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Apple’s iOS 14.5, available as of April 26, gives users the option to block IDs for advertisers (IDFAs) at the app level. This update threw a monkey wrench at data-driven marketing as we know it and sent a shockwave across the gaming industry. Gaming marketers — who are already juggling paid acquisitions with different goals (e.g., installation, in-app purchases, value optimization) on various ad networks — are now grappling with the implications.
Although Apple users only account for 22% of the global gaming ecosystem, they represent a large portion of revenue. The iOS 14.5 update has changed the rule of the user acquisition and attribution game. It has created a new reality that requires gaming marketers to readjust their measurement and optimization strategies.
To thrive in the brave new world of iOS 14.5, you need to understand the key changes, how they impact game marketing, and what you can do about them:
iPhone users can now choose whether to enable IDFA tracking, which allows advertisers to collect and analyze their individual-level data. Forecasts show that only 10–40% of gamers are expected to opt-in. Here’s what this means for gaming marketers:
Shift your focus from user actions to user lifetime value (LTV) and strike a balance between the quality and quantity of the available data, so you can optimize on the right signals to support lookalikes and retargeting campaigns.
If you have several games on the market, double down on cross-promotion between the games. Cross-promotion allows for attribution based on IDFV (Identifier for Vendors) since there isn’t any data-sharing with third parties. You can also consolidate your ads to run fewer campaigns with broader targeting to find the sweet spot between specificity and reach.
There are some key areas you can focus on to achieve a consolidated campaign structure:
Gaming marketers have to work with a 6-bit limit (maximum of 8 conversion events in the standard schema, or 63 events in the custom schema). No reporting will be available for any event not mapped in the schema, and within the schema, only the highest priority for each user will be measured. It’s therefore critical to choose the right 6-bit event mapping/schema that balances your conversion window and events, strategically, to collect the most meaningful data. This should be determined by your game economy and funnel.
Since in the gaming industry user value can vary from a few dollars to hundreds or thousands of dollars, it’s more important than ever to measure user value to inform optimization and evaluate campaign performance. Relying on one of a few funnel events that happen within the first few days of a download will not yield accurate (enough) growth predictors. Instead, observe a user’s interaction over time, preferably for as long as the business case allows you to, before making a determination on the user value.
However, just stretching out your timeframe won’t solve all the problems. While a more extended time window allows you to collect more representative data, it lacks the speed-to-insights for time-sensitive optimization. Moreover, if only one event is registered, how would you determine which signal to send so you can represent both past and future activities?
Predictive modeling can overcome these obstacles by using a single signal to embody a user’s LTV based on a complete set of actions and behaviors, in addition to campaign performance. This allows you to send predictive signals for users who are most likely to make high-value purchases. For example, Voyantis’ analytics solution supports gaming marketers so they can optimize and measure campaigns with predictive signals derived from user LTV.
Whether or not a user is opted-in, all attribution data will be cut down to 7 days in iOS14.5. This means you have a lot less time to extract quality conversion and attribution data for measuring costs, revenue, and return on ad spend (ROAS.) If you have been using longer conversion windows, you need to change how you measure cost per conversion.
The Ad Manager will show a higher cost than you’re used to when you measure the 7-day ROAS. Furthermore, ad networks recommend (and may even enforce) cutting this window down to 1–3 days to account for the additional 48–72 hour delay between the time an event occurs and when it’s available to the network.
As reporting and attribution capabilities from third-party platforms decrease, gaming marketers need to rely more on internal data and modeling. Predictive modeling will become the only way for companies to understand long-term engagement and LTV. As such, game marketers need to build models that send the right signals to the ad networks.
If you haven’t been using server-side conversions already, it’s time to build or buy, the technological capabilities and marketing know-how to support sending signals for user LTV. Such server-side capabilities will allow you to send more complex signals to ad platforms, so you aren’t dependent on a single event. Facebook, Google, and Snapchat already support server-side conversions while Ironsource has it in beta. We expect that other networks will follow suit.
The changes to IDFA introduced in iOS 14.5 are yet another illustration that brands need to build or buy their own predictive model, instead of relying on third-party platforms, to understand and optimize user LTV.
However, developing the marketing technology with AI capabilities in-house to support user acquisition optimization is cost-prohibitive for all but the most prominent players in the industry. That’s why we’re so excited that Voyantis is making signal optimization technology available for all gaming marketers through our AI-powered LTV predictive platform, which helps you scale up quickly by understanding the true value of your users.