Don Dodge on The Next Big Thing

TechStars Demo Day - Boulder 2008

 TechStars is a startup incubator based in Boulder, Colorado. TechStars selected 10 teams and provided funding of about $15,000 per team, free office space, operational support, and mentorship from former entrepreneurs and business leaders.

This is the second year for TechStars, and they have already had an acquisition. SocialThing was recently acquired by AOL.

The teams presented today to about 100 VCs and Angel investors for the first time. These companies are three to six months old and have two or three founder employees.

TechCrunch also has coverage of Demo Day.

Gyminee -A fitness social network for detailed tracking, online accountability, and motivation. With Gyminee, you can find workout programs and track your progress, track your food and nutrition, and set goals for whatever is important to you. On the social side of things, you can find GymBuddies to keep you accountable towards your goals and participate in fitness challenges. They already have over 35,000 users and over 1.2M page views. On the nutrition side they have a database of 50,000 food items complete with nutritional information that you would find on the label. You can track your diet, calories, and nutritional value. Freemium business model. Free service where you can upgrade to premium services for $5 per month. Looking to raise $300K in seed funding.

Ignighter - Wish dating could be as fun and easy as
going out with your friends? Ignighter is group to group dating. Meet people the way you do in real life...like you did in college. Ignighter is about hooking you and your friends up with someone else and their friends. They believe group socializing is safer and less intimidating one to one blind dating, and leads to personal dates. Ignighter has elements of Facebook for groups and Match.com for dates. They have an iPhone app that uses GPS to find other groups close to your current location. They have over 10,000 registered users. Business model; premium services like better search placement, and of course advertising.  Looking to raise $300K.

Peoples Software - WhozAround? from People’s Software takes the pain out of making plans with your friends with planning and scheduling tools that plug right into your Facebook account, your contact list, or your mobile phone directory. Lightweight and location-aware, WhozAround sorts your friends, makes plans with one click, and outputs your events into a clean feed that can go right to your calendar, email,  or your phone.

Peoples Software founders are Susan Mernit formerly a VP at Yahoo and AOL, and Lisa Williams, a founder of several companies, and formerly at Boston.com. It is great to see two women founding a cool new startup. Business model; locally targeted advertising. They believe they can get $7 to$10 CPM rates because of the local targeting, and by partnering with regional media companies. They are seeking $225K in seed funding.

Devver - Takes the tools that developers already use on their desktops and turns them into cloud-based services. Currently focused on Ruby tools and testing suites. Strong emphasis on test suites. They will add PHP, Python, and Java later. They will also have an open API so that developers can add other languages.

By putting developer tools in the cloud, they can execute them more quickly, reduce setup and configuration time, enable easy scheduling, display rich reports, and make it simple to share data between team members. The dev tools and environment is set up once on a cloud based server, then team members can be added quickly and have all the same tools, projects, and code.

Business model; subscription fee of $100 per developer per month. Sales channel - seems to be word of mouth through the Ruby development community. Seeking $200K in seed funding.

 The Highway Girl - is a traveling music show for the digital age. Hosted by singer songwriter Samantha Murphy, the show educates artists on how to manage their careers in the digital age while also giving fans a true behind the scenes look inside the life of a singer / song writer on tour. It is initially based on Samantha Murphy, but soon will include other artists. TheHighwayGirl.com will sell exclusive content on the artists they feature, as well as act as liaison between artist and fan on non-traditional transactions that connect them.

 Samantha delivered one of the most unusual startup pitches I have seen. She sang a song about raising money and building a business. Wow! Samantha is an incredibly talented singer /song writer. Business model; Exclusive content, tours, merchandise, and a traveling music tour called The Highway Girls. Also partnering with TopSpin. Seeking $500K in seed funding.

Application Experts provides Software as  Service (SaaS) to venture capital and private equity fund managers and to the pensions, endowments and other parties that invest in venture capital and private equity. Based in Denver, Boston, and Chicago. The founders were in private equity firms prior to founding the company. 

The idea is to build a social network of private equity and venture capital investors to share best practices and information. They also provide a deal tracking dashboard to help manage the pipeline of investment deals in progress.

Their target audience has plenty of money and is willing to pay. They charge $3k per person with a minimum of $15K.

Occipital - Photography has evolved over the years, but the ways we interact with digital photos are still decidedly primitive. Occipital is using artificial intelligence to organize your photo stream, enabling vivid recollection with groundbreaking visualizations.

