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Why does the author assume normal distribution (bell curve) for apps' revenues? In reality app sales are similar to those of books and follow power law distribu

by 1gor 16y ago

Why does the author assume normal distribution (bell curve) for apps' revenues? In reality app sales are similar to those of books and follow power law distribution. A few bestsellers will account for large chunk of overall app sales. Then there will be a very long tail of unprofitable apps. Therefore all of his numbers and his final conclusion are wrong. People do not write iPhone apps in order to achieve some sort of 'average' income. They hope to strike it lucky and get a disproportionately large payoff.

alttab 16y ago
Where are you getting the normal distribution information from? "This is the average, remember, it is not the median. The average skews too high because of the long tail. There are a few who make several millions, who distort the average number, so it is not true that half of iPhone App Developers earn more, and half less, than $3,050 per year." He references the long tail you mention, and describe exactly what you mean about some people making a lot, but because of distribution and how users find and download apps - its more akin to say - the lottery - than actual market strategy. Some will make money. Most of them will be development/contractor shops that charge out-the-ass for mobile apps to companies who want a "mobile presence." These medium to large companies won't realize that the money they are losing isn't worth it until its happened a couple of times. Then they'll stop coming back. That said, independent developers making money on that app store directly is a complete crap-shoot. Very few get rich, lucky ones make a very modest living, more get a hobbyist return, most get dick - and some don't even get the money they did earn from Apple. Therefore all of your rebuttal and final conclusion are wrong. How many books have you written on the subject? Note: The reason he uses a normal distribution is because it would actually help DISPROVE his thesis, a normal distribution would make it easier for an app developer to make money, not harder. When the normal distribution showed a shitty return - he reminded us it was actually worse.
- NyxWulf 16y ago
  Unfortunately that's not necessarily true. A normal distribution is just vastly different than an exponential distribution. Using the central limit theorem allows you to expect the mean to be normally distributed around your samples, but that's about all. The reality is that taking an average over an exponential distribution is largely meaningless. There are an infinite number of distributions that would create that exact mean. Some of them not at all profitable for certain apps, others very profitable. The problem with using an average over this distribution is that it doesn't give you anything to work from. You can't figure out who is profitable and who isn't, or how high up the curve you need to be to be profitable. Taking an average over all of the apps in the app store is like taking the average revenue of every website that tries to make money on the internet. It's a meaningless number. At the end he compares the low numbers in averages to a single anecdotal example of something that had a 100 Million downloads. On the one hand he dismisses the few highly successful appstore apps but then uses another singular example of a highly successful app to recommend a different platform. Overall the methodological approach is deeply flawed. I could go on, but ultimately, I found this analysis not very insightful. As with any new channel, it takes some time to figure out what works and what doesn't. Who is going to buy and who isn't. In almost all software the distribution is exponential where the top 10 to 20% make over 90% of the revenue. The same is true of the app store. It all comes back to fundamentals. Find an unmet or under-served need in the market, figure out how big that market is, figure out how much it's going to cost to fill that need, make sure your app fills the need, and start trying to sell it. Then once you've built up a sales platform, then you start scaling it.
- 1gor 16y ago
  > Where are you getting the normal distribution information from? The author spends much effort estimating an 'average' app income and costs. Talking about averages does not make any sense in case of power law distribution. He is using Gaussian approach which is a wrong model for given phenomena. Bringing skewness/kurtosis/whatever to the table doesn't help a thing since he has completely mis-classified the problem. > That said, independent developers making money on that app store directly is a complete crap-shoot. Can the same can be said about entrepreneurs in general? What is an 'average' income of an entrepreneur (including failed ones)? Is it worth it? Do you aim for this dismal income when you start a business? Scalable business model is completely different animal from a non-scalable one (i.e. selling your personal time as a developer, consultant etc.). Quite a few developers expect from iPhone apps the same they are used to in their contracting/salaried careers.
powrtoch 16y ago
People play the lottery for the same reason. The point (don't waste your time) still stands.
pvg 16y ago
Why does the author assume normal distribution (bell curve) for apps' revenues? He doesn't. He tries to estimate the median precisely because he doesn't actually know the distribution although in several places he specifically mentions that it's likely not 'normal'. He's going for the median because it's more informative than the average, given the uncertainty about the distribution. It's a little moot, anyway, since the average figures are pretty lousy and given the most likely distribution, the median just makes it worse.

