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How to define a whale?

By on November 29, 2012
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I am toying with the idea of defining the cut-off for whales as below:

“Whales are those users who, together, make up 50% of your revenue.”

That makes it possible to quickly determine what percentage of users sit in that bucket (I tend to see 15-20% as a healthy number) and whether you are either too dependent on whales or are leaving too much money on the table by not making it possible for those who love your game to spend bucketloads of money on things they value.

I’ve asked the GAMESbriefers and you can read their thoughts on Monday, but what do you think?



(The lovely picture of a whale comes from Whit Welles)

About Nicholas Lovell

Nicholas is the founder of Gamesbrief, a blog dedicated to the business of games. It aims to be informative, authoritative and above all helpful to developers grappling with business strategy. He is the author of a growing list of books about making money in the games industry and other digital media, including How to Publish a Game and Design Rules for Free-to-Play Games, and Penguin-published title The Curve:
  • Jean-Christophe Rodrigue

    50% feels a bit arbitrary. At that cutoff there is a risk of increased heterogeneity in the group. One thing you can do is build a pareto chart and bucket your users by monthly revenue using a quantile function like cut2 in R. Then try different number of quantiles to get a representation that is a good tradeoff between ease of understanding while still having some sort of homogeneity in the buckets.

  • Jim

    How would that work for non-static product catalogues, or economies built around consumables (e.g. energy, coins, tokens, gacha, etc.)?

  • As a very high-level benchmark, 50% of revenue is pretty good. One way to proxy bottom-up while still using broad revenue numbers could be to define a whale as someone who has spent at least 1% of the total product catalogue (ie if the total product catalogue is €5k then a user who has spent 50€ is a whale)

  • I’m sure you are right, Eric, but most of my clients are in the early days of getting to grips with data driven design. I’m looking for a simple rule of thumb to get them started. If 50% of revenue is not the rule of thumb, could you suggest any others?

  • I agree that people who are not whales in a monetary sense are very important. I regularly tell people to “love their freeloaders” as a a reminder that free plays add lots of value.

  • In my opinion, a top-down approach doesn’t work for “whale spotting” — whales are primarily defined by behavior (revenue spent is the artifact left behind by that behavior), and I feel that grouping them as the “50% (or whatever arbitrary number) of revenue” group doesn’t actually add anything to the organization’s understanding of its players but another graph on the dashboard. If you know, bottom up, who whales are because you’ve identified the behaviors that most whales tend to exhibit, then you can actually use that information to inform the evolution of your game.

  • Funny- I just tweeted that I yelled “I’m a whale” in the Chartboost offices. This is why I know I’m a whale: a. I used to be a console gamer and buy platforms, devices and games so I’m accustomed to spending money on games/entertainment. b. I’ve been a “whale” on social Facebook games and spent over ~$40 on virtual goods. c. I play mobile games relentlessly and because I’m busy with my day to day, I feel that it’s worth paying a few dollars here and there. d. I share my favorite games with friends on twitter, facebook, face-to-face, etc.

  • Keep in mind that there are whales outside of monetization. You also need viral whales if your game is going to succeed and I would add community whales.