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Comment by somedude895 | Hacker News Reader

> The average monthly payment was $5000 (skewed massively by the top 5%).

I used to work in the direct carrier billing department of a large telco and I'm still amazed by the phenomenon of whales. We'd get 98% of people spending 20 bucks on Spotify and the odd app here and there, and then there were people who would consistently spend 15k+ on Candy Crush (and pay their bills). Not the same level as what you're talking about but I couldn't help but wonder about the millionaire sitting on their couch playing terrible mobile games all day.

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I once worked in an unrelated industry where we had a customer who spent so much money with us, that we shipped them a free iPad out when theirs broke so they could resume spending silly amounts of money.

I read an article a few years back about one such "whale", the guy played Clash of Clans or something similar and claimed to spend something like $500/wk on iAP purchases.

Thing is when they asked him if he felt bad spending all that money on a game he said "oh no, I'm saving money, before I picked up this game I would go out in NYC with my friends and blow a grand every weekend".

I guess it's all relative.

I know more about the online poker industry than I wish I did.

This “whale” phenomenon describes exactly why online poker is so profitable for the site operators.

The profits don’t come from the masses of people cautiously playing on micro stakes tables, but the whales, who will give the poker rooms thousands each month in rake.

Do poker site operators not entice whales by offering rakeback deals and special discounts?

Poker is weird because the largest chunks of all monies go from one player to the other. But I assume rakes, at higher stakes, do add up really quickly...

> But I assume rakes, at higher stakes, do add up really quickly...

I used to deal poker in a past life, here's an anecdote.

We started a low limit game and everyone (10 players) bought in for 60$ - 100$. Over the course of the next hour no one rebought and no new players came in. It was a pretty average game, no one was really 'hot'. After an hour one player noticed that everyone had less money than when the game started (even players that only won hands). He got up and left and I never saw him again.

We took a 5 + 1 rake (1 for jackpot) per hand. 40 hands an hour. 240$ removed from the table in that time span. Basically taking ~3 players money off of the table an hour.

They certainly do. They use loyalty clubs, rakeback deals, reward points (essentially a form of rakebak with lock in), comps, tournaments, and everything else you can think of to keep the whales engaged.

Why you should always report both mean and median!

Even if there is a large skew, the mean and median will be often still be pretty close together. Especially with a large sample size.

That's not how it works... The larger the skew, the farther away they are. If your median goes up significantly because of whales, that means they're not really "whales" as usually understood.

If you have 90 creators earning 5$ / month and 10 creators earning 50k$ / month, they earn 5,4k$ / month on average while the median is 5$ / month. On my books this is not close together.

If it’s somewhat Gaussian or normal sure. But if it’s a different distribution then this isn’t true at all.

What use is median in a Pareto distribution (which this phenomenon falls under)? From what I can tell median is useless, I can't think of a use case, and the internet fails to give me one. Average gives you an expected value to work with. Median though, can be worthless in a pareto distribution where the 90% of the value is in the top 10% of the distribution.

I feel like people have this default reaction to assert that median is as or more important than mean. When, in reality, median is useful for in only specific distributions.

I think people say "median", but what they are really interested are the moments of the distribution. Median just is a key moment in Guassian distributions, other distributions have different important moments, and median isn't necessarily one of them.

Mean and median give you strictly greater information than just mean (or just median).

Given assumptions about the distribution, you may even be able to fit (or at least narrow down) the exact shape based on these two values.

If the median and mean are significantly far from each other than that's an immediate indication that the distributon is skewed, and we also know to what side. If you know the sample size you can also get a degree of skew from this. I challenge you to tell me any other two numbers that can give you that much info by themselves with no knowledge of the underlying distribution.

I interpreted that $5000 "average monthly payment" as what the average performer took home, rather than what the average paying viewer paid.

> people who would consistently spend 15k+ on Candy Crush (and pay their bills).

Sounds like a very successful money laundering operation.

OK, I'm channeling my inner Peter, Michael and Samir here, but how exactly do you launder money by spending it on Candy Crush? Is King supposedly in on the scheme?

How would that even work? I doubt anyone is buying accounts for even a fraction of the amount spent on microtransactions.

It isn't. This is normal in mobile games.

Why tho?

It ain't exactly a dry cleaners

Money laundering is a challenge even in the more tightly regulated industry I worked in. Conversely at one of my previous employers some of our big spenders were publicly known high end rich.

At one of my former jobs, we had a tipping system where we took 15% off the top.

We stored every transaction and user in a graphDB. It was fun seeing normal flows, until you see the money laundering flows show up.

It was above my pay grade to deal with them, so I still don't know how that turned out.

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