by 1gor 16y ago

alttab 16y ago

Where are you getting the normal distribution information from? "This is the average, remember, it is not the median. The average skews too high because of the long tail. There are a few who make several millions, who distort the average number, so it is not true that half of iPhone App Developers earn more, and half less, than $3,050 per year." He references the long tail you mention, and describe exactly what you mean about some people making a lot, but because of distribution and how users find and download apps - its more akin to say - the lottery - than actual market strategy. Some will make money. Most of them will be development/contractor shops that charge out-the-ass for mobile apps to companies who want a "mobile presence." These medium to large companies won't realize that the money they are losing isn't worth it until its happened a couple of times. Then they'll stop coming back. That said, independent developers making money on that app store directly is a complete crap-shoot. Very few get rich, lucky ones make a very modest living, more get a hobbyist return, most get dick - and some don't even get the money they did earn from Apple. Therefore all of your rebuttal and final conclusion are wrong. How many books have you written on the subject? Note: The reason he uses a normal distribution is because it would actually help DISPROVE his thesis, a normal distribution would make it easier for an app developer to make money, not harder. When the normal distribution showed a shitty return - he reminded us it was actually worse.

NyxWulf 16y ago
Unfortunately that's not necessarily true. A normal distribution is just vastly different than an exponential distribution. Using the central limit theorem allows you to expect the mean to be normally distributed around your samples, but that's about all. The reality is that taking an average over an exponential distribution is largely meaningless. There are an infinite number of distributions that would create that exact mean. Some of them not at all profitable for certain apps, others very profitable. The problem with using an average over this distribution is that it doesn't give you anything to work from. You can't figure out who is profitable and who isn't, or how high up the curve you need to be to be profitable. Taking an average over all of the apps in the app store is like taking the average revenue of every website that tries to make money on the internet. It's a meaningless number. At the end he compares the low numbers in averages to a single anecdotal example of something that had a 100 Million downloads. On the one hand he dismisses the few highly successful appstore apps but then uses another singular example of a highly successful app to recommend a different platform. Overall the methodological approach is deeply flawed. I could go on, but ultimately, I found this analysis not very insightful. As with any new channel, it takes some time to figure out what works and what doesn't. Who is going to buy and who isn't. In almost all software the distribution is exponential where the top 10 to 20% make over 90% of the revenue. The same is true of the app store. It all comes back to fundamentals. Find an unmet or under-served need in the market, figure out how big that market is, figure out how much it's going to cost to fill that need, make sure your app fills the need, and start trying to sell it. Then once you've built up a sales platform, then you start scaling it.
1gor 16y ago
> Where are you getting the normal distribution information from? The author spends much effort estimating an 'average' app income and costs. Talking about averages does not make any sense in case of power law distribution. He is using Gaussian approach which is a wrong model for given phenomena. Bringing skewness/kurtosis/whatever to the table doesn't help a thing since he has completely mis-classified the problem. > That said, independent developers making money on that app store directly is a complete crap-shoot. Can the same can be said about entrepreneurs in general? What is an 'average' income of an entrepreneur (including failed ones)? Is it worth it? Do you aim for this dismal income when you start a business? Scalable business model is completely different animal from a non-scalable one (i.e. selling your personal time as a developer, consultant etc.). Quite a few developers expect from iPhone apps the same they are used to in their contracting/salaried careers.

powrtoch 16y ago

People play the lottery for the same reason. The point (don't waste your time) still stands.

pvg 16y ago

Why does the author assume normal distribution (bell curve) for apps' revenues? He doesn't. He tries to estimate the median precisely because he doesn't actually know the distribution although in several places he specifically mentions that it's likely not 'normal'. He's going for the median because it's more informative than the average, given the uncertainty about the distribution. It's a little moot, anyway, since the average figures are pretty lousy and given the most likely distribution, the median just makes it worse.