What increased user privacy means for mobile advertising

Ever since Apple introduced its ATT privacy framework to give app users more control over their data, ad tech companies have had to compromise to meet new data constraints while still meeting their growth goals.

While mobile advertisers can no longer use personal IDs to track the 70% of iOS users who have not consented to be tracked have other tools at their disposal — such as contextual cues and probabilistic attribution — to identify and target quality audiences across the mobile ecosystem.

That said, in-app advertising may seem less efficient with the Identifier for Advertisers (IDFA) deprecated. But with the right data, strategies and partners, not only is it still a viable growth strategy, but a of vital importance a.

What has changed after iOS 14.5

Under the new privacy restrictions, app advertisers can no longer rely on the IDFA to provide them with device-level data to show relevant ads to users on iOS devices. Since advertisers can no longer track a user’s activity in apps on iOS, including their clicks, downloads, and conversions, they also have fewer opportunities to measure the effectiveness of their ads and use that information to optimize their campaigns and ad budgets accordingly .

This loss of efficiency means lower conversion rates, but also cheaper CPMs (cost per 1,000 impressions). So while scaling campaigns to beat KPIs may be more complex, growing apps can be cheaper than before.

Performance marketing is different, not worse

As of iOS 14.5, while advertisers can’t access device ID data, they can still use contextual cues to serve ads to quality users. What are Contextual Signals? They are privacy-compliant data points that provide useful information about an advertising opportunity, such as location, device type, and information about the environment in which an ad is displayed (i.e. features of an app or website).

This kind of data allows advertisers to use contextual targeting—matching an ad to an impression opportunity—to accurately predict how likely a user is to interact with an ad. From there, they can determine the amount to bid for each impression.

Because users are automatically opted out of IDFA tracking, advertisers can no longer rely on the device ID to access data about how a user interacts with an ad, nor target one-to-one audiences based on in- app events. Instead, machine learning (ML) models use new contextual cues to make effective predictions.

While this has made in-app ads less efficient, iOS ads still meet or exceed advertisers’ ROAS goals. For example, at LifeStreet, we’re seeing fewer conversions per ad dollar spent on traffic with no device ID, but our CPMs are about 2.1 times lower. This leads to a 10% increase in ROAS on media spend without a device ID. While the impression-to-conversion rate has changed, lower costs have made advertising on iOS more effective.

New data, new competitive landscape

Contextual signals can also be combined with other statistics. For example, the number of interactions with a specific attribute of an ad indicates which part of the creative adds value. Of course, this isn’t as accurate as using the IDFA, but technologies like ML make it possible to take these signals and predict in real time the value of each ad impression with almost the same level of accuracy as ads based on device IDs.

In addition, the mobile advertising competitive landscape is much flatter than ever before. Today, all ad technology players – not just those outside the walled gardens (Facebook, Google) – have less information about users than before. This has created space for smaller, niche players with specialized historical ML models and agile algorithms to compete with the tech giants.

For this reason, marketing platforms that have seen the most success since the IDFA ended are those that continue to invest in improving the performance of their models by adding more predictive signals. The ability to produce new signals that can be used to train models to continuously improve their predictive accuracy will lead to more effective bidding, enable lower CPIs and higher user quality, and ultimately increase ROAS for their advertisers.

How to set up your mobile advertising strategy for success

Now that the rules of the mobile advertising game have changed, so have the methods of winning it. What are the strategies for successful mobile advertising in today’s privacy-based advertising technology landscape?

Re-evaluate incrementality and experiment with your media budget

As mentioned above, the economics of mobile advertising have shifted since iOS 14.5. That means it’s smart to re-evaluate the tangible impact of your spending and experiment with your media budget. Be open to testing new channels and specialized partners. Work closely with your mobile measurement partner (MMP) to maximize available attribution data and understand the incrementality of each partner’s campaign performance, enabling future campaign success.

Be open to partnering with independent ad technology companies

Today, the playing field is more level, allowing smaller, niche technology providers to achieve stronger outcomes than previously possible. For advertisers, there is an opportunity to partner with independent ad technology companies that can provide bespoke solutions to suit their needs rather than the “one-size-fits-all” approach of the walled gardens.

Demand more from your growth partners

Finally, advertisers need to be demanding of their partners, monitor how they operate and make sure advertisers get the information they want, not just performance. With Apple’s ongoing privacy changes — and soon Google’s — strong performance today is no guarantee of strong performance 18 months from now.

It is essential that advertisers ask themselves: am I working with the right partners? Are they transparent and do they pass data I can use to scale future campaigns? Do their process and expertise inspire confidence? If the answers to those questions are not affirmative, it may be time to rethink your current marketing mix.

Despite increased privacy, the future of mobile advertising looks bright

The mobile games market is expected to grow exponentially in 2029. The advertisers making the most of this boom are those whose partners can efficiently test and use the contextual signals they receive from ad exchanges to iterate on their predictive modeling. In our current era of increasing user privacy, the methods of successful mobile advertising may have changed, but the ability to succeed has not. Ad technology has always been full of pioneers who thrive in moments of uncertainty, and this moment will be no different.

Levi Matkins is CEO of LifeStreet.