Venture Capital Family Tree

About six months ago my friend Chris Fralic (@ChrisFRC) invited me to a screening of Something Ventured, a film about the origins of the US venture capital industry. Definitely worth checking out. One of the things it got me to thinking about was how intertwined the early VC firms were. So, in the spirit of one of those genealogies of rock music posters, I gathered some data and made a visualization. It's not pretty like the rock and roll one. And it's woefully incomplete, which I need your help on. We'll get to that.

The whole thing

Zoomed in on some interesting '90s reshuffles

I used jquery and d3, although I had to customize d3 a bit. Because it's d3 and there are a lot of svg objects, it could be slow on slower computers. Also, screen size makes a big difference here, not recommended for mobile viewing.

I was trying to put in firms from the early days and firms that were critical links between the early days and today, so there are a very few firms founded in the last ten years in there. It's a historical study, not a contemporary view. The founders of the firms are noted, but not seminal later partners (i.e. Kleiner and Perkins but not Doerr or even Caulfield.) Although new partners can have a huge impact on a firm's direction*, I just didn't have time. Maybe in the next iteration.

Firms founded in New York are blue, in Boston are red, and in Silicon Valley are green. Others--including those that do not yet have an entry for place--are orange. Type a firm name or founder into the box (there's autocomplete) and click to zoom in on that firm. Also, pan and zoom using the mouse.

Venture firms never really die, they just fade away. And some firms stop being VCs (in the '80s many firms abandoned venture for PE) or were financial orgs and became VCs. This is denoted by a 'tear' at the beginning or end of the firm's bar--the firm had a life before or after, but was not an active venture investor.

I've also started adding noteworthy investments, but there are only a few. As far as I can tell, there is no extensive list of who backed who when. Which brings me to my ask.

I've put in info as I came across it for the last six months, but I have other commitments, so it's been slow. And the easy info sources are running dry. So I slapped on a form, hoping you all would help. All contributions are welcome, but in the spirit of the thing, I'd like to prioritize adding firms that were either critical links between the past and present, that trained a bunch of people who went on to found their own firms, have been influential for a long time, or were influential in the past and have disappeared (i.e. TVI, MPA&E.)

When contributing investments made by firms, I would rather not add every investment. I've tried to add investments that were important or household names. This is a public historical document, I think it's more interesting (and puts the better foot forward) to show that Starbucks and McDonnell Aircraft were venture backed (or Pizza Time, for that matter, even though it failed) than, say, Kozmo.com**.

To contribute either click on the '+' button on the upper right to add a new firm, or click on the name of a firm to edit/augment their info. When you hit 'submit', it should reflect locally, but it doesn't add it to the database (I'm not a back-end guy) it emails me. I will edit and add data, I don't expect to get a ton of submissions. The data is open source (cc by-sa), and any contributions will be considered open as well. I will add your name to the contributor list on the help page if you put it in the 'Comments' box on the form (there's no other way for me to know who you are.) Also, put your email address there if you want so I can contact you re your submissions.

But please, do submit! It struck me as odd when doing the research here how little the venture community values its roots. Law firms have web pages and sometimes whole self-published books celebrating their founders and history. Your typical VC firm comes across as if it's in the witness protection program. It's crazy that I can't figure out who all four founders of Menlo Ventures are and where they came from, or who backed Federal Express and when. I've got decent google-fu, and I looked, trust me. Someone out there knows, and you should enter this stuff. The mainstream industry is now some 50 years old. We are in danger of losing our past.

If someone knows of a source of data for this (that is either free or you can get me access to), I will port stuff.

Primary sources were firm web sites, Wikipedia, and The New Venturers by John Wilson, a great book now out of print. Some data was taken from Venture Capital at the Crossroads, Creative Capital, Valley Boy, The Startup Game, and Elfer's Greylock. I'm planning on skimming Done Deals and Venture Capitalists at Work for more. Other sources are in with the rest of the data as 'cites'.

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*  In a couple of case, Paul Bancroft joining Bessemer from DG&A, for example, I think it was significant enough to consider that the start of Bessemer's venture activity, even though that is not strictly true.
** Well, hard to say. I can only think of interesting companies because I only remember the interesting ones. Kozmo might actually be an interesting investment from a dot-com bubble point of view. Maybe just send me whatever you want and I'll figure out some way to highlight some and not others. I don't know.

That joke's not funny anymore

"[Y]ou have to assume that humans are capable of looking at facts, finding root causes and formulating solutions. On my planet there's not much evidence to support this assumption... If humans had the ability to look at facts and make good decisions, think about how different the world would be. There would be only six kinds of cars on the market and nobody would buy a car that was second best in its price range. There would be no such thing as jury selection since all jurors would reach the same conclusion after viewing the facts, and all elections would be decided unanimously. That's not the world we live in. Our brains are wired backwards. We make decisions first--based on irrational forces and personal motives--then we do the analysis. The facts get whittled until they fit into the right holes."

-- Scott Adams*

[The first section of this post was previously published on AdExchanger, and there's an excellent comment thread there, so you should go read it. This is the rambling version.]

