When should you buy ads? Let’s assume your goal is for people to click on the ads and give you money. (Reasons this may not be true: persuasion, brand-building, budget-maximizing.) The return from a block of ads is thus revenue - marginal_costs - ad_costs. Ads are an investment like any other; you keep buying them until your return on investment (revenue - marginal_costs / ad_costs) equals your cost of capital (usually the interest rate).

For simplicity, we’ll assume your marginal cost is zero. (My marginal cost is almost always zero, so this doesn’t strike me as too unrealistic.) So how do you estimate revenue? You can track how much money people who click on your ad give you, but this has two flaws. First, customers often give you more money over time. Maybe they buy level one of your video game when they click on the ad, but then they may buy levels two and three the next day after they beat level one. The future is always in the future, so revenue-per-user numbers may be too small.

Second, they may have giving you money anyway. Your video game ads probably run on video game review sites, where readers might buy your game just from the review, even if you hadn’t bought an ad. So your revenue numbers may be too big.

But these problems aren’t so serious. In the first case, the worst that happens is you don’t buy as many ads as you should. In the second, you don’t actually lose money, it’s just that some extra profit you could have kept has gone into ads.

But what are you bidding on? Ad sellers want to maximize revenue per impression, but ad buyers want to maximize profit per expense. In an ideal world, ad sellers auction off impressions (this is what Google Ad Manager does) while ad buyers bid per dollar of profit (entering their cost of capital).

Determining how much profit you make from an ad is hard. Can we just trust you? Let’s say you make $2 in profit per 1000 impressions and everyone else makes $1. Now you can lie and say you make $1 in profit and then pay twice as much per profit-dollar. Now you pay the same amount as before, but you win all the profit-dollar auctions. Now that’s not wrong — you’re clearly making more money than the other bidders, so you should win — but your bid isn’t cost-per-profit anymore, it’s cost-per-impression.

What if you paid based on revenue? Verifying revenue is difficult, but Google could do it if everyone was used Google Checkout. (If you sent some of your users to a non-Google Checkout system, Google could catch you and fine you.) Google offers nicer ads to Checkout users, but they still don’t have much market share, making this system impractical at present.

Some search engines apparently had cost-per-action (CPA) auctions, where you paid based on how many people actually bought things. I have no idea how they made that work, since lying about how many people took an action seems really profitable and easy. Maybe that’s why no one does this anymore.

That just leaves cost-per-click (CPC). Cost-per-click seems ideal, since it’s verifiable by both the ad seller (who uses a redirect link to track clicks) and the ad buyer (who sees the users show up on their page). It’s a nice half-way point between buyer and seller.

So the ad seller holds an auction for CPC and multiplies CPC by click-thru-rate (CTR) to calculate CPM. They shows the highest CPM ads, charging each the bidder below them’s CPC, times their relative CTRs. (In reality, Google doesn’t just use CTR; they also factor in the relevance of the ad and the quality of the page it goes to.) And, voila: we’ve derived the basics of an online ad system.

It seems like this should be pretty easy, and indeed Google does provide tools to calculate ROI, but apparently not to optimize it. What they do provide is a tool to optimize your cost-per-action. Does anyone know why this is?

It seems like an automatic ROI optimizer would lead many people to spend more money on ads. It’s hard to believe Google is leaving all that money on the table.

But Google does intelligently optimize is the ads themselves. The variance in click-thru rates between different ads is huge — it’s not uncommon to see two very similar ads, but one gets ten times as many clicks as the others. Google lets you put in as many ads as you like and automatically rotates them, showing ads with better CTRs more often.

One option is make the buyer choose. This is how Google Search works: Google holds an auction for each search query and buyers pick which ones they want to compete in. Another is to group related websites together and run ads evenly across all of them. This is how most smaller ad networks work. And then there’s AdSense. AdSense scans a page for relevant keywords, then runs the Google Search ads that won auctions for those keywords.

Google also knows a lot about ad viewers. By tracking what web pages you visit, they know what topics you’re interested in. I’m apparently interested in Unix, the environment, elections, government, and social science, so Google prefers to show ads on those subjects to me.

But there’s another way to think about ad matching: as a giant optimization problem. Which combinations of user, ad placement, and advertisement optimize click-thru rates (or, ultimately, ROI)?

