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Archive for September, 2010


Why Angel Investing Is Like Selling Narcotics

Tuesday, September 28th, 2010

There is collusion?

Anyway, I knew everyone would want my opinion on how things went down since I was at the meeting and most of these people call me when they are thinking about things like this, so here it is:

Ron Conway: Awesome investor, slightly disingenuous email

Dave McClure: Open mouth, insert foot

Collusion: Probably not that big a risk.

Let’s drill down.  So these two meetings happen to discuss how deal terms could be improved if people agreed (read: colluded) to abide by a collective set of rules.

That is kind of what brought venture capital to where it is today.  New angel investors are being born every day in Silicon Valley and NYC.  I confess that if Ron Conway offers you money and the terms kind of suck, I would generally suggest you take his money.  Some people won’t.  As the terms get worse, more wouldn’t.  I don’t think any of these investors think their deal flow is so amazing that they pass on deals that are awesome.

Great entrepreneurs have a lot of ability to drive the terms, I think we all agree there.  Any investor would say there are not enough great entrepreneurs to invest in, so there is competition for those deals (Disclosure: I am raising a seed round for my startup and I am not feeling like FourSquare, so I don’t put myself in that bucket.)  If there is competition, collusion will fail.  Then individual investors start moving the line on individual entrepreneurs (I worked with him and he is a superstar!) and all of the sudden it is all out the window.

So then Dave McClure writes this blog post.

I figure a blog post is one of three things:

  • A denial that the meeting happened
  • A denial that the meeting was about collusion
  • An argument that driving to standard terms among angel investors is good

I was a debater for many years and I have to say, that about rounds out the arguments one could possibly make.

Dave probably should have taken his own advice and had the sense to write nothing.  Instead he writes a rambling version of #2: This meeting was not collusion, it was simply a meeting of angel investors.  Pre-money valuations are too high these days.  We discussed valuations, term sheets, convertible notes, and other things.  But if you are a great entrepreneur none of that will matter.

Sounds suspiciously like “it was informal collusion, not formal collusion”.  If you are going to make that argument, you are better off probably saying nothing because people that love you will think you are ok and people that hate you will find this proof that you are evil.  Which is pretty much what you would have had if you had said nothing.

Further, I think in a situation like this you want to come across as humble, thoughtful, and reasonable.  I think even Dave would agree that his writing style does not really fit that style.  The result is that he comes across as defensive, which you don’t want to do.

Then Ron Conway, probably the most famous angel investor out there, pens this email.  Best thing about this email: He sent it to specific people.  This was not a blog post for the general public.  He was telling certain people that he didn’t like them.  What is not too like about that.  If you can’t keep it inside you any longer, I think it is totally reasonable to send someone an email saying you hate them.  (Although you probably need FU money to decide that you can’t keep it inside any longer.)

Also, as I said, I thought that the email felt a little disingenous.  He has a fund.  He is managing other people’s money.  He does have a little bit of a fiduciary duty.  In the same vein, virtually all of these angel investors are rich by almost any person’s standards.  They are angel investors because they want to be involved in building stuff.  Josh Kopelman didn’t start FRC for the money any more than Ron Conway did.  Josh is probably the only person in this blog post that I actually know and he loves building.  He has a passion for building that gets people excited.  I would put his passion up against any angel.  Peter Thiel didn’t start Founder’s Fund because he was broke.  Aydin Senkut: not broke.

Now, I recognize that none of these people were probably people on Ron Conway’s email thread, but the central point is this: Almost everyone who does angel investing loves building companies.  Anyone with a fund that is not their own money has some fiduciary duty.  Also, as Jerry Neumann says, in a great post, if you don’t make money, you don’t get to fund more start-ups.

A perfect example of, “This blog post was worth what you paid the paywall to get access to it.”  I know none of these people, I love all of them. People make mistakes, I don’t think too much of this molehill.

What is a Retargeted Click Worth?

Sunday, September 26th, 2010

Great post stating the obvious for the record (a frequent tactic of my blog) by Alan Pearlstine on AdExchanger.

His point is that last click attribution overvalues the last click, particularly in retargeting campaigns.

I see more and more companies offering CPC retargeting on display inventory (that they probably had to buy on a CPM basis).  This is kind of a no-brainer to offer because click-through rates are so high that the cost of testing is probably not excessive.

Here is my question coming out of that:

Are the CPCs that people are paying for retargeting campaigns greater or less than the appropriate proportional value that should be attributed to a retargeting impression?

