Why does my Google Analytics 4 Conversion attribution differ from Universal analytics?

Lace Chantelle Rogers
5 min readJul 7

1. Why are my conversions attributed differently?

Firstly we are looking at two very different tools, UA was set to a specific logic whereas GA4 now takes advantage of advanced AI and machine learning, coupled with a customisable attribution model for conversions.

How does universal analytics model attribution?

UA allocates create to the last click source and medium. This means whatever the last source of the click the attribution will be credited to this. The default look back window is 6 months. If you want to review a different type of attribution model such as first touch in the model comparison tool. Link

How does google analytics 4 model attribution?

GA4 has multiple scopes of attribution, this means there will be differences between your UA and GA4 conversion attribution. The default look back window is 90 days. Link

· User

· Session

· Event

Customisations in GA4

Within GA4, you also have data driven attribution, which you can adjust 4 aspect of the model link

· The model used (default is data driven)

· Channels eligible to receive credit with web conversions shared with Google ads

· Conversion window for acquisition conversion events

· Conversion window for all other conversion events

What is recommended?

I highly recommend using the data driven model, whilst the results are harder to explain, the outcome is that you will see a truer reflection of your marketing efforts and how this impacts conversions. For example if you do paid search and then the next day a user searches for your website as an organic user, it is likely the paid search activity drove that organic search.

By using the data driven model, you are able to accurately view the performance of mix marketing models and then benefit by using these more accurate converting users in your…

Lace Chantelle Rogers

https://www.bigquery.co.uk/ Head of data and analytics . GCP, BigQuery and GA4 expert specialising in data engineering and data science, with Python,sql

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