An inability to associate conversions with ads could cause brands to have an incomplete picture of the customer journey. As privacy updates evolve and the use of individual identifiers continue to be restricted, Google plans to increase its conversion modeling efforts to replace diminished observed modeling.
About Conversion Modeling
According to Google, conversion modeling refers to the use of machine learning to quantify the impact of marketing efforts when a subset of conversions can’t be associated with ad interactions. They are not identifying specific individuals but are instead using the behavior of observed groups to predict the behavior of other groups. Quality conversion data (1st party, aggregate customer behaviors and contextual signals) coupled with machine learning-based modeling will provide an accurate, representative view of campaign performance and fill gaps that exist in the advertiser’s view of the customer journey.
Recommendations to improve the quality of Google conversion modeling:
- Detailed first party data collection
- Proper Tag set up
- Smart Bidding knowledge
- Proficiency in both Google Analytics 360 and the new GA4 platform
With Google accounting for approximately 18% of all eCommerce revenue, it is imperative that your advertising agency understand the impacts of campaign performance measurement in this platform. Trone’s paid media specialists are certified and experienced in all Google Marketing Platforms. Contact us to find out how we can help you optimize and accurately measure campaign performance to ensure a healthy ROI.