October 23, 2015

Learning by Playing

What we learned by playing all the top grossing games.

You need to have a deep feeling for what appeals to your players. Not just a rational explanation, but an emotional understanding. The only way to get that is by putting yourself into their shoes. By playing the games they play.

The way we do this at Tribeflame is that we assign a representative sample of the top grossing games to each person in the company. Everyone then plays and analyses the games they have been assigned.

This practice evolved from an earlier version we had where every week one person in the company presented a top grossing game that they had chosen and played for a few weeks. Their task was to explain to the others on the team why that game had made it to the top grossing charts instead of all the others that do not make it. While this was useful, it led to a very selective sample of games that we analysed.

To get a better picture, we next did a rough categorization of the games on the top grossing charts. I encourage you to do this too, and you will quickly see that the games on the chart fall into categories quite nicely. You have the Supercell style town building games, the King style Match-3 games, the Casino games and a few more categories. You can argue about exactly how to draw the line between your categories, but I think that is less important. For example, are Hay Day and Clash of Clans in the same category? How about bubble shooters, TwoDots and Candy Crush Saga? One, two or three categories?

With broad definitions, the three categories listed above (Town builders, Match3, Casino) will cover the majority of games on the top-100 grossing chart. Some 70% fall into those categories. (This keeps changing, of course, but surprisingly slowly.)

Next, we need to agree a way to analyse the games. There are a bunch of good advice on various blogs that you can use as a starting point. For instance, here and here. Make a list of features that you think the top-100 games will certainly all have in common. Or at least most of them. You can also include some of your own favorite features that make you yourself enjoy a game. Say you like a good storyline in the games that you play. Add that to your list. Not that you will find many such games on the top-100 grossing list, but at least you will learn that what you like yourself is not necessarily what makes for good game revenues.learnbyplaying

After this, you assign 10 games to each person. If your team is small, you get to analyse only e.g. the top 50 games. If it’s large you can analyse top 300, or have several people analyse the same games (that might be useful to see how objective/subjective your criteria of analysis are). Now take a time out of some weeks for playing the games, and then get back to the reporting part.

Once everyone has played their games, it’s time to report the results. Simply list the features you thought they would have in common and have everyone count how many of their games include that feature. For instance, you might be certain that 3D is gaining traction on the app store, or that games should be playable without a network connection. You just ask everyone to count how many of their games were 3D and how many required a network connection to work. For some features, you might want to allow half points. For instance, the example of the story line above is not a clear case of yes or no, but can include in-between levels.

There are some weaknesses to this approach. There is bound to be some subjectivity to your scoring, and you are only analyzing the winners, not the possibly identical games that never made it to the top. Also, the top-100 grossing list only includes games that make their revenue through in-app-purchases. Some games might generate a lot of ad revenue, but they do not show up in the top-100 list. Last, the top-100 list will not tell you how much is spent on advertising each app to keep it there. Some of the apps might stay high on the charts simply because every dollar that they make is immediately put back into advertising to get new users. Which means that a high position on the charts does not guarantee profitability for the game or developer.

Still, despite all these caveats, I would argue that the exercise is very useful. At least for our company, it has enabled a very good common understanding of what we need to think about when developing a game.

Join the conversation! 3 Comments

  1. […] This time, I am going to tell you the two most obvious rules we got from analysing the top grossing games, as described last week. They are the 666 rule, and the 2×1000 rule. If you didn’t already, I suggest you first read about how we analysed the games. […]

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  2. […] very first post I wrote was about test playing and deconstructing […]

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  3. […] very first post I wrote on this blog was about test playing and deconstructing games. It is really, really useful to do, but we never seem to have enough time to do it as much as […]

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