conversion tracking higher ed August 21, 2025

When 1+1 = 3…How Ad Platforms Measure Conversions

Conversions are a foundational element of digital marketing. Having said that, they can also be exceptionally confusing. Given this, let’s start at the very beginning.

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Originally published by VisionPoint Marketing, August 21, 2025.

What is a Conversion?

Put simply? Just about anything can be defined as a conversion.

A lead? Absolutely.

An application? Sure!

A click? If you want it to be.

A page view? Even this!

Sometimes the simplest things can be taken for granted. And the simplest way to define a conversion is as a measurable action you’ve decided matters.

Once you know what you want your conversion action to be, you then go through a series of steps involving your various ad platforms, pixels, tags, triggers, and webpages to ensure that the action your action is being tracked appropriately. The details of that process are an entirely different article (I’ll add it to the list!), but if we were making a list of steps you take, it would be:

  1. Define the conversion
  2. Set up the conversion
  3. Track the conversion ← you are here

By the time we get to step three, the assumption is that the two steps before it have already been done, dusted, and QAed – i.e., everything is set up correctly, and now we’re unpacking the data you’re seeing, what it means, and why it might be confusing.

With that preamble out of the way, let’s talk about how conversions are tracked.

Attribution Settings for Conversions

While there are a lot of different conversion-related settings you can manipulate, there are two key overarching components that you need to understand:

  • Attribution settings – these are the settings that define how conversions will be calculated
  • Attribution window – the time frame during which those settings apply.

Attribution Type – Click vs. View

The two most common attribution types we track via ad platforms are view-through and click-through conversions.

  • Click-through conversions: users who clicked on an ad and then converted.
  • View-through conversions: users who saw (but didn’t click) on an ad, and then subsequently converted.

Count Type – Once vs. Multiple

The second attribution setting it’s important to pay attention to is the count type – whether you’re counting conversions per user once or multiple times.

  • Once/First: each user’s conversions are only counted once.
  • Multiple/All: every time a user performs a conversion action, it counts as a conversion.

For example, you’re counting clicks on your webpage as conversions. After arriving at your landing page, a single user jumps around to 10 different pages. If you’re counting once/first conversion, this would be counted as one conversion. If you’re counting multiple/all conversions, this would be counted as 10 conversions.

Attribution Window

The attribution window refers to how much time can pass between an ad having been viewed or clicked on and the conversion action taking place. The most common attribution windows are:

  • 1-day: within a day of the ad having been viewed/clicked.
  • 7-day: within seven days of the ad having been viewed/clicked.
  • 30-day: within 30 days of the ad having been viewed/clicked.

Typically, the window for click-through and view-through conversions are set up independent of each other. This means that there’s a different clock tracking every single impression of your ad that’s been served.

For example, on Google Ads you might have:
Click-through conversion window 30 days
Engaged-view conversion window 3 days
View-through conversion window 1 day

A person who was served your ad but didn’t appear to have engaged with it, a person who watched a portion of your video ad, and a person who clicked on your ad and arrived at your landing page are each being tracked (essentially, they are being followed around the internet courtesy of your pixel) for a different amount of time.

Important: Every Ad Platform Has a Minimum Attribution Window

One of the most crucial things to keep in mind when reviewing conversion data is that the shortest selectable attribution window for clicks or views on most ad platforms is one day. None of the major platforms – Google, Meta, LinkedIn, StackAdapt, TikTok, Snapchat – will give you attribution window options that only track same-session conversions.

This means that the pathway to a conversion looks like this:

Click/View Happens + Conversion Happens Within Appropriate Time Frame ⇒ Attributed Conversion

This also means that there are inevitably a variety of circumstances where an action taken by a user meets the inclusion criteria to be counted as a conversion, but the pathway taken to that conversion will be indirect – which is a nice way of saying really confusing.

What might be confusing about it?

  • A lead conversion may have been attributed to a given campaign, but there are no UTM tags appended to leads in your CRM that reflect that conversion
  • A conversion classified as Direct or Organic in GA4 is also classified as a Google Ads conversion within that platform.
  • A conversion classified as Direct/Organic in GA4 and as a conversion in Google Ads could also be classified as a Meta conversion.

Yes, it’s possible to do nothing wrong during setup and still have one conversion correctly attributed to three different platforms, with no campaign-specific UTMs.

Wild, right? And it’s exactly why conversion numbers should be seen as a source of trends, not a source of truth.

Conversions as a Source of Trends, Not Source of Truth

Attribution settings and windows effectively ensure that you will never have a 1:1 relationship between key events – like RFI or application submissions – and your conversion numbers from different ad platforms.

Instead of spending our time debating whose numbers are “wrong” and whose are “right,” we need to make sure we understand the meaning of “conversion” in the context of how each platform defines it. If we don’t, we risk:

  • Over/under-counting results, which can skew ROI.
  • Over/under-valuing real performers, adjusting spend toward or away from the wrong channels.
  • Misreading trends, chasing patterns that are really quirks of attribution windows.

The good news is that once we understand the nuances of conversions, we can analyze our data in ways that work with each platform’s attribution settings and windows.

To do so, it’s important to:

  1. Document the attribution settings and windows you’re using for every platform (or campaign, if you use different settings on the same platform).
  2. Cross-check your platform data with data from other analytics sources like GA4 and your CRM.
  3. Focus on patterns over time instead of one-off platform numbers.

In this post, we focused on the rules each platform uses to count conversions. But counting is only part of the story - how a conversion actually happens can be just as important. Next time, we’ll unpack the nuance of view-throughs, assisted conversions, and the winding paths people take before they finally convert.