June 2012

This year, I’ve got a number of startups all gunning for series A. A lot of us have been working on getting these startups to a point where they can present the best possible chance for getting their next round. Then, on the 500startups discussion board, the same topic came up and I posted an answer there. Rather than having it trapped there forever, I thought I’d repost it here (and edit it slightly) for all to take a look at some of things we’re thinking about as we’re prepping our startups for series A:

So what makes you most attractive to landing a series A? Sometimes it can be infuriating to see a competitor get funded and you not. Sometimes you can’t even tell why.

Here are things to work on for your series A, that can help you land one:

1. Relational – if the VC knows you, has a history with you, or even better has had an exit with you, then they will back you. Go out and smooze some VCs now!

2. Interpersonal – Very few VCs will invest in you if they can’t stand being around you. So work on your interpersonal skills.

3. Show entrepreneurial attributes – This is a given. Don’t let them think you aren’t going for the gold even in the slightest.

4. Big market -If your market is not big, you’re in trouble. Better go find one.

5. Vision – It could mean that your vision is big and strong enough. If you have a small vision for your future, or an undefined one, that is much less attractive than if you had one.

6. Traction, showing large/exponential growth – This one is hard to attain at early stage. but then if you have tremendous traction, then why do you need funding? So make them pay up! For some startups, your revenue path is very unclear so you absolutely need to show tremendous traction before you get funded. If you are making lots of money, that’s obvious although then you have to show how much *more* money you can make – making $1M is awesome but if you can only make $5M max, that’s not so awesome to a series A VC.

7. Understanding of key metrics, even if not large in magnitude – This one is most important if you don’t have 5. For example, for ecommerce, you need to show that you can acquire a ton of customers cheaply, and sell them something that makes you a lot more money than what it cost to acquire them. Show that you can then keep selling them more stuff and you have a lifetime value that is super high. Then a VC can then just think if they spend $X million on customer acquisition, then I will make $X+Y million. If you can show great metrics but not necessarily tremendous traction, then you need to show metrics which will talk about your potential, once you get tremendous traction.

8. Why are you better than your competitors – If you have a lot of competitors, the probability of you getting funded drops. If you have less, the probability grows. In either case you need to show why you are better than the other guys in your space.

9. Exit potential – 10X or better – For series A, they will look to return 10X or better. They will NOT be playing to exit at 3-5X. If you can’t show that in your numbers and potential, you’ll never get your series A. Work on your plan and story to get that. Study M&A data to understand if it’s even possible.

10. Timing and market conditions – Here is one example: after instagram got bought for $1B, that ruined the market for all the other startups out there trying to get their series A; all the VCs started hunting for the next instagram! Talk about herd mentality. However, after 2008’s crash, VCs started looking for revenue generating startups and less those that only have traction. So the market changes regularly.

11. Defensible, sustainable competitive advantage – This attribute has been around since the dawn of venture time. If you have one, a REAL one, then you will be fundable.

Knowing the above, then comes to another part of this puzzle for those raising money now, which is how much money do you need to make a good showing in a large number of the above?

We tell people to raise for 18-24 months now. It could be even longer given the type of startup you have. 12 months or less is definitely not enough in today’s climate. So it could be $500K, it might be $2M – whatever is appropriate for what you are building. Also remember there are two levers to adjust: how much you raise and how much you burn. So it’s not as simple as doubling your raise to get to 24 months – it could mean you should burn half as much.

NOTE: 18-24 months is HIGHLY dependent on industry and market conditions at the time. It was 12 months back in 2006 timeframe; it could be worse in the near future. Or it could retreat back to 12 months. Like it or not, it’s 18-24 months right now.

Should you ask VCs what they look for in series A?

Asking VCs does work but it may also not work. Unless your business is in a category where there are known metrics, like ecommerce, or in an area where the VC has experience in a previous investment, it may be hard to get a good answer. You may get a generic answer like “show more traction”. Well that’s nice, but how much exactly? And is that enough? So find a VC who has experience and investments in a similar industry AND is friendly enough to take advice meetings in their busy schedule and you could get some good answers. But they could also be generic answers.

I think a better path is to find someone in a similar business who can tell you what metrics they track and see if they adapt to your business.

Proving and Showing the 10X Return Case

Another thing you can do is to do some math to show that you can generate a 10X or better return for an investor via comparison with historical data.

First, if you can, look up similar companies in your space. for some this is impossible. for others you may need to look at what a potential acquirer has paid for in the past. and still for others, it could be that you can find some public companies in similar spaces for comparison. google around the web for M&A data. some of that you’ll have to find in a M&A database like MandAsoft.com or CBInsights.com. Look also at press releases, Techcrunch, SAI, etc.