For each of these, there are lots of variables. For each user, you know their history, geographical location, computer (browser, operating system, screen size), ISP, etc. For each ad placement, you know time of day, hosting website, page content, etc. And for each ad, there are numerous possible variations in phrasing and design that can be tested, as mentioned before.

The possible combinations are infinite. You can’t test all of them, so you need to come up with ones that are plausible. You can look at which combinations worked in the past: has this ad done significantly better in some cities than others, or at some times than others? And you can look for patterns across ads: do ads that do well on CNN also do well on MSNBC? These hypotheses can then be tested and, if they work, you start running ads more there.

Netflix claims they’ve made millions from slight improvements in their movie recommendations.¹ When they offered a prize for more, researchers found thousands of tiny patterns and came up with all sorts of innovative algorithms to try to get an edge. After 32 months, researchers doubled the algorithm’s effectiveness.

Imagine how much more is at stake for Google. Last year, they received $21 billion in ad revenue, of which 60% was apparently profit. Even tiny improvements would be worth the highest salaries — a 0.004% improvement would make $500,000. Doubling it would create unspeakable wealth.

Yet Google has no contest for improving ad click-thru rates. Indeed, press reports suggest they don’t even have an internal team working on it. The AdWords user-interface (recently redesigned from jaw-droppingly wretched to just wretched) would seem to suggest they don’t do this kind of optimization at all. Their blog asks people to optimize things manually. No doubt there are some things humans (even ad purchase reps) can do better than computers, but surely there’s a lot more they can do together — with humans giving the machine additional hints and hypotheses to test. But there doesn’t seem to be anything like that.

It’s hard to believe this is true. It’s hard to believe this can last.

Right now Google takes a 20% cut of every auction price. What if you were willing to take just 10%? You could give ad sellers a slightly higher CPM — they’d gladly run your ads when they paid more and Google’s the rest of the time. Then you can offer ad buyers a slightly lower CPC. As long as the money people made was more than the cost of setting things up, they’d switch. I’m actually not sure why this hasn’t happened.

Now imagine that you were a genius CS student who could come up with a better ad optimization algorithm. Your system would have a higher overall CTR, since it presented users with better ads. This means that, again, you can pay higher CPMs (since more people click per impression). And you can redirect some of the money you would spend on higher CPMs into lower CPCs, to attract advertisers.

But to develop the algorithms and do the optimization you need the data. Lots of it — lots of users, lots of advertisers, lots of ad spots. No startup will ever have that; it’s only left to Google (or whichever giant eventually replaces them).

I’m not normally one to be too concerned about improving Google’s bottom line (they seem to be doing alright), but as an ad buyer I’m frustrated I have to do this work myself. I’d rather solve the problem for everyone. And if Google wants to pay me for that, I certainly wouldn’t mind.

It’s a big decision to make your first hire, because what you’re really deciding is whether you want to keep a lifestyle business or attempt to cross the chasm and maybe even get rich.

There’s already a lot of great advice about hiring at little startups. Before I give you mine, here are some of my favorite articles, in no particular order:

• Smart, and gets things done by Joel Spolsky — The classic guide to what to do during the interview and how to know whether to “hire” or “not hire.”
• Why startups should ALWAYS compromise when hiring by Dharmesh Shah — There are many attributes you’d like to see in a hire, but compromise is necessary; here’s how to do it.
• Five quick pointers on startup hiring and Disagreeing with Entrepreneur Magazine by Dharmesh Shah — Assorted tips, all important.
• Hazards of hiring by Eric Sink — Great tips, including some specific to hiring developers (for more on the latter, here’s another).
• Date before getting married Part 1 and Part 2 by Dharmesh Shah — A strong argument in favor of working with a person rather than relying on interviews.

I’m not going rehash those or attempt a “complete guide to hiring.”

But I do have some fresh advice you might not have seen before:

A few years ago Patrick and me were invited to greek Blogger Camp. It was a very inspiring trip and we met a lot of great people. We felt, and were treated, like VIPs and stayed in beautiful hotels, enjoyed great food and partied all night.

