Introducing the Capital Concentration Index™

A measure of startup competition.

Sebastian Quintero
Dec 20, 2017 · 6 min read

How can we measure competitiveness in private startup markets? And what does it really mean when a company raises over $100m in institutional venture capital? Lemonade ($120m), Vacasa ($103m), Compass ($450m), Slack ($250m), Reddit ($200m), and Peloton ($325m) — these companies have all recently raised massive rounds of capital, but in the absence of competitive context, isn’t the absolute value of a single round of capital for a random company a bit of a hollow statistic? Where do these capital injections position the aforementioned startups vis-à-vis their unique competitors? These questions have occupied my mind for quite some time.

Economics, more specifically the field of Industrial Organization, has a long tradition of measuring market concentration and competitiveness. However, current standard measures are usually based on realized market shares. In private markets, and for early-stage startups in particular, it’s impossible to assess market share. Not only do startups rarely disclose the information that would allow us to calculate those statistics—often times they’re focused on developing a product idea, and the product isn’t even available for purchase at the early stage. So how should we think about the competitiveness of a market that has millions of dollars invested by multiple VC firms but no market share data?

The answer is simple — we measure the distribution of capital in the sector.

Inspired by the Herfindahl-Hirschman Index, the Capital Concentration Index™ (CCI) measures the degree to which venture capital dollars are consolidated among competing startups in a sector. It helps us understand how attractive a sector is for entrepreneurs and VCs, and allows us to evaluate how an individual startup’s latest financing event influences their sector’s competitiveness. Not only that, but it ended up being an informative metric for Startup Anomaly Detection™, our state of the art machine learning algorithm which estimates the probability that a startup will exit via an initial public offering or acquisition.

Some simple math

The Capital Concentration Index™ is calculated by taking the sum of the squares of the capital shares for all startups within a sector.

Where c is the percentage capital share held by the i-th startup, and N is the total number of startups in the defined set. In general, the CCI approaches zero when a sector consists of a large number of startups with relatively equal levels of capital and reaches a maximum of 10,000 when a sector’s total invested capital is consolidated in a single company. The CCI increases both as the number of startups in the sector decreases and as the disparity in capital traction between those startups increases.

In venture capital, more recent funding events are more relevant (since capital is burned to push a company forward but then never seen again), so we report the CCI on a rolling three-year basis. Taking a cue from the U.S. Department of Justice and their interpretation of the Herfindahl-Hirschman Index, we describe the CCI as follows:

  • 0-1500 — Competitive: A healthy mix of startups, with more or less similar levels of capital.
  • 1500-2500 — Lightly Concentrated: One or more startups have a mild competitive advantage in terms of capital.
  • 2500-5,000 — Moderately Concentrated: One or more startups have a moderate competitive advantage in terms of capital.
  • 5000-7,500 — Highly Concentrated: One or more startups have a significant competitive advantage in terms of capital.
  • 7500-10,000 — Clear Leader(s): One or more startups dominate the sector in terms of capital.

Some examples

Consider U.S. Influencer Marketplaces, where companies operate two-sided marketplaces that enable brands to connect with influencers for social media marketing purposes. In this space, we’ve identified 12 startups with $91.4m in aggregate capital invested. The top five best-capitalized startups are TapInfluence ($23m), rewardStyle ($15m), Mavrck ($8.1m), Reelio (8.1m), and Influential ($7.5m).

(Left) Funding dynamics for the five best capitalized startups in the sector. (Right) Three year trailing CCI and aggregate capital invested in the sector. Analyzing both charts helps us trace how financing events on the left plot impact the rolling capital concentration levels on the right plot.

Notice how capital concentration started decreasing significantly in 2014 as the current leading contenders entered the space. The CCI for this sector is currently 1404, which suggests a healthy mix of startups with more or less similar levels of capital. Taking into account the magnitudes of capital held by the various startups in this sector, if one were to raise a $100m round—that would be a significant, course-altering event. To contrast, let’s consider that same $100m in the Short-Term Rental Platforms sector. You know—the one defined by Airbnb ($4.4b).

(Left) Funding dynamics for the five best capitalized startups in the sector. (Right) Three year trailing CCI and aggregate capital invested in the sector. Using both plots helps us evaluate how absolute value financing events on the left plot impact the rolling capital concentration levels on the right plot.

The CCI for rental platforms is currently 8451, which indicates that there’s a clear leader that dominates the space in terms of capital. In this competitive context, Vacasa’s $103m round on October 17th, 2017, barely makes a dent (left plot, in red — right plot, small dip in yellow at the end). Airbnb’s economic position dwarfs the competition — effectively deterring entrepreneurs from mounting a direct challenge.

Looking backwards to see forward

Like any good data science effort, the Capital Concentration Index™ leaves us with more questions than answers. Could the CCI help us further understand the evolution of capital in industries now dominated by household names? Earlier this year we mapped out the CCI for social networks (Facebook), search engines (Google), e-commerce retailers (Amazon), and ride-sharing services (Uber). Including capital injected via IPOs produces the dynamics shown below.

Three year trailing CCI for social networks (Facebook), search engines (Google), e-commerce retailers (Amazon), and ride sharing services (Uber).

While clearly the dominant e-commerce platform, Amazon has historically faced considerable opposition from small and large competitors around the world. That’s shown in the competitive CCI levels for the e-commerce retail sector. The sectors defined by Facebook and Google are interesting in having followed somewhat similar capital concentration paths on a shifted timeline. Both social media and search engines were very competitive sectors until Facebook and Google captured the dominant position, with Google’s IPO at ~8 years, and Facebook’s IPO at ~15 years. Even though Facebook’s IPO was monetarily larger than Google’s ($104b vs $23b), it was less significant from a CCI point of view (peak capital concentration was lower). Put another way, Facebook contended in a stronger competitive climate.

Ride-sharing, being the newest of the sectors specified above, is thought provoking to say the least. Uber recently announced a target IPO date of 2019, which would put ride-sharing on track to peak somewhere between search engines and social networks. At the same time, the capital dynamics of ride-sharing appear to be following a path we’ve come across frequently — one of a gradual decrease in concentration followed by intense competition, with no clear winner in the end.

Overall, the CCI provides us with a comparative framework to evaluate the startup competitive lifecycle and gives clear insight into what would otherwise be hollow funding statistics.

By definition, the CCI depends heavily on how a sector is delineated. Slice it too broadly and you have the illusion that a market is competitive — too narrow and you’re left with a sector composed of one or two companies. Luckily we’ve got some really smart people here at Radicle actively working on defining startup sectors and their constituents with the aid of our Disruption Discovery Platform.

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