Jokes all start with one of a few stock set-ups. "A man walked into a bar." But the punchlines are all different. VC pitches are the opposite: the set-ups are all different, but the punchlines are all the same.

Stop me if you've heard this one before. "We enable the half of advertising that is not yet online: brand advertising!" Been hearing that one for more than ten years now. It permeates the hopes and dreams of every adtech entrepreneur and investor. And still no one has cracked the code.

My friend Tim Hanlon got together with Tim Chang a few weeks ago over on AdExchanger to offer some reasons why this might be. Worth your time, but here's the tl;dr**:

• No standards or consistent measures of “success” other than outdated or inadequate metrics like CPM and CTR;
• Limited real-time intelligence;
• Unsuitable display ad formats; and
• Lack of creativity in formats.

The prize is huge. As Tim and Tim point out, two-thirds of advertising spending is brand advertising, but online only one quarter is. In fact, if brand advertising dollars moved online in the same proportion that sales advertising has, it would almost exactly close the famous gap between time spent online and ad dollars spent online. The $50 billion gap that Mary Meeker mentions is exactly equal to the missing brand spend.

So I understand the urgent desire to figure out online brand advertising. If we did, we'd more than double the online advertising market. Online pubs would rejoice, online marketing pros would have more excuses to go out drinking with prospective clients, my portfolio value would quintuple overnight. Good things all. And I appreciate the optimism that Tim and Tim have, their willingness to keep suggesting solutions. But I think it's the triumph of hope over experience. Each of these things has been tried, and tried and tried. And still we believe that this time it's different, that this year an online branding play will work. Online video maybe, or Facebook, or Pinterest. Every new company is touted as the one that will make branding work online.

But what if we try all these things, like we've tried everything before, and they don't work? What if we eliminate all the possibilities and what remains is... nothing? I'm going to be branded a heretic for saying this, but what if online just doesn't work for branding?

I mean, not to be defeatist, but we understand branding pretty well. Marketers have been creating brands nigh on one hundred years now, it's not a black art. And the solutions I hear, even Tim and Tim's, are not untried. More, they are not what makes brand advertising effective in other media. I don't buy that these are the solutions. I think it's distinctly possible that there are no solutions.

Maybe the medium itself is antithetical to the way brands are built. Like direct mail, maybe the very fact of delivering your message in a low-budget, specifically targeted way can not in any way build a brand. Brands attempt to exist autonomously, they are objects of desire, they want to distinguish what otherwise is indistinguishable. The psychological processes of branding are inimical to the idea that the brand has been chosen for you. Brands do not choose you; you choose brands. Brands are aloof, they aspire to be the Platonic ideal, their competitors just shadows.

Perhaps. I mean, I could be wrong. It could be that even though we sell ourselves to clients as brand-building geniuses, we don't know what we're doing; that we're groping in the dark, throwing random darts and just haven't hit the bulls-eye yet. We could be a bunch of monkeys at typewriters and Shakespeare will just roll on out one day. Could be. But it seems unlikely.

What if I'm right? What if online branding is a mug's game? If it is, it won't be too much longer before marketers get wise and just stop listening to online branding pitches. Maybe they already have. Maybe they never did listen to them. What's the fallback plan? How do we go about getting the brand advertising dollars if online brand advertising doesn't work? What can we do that will cause brand advertisers to move their branding dollars out of advertising altogether into some other online channel? How do we disrupt branding?

*****

What is branding, really? Why does it work? For the marketer, branding is a way of wrapping all of a product's attributes in a neat package and giving it a handle so they can refer to it easily. For the consumer, brands are a shortcut: for products where the potential benefit of making a choice is smaller than the cost of choosing, a brand is a fallback. Brands are Scott Adams' whittled down facts, except that marketers have done the whittling for us so they can control the outcome to their advantage. The hole they fit into is your brain. And research shows people only have a few of these holes in their brain.

This can work in a couple of ways. A consumer confronted with a dozen pasta brands in the spaghetti aisle*** would have to expend some time and effort deciding which was best for them. The small potential benefit from finding a better quality pasta is less than the cost in time and effort to determine this, for most consumers. So even if De Cecco is a better pasta, it is a rational for someone familiar with Ronzoni to buy Ronzoni. The pastas are similar enough that someone who just wants a bowl of spaghetti should not expend any effort distinguishing them: just choose your brand and move on.

On the other end of the spectrum, some things are extremely costly to evaluate. Choosing a motorcycle, for instance. The variables that come into play include not just the motorcycle itself, but complementary goods like service quality and availability of third-party components (if the stock pipes are too tame, say.) There are also intangibles, like aesthetics, community, and how you will be perceived among your peers if you are riding a Honda instead of a Harley. A brand can ensure that, even when the objective technical qualities of the bike itself are the same or inferior, it has an advantage among certain consumers because the cost of objectively evaluating differences between bikes is, for most people, impossibly high.

This cost/benefit analysis masks another obvious aspect of branding: risk-mitigation. I have, driving down the highway with my kids, chosen McDonalds though this would be at other times not on the list of possible dinner spots. But I know exactly what I'm getting, how long it will take, and how much it will cost. Because there's a fixed cost of investigating new options, even if for one-time use, the risk/reward curve is not linear.

