You Do Not Have To Sell What You Make

Here is a quick marketing lesson from a very successful businessman – Charles Revson, the founder of Revlon:

“In the factory, we make cosmetics. In the drug store, we sell hope.” (Source)

It is a lesson that is easy to forget, particularly in the world of software, where we mostly try to sell what we make. Well, think again. Is your marketing message tuned to what you make or to what people want?

You do not have to sell what you make. You just have to sell what people will buy.

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Paul Graham Vs Albert Einstein

Paul Graham:

“Empirically, the way to do really big things seems to be to start with deceptively small things. Want to dominate microcomputer software? Start by writing a Basic interpreter for a machine with a few thousand users. Want to make the universal web site? Start by building a site for Harvard undergrads to stalk one another.

Empirically, it’s not just for other people that you need to start small. You need to for your own sake. Neither Bill Gates nor Mark Zuckerberg knew at first how big their companies were going to get. All they knew was that they were onto something. Maybe it’s a bad idea to have really big ambitions initially, because the bigger your ambition, the longer it’s going to take, and the further you project into the future, the more likely you’ll get it wrong.”

Summary: Find the tiny thing that turns into the giant idea. Find the dinosaur egg (Source)

Albert Einstein:

“One should not pursue goals that are easily achieved. One must develop an instinct for what one can just barely achieve through one’s greatest efforts.” —Albert Einstein (Source)

‘Building a site for Harvard undergrads to stalk one another’ does not fit Einstein’s description, obviously.

Maybe research and business are two different things, after all?

(Image Credit: Choosetoawaken)

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An Idea Is A Pointer To An N-Dimensional Array

Recently, there has been a lot of criticism on the whole concept of Ideas – common wisdom seems to be moving from ‘Ideas are plenty, execution to key’ to ‘Ideas are evil’. Here are some reasons why we think Ideas are not evil.

An Idea is basically a pointer to an n-dimensional array. Imagine memory. The toughest part is getting to the location (the overall area) – once you are there, you can play around with pointer arithmetic to get to the exact location you want. OR to the exact location that has the maximum value. The initial idea is the pointer that takes you to the area. How do you plan to locate the memory location with (atleast) a local maxima if you cannot get to a part of the graph in the first place?

The ‘Ideas Are Evil’ thought assumes that Ideas are very precise – they might be, but more often than not, you just know you need to move west, for example. That is the idea. Here is PG:

“I think the way to use these big ideas is not to try to identify a precise point in the future and then ask yourself how to get from here to there, like the popular image of a visionary. You’ll be better off if you operate like Columbus and just head in a general westerly direction. Don’t try to construct the future like a building, because your current blueprint is almost certainly mistaken. Start with something you know works, and when you expand, expand westward.”

If you digest the fact that ‘move westward’ is the idea and not ‘move to location with co-ordinates x,y’, you will realize that Ideas are not evil – they are a godsend.

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Paul Graham: ‘Money Is Not Wealth’. Really?

Paul Graham writes very convincingly. So when he makes an argument saying Money is not Wealth and backs it up with strong points on how money is just a medium to move wealth but it is only wealth that can be created, it is very difficult to spot fallacies of any kind in the argument. But we spotted a weak signal of Narrative Fallacy in the argument.

While his argument on how it is wealth that needs to get created is spot on, he goes a little too far with the assumption that Money is just a medium. It used to be, in the old days when there was a more or less “fixed” amount of money. But in today’s world of operation twists and QEs, looking at Money as just a medium to move wealth around, would be a mistake. Why do we say that?

Not because Bernanke can print Money. But because, the premise of Paul Graham’s argument, which is that you need to create wealth – something people want, makes this critical assumption:

“The advantage of a medium of exchange is that it makes trade work. The disadvantage is that it tends to obscure what trade really means. People think that what a business does is make money. But money is just the intermediate stage– just a shorthand– for whatever people want. What most businesses really do is make wealth. They do something people want.”

The issue though, is that the medium is heavily manipulated these days. In a scenario where governments and central banks can essentially create money, just because they can, looking at Money as just an intermediate stage would be a serious mistake. It is very much part of the equation (unless attempts like Bitcoin change the concept of Money) – a central bank issuing currency based on an asset takes a totally different meaning when that asset is just trust.

