ATT hasn’t shut down in-app ads, but it will still require big changes
Considering that it didn’t bring much additional control for mobile users, Apple’s App Tracking Transparency (ATT) feature packed a surprisingly big punch to in-app advertising
Understandably, the 75% opt-out rate this leaves is concerning for advertisers reliant on user-level data to power relevant and impactful experiences. But there are plenty of opportunities for significant reach and engagement. Not only has global app usage climbed to record levels in the past year — hitting 230 million downloads and average daily time spent of almost five hours — but users are also open to in-app ads. In fact, our own research has found audiences are three times more likely to accept ads in return for free content than pay for apps.
Far from capping ad potential, more stringent protections could help fuel better customer connections, if advertisers fulfill their end of the deal. As well as exploring different data sources, there is a need for stronger focus on identifying and delivering what users want.
Providing better value for data
Consumer willingness to accept ads is a positive sign that the value exchange remains alive and well. With our research highlighting only around 7% of users across the UK, US, Germany and Japan would prefer to pay for ad-free apps, this is encouragingly high receptivity and an opportunity for advertisers to build on the benefits ads bring for ensuring broad accessibility.
At the same time, however, privacy sensitivity is growing. As recognition of in-app tracking increases, so does scrutiny of whether it works for audiences. Almost six in ten (58%) UK users view the application of in-app tracking to fuel ads as unfair, followed by 50% in the US and 48% in Germany. This finding underscores that while audiences aren’t necessarily opposed to ads, they also don’t feel that advertisers’ efforts to reach them via mobile devices currently provide a good deal in return for their personal data.
Determining how to meet these expectations is challenging. With regulations and restrictions stripping away ever more layers of insight it’s getting harder to apply the standard approach of enhancing ad resonance — and justifying data use — through refined personalization. To reinforce relationships, advertisers must focus on delivering experiences that match up with audience preferences and making better use of innovations in privacy-first targeting.
Getting back to creative basics
The fundamentals of good mobile advertising should never be underestimated. Amid the mass shift to user-based targeting by default, the industry has often overlooked the value of tailoring ads for their environment and seeking direct input from users. Our past surveys, for instance, have revealed that aside from relatively obvious basics — such as truly engaging messages — mobile users tend to be hooked by ads that tie in with their context.
Specifically, 20% of users were more likely to pay attention to ads using interactive elements. Given the nature of mobile use, this makes sense: users who have actively chosen to fire up specific apps will be more inclined towards ads designed to feel like part of the experience. This might also explain why wider studies have concluded that interactive ads are among the most effective mobile formats, second only to similarly immersive playable ads.
While not the only key ingredient for successful in-app campaigns, catering to the appetite for active participation is a solid starting point for re-establishing confidence and boosting ad value. From this baseline, advertisers can home in on giving ads the personal touch using smarter methods of harnessing available data and the latest breed of probabilistic tools.
Enlisting intelligent assistance
From here on, ensuring maximum ad relevance is going to be about wielding accessible data effectively. On the publisher side, ATT hasn’t entirely cut off app insight. Apple’s SKAdNetwork still shares ‘post-backs’ containing the campaign ID and details about conversion value in the first 24 hours of a download. This means publishers can link particular acquisition campaigns to revenue generated within apps, initial retention rates, and predicted lifetime value (LTV).
Combined with advanced modelling, such insight can help enable not just relatively precise attribution, but also optimization. For example, artificially intelligent (AI) models can analyse huge volumes of past and incoming data to trace the connections between specific campaigns and desired outcomes. Fed into systems driven by AI subsets such as reinforced learning (RL), this insight can then be used by sophisticated algorithms to define which types of ads are likely to spark actions associated with strong conversion and satisfaction in certain apps — be that a high level of play or estimated LTV — and serve messages accordingly.
Covering anonymized in-app events, ad network reporting, and deterministic insight about opted in users, available datasets for advertisers are much more limited. There is, however, scope to build up from and activate this data with AI modelling. For instance, inputting known traits and engagement from consenting users, along with anonymized data, can create deeper understanding of tastes and habits for unique app audiences. As well as informing targeted ads, this data can be inputted into RL systems to allow a similar kind of automated decision-making; with ads chosen for their probability of eliciting desired responses and giving users what they want.
The impact of ATT will undoubtedly cast a long shadow on in-app ads, but it doesn’t have to shut down in-app ads. By broadening their insight horizons and looking beyond user-based data alone, advertisers can find new creative ways of regaining user trust and ensuring ads offer better value. To unlock the positive possibilities of tougher privacy provisions, they’ll need to pay more attention to what users themselves feel ads should provide and get to work on making the most of the data they’ve got with advanced modelling technology.