The answer seems obvious. If branding is a needed compensation for something our brains are just not good at, a low quality way to reduce search costs, an easy alternative to remembering tons of facts, then the answer is to provide a better, more efficient way to sort alternatives. The internet, in its ability to instantly connect you to huge data sources and extremely fast algorithms no matter where you are and what random question you're asking, seems to be the perfect answer.

This is what computers are good at. Lots and lots of data, changing prices, personal utility curves. Right now I might walk into the supermarket looking for a relatively healthy breakfast cereal that my kids will eat. Given the huge number of choices, I might settle on Frosted Cheerios (even though they're probably about as healthy as a glazed donut) because Cheerios has pounded the idea that they are healthy into my brain. I can imagine, instead, walking into the supermarket, scanning the Lucky Charms with my smartphone and asking it to rank healthier alternatives for me. I can imagine a world where I tell an application what I like and dislike about my current pair of sneakers and it recommends a pair that would be better for me. I can imagine a world where I enter the specs and spec tradeoffs for any good imaginable--skis, cars, laundry detergent--and my computer finds me the best match.

But I'm not leading you down a garden path here. I don't do Socratic dialogue. I do not know the answer to the question I'm asking. I do not think these ideas will work because nobody will pay for them.

*****

Generally, and certainly with advertised goods, the seller is the one paying to find buyers and not vice-versa. This has resulted in all sorts of market distortions. Sellers are motivated to sell, and not necessarily only if the product is right for the buyer. That the seller is paying to find buyers--any buyers--instead of the buyer paying to find the perfect seller is a bit of an historic accident. The media was once solely a broadcast mechanism, a mass-reach vehicle. Before the internet, seller-financed advertising was cost efficient while buyer-financed search was cost prohibitive. Even though that is no longer necessarily true, advertising is stuck in a local maximum.

It would certainly be more systemically efficient today if consumers decided what they wanted and then went out and searched for their best match themselves. Then advertising would be less effective so there would be a lot less of it. If sellers did not need to advertise, they could lower the cost of the product and this lower cost would--I'm guessing--more than compensate buyers for the time needed to find the right product. The buyer would end up even on cost (lower product cost ~= higher search costs) but with a more appropriate product. That's the ideal world, but it requires massive behavior change from both sides of the market at once. There's no way to achieve that kind of coordination.

As long as advertising continues to be cost-effective, sellers will advertise. As long as they advertise, they will not lower prices. And as long as they don't lower prices, buyers would have to pay twice if they decide to do the search themselves: once for the advertising and once for the search. This is a long way of saying that no one except the sellers themselves will pay for anything to do with informing consumers about products and services. We are stuck with what we have, efficient or no.

Want to quibble? We now have some seventeen years of evidence that, even if it's a better way of doing things, consumers will not pay for search in any way other than by looking at ads. This is, if you think about it, probably the most bizarre thing about internet marketing. People pay for media that compares and analyzes products, but in a way that undermines the value of these comparisons. Yelp, Google (like Car & Driver magazine offline) critique the very industries that finance them. Their interests are in question. Marketers are attempting to influence people right as they are trying to make uninfluenced choices. Search for a product on Google and you are inundated with ads. Odder, many are clicked. People are searching for someone to convince them, they are going through the motions of choosing and then avoiding making choices. The media soothes the cognitive dissonance with a pleasing veneer of objectivity, but the objectivity is--has to be--a sham. Follow the money.

The non-profit Consumer Reports has overcome this criticism by refusing to accept advertising. But they may be the exception that proves the rule: despite almost certainly being worth the subscription price for anyone who buys even one thing in any category they cover, they only have some seven million monthly subscribers. Consumers will not pay to inform themselves. That's why we're stuck with marketing.

*****

Some other, possibly spurious, correlations to note:

	TV	Print	Online Display
Measurability	Low	Medium	High
Involvement	Absorbed	Absorbing	Engaged
Audience	Mass	Select	Targeted
Branding	Yes	Sure	Not so much
CPMs	High	OK	Low

Many intelligent observers, when contemplating low CPMs or recalcitrant brand advertisers say we just need more measurement, more engagement, or more specific targeting. But these things seem to go the wrong way. On the other hand, there are some exceptions: the trade press is more targeted and has higher CPMs; search is more engaging and has higher (effective) CPMs; etc. So the point here is not that we're doomed, but that the easy answers will not do--we're probably analyzing success along the wrong dimensions.

*****

Regardless, I believe in the power of the internet. I think that we can achieve a better product-consumer match by using personalization, community, data and machine learning. In fact, this seems almost too obvious to say. The internet has the power to create a much better branding mechanism: one that works better for brands and for consumers.

I also believe that brands can be valuable. They are proprietary marks, so can guarantee implicit promises and ensure repeat business. They allow trust, and trust is a necessary lubricant for commerce. If there were no newspaper brands, no one would read newspapers, because they would not be able to judge the quality of the news they were reading. If there were no retail brands, every purchase would be like walking into a generic electronics storefront in Times Square: buyer beware.