Post your best guess in the comments.

How To Build A Great Start-up Economy

Wednesday, September 15th, 2010

Building an economic environment in a microcosm might look a lot like a farmers market.  If you are starting a farmers market, it can only be so big to start.  If you have tons of farmers but not tons of consumers, the farmers don’t make money and leave.  If you have tons of consumers but not tons of farmers, there is not enough to buy and the consumers leave.  You have to start building each metaphorical leg of the stool to achieve big size.

If you are looking for the ad network metaphor, it is the exchange, duh.  You need advertisers to get inventory, you need inventory to get advertisers.

Anyway, lots of people talk about lots of things when it comes to building a great start-up economy, but I wanted to talk about mine.  Here are some stool legs that have to be built for an awesomely vibrant economy:

  • Great schools: Austin has UT.  San Francisco has Stanford.  Boston has some schools, I have been led to understand.  Great schools give start-ups access to people who will work 60 hour weeks for $30k/year – and think they got a good deal!  Cheap, smart talent is critical.
  • Big companies: Austin has Dell, etc..  Big companies retain college grads and put them through monstrous training programs.  Big companies also have skilled individuals who become intimately familiar with markets and disgruntled with big companies.  These people start companies and provide experience when companies need it.  If you were in Austin and needed a young, hungry enterprise sales guy with at least 3 years of experience, there are about 10,000 available.  Big companies also have compensation alignment problems.  Super-duper stars that join right out of school are grossly underpaid relative to their value for 10 – 15 years because big HR requires alignment.
  • Big Success Stories: You need a few companies that won big.  This does a lot of things, but first and foremost, people that worked there think it is easy.  They want to get rich, they want to do a start-up, and they have a built in network of relationships in an industry.  In Baltimore, is a classic example: Millenial Media, TidalTV, LocalRollCall, Deconstruct Media, Lotame and others are all essentially companies inspired by the success of  Further, companies like Carchex, DoublePositive and Blue Sky Factory essentially came from the same network (Ferber relationships) and staffed up via access to people and investors.
  • Investors: I mean A round and seed investors.  And I mean sophisticated investors.  People have to be willing to write checks to these companies.  An environment that seems conducive to funding energizes entrepreneurs and creates the possibility of big hits.  If all of the companies are bootstrapped, you don’t create the network effect of creating Big Success Stories and Big Companies that fuels the economic feedback loop.  Specifically, you need enough investors that there is aggressive competition for deals and pressure to move quickly as an investor.  When I lived in Philadelphia, my constant example was always Safeguard Scientifics.  They were the only big VC firm actively investing in Philadelphia and the result was they felt little pressure to invest.  They could bide their time and wait to see how things turned out.  This is always bad for entrepreneurs because every deal has warts.  Part of what makes Silicon Valley what it is are the legendary “term sheets by that evening”.  There are so many investors and so much pressure to do deals that some deals get funded before they have nailed their business model.  Not every company works out, but enough pivot their way to a business model that the economic loop is fueled.  Alternately, without aggressive funding, the time it takes to pivot a business model is so extended that the loop becomes derailed.  Investors have to aggressively be seeking to fund entrepreneurs.

Those are my four things.  Access to talent and capital and people with the motivation to win and the relationships to get them where they need to go.  If you have that, you are pretty ready.

Y Combinator and incubators are essentially sub-categories of big success stories and funding.  People that have participated in Y Combinator have won!  And they introduce you to a network of people that have won and tell you how easy it is!  (Just work really hard and get a little lucky!)  And they help you raise money!

I left out Government.  I generally think that no government institution will be able to institutionally move fast enough to help small tech companies.

Anyway, that is my opinion: You have those 4 things, you are off to the races.  What am I missing?

Fantasy Football Opinions and Online Marketing

Monday, September 6th, 2010

This post is going to be crazy because I am going to deep dive on fantasy football draft strategy and, in tribute to my loyal fan base, which is no doubt sick of this new football thread, include a reference or two to online marketing. It is going to be sick!

Let’s get started.  Most people doing fantasy drafts simply make a list of who they think the best players in the league are and bang, bang, bang, draft.

Let’s call that “Old school media planning strategy”.  Or let’s call it “People who evaluate campaigns based on CTR“. Or “people who don’t love math”.  Or “people who suck!”  Or “me”, most years.