At that same trip we also met Timothy Ferriss.
Yeah, 4 hour workweek Ferriss. He gave a presentation right after me in which he explained his idea about “more currencies than money”. What it comes down to is that if you want to do big mountain skiing in the Andes then you shouldn’t spend your life in a cubicle saving money to go big mountain skiing in the Andes one day.

You should just go.

Don’t take the detour to achieving your dreams. I was sitting there, in my swimming trunks, looking out over the warm blue Greek ocean and I ‘got’ it. I wasn’t doing boring work to go be able to afford a vacation to Greece; I was working in Greece, and it felt like a vacation!

Fast forward to 2009 and Huub van Zwieten. Huub wrote a book on how to quit your job. He isn’t saying that you shouldn’t work. He is saying that there are some people who are so passionate about the work they do that they don’t even consider it a job. I’m in that book too and one quote that he highlighted is “There are more currencies than money”.

Yeah, the quote I stole learned from Timothy. The reason I’m in the book, according to Huub: “Boris inspires in combining personal and professional life, with extraordinary results and a lot of fun”.

Now Huub is organizing an event, in the Netherlands, which I’m going to attend. On Novemeber 20 where you can experience the same adventure that Marijn (who the book is about) experiences. Would be cool to see you all there:

http://talentfirst.nl/werkeninovervloed/

If you’re wondering which you should measure and improve first effectiveness or efficiency – it’s not a chicken or egg question -choose effectiveness.  This may seem counterintuitive since financial pressures often take you down the efficiency path, but improving how your marketing effectiveness is about generating incremental sales and customer value as opposed to efficiency which focuses on reducing waste.  It’s hard to make decisions about where to cut when you don’t know what is and isn’t working.  This choice is about doing the right things and then focusing on how to do these things right. Only by starting with effectiveness can you demonstrate marketing’s impact  on the achieve key business outcomes and make a strong case for playing claim a strategic role.

Of course to measure effectiveness takes data.  One of the primary reasons we fall short of being a strategic partner is that we lack the data, analytical models and right metrics needed to demonstrate our contribution and connect marketing back to the business.    To drive effectiveness you will need analytics and data that can be used to tease out the causal relationship between particular marketing efforts and such business outcomes as customer acquisition, customer loyalty, and customer profitability.  The more you can show the impact of marketing efforts and investments on the bottom-line the more influence marketing will have on company business decisions and future business strategies.

VisionEdge Marketing, Inc, is a leading data-driven metrics-based strategic and product marketing firm located in Austin, Texas. The company specializes in consulting and learning services that help organizations use data to make fact based decisions to address market, customer, and product opportunities and to improve and measure marketing performance. For more information, go to www.visionedgemarketing.com.

The recent Facebook announcements were extremely interesting to me.  I continue to see a familiar pattern around relying too heavily on one platform.  From a developers standpoint, its hard to build a business if you don’t own the very ground that you are building on.  I have blogged about this topic before and I still feel the same today.

The Open Graph announcement was extremely interesting to me.  It is super-smart and shrewd of Facebook to open up its platform outside of its walled garden.  We all don’t have the specifics yet, but, it looks to be if you are outside of the FB world you can incorporate core functionality into your own site. TechCrunch’s MG Siegler does a nice job covering it here.

I wonder what happens if this really takes off.  For one, you as a developer would be outsourcing key elements of your community capability to another  company.  But more interesting is what is the impact of large players like Google.  If you are Google, you’ve got to be worried about Facebook  eating up more capability and eyeballs by potentially incorporating more traffic reach into its own platform.  Heck, what if FB incorporates really great social search using the Open Graph technology.  This is all predicated on world-class execution, but, the FB Connect technology has been already adopted on many top sites. If you are Google would you decide to penalize sites that use Open Graph in natural search results?

The happy meal is the quintessential version of great product bundling

How offers add value
There have been a lot of conversations about the evils of offers in social gaming, and one thing that’s getting lost in the conversation is the potential for offers to actually generate value overall.

Ultimately, offers are about “product bundling” and it adds value to the economy the same way that any product bundling adds value – by giving people more of what they want, often for less. And naturally, some configurations of different bundles are more effective than others, as we’ll see below.