My objections are not to the internet or to branding. My objections are to the way we are approaching disrupting**** branding. I do not believe the success of online brand advertising is about waiting a bit longer, or measuring better, or creating more engagement. We've waited long enough, we measure better than any other medium, and we are as interactive a medium as they come. If you are espousing those ideas, then you have to also explain why you are right now when you would have been wrong all these long internet years. Things do change, but sudden change is either because of a compounding effect or a catalyst. It does not look like to me that online brand advertising is increasing in an exponential way. Nor do I recognize a catalyst*****.

Or, and I think this is a more promising path, we need to accept that branding may not change to accomodate us, we may have to change to accomodate branding. No more complaining that brand marketers just don't get it. No more waiting on incremental change in measurement or attribution technology. Find a way to allow brands to hone and prove their promises, while giving them a much larger payoff for doing so. Don't think about how to service Procter & Gamble or Coca-Cola--disruption starts off by creating new markets, not servicing old ones--think about how you could help a quality product or service build a brand from the ground up for far, far less than a TV branding campaign would cost. If you do that you will have the big brands' attention, and an amazing business.

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* Quoted in Bruce Tremper's Staying Alive in Avalanche Terrain, a must read if you like the backcountry in Winter.
** Seriously? What are you doing here?
*** I was in a supermarket in a hispanic part of Pennsylvania recently where pasta was in an aisle labeled 'Ethnic' while the Goya black beans were in an aisle labelled 'Beans.' Where I live in Hoboken, the exact opposite is true. I wonder if there's a place where the ethnic aisle stocks Oscar Meyer and Easy Cheese.
**** I wrote a typically long blog post on disruption and what it means in this context here.
***** A catalyst has to be a new technology or an entirely new way of utilizing it. The internet itself, say, or social media, or collective intelligence, or online video, or data-driven matching. These could all have been catalysts but, as it turned out, they were not.

Selecting, not filtering: Give me a reason to say yes

Raising money for my last startup was humbling, frustrating, time-consuming. But that part was okay: any highly selective process will be humbling, frustrating, and time-consuming. The part that really bothered me wasn't that it took so much time, but that so much of that time was a complete and total waste. In almost all of the VC meetings, we did not leave with a check. But in some 80% of the meetings we also did not leave with any insight as to why not*.

The best VCs listened to us and then gave us some insight into their thinking. Fred Wilson and Brad Burnham actually said no to us and then worked through their thinking about what we were doing in great and helpful detail. Josh Kopelman and Howard Morgan told us it wouldn't work, told us exactly why, then invested, and--after that--introduced us to people who helped us fix the flaws in the plan. But many others gave us either no response at all ("we'll get back to you") or generic non-responses ("we'd like to see more traction.")

We had a pretty firm idea of the problem we wanted to solve, but we were somewhat flexible about how we would solve it. We used the feedback from the money-raising process to hone our ideas. When we got no feedback, we felt we had given the VCs critical market intelligence and gotten nothing in return.

One of my ideals when I started investing was to always provide feedback when I said no. But here I am four years in, going through the pitches that piled up last week while I was on vacation. I'm finding it hard to live up to that ideal. I'm saying no to companies that I don't have a concrete reason to say no to. After a bit of introspection, I think that finding a reason to say no is not really how I make the hard decisions.

I have a tangible reason to say no to some 85% of the pitches I see, and I say yes to less than 2% (some of these I don't end up doing because we can't agree on a deal.) Here's a swag at how my dealflow works out:

• 40%: No; I do not know your market well enough to help you succeed (also known as I do not know your market well enough to make a good decision about investing);
• 20%: No; I do not think your idea will work and I can't see where else you will be able to put the technology you're building to work/you are completely inflexible about entertaining other potential markets for your technology/you are too flexible about where you will put your technology to work (the "we're a platform!" syndrome);
• 10%: No; You are creating something merely better, not different;
• 5%: No; You have the wrong team/your team does not seem to gel/you do not seem to think you need a team at all/you are coding in .NET;
• 5%: No; Other explainable reasons;
• 5%: No; Bad**;
• 13%: Meh;
• 2%: Like.

I always explain, in as much detail as the entrepreneur wants, my thinking behind the 85% where I can say no. And I am always happy to explain why I like the 2% I like.

The rub is in the penultimate 13%. These are companies that I don't have a real reason to say no to, companies where I analytically think they have a venture-capital-winner expected value but where I just can't get excited about them. The reality is that with these companies--and, in fact, with all companies--I am not looking for a reason to say no; I am looking for a reason to say yes. With the 85%, there is a glaring reason why I can't say yes. With the 13%, I just can't get the word to come out of my mouth.

For the companies I can easily say no to, some dimension of their plan (team, market, vision, product, customer, etc.) does not rise above my threshold of yes. For the 15%, all aspects do. Analytically the fitness function then necessarily also rises above my threshold.

The difference between the 'meh' and the 'like' is that the 'meh' companies are good enough in all aspects but not great in any of them. The 'like' companies are the ones where they really excel in at least a couple of ways: a great team, a big market, a compelling vision. I try to select not just for how good a company is, but how good it will be. It's easy to improve along one dimension, it's possible to improve along a couple of dimensions, but it's almost impossible to improve along all dimensions. The companies that are just good enough in all dimensions need to improve in all dimensions. The companies that are great in a few just need to improve in a few others, not all, to be great overall.