Anyway, here is what I think you are supposed to do.  First, recognize that there is data and there are algorithms.  Algorithms take data and tell you what you should do, hopefully.  If you feel as though what the algorithm is telling you to do is wrong, the problem could be that the algorithm is bad or the problem could be that the data is bad.  Figuring this out is absolutely critical.

There are three algorithms in fantasy football draft strategy, one of which is simple and perfect, one being the most interesting algorithmic challenge, and one being shear poker madness.  Here is the model I use when I think about optimizing the fantasy football draft process:

The algorithm that works right every time is the middle algorithm: Given an accurate prediction of future player performance and an understanding of the scoring rules for your fantasy league, you can predict with absolute accuracy the scoring of other players.  Simple.  The problem is everywhere else.  Let us walk through the process sequentially.

The first thing we want to do is generate a prediction of how each player will perform in an upcoming year.  The best indicator we have of this is past performance, however much like your favorite mutual funds, past performance is no guarantee of future success.  Everyone who is remotely familiar or unfamiliar with sports recognizes this, so there is a degree of guesswork and other “psuedo-algorithms” injected into this process.  One could take average performance over the last several years, the age of the player, and an algorithm that compares past performance over time to performance of other players at the position at a similar age to model performance in the upcoming year, plus you are really high on this rookie running back.  But the point is that you want to model what you think they will do on the field next year.  Not “where I think they should be in my fantasy rankings”.  If you think Player X should be above Player Y in your rankings, you clearly think that Player X will have better statistical production than Player Y.  If not, you are doing yourself a grave disservice.  My point is that you don’t simply bump someone up in your fantasy rankings.  What you do is model how their actual production will actually be different then run it through the algorithm to generate your fantasy rankings.  Change their predicted production, not their ranking.  Post algorithm “manipulation” indicates a flaw in an early step in the process that should be addressed at its root.  So we take a bunch of data and generate a prediction of how each player will perform in the upcoming year.  Then we apply league scoring rules to determine how many points each player will score that year.

A lot of fantasy football players would stop there.  If you had a list that showed with absolute certainty how many points each player would score, you might think you would be in pretty good shape for your fantasy draft, but you can go further. A really excellent model then arbitrages the players, positions and league. What you would like to do is generate a model that arbitrages the value of players against each other. Let me give you a simple but preposterous example: You are in a 5 team league.  You know with absolute certainty the point production of a variety of players and you are in a league that only allows you to start 2 players each week: A QB and a RB.  You have the first pick in the draft and the highest scoring player in the league this year will be a QB. Simple, you pick the QB, right?  Wrong.  By analyzing the relative strength of each position, you realize that the top 10 QBs all score with 10 points of each other, yet the #1 RB scores 50 points more than the #2 RB.  Knowing this, you realize that the relative value of the #1 RB is much higher than the relative value of any other RB in the draft (or league).  Selecting this RB will ensure your fantasy victory this year because having the #9 QB (The last pick of the second round, worst case scenario) is not significantly different than the #1 QB.  The arbitrage opportunity is typically more subtle (After the top 3 QBs, the next 6 QBs are basically the same), but identifying the relative value of players is critical to successful drafts.  Recognizing where the “cliffs” are is key.

You may need to amp this model up by modeling production in the last weeks of the season (when fantasy playoffs are likely) and considering the impact (resting players, WRs vs. Darrell Revis, etc.) and factor in the draft tendencies of other players (True story: I drafted Tony Romo in the third round last year just to trade him to a guy that loved Tony Romo – the result: I got a Top 20 player for a Top 30 player.).  This is the poker part of the equation.  Knowing your cards and the cards on the table are one thing, reading other players counts for a lot – The #1 defense is worth a lot more than the #2 defense, but how long can you afford to wait to grab that defense?

This same logic is critical in online advertising.  Recognizing the effective cost of media is huge, but identifying the best opportunities to exploit media value is how you take it to the next level.

When Did Retargeting Get So Creepy?

Wednesday, September 1st, 2010

I find it creepy.  It is a good thing I don’t follow New York Times reporters on Twitter or you might find that splashed across a major paper today.  These days I feel like I see completely incongruous ads showing on inventory and I know they tracked me there.  (I have not read the Times article or any other related articles, for what its worth.)

(This is “LeadBack” or retargeting, as explained on the Japan site today.  Notice how the cookie looks like a golden coin!)