This post will touch on a couple topics:

• Amazon and “relevant” bundling
• How to define good product bundles
• What’s actually happening with offers and bundling
• Solving the 1% ecommerce problem at the Point of Sale

Let’s get started:

Amazon.com and product bundling
When you are shopping at Amazon.com, and you’re in the process of buying a book, and different book is recommended, how do you feel about that? And even more, if you happen to decide you like both books and want to buy them, and Amazon is willing to give you an aggregate discount, how do you feel?

I think that intuitively, the cross-sell and bundling that happens on Amazon is great for the customer experience, and exemplifies the good side of product bundling.

Here’s some additional information about it from Wikipedia:

Product bundling is a marketing strategy that involves offering several products for sale as one combined product. This strategy is very common in the software business (for example: bundle a word processor, a spreadsheet, and a database into a single office suite), in the cable television industry (for example, basic cable in the United States generally offers many channels at one price), and in the fast food industry in which multiple items are combined into a complete meal. A bundle of products is sometimes referred to as a package deal or a compilation or an anthology.

The article goes on to say that the strategy is most successful when:

• there are economies of scale in production,
• there are economies of scope in distribution,
• marginal costs of bundling are low.
• production set-up costs are high,
• customer acquisition costs are high.
• consumers appreciate the resulting simplification of the purchase decision and benefit from the joint performance of the combined product.

Note also there’s a darker cousin to the above, called Product Tying, in which the consumer is forced to buy the whole set and not just one. This can lead to crappier products becoming more successful, and is the kind of thing you can read about in DOJ monopoly cases.

When bundling is helpful
As mentioned in the list form Wikipedia, there are many situations when bundling is helpful to both the consumer and the business. The bundling is extra helpful when:

• The product being bundled “makes sense” to the consumer
  • “Makes sense” often means a complementary good (drink+burger)
  • Or, it might share the same context (2 of product X are better than 1)
  • Clearly targets the same audience (people who like A also like B)
  • etc.
• Also it can be a great bundle if it was something you were going to buy anyway – like if you put two items in your cart, hesitated and took one out, but were then offered the bundle together

Just as in advertising, you need to “target” your bundles and make sure they are as relevant as possible. If the industry continues to deliver irrelevant offers to consumers, then it’s no surprise that ultimately the whole thing will be written off.

I’m sure I am missing many other examples from above – please write in the comments if you have additional thoughts.

Product bundling in the offers and leadgen world
With the above points in mind, you can imagine what is happening behind the scenes in the leadgen/offers world for social gaming.

The product bundle ends up:

• X dollars worth of virtual currency
• Y dollars worth of bundled product (plus Z dollars of built-in marketing expense)

We can look at this from a couple points of view.

For the product seller, if you’re selling a product for $20, and it costs you $5 to make the item, then you have $15 worth of margin to spend on marketing and still break even. Thus as the product creator, you would be excited about buying up to $15 of virtual currency for the user, if it gets them to buy your product. And if you can buy even less currency for them, that generates profit for you and the leadgen networks and publishers between you and the user.

From the user’s perspective, the above deal can work well if the bundled product “makes sense.” If you were already going to buy a Netflix subscription, and you are being offered the same price and you get some virtual currency to your favorite social game, then that’s great.

So when Michael Arrington of Techcrunch writes that it’s bad for users to pay more for in-game currency than if they paid cash, I think that’s just misunderstanding how offers actually work in the aggregate economy:

In short, these games try to get people to pay cash for in game currency so they can level up faster and have a better overall experience. Which is fine. But for users who won’t pay cash, a wide variety of “offers” are available where they can get in-game currency in exchange for lead gen-type offers. Most of these offers are bad for consumers because it confusingly gets them to pay far more for in-game currency than if they just paid cash (there are notable exceptions, but the scammy stuff tends to crowd out the legitimate offers). And it’s also bad for legitimate advertisers.

How offers solve the 1% problem at Point of Sale
Ultimately, the biggest problem that offers solve for advertisers is the 1% problem of e-commerce. That is, at any given time, the number of people “in market” for anything is actually quite small, and the percentage chance that they will actually purchase something is also very small. As a result, if you are at a “Point of Sale” and they have their credit card out, you might as well try to cross-sell and bundle as much related stuff as possible.