In fact, some of my favorite companies are the ones that may not even rise above the threshold in one or two dimensions but make up for it by having a superstar team or a gigantic market or a world-beating vision. These are the companies that have a shot at being legendary.

I don't know what to say to 'meh' companies after they pitch me. It's hard for you to recover from a "we're not so bad" pitch. But if you're dreaming up your startup right now my recommendation is to be good at everything, but to be insanely great at something. That's what gets me excited.

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* And, I should note, the founding team knew the venture market inside and out. We had done our research on which firms to approach based on what they were interested in, which partners to approach, had pre-sold the idea before the physical meeting, had customized the deck to highlight the aspects that particular firm/partner could grab onto most quickly, etc. Highly suggested in any case.

** My dealflow right now is pretty highly curated so I don't get a lot of pitches that are just, well, bad. Not to be judgemental. Bad, to me, is a founder who simply does not know what they're doing: a non-coder trying to enter a market either (i) that they just don't know anything about--generally where they've had a bad customer experience but have not done the research to understand the institutional framework behind the root cause, (ii) where there are great companies already doing exactly what they want to do and they've never heard of them, or (iii) that is so small that even revolutionizing it will create almost no societal value. Or, they could give a damn about creating societal value, they just want to make some money quick.

VC/Company Investment Visualizer

A friend asked me last week if I knew a tool to help him visualize which VCs were investing in a sector. I did not. But I realized I could pretty quickly repurpose the VC Bar Chart code and some unpublished code that pulls in data from a Google spreadsheet to show a force-directed graph. So, weekend project.

Data from Crunchbase, visualizaton using the d3.js library.

Here's my portfolio.

The site is here. Just start typing company names in the upper-left hand corner box and hit plus to add. Real name to Crunchbase permalink translation uses the list of companies as of Friday* or so, so if the company was added to CB later, autocomplete finds nothing;  just type in the permalink and the company will still be added. In the screenshot above a few of my companies had no CB investor entries, so they're just floating out there. Many of my other companies are not linked to me because CB does not mention me as an investor.

One way to explore is to enter a bunch of companies in your area of interest and see how the graph falls out.  Here's one of the AdTech industry.

The save functionality is experimental (to me, that is.) It uses HTML5 localStorage. The caveat is that you can't email visualizations around that way, and there may be times when your browser clears localStorage (sometimes when clearing cookies, for example.) If it does, you lose all saved visualizations.

The code is all client-side, so it's right there in your browser if you want to look at it. I found myself late last night using a non-analytical debugging process** when I was trying to get the 'load visualization' piece to work. I'll put it up on GitHub some time after I clean it up.

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* And I redacted the list to only include companies that CB showed having investors. The full list was too big to load efficiently.
** Mainly making random code deletions.

You can't manage what you can't measure. Not at scale, anyway.

A year ago I wrote, re investing in social marketing, "The social loop will share superficial characteristics with the display loop, but it's really completely different... the area with the most near-term leverage will be tools that help communicators understand the impact of how they are communicating and then help them make better decisions." This has turned out to be completely true.

I've been thinking about social marketing for five years. It has seemed obvious that major advances in marketing technique will occur through the social channel, but it was never clear to me exactly what those would be. I looked at and worked with a couple dozen social media marketing companies before throwing up my hands and declaring non-prescience.

My rule of thumb is that when the evolution of the landscape seems unknowable it is usually because the technology that will underpin the advance is still in flux. The obvious solution is dropping a level deeper in the stack and looking for investments there. In mobile, that meant Flurry four years ago and Media Armor a year ago. In social, it meant Awe.sm.

The smartest guy I ever knew in the ad business (like being the tallest dwarf, I know...) said, of managing people, "Whatever chart you put on the wall goes up."

-- Clay Shirky

That was me, the tallest dwarf, from back when I knew Clay, when he was just another guy.

I worked at IBM during the heyday of the Six Sigma movement. I was a design engineer, trying to optimize a very small piece of the central processor of what became the System 390 series of mainframes. As a design engineer there were several layers of abstraction between me and the silicon: the design language was a visual one--I wrote a flowchart which was compiled into a set of logic gates which were then mapped onto silicon. Aside from tweaking the logic gate-level design to try to get better performance, I spent my time at the flowchart level, as did most of the engineers.

Six Sigma methodology has you measure processes, find causes of errors and remedy them. The idea is to improve processes until there are fewer than 3.4 defects per million. IBM had a company-wide mandate to implement Six Sigma. I was subject to this mandate.

I asked my manager how I was supposed to measure my 'defects' and why would I even want to if I had to define them in such a way that I essentially never, ever made that type of mistake. He said "How are you going to improve if you aren't noticing your mistakes and figuring out how to stop making them?" "I already do that," I said, "I'm just not marking them down on some stupid piece of graph paper thats been pre-printed with a normal curve." He said "But then how can we manage it?"

Ah, Bach.