They can stitch photos together into a panorama, automatically label and tag photos, and construct 3D scenes from your photos. They can zoom in, fly over, step inside buildings...all based on simple photos stitched together into a 3D presentation. They find objects in your photos and link them to the same or similar objects in other photos and stitch them together. This is hard to explain with words, but the visual demo was amazing.

BuyPlayWin.com - Combines online shopping with tournament games. Buy products, play games, win the product. Every shopper gets a chance to win full refunds for everything they purchase by playing fun games against other shoppers. For example, buy a $120 college text book. Compete with six other people who are also buying the book. Win the game and you get the book for free. They use the profit margin in the product to pay for the winners purchase. If a product has a 33% profit margin they need three players to break even. With 10 purchasers they make a very nice profit. They are seeking $400K in seed funding.

Foodzie - An online marketplace where consumers can discover and buy food directly from small artisan producers. The Foodzie technology makes it simple for small producers to sell their products online and aggregate all these products within a marketplace that makes it easy for "foodies" to discover the very best food. They focus on gourmet foods and organic health foods. These are high end and high margin products. Foodzie takes a 20% commission on every sale. Traditional retailers take 50% margin, while a distributor takes another 10%. The food supplier only ends up with 40%. So, with Foodzie the producers get to keep 80% of each sale. They are seeking $350K in seed funding.

Travelfli - helps frequent flyers maximize the full potential of their loyalty programs and discover the value in this hidden currency. They help users manage their award programs in one centralized and secure place, find ways to get free travel using their miles, and book award travel online. TravelFli allows you to aggregate frequent flyer miles and hotel points from family members and keep track of al the various rewards programs. They help you keep track of when miles expire, or when there are special promotional programs for your miles.

There are over 120M people in frequent flyer programs, and trillions of frequent flyer miles that never get used.  There are 17M elite flyers that account for 43% of all flights. These elite flyers are a very lucrative market for airlines, hotels, rental car agencies, etc.

Business model; commissions on all sales. Advertising - CPMs for travel are very high. They will also sell aggregate data on flights, hotels, and car rentals. They are seeking $500K in seed funding.

Ycombinator startup demo day Boston 2008

Y Combinator provides seed stage capital and a 10 week startup boot camp for budding entrepreneurs. At the end of the 10 week session Y Combinator invites VCs and angels to an investor day / demo day. Today YC unveiled 20 new startups to about 80 Boston area VCs and investors. Scott Kirsner (Boston Globe) and Roger Krakoff (Sigma Partners) are pictured here in the first row.

The companies covered areas like; a startup job site, video conferencing, cloud database software, a site for students, a news aggregation service, photo-sharing, social browsing, POS customer satisfaction surveys, white labeled social news, audience response software, music distribution, green certification, site creation for small business, a mobile-focused Evite competitor, a secondary ticket market, an event site, and a comment crawler.

These companies are only 10 weeks old, so some haven't launched yet and are still in stealth mode. Here is a summary of some of the companies that have launched.

Frogmetrics - puts touch screen devices into the hands of customers to get accurate, real-time feedback at the Point Of Sale. Frogmetrics measures customer satisfaction, employee performance, and advertising effectiveness to tell businesses what their customers think about products, services, and employees. Survey response rates typically exceed 85%.

The software aggregates data from unlimited locations, highlights significant trends, and helps companies gain insight into business performance—instantly, from any web browser.

Posterous is dead simple blogging by email. Just send text and attachments to post@posterous.com—no signup and no setup. You can photos, audio, video, documents, and rich text. Posterous automatically sets up a blog for you, then sends you an email reply with the URL address of your new blog.

TicketStumbler - a site to find and buy tickets to sporting events. Similar to StubHub, except TicketStumbler aggregates tickets from all the various ticket resellers. You can search by date, price, location, etc.

Best line of the day came from the TicketStumbler presenters "People go to Facebook to "poke" friends or some useless thing. People come to TicketStumbler to buy tickets. We make money on every sale."

Anyvite - Similar to Evite, a way to create events and invite guests. Ideal for the small to medium events. Simple to use. Guests can use email, SMS or IM to be notified of new events, and to respond without even visiting the site. Anyvite’s fully integrated mobile interface gives users the freedom to create and manage their events at any time and from any place.

Job Alchemist - a site for online recruiting, launched Startuply, a startup-specific job site, in July 2008. New sites targeted to specific industries and communities can be launched and populated in as little as 30 days.

