Ways to think about market size.

When you try to work out the market potential for something fundamentally new, you’re actually trying to resolve two, linked problems.

  • First, you have to look past what it is now, and see how much better and cheaper it might become
  • Second, you need to think about who would buy it now, and who else would buy it once it is better and cheaper, and how it might be used. 

The second problem is actually the hard one. Anyone with a sense of history ought to have been able to look at a phone the size of a brick and say ‘well, this could come down to the size of a pack of cards and cost $100, given time”, just as anyone should have been able to look at the Krieger electric landaulet above and see that it would get much better and much cheaper, just as trains and steamships had done. If you understood technology, that much was pretty easy. But if automobiles had only replaced existing horse-drawn carriages and carts then the market would have been much smaller. The hard part was to forecast Wal-Mart, and Los Angeles. 

That is, it’s easier to predict ‘cheaper and better’ than to predict the changes in behavior that will come from that. And pricing is only one dynamic – once the price falls below a certain level it stops mattering. Cheaper and better is necessary but insufficient: if billions of people can afford it, it doesn’t follow that billions of people will buy it. You need to have a theory as to why more and more people will care.

Hence, if I’d shown you a 2015 PC in 1975, would you have predicted that there’d be 1.5bn of them on earth 40 years later? Why? If I’d shown you an iPhone or Android smartphone in 1995, would you have predicted that we’d now be on track to have 4bn of them on earth – fourth fifths of all the adults on earth? 

So, to work out market size, really, you have to work out who will care, if it is cheap. To do that, as for any estimation, you look for numbers that might tell you – other, similar products, or the products you’ll compete with – something that can act for a proxy for how people might look at what you’re making. There’s a sliding scale here, I think: there are some markets where you have a lot of data, and others where, really, you’re just guessing. 

First, at one end of the scale, there are those people who are entering an existing, fairly mature market, with a superior product or price, expecting to take market share. In that case you already know how the market size works – you why and how people use these things. For example, the US market for, say, refrigerators is xm units a year, with ym homes having them and replacing them every z years. Prices are low enough that every home already has one and the product lasts for a decade or more, so you only change them when you move or rework your kitchen. So annual sales in the overall market (for the sake of argument) are outside your control, but you can take share. You can get people to buy yours, but not to buy more than they did before, so the question is how much market share you can take with a better operating model.

Second, at the other end of the scale, there are companies that are creating something entirely new. The personal computer was an example: imagine trying to forecast this in 1980. You know what typewriter sales are, you know how many middle class households there are and you can assume that only corporations and middle-class households will be able to afford one for the next few decades. But you don’t know about the internet as the key driver for consumer PC adoption,  and you don’t know how many office typewriters will become PCs, nor that typing pools will disappear and every executive will write his own emails instead of dictating letters to his PA. 

The same problem applied to mobile phones. You could do a bottom-up analysis that counted business travelers, taxi-drivers, fleet dispatch and so on, and get to maybe 10-15% of the population. Lots of people did that in the 1990s. They were all wrong. For phones, as for PCs, you had to make an imaginative leap into the unknown. You had to say ‘I believe’ that this experience will be transformative, and everyone on earth who has the money will get one. Moore’s Law takes care of ‘having the money’ meaning 4-5bn people, but it’s the imagination that gets you to teenage girls living in text messages. You could predict that phones might get really cheap, but not what that might mean. 

In that light it’s worth comparing these two mobile phone ads from the early days of the industry in the UK. The first, perfectly rationally,  starts from the mentality ‘how many people will need this?’ This is the ’10-15%’ argument. The second, from Orange, assumes that everyone will want one and it’s our job to get it to them, because we’re changing the world. Phones don’t have specific use cases – they’re a universal product. Hence, the CEO at the time, Hans Snook, went around saying that the UK would go to 150% penetration and most people thought he was mad (note that the Cellnet ad was made two years later). 

This is the problem with forecasting sales of the Apple Watch. Annual watch sales are a bit over a billion units, and people buy watches at anything from $5 (China exported over 600m watches last year at an average wholesale price of $3) to $500, $5000 and $50,000. But this doesn’t tell us anything useful. The fact that you buy a $10 watch, or a $1,000 or $10,000 watch, or buy no watch at all, tells me nothing about whether an entirely new product that you also wear on your wrist would be appealing. The fact that you bought a watch x years ago and the average replacement rate for watches is y tells me nothing about whether you’d replace it with an Apple watch, tomorrow, if you saw one. 

That is, there are, in principle, hundreds of millions of people available to be persuaded to buy a smart watch, but we cannot draw any firm conclusions about how many will do so from looking at the existing watch market. That’s like looking at the typewriter market to forecast PCs. It might be more helpful, perhaps, to look at the broader luxury goods market (how many women buy how many $500-$1,000 handbags each year?), or the camera market before smartphones killed it, or the phone case market. One can look at the high-end segment of the phone case as a proxy. One can triangulate one’s guesses. But we’re really just going to have to wait and see. We have no data for how many people will find a place for this in their lives, just as, 20 years ago, we had no data to support the idea that almost everyone would find a place for a mobile phone.

Third, you have companies that sit somewhere in the middle – companies that are entering a market in which the top line dynamics are mostly fixed  but there remains plenty of scope to change things. This is where the iPhone and Android came in. The global mobile phone market has somewhere between 3.5bn and 4bn users, growing steadily as a function of macroeconomics and increasing distribution. Apple and Google didn’t change that – they couldn’t. By reinventing what a phone was, Apple did not change how many people bought a phone, or even (really) how often, but it did change what they paid. It converted $200 phone sales to $500 iPhone sales (only partly helped by operator subsidies), and Android followed at lower prices, such that together they now make up about 70% of unit sales.  As a result, the average selling price of a mobile phone more than doubled from 2007 to 2014, from $80 to around $185. 

Everyone likes to quotes the Wayne Gretzky line that he was skating to where the puck was going to be, not where it was, but Apple and Google didn’t do that – they changed what the game was. In the same way, saying that you’re aiming for x% of a $ybn industry is unambitious – great companies change the y, not the x. It’ll be interesting to see what, if anything, Apple is planning in cars. I’m not entirely sure there is quite the same scope for changing the market size that there was in phones. Watches on the other hand, are wide open.