Offer Yehudai is the president of Fyber.

IDFA is dead. We realized it quickly and now have to acknowledge it as reality. Times like these will come along no matter what industry you are in and, if anything, we should view this as a call to action for people in our industry to reshape our space and find innovative solutions that will serve our partners the day after.

The industry could not have predicted the exact details of Apple's new approach to the IDFA but, essentially, the writing was on the wall and players across the value chain have been bracing themselves for the change and its potential impact for a while now.

The SKAdNetwork V2.0 was released during the Apple Worldwide Developers Conference (WWDC), offering a glimpse at Apple's plan to own attribution in their own style - with privacy positioned at the forefront.

Driving performance with context

The de-facto deprecation of the IDFA is a massive game-changer as it is now used to identify a user, retarget a user, compile suppression lists (lists of users who already installed the app) as well as close the attribution loop based on view or click-through. Without it, advertisers, networks and DSPs will fly blind and the first metric to get hit will be the return on ad spend (ROAS).

Trying to look for alternative signals that drive campaign performance in a privacy-friendly manner, our team turned to answer the question at hand - what can DSPs know in real time about the opportunity, and not about the user? Contextual targeting is what we came back with.

Contextual targeting existed in the web environment for years. One main difference between the mobile version and its web sibling is that it cannot rely on written content – as such deduction of context is not applicable to a large portion of the app environment. But that environment does give us some great data points that we can leverage to figure out context.

The parameters of contextual targeting

One of the most important data parameters that we can see is the depth of impressions. Is this the first ad impression of the day for the user? Or is it the 20th? How long has the app been in use? At the moment, DSPs are not exposed to such information but in a world with no IDFA, these data points will become vital signals into understanding the context of the user experience.

For example, a performance marketer looking to generate wider brand awareness will probably want to target the lower end of the impression depth. This would allow him to put his ad in front of fresh eyes - maximizing the chances of engagement and retention.

Other examples of parameters include device status signals such as network connection strength, battery level or disk space. All of these signals can provide insight into the situation in which the device is in right now - Is the network strong enough to download a gaming app? Will the battery last? Is there enough storage space? Understanding signals like these ensures ads are landing where engagement is most likely.

Contextual targeting provides context that is generated from a mix of data points coming from the device, the underlying technology, and the content, blended with session-level behavioural information. It also leverages privacy-aware parameters that cannot be used to identify an individual user or track users across apps.

Undeniably, the entire app ecosystem has a vested interest in the shift to app bidding, as a means to diversify demand, increase yield and operational efficiency, and retain control for advertisers and publishers alike.

We feel that while this announcement has the potential to put sticks in the wheels of programmatic, it actually presents an opportunity to establish standardized OpenRTB custom extensions that can be seamlessly adopted and used for targeting by the programmatic app industry. This is where we are heading.

Different game genres, different impact

Fyber and mobile game developers have been working closely for years. We understand developers' considerations and needs - and plan to be there for them when this tectonic shift takes place. Different game categories are bound to be affected at different levels and the industry as a whole will adapt, while embracing the new tools at hand.

Monetization strategies vary across different game genres, and that variation will affect the solutions that publishers in each of the genres will need to embrace. While hyper casual games usually rely solely on ads for revenue, casual game genres such as puzzles and idle usually have a more balanced monetization strategy that combines ads and in-app purchases (IAP). Mid-core game publishers usually turn to IAP as their main source of revenue.

The impact for the IAP heavy-to-moderate games will also be interesting to watch, as identifying and targeting the big spenders - the whales - requires leveraging granular user-level data. Thus, alternative ways to generate and leverage data signals are crucial for the publishers of these games and will affect their strategy.

After Apple's announcement we assumed that hyper casual publishers, due to their thin LTV-CAC margins, will sustain the greatest hit in the likely case of a drop in CPM rates. Yet, a second look, with contextual targeting in mind, made us more optimistic. The short-lived nature of hyper casual games (less than 7 days) together with its short retention rates see users explore new games based on their categories.

We are working with our partners and the industry to already devise this post-IDFA strategy, that will leverage contextual targeting opportunities as well as generate the necessary strategy shifts that will benefit everyone.