You can't manage what you can't measure. Stupid as managing designers on the binary idea of defect/not-defect and on such a stringent scale, constantly knowing how well you are doing so that you can constantly improve is extremely powerful. This idea, probably more than any other, drives my investment strategy: things that are not being measured are being managed poorly; creating new ways to measure creates ways of doing things immensely better, it creates entirely new businesses.

The fact is, you do get what you measure, whatever graph you put on the wall will go up. But the moral of that pithy aphorism was meant to be: be careful what you wish for.

If what you are measuring in social marketing is Likes or Follows, that is what you will get. But how closely aligned are these measures with what a business really wants: happy and loyal customers, higher sales? You don't know. No one knows. This particular loop hasn't been closed. Because the social gesture cause and business result can't be tied together in a measurable way, it can't be managed and it can't be improved.

I invested in Awe.sm's seed round because they provide core social measurement functionality, the ability to tie social actions into their actual results, to close the loop. I re-upped into their Series A because they're now doing something even more interesting: they're providing this functionality to other developers via API. Instead of being just an analytics player, they're now enabling the creation of an entire social marketing infrastructure that can use measurement to provide a ever-improving feedback loop.

I may have gravitated to marketing in part because dealing directly with people is too messy to ever even approach Six Sigma, but the engineer in me still believes that by measuring you can improve, and by linking measurement and algorithms you can create a feedback loop that allows you to improve adaptively and in real-time. This idea has revolutionized online advertising over the past few years. It's going to revolutionize social marketing over the next few.

iMapBox

I've always been the type who, when confronted with a one-hour task, will instead take two hours to automate it. Here's an example.

VCdelta is my bot that tracks additions to VC portfolio pages. It has its own twitter feed. Its twitter feed is about to surpass my twitter feed in number of followers. It seems my bot is more interesting than I am. I thought it would be interesting to graph the number of people who have followed me versus the number of people who have followed VCdelta over time. Twitter does not provide stats like that, but whenever I get a follow email from Twitter, I hit archive, not delete. So all I needed to do was count the follow emails by month.

Turns out Python doesn't have a very good library for using a mailbox as a data source. The Python email libraries assume you are planning on writing an email client. So I wrote an abstraction layer for the Python IMAP library. Code is here*.

Here's the code to count twitter followers:

import IMapBox 

me=IMapBox.IMapBox("imap.gmail.com",my_acct,my_pwd)
mymail=me["[Gmail]/All Mail"]

myfollows=mymail.frm("twitter").subject("following")

mydates=[myfollows[x]['date'] for x in myfollows]

The 'me=' and 'mymail=' open a connection to my email account and select a mailbox, in this case the All Mail mailbox. (The command 'me.list()' lists all the mailboxes for the account.)

The next line filters mymail so myfollows is only emails from Twitter that have 'following' in the subject line**. iMapBox is lazy--it doesn't fetch the emails itself until it has to--so this is pretty fast. myfollows acts like a dictionary, so you can len() it, ask for the keys()--these would be the message IDs--or the items(), iterate over it, or get items.

Each of the items in the dictionary is an email message. These also act like dictionaries, with keys like 'from','to','subject','date', and 'text'. The next line creates a list called mydates of the date each follow email was sent. It does this by iterating over each item in myfollows and pulling its date out. This is the slower part: when you set up an iterator, iMapBox gets all the headers***.

The part about counting follows per date I will leave as an exercise to the reader. Here's the graph of my follows and VCdelta's follows. I've been tweeting for some three years, VCdelta for six months.

On a sidenote, this is a logarithmic scale. The green line is my trend. This is odd, no? I mean, I'm not getting exponentially more popular, so this argues that a lot of follow behavior is algorithmic of some sort. I had expected more linear growth.  I also expect VCdelta to level out soon, as it reaches the limits of its natural audience.

Another example, email volume over time:

You can see where I started using my current email account full-time, in September 2006. And you can see when I started investing full-time, in mid-2009. And you can see why my email response time has slowed dramatically.

The code:

from datetime import date, timedelta
import IMapBox

me=IMapBox.IMapBox("imap.gmail.com",my_acct,my_pwd)
mymail=me["[Gmail]/All Mail"]

for yr in range(2006,2012):
 for mo in range(1,13):
  beg_month = date(yr,mo,1)
  end_month = date(yr+mo//12,mo%12+1,1)-timedelta(days=1)
  print mo,"/",yr,"\t",len(mymail.dates(beg_month,end_month))

This is an alternative way to count emails per month, filtering by date instead of collecting dates. The 'dates(x,y)' method filters the emails for only those that were received between date x and date y (inclusive.) This is faster because even the headers are never fetched.

Some other ways to use it:

c=mymail.frm('josh')+mymail.frm('matt')
d=mymail.frm('josh')-mymail.to('matt')
e=mymail.today()
f=-mymail.today()

The first is all messages from either Josh or Matt. The second is all messages from Josh that aren't also to Matt, the third is all today's messages, the fourth is all messages except today's.