The real skill and value created in all of this, of course, is in actually creating useful product bundles rather than the asinine ones I keep seeing. Social gaming and life insurance don’t mix, the same way that Free iPods and life insurance didn’t mix for incentivized leadgen.

This doesn’t mean that offers companies aren’t totally slimy and the industry isn’t broken
I want to make it clear that all of the above isn’t a judgement on whether the offers industry is working or not working. Frankly, it’s probably pretty broken (I’ll leave that discussion for another post). But I do believe that there is some fundamental value being generated, in the long-run, and someone will build a great company around dynamically creating and targeting product bundles at Point of Sale, wherever you are across the internet.

Whoever does figure that out will make a lot of money, and we’ll forget about all of this social gaming stuff.

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If Facebook doesn’t clean up the offers industry, then this guy will

As a quick follow-on of my last post on How social gaming offers create value for everyone, it strikes me that what the industry needs to survive for the long-term is for one of the big players to break out of the stalemate of zero information sharing, and start advocating for sustainability.

Why all the advertising and leadgen companies hide their information
One of the big problems for the advertising and leadgen industries is the massive lack of information sharing between different parties. The reason is that ultimately, there are really just two parties involved:

• The paying customer
• The company providing the end product or service

But then lots and lots of middlemen get involved, including:

• Agencies / SEMs
• Ad networks
• Publishers
• Infrastructure providers
• Data providers
• etc.

Everyone in that extended chain are just middlemen, and their job is that for every $1 of profit, they want to outmaneuver everyone else in the stack to get as much of that dollar as possible. So if an ad campaign is doing really well, the agency doesn’t want to tell the ad network, for fear that the ad network will raise their rates. On the other hand, the ad network can’t figure out which of the publishers in their ad network actually deliver good performance.

This all sucks, and requires a central party to think long-term. That player might ultimately just be Facebook, but could be a publisher like Zynga (though I doubt it).

What information could be worth exposing
In general, I believe the key to thinking long-term on the offers industry would be to expose all sorts of feedback information, out in the open, at a granular level.

Users would also be able to get information like:

• What are they actually signing up for?
• A standardized view of every offer, like a checklist, similar to FDA mandated food packaging guidelines:
  • What is the 12-month cost of this offer?
  • What is the $ value of this offer to the advertiser?
  • Is this a subscription, yes or no?
  • Am I going to get emails?
  • Am I going to get a phone call?
  • Is my information getting shared with any other parties?
  • How can I cancel? (and this should be standardized too)
  • How do other users feel about this offer?
  • What is the cancelation rate?
  • How do I get customer support if I opt in to this offer
• Every offer should link to an “advertiser profile” on Facebook, with comments, ratings, etc.
• Facebook should be able to instantly ban specific advertisers and offers from ever coming up across all of Facebook

For advertisers and everyone else, they would get to see information like:

• Where are my offers showing up? (by app)
• What kinds of users are filling out my leads? (demographics, geo, etc.)
• What is the $ incentive for users? (by app, by $ amount)

Similarly, there is soft information like:

• How are users rating the app?
• How do they feel about the particular offer?
• How often engaged are users? How much churn is in the app?
• How often do they repurchase virtual currency?

For all of the above, I think a lot of companies would hate it in the short run, and a lot of dollars might be banned, but long-term, this would be better for the overall ecosystem.

Let’s hope that something like this happens!

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Call to action / conversion / user acquisition, whatever you want to call it. Its probably crucial to your web-based business strategy. 98% of the time, if you have not caught my attention on your homepage, in less than 3-5 minutes, you probably won’t see me again; This is probably a typical consumer on the web.

I ran across Zumbox.com, I’ve heard of this business model before, its a very narrow market (digital postal mail service) that was popularized for a time via a television show known as Startup Junkies. Startup Junkie featured EarthClassMail.com, the initial pioneers in this field, which offers a nearly identical product.

Comparing Homepages

Zumbox.com

These people get conversion. Video is really important! This is a new market/product space, we need to convince Joe Consumer Internet that this is a problem they are having, in plain English. Nothing does that better than video, with a disarmingly friendly female narrator. Unfortunately, The woman moves around (silently) for a few seconds, totally distracting me from the big pitch text on the top left, so I don’t even read it initially.

