Understanding Attribution Models Is Crucial To Analyzing Your Digital Marketing Campaigns


With the advent of the internet and online advertising, businesses have been given the ability to measure the effectiveness of their marketing campaigns in a way that was unimaginable before the internet.

Measuring the effectiveness of your digital marketing campaign(s) may seem like a simple matter of installing conversion tracking code snippets and calling it a day. Many forget to consider their attribution model. This can be a confusing topic for many to grasp but it’s crucial if you are to truly understand how well you’re doing with each marketing channel.

The attribution model you choose can drastically change the way your data is reported and therefore could give you false insight into which of your marketing efforts are generating the best results.

The default attribution models available in Google Analytics are:


The default attribution model for all of your Google Analytics is ‘Last Interaction’. This means that it credits the last traffic source that immediately preceded the the goal conversion.


The problem with this is that the buyer journey is rarely a linear path, meaning they barely convert on their first visit.

So for example, let’s say your buyer journey is something like this instead:

1. Visitor clicks on your Google Ad but doesn’t convert.

2. Visitor does an organic search for your business a couple of day slater and doesn’t convert.

3. Visitor likes your page on Facebook and visits your website but still doesn’t convert yet.

4. Finally, the visitor goes directly to your website a week later by typing in your URL in the browser address bar and finally converts.

With the last-interaction attribution model, Google Analytics would give ‘Direct’ traffic source credit for the conversion. This would lead you to believe that your Google Ad campaign wasn’t generating any results or that your social media channels weren’t a factor in the conversion. Which would be false.

There’s a lot the last-interaction attribution model doesn’t tell you, which is why it’s important to use different attribution models when analyzing your data to truly see which marketing channels are contributing to the final conversion.

You can do this easily by using Google Analytic’s “Model Comparison Tool”:



Attribution models like linear, time decay and position based will credit the conversion to each interaction that was part of the buyer’s journey, not just the first or last.

‘Linear’ gives equal credit to each interaction. ‘Position-based’ gives most credit to the first and last interactions with some credit given to the interactions in the middle. ‘Time decay’ gives more credit with each interaction that leads up to the final conversion with most credit given to the last interaction.

Comparing attribution models against each other helps you get the full picture so you know how to fine-tune your marketing to maximize results.