 ----- 
 * I'm an electrical engineer, not a computer scientist. So I can build a waveguide to your specifications, but I'm not entirely sure that this code is all that good. Please, feel free to fork, suggest improvements, make improvements, tutor me on garbage collection or unit testing, whatever. 
 ** I like object chaining. I know it's not Pythonic, but I'm not sure why. It strikes me that since I don't really understand too deeply how Python garbage collects, that this may be creating extraneous intermediate objects. If you plan to use this is any sort of real code, you might want to figure that out. I did notice that if I object-chain the IMAP connection ('me' in this example), it gets dereferenced and gc'd, which invoked the very polite __del__ method, closing the connection. I'm not sure how to avoid that, so I just commented out the __del__ method, leaving a messy open connection to the server. 
*** My thinking is to only go do the time-consuming fetching of messages when needed: when an email message object is referenced or when an iterator is set up (on the assumption that when you set up an iterator, you plan to consume the whole set of messages.) This latter is because fetching 100 messages in a single fetch is far faster than 100 single message fetches. The default is to only fetch the headers, except when the text itself is explicitly asked for. This default can be changed by setting priority='both' or priority='text' when you call iMapBox to open a connection to the server. 

Disruptive innovation, buy vs. build, the most pernicious lie in business, and how to know if you're fooling yourself

If a man has good corn or wood, or boards, or pigs, to sell, or can make better chairs or knives, crucibles or church organs, than anybody else, you will find a broad hard-beaten road to his house, though it be in the woods. 

—Ralph Waldo Emerson, big fat liar

No matter what the dictionary says, you can't describe a company as disruptive without giving weight to Christensen's description of innovation. It's perhaps overly simplistic to divide innovation into two categories--disruptive and sustaining--but the strikingly different characteristics of companies pursuing these strategies makes the partition a natural one.

Sustaining innovation means finding ways to do things better. Lowering the cost of manufacturing a widget by 10%, making a widget 20% more durable while only spending 10% more, reorganizing a department so ten people can do the work of twelve, creating an integrated supply chain to deliver goods to your stores in smaller quantities and less time. That sort of thing. Sustaining innovation often results in products that exceed customer needs at a given price point. The proliferating options in Microsoft Office show a sustaining innovation cycle that has exceeded most of the market's need.

Disruptive innovation means creating a product or service that is radically cheaper but much less functional (and this needs to appeal to a customer set that was previously underserved, so disruptive innovation often creates entirely new markets) and then using sustaining innovation to improve it until it meets mainstream customer needs (but is still radically cheaper.)

Before Google, there was targeted advertising. Very targeted. Hog Farmers Digest (now National Hog Farmer) was aimed at hog farmers. If you were a hog farmer, you read it; if you weren't, you didn't. It was a pretty effective buy: not a lot of wasted impressions. But creating an entire magazine for a very specific market is a difficult business proposition. The fixed cost of putting a book together limits how small its audience can be and so how targeted its ads can be.

Google's disruptive innovation was being able to create content for next to nothing. They can create a page that addresses a market segment as small as a single person for nominal marginal cost. Even though the content was lower quality than that it was competing with--the lack of human writers and editors means that any specific page is much less useful than a well-written and thought-out page would be--it turned out it was good enough. And because advertisers could be so specific in their buy, they could spend much less money. This opened up an entirely new market: advertisers that don't have multi-million dollar budgets.

Existing publishers could not compete: they could not lower their cost per page to anywhere near Google's. If they tried, they would lose quality and the loss of quality would mean losing their existing customers. This is the beauty of disruptive innovation: it is almost impossible for incumbents to respond. Disruptive innovations are disruptive because business logic precludes old-line companies from shrinking their business to address the disruptors.

It's incredibly difficult and expensive to challenge incumbents with nothing but a better product. Sustaining innovations are easy to copy and well-managed incumbents are always on the lookout for challengers and willing to learn from them. But when a disruptor comes along, they are trapped.

*****

What kind of innovation are we peddling in adtech? Article after article calls our companies disruptive, but do we really fit the Christensen mold? A disruption scenario would look like this:

• the existing industry would supply a product of higher quality/functionality than the majority of potential customers actually needs and at a very high price;
• the disruptive companies would find a way to bring in a product of lower quality/functionality at a much lower price;
• customers that did not need and could not afford the old product would emerge as customers of the disruptive product, allowing the new companies the wherewithal to quickly mature their technology until it was competitive in the old product's market.

Does this sound like ad tech to you? It doesn't to me. The current ad-world is not supplying services at a higher quality than its customers need and there seems to be advertising inventory at every price point. If you can't supply advertising at a radically lower price point to customers who were previously underserved at a quality level that the incumbents are not interested in touching, you aren't really in a position to be disruptive. Almost all of adtech now is sustaining innovation: building a better mousetrap.

We clearly have a better solution than what existed, no argument. But the big lie of business, the pernicious fallacy that has deluded countless entrepreneurs, is that if you build a better mousetrap the world will beat a path to your door. It doesn't work that way.

*****

What is going on in adtech right now is clearly innovative. But because it's not disruptive in the Christensen sense, it means we're going to have to earn our money. We need to move fast to build scale.

