The user acquisition (UA) battle for casual gaming has become very competitive lately and it is only going to get harder. Mobile advertisers have had the difficult task of acquiring new users in an ever-changing scenario. The rising cost of advertisements and fragmented data in the post-iOS 14 era has had a strong effect on the casual gaming industry.
While all types of gaming apps can benefit from predictive analytics, it can be especially useful for casual gaming apps. When it comes to casual games, there is a very short timeframe to define if a campaign is successful or not. For example, if a hyper-casual game doesn’t reach approximately 35% D1 retention and a $0.50 CPI soon enough, this might be proclaimed unprofitable.
To talk more about how casual gaming can benefit from predictive analytics, we spoke to Adam Smart, Director of Product-gaming at AppsFlyer, a San Francisco-based SaaS mobile marketing analytics and attribution platform.
Why is AppsFlyer a good MMP fit for Casual Gaming apps?
Working with a substantial number of casual gaming studios has helped us develop a deep understanding of their specific challenges. Generally speaking, casual gaming titles use a diverse set of networks for optimal reach. When you add in the use of Self Reporting Networks (SRNs) that attribute their own traffic, it creates a much more complex scenario that is more complicated to measure. AppsFlyer is integrated with the most commonly used networks, so we offer casual gaming apps a clear picture of how campaigns perform, which channels work best, and so on. In addition, we can show the true ROAS (Return on Ad Spend) of your campaigns, including purchase data from in-app purchases your users make and the revenue they generated from ads in your game.
User acquisition fraud can also be a challenge for casual gaming apps, due to the diverse ad networks they use. AppsFlyer has a strong fraud solution that not only stops fraudulent installs from being attributed and paid for but also continues to work post-install by checking for anomalies in user behavior and retroactively marking them as fraud.
How did AppsFlyer adapt to SKAdNetwork?
Following Apple’s announcement of the App Tracking Transparency (ATT) feature, our approach at AppsFlyer was to view these changes as an opportunity to reimagine marketing measurement instead of a limitation. We quickly adapted to Apple’s SKAdNetwork API as a strategic solution for marketers to measure the success of their ad campaigns while maintaining user privacy. Just eight weeks after Apple’s initial announcement, we released the SKAdNetwork Simulation Dashboard, enabling advertisers to understand how their data would be processed via the SKAdNetwork system.
Our SKAdNetwork solutions suite, released ahead of iOS 14.5, was designed to address advertisers’ needs in the post-iOS 14 era — from fine-tuning conversion values with tailor-made revenue recommendations to enabling predictive analytics capabilities that accurately forecast the lifetime value (LTV) of mobile users on iOS SKAdNetwork campaigns. Shortly after, we released our Single Source of Truth capability, which helps advertisers consolidate and deduplicate the multiple data sources of iOS (SKAN, consented users, and more) to get a crystal clear image of their iOS campaign performance.
Most recently, we launched SKAdventure 4.0, an interactive platform allowing advertisers to view industry-specific simulated SKAdNetwork 4.0 data (including two gaming categories: casual and strategy) and compare it with previous versions. This helps advertisers understand the impact of SKAN changes on LTV measurement, campaign breakdown, and web-to-app attribution and adapt accordingly.
How does AppsFlyer anticipate the rise of the privacy era and the coming industry shifts?
AppsFlyer has always prioritized consistent, unbiased, and independent positioning, an approach that instills trust in our platform and enables effective collaboration across the ecosystem. The key to creating better and safer data collaboration lies in providing powerful, aggregated campaign insights based on customers’ first-party data that preserves the user’s inalienable right to privacy.
AppsFlyer has taken an active role in leading the shift to privacy-centricity in the mobile landscape with Privacy Cloud, our open and trusted environment that enables ad networks and advertisers to join forces in privacy-preserving collaborations. The AppsFlyer Privacy Cloud offers access to powerful campaign insights based on user-level data stripped of identifiers, allowing advertisers to analyze aggregated data and gain actionable insights that power precise campaign optimization.
As the first technological innovation within this new framework, our Data Clean Room solution allows advertisers to regain visibility into all of their marketing campaigns by creating a secure environment where they can enrich their own first-party data with AppsFlyer conversion data. By joining the two together, advertisers can deliver tailored user experiences that preserve the end user’s privacy and maintain full control over what happens to their data.
How do you see/imagine the future of UA?
Marketers, especially those in the gaming sector, have to move fast and make data-driven business decisions almost in real time. One of the biggest challenges to this is figuring out how to continue to optimize campaigns and thrive in the age of enhanced privacy, where user-level data is unavailable. To succeed, marketers must implement an effective cross-channel strategy that delivers personalized user experiences that engage and convert. The winners will be those that are able to build precise audiences and establish synergy between owned and paid media to measure the complete user journey — during and after users install the app.
In addition, we’re seeing more and more gaming advertisers integrate predictive analytics logic into their UA calculations to provide insight into long-term results early on in the campaign lifecycle. While not all advertisers have the capability to develop these insights in-house, AppsFlyer’s Predict solution offers the opportunity to harness this capability and make more accurate campaign optimizations than ever before. With Predict, advertisers gain priceless insights into their users’ aggregated Day 30 ROAS, Average Revenue Per User (ARPU), Retention, and percentage of paying users as soon as 24 hours post-install without relying on user identity, which preserves customer privacy.
In many ways, the future of UA is already here. Armed with predictive analytics capabilities, gaming advertisers can be sure they are making smart choices from day one and edge out their competitors.
These were some valuable insights from Adam as to how prediction is key to success in user acquisition in the mobile gaming industry as data privacy takes precedence over everything else. As users get more aware of how their data is being used, prediction is a way to make up for the loss of data.
Want more information on how to grow your gaming app and stay competitive in a dynamic market? Download our 2022 User Acquisition Guide for Gaming Apps here.