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Available Google Analytics 4 recommendations

Jonas Østergård Bæk avatar
Written by Jonas Østergård Bæk
Updated over a week ago

Alvie checks your Google Analytics 4 accounts for a multitude of different things that can help you improve its performance and ultimately help you get a better return on your investment.


The following rules are monitored across your GA4 accounts:

Best Practices

Alvie currently has no recommendations of this type for GA4

Performance

1. Campaigns with a significant drop in key events

Some of your campaigns have had a significant drop (>90%) in key events in the last 30 days compared to the previous 30 days. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

2. Campaigns with a significant drop in key events (LNDA attribution)

Some of your campaigns have had a significant drop (>90%) in key events in the last 30 days compared to the previous 30 days when looking at LNDA attribution. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

3. High-value campaigns with a significant drop in key events

Some of your high-value campaigns have had a significant drop (>80%) in key events in the last 30 days compared to the previous 30 days when looking at DDA attribution. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

4. High-value campaigns with a significant drop in key events (LNDA attribution)

Some of your high-value campaigns have had a significant drop (>80%) in key events in the last 30 days compared to the previous 30 days when looking at LNDA attribution. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

5. High-value campaigns with a significant drop in sessions

Some of your high-value campaigns have had a significant drop (>60%) in sessions in the last 30 days compared to the previous 30 days. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

6. Source/mediums with a significant drop in key events

Some of your source/mediums have had a significant drop (>90%) in key events in the last 30 days compared to the previous 30 days. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

7. Source/mediums with a significant drop in key events (LNDA attribution)

Some of your source/mediums have had a significant drop (>90%) in key events in the last 30 days compared to the previous 30 days when looking at LNDA attribution. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

Errors

1. Events with significant shifts in attribution

Some of your events have had a significantly change in the difference between the last non-direct and default attribution models. This could be due to changes in user journey patterns, cross-device tracking issues, campaign tagging inconsistencies, or integration problems between platforms. Review the affected source/medium and their full conversion paths to understand the attribution differences and take action accordingly.

2. Meta Ads source/mediums with a significant drop in sessions

Some of your source/mediums that we've identified as coming from Meta have had a significant drop (>70%) in sessions in the last 30 days compared to the previous 30 days. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

3. Google Ads source/mediums with a significant drop in sessions

Some of your source/mediums that we've identified as coming from Google Ads have had a significant drop (>70%) in sessions in the last 30 days compared to the previous 30 days. Check if there is a reason behind the drop, or if it is due to natural factors such as seasonality, short-term campaigns, etc.

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