Data Differences Between Facebook And Google Analytics

Why the Data Between Facebook and Google Analytics Don’t Match

Every digital marketer understands that the ability to track the performance of campaigns is crucial to the maximization of success. The issue, however, is that Facebook data would never match with Google Analytics data and a lot of business executives find this worrying.

In case you are wondering why this is so, then don’t worry, we’ve explained some of the most popular reasons why it happens so, but before we delve into them, let’s look at the basics.

How to Track Conversion?

Use Google UTM Tags on Your Facebook Ads

In order to be successful at tracking your Facebook traffic with the use of Google analytics, there’s the need for you to incorporate the use of Google UTM tracking.

During the process of setting up your UTM tracking, it is important that you correctly fill the fields for source and medium.

Now that we’ve gotten grabs on how to begin to track traffic let’s now talk about the reasons for the worrying discrepancies that often occur between Facebook data and Google analytics

Cross-Device Tracking

In our time, people have gotten so used to combining multiple devices that it will be difficult to complete a purchase journey without having to touch different points, and this certainly means the use of various devices.

Take this illustration as an example: assume while out with a friend, you discovered that you need a particular product and begin to browse through a commerce site on your mobile phone. You add to cart but don’t complete purchase eventually before leaving the meeting with your friend. Later in the day, while at home, you are fondling through your computer, then a notification pops up, reminding you of the cart you had abandoned. You jump on the site and complete purchase, using your desktop. Google analytics, instead of attributing conversion back to the initial click that happened on a mobile phone, would instead attribute conversion entirely to the desktop, therefore underreporting results.

This is quite a different case scenario with Facebook as it has a unique ability to track conversions back to users, instead of the usual cookies. What this means is that while calculating conversion, you can track each conversion across multiple devices used by the buyer, if they are logged into their Facebook account. Hence, by comparison, you can rightly conclude that Google analytics tens to rely on cookies for reporting conversion, meaning that it interprets all tracking to take place only on the browser where the cookie was dropped.

There is a possibility to make the difference in data as small as possible. Within Google Analytics there is a possibility to set the Google Analytics User ID. This advanced setting within Google Analytics ensures that you can follow your users on your websites who log in in various devices (like Facebook does). This YouTube video from Google Analytics itself explains you more about how you can set this within GA.

Impressions and Clicks

This is one other primary reason behind the discrepancies that are often reported between Facebook data and Google analytics, and it is not so hard to see why.

Like we discussed in the first point, Google Analytics relies on cookies when tracking users across a website, instead of tracking impressions as is typically done on Facebook. This means that when using google analytics, you would find it impossible to track users when their cookies are disabled for any reasons.

Of course, with Google analytics conversion is recorded when a user clicks on the link from whatever source it is coming from. With Facebook, on the other hand, a user would be tracked as a conversion when they convert, and not when they click on the link.

It is worthy of note that all data remains in Google analytics, even after a user clears their cookies, while the data gets cleared from custom audiences when Facebook is being used. It is also important that we state clearly here that Google Analytics has an ability to backdate data, unlike Facebook, that collects data from the day an audience gets setup.

UTM Parameters

Before now, did you have the slightest idea that tracking providers like Google analytics are credited with using the URLs of the referrer to credit conversions back to ads? This means that in most cases, Facebook conversion ends up being underreported by up to 40%. You may be asking the reason for this. Well, it has been reported that about 40% of people that log into Facebook daily do so using https instead of HTTP. So, the problem arises when a user clicks on a Facebook ad and converts from the resulting site. Usually, it is difficult for Google Analytics to record the referrer since the user migrated from an https environment to a HTTP environment. This is one of the primary reasons why Google analytics and most other providers end up underreporting conversions to Facebook ads.

In a not too distinct case scenario, if a user opens a new tab while at work, but delays purchase on the same site until they are home from work, then there’s a huge probability that the referrer URL will no longer be there. The analytic tool uses this criterion to consider the sale as a brand-new user, instead of attributing it to Facebook.

Clicks vs. Sessions

Over time, this one has always proven to be a hard nut for marketers to crack.

You’ll often see marketers complaining or asking why their clicks on Facebook doesn’t always seem to match with the sessions reported in reports by Google analytics. If you fall into this category of marketers, then you may want to pay attention to the reasons why.

The truth is that there are quite several reasons why this discrepancy happens most of the time.

Take, for instance, if a user clicks your Facebook post multiple times or at least twice within a thirty-minute window, the whole session is tracked as one session by Google Analytics, irrespective of the number of times it is. Facebook, on the other hand, reports this as more than one click, and that is why you would often see once Google analytic session being reported as two or three Facebook clicks.

As another instance, assume that a user clicks on your Facebook post, then visits your website, but gets distracted by another activity that keeps them inactive for about 30 minutes or more. If the same user gets back to what they were doing on your site after 30 minutes of being inactive, Google analytics will record it as two different sessions. Facebook, on the other hand, would report just a single click.  Unlike the previous case, one Facebook click here equals to two Google analytic sessions.

In all these, if a user clicks accidentally on your Facebook ad, but goes off it immediately, Google Analytics would most probably not record this, considering that you jumped off even before the page fully loaded.

Difference in attribution

To understand the data, it is important that the conversions are attributed in the right way. Both Google Analytics and Facebook using a different way to attribute conversions while Facebook also records view-through conversions. These are the conversions that were realized after someone saw an ad but did not clicked on it.