As the story was told to me, John Ferber was actually the person that invented retargeting.  He had a bolt of lightning in his brain one day that made him see how the technology that was being used for analytics and conversion pixels could be applied to deliver ads to people after they had visited a website and he named this “Advertiser LeadBack”.  (Advertiser LeadBack is a designated trademark of, a wholly owned subsidiary of AOL)  Advertiser LeadBack was a phenomenally successful product.  So successful, in fact, that advertisers would ask other companies for “LeadBack”. felt like they were the Coca-Cola of the trade, the brand identity of their retargeting solution was so popular and well-known.

One battle we continually fought at was the battle to cut down the number of retargeting campaigns in a buy.  (I thought I had posted the white paper I had written on this subject to the blog, but I cannot seem to find it.)  Essentially, our thesis was this:

  • Advertisers wanted to spend more on retargeting because it performed so well, but they still frequency capped campaigns because everyone agreed that high frequency was not improving performance.
  • had the biggest network from a reach perspective.
  • Most of the other networks were buying the same inventory to get reach, just different frequencies.
  • Ipso facto, buying a campaign on another ad network was typically simply increasing the frequency to a user rather than reaching new users.
  • Buying retargeting campaigns from other companies was wasteful.

As it turns out, every time we won that battle, I now think there was another effect: We decreased creepiness online.

I find it creepy.  No lie, it is totally incongruous to see some of the ads that I see on some of the sites that I see them on.  We talked about creepiness all the time at  Ho Shin’s ( General Counsel) favorite example was “If I visit a Korean site and then visit the Washington Post, we can’t show an ad in Korean.  It would freak people out!”  While the ads I see are all in english, I get the same effect regularly today.

I attribute four things to the rise in the creepiness factor:

  • Small advertisers having access to retargeting technology.  At, we had huge minimums: $25/k month.  Only the biggest advertisers in the world advertised with us.  If you advertised with us, you were spending an absolute bucket of money advertising online.  Only a tiny sliver of your budget was being devoted to retargeting.  The result was that people did see these ads all over the place and most of them weren’t retargeted.  Further, people had become accustomed to the idea that big advertisers ads would appear in random places as part of a network buy.  So if you went to a big web site and then saw an ad for that website somewhere, you could write it off to big marketing campaigns.  Not too creepy.  With the influx of small advertisers, now people see ads all the time that they know had to be targeted to them.  These small advertisers are not buying ad space on all these sites!  They are only here because I am here.  Creepy!
  • Customized creatives.  It is one thing to see a Best Buy ad.  Best Buy is a big brand, they spend a lot on marketing.  It is another to see the TV I was just looking at being shown to me again.  Creepy.
  • The dramatic increase in retargetable inventory.  When most people bought most of their retargeting via, while we had huge reach, we actually worked very hard to limit the amount of frequency that we bought.  This was because typically we didn’t have that many ads to show any given person.  (As I said, we had high minimums which limited the number of advertisers we worked with at any given point in time.)  The result is that you would only see a couple of ads.  To extend the Best Buy metaphor, you would go to twenty or thirty web sites and you would see a specific ad that had been retargeted to you on one or two.  The campaigns were frequency capped and we simply didn’t have that much inventory.  A few billion impressions per day.  Now, with the advent of exchanges, people can peak at 10 billion plus impressions every day and people are much looser with frequency caps because the ROI continues to be strong.  The result is that you might see these retargeted ads on 10 or 15 of these web sites.  Even the biggest advertisers probably aren’t buying all the inventory directly!  They must be following you.
  • My final point is, in some ways, simply an extension of the above: Quality of inventory is declining.  I don’t mean quality in an absolute sense, but in that abstract sense that advertisers tend to think of quality: Big Brands.  As long tail inventory gets exposed to exchanges, it just feels less like an advertiser bought the space and more like the advertiser bought you.  Best Buy inventory appearing in Yahoo! Mail?  But of course!  Best Buy ads appearing on random blog about punk rock?  Bizarre.  Creepy.

I recognize there is no going back, but to deny the creepiness is a lie.  We always discussed how it would be “best” if people felt like these ads were not following them at all.  The point of these ads, from a squishy brand perspective, is that when a consumer sees these ads, they bolster the credibility of the advertiser – “Wow, that web site is big enough to be advertising on some of my favorite sites, I trust that web site more.”

It would be interesting to see someone A/B test some of these hypotheses to determine their impact on the value of retargeting campaigns.  Get to work!