“Why is there such a big difference between our sales from Facebook on Facebook Ads versus our sales shown on Google Analytics?” “GDN and Discovery are spending so much money and hardly providing sales; why are we throwing money down the drain?”If you are a digital advertising manager, chances are you’ve heard these questions more times than you can count but probably not more than the number of times you’ll hear the word “attribution” as an answer to those questions.
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What Is An Attribution Model?
If you’re new to the digital advertising world, an attribution model is a specific structure each advertising channel follows to assign a conversion (a purchase, lead, or whatever a business deems as valuable) from one platform to another. It also determines the contribution of the said platform versus another when several are present in the conversion path, or in other words, which touchpoints, or marketing channels, receive credit for a conversion.
Google Analytics Vs. Facebook Ads Attribution
Focusing on one of the main challenges digital marketers face today in eCommerce, here are a few tips on how you can navigate your client (and yourself) through cross-platform attribution challenges.
Google Analytics Vs. Facebook Ads attributions are the two largest digital juggernauts in the world, often referred to as “the duopoly,” battling it out for who gets credit for businesses’ results and advertising budgets, Impression-based Vs. Click-based, Push Vs. Pull, etc. Commonly, clients will complain about the differences in results between what they see in Google Analytics and Facebook Ads manager.
Facebook attribution, especially when looking at remarketing-based campaigns, presents significantly better results in its campaigns than Google Analytics, which will consistently show a lower number of transactions and revenue coming from Facebook Ads. In turn, this sometimes leads clients to rethink their digital strategy and unjustifiably re-allocate budgets between platforms.
What Creates This Difference & Which is Actually Correct?
Data collected by Google Analytics and Facebook’s Pixel will always differ because they collect data differently. While there are many differences between the platforms, we want to focus on how to convey this concept best to a client so they do not miss out on opportunities. The clearest difference between the two is that the Google Analytics attribution model is a cookie-based, last-click attribution model, while Facebook uses a user-based impression attribution model.
So while Facebook will give value and assign conversions based on users seeing and clicking on its ads, Google Analytics doesn’t recognize or even track Facebook’s impression-based conversion.
So while Facebook will give value and assign conversions based on users seeing and clicking on its ads, Google Analytics doesn’t recognize or even track Facebook’s impression-based conversion. This is a big problem considering Facebook is, in fact, a “Discovery” platform that people come to not necessarily as searchers (which is associated with click-based behavior). Therefore, their conversions following interactions with the platform’s ads will be impression-based and not click-based. It’s kind of like ignoring the concept of zero gravity and saying that people are simply slower on the moon than on earth.
On the other hand, Facebook’s attribution model has been widely considered over-generous because it is not a multichannel platform. As such, Facebook does not take into consideration other channels that were on the conversion path. So even if the user had more digital touchpoints on other channels leading to the final conversion, Facebook attributes all of the conversion to itself. Add this to the fact that Facebook’s attribution model’s conversion window is very wide (28 days click & 1-day view), and you get a closed system giving a lot of credit to semi-window shopping behavior.
So between Google Analytics Vs. Facebook Ads attributions, which are actually giving you the right information? Like many discussions, just because two sides are different doesn’t mean one side is necessarily right or wrong; the truth is somewhere in the middle. This is the basis of what your client needs to understand when considering how to analyze results and make decisions despite the discrepancies between the two channels’ results.
Tips To Help Your Client Navigate Their Digital Strategy
So now we understand what attribution model discrepancies are and why each platform is both right and wrong. After your clients have also understood this concept, we need to figure out how to help them to prioritize between the two. Here are some valuable tips and tools:
Look into Google Analytics’ multi-channel conversion report to learn more about assisted conversions and popular conversion paths.
Try to create an agreed-upon formula with your clients which balances what you see in Google Analytics and Facebook ads.
For example, take the Facebook Ads conversions presented on Google Analytics (don’t forget to add the correct source/medium UTMs to your Facebook Ads!), then add another 35% of the conversions reported on Facebook Ads to that number and top it off with another 60% of the assisted conversions associated to Facebook Ads, as presented on Google Ads.
Leverage as much purchase data as you can get from your client’s back-end and CRM to learn as much as you can about purchase trends and customer behavior so you can attempt to create a client-specific model.
Try time-limited tests in which you lower or stop your activity on Facebook and see how this affects conversion volume. We suggest you do this when no special promotions or holidays are coming up and, of course, to avoid any other changes to your digital presence.