However, there is nothing else to do here, its learn and convert. there is no top nav to distract, no giant intimidating blocks of text, just simple pitch, simple sign up. ALWAYS start the signup process on the homepage. take them to another page if you must, but at least there is psychological buy-in immediately. I don’t love Zumbox’s buttons, they are not bold enough, they don’t scream “you want to click, nay, you NEED to click me.”

Nothing below the fold! I feel like I cognitively understand the entire homepage at a glance, which lowers mental overhead and anxiety of potential data overload. The homepage is almost like a lead gen form, which I think works to their advantage.

EarthClassMail.com

This page intimidates me, immediately. TWO columns of points? I am not going to read this. Personal? Small Business? Enterprise? I am not sure I care? Hiding below each of those tabs is 7 items that roll out below them, most of them seem to refer to the same set of information.

Information Overload. there is too much information and text thrown at me. This concept of digitizing postal services is new to the average user, however, they do not need a PhD in the concept. You can tell they are very concerned about you groking the business model, they give you a toll free number to ask them what the hell its all about!

Their call to action is barely a call to action, however I prefer their button style. Speaking of buttons, Sign up should not be the same size as tell me more, I can’t tell if orange is more important than green, and both feature bolded text.

Their is a hidden sign up button below the fold, I’ll forgive them for putting it their twice, but why not start the user on the sign up process? No form fields on the homepage.

EarthClassMail was definitely the pioneer in this field, so I give them credit for having to carry the burden of teaching their users the benefit of this service, however, too much data is going to make the user think this is going to just create more problems, or requires too much effort and up front investment to even justify signing up.

Pricing Strategies

Zumbox.com

Zumbox.com, to the pre-acquired user, is perceived as a free product! Now, clearly, there most likely is a “pro” featureset you upgrade to, or features you probably pay for per user (maybe the pay your bills feature?). This again relaxes the user, I can try this out, free of charge, and my commitment level pre-signup is very low.

EarthClassMail.com

Ouch, no free plan? How about a trial, not even 30 days? I’m sure if I called their 800 number, they would set one up, but clearly they want to make me call them to set that deal up. Setup fees! ewww. Again, this page has two CTA’s for the signup form. No form in sight, come on!

EarthClassMail Sign Up Process

Well, since I have to go out of my way to experience the signup cost/overhead associated with EarthClassMail, I felt it deserved to be reviewed in its entirety.

Page 1: Preamble?!

Are you kidding me?! I click sign up and the first thing I DO NOT see is the sign up form!? Okay, I understand, this is going to be legally hairy in a moment, but this could just flat out scare me away. Also, why have a cross-cutting copy page? Sign up for biz and personal can and should be different, make the copy specific to the conversion flow.

Page 2: Step 1 (hah) Choose your plan

This should really have been the initial signup bootstrap, I shouldn’t have to pick this now, I should have picked from one of these to start with from the initial CTA. I find this version of the form easier to read than their website, honestly. A lot less clutter. Lets choose essential.

Page 3: Step 2 Begin to tell us who you are

This form is boring. Forms are boring, make this more fun to complete. clearly, everything is required, why not just say that once and eliminate the noise? Also, I am now on page 3, and I have no idea how much longer this form is going to take. I need to know how many pages this is out of, at this point.

You get the point. the next page is billing and account setup.

Billing as Conversion Overhead

This is an interesting concept to roll around during your user conversion flow. If you do not offer a free entry point into your application, you require the mental overhead of setting up and entering billing information, before your user can even try the application. I would suggest this tactic be avoided whenever possible on the web.

Zumbox.com literally has no other steps to their conversion process, than the one you see on the homepage. After that form is completed, you are inside the application, and looking around at the features, first hand.

Final Note

There is no silver bullet in user conversions and landing pages! A/B Test everything you can, and learn from you users at every step of the way. What sort of stories/ideas/anecdotes do you have to add about user conversion?

My experience in venture capital
As I’ve blogged about before (though quite a while ago), I spent some time at Mohr Davidow Ventures as Entrepreneur-in-Residence – for more about what that job is, read here and here. A couple years before that, I had spent some time at MDV in their Seattle office, towards the end of the dot com bubble, as an analyst/intern. Both experiences were a ton of fun, and I justified the ~3 years in venture capital where I could have been starting companies as an education that would help me later on.