Their next product will be JobSyndicate, a distributed affiliate job network. Companies put recruiting bounties on jobs, and anyone can use the widget technology to advertise these jobs on their site. When a publisher sources an applicant who gets hired, they get half the bounty: a payout of $2-10K or more.

There were several other interesting companies that I can't talk about yet because they are still in stealth mode. The 20 companies this year were very polished and business focused. The Boston area VCs are paying attention to Ycombinator now.

Some of the VCs I talked to included; David Hornik (August Capital), Fred Wilson (Union Square Ventures), David Beisel (Venrock), David Baum (Stage 1 Ventures), Rich Lavendov (Avalon), Roger Krakoff (Sigma Partners), Neil Sequiera, David Orfao, and Joel Cutler (General Catalyst), Eric Hjerpe (Atlas), Jeff Glass (Bain Capital), Bijan Sabet and Rob Go (Spark Capital),  Saar Gur (Charles River Ventures), Jonathan Seelig (Globespan Capital), and Jo Tango (Kepha).

Dharmesh Shah (HubSpot), Bob Buderi (Xconomy) and Scott Kirsner (Boston Globe) attended the YC Demo Day and wrote reports on their blogs.

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How does web advertising work? How effective is ad serving technology?

Lots of startups and VCs are betting their business on web advertising as a business model. They point to Google, Yahoo, and other big sites as examples of success and assume they will have proportional success. Not likely.

In a previous post "Is Ad Targeting The Next Big Thing" I asked why we aren't seeing higher CPMs and better targeting based on all the attention data from Web 2.0 services and click stream data. I heard from several advertising executives and would like to share their insights here.

Michael Yavonditte, formerly CEO of Quigo (acquired by AOL) answered my questions with these concise and insightful responses;

(1) It's hard to use all the available data to target. There are lots of reasons for this. Advertiser confusion is a big one. Too many choices can overwhelm advertisers and create a watered-down marketplace.

(2) Advertisers will pay more for inventory that converts better but they also need scale. Often times better targeting leads to smaller quantity.

(3) I know of some "attention data" being used/tested. The results can sometimes be surprising and counterintuitive. It's very hard to find new targeting data that can also scale across lots of inventory or sites, which is why behavioral targeting hasn't become a multi-billion dollar market yet.

(4) There is a ton of inventory but not enough high quality inventory at the moment. I think prices will eventually move up as new ad formats are invented and big branding dollars begin to match online user consumption habits.

 

OK, let's dig a little deeper. First let's level set on some definitions.

Page Views - We need to distinguish between advertising on Search Engine Result Pages (SERPs) like Google, and advertising on typical web content pages like Yahoo.

SERP ads - Google has been very successful with SERP advertising for two basic reasons, and lots of complex reasons. First, SERPs have the advantage of targeting an advertisement to a very specific search term entered by the user. Second, the user is in active "search and discovery mode" so they are more open to an ad offer.

Display or text ads on content pages from Yahoo, MSN, AOL etc., don't have either of the above advantages. Content pages have hundreds or thousands of words so it is hard to target. And, the user is in passive "browse mode".

How do ad servers work? Most ads, other than SERP ads, are targeted based on content on the page, in very broad categories like; news, sports, business, politics, etc. They try to dig deeper into the context of the page, but with varying degrees of success.

Daniel Jaye, a former exec at Tacoda, (now part of AOL) explained to me some of the complexities of ad servers. Here is a snippet from our discussion;

Most ad servers do not allow the ability to perform complex targeting based on the wide variety of data available, but the issues are complex.

1) Ad Targeting technology (most ad servers have the following insufficiencies):

a. Multi-valued attributes (ie a browser (person) may be a member of several segments, how do you choose/prioritize?, traditional Boolean logic doesn’t suffice)

b. Complex Boolean targeting (ORs, ANDs, etc in specific order of evaluation)

2) Inventory Management

a. Multiple criteria: Ad servers have to prioritize delivery based on multiple criteria today: (roadblocks/takeovers by content or by targeting criteria, schedule commitment, performance objectives, etc.). The more data we add, the more difficult it is to predict and allocate available inventory, manage pricing/scarcity etc.

With regard to real results, the performance improvement varies.  For some categories (auto intender, consumer electronics shopper, etc.) the performance gains are clear and relatively easily obtainable.  For the broader set of offers, automated optimization has many challenges and has NOT demonstrated a clear advantage over basic techniques like frequency capping and contextual targeting. 

