San Francisco is the new center of start up activity

tl;dr Start up fund raising is growing across the board and increasing in geographic diversity.

The new year presents a great opportunity to look back at trends in start up activity and fund raising. Pitchbook has created a great summarization of start up funding and valuations from 2013.



We can see that aggregate dollars raised in 2013 is up slightly from 2012 but both down for the peak in 2011. Let’s examine geographic dispersion to better understand and visualize the broader trend. Thanks to Crunchbase’sopen platform and Google’s geocoding, there is raw data to analyze.

The Maps


Venture capital raised in 2013, by US Region.


As also reported by CB Insights, California dominates start up funding with New York and Boston closely following. This static view of the distribution of fund raising activity doesn’t present the full picture. Inspired by a beautiful Foursquare visualization, where check ins represent the heart beat of a city, I’ve taken a pass at representing the heart beat of the US economy through start up activity.

Some GIFs


Venture capital raised, by US Region. Each frame is one year.


In the animated gif above, each frame is the funding data for one year starting in 2005 through 2013. 2005, investment is mainly centered in NY, SF and Boston with little start up activity in more diverse areas. These central tech hubs see large gains over the 8 years covered. As the decade progresses, the start up community begin to also grow in Dallas, Austin, Raleigh NC, Seattle, DC, Chicago and beyond. Some of these secondary cities have now grown beyond where NY and Boston started. In a network effect business, which I would argue includes technology start ups, solving the chicken and egg problem is the most difficult. Now that technology start ups have passed a reasonable scale in the top 10 US cities, we can hope that the pace of innovation will continue to accelerate. There are benefits to starting a company in Silicon Valley but the success of some large unicorns outside of the bay area proves it is not a requirement (this is a big enough topic to warrant an independent post).


Venture capital raised, by CA City. Each frame is one year.


In the more mature tech market of California, the center of gravity has moved north from silicon valley to San Francisco proper. In the mid aughts, Silicon Valley and San Jose represented the majority of the Bay Area investment. As the teens turn, San Francisco became the focal point for start up activity. We also see that LA and San Diego have continued to grow in terms of raw investment dollars. I expect with the recent sale of a company like Gravity1 that the LA area will continue to see new investment.


Venture capital raised, in SF Bay Area. Each frame is one year.


Zooming into the Bay Area, we see that aggregate dollars raised is increasing and spreading out. The center of gravity has become San Francisco. The bay area, like the US and CA, sees increased geographic distribution. There has been increased investment beyond Palo Alto distributed across communities like Berkeley, Mountain View, Fremont and San Jose.


Start up fund raising is growing across the board and increasing in geographic diversity. In new start up empire, all roads lead to San Francisco.

Code and Data

Here is a R script for generating graphs and see Crunchbase for the raw data.

  1. Redpoint portfolio company. 


When to raise using Crunchbase data

 tl;dr the likelihood of a follow on financing peaks at around 9 months.

When I worked at Google and later at Hotel Tonight, data that represented actual user activity (search, click, purchase events) was always more valuable than the best academic model. For the venture industry, fundings are the most public data for start up behavior. Crunchbase represents a treasure trove of this great start up data.

In my first post, I took a look at how much start ups raise. I concluded that start ups should target 12 – 18 months of runway. As a follow up, I want to take a deeper look at timing. The empirical cadence and timing of funding can hopefully inform time lines.

By reconstructing the start ups funding history represented by the crunchbase data, we can observe how likely start ups are to raise a subsequent round after an initial financing. Note not raising another round isn’t necessarily a negative signal. For the purpose of this analysis, we’ll take a simplifying assumption that start ups below a Series C will require subsequent financing to be successful (reach profitability or acquisition). Also, Crunchbase represents publicly announced funding. For this analysis, it is assumed that delays in announcements affect each round equally in aggregate.

The Numbers

Median First Raised Amount

Looking at the fraction of start ups, that subsequently raise at any point after a number of months after financing, will demonstrate an empirical likelihood. Start ups at different funding round stages (Angel, A, B …) should be considered differently as they have different risks and capital requirements. The median time between rounds increases in subsequent rounds but not by much. The median successful start up in any round raises after about a year.

Likelihood of Raising a Follow On Round by Time.

Angel and Venture stage companies behave very similarly and are much less likely than a Series A or B to have a follow on round. For Angel start ups, the likelihood of raising a subsequent round monotonically decreases with each month from their seed round. Series A and Bs behave similarly (with As consistently less likely to raise another round at each). Their likelihood for a subsequent financing peaks at 9 months after financing. Intuitively, this makes sense. If start up valuations (and likelihood of fund raising) only increases on mitigation of risk, 9 months seems like the point at which start ups prove their model. Whether this is a scalable business model, a distribution channel, or product engagement, start ups need to be razor focused on it. The peak probability of raising is very quickly after your last raise.

The discrepancy between Angel rounds and Series A and B could be explained by differences in the round size. Decomposing the trends by both round and amount helps eliminate the interaction.

Likelihood of Raising a Follow On Round by Amount.