Startups need to understand that the concept of creating Money is changing, and hence need to err on the conservative side, when the wealth they create, gets translated into Money. One example is valuation. Remember this is more or less free “money” (low interest rates) – the economy is bad but who cares – the cost of capital is unbelievably low, you shd count that in when you raise money, for example.

Is it not strange, that investors conveniently refer to a ‘bad economy’ and never refer to a zero percent interest rate scenario, which shd be the more relevant question – the cost of money?

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Blaming Bernanke For QE2

NYTimes has an article today titled “Stimulus by Fed Is Disappointing, Economists Say”. The key argument being put forth is that the bond buying program did not achieve enough – there has been no significant improvement in many parameters including growth inflation and employment.

This kind of blame is classic narrative fallacy. Let us look at the definition of Narrative Fallacy again:

“Our need to fit a story or pattern to a series of connected or disconnected facts”

This from the article:

“I wasn’t a big fan of it in the first place,” said Charles I. Plosser, president of the Federal Reserve Bank of Philadelphia and one of the 10 members of the Fed’s policy-making board. “I didn’t think it was going to have much of an impact, and it complicated the exit strategy. And what we’ve seen has not changed my mind.”

Thats classic “I told you so” – which is a clear symptom of Narrative Fallacy. We believe the response from The Economist – Who’s disappointed in QE2? nails it:

“The Fed chose a direction rather than a destination, and when its action left it short of the destination, it opened the door to criticism that the direction was wrong, when in fact it may simply have traveled an insufficient distance (perhaps thanks to unexpected headwinds). If you target a destination, you don’t run into that problem.”

Source: NYTimes, The Economist

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The Airbnb Episode: Classic Narrative Fallacy?

Fred Wilson’s post on not funding Airbnb, and then PG’s response with some email communication around that time – put these things together, and you get a great lesson for any VC: summarized very well by Fred:

We made the classic mistake that all investors make. We focused too much on what they were doing at the time and not enough on what they could do, would do, and did do. I am proud that our portfolio is full of companies where we saw the vision before other investors did and backed a great team. But we don’t always get it right. We missed Airbnb even though we loved the team. Big mistake. The cereal box will remain in our conference room as a warning not to make that mistake again.

If there ever could be a textbook example of Narrative Fallacy, this would be it. Let us look at the definition of Narrative Fallacy:

“Our need to fit a story or pattern to a series of connected or disconnected facts”

Remember what triggered this post: this question: “Tell us about something you saw that was intensely interesting but was not something you’d invest in. And why.”

Looking back at events to gather evidence for this is simple, as PG has proved. It is easier to fit a story as well (if the founders are great fund them) – hindsight is 20-20; the tricky thing is this: what is the heuristic to identify such greatness?

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The Problem With The Pew Study

“65% of internet users have paid for online content” – you will see this headline all across the internet in this coming week. Thanks to a survey by the Pew Research Center, these numbers will be interpreted in multiple ways and mostly used to convince stakeholders of all categories that people have finally started paying for things on the Internet. The full report is here.

So whats the issue with the study? The one number from the report that will NOT be quoted is this: 1003. That number is the total number of people that participated in the survey.

From the report:

The PSRAI October 2010 Omnibus Week 4 obtained telephone interviews with a nationally representative sample of 1,003 adults living in the continental United States. Telephone interviews were conducted by landline (672) and cell phone (331, including 134 without a landline phone). The survey was conducted by Princeton Survey Research Associates International (PSRAI). Interviews were done in English by Princeton Data Source from October 28?November 1, 2010. Statistical results are weighted to correct known demographic discrepancies. The margin of sampling error for the complete set of weighted data is ±3.7 percentage points.

Definition of sampling error from Wikipedia:

The likely size of the sampling error can generally be controlled by taking a large enough random sample from the population,[2] although the cost of doing this may be prohibitive; see sample size and statistical power for more detail. If the observations are collected from a random sample, statistical theory provides probabilistic estimates of the likely size of the sampling error for a particular statistic or estimator. These are often expressed in terms of its standard error.

So here is what is missing from the Pew study: Where are the probabilistic estimates of the likely size of the sampling error? The report quotes some percentage points – what are the calculations that have gone into it?

And for everyone claiming that most internet users now pay for online content – this is classic Narrative Fallacy. Yes there has been a survey and there are results. Yes there has been an uptick in online content purchase activity. But connecting these is Narrative Fallacy – our need to fit a story or pattern to a series of connected or disconnected facts.

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