M8 Games is a self-publishing mobile gaming studio formed by merging two earlier studios at the start of last year. In their first year they soft launched two games, and are now scaling a third. The team runs on transparency: every employee sees the numbers, the UA spend, and what is happening across the games. We spoke with Tunç Şardan, Co-Founder, about why Bruin has become the single tool the team reaches for most.

Challenges Faced Before Bruin

For an idle game, the volume of in-game events is enormous. A single mechanic, harvesting a fruit, can fire hundreds of thousands of events per user, and at 100,000 daily active users the traditional game analytics tools simply cap out. Beyond the caps, the deeper problem was the quality of what came back. Firebase and analytics platforms only ever returned bulk, unrefined data, which forced the team to make assumptions about why players were behaving the way they were.

That guesswork was expensive. Up to this point the team had run dozens of A/B tests on their scaling game, only a couple of which moved the needle. Each test takes a minimum of a week, and longer tests run two to three weeks, so a wrong assumption did not just cost a decision, it cost months.

The stakes became clear when one of their casual games failed. By the early numbers the game looked like a winner, and the tools they had projected it would do well. But those tools only showed the first few weeks, and the team had no data of their own to see further. Over the following months the game quietly lost users and slipped into the negative. They had to shut it down, and it cost them.

Decision Points for Choosing Bruin

When the team first saw Bruin, the reaction was immediate. Within the first ten minutes of the explanation, they understood that this was a different category of tool. But understanding is exactly the point Tunç keeps returning to: the value is hard to grasp from a description alone, and only becomes obvious once you get deep into your own data.

“The first ten minutes of them explaining it, we said this is the next big thing. The only reason someone wouldn't buy a tool like this is because they don't understand it yet.“

There was real skepticism first. The proposition sounded almost too good, and the team assumed an AI-driven analyst would simply hallucinate its way to wrong answers. What removed the doubt was a free first month in which the Bruin team worked hands-on to teach the system the game. During that month M8 ran their own internal audits, checking Bruin's conclusions against A/B tests they could verify. As the system learned the game, its answers sharpened, until it understood the game close to as well as the founders did.

The efficiency case sealed it. Building this kind of analytics capability in-house means standing up an entire data function (pipelines, infrastructure, and the ongoing upkeep behind them), months of work before the first useful answer. Bruin gave a small team that foundation from day one, letting them compete with studios many times their size.

“Could I build a team this good for what Bruin costs? No. It allows a small company like ours to build a strong foundation for data analysis for much more feasible numbers.“

Impact of Bruin

Bruin's biggest contribution has been removing the noise. Where Firebase gave bulk numbers and left the team to guess, Bruin narrows a churn problem down to two or three plausible causes, which the founders can then reason through, argue about, and turn into a targeted test rather than a blind one. That shift is expected to cut the number of A/B tests they run by roughly a third.

The clearest example came from their flagship idle game, which starts at 45+% day-1 retention and settles at 10+% by day seven. Digging into the retention decay, Bruin pointed to a mid-game progression wall as the cause of churn.

“Taking it at face value, I would have reworked that wall and probably lost money. When I asked Bruin to cross-reference against monetization points, it showed the players churning there were actually heavy monetizers. That changed what we fixed.“

The team also tied Bruin into their Firebase A/B tests to produce daily reports that go far beyond what Firebase surfaces on its own. A Firebase "IAP purchase successful" event only tells you how many people fired it. It says nothing about purchase revenue or how those players behave afterward. With Bruin, that behavioral layer is now part of the daily review, alongside ROAS predictors and financial dashboards the team uses to forecast where a cohort will land by day 30.

That depth changes conversations with partners, too. Working with an ad monetization team, M8 could go past simple purchase events and speak to the exact behavioral cohorts that drive returns.

“We can tell an ad partner that a player who watches five sprinkler-upgrade ads and upgrades the office produces higher ROAS. They ask how we possibly know that, and we say: because we use Bruin.“

Tangible Benefits

• A data foundation for the current game and every future game, so a small team can compete with far larger studios, without standing up a full data function of its own.
• Fewer wasted experiments: roughly a third fewer A/B tests, saving weeks per avoided test.
• A daily behavioral layer on top of Firebase A/B tests, plus ROAS prediction and financial dashboards, answering questions in minutes instead of a week of analyst queries.
• Cross-referenced churn analysis that separates players who leave from players who leave after monetizing, so fixes target the right problem.

Conclusion

For a lean self-publishing studio, Bruin has become the tool the team uses most, second only to checking live numbers. It is not magic, and Tunç is candid that it can still make mistakes and requires someone who knows the game to steer it. But used well, it gives a small team the data infrastructure and analytical depth that would otherwise take years and a dedicated team to build.

“Without Bruin I'd probably cry for a week and then figure out what we'd do. It lets us set up a real data foundation for this game and every future one, in less time with fewer up front costs. That's a huge luxury.“