Second, if they have revenue, this is most straightforward. Look at typical multiples on revenue or EBITDA. There will be high/mid/low values for typical M&A-ed companies, or easier when a company is public.

If you don’t have revenue, this can be very hard. You may just need to find M&A data on companies that were acquired by a potential of acquirer of you. Gather metrics on those companies, like number of users, etc. to use as comparison.

Next, now you relate the performance of your company at a given exit value. But what is that exit value? Now go back to some scenarios on funding. For series A guys, what would a potential valuation be, for a given amount raised? Let’s say you want to end up at $20M post money. If a series A guy wants at least 10X, then you would have to exit at $200M assuming no more rounds of financing after them (highly unlikely that other rounds may not be required, but let’s start here).

If you have great revenue potential, then take the multiple on revenue and the multiple on EBIDTA and figure out what revenue you’d have to make in order to achieve that $200M, and/or also what your EBIDTA would have to be. Now you have these two numbers – if you can build a believable plan to get to these numbers in a reasonably short amount of time, say 5 years or less is optimal, 10 years is the absolute maximum which is the typical life of a fund, then you have a good chance of getting a series A.

If you’re off building to huge user traction, looking for the Instagram win, then you’ll have to show the traction buildup of similar companies sans revenue.

Remember that Pinterest took 1.5 years of hanging around until they started to hockey stick. Twitter took nearly 3 years – those guys could have hung around for 10 years if they wanted to. But once they took off, then the game was on.

There are many out there who are looking for high traction services, either to find the next Instagram or on the assumption that if you have that many users then you’ll be valuable to someone eventually, or you’ll figure out how to monetize them even if with ads.

So all traction based/sans revenue startups have to do is to get to their own hockey stick and survive long enough to do so, but you may have to wait until that hockey stick happens before you get your series A….

Now having said all that, put all those calculations and data into a slide in your deck and get ready to talk through it with a VC. Don’t count on a VC to do that math for you; they may not have enough experience in that industry or sector to do it on the fly.

If you can’t achieve those results no matter how you jigger your spreadsheets and models, then i think you have a pretty low chance of getting a series A. if that’s true, THEN DO SOMETHING ABOUT IT. change yourself. pivot what you’re doing and/or pivot your plan. otherwise you’re going to have to figure out how to survive on just your angel round, assuming that the angels you get also have lower expectations.

Am I Sunk If I Don’t Exhibit Typical Series A Attributes?

While not being able to show typical series A attributes, it doesn’t lower them to zero. There can be so many random factors that can land you a series A.

I would say that most VCs are pretty conservative relatively speaking and want proof points alongside the vision and things that are not yet shown or proved yet. but that doesn’t mean you couldn’t find someone to bet on you even with large sums of money.

The lesson here is: keep trying! Don’t give up! If you have absolute proof that you should change your pitch, then do it. But there also may be somebody out there who will fund you with your current plan. You’ll never know until you pitch as many people as possible. So DON’T GIVE UP.

In the wake of the lackluster update to the ‘jobs report‘ that was recently released, I thought I’d post a quick update regarding the macroeconomic data that we used in our MegaTrends Infographic.  We recently refreshed the data to include the year to date.  Below are the updated graphs and some brief thoughts:

Percent Change From Preceding Period in Real Gross Domestic Product, Q1 1980 – Q1 2012
Source: Bureau of Labor and Statistics

Above is a graph of the percent change in quarterly GDP from the previous period since 1980 – the green represents the percent change while the red line represents the average across the last 3+ decades (80s, 90s, 00s, 10s).  The most noteworthy feature is the drastic decrease in Q4 ’08, where GDP was 8.9% lower than in Q3 ’08.  While growth in the last few years has not been explosive, GDP has not regressed.  We have witnessed a steady increase in GDP each quarter.  The average quarterly increase since Q1 ’00 has been 2.3% – an improvement over the last decade but not quite at the levels witnessed in the 80s or 90s.

Unemployment rate, seasonally adjusted, January 2007 – May 2012
Source: Bureau of Labor and Statistics

Above is a graph of the unemployment rate from January ’07 to April ’12.  The rate has been on a very slight decline since it peaked at 10% in October ’10 but it has not broken below 8% since January of ’09.

Duration of unemployment, percent distribution, January 2007–April 2012

Source: Bureau of Labor and Statistics

The graph above shows the percentage of unemployed that have been so for longer than 27 weeks, so called ‘Long-Term Unemployment’, since January ’07.  Long-Term Unemployment is particularly troubling as more and more of those unemployed find that their skills are diminished or are no longer suitable for employment.  Notice that the shape of the curve mimics the one directly above it, which indicates that there is likely added pressure on reducing the unemployment rate attributable to a mismatch of skills possessed by the unemployed and those desired by potential employers.

