The difference in conversion attribution between your marketing platforms

Making decisions based on data is essential in online marketing for optimising marketing strategies. However, tracking isn't as straightforward as it appears, even when you have a Server-Side Tagging For example, different analytical and marketing platforms, such as Meta Ads, Google Ads, TikTok Ads, and Google Analytics, use varying methods to process and analyse data. These variations can lead to discrepancies in reported data, making it challenging for you as a marketer to get a cohesive overview of your marketing performance.

Google Analytics, for example, uses UTM parameters die aan website-URL's worden toegevoegd om de herkomst van bezoekers te traceren. Meta Ads gebruikt daarentegen fbc- en fbp-cookies om te volgen wat gebruikers buiten hun socialemediaplatforms doen. Deze cookies koppelen externe acties aan de advertenties die gebruikers op Facebook of Instagram hebben gezien of waarop hebben geklikt. Hierdoor kan Meta Ads een conversie claimen omdat de fbp-cookie overeenkomt met een bezoeker die een advertentie heeft gezien, terwijl Google Analytics deze conversie toekent aan organisch zoekverkeer. Hoe moet je als marketeer nou weten welk platform je kunt geloven waar een conversie vandaan komt en welk marketingplatform of campagne beter presteert dan de rest als iedereen verschillende rapportages geeft en elk platform dezelfde conversies claimt?

In this article, we delve deeper into the nuances of online platform tracking methods, exploring how these differences can influence data interpretation. Understanding how these systems work and where they vary is crucial for optimising digital marketing efforts and gaining accurate insights into consumer behaviour.

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Attribute pane

An attribution window specifies the period during which a conversion can be attributed to a particular source or campaign. This concept is crucial in the world of online marketing as it determines which interactions and events on one domain (social media platform or search engine) led to the desired actions on another domain (your website or web shop), such as purchases or sign-ups. However, different platforms have different attribution windows, which can lead to differing insights and strategies.

An attribution window means that if a user converts within a specific period after interacting with an ad, that conversion is attributed to that ad. This helps marketers understand which campaigns are effective and which ones aren't. A shorter attribution window may lead to fewer attributed conversions as people often need time to make a decision, while a longer window can capture more conversions but also introduce more noise and less accurate measurements.

Facebook uses a 7-day attribution window for click conversions and an additional 24-hour window for view conversions. This means that if a user clicks on a Facebook ad and visits your webshop, but doesn't make a purchase at that moment, they return to your webshop within 7 days of that initial click and make a purchase. Meta Ads will then count this purchase as a click conversion. However, Google Analytics will see that the user arrived directly on the site during their session when the purchase was made, and therefore will not attribute this conversion to Meta Ads.

When a user who ultimately converts has seen your Facebook ad but not clicked on it, and then opens their browser and navigates directly to your site's URL, Meta Ads will attribute this conversion as a contribution from their ad. However, in Google Analytics, this conversion will be credited to direct traffic; there will be no link whatsoever to Facebook as the source of any of that user's sessions.

For example, let's say a user clicks on a Google Ads campaign but doesn't convert that day. However, five days later, they see a retargeting ad on Facebook and click on it. On this day, the user decides to convert. This conversion will be reported as a click-conversion by both Meta Ads and Google Ads. This will result in duplicate conversions being reported when you, as a marketer, compare the results from multiple platforms.

Understanding these differences and their impact on data interpretation is crucial for marketers. Without this knowledge, decisions based on incomplete or contradictory data can lead to wasted marketing budgets and less effective campaigns. Therefore, it is essential to thoroughly understand both the different attribution windows and their impact on the interpretation of conversion data.

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Attribution date

Another reason for differing conversion rates is how platforms handle the attribution date. The attribution date refers to the specific moment when a conversion is attributed to a particular marketing action. This is a crucial concept, as it determines how marketing performance is measured and analysed. Google Analytics records events on the day the action was performed in the user's time zone. Meta Ads, on the other hand, reports conversions based on the date of the ad click or impression in the time zone of the Facebook ad account. This difference in attribution data leads to discrepancies in reported results between different platforms, primarily for websites and online shops that operate internationally.