Looking first at Angel rounds, the likelihood increases with an increase in the initial funding amount. While this makes sense, this is correlated and not necessarily causal. This may be a reflection of the type of companies that command a large seed round. After the venture and angel rounds, the peak likelihood for Series A is actually $5-10M rounds and the max for Series B is $20-40M. Interestingly, there is not a clear correlation between round size and likelihood. It seems like there is a sweet spot in an amount to raise but more isn’t necessarily better on later rounds.

Likelihood of Raising a Follow On Round by Category.

Finally, let’s look across start up categories. Most categories show similar trends, with the primary difference being the aggregate likelihood (e.g. at month 0 Advertising at ~40% vs Ecommerce at ~30%). In categories that are about scalable business models, ads, biotech, and enterprise, there is less of a lottery ticket consumer adoption model. Within these categories, non-seed rounds have a significantly higher likelihood of raising. Presumably these companies have already proven a business model and value proposition. They are raising additional funding to scale with the goal of increasing marketing or hiring addition sales people.

For categories, where consumer adoption is the primary risk, mobile, video games and to some extent ecommerce, there seems to be similar risk levels at each round. These companies either hit it and find a scalable distribution model or don’t. Every month without that hockey stick just eats into the war chest.

In summary, the likelihood of a follow on financing peaks at around 9 months. As we saw previously, there is a right amount to raise to maximize likelihood of subsequent rounds. Interestingly, as with funding amount, timing also varies dramatically by category.

Code and Data

Here is a R script for generating graphs and see Crunchbase for the raw data.


How much to raise using Crunchbase data

tl;dr Raise enough to hit the next milestones to raise the next round plus a healthy buffer.

After starting PrimaTable in 2011, raising a seed round and selling to Hotel Tonight and now sitting on the other side of the table, I’ve been asked: How much venture funding to raise? Fund raising can be more art than science with a competitive process that dictates terms. In this post, let’s take a quick look at the data.

It’s been written about before:

  1. Tom Tunguz “Raise enough money to achieve a set of milestones that will attract a subsequent round of investment from new investors.”
  2. Mark Andreessen1 “Raise as much as you can without giving away control of your company, and without being insane. … In a normal scenario, raising more money rather than less usually makes sense, since you are buying yourself insurance against both internal and external potential bad events.”

Thanks to Crunchbase, there is data to examine.

The Numbers

Cumulative Distribution of First Round Amount.


Looking at the distribution of the first round amount (restricting to only recent companies first funded between 2010 and 2013), the median is $1.2M with few extreme outliers. While this itself is informative, further funding history is a layer deeper. Raising a subsequent round can be viewed as a signal for some success, as other people have done (Benn @Mode).2

Follow On by First Funding Amount.


There seems to a positive correlation between the initial fund raise amount and the likelihood of a follow on round. Note, this is clearly an instance of correlation and not necessarily causal. The companies that raise more money may be more likely to succeed or better able to raise a subsequent round of funding. There are likely exogenous factors that influence follow on rounds. However, the relationship makes sense. In order for it to also reflect the collective wisdom on fund raising, the relationship should demonstrate a very specific activity based on individual company dynamics.

Follow On by Category.


Decomposing fund raising impact further by category, the positive correlation in general persists but varies dramatically by category. In many categories, Biotech, Cleantech, and Software, there is no explicit relationship. Companies that have raised larger initial rounds haven’t converted to a second round at a greater rate. In the case of Mobile, the relationship is the inverse. Mobile companies that have raised more are in general less likely to raise a follow on round.

Median First Raised Amount


In addition to differing relationships with additional funds, the aggregate amounts across category varies. The median amount raised when conditioning on follow on rounds varies wildly. In ecommerce, the median first round for companies that raised a further round is $1.3M vs just $.5M for companies that haven’t.


This data can help substantiate the thesis that you should raise enough to hit the next milestones and mitigate risk with a sufficient buffer to weather the inevitable bumps. Valuation for startups only increases on mitigation of risk. For example, in some seed stage companies, this can mean mitigating technical risk and building a working product. For a series A, this might mean finding product market fit and showing user engagement. For later stages, this can be demonstrating a scalable distribution channel and business model. Regardless of the stage, future rounds will necessitate mitigation of risk.

Mark argues to mitigate financing market risk by raising at the max of the range that is possible. This make sense to protect against macro changes that change fund raising dynamics as well as gives as much fuel to hold on as long as possible. This can be detrimental because this ups the level of risk that must be mitigated prior to a subsequent round.

In practice, for most early stage startups, the increments of funding look to be 12 – 18 months of runway. The round size varies with the team but you can use a rule of thumb of $125K / developer / year ($100K salary + 25% expenses).

In summary, raise enough to hit the next milestones plus a healthy buffer.

Code and Data

Here is a R script for generating graphs and see Crunchbase for the raw data.

  1. As quoted on Venture Hacks from an old post subject to link rot
  2. This neglects bootstrapped companies, companies that reach profitability or companies that sell, not requiring subsequent financing.