“Why is my Facebook account showing me such different numbers from my Google Analytics (GA) account?” The question is a common one among marketers getting started with Facebook advertising.
Just when pixel deployment is complete, the site is quality assured, and media is pushed live, the real questions start. For some reason, Facebook is suddenly showing much higher conversion numbers than Google Analytics is. What’s going on? Why is our Facebook and Google Analytics data so different?
Luckily, because this question is fairly common, many people have already been working out the answers. In general, there are four causes that often make up the difference:
- Attribution modeling
- Tracking issues
- Traffic loss
- Lookback windows
You can pretty much eliminate causes two and three on the list from consideration and just focus on attribution if the amount of website traffic Facebook is reporting is within five to 10 percent of the sessions from Facebook that Google Analytics (GA) is reporting.
Remember that Facebook reports on multiple types of clicks, and not all of them drive to your website. For most formats, you’re better off using ‘link clicks’ rather than ‘all clicks’, as link clicks track clicks to the selected destinations only.
Attribution is far and away the most common cause for a discrepancy in reports. Even if everything is correctly set up, Facebook and GA use very different models for attributing conversions to online channels and will report very different numbers.
Facebook now (as of March 2021) defaults to a seven-day post click and one-day post view post-click attribution window – except for iOS14 app install campaigns where the attribution window will be provided by Apple’s SKAdnetwork application programming interface (API). This means that if a person saw your ad and made a purchase within 24 hours, Facebook would count that conversion regardless of whether or not they clicked your ad. Similarly, if they clicked your ad, Facebook will count any conversion in the next seven days.
GA defaults to last interaction, with that last “interaction” almost always being a click. Using this model, GA would only count a conversion for Facebook if a person clicked on a Facebook ad, went straight to the site, and made a conversion during that session. If the person didn’t click an ad, or clicked, but decided to come back later – perhaps via search or directly typing in the uniform resource locator (URL) – GA won’t count the conversion for Facebook.
For most advertisers, Facebook tends to operate close to the top of the funnel, driving awareness, interest, and brand affinity. The time between a Facebook impression and an eventual purchase is, on average, much longer than that between a search and click on a Google ad. This means it is unlikely for Facebook activity to drive people straight to a purchase. In turn, there is almost always another touchpoint (including organic search or directly typing in a URL) between Facebook and GA, so GA will count zero conversions for Facebook.
Below, you can see the differences between the types of activity Facebook will record a conversion for versus those that GA will record a conversion for. As you can see, there are quite a few gaps between Facebook and GA.
Facebook’s model may seem optimistic, but GA’s model isn’t quite right either. Evidence from Croud’s client base suggests that the truth probably lies somewhere in the middle. In fact, some case studies have demonstrated even greater impacts from Facebook advertising than Facebook’s own attribution model suggests.
While a full discussion of attribution models, conversion deduplication, and media mix modeling are beyond the scope of this post, some readers may find it helpful to consider using GA’s “assisted conversions” to get a quick feel for what performance would look like “somewhere in the middle.”
If you’ve evaluated clicks to your website, as reported by Facebook, and compared them to GA sessions, and found a discrepancy larger than 10%, then there may be other issues at play.
The next most common cause is tracking issues. These occur when traffic is coming through to your site but isn’t being recorded properly. To diagnose these problems can take a bit more work than comparing attribution models.
In approximate order of importance, we recommend checking that:
- All Facebook ads have tracking (e.g. universal transverse mercator (UTM) parameters) correctly applied
- The Facebook pixel is correctly implemented with an applicable conversion event
- No landing page URLs are being redirected – server redirects often strip tracking parameters
- The GA profile you are using does not have any filters in place
- GA is firing in the page header on all pages
- GA is not configured to override UTM parameters
- No other site components, such as tag managers, are interfering with the GA tag firing
- With the upcoming iOS14 update, ensure that you have no more than eight pixel events – any additional ones will not be used for campaign optimization and reporting due to new restrictions
If clicks/sessions are too low to be differences in attribution models and you’ve checked the tracking issues above, the problem may be traffic loss.
Traffic loss occurs when a user clicks an ad but ultimately does not see the landing page load. The most common drivers for this are dead links in the Facebook ad or long load times. The bounce rate should also be considered in this case.
Manually checking that the landing pages work, by copy-pasting the links from Facebook Ads Manager into the URL bar, or using a bulk link checker, can assess dead links.
Long load times can be assessed by GA page timings or other tools that measure site speed. Although there are differences between user-side and server-side speed, any GA timings (server-side speed) over five to seven seconds may be a traffic loss driver. This is especially true for mobile traffic, where users are much quicker to abandon a page that is slow to load.
As our clients start to use click trackers more frequently, we need to be considerate of traffic loss across the account and accurate reporting. We should be considering bounce rates, session durations and the discrepancy between clicks, landing page views, and how that compares to the analytics reporting available.
The default lookback windows for Facebook and Google Analytics are also slightly different.
By default, the Facebook lookback window for attributing conversions is based on one-day view and seven-day click, which means the reporting table will show these actions if they happened within a day of somebody seeing your ad or within 28 days of someone clicking your ad.
You have the option to edit this lookback window at the ad set level via the “attribution settings”. With the exception of iOS14 app install campaigns, Facebook allows you to change the default lookback window to one of the following:
- One-day click
- Seven-day click
- One-day click and one-day view
- Seven-day click and one-day view (default)
In Google Analytics the default lookback window is 30 days, however this can be modified up to 90 days (which is only necessary when using an attribution model other than last click).
This blog has been last updated March 2021.