In a world where the likes of Google and Meta are encouraging the adoption of broad targeting campaigns like UAC and Advantage Plus, it can be tempting to assume that mobile user acquisition (UA) performance is governed almost exclusively by creative.
Creative is unquestionably important, but why is it that advertisers with amazing creative don’t always see the results they want? The answer is often how they’re able to leverage one of their most valuable assets – their first-party data.
First-party data is always front of mind (especially for anyone who has had to do compliance training), but depending on where you sit in a business, it can take different forms. We set out where first-party data is of greatest value in your app user acquisition strategy, highlighting how more advanced advertisers are unlocking incremental value from their data by thinking about their approach more expansively.
Direct optimisation
Once upon a time in the mobile space, advertisers would simply optimise towards install, with cost per install (CPI) being the performance Northstar. With the adoption of mobile measurement platforms (MMPs) and the advancement of UA platforms, optimisation against events beyond install has become the new normal, with target CPAs and return on advertising spend (ROAS) a common currency when it comes to KPIs measured by app marketers.
While almost every advertiser is adopting this approach, the most sophisticated mobile advertisers have taken this methodology even further by asking more expansive questions from their first-party data. This means moving beyond a single fixed conversion event, like registration, and optimising towards the behaviours that signal genuine engagement within a defined period after install, such as registering within the first 48 hours and opening the app at least four times over the same period.
Understanding user behaviour ultimately leads to a better understanding of user quality and reframes conversations around which data is important when defining a mobile user acquisition strategy.
Once user behaviours are identified, they can be configured as MMP postbacks (automated server-to-server messages that send app event data from an MMP to an ad network or advertiser) and used to optimise directly, fine-tuning how campaigns are run to acquire the best quality of installers.
This process may sound daunting, however with the right hypotheses to explore, evolving your postback schema can unlock tangible wins.
Audience signals and lookalike targeting
All mobile paid user acquisition channels make great play of the sophistication of their UA algorithms. Strip away the noise, and they are ultimately predicting the likelihood of a prospect installing an app when an impression is served, or subsequently completing a secondary action such as registration, trial start or purchase.
If you’re optimising towards ROAS, the prediction becomes more complex: the algorithm needs to assess the likelihood of a prospect installing, subsequently making a purchase, and the potential value of that purchase. The more signals you can provide to inform these predictions, the better the algorithm can optimise.
A common assumption is that efficient algorithmic optimisation requires either a massive app user base – daily active users (DAU), MAU, and the usual acronyms – or significant budgets. This isn’t necessarily the case.
Audience signals and lookalike targeting, derived from first-party data, are great ways to point user acquisition campaigns towards the best pockets of prospects as early as possible. Many advertisers will create audience signals and lookalike audiences from MMP purchase events and while this is undoubtedly effective, it can leave other sources of value overlooked.
More advanced advertisers look beyond leveraging only their MMP postbacks for this type of modelling, instead connecting their customer data platforms (CDP), or data management platforms (DMPs) to build more expansive audiences, often looking at longer term value, beyond what might typically be shared through a postback.
Perhaps a more valuable lookalike seed audience would be users who have made multiple purchases, or customers who have demonstrated the greatest sustained value over an extended period.
By sharing audiences with a CDP/DMP, advertisers are no longer limited by their postback schema. This enables more sophisticated segmentation and modelling, including identifying the motivations that might drive prospects to consider a specific app and using these insights to inform more tailored messaging. It can also complement persona work developed by insights teams.
Advanced data analytics
First-party data’s value goes well beyond the direct connections that exist between an ad platform, an MMP and a CDP/DMP. First-party data can shine a light on a whole range of advanced insights that can give your user acquisition campaigns an additional edge.
A great example of this, and particularly relevant in the gaming space, is the relationship between a device-make and model, and longer-term installer value. Once understood, this can be incorporated into campaign structure and setup, moving away from a ‘one-size-fits-all’ approach to bidding, to a more tiered approach, with bids reflecting predicted value. This is a fantastic way to get the most from ad network, programmatic and preload campaigns.
We’ve touched upon how the time between install and events is often a barometer of install quality. More sophisticated advertisers don’t look at events in isolation; they consider context too. Once these types of insights are unpacked, it opens the door to a more sophisticated postback setup, with event attribution windows tailored to reflecting cohort value (e.g. event A within 72 hours of install).
Additionally, where data confidence allows, advertisers are using their first-party data to better understand more nuanced value of new installers, including by operating system (OS), channel and region. As performance is assessed at varying levels of granularity, it becomes possible to develop bespoke KPIs by channel, OS and other relevant variables, enabling more precise optimisation and ultimately driving stronger performance.
Every advertiser is at a different stage of their first-party data journey, and it’s important to remember that there is no one-size-fits-all, or ‘right’ approach. However, thinking more expansively about how first-party data can answer strategically important questions will only ever enhance a mobile user acquisition strategy.
Yodel Mobile have unparalleled experience helping advertisers unlock value from their data. To discover more, or to chat to our team about your approach to user acquisition, get in touch.