Google Analytics also registers multiple sessions if a person visits a site multiple times a day, depending on the time between visits and the source of their visit. Sessions can end in two ways: after 30 minutes of inactivity or at midnight, marking the end of the session period. Additionally, a session also ends when there is a change in the campaign source. For example, if someone clicks on an advert in the morning and visits the website, and then clicks on another advert in the evening and returns to the website, these will be counted as two separate sessions. If a user visits your site at 23:59 via an Instagram advert and converts after midnight, Google Analytics will not attribute this to a paid social campaign from Instagram, whilst Meta Ads will likely claim this conversion.

Understanding these differences in handling an attribution date is crucial because it directly impacts how marketing performance is analysed and interpreted. If you, as a marketer, are not aware that these differences exist, you may draw incorrect conclusions from collected data, leading to faulty analyses of campaigns across different platforms and the development of suspicion regarding the data within Google Analytics. By knowing this way of attributing conversions, you, as a marketer, can make better-informed decisions and explain to your clients why your reports differ from what they may see.

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Recognise users

Different marketing platforms use varying methods to recognise users, which can lead to discrepancies in the interpretation of marketing performance. By user recognition, we mean identifying where a visitor has come from. In other words, the answer to the question of how/via which action the visitor arrived at the site.

Google Analytics uses UTM parameters to recognise users from third parties. These are small pieces of text that you add to a URL to identify the source, medium, and campaign when a user clicks on a hyperlink or campaign with that destination URL. When someone clicks a link with UTM parameters, you pass extra information to that user the moment they land on your site, so that Google Analytics can precisely see where the visitor came from, through which action they arrived on the site, and to which campaign the initiated session can be attributed.

Meta Ads uses fbc and fbp cookies to track users. The fbc cookie records the click ID of a Meta ad and is passed in that user's session. The fbp cookie is not linked to a specific click, but to the user's Meta profile. If you have ever logged into Facebook, Instagram or Whatsapp in your browser, your own fbp cookie will be filled with a specific code that Meta can decipher. Therefore, if it is recorded that a user sees a campaign and then converts on the site, Meta can investigate whether the fbp cookie attached to the conversion event matches all Meta profiles that viewed the campaign.

TikTok Ads uses ttclid cookies to recognise users and measure ad effectiveness. This cookie stores the click ID when a user clicks on a TikTok ad and can attribute all received conversion events to the correct campaigns based on this ID.

E-mail marketing platforms usually recognise users based on their email address. When someone clicks on a link in an email, their email address is used to identify and track them.

For Google Ads, Google uses glcid, wbraid, and gbraid cookies. The gclid cookie is used to track standard clicks on a campaign. The wbraid and gbraid cookies were created after the iOS 14 update to differentiate between web conversions and app conversions.

Understanding these different user recognition methods is crucial as they influence data interpretation. If a user clicks on a Google Ads campaign, a Facebook campaign, and a TikTok campaign within a single day and then converts, that conversion event will be populated with different parameters. Consequently, all marketing platforms will claim to have been responsible for the same conversion. If you then report to your client that Meta Ads led to many conversions, but the client sees in Google Analytics that this is not the case, you will need to be able to explain this discrepancy in your reporting.

When different platforms use different identification methods, the same users can be tracked and reported on in various ways. The platforms themselves also cannot decipher the cookies of other platforms, so they can only see for themselves whether they have accounted for the conversion. This can lead to inconsistencies and misunderstandings about the true impact of marketing campaigns. By understanding how these methods work, marketers can make better-informed decisions and optimise their strategies for more accurate and effective results.

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Problems with firing pixels and scripts

We've all done it: clicked on a Facebook, TikTok, or Google Ads advertisement and closed the window before the site has fully loaded. At that moment, the tracking scripts or pixels haven't loaded yet either. This means that, among other things, the page view and the initiated session aren't measured in your analytics and marketing platforms, but the marketing platforms do count the click. This inconsistency is a major problem for marketers and one of the biggest frustrations in the world of online marketing. Even when you use Server-Side Tagging, thereby bypassing ad blockers and browser tracking prevention, you can still see a difference in the number of campaign clicks and the number of landing page views. With Server-Side Tagging, your tagging pixel loads faster than third-party pixels and scripts, making this a smaller problem, but still, not all misclicks on your ads will be measured.

