Difference in conversion attribution between marketing platforms explained

Data-Driven Decision-Making in Online Marketing

Basing your marketing decisions on reliable data is crucial for refining online marketing strategies.

Yet, even when you utilize a Server-Side Tagging setup, accurate tracking can be more complicated than it first appears. Different analytics and marketing platforms, such as Meta Ads, Google Ads, TikTok Ads, and Google Analytics, each process and interpret data using their own methods.

Because of these distinct processes, you may notice inconsistencies across platforms, making it hard to form a clear, unified picture of your marketing performance.

For instance, Google Analytics relies on UTM parameters added to website URLs to identify where visitors originated. In contrast, Meta Ads uses the fbc and fbp cookies to monitor actions taken outside of Facebook or Instagram.

These cookies link a user’s off-platform activity to the ads they have viewed or clicked.

Meta Ads may recognize a purchase and attribute it to its platform based on the fbp cookie, even though Google Analytics might categorize the same conversion as organic search traffic.

As a marketer, you might wonder which data is correct and how to determine which platform or campaign is performing best, given that every platform seems to report conversions differently and may claim the same sale.

This article delves deeper into the nuances of tracking approaches across various online platforms. We will examine how these differences can affect data interpretation and why understanding them is vital to optimizing your digital marketing campaigns and accurately assessing consumer behavior.

Attribution Window

An attribution window specifies the time frame in which a conversion can be credited to a particular source or campaign. This concept is vital in online marketing because it shows which interactions on one domain (e.g., a social media platform or search engine) lead to actions on another (like your website or online store).

Different platforms use different attribution windows, so the data they report, and the insights you draw, can vary considerably.

When a user converts within a specific period after seeing or clicking on an ad, that action is attributed to the ad. Shorter windows may result in fewer attributed conversions, as many consumers take more time before making a decision.

Longer windows can capture more conversions but may also introduce additional noise and less precise measurements.

For example, Facebook (via Meta Ads) typically uses a 7-day attribution window for clicks, plus an extra 24-hour window for view-through conversions. This means if a user clicks a Facebook ad, visits the online store, and purchases within seven days, Meta Ads will count that purchase as a click conversion.

However, Google Analytics sees the user returning directly to the site and logs the transaction under direct traffic instead of attributing it to Meta Ads.

Similarly, if a user sees your Facebook ad (without clicking) and later types your website’s URL directly into the browser, Meta Ads would claim that purchase as a view-through conversion, while Google Analytics would label it as direct traffic, having no record that Facebook influenced the sale.

Consider a scenario where a user clicks on a Google Ads campaign but doesn’t convert immediately.

Five days later, they click on a retargeting ad on Facebook and make a purchase that same day. Both Meta Ads and Google Ads will register that conversion as click-based, leading to double counting if you compare both platforms’ reports.

Understanding these differences is crucial.

If marketers overlook them, they risk making decisions based on fragmented or contradictory data, which could waste marketing budget and yield less impactful campaigns. Being aware of how attribution windows function in various platforms helps you interpret conversion data more reliably.

Attribution Date

Another factor behind inconsistent conversion figures is how different platforms treat the attribution date, i.e. the exact date on which a platform assigns a conversion to a marketing action. This concept greatly influences how you measure and analyze performance.

Google Analytics logs events on the actual day (in the user’s time zone) the action took place.

Meta Ads, however, typically reports conversions on the date of the ad click or view, using the time zone set in the Facebook ad account.

This discrepancy can lead to further mismatched results, particularly for websites operating internationally.

Additionally, Google Analytics counts separate sessions if a user returns to the site multiple times in a single day, depending on inactivity periods (30 minutes) or hitting midnight, which resets sessions for a new day. A session also ends when a campaign source changes.

For instance, if a user clicks on your ad in the morning and then clicks another ad in the evening, Google Analytics will count two sessions. And if a user clicks an ad on Instagram at 11:59 p.m. and then completes the purchase just after midnight, Google Analytics won’t attribute the sale to the Instagram paid social campaign, even though Meta Ads would include it.

Being aware of these differences in attribution date handling is crucial to avoiding inaccurate conclusions.

Marketers who aren’t informed about these nuances may draw the wrong inferences, potentially distrusting Google Analytics data or making poorly informed campaign decisions.

With an understanding of each platform’s attribution date rules, you can make clearer, data-driven recommendations and better explain reporting variances to clients.

Recognizing Users

Each marketing platform uses its own system to recognize or identify users, which can lead to differences in reported performance. Identifying visitors means pinpointing the channel or campaign that sent them to your site.

• Google Analytics uses UTM parameters, tracking tags appended to URLs that indicate the source, medium, and campaign. When someone clicks such a link, Google Analytics uses these parameters to record how the visitor arrived and which campaign prompted their session.

