The “Beat Goliath” Playbook for Indie Game Developers
Electronic Arts has 18 data analytics job openings. Zynga has 40 openings for the same thing, and Nintendo has 23. Each of these organizations, and every large game publisher, runs a sophisticated operation of data scientists and analytics experts who use game data to understand their market, maximize monetization opportunities, and plan their game development roadmap.
On the surface it might seem that without a multimillion dollar budget, everyone else is going to be at a disadvantage. Indie game developers are focused just on building and marketing their games, and are doing so with small teams who are already overworked and tired of looking at those damned Post-Its on the wall. One would think it’s simply not possible for the indies to keep pace when it comes to analytics.
This leads to the spiraling thinking that drove my mother to determine that the “C” on my 10th grade chemistry midterm would prevent me from getting into a good school, which would help me get into a great medical school, which would then lead me to a successful, happy life as a surgeon. Well, I didn’t want to be a surgeon, and that “C” didn’t keep me from arriving at a happy, successful outcome. Anyway, that thinking is responsible for an attitude that serves to reinforce the status quo — in other words, the big players have money which gives them the resources to derive insights from data that will always give them market advantages and continue to edge out indies.
This kind of thinking is imprinted on our brains and unfortunately it is perceived as a foregone conclusion — the big guys stay big, the indies will always have to struggle.
Let me dispel you of any notions about big vs. indie, and let me also explain that every time you read a headline about technology democratization, they are talking to you, indie game developer.
Yes, EA has the budget for an analytics team and every analytics tool on the planet. But consider two things that every analytics team does, whether it has 100 people, or someone who investigates user data as part of her dozen other responsibilities:
- Identify a source: where are you getting data? Well, keep in mind that the only real data you have access to, and the data which is most important to you, is coming directly from your own games. So the question is, do you have access to that data? An army of data scientists won’t do you much good if there isn’t a source which you can use.
- Understand the data: the second most important thing that any organization needs, if they want to benefit from data, is to have a way to interpret and make sense of all the information available to them. Much of what analytics teams do is create interfaces from disparate sources so there can be a coherent format for looking at data.
- Make decisions based on the data: armed with data, these teams now have to make recommendations for what to do to improve performance, whether that’s in the form of less churn, more playtime, or an increase in monetization opportunities. Then they begin the work of building these recommendations into improving exiting games and creating new ones based on this data.
In typical corporate fashion, Parkinson’s Law dictates the processes and operational activity to perform all the tasks built in to the items listed above. For a company with 12,000 employees, 6 high profile game franchises, and investors who expect growth every quarter, the job of analytics involves both being overly cautious with covering their asses. If the data told you X, and you did X, then it’s not your fault if no one ended up buying your game.
But the reality is that identifying a source, making sense of data, and then using that data to improve games doesn’t need to be complicated. It doesn’t require meetings, PowerPoints, and scores of highly paid data scientists. The line from understanding data to implementing that data can be fast and deliberate, and it’s precisely what indie developers should have access to.
Let’s think more about the three things that are needed to use analytics correctly. But now, let’s put them into the context of an indie game developer who is strapped for time and cannot rely on highly paid data scientists. Here’s what they need and this is how easy it should be for them to get it:
- Source: indie developers need a solution that does not require setting up, configuring, and managing a server. The concept of a back-end should not even enter their brains, and instead, they should rely on a service that tracks and analyzes their games based on standard player and game performance metrics. What’s more, they should be able to easily connect their games to a service through a simple API and/or plugins for main game engines. Additionally, they need to be able to define custom data points they need and incorporate those into their analytics service.
- Understand the data: some data points will register with you immediately — if DAU or MAU is dropping, you’ll want to investigate further, and you should use additional data to go to the next level. Other data points immediately shine a light on important aspects of your game. For example, if features X, Y, and Z see the most playtime, or if those are the places in the game where players invoke social functionality to invite others to play, it’s clearly a sign of popularity. If 75% of players drop off after using feature A, well maybe it’s a lousy feature, or perhaps there’s some aspect of how it renders in the game that players don’t like. These do not require Tableau charts or algorithms to interpret. If you know your game and understand the gamer mindset, your ability to see data in an easy-to-digest dashboard or heatmap will arm you with insights, and those insights give you power to make improvements.
- Make decisions based on the data: if you’ve learned that 90% of your players choose to perform their secret ops and capture the royal family in urban settings vs. rural settings, how many meetings and spreadsheets does it take to decide to offer more opportunities to function in urban settings? Again, when you know your game and the mindset of players, data like this enables you to adapt existing games rapidly and plan for future games with a greater accuracy of meeting player desires.
In every way, the functions of big studio analytics teams is no different from what can be done by smaller, indie game developers. The main difference is approach. For any team, what they need should be able to be set up without the need for any specific expertise or additional tools. Integrations need to be simple. Backend infrastructure should be removed from the equation. And this is available to any organizations, but it’s the indies who are taking advantage of it the most, and realizing the biggest rewards from doing so.
This is the promise of technology democratization — you should be able to set up a solution to meet your goals within a matter of minutes, and it should begin feeding you usable data immediately. Then, your job is less about managing technology and more about using that technology to help you make better decisions about the thing you do well — build great games.
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