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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.
AttentionMake sure the channel integration with Airbridge is completed before checking up on the causes of data discrepancy.

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Differences in the Attribution Model

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.

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Differences in Aggregating 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.
Google Ads and Airbridge may use different data sources. When you use Firebase SDK alongside Airbridge, Google Ads uses data from both Firebase SDK and Airbridge SDK, while Airbridge does not use data from Firebase SDK. This may cause higher conversion or revenue numbers in Google Ads compared to Airbridge reports.
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.

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Differences in Fraud Validation Rules

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.