• Meta Ads relies on fbc and fbp cookies. The fbc cookie stores a Meta ad click ID, while the fbp cookie is linked to a user’s Meta profile.

  
  

  Whenever someone who is logged into Facebook, Instagram, or WhatsApp in their browser views an ad and then converts on your site, Meta can match the fbp cookie with the profile that was shown the ad.

• TikTok Ads uses ttclid cookies to track users and evaluate ad performance. This cookie logs the click ID whenever someone clicks on a TikTok ad, and any conversions reported can then be tied to that campaign ID.

• Email marketing platforms often track users based on email addresses. If a subscriber clicks a link in an email, their email address can be used for tracking that session.

• Google Ads implements gclid, wbraid, and gbraid cookies for tracking. The gclid is used for standard campaign clicks, while wbraid and gbraid were introduced to handle some of the changes prompted by iOS 14, distinguishing web conversions from app conversions.

Understanding these varied identification methods is crucial for interpreting data. Suppose a single user clicks on one Google Ads campaign, one Facebook ad, and one TikTok ad all in the same day before converting.

Each platform’s parameters or cookies will claim that conversion. Without recognizing how these systems work, your clients may see discrepancies and question which platform truly “drove” the sale.

By explaining the mechanics, you can clarify why each platform might appear to have generated the same conversion.

Multiple Clicks on the Same Ad

Users frequently click the same campaign more than once, this happens a lot for search campaigns in eCommerce, where individuals may be specifically looking for a product and comparing various sites and offers.

It also occurs on platforms like Meta or TikTok, where you might serve ads to users who aren’t actively searching for your product or service, but end up clicking your ad multiple times within a short period.

From Meta Ads’ or TikTok Ads’ perspective, two clicks on the same campaign within a half-hour mean two recorded clicks and two landing page views. By contrast, Google Analytics will often lump these actions into a single session.

Consequently, your marketing platform might report more clicks or views than Google Analytics shows sessions.

Problems with Firing Pixels and Scripts

Most of us have clicked on a Facebook, TikTok, or Google Ads campaign, then closed the site before it fully loaded. In these moments, the tracking pixel or script may never fire, so the visit isn’t counted in Google Analytics, Meta Ads, or any other platform, even though the ad platform logs the initial click.

This gap in tracking leads to inconsistencies and frustrates marketers.

Even with a Server-Side Tagging setup, which circumvents many browser tracking blocks and ad blockers by firing the tag faster than third-party scripts, some users will still abandon the page before it fully loads.

That means your marketing platform counts the ad click while your analytics program misses the session. Server-Side Tagging reduces the likelihood of missed data, but it can’t completely eliminate instances where users quickly bounce away from the page.

Strategies to Align Facebook and Google Analytics 4 Data

It’s inevitable that some data will always differ between platforms, but there are steps you can take to narrow the gap. Understanding these differences will help you make wiser decisions about budget allocation and performance tracking. Here are some strategies:

1. Use UTM Parameters

Although many marketers already employ UTM parameters, it’s important to emphasize their value. By customizing your destination URLs with UTM tags, you make it easier for Google Analytics to categorize your site traffic.

Generating these links can be done through Google’s Campaign URL Builder or other tools, or even by hand.

For example, if your base URL is:

www.yourdomain.com/pagetitle

you might add:

utm_source={{site_source_name}}&utm_medium=cpc&utm_campaign={{campaign.name}}&utm_campaign_id={{campaign.id}}

to track source, medium, and campaign in Google Analytics. This helps you compare campaign performance across different channels more reliably and lets you see how users behave once they arrive on your site.

2. Exclude View-Through Conversions

If you wish to simplify tracking in Meta Ads, you have the option to exclude view-through conversions (i.e., conversions attributed to someone merely seeing your ad). This choice can reduce the discrepancies between GA4 and Meta Ads.

However, keep in mind that you’ll lose insights into any sales driven by your ads being viewed but not clicked. Those conversions will instead appear in GA4 as “direct” or “organic search,” possibly making Meta Ads campaigns seem less effective than they truly are.

If you still want to exclude view-through conversions in Meta Ads:

1. Go to Ads Manager

2. Select the relevant ad set and click Edit

3. Find the Attribution Setting section

4. Under “View-Through,” select none

3. Implement Server-Side Tagging

For minimizing attribution inconsistencies across platforms, Server-Side Tagging is an excellent approach. It allows you to control and structure event tracking, bypass many ad blockers, and neutralize certain browser tracking restrictions.

This leads to more accurate tracking of sessions and conversions, letting you have greater trust in the data you use to make marketing decisions.