There were several industry terms in Mr. Jaye's response that need further definition;

• Frequency Capping - means restricting or (capping) the number of times (frequency) a web user sees a specific ad within a 24 hour period, across a whole network of web sites. This is a simple concept, but incredibly difficult to execute millions of times a day, in a split second, for every individual user, over hundreds of web sites.
• Contextual Targeting - means targeting ads based on the words (context) on a page. Again, simple in concept but incredibly hard to do at web scale in less than one second.
• Road Blocks / Takeovers - when one advertiser wants to dominate (Takeover) all available pages and (Block) other advertisers. Sometimes referred to as a "carpet bombing advertising campaign".

So, the ad serving technology needs to improve significantly. Results from ad targeting campaigns need to be proven. And, the ad serving technology must be easy for a junior ad buyer to understand and use.

Mike Troiano, a former advertising exec, currently CEO of MatchMine, said on his blog;

Sometimes tech folk forget that at the other end of the digital tentacles reaching across the ad-powered web, sooner or later, is a person pulling the levers. Joe Blow media buyer - think pimply-faced state college graduate 2-years out of school making $18K/year and living in Queens - simply can’t keep up with the pace of innovation on the web. They learn a few of the biggest ad targeting systems, which incidentally are the only ones with sufficient scale for them to complete their buys and move on, and crank 90% of their ad budgets through them. Once in a while one of the better ad network sales guys buys them some really good sushi and makes a decent case for some experiment, and voila, that technology gets thrown a $10K “test buy” bone.

The equation the ad buyer solves in his head:

1. What is the probability that doing this will make me a hero with my boss and/or client?
2. What is the probability that said boss and/or client is going to smack me for wasting time on this $10K diversion instead of doing everything I can to “optimize” the $500,000.00 buy we already have in process on Yahoo?
3. Is the potential upside of 1. materially greater than the potential downside of 2.?

Everyone agrees that ad serving technology will improve, and that "attention data" will be used to better target ads. They also agree that advertisers will be willing to pay higher CPM rates once the effectiveness is proven. As usual, the technology will advance faster than the customer's ability to use it and desire to pay for it. The big question is when will all these factors converge to launch another multi-billion dollar market? My guess is two to three years.

What do you think? Leave a comment and join the discussion.

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Olympic swimming gold captured by Silverlight

Have you seen the amazing Olympic final in the men's swimming 4X100 relay? World records were set by many swimmers in this race and it all came down to the final touch at the wall. The Americans beat the heavily favored French team by .o8 of a second. You can see it again thanks to Microsoft's Silverlight and NBC.

The Wall Street Journal says NBC is providing some 3,600 hours of coverage of the games, about 75% of it live, across its broadcast and cable networks and its Web site -- even as it works to keep unauthorized feeds from its potential audience in the U.S.

The quality and clarity of the Silverlight video is absolutely amazing. I don't normally watch video on my PC because of it is usually slow and poor quality. Not any more. This is fast, no jerky motion, and awesome quality. Note the "powered by Silverlight" logo in the lower left hand corner.

You can watch continuing coverage of all the Olympics events on MSN.

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Mac vs PC - Mac twice as expensive

Macs have always been more expensive than PCs. The Mac has traditionally had about 6% market share, and have recently "popped" up to around 8%. It is expensive to be cool...twice as expensive. Joe Wilcox at eWeek compared the prices of Apple laptops and desk tops to PCs by Dell and HP, and found that Macs were two to three times as expensive as PCs.

It is a big market and there is room for everyone, but 92% of the market still prefers the PC. Competition drives prices. There is lots of competition in the PC market place, and none in the Mac market. That explains most of the price difference.

Nothing stirs up a debate like a comparison of the Mac to the PC. The Mac fan boys come out of the woodwork anytime there is a discussion any where.

Personal preference. Some people absolutely must have a Harley, while others prefer a Honda. Some prefer a Volvo while others like a Ford. The price differences are huge, but a small portion of the market is willing to pay it.

Personally, I have always used a PC and am very comfortable with it. I have used a Mac when visiting friends and it is just enough different to be annoying. Simple things like "right click", keyboard short cuts, setting preferences, and even differences between IE and Safari browsers just slow me down too much. Mac users probably have the same hassles when they try to use a PC.