We first ave to understand how Google Analytics handles this issue. As we already told Google Analytics uses the attribution model by default: indirect last click. The conversion is so to speak attributed to the last channel that the user brought into the website before it made a conversion. In this way the “direct” channel is excluded and GA is only recording the click-through conversion. While Google Analytics can’t determine whether someone has seen an ad view-through conversions aren’t counted.

Facebook on the other hand handles this differently. Facebook uses some sort of linear model where they allocate the conversion when someone has interacted with the Facebook ad (share, comments, like or click) or has seen the Facebook ad. This has set by default to 28 days after the click (click through conversions) or 24 hours after the display of the advertisement (view-through conversion). This can also be the reason why it is important to report 28 after the period is done.

This can be explained best by an example. Through Google a user searches for your product and ends up on your website through an organic search. The user must think about the product so it doesn’t convert at that time. After this he is retargeted by a Facebook ad, click on it and enters the website again through Facebook. He is still not converting while he has to think about the purchase another day. Again, the user searches for this product through Google within 28 days and he is served with a Google text ad. He clicks on the ad and now he is convinced of his purchase and buys it. As you understand Google Analytics is attributed the conversion to Paid Search and attributes Facebook with a supporting conversion. When you compare this with Facebook, they claim the conversion as well while the user has interacted with the Facebook ad as well.

There is a way though to minimize this difference in attribution. You can change a setting within Facebook ad management to exclude view-through conversions. You can do this by the ad management and click on “adjust columns” in the overview under “columns”. In the window that opens you can click on “compare time windows” in the bottom right corner. Uncheck the option “add standard time window for assigning actions” and select “28 days” under “click”. Now you can see that the attributed conversions are down due to this adjustment and that the data is already better aligned with Google Analytics.

Multiple Conversions

It is also essential that we talk about this one because it happens almost all the time. Google analytics only works on a one-per-click attribution basis, and this means that only one conversion would be counted irrespective of the number of conversions that took place. Take, for instance, if a user clicks on an ad more than once, Facebook attributes the multiple conversion that has happened to the last ad clicked.

The Wrong Page is Set as Conversion Page

One other reason why Facebook might report a greater number of conversion than Google analytics could be as a result of the placement of Facebook pixel in the wrong conversion page. Ironically, this is one case that happens a lot of times because digital marketers subconsciously do these things. Facebook isn’t wired to automatically know what conversion exactly means for your business, hence, the need to spell it out exactly for Facebook. The bad side of this is that with the inaccurate definition from you comes a corresponding report of inaccurate results.

Over the years, one common mistake that we’ve seen digital marketers make repeatedly is the placement of the pixel on the sales landing page. Knowing that this is a page that your ad would refer users to, you want to be careful about what happens there to ensure that clicks lead to conversion. However, in any case, where the user visits this page but doesn’t convert, there’s a need for you to know. To accurately track the conversion gotten from your campaign, there’s the need to put the pixel on the page that users would be referred to upon competing conversions. In most websites, this page is usually a “Thank you for your purchase” or “Thank you for signing up” page.

From researches and experience, we’ve found that these are the most common causes of the discrepancies that digital marketers notice between Facebook data and data gotten from Google analytics.

A few more reasons that we’ve found include:

  • Loading a page from the cache
  • Users being located in places of distinct time zones
  • Visitors of certain data filters.
  • Ad blockers

After all this information now, the question that’s probably lurking in your mind now is which is right? Facebook data or Google Analytics data?

The truth is that it is not a matter of which is right, or which is more accurate than the other. Instead, it is a matter of being aware of the different tracking methods and how each of them is being used.

Keep all the reasons that we’ve mentioned above in mind and adjust your report accordingly.

Making Use of Facebook and Google Analytics For Creation of Integrated Report

Indeed, the effective combination of data gotten from Google analytics and Facebook into one marketing report (either manually or with the help of report automation software) would help for the coverage of all the bases that need coverage during strategic decision-making processes. It also helps you as a marketer to prove to your management team that your efforts are yielding results.

In order to create an integrated report that would work for all these uses, these tips should be followed as closely as possible:

  • Select the right metrics to use in reporting, based on the organizational goals, and get them as well organized as possible. Many online guides can help you through this face, but you can more specifically check some of the previous articles that we’ve worked on concerning this topic on our site to get tips that can help you navigate through this stage successfully.
  • When faced with a case of duplicate metrics (for example, total conversion as it is reported by Google Analytics and complete conversion as Facebook reports it); a marketer should be able to fashion out how to report both metrics on a side by side basis. He should clearly identify them as Facebook data and Google data for easy understanding when non-marketing-oriented members of the management team goes through it. Those metrics should be followed up by their average values and every other information that is deemed fit.
  • Include notes to explain the differences that may occur between similar metrics. In clear terms, you should be able to explain all differences that occur between metrics that follow the same pattern. For example, take note of the specific type of Facebook conversions that you are reporting (Only click-through, or view-through and click-through). Also, take note of the kind of Google conversions (click-through).
  • Additionally, apart from including relevant notes to explain your metrics, you can also add detailed commentary, explaining the meaning of each commentary. Try to signify the data point that shows success, which shows failure, and which is averaged okay. Also, point out data points that prove the effectiveness of your work.

On a final note, while in the process of presenting your report to the organization, bear all the differences between Facebook data and Google analytic data in mind, so that you can provide the management team with all that’s needed to help them see the bigger analytic pictures. If they can see and understand the big picture, then you would be able to communicate more easily with them what’s working and what’s not.

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