Now, a couple years later, I thought I would reflect a little bit on where the VC experience helped and hurt me relative to actually trying to build a startup. The net of it is that the time was mostly helpful, and a big chunk of knowledge transferred over, but it was mostly high-level stuff. A lot of running a startup involves mastering nitty gritty details, and the VC experience did nothing to help there

For the lazy/impatient, here are some key things I’d say where it can help:

• It helps with traditional investor/entrepreneur information asymmetries
• Lots of tactical holes still exist
• Investors can often oversimplify startup issues, or overmatch on patterns
• Helps with understanding of investor motivations, which can otherwise appear mysterious

Let’s dive into each of these issues below.

It helps with traditional investor/entrepreneur information asymmetries
Some of the stickiest situation for entrepreneurs are cases where they infrequently encounter a situation, which generates information asymmetries where an investor often knows much more. These asymmetries often involve events like fundraising, selling a company, recruiting executives, etc. In the positive case, investors can be helpful and coach startups through these times, which is great. In the negative case, it provides an opportunity for investors to engage take advantage of naive entrepreneurs, which is not so great. This is why sites likes VentureHacks and TheFunded are useful, because they help even the playing field.

Part of the problem for me, however, is that only the General Partners at VC firms end up actually doing deals. All the associates, EIRs, etc often participate, and you see the final deal terms, but rarely get to see all the back-and-forths that end up with the deal getting done. This creates familiarity with the process, but not the battle-tested experience of having gone through lots of nitty gritty negotiations. But even then, you hear about, and know what the levers are, so everything is less mysterious.

(But like I said, VentureHacks and TheFunded are great, and I only wish there were sites with that level of candor about this obscure industry)

Lots of tactical holes still exist
One area where a venture capital background didn’t help at all was dealing with all the tactical details of getting a company off the ground. In particular, the biggest hole by far is hiring and managing people, which gets abstracted at the financial level. Someone in VC-land can talk abstractly about strong teams, but you don’t have to go through the process of interviewing dozens of people to find the right person.

I’ve written up some of my thoughts here on this topic, in a post called “Building the initial team for seed stage startups” where I talk about a couple points I’ve come to believe:

• Hiring T-shaped people versus specialists
• Try to get doers
• More candidate flow solves a lot of problems
• Interview for the actual work you’ll be doing, not skillset trivia
• Raw intelligence is just one factor – don’t overestimate it

There are also some even deeper questions that are unanswered by VC experience, such as how you actually build out a suitable recruiting pipeline? Or how do you interview people where you don’t have the skillset to comment about their competence one way or the other?

I would say hiring is probably one of the most difficult areas to master, and although there are other block and tackle issues – accounting, leasing an office, operations, etc – getting the right people is just a very hard topic. It’s not a surprise that so many startups struggle with it.

Investors can often oversimplify startup issues, or overmatch on patterns
Venture investors often spread their time across a whole number of industries – you look at their websites, and they’ll say they invest in everything from consumer internet to clean tech to life sciences. MDV was no different, and we were responsive to companies across a large number of markets. One VC explained to me early on that you have to respond to what entrepreneurs are producing, and if you get too “top-down” about a particular industry, it gets easy to overinvest in a bunch of mediocre companies rather than trying intently to just focus on finding the best single team and opportunity you can.

Mike Moritz has talked about this before:

Moritz waxed philosophical by comparing venture capital investing to bird spotting. “I rarely think about big themes. The business is like bird spotting. I don’t try to pick out the flock. Each one is different and I try to find an interestingly complected bird in a flock rather than try to make an observation about an entire flock.” For that reason, while other firms may avoid companies because they perceive a certain investment sector as being overplayed or already mature, Moritz said Sequoia is “careful not to redline neighborhoods”.

Continuing with the ornithological analogy, Moritz pointed to Cisco and said, “There’s a lot to be said for investing in the ugly duckling.” When Don Valentine led Sequoia Capital’s investment in Cisco, many others had passed on the husband and wife founding team of Len Bosack and Sandy Lerner.

