to learn more? Research these portfolios, their underlying companies, employee counts, burn rates, etc. sign up for a free trial of Mattermark Professional today. SIGN UP NOW

Why Ranking Startup Investors Matters For Founders

Published on in Venture Capital , by

At Mattermark we’re all about answering questions with data, arming investors, founders, sales, marketing, biz dev, M&A — any dealmaker, with the information they need to intelligently move forward with a transaction.

For founders, ranking investors can help answer extremely important questions:

FUNDRAISING: if you want to ensure you’ll raise your next round, which is the best firm to work with? (first attempt at these rankings is here) if you want to ensure you won’t waste your time, which funds are actively investing right now? (the original “zombie VCs” post that started it all) at which stages and in which sectors? TEAM: if you are expecting a firm to create value-add in recruiting, which firm’s portfolio companies have been most successful at hiring after raising from them? (see our first attempt at these rankings here)

TRACTION: if you are expecting a firm to create value-add in marketing/sales, which firm’s portfolio companies have been most success increasing their momentum after raising? (first attempt here)

MARKET: if you’re working to ensure a range of exit options for your company, which firm’s portfolio companies have been most successful in M&A transactions and/or IPOs?

BOARD CONSTRUCTION: within each firm, which partners have the best returns, follow-on funding rates, recruiting, distribution, etc?

PRODUCT: what firms have produced the most companies with products that have real product/market fit? Which firm’s portfolio companies have survived product pivots the most successfully?

I’ve tackled some of these questions with four unique analyses… but we still have a long way to go to collect all the data needed — especially when it comes to partner attribution and actual fund performance data. As Jonathan Weber of The Information explains in his post last week (paywall), historically the VC industry has been extremely opaque.

There are other questions we could answer but choose not to focus on, like which investors have made the most investments or deployed the most capital. While these are interesting questions from a macro perspective, I don’t believe they actually help founders make the decisions listed above.

How You Can Help

If you are an angel investor, venture capitalist, limited partner or founder who would like to work with us to move data-driven answers to these questions forward we would love to do a data exchange with you. Please feel free to email me directly at danielle (at) mattermark.com

If you are a technical analyst (read: has scripting and database skills), software engineer with a focus and experience in machine learning, deep learning, neural networks, artificial intelligence — or simply love this data and these questions and want to spend all day every day working to answer them you should know Mattermark is hiring! Check out our open jobs.

Mattermark is the premier source for private company research, utilized by the world’s most influential venture capital firms to source, track and diligence potential investments. Sign up for a free trial or learn more here >>