Comfortable habits - It is all about what you get comfortable using. About 95% of the market is comfortable using PCs. That is just the way it is, and it works both ways. About 70% of the market is more comfortable using Google too. Technical comparisons and price differences don't matter for some segment of the market place. It has always been that way...and always will be.

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Is Ad Targeting The Next Big Thing?

Better targeting equals higher ad rates - Lots of startups and VCs are pinning their hopes on this simple premise. It seems obvious, but there is very little evidence to support it. So what is wrong?

• Is the ad serving technology not able to take advantage of all this new "attention data" to better target the ads?
• Are advertisers not willing to pay higher CPM rates for the better targeting?
• Has ad targeting been tried with all this "attention data" and the results are not much better?
• Is there just too much ad inventory which is depressing prices?
• Are we just too early in the game to get good results?

Cnet writer Stefanie Olsen has a good story on what VCs think will be the next big things. Not surprisingly, they think ad targeting will be huge. Here are a few nuggets from Stefanie's story;

"The first wave of Internet investing dealt with commercializing the Web, helping companies like Amazon.com and eBay get on their way. The second wave has been about helping people socialize and connect through sites like Flickr, YouTube, and Facebook. The third, venture capitalists say, will be about making sense of all the data people create around the Web, and then searching for patterns in the data to improve the delivery of personalized content, search results, or advertising."

"Everyone talks about all the data that's being created and how valuable it is, but the way you make it available is by doing something actionable with it," said Rob Hayes, partner at First Round Capital."

"Social networks and social media sites have created so much new ad inventory on the Web, but they have yet to make significant money from it."

"We are really fascinated with data and the ability to use it to increase effective (cost per thousand) for ads. There's this explosion of inventory, but people haven't figured out how to monetize it yet--data will be the difference," said Fouad ElNaggar, a principal at Redpoint Ventures."

I have seen so many companies, literally hundreds, that are building social, fun, aggregators, filters, recommendations, communities, and services that all boil down to one thing...building profiles from implicit data and explicit actions to better target advertising. It is the biggest "head fake" in business history. All these widgets and services appear to be fun consumer toys, but underneath they are advertising driven data collectors.

It seems obvious that if you can collect demographic data from users when they register for a service, and then collect preferences, rankings, click stream data, social network connections, etc, that you should be able to use this data to better target advertising. It will happen...but there is no evidence of it yet.

Low CPM Rates - Social Network content sites get the lowest CPM rates, an average of $0.27, but sometimes as low as $0.02. Gaming sites are the highest. Several months ago I talked to a Facebook App developer who told me his app is generating 300 million page views per month. Wow! Then I asked what kind of CPM (Cost Per Thousand) ad rates he was getting. He shrugged and said somewhere between $0.02 and $0.05 per thousand. That pencils out to between $6K and $15K of advertising revenue per month for those 300 million page views.

Last night at Mashable's SummerMash in Boston, I talked to the founders of a new startup called Wiggio which is building a collaboration tool for college students. When I asked about their business model they said "highly targeted ads based on user demographics". I asked them if they had checked with the major ad networks to see what kind of CPM rates they could expect. "Well,...uh...no." I suggested that they should spend some time researching this out before going too much further.

In October I will be hosting a forum at MIT on advertising networks and the future of online advertising. We are recruiting some of the brightest minds in the advertising world to speak at the forum. I hope to dig deeper into some of these issues to better understand the problems.

What do you think? Why aren't we seeing higher ad rates? Is the targeting technology not working? Or, are web surfers just not responding to the ads?

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Why VCs say no 99% of the time

Venture Capital investing is a very tough game...and very lucrative if you are good at it. Part of my job at Microsoft is working with VCs, so I have learned a lot about the way they think...and why they say No to 99% of the deals they see...and still end up making investments that fail.

Fred Wilson has another great post today on Venture Fund Economics which I covered in my previous post. After posting that I remembered a blog post by Jeff Bussgang, of Flybridge Capital Partners. In it Jeff explains why VCs want to see every new startup...but say no 99% of the time.

"As one wise old VC once told me, "the trick in this business is to spend very little time on a lot of deals, and then a lot of time on very few deals."  In other words, see everything to be a better investor, but exert a very tough first filter so that you only spend time on very, very few deals.  In my experience, a typical VC has the bandwidth to actively "spend time" or actively work on only one to two deals at any given time and perhaps 10-20 in a year -- as compared to those 300-500 they get exposed to."

