Liudmyla Kharchenko
AuthorAttribution tracking is the process of following a customer's journey and giving credit to the key actions or touchpoints that lead to their decision to convert or take action. In this article, we’ll explore the importance of attribution tracking and making the most of it with Stape.
Attribution tracking is a method used to understand how customers interact with a brand across different touchpoints before making a decision, such as making a purchase or signing up for a service. These touchpoints can include website visits, social media interactions, email clicks, online ads, or even offline experiences. Marketers follow users across their journey by attributing value to specific touchpoints. A single user’s journey to conversion could be unique, but the picture gets clear when you combine large amounts of data from different user journeys. With proper attribution tracking, you can discover what channels work best, what marketing efforts bring better results, and what places could use some (or more) improvement.
Without accurate attribution tracking, you're missing insights and wasting budget with no clear direction. While some of your efforts might eventually pay off, what about the missed opportunities from steering your resources in the wrong direction?
Tracking attribution helps you focus on what truly works, ensuring that you’re investing wisely and not ignoring anything important.
Instead of trying to figure out what made your campaign successful every time you analyze one, you can set up accurate attribution and get all the insights you need about each touchpoint. Attribution takes much of the guesswork out of the process, helping you get to the sense of it all faster. In other words, attribution guides what went well, what should be improved, and what should be left out in your marketing efforts.
Attribution conversion tracking can be implemented in many ways. Before we discuss attribution models and how they assign credit for conversions, it’s important to understand how the mechanics of attribution tracking work.
There are tools, methods, and technologies behind attribution tracking, so let’s examine them more closely.
Pixel-based tracking relies on small pieces of code embedded on web pages to monitor user actions. Pixel-based tracking is implemented with the help of Meta Pixel, Google Ads tag, LinkedIn Insight Tag, etc. This method is great for tracking conversions, retargeting, and audience building.
On the other hand, UTM parameters are URL tags that help track traffic sources and campaign performance. To use this method, you have to add structured parameters to your link. You can do it with the help of link generators in ad platforms. This method is great for tracking which marketing efforts (social posts, emails, ads) drive traffic or conversions.
Online tracking is pretty straightforward, since digital actions can be recorded quickly. Offline actions, like in-store purchases, calls, word-of-mouth referrals, and in-store interactions that did not lead to purchases, are more complex to track.
To match offline actions with online ones, marketers use CRM systems, call tracking software, and other tracking tools that can help them fill in the gaps in the customer story.
Different advertising platforms have tracking systems and rules to assign value to interactions. Based on the platform you use, you need to fully understand how it tracks user behavior and how the attribution models differ. This way, you will be able to get consistent and accurate reporting. For example, Google Ads might credit a conversion to the last ad clicked, while Meta Pixel might attribute it to the first point of contact.
Marketing attribution works based on models.
Attribution models determine which touchpoints or channels deserve credit for a conversion. An attribution model is a set of rules for analyzing this. In Google Analytics, there are seven key attribution models:
Let’s take a closer look at each of them.
First Interaction
All credit goes to the first ad the user clicked.
Example: A user clicks a banner ad, but doesn’t book. One week later, they click an Instagram ad and book. The banner ad gets all the credit.
Last Interaction
All credit goes to the last ad before the booking.
Example: A user sees and clicks a banner ad but doesn’t book anything. A week later, they click an Instagram ad and make a booking. The Instagram ad receives all the credit for the conversion, even though the banner ad played a role in initially driving interest.
Last Non-Direct Click
Ignores direct visits (like typing the website) and credits the last ad.
Example: A user clicks a Google ad and later visits the website to make a booking. The booking is credited to the Google ad due to the Last Non-Direct Click attribution model, which gives credit to the last non-direct interaction before the conversion and ignores the direct visit.
Linear
Credit is split equally between all touchpoints.
Example: A user clicks on a banner ad, then an Instagram ad, followed by a YouTube ad before making a booking. Each ad receives one-third of the credit for the conversion.
Time-Decay
More credit goes to ads closer to the booking.
Example: Before booking, a user clicks on a banner ad, then an Instagram ad, followed by a YouTube ad. The YouTube ad gets the most credit, Instagram gets some, and the banner ad receives the least.
Position-Based
Most credit goes to the first and last ads, less to the middle ones.
Example: Before booking, a user clicks on a banner ad (first), an Instagram ad (middle), and finally a YouTube ad (last). The banner and YouTube ads receive the most credit, while the Instagram ad gets less.
Custom
You choose how to give credit based on what matters to you.
Example: A business decides to give 70% of the credit to the Instagram ad that led directly to the booking, and 30% to the first banner ad that helped initiate the customer journey.
With accurate campaign attribution, marketers can understand the impact of their efforts across different channels and evaluate the effectiveness of their marketing campaigns. Server-side tracking offers a lot of advantages for tracking and attribution. Take a look at the infographics below.
With Stape, you can avoid data loss by extending cookie time and bypassing tracking restrictions.
Stape has tools for increasing cookie lifetime:
And tools for bypassing tracking restrictions:
Stape can also help you with paid campaign attribution. We created a Facebook conversion API tag for the Google Tag Manager server container.
It works with Google Analytics 4 and Data Tag. It also extracts event data from any client, parses the server client, and automatically adds necessary parameters to the request. It sends user data to increase the match quality score and sets up event deduplication.
Server-side conversion tracking in Google Ads is also easier with Stape. Server-side Google Tag Manager can help you move your Google Ads conversion tracking tags from the webpage to the server.
Here’s a short and simple explanation on how to set attribution tracking.
Server-side attribution tracking is a way of tracking user actions and conversions by sending data directly from your server to an analytics or ad platform rather than relying on the user’s browser. In simple terms, instead of tracking with browser cookies and pixels, your server sends all the data, like page visits, purchases, or form submissions, directly to the analytics platforms.
You can integrate Stape with Google Tag Manager —specifically, with Google Tag Manager Server-Side . This setup allows you to send data through a server container, which can improve tracking accuracy and privacy.
No, Stape doesn’t track multi-channel attribution directly, but it enables it by providing server-side tracking through Google Tag Manager Server . You set up tags in GTM to send clean data to platforms like GA4, Facebook, and TikTok. These platforms then handle attribution (e.g., first-click, last-click).
Stape helps by:
For multi-channel attribution, you still need platforms like GA4 or Meta CAPI.
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Liuda is a Content Manager at Stape, writing about server-side tracking and tech that simplifies work. She helps businesses improve data accuracy, find the right customers, and build connections.
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