Data discrepancies may occur between Google Ads and Airbridge due to varying reasons. Read on to learn the primary causes of the discrepancy. For more details, refer to the Google Ads Guide.
Attention
Make sure the channel integration with Airbridge is completed before checking up on the causes of data discrepancy.
Google Ads and Airbridge operate on different attribution models, which leads to discrepancies in the attribution data.
The conversion window might be set differently between Google Ads and Airbridge. By default, Google Ads tracks first open or install conversions within 30 days of the ad interaction, and in-app conversions within 90 days of the ad interaction. Airbridge tracks ad interaction with Google Ads within the 30 days prior to the time of install by default.
Google Ads and Airbridge also differ in their use of identifiers such as GAID, GCLID, and gBraid, which may be the reason for the data discrepancy.
Google Ads attributes conversions to Google Ads when there has been any interaction with an ad from Google Ads within the attribution window. Airbridge, however, collects touchpoints from various channels and attributes conversions to a winning touchpoint based on the attribution model used in Airbridge. For more details, refer to the user guide on attribution models.
Attribution conventionally involves matching the touchpoints and conversions using ADIDs and creating a user journey for each identified user. With growing concerns about data privacy and more stringent privacy regulations, collecting ADIDs is getting more difficult.
Against this backdrop, Google Ads uses the conversion modeling method to track campaigns when ADIDs are not available. The conversion modeling estimates the conversions using machine learning techniques. For more details, read the Google Ads Conversion Modeling Guide.
Airbridge does not employ conversion modeling for attribution. In addition, Google Ads does not share the conversions attributed using the conversion modeling with any third-party, which may be the reason for the discrepancy in data.
Google Ads and Airbridge operate on different rules when aggregating data, which leads to discrepancies in the attribution data.
Google Ads aggregates data based on the day a user interacted with the ad. Airbridge, on the other hand, aggregates data based on the day the conversion event occurred.
Google Ads gets the conversion event data via postback, and it takes several hours for the data to be displayed in the Google Ads dashboard, whereas in Airbridge, most of the conversion events are fed and displayed in the dashboard in real-time.
When the time zones for Google Ads and Airbridge are set differently, the data will be displayed differently, causing discrepancies. Google uses the local time set in the advertiser's account, and Airbridge uses the app time zone set by the Owner of the app.
Google Ads cannot use the personal data of end users in the European Economic Area (EEA) without receiving the consent values. Even when the consent values are received, Google Ads will still not be able to use the personal data if the end users did not give consent to use their data for ad personalization or to send their data to Google for ad-related purposes.
This explains why compliance with Google’s updated EU user consent policy may result in a potential decrease in the performance of your Google Ads campaigns in the EEA.
The United Kingdom and Switzerland are not members of the EEA and, thus not subject to Google's updated EU user consent policy.
Google Ads and Airbridge operate on different sets of fraud validation rules, which can lead to data discrepancies. When Google Ads identifies ad fraud based on its internal validation rules, the fraudulent traffic is removed and not included in the attribution data.
Airbridge identifies ad fraud based on the fraud validation rules you configure in your Airbridge dashboard. The fraudulent conversions and touchpoints are processed according to the prevention level you set - they can be marked as fraud but still attributed or not attributed at all.
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