One of the difficulties for me personally in seeing a wide variety of companies all the time was that it was impossible to not start to pattern match and draw conclusions about the companies that were probably false. You end up in the proverbial “mile wide, inch deep” level of knowledge about that industry, which makes it all too easy to make generalizations. Similarly, there is a drive to simplify your understanding of a company, since you have to socialize it and talk to other venture partners about particular spaces and companies, which also causes oversimplfication.

Contrast this to startup life, where you end up devoting yourself to one company (which may encapsulate many ideas, as you iterate) for the period of years. You end up diving very deep into situations, and learning about all the different details tradeoffs that cause products to be successful versus not.

Helps with understanding of investor motivations, which can otherwise appear mysterious
Finally, one area where having a venture background helped a lot was understanding investor motivations in general. Entrepreneurs ask a lot of great questions, like, “Why don’t investors want to invest in my idea X which will be highly profitable?” or “Why does hot consumer internet startup X lose tons of money but is valued so much?” The answers to these questions drive a lot of investor behavior, which can be mysterious if you don’t know what’s going on.

The interesting part is understanding why VCs are structured the way they do, why they have a 1 in 10 portfolio strategy, and how they think about their Limited Partners. They have a boss too, of course

The major point here is that building medium-sized, profitable companies that aren’t growing quickly is not really part of the venture capital model. Knowing that can help with all sorts of things, such as massaging your business plan into something “sexy” that investors will respond to. Similarly, it will help get everyone aligned on major decisions, such as financing events, exits, exec team building, etc.

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There is a certain well respected venture capital firm (VC) that has a program for fledgling entrepreneurs.   The teams that are selected get a desk, a small stipend, and advice for a few months from experienced VCs.  I could imagine back when I was starting my first company thinking this was a great opportunity – especially the advice part.

Here’s the problem.  A few years into the program, approximately 25 teams have gone through it.  The sponsoring VC funded one team and passed on the other 24.  None of those other 24 have gotten financing from anyone else.  Why?  Because once you go through the program and don’t get funded by the sponsoring VC, you are perceived by the rest of the investor community as damaged goods.

Most early stage investors are bombarded with new deals.  There is no way they could meet with all of them, or even spend time seriously reading their investor materials.  In order to filter through it all, they rely heavily on signals.  The person referring you to them is a very big signal.  Your team’s bios is a very big signal. And if you were in the seed program of a VC who has a multi-hundred million dollar fund and who decided to pass, that is a huge signal.

Meanwhile, the unsuspecting entrepreneurs think: “I was at a prestigious VC this summer – this will look great on our bios and company deck.”  The truth is exactly the opposite:  the better the VC, the stronger the negative signal when they pass.

Thus, the most important question to ask before taking seed money is: How many companies that the sponsor passed on went on to raise money from other sources?

The best programs don’t have sponsors who are even capable of further funding the company.  Y Combinator simply doesn’t do follow ons, so there is no way they can positively or negatively signal by their follow on actions. (Although now that they have taken money from Sequoia people are worried that Sequoia passing could be seen as a negative signal.  I just invested in a Y Combinator company and was reassured to see Sequoia co-investing).  Other seed programs lie somewhere in between — they aren’t officially run by big VCs but they do have big VCs associated with them so there is some signaling effect.   (I would call this the “hidden sponsor” problem.  I didn’t realize the extent of it until I got emails responding to my earlier seed program posts from entrepreneurs who had been burned by it).

The most dangerous programs are the ones run by large VCs.  I would love for someone to prove me wrong, but from my (admittedly anecdotal) knowledge, no companies that have been in large VC seed programs where the VC then stopped supporting the company went on to raise more money from other sources.

As has been widely noted, startups – especially internet-related ones – require far less capital today than they did a decade ago.  The VC industry has responded by keeping their funds huge but trying to get options on startups via seed programs.  Ultimately the VC industry will be forced to adapt by shrinking their funds, so they can invest in seed deals with the intention of actually making money on those investments, instead of just looking for options on companies in which they can invest “real money.”  In the meantime, however, a lot of young entrepreneurs are getting an unpleasant introduction to the rough-and-tumble world of venture capital.

Disclosure:  I am biased because as an early stage investor I sometimes compete with these programs.