myTracker Introduces Free LTV Predictions Based on SKAdNetwork Data

Partner Post - MyTracker Multi-platform Analytics and Attribution

Posted: September 23, 2021

According to myTracker data, as of September 22, 2021, 74.6% of iPhone and iPad users globally have upgraded to iOS 14.5 or higher.

The new iOS version came with restrictions in the form of ATT and SKAdNetwork, which significantly limited the ability of developers and marketing specialists to adequately assess the ROI of their ad campaigns using traditional tools. Now all hopes are pinned on the ability of ad platforms and tracking systems to deliver innovative solutions that will save the day.

One such solution is LTV forecasting. Currently, there are two ways to do this:

  • LTV forecasting with SKAdNetwork Conversion Value functionality for devices
  • LTV forecasting using predictive models based on available data for ad campaigns.

Standard SKAdNetwork mechanisms enable the sending CVs ranging from 0 to 63. For example, you can create an LTV–CV table and forecast the approximate ad campaign revenue.

However, this method has a number of downsides such as time lags in displaying data and high indirect costs, making it difficult to implement this option in the app independently. You can read about other issues with this method in our blog post Predictive Analytics and SKAdNetwork | How to Predict LTV in iOS 14.5+

The other method involves using machine learning models based on available data to predict revenue from users acquired through various ad campaigns. And this is where myTracker blazes a trail by introducing free LTV forecasting (30 to 180 days) for ad campaigns on iOS 14.5+ via SKAdNetwork, with a prediction accuracy of up to 94.3%.

Today, myTracker’s prediction models can:

  • Predict an app’s revenue for a long period and with high precision. This becomes possible thanks to the fact that SKAN postbacks are received within 48-72 hours, which gives plenty of time for the system to thoroughly analyze user post-install behavior.
  • Distinguish between the revenue generated by organic users and users brought in by ad campaigns.
  • Make an LTV prediction for each type of revenue separately: in-app purchases, subscriptions, and ad monetization.
  • Determine the app install date via the CV receipt date.
  • Allocate the app’s ad revenue to ad campaigns – and consequently to ad networks.

myTracker’s free LTV prediction based on SKAdNetwrk Data

Click the image to open a full-scale version

To start working in myTracker, you need to register and make sure the app is active and the data is fed to the analytics system (it is necessary to train predictive models).

myTracker’s long track record in LTV forecasting coupled with its unique machine learning algorithms empowers its customers to predict income to be generated by users based on SKAdNetwork data.

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