Measuring and maximising conversions is the foundation of performance-based marketing. Marketers invest in various ad and business intelligence platforms that allow them to keep track of their conversion data.
The problem with ad platforms is that it only has access to a limited amount of information. Two of the biggest online ad platforms, Google and Facebook, offer trivial insights on different web traffic sources (they don’t even count non-web-based traffic, like email).
Marketers need access to built-in attribution tools for ad conversion reports to be insightful enough to actually advance marketing strategies.
Attribution tools go beyond the simplicity of these platforms and give an all-inclusive picture of different traffic sources. Every ad platform has its unique built-out attribution structure that records purchases and leads. This helps pinpoint the results attributable to specific ads so the marketer can accurately assess ad performance. Both Facebook Ad Manager and Google Analytics offer inbuilt attribution tools — though Facebook now has a new standalone tool, “Attribution”, which works separately to Facebook Analytics and Facebook Ads.
At its core, attribution models evaluate every customer touchpoint to allow you to determine the specific marketing channels that contribute to each sale.
Although attribution basics are easy to grasp, managing different platforms and analytics can make it difficult to gain clarity on key metrics. Each platform utilises distinct metrics, and each is supplemented by different tools, media, and KPIs.
In this post, you'll get a comprehensive outlook regarding conversion tracking, particularly for Google Analytics and Facebook Attribution.
Google Analytics and Facebook Analytics sessions are alike if they have been set accurately in the tagging system. A problem arises, however, when it comes to their campaign conversions and campaign attributions.
When it comes to conversions, both platforms have similar triggers. However, both platforms utilise different models to trace conversions. As a result, you do not get the same figures on these platforms.
To figure out the true source, you first need to get a basic understanding of how conversions are being tracked.
At the most simple level, tracking within google is session-oriented (cookie-based), whereas Facebook is pixel oriented (people-based).
Since these systems function by default and track differently, we can start to see why the tracking data doesn't fairly match up. Let's get into the details for each platform:
There are two types of Facebook attribution:
When someone clicks on an ad and completes any action, it is known as click-through attribution. However, if a user only views the ad—Facebook will count it as an impression.
Alternatively, when a user doesn't click but takes action within the standard attribution window, it is a view-through attribution.
Facebook takes the last-touch attribution model approach by default and does not report the traffic source that initially landed the user on the Facebook ad. So, if a Facebook ad was interacted with or clicked by a user, Facebook takes the credit.
Due to the last-touch attribution approach and the lack of an alternative, Facebook can count conversions that other conversion analytics platforms may not acknowledge.
By default, Google Analytics uses the last interaction or the last click model that tracks where the user came from before driving the conversion.
Google Analytics features a slower process and a lower conversion rate than Facebook's Attribution platform. A few key reasons behind the low conversion rate on Google Analytics are:
· It gives full credit to the last click irrespective of the channel
· It cannot measure Facebook's view-through conversions
· It cannot track conversions across multiple devices
Assume a person clicks on a concert ad run by Facebook that directs them to a website, but they don't purchase the tickets. The very next day, the same individual decides to go for it and googles the concert details and buys the tickets.
In this case, if the user ends up on the same website to buy the concert tickets through search results, Facebook takes credit for the sale. However, Google Analytics only considers the last click (such transactions are therefore attributed to the organic channel), so Facebook doesn't get credited with a conversion on their platform.
Conversion insights give you a better idea of user interaction and engagement among various platforms and how they work together to achieve an intended result. The use case for attribution is that it helps figure out how to optimise your ad spend. When it comes down to it, Google and Facebook need to be compared to gauge which platform provides the highest return. But the main question is - how do these platforms track conversions?
Let's delve deeper into the disparity between Google Analytics’ and Facebook Attribution’s conversion data.
Google's standard attribution model is the Last-Click or Last Non-Direct Click attribution model. This model works by giving the full credit for a conversion to the origin source of the last click immediately before the conversion.
That is, reporting based on Google Analytics only gives credit to the very last ad or channel link that a user may have visited before directing to your website.
On the other hand, Facebook attributes its own platform for all conversions from viewers of the ad. This default attribution model is the major reason for the disparity between Google and Facebook attribution data.
Google Analytics is unable to recognise and monitor Facebook's impression-based or view-through conversions, as there is no way to do so.
Facebook's default attribution window is post-click (28 days) and post view (1 day). This means that any user who views an ad on Facebook but doesn't click on it within the given timeframe on Facebook is considered a conversion which is not the same for Google Analytics.
Therefore, with Facebook reporting, you need to take into account the post-click conversions if you want to get better and accurate numbers.
Facebook has the capacity to track the activities of users across multiple devices, i.e. phone, tablet, and desktop. In practice, this means you can monitor, target, and reach the same user on their different devices and browsers as long as they remain logged in to their Facebook accounts.
This is an advanced feature that allows Facebook to associate and gauge individual user actions on multiple platforms that drive conversions.
Meanwhile, Google Analytics is unable to track cross-device conversions and relies on cookies. This confines Google's tracking ability within the same browser and platform where the cookie was dropped.
Google Analytics also has certain limitations when it comes to recognising users' data when they are not signed in from a Chrome browser which makes it difficult to keep track of cross-device conversions.
With an increased emphasis on optimising marketing conversions, it is critical for marketers to comprehend the attribution models and data discrepancies between Google Analytics and Facebook Attribution.
In this way, marketers can effectively pick on the right approach, set audience targeting, and implement it successfully, ultimately driving conversions. The attribution data is gathered differently from both platforms, and you need to assess what works best for your business model.
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