Don’t miss a beat, or bit, with our explanatory guide of iOS14+ solutions

Owners of an iOS device are now familiar with the renowned ATT prompt. 


The prompt asks people whether or not they want to allow the app to track their activity across other companies’ apps and websites.


To keep on using data to measure and optimize their online marketing strategies, businesses have implemented the ATT prompt. 


Despite iOS 14.5+ updates that have been installed by over 80% of the eligible iPhone owners, we have observed that the ATT prompt has not been implemented in 52% of apps globally, 39% specifically for Gaming apps.


Why does it matter? 

Without ATT consent by users, data becomes available only in SKAN.


Many advertisers are still learning about SKAN today, despite its existence for several years. Apple’s StoreKit Ad Network (in short, SKAN or SKAD) “allows advertisers to measure the impact of their ad campaigns without device-level data, so that {advertisers} don’t track users.


Here are some of the features of SKAN:

  • Post-install event measurement must be configured and mapped in advance by advertisers as “Conversion Value” and are limited in quantity, using a 6 bits mechanism with maximum 64 outputs.
  • Only one postback is sent after an install and it includes the conversion value. Advertisers need to ensure their setup is done correctly and efficiently to be able to have visibility into post-install events and also optimize ads on ad networks.
  • Data is aggregated, which is a reporting methodology marketers need to adapt to.


The time for sending back the configured values is limited after the install. Therefore, the right configurations and schema setup in SKAN would allow marketers to keep on drawing valuable and actionable insights to optimize ad campaign performance.


Diving into the limitations… and their solutions

One of the most complicated areas brought by the limitations of the new iOS 14+ involves SKAdNetwork’s conversion value and timer extension mechanisms.
In Apple’s SKAdNetwork data is far less in-depth and at length: you need to set your schema in a way that can only be translated into 6 “bits” and 64 combinations of such “bits” to map post-install activity. Moreover, post-install activity data availability is time-limited.

In other words, conversion values are SKAN’s alternative to [limited] LTV.


How should marketers map their conversion value schema to make the most of SKAN – limited – features?


Bits can be thought of as binary values, each of them can represent a metric, a signal of user behavior, an event. The hassle with bits and timers lies in the fact that you usually need to map, translate into bits and think of many possible combinations. 


There are 6 bits, but ultimately 6 bits can be configured to yield 64 possible combinations. How? Each bit can be either on or off, 0 or 1. When taking into account all possible combinations of 6 bits being 0 or 1, there are a total of 64. Therefore, there are 64 different possible values. We call the strategy to combine the different bits “splitting the bits” and while cumbersome, it is the most comprehensive way you can draw insights into post-install user behavior.

There are several ways of “splitting the bits” : Flat, Split, or Combo Split. Meaning you can map 1 metric (an event, or an  action, or a  signal), multiple metrics, or a combination of different types of both:



Let’s look at an example represented by the image above. In a gaming app, the marketer wants to measure in-app purchases (revenue), game progress, and whether or not the user has registered. Revenue has 3 bits allocated (8 possible outcomes), progress has 2 (4 possible outcomes) and sign up, which is binary, has one bit (2 possible outcomes, yes/no). The marketer has mapped out all possible outcomes, and here is one of them:

  • 011 = revenue of $5-$10
  • 10 = progress – completed 5+ levels
  • 1 = sign-up – yes

011101: is the outcome, meaning the Conversion Value in this example would be 29.

Mapping out all of the bits, testing them, optimizing them and sharing them with media partners can be an immense undertaking for marketers.


Now, if you were given the option to easily set up your schema within a simple interface, would you take it?


AppsFlyer Conversion Studio provides you with maximum flexibility to make every bit count. You determine precisely what measurement data should be encoded within the Conversion Value —including what activity and for how long to measure during the post-install period. 


Below are the different types of events mapping you could choose to configure. You can choose to focus on one or combine several. All of them can be easily selected within AppsFlyer Conversion Studio without complex combinations of bits: 


Revenue: Revenue generated by the user during the activity window before the one-time postback is sent. It can be recorded using a single event, or associated with revenue by stream (IAP, IAA, subscription revenue) using select in-app events. 


In-App Events: Post-install in-app behavior such as tutorial completions, logins, purchases, shares, and level completions. Marketers can measure the number of unique users performing an event, the number of times an event was performed, or both.


Funnel: Measures the occurrence of in-app events based on a list of sequential events in a funnel. A user performing any event in the funnel is regarded as having performed all the events preceding that event. This is the most efficient way to measure sequential events, using fewer values for the same amount of in-app events measured.


Now that we have explained the ‘how-to mapping’ of Conversion Value and you know some of the benefits of Conversion Studio, we can show you what we have learned from over 600 apps who have recently adopted our solution.

As the default setting, 24-hour activity windows are the most common.


An example of Revenue + In-app Events setup of a gaming app:


Timer and intervals: going beyond the 24 hour default


The timer within the SKAN framework represents the post-install activity window. 

At AppsFlyer, we have capitalised on the ability to reset this timer to get a better understanding of retention. 


Retention rate is being calculated according to which interval the user action was last recorded. 

So within Conversion Studio, you can find intervals within an activity window.

The interval also helps us to calculate the install time more precisely:

Install time = Postback arrival time – [Avg. time post install] – [Avg delay time]


The timer can be configured for up to 72 hours providing much more flexibility and insights into post-install user behavior.


Beyond the fact that 24h-hour window is the default, it’s important to remember that data can only be collected once, so there is an intentional tradeoff. 


Shorter activity windows enable faster data collection, but leave you with limited information. Alternatively, longer windows provide richer data, but access to it will be delayed.


Also, the timer cannot be extended for all users – so even if it’s extended, it will only apply to a portion of users. The only way to extend the timer is by updating the conversion value, which can only happen if the app is opened.


So, even if you set the timer to 72H, if the user didn’t open the app for 24H, the conversion value is locked. For example, if a user opens the app on day 0, day 1, and day 3, the activity of day 3 won’t be recorded – because the app wasn’t opened on day 2.


As SKAN usage matures among marketers, we expect things to change. 

Your success with conversion goals depends on how you tailor your strategy to your unique app. 


This guide  is  a good starting point, but remember: there’s no “right” answer, only what’s best for you.


Still puzzled? Learn more about Conversion Values by watching this short video

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