How AI Analytics Eliminates Guesswork in Game Development

There’s an art to developing a successful game. But there’s also a science to it. Player behavior is something that developers have notoriously just made a lot of guesswork on.

You know what’s been a huge struggle for me in the past?

1. Interpreting the causes of drop-off points.
2. Understanding the meaning behind certain engagement metrics.
3. Figuring out design issues.

Traditional analytics tools are limited in what they can do with your game’s data. Developers and analysts have been left with the daunting task of making sense of their numbers…manually.

And that’s just a lot of wasted time.

But AI-powered analytics changes all of that…

The Challenges of Analyzing Player Behavior

To hit home how annoying analyzing a game has been for me, let me provide you with an example:

Let’s say you’re trying to determine why players quit a game at level 10. You’ve checked everything – from heatmaps to sifting through event logs with your bare hands.

With the limited help of your analytics platform, you assume that either:

• The boss is too hard…
• Maybe there’s an issue with the game’s economy.

So you go and adjust the difficulty levels in your game. And yet, you still have no idea if these optimizations actually solved anything.

And it doesn’t stop there. Some other issues I’ve faced include:

• Too much data, with dated dashboards that can never tell the full story behind it.
• Blind spots in the player journey and not being able to look far back enough to find the root causes of the problem.
• Iterating for way too long, and testing and validating hypotheses for weeks (sometimes even months).

Thankfully, we now live in a time where these issues are easily fixable.

How AI Fixes All of These Problems (+ Removes Guesswork)

Today, AI-driven visualization and behavioral analytics can automate a lot of these processes.

Imagine that you have someone sitting next to you:

• Constantly monitoring your game
• Keeping track of every single action
• Making lots of hypotheses (and validating them)
• Giving you the final insights (what’s happening and why).

This is how AI can completely change the way game developers understand their player behavior.

And Keewano does just that – without any manual queries or tedious configuration.

Real-World Examples from Keewano

Keewano is an AI Analytics Agent that detects behavioral patterns and presents developers with the clearest, most relevant insights.

Here are some examples of what it can detect.

Retention Issues

While traditional analytics tools present churn rates, Keewano can pinpoint the root causes of why players drop off.

Remember the example we shared about players leaving the game at Level 10?

Well, Keewano provides the following insight: Those players struggled to defeat the boss because they didn’t collect the golden sword to defeat him 10 days earlier (on Level 2).

That’s the level of detail and insight that Keewano’s AI Agent can investigate.

Rage Tapping

Keewano can detect when players are repeatedly tapping a button, indicating frustration. What’s more, is that it automatically segments affected users and recommends how to rectify the problem for each cohort.

Login/Logout Loops

If players are rapidly logging in and out, Keewano will flag it as a potential engagement issue or a bug.

As previously mentioned, traditional analytics might show you where or when players churn. But Keewano explains why. How exactly does it achieve this?

How Keewano Can Eliminate Guesswork with Root Cause Analysis

Keewano’s AI traces behavior patterns back to their origins. Rather than just addressing the symptoms of issues, developers can go right to the source of the problem and fix it.

Again, we can go back to that Level 10 Big Boss fight!

After highlighting the root cause, the AI will then recommend how to fix this problem. In this case, it will be either to improve aspects of onboarding or to make the sword more visible.

By identifying the real causes of problems and presenting the correct solutions, Keewano prevents developers from wasting precious time making the wrong fixes.

Zero-Guesswork Game Analytics Has Arrived

Today, game developers don’t need to spend hours upon hours assuming what’s wrong anymore.

Keewano’s AI analytics agent autonomously raises and validates hypotheses. It pinpoints the true causes of churn. And it provides direct recommendations.

This data-driven, evidence-oriented decision-making is an absolute game changer for developers. It enables them to focus on what matters: Creating the best experiences possible for their players