Changes in the Attribution World

By Tanuj Joshi, Eulerity

Facebook and Google have announced significant changes to their respective attribution tools. Facebook’s changes are primarily affecting users who use the Facebook attribution platform on ads served on Facebook but Google’s changes are more widespread. Google’s changes affect Google Analytics which is the leading software used by many brands to analyze the traffic coming to their website (including analyzing marketing initiatives).

Below is a quick summary of the changes each platform is planning to implement.

Changes by Facebook

Facebook announced removing the 28 days attribution window option in their Facebook attribution models. Attribution models make advertisers able to measure particular responses based on rules made by the advertiser to their campaigns. Instead of 28 days, there will be a limited overview of seven days of direct response performance. This change is expected to only influence expert Facebook marketers and the advertisers who operate large campaigns. On the other hand, it will impact highly automated systems that are set up to understand only Facebook marketing events.

These changes will work from the 12th of October, and all the historical information will be accessible until that day. If you have used attribution models before, it might be good if you downloaded your data to track the historic performance.

Google Analytics Changes

Google has updated Google Analytics platform with new machine learning capabilities, unified app and web reporting, native integrations, and privacy updates. The new, more intelligent Google Analytics that builds on the foundation of the App + Web property was introduced in beta last year. It has machine learning at its core to automatically surface helpful insights and gives the user a complete understanding of customers across devices and platforms. It has a new privacy-centric design, so the users can rely on Analytics even as industry restrictions (on cookies and identifiers) create gaps in data.

Some new features include:

• Advanced machine learning models that can automatically alert users to significant trends in their data, like calculating churn or purchase probability;
• Unified measurement to remove fragmentation and help businesses understand how all channels are performing in real time;
• Privacy-safe measurement with new controls to help users better manage their usage of data.

Tanuj Joshi is the CEO of Eulerity. Using machine learning and automation, Eulerity’s state-of-the-art technology simplifies the complex world of developing and executing digital marketing programs — all for a flat and transparent fee — a fraction of the cost of traditional vendors. For more information about International Franchise Association (IFA) supplier member Eulerity, click here.