For Example:
If a customer clicks on a Facebook ad and then a few days later visits the site through a Google Search right before then making a purchase, the attribution to the purchase will go to Google (the last click).This model has its advantages and disadvantages.
Advantages:
- Factual and Not Opinionated
- What UTMs track and say actually happened. They are not influenced by attribution models and cannot have conflicting views (like algorithmic attribution)
- Simplicity
- It’s easy to implement and understand last click attribution through properly set up UTMs
Disadvantages:
- It does not take into account other touch-points that may have influenced a customer’s decision to make a purchase
- There are ways to ‘break’ the model
- Checkouts can break UTMs
- Customer can refresh or leave a page and then come back and make the purchase
- Ad blockers can break UTMs
Why do we focus on Last Click Attribution?
There can be a lot of steps in the customer’s journey before making a purchase. While we do already report on platform-reported conversions, it is really valuable to have a fact-check of last click to pair what actually happened right before the purchase occurred. In addition, we stitch GA data with Shopify data to get the best UTM coverage and then we enrich our attribution capabilities with Zero Party data (Post Purchase Surveys) and platform-reported windows to get a full picture. Knowing what happened right before a customer made a purchase can lead to valuable and interesting insights as to a customer’s behaviors right before purchasing.For Example:
- Do customers consistently come from a social media platform right before purchasing?
- Do customers consistently come through a search of your company right before purchasing?
- Do customer consistently come through a specific landing page right before purchasing?
- Do customers consistently come through an email/sms right before purchasing?