There have been scores of M&A discussions in adtech this Summer and only a few have resulted in deals. One of the things I heard as an excuse over and over (from buyers, from sellers, from bankers, from founders, after a few drinks) is that the buyer said "we don't need to pay up for this, we could build it internally."

Build versus buy is an interesting discussion to have before you buy anything, especially something with the revenue multiple adtech VCs are looking for. Cold hard fact is, there's almost nothing out there in adtech that someone else couldn't build from scratch. The CTO would certainly tell the CEO that building would be cheaper than buying a company, and be right.

And yet, and yet. And yet the companies that are prowling for bargains still can't get advertising right. They clearly have a ton of tech talent in their core businesses, and the ability to hire more. They have the money to hire and manage and build adtech solutions. But they don't. Why not?

When I was at Omnicom, back in the 90s, investing in the early interactive agencies--clearly not disruptive businesses--the old-guard ad agencies that then made up the bulk of Omnicom's business talked big about building their own interactive units. But they never could. They also refused to pay the valuations the i-agencies commanded. They were on the sidelines while their clients hired hotshot young startups to build their websites, and some of the startups got pretty big in the process.

There were several reasons for this. Primarily, the old guard couldn't hire good people: no one who understood the web back then would go work for an agency whose primary business was making 30 second films for TV. Why would anyone who was any good go be a second-class citizen at a firm that was paying nothing but a salary and had no career path in interactive? Why wouldn't they go instead to Razorfish and get stock options and be a hero to their management everyday? They would, of course, and they did. And almost all the true stars of that era spent time in one of the independent agencies.

As then as now. Why would any competent adtech engineer go work for AOL or Yahoo or Twitter or any of the other big old companies where stock options issued today will in all probability never be worth anything? There are plenty of good jobs at exciting startups where there's the possibility of making actual money*. More importantly, why go to one of those big companies and be a second-class citizen, the "ad guy," when at a startup you're essential to their product?**

Companies can do very well at their core mission. But when their core mission is media or software or infrastructure or professional services, it's going to be really hard for them to get a foothold in the quickly changing adtech world. This never seems to be taken into account in build versus buy analyses: they can't build, and even if they could, they won't. And if they do, it will suck. Trust me, I've been there. And if you don't trust me, just take a look around.

But remember that the era of the independent i-agencies only lasted some six or seven years. At some point the number of people that could do the work more than competently was enough that even old-line agencies could hire them. At that point the i-agencies were like every other agency: they competed head-to-head with the old guard. Many of the biggest remained independent until acquired for great prices. But these were the ones who earned it. Unlike a disruptive business where nothing but guts, an innovative spirit and a huge dose of luck are necessary, competing head-to-head means competing: blood, sweat and tears.

We need to keep building, ignore the distractions and focus on winning clients, not just raising money, so that when it comes time to compete head-to-head, we will win. That's as it should be, of course, and I think many of our industry leaders have what it takes. But if you're starting an adtech company and you want to win, you have to know that you're in it for the long-term. It's a marathon, not a sprint, the cliche goes, and it's true.

*****

Meh, you say. I'm disruptive, I am going to go viral, achieve imminent world domination and sell to Google for $5 billion in two years. Neumann's an idiot.

Maybe. But disruptive businesses have certain characteristics. Ask yourself these questions.

1. Am I creating a new market, bringing in a set of customers for whom there was previously no value proposition?

Disruptive businesses bring out a product or service that is so far off the industry price/quality line that customers who would never have used the industry's products start to. This gives the disruptor the foothold it needs to start improving quality until it threatens the incumbents. Google AdWords is an excellent example of this.

Who are the unserved markets in advertising? Are there any? I think there are, and I think that if you don't see any, you need to think about what advertising is more broadly.

2. What is price in my market?

If you're in ad-tech, what does price even mean to your end-customers (the advertisers***)? Is it just lower CPMs? There have always been low CPMs out there. Is it higher ROI? That's probably closer to the mark. The best answer I have heard is that it is lower risk: the ability to more accurately predict ROI.

You have to credibly answer this question and then be radically better along this dimension if you are disruptive. I think there are many answers here, and your answer will depend on your answer to question one, above.

3. What is quality in my market?

In disk drives (Christensen's first case study), this is an easy question: quality is how much data can be stored. The disruptors built lower-quality disk drives at lower prices, then used the march of progress to threaten the old-line disk makers. The old-line disk makers' customers wanted more storage, not less, so they did not see this market and could not address it with the existing customer bases. But key to the disruptors long-term value was the ability to improve quality quickly. If they could not, they would not have been able to displace the old guard.

What is quality in adtech? Conversion? Click-through? Pinpoint targeting? And if you know what quality is to your market, can you then improve quickly along that metric so you serve not only the new market you've created, but the giant market that already exists?

Quality. I've been thinking about this question for ten years and don't have a definitive answer. Do you?

If you do, if you think you really have a disruptive business model, call me, I'm looking to back people like you.

-----
* If this is you, email me.
** Soldiers don't get promoted if they haven't seen battle. If you want a career path, always take the job in the middle of the action, even if it pays worse.
*** And are the advertisers really your customers? Why aren't the 'consumers'?