The Mobile User Acquisition Show

📈Are You Overpaying Your Ad Network by 30-40%? Decoding SKAN vs. probabilistic billing🧐

Sep 15, 2023

The podcast discusses the pitfall of using probabilistic models for optimization but relying on SKAN data for billing in ad networks, potentially leading to overpayment. They explain the difference between SKAN CPA and probabilistic CPA in ad networks and highlight the limitations and challenges of using scan attribution for billing. The hosts recommend a conservative approach for accurate spend verification.

08:44

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Quick takeaways

Working with ad networks that use probabilistic modeling for attribution and reporting while relying on SKAN data for billing can result in a 30-40% increase in actual spend compared to reported spend.

To address the discrepancy in ad network metrics, advertisers can either take an aggressive approach by considering billable spend as the source of truth and adding a multiplier for missed conversions, or a conservative approach by relying on scan conversions as the source of truth and disregarding probabilistic conversions, ensuring easier comparison across channels and more credible metrics.

Deep dives

The Pitfall of Using Probabilistic Modeling for Ad Network Attribution

One main idea discussed in the podcast is the potential pitfall of working with ad networks that use probabilistic modeling for attribution and reporting. The speaker highlights that while these networks may use probabilistic models for optimization and reporting, they rely on scan data for billing. This discrepancy can lead to a significant difference between the spend accounted for in daily and weekly reports and the actual bill from ad networks, with a potential increase of 30 to 40%. This gap can result in significant financial loss if not carefully monitored and accounted for, especially if there is a disconnect between the finance team and the media buying team. The example of the difference in reported spend between probabilistic and billable according to scan data is provided to illustrate the magnitude of the issue.

Introduction

3min

Understanding the Difference Between Scan CPA and Probabilistic CPA in Ad Networks

3min

Challenges and Approaches for Attribution and Billing in Mobile User Acquisition

4min

In this episode, we dive into a common pitfall we’ve seen many developers fall into lately. While many ad networks use probabilistic models for optimization, they turn to SKAN data when it comes to billing. This discrepancy might mean you’re paying 30-40% more than anticipated or that your campaign’s performance isn’t as stellar as you believed. In this episode, I unpack the underlying mechanics of what is happening – and what we recommend doing instead.

Check out the show notes here:
https://mobileuseracquisitionshow.com/episode/ad-network-skan-billing/

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