Can someone explain how conversion data be missing or partial in my case?
I started an ad campaign where I want users to sign up for my app/tool.
The ad itself, when clicked, sends users to a
/sign-uppage. The conversion I’m tracking I labeled asCompleteRegistrationand is set to when a user goes to our/onboardingpage (the page they’ll go to after they sign-up).When I look to check the stats of my campaign, I’m getting this message when I hover over my
CompleteRegistrationstat:“These results may not include all conversion data. Statistical modeling may be used to provide more complete measurement when conversion data may be missing or partial”.
I figured what I made a conversion was pretty easy to track so I’m confused how data can ever be missing or partial. How can it be missing or partial in my case? Is this even something I need to worry about.
The short answer is:
The missing or partial conversion data is likely due to platform restrictions on browser-side tracking, such as Apple’s Intelligent Tracking Prevention (ITP) on Safari, or users actively blocking cookies and tracking with browser settings or extensions.
These measures prevent your ad platform’s tracking script from reliably recording the conversion when the user lands on the /onboarding page.
To get a more complete and accurate picture of your conversions, you need to implement server-side tracking using the platform’s Conversions API.
This involves sending conversion data directly from your server to the ad platform, bypassing the browser-based limitations.
A common and cost-effective method is to use Google Tag Manager (GTM) with a server-side container, often hosted affordably via a service like Stape or your own Google Cloud Platform (GCP) setup, to relay the conversion event, such as a CompleteRegistration, securely and reliably.
The long answer is:
The issue you’re seeing is a direct result of the ongoing shift toward increased privacy protections that limit the effectiveness of browser-based tracking.
Your current setup relies on a piece of JavaScript code (a pixel) placed on your website that fires when a user reaches the /onboarding page.
This is called client-side or browser-side tracking.
However, modern browsers like Safari (with ITP) and Firefox, as well as browser extensions and privacy settings used by many users, actively restrict third-party cookies and shorten the lifespan of first-party cookies, which are essential for your ad platform’s pixel to reliably attribute the conversion back to the ad click.
When a user clicks your ad, but their browser deletes the tracking cookie before they complete the sign-up and land on /onboarding, the platform’s pixel on that final page has no way to link the conversion back to the original ad click, resulting in missing or partial data.
The “Statistical modeling” is the platform’s attempt to fill these gaps by estimating the true conversion count, but it’s an estimate, not a true measurement.
To solve this, you should implement server-side tracking, which involves using a Conversions API like the one provided by Meta (Facebook) or Google.
This API allows you to send the conversion event data directly from your server to the ad platform’s server, essentially bypassing the privacy restrictions in the user’s browser.
A robust and cheap way to set this up is to use Google Tag Manager’s server-side container.
You would use your website’s GTM (client-side) to collect the user’s information and conversion event, and then pass it to your server-side GTM container.
This container then processes the data and securely forwards a server-to-server CompleteRegistration event to the ad platform’s Conversions API.
Hosting this server-side GTM container on a service like Stape or your own Google Cloud Platform (GCP) account is an excellent and cheap solution.
Stape offers a ready-made, managed service specifically for GTM server-side containers, often with a generous free tier or very low cost for small to medium traffic volumes.
Using GCP gives you ultimate control and is also very cheap to run for low traffic, only charging you for the actual resources used.
This method significantly improves data accuracy and completeness because the conversion is reported directly from your controlled server environment, overcoming the limitations of the user’s browser and reducing your reliance on statistical modeling.
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