If by comparing Google Ads data with offline data you find a difference in the number of sign-ups for ads between the two sources, and you believe the issue lies with when a conversion was counted, what’s the likely source of that data discrepancy?
- It’s probably due to the fact that Google Ads reports conversions against the date/time of the click that led to the conversion. Depending on the other data source, it might use the date/time of the conversion itself.
- It’s probably due to the fact that Google Ads reports clicks against the date/time of the event that led to the conversion. Depending on the other data source, it might use the click of the conversion itself.
- It’s probably due to the fact that Google Ads reports views against the device type of the view that didn’t lead to a conversion. Depending on the other data source, it might use the date/time of the conversion itself.
- It’s probably due to the fact that Google Ads reports conversions against a unique ID of the event that led to the click. Depending on the other data source, it might use the click of the conversion itself.
Explanation:
The correct answer is **’It’s probably due to the fact that Google Ads reports conversions against the date/time of the click that led to the conversion. Depending on the other data source, it might use the date/time of the conversion itself.’** This answer accurately identifies a common source of data discrepancy between Google Ads and offline data when comparing the timing of conversions. Google Ads typically reports conversions based on the date and time of the click that led to the conversion. However, other data sources, such as offline tracking systems, may record conversions based on the date and time the conversion actually occurred, which could differ from the click time. This difference in reporting methods can result in discrepancies in the number of sign-ups attributed to ads between the two sources. Understanding this discrepancy is crucial for accurately analyzing campaign performance and reconciling data from various sources. Therefore, the selected answer provides a plausible explanation for the data discrepancy and highlights the importance of considering differences in reporting methodologies when comparing data from different sources.