What do you do if your game marketing and user acquisition strategies lack logical reasoning?

When shaping game marketing strategies, I always focus on the end goal, whether it's scaling up, maintaining a steady user base, or hitting specific revenue targets. Understanding the balance between scaling and profitability is crucial. For example, aiming for a broader audience requires optimizing ad spend, which significantly increases install volume but generally nets lower roas. Targeting ROAS directly usually goes hand in hand with lower scale but more profitable cohorts.

Conduct an evaluation of your current marketing and user acquisition strategies. Identify specific tactics, channels, and messaging used to promote your game and attract users. Determine which aspects lack logical reasoning or fail to generate desired results.

Analyzing high-level metrics like Retention, ROAS, CPI, and ARPDAU is your bread and butter in crafting a balanced strategy. In my experience, ensuring a high ARPDAU is only second to sustaining high retention levels. For example, I've been in situations where ARPDAU initiative resulted in lower retention rates. By analyzing user behavior data, we adjusted our in-game offerings and decreased offer rates to increase the perceived value, which in turn boosted ARPDAU and improved retention. This balance is essential for a profitable and engaging gaming experience.

Experimenting with different creatives is a strategy I've employed with success. It allows you to test new features or directions for your game indirectly, proxying player interest through their engagement with various ad creatives. This approach has a twofold benefit: first, it identifies what resonates with your audience, informing your messaging and product development. Second, when a particular creative shows promising results in the initial funnel, it provides a data-backed motivation to integrate those tested elements into the game.

Leveraging econometric models has been instrumental in my strategy to breakdown performance nuances between Android and iOS platforms. Since granular demographic data is often missing, I prioritize a balanced approach across various campaign types. By allocating resources to incentivized campaigns, we can boost user engagement at a low cost. Simultaneously, focusing on the CPI and ROAS campaign mix helps in optimizing ad spend for direct user acquisition. Investing in search ads targets users with high intent, capturing an audience actively seeking what we offer. Daily alert for decreasing Network performance also helps.

A/B testing, especially with eCPM changes, low and high bids, is a vital part of optimizing the marketing approach. In my practice, the real value emerges from continuously testing new networks, not just sticking to conventional ones. By experimenting with various aspects of network campaigns, we can figure out insights that would otherwise remain hidden. For instance, tweaking the network spend mix can significantly impact our campaign's performance, revealing optimal allocation that maximizes ROI. ML can be handy too but generally it falls down to a heuristic approach at the low level of spend (<100 mln.)

Consider seeking guidance from industry experts, consultants, or marketing professionals with experience in the gaming industry. Leverage their industry insights to prioritize tactics that align with your objectives.