Postwar Recessions (1946-2008): Cumulative Decline from NBER Peak (pct)

Source: Federal Reserve Bank of Minneapolis

The graph above shows the number of months it took to return to peak employment for every recession since WWII.  I’ve highlighted the last two – 2001 & 2007 – in red, as they are clear outliers.  The recession that began in 2001 took roughly 46 months to recover.  The current recession, which began in 2007, has yet to recover after 53 months and also saw the steepest decline in employment as compared to the peak.  If you look back a bit further, you will see that each of the last 4 recessions have set the mark for the longest ‘time to recovery’, which leads me to believe that structural unemployment is becoming a much greater problem as our economy continues to evolve.

Labor Force Participation Rate: 25-54 years, Men, January 1948 – May 2012

Source: BLS Data via Economagic

Structural unemployment is also a likely contributor to the graph above, which shows the labor participation rate for men aged 25-54 since WWII.  Skills are rapidly becoming obsolete for both blue-collar and white-collar jobs due to technological advancement in mechanization, automation and process improvement.  Already, we are seeing that the skills learned in school or early in careers (for those college graduates that are able to find early career track jobs) are no longer enough to support an entire 40 year career for many Americans.  As technology continues to evolve at an increasing rate, this is only going to become more apparent.

Looking back to the MegaTrends, the new data heavily support the continuation of the “personal efficiency” trend.  Persistent unemployment and underployment play a strong role in creating demand for the various platforms that allow individuals to monetize their existing assets and talents.  The collaborative consumption, crowd sourced labor and digital cottage industries sectors will continue to grow while these conditions are present.  At LaunchCapital, we will continue to search for innovative businesses that can create ways for the displaced members of the labor force to monetize their existing skills and/or to learn new skills.


So what do healthy snacks, razors, jewelry, and underwear have in common? If you answered: “All can be mailed to you on a recurring basis!” you’d be correct. Subscription e-commerce, or Subcom, has exploded onto the startup scene as the next big thing. You can’t go a day without reading about another subcom startup attacking a new vertical (condoms anyone?). At Launch Capital, the room for e-commerce growth something we’re particularly interested in (only drives 4.9% of overall retail), so we have done deep dives into many companies in the subcom space, but have yet to pull the trigger. After looking into many of these companies, I have identified some patterns and characteristics that I believe that the big winners in subcom will possess.

The subcom space is eerily similar to the proliferation of flash sale and daily deal sites a couple years ago. Where deals were the hook to drive customer adoption and eventually build e-commerce platforms (see Gilt), subscriptions are a similar hook. The issue is that people tire of daily deal emails and are not going to have 15 different monthly subscriptions. So these companies need to scale, and scale fast. So what does a winner look like?

1) Initially a discovery/distribution channel for new brands – While this isn’t absolutely necessary, I believe it’s the best way to grow a new subcom quickly. Brands get exposure to a targeted userbase, are initially willing to provide sample inventory at a discount or free (keeps costs low) and it provides an online channel that most smaller brands can’t do themselves – win/win for everyone.

2) Long-term goal is e-commerce platform – In the long-term, platforms have to convert subscribers to repeat purchasers through the site. As I mentioned before, I believe subscriptions are a way to acquire customers but aren’t sustainable over the long-term. Companies need to give users the ability to buy sample products they liked through the platform to drive significant revenue.

3) Sell essentials – This is the big one. Products need to be something that people use everyday, because otherwise why would you need a monthly subscription? Many subcom companies fall into the “gifting” trap, offering cool, nichey items that are perfect for gifts. Gifts, however, are inherently one time purchases and you don’t need a monthly subscription for them. Categories that I think work are: entertainment, makeup, razors, baby products, food could work in certain aspects (non-perishable), clothes work but have a major fit issue, and I think accessories/jewelry are much more essential for women than men.

4) Price point needs to be under $40 – I think $20 is close to optimal. People don’t like seeing line items on their credit card statement for $50+ for non-essentials. Especially when subcom companies are fighting rent/mortgage payments, cable bills, phone bills, insurance, etc. already happening on a recurring basis.

5) Personalization/curation – Collect data and develop some type of personalization algorithm that can help curate items for different customer segments. See Amazon, Netflix.

6) Opt-in/Opt-out – While you lose a bit of the surprise factor here, I think it’s better for both the customer and the company to let users see what they’re getting beforehand and give them the option to opt-out of the box or items they don’t want (Frank&Oak’s Hunt Club and Bespoke Post do a good job with this). It solves the returns issue for the company and is a way to gather more information on your users to see what they like/don’t like.

I think Birchbox is quickly becoming the major player in subcom. They figured out beauty products are essential items that people like to sample/discover, have kept a low subscription price point, and are quickly becoming a true e-commerce platform as 40% of their subscribers have purchased a product through their site.

Additional Reading: