Anyone who has ever run Facebook Ads and compared their data with Google Analytics will have encountered the same problem: they NEVER match. The discrepancies can be as high as 50% - 90%! But why is this, and can the problem even be fixed? Here is the information you need!
1. Different tools use different tracking methods
When working with different tools, you should be aware that each one uses its own measurement and processing methods. This is the case with Facebook and Google Analytics (GA). While the latter uses classic cookie tracking, Facebook uses a "people-based" tracking method. The advantage: while GA can only track users across the same browser session, Facebook can track user activity regardless of the browser or device used. Conversely, this means that as soon as a user closes the browser or switches devices, such as from mobile to desktop, GA cannot automatically recognize these users again—but Facebook can.
2. Facebook clicks vs. GA sessions
The next point: Facebook clicks are not the same as GA sessions! While a Facebook link click is tracked as soon as a user clicks a link, GA tracks a pageview and thus the start of a session only once the website has fully loaded. If a user clicks a link but leaves the page immediately—perhaps because the click was accidental or the load time was too long—GA will not track a session. Furthermore, a GA session lasts 30 minutes. This means that if a user leaves a site and clicks on the same Facebook ad again within the next 30 minutes, GA will track only 1 session, whereas Facebook will track 2 link clicks.
3. Facebook attribution vs. GA attribution
Conversion attribution also differs significantly between the two tools. GA only measures click-through conversions, while Facebook also claims view-through conversions. In other words, GA cannot measure if someone simply saw an ad and subsequently made a purchase, but Facebook can.
The attribution models of the two tools also differ. GA uses the so-called last-non-direct-click attribution in its standard reports: if a user sees a Facebook ad, then searches for the advertised product via a search engine, and subsequently completes a purchase, the purchase is attributed to the search engine. However, since Facebook claims both click-through and view-through conversions, it would also claim this purchase. For Facebook, the rule is: as long as a user has seen an ad and converts within 24 hours, or clicks an ad and converts within the next 28 days, Facebook receives 100% credit for the conversion.
Furthermore, both tools have different attribution windows and conversion time recording. While the standard attribution window in GA is 6 months, it is only 28 days for Facebook. Additionally, GA attributes conversions to the day of the transaction, whereas Facebook attributes them to the day of the view or link click. This naturally leads to further data discrepancies.
4. Ad blockers & cookie blockers
Another reason for data discrepancies is the use of ad blockers or cookie blockers by users. Ad blockers prevent the Facebook pixel from firing, whereas GA cannot track data if the user has a cookie blocker installed. The resulting data discrepancy is self-explanatory.
5. Other factors
Other reasons for data discrepancies can include Facebook bot traffic or URL redirects. With the latter, Facebook in particular often tends to strip away campaign parameters. If you are working with UTM parameters, they may be lost during a redirect. Therefore, it is better to use short URLs (Bitly, TinyURL, etc.) for UTM parameters and ensure that bot traffic is excluded in both GA and Facebook.
Tips for improving data discrepancies
- View Facebook view-through conversions separately from click-through conversions
- To view these separately in Ads Manager, go to "Columns," select "Performance," and then "Customize columns." Adjust the attribution window at the bottom right, selecting 28 days for "Click" and 1 day for "View."
- Use multi-channel funnel analyses instead of standard GA reports, as these show all paths a user took before converting, not just the last channel.
- Set a consistent conversion attribution window that fits your product or industry (e.g., for insurance, a longer window makes sense as the decision process is longer than for a low-cost fashion brand).
- A final analysis should not only take place after the campaign ends, but also after the attribution periods of both tools have expired.
- Use UTM parameters to track campaigns, but use short URLs. Ensure that both tools are set to the same currency and time zone.
As you have seen, there are various reasons for the significant data discrepancies between Facebook and Google Analytics. The points above should help you minimize these differences and, more importantly, make them justifiable. Nevertheless, you should be aware that it will never be possible to achieve 100% data alignment. To get a holistic overview of channel performance, you should always compare different tracking tools and attribution models.