What are the odds? - VCs are exposed to about 500 opportunities a year. They spend time seriously looking at about 20 companies a year, and invest in two or three. So, they say no about 99% of the time.

We all say no 99% of the time - I would guess that every one of you reading this blog have a stock portfolio with 5 to 10 individual stocks or mutual funds. There are more than 5,000 publicly listed companies to choose from, and another 5,000 mutual funds. But, out of 10,000 possible companies you chose 10 to invest in. Why? Why did you reject the other 9,990 companies? Obviously there are more than 10 good companies to invest in. Other investors chose to invest their money in the other 9,990 companies...why not you?

We invest in people we know and companies we understand - We do this in our own personal investing, and VCs, with rare exceptions, do the same when they make decisions. We all say no 99% of the time, and we reject perfectly good companies, but we invest in things we feel comfortable with.

Here is the painful fact; even after being very picky and saying no to 99% of the opportunities...we still invest in failures about 33% of the time. VCs do it all the time, and if we look dispassionately at our own personal investment track record...we probably do too.

Find the right VC match - Don't be too quick to change your strategy or company pitch just because the first batch of VCs rejects it. It is all about finding the right VC that is interested in what you are doing and comfortable in the market space. Don't waste time trying to convince a reluctant VC. Move on and spend the time finding the right VC for you...that "gets it" the first time. There are at least 1,000 VCs in the USA. They all have different investment tastes...just like all of us do. Go for it!

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Why VCs look for 10X returns - What you need to know when pitching a VC firm

VCs want to invest at least $5M in startups that have potential 10X returns. That is because it takes as much time to manage a $1M investment as it does to manage $5M. Secondly, every startup looks like a winner when they write the check, but Fred Wilson suggests that 33% will fail, 33% will break even, and 33% will be big winners. VCs start out hoping for a 10X return on every deal but average about 3X to 4X after all is said and done.

VC Firm Partners - If a VC firm raises a $250M fund they will probably have 5 partners in the firm, with each partner managing about $50M. If they invest about $5M in each company over several rounds, then each partner will sit on 10 company boards. That is about all a single partner can handle and still do a good job for the portfolio companies.

VC Firm Investors - VC firms raise money from Limited Partner investors like insurance companies, pension funds, university endowments, and wealthy individuals. These investors know that venture investing is risky and expect higher returns to compensate for the risk, typically 3X their money over the 10 year life of the fund, or a net IRR of 30%. More on this later.

VC Firm Economics - VCs usually take a 2% - 3% annual management fee and 20% to 25% (carried interest) of any capital gains on exits. So, when you take out the VC fees and gains, and factor in the LP investor expectations, what does the VC fund have to return? Fred Wilson of Union Square Ventures did a great post on this and provided some real numbers on his model.

There are a lot of numbers here, but if you study them carefully they explain almost every question you might have about how a VC firm works.

VC Fees and Gains - Note that on a typical $100M fund management fees can take $20M off the top, so there is only $80M left to invest. That 2% annual management fee over the 10 year life of a fund really adds up. Also note that if the fund returns 4X on invested capital (4 X $80M = $320M) that the VC gets 20% of the gain or $44M ($320M - $80M = $240M, less the $20M in fees = $220M. The VC gets 20% of that gain or $44M.

On a $100M fund the VC gets $20M in fees and $44M in gains over the 10 year life of the fund. Now you know why everyone wants to be a VC.

VC Limited Partner Returns - In this case the LPs invest $100M and get back $256M, or about 2.5 times their money. Because they invest their money over the first 4 years of the fund, and collect their returns over the last 5 years of the fund, their Internal Rate of Return (IRR) averages about 30%.

What does this mean to entrepreneurs? - When you pitch to a VC you need to show the "potential" for a 10X return. The truth is that no VC knows which company will return 10X and which one will fail and lose all the money. Believe me, if they knew...they would only invest in the winners. Like I said, they all look like winners when they write the checks.

VCs will not invest in startups that address a small niche market, or companies that are profitable but don't look like they can bring 10X returns. They are not interested in potential 4X returns because they know that on average 66% of all investments will either fail or break even. If a company starts out looking like a 4X return, chances are, given the long VC history, it will break even at best. It is like probabilities in poker.

So, here is the inside secret to all of this. Build your plan on a 10X return, expect a 4X return, and hope you don't end up in the 33% failure category.

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