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Multiple clicks on the same advert

It happens more often than you think that users click on your campaign more than once. For search campaigns of e-commerce webshops, this is mainly a problem because you are dealing with users who are specifically looking for something and want to compare different sites and their offerings. However, it is also a problem on marketing platforms where you display campaigns to users who are not necessarily looking for your product or service, such as Meta or TikTok. When someone clicks on the same campaign twice within half an hour, Meta Ads or TikTok Ads will see this as two campaign clicks and two landing page views, while Google Analytics will, of course, count this as one session. This can lead to deviations in your reports between your marketing platform and your analytical platform regarding user acquisition.

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Strategies for Aligning Facebook and Google Analytics 4 Data

Deviating data will always be a problem, but you can minimise it as much as possible. Failing to understand these differences can lead to making the wrong choices for investing time and money. However, there are ways to bridge the gap between the data from your different platforms.

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Use UTM parameters

Many marketers already use UTM parameters as standard, but if you aren't using them yet, we recommend implementing them straight away for yourself and all your clients. Customising your destination URLs by using UTM parameters is a simple way to create the clearest possible overview of channels in Google Analytics. There are many different ways and tools to create these UTM parameters and add them to your destination URLs. However, we recommend creating them manually via a manual tool and adding them as a complete URL to the destination URL input field.

Let's say you want to use the following landing page URL in your next campaign: www.yourdomainname.nl/landingpage. When you add UTM parameters to this, you will therefore specify the campaign source Facebook use, the campaign medium is then paid social and the campaign name can be invented by you. The final URL will then be www.example.nl/landingpage?utm_source=facebook&utm_medium=paid_social&utm_campaign=campaignname. By adding these UTM parameters to your URL, you can get the clearest possible overview of where your visitors are coming from via Google Analytics. This way, you can better monitor the effectiveness of your campaigns compared across different platforms and understand user behaviour.

To generate UTM parameters yourself as easily as possible, you can Campaign URL builder tool from Google Analytics to use. Here you enter your destination URL and further fill in your source, medium, and campaign name, and your new destination URL with UTM parameters will be automatically generated so you can paste it directly into your campaign.

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Exclude View-Through Conversions

To simplify conversion tracking, it's possible to exclude view-through conversions within the Meta Ads attribution settings. This results in Meta Ads only counting click-through conversions, which can help reduce discrepancies between measured conversions in GA4 and Meta Ads. However, we do not recommend implementing this, as Meta Ads uses view-through conversions to measure the latent needs of your target audience. This hidden need, sparked by seeing ads without clicking on them, would then no longer be measurable. These purchases would then only be attributed to ‘direct’ or ‘organic search’ in GA4, and your Meta Ads campaigns will perform worse than you're used to.

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Follow the steps below to exclude view-through conversions. By adjusting this, only click-through conversions will be visible in your Meta Ads Manager.

1. Open Ad Manager
2. Select the relevant ad set and click ‘Edit’.
3. Go to the ‘Attribution setting’ section.
4. Under ‘View-through’, select the ‘none’ option.’

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Set up Server-Side Tagging as a tracking setup

To minimise the issues with attribution across your various channels and platforms, Server-Side Tagging is the ideal solution. This gives you control over the creation of events and thus the collection of customer journey data. It also bypasses the tracking protection software of browsers like Firefox and Safari, which can block third-party tracking, and circumvents your visitors' ad blockers. As a result, the measured sessions and conversions will be as accurate as possible, allowing you to trust your marketing activities and make the right decisions.

Start creating a Data Deck immediately to find out where the bottleneck is in the current tracking setup of your site or your clients' sites. Or Book a demo directly where one of our tracking experts can explain how Server-Side Tagging can improve your tracking or the tracking of your clients.