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The Strange & Confusing World Of Attribution

January 25, 2019 | Andrew Terpstra

The Strange & Confusing World of Attribution

Has there ever been a time where you are combing through your Google Analytics numbers and you notice that your direct traffic seems far higher than any of the other traffic coming to your website? I know it has happened to me on plenty of occasions; and before I really understood the ins and outs of attribution, I never could figure out why.

What is Attribution?

Digging through data can be an extremely arduous process with a lot of potential headaches, especially when you can’t definitively determine the source of your numbers.

When you log into your Google Analytics account and see that massive amount of direct traffic, the first thing you want to know is “why?” and “where are all of these people coming from?” Those two questions make up the biggest parts of why attribution is so important when reading data. The dictionary defines attribution as “the action of regarding something as being caused by a person or thing.”

When thinking about this in regard to digital data, tracking who is coming to a website, and where they are coming from, attribution simply means knowing exactly what channel brought in a user.

Why Does it Even Matter?

This question is the most obvious, but also the most important, when thinking about attribution as a whole. Because at the end of the day, every digital marketer needs to know why attribution is so critical to understand.

Let’s go back to the direct traffic I was talking about earlier. When we see direct traffic in our Google Analytics data, we don’t really know what that means or where it came from. Even when you click into the traffic to see where exactly the users are landing on your website, you still have no idea where they came from.

As you can imagine, if you are running a massive AdWords or Facebook Ads campaign, it is extremely important to you to know if one of your ads is what brought a user to your site. If you don’t know where they came from, you don’t know where to spend your advertising money to help bring in more users.

This is where different types of attribution models start coming into play.

Deciphering the Data

In order to best understand exactly where your website traffic is coming from, you can use a number of different attribution models depending on how you want to view your data.
Inside of Google Analytics, there are seven different default attribution models: Last Interaction, Last Non-Direct Click, Last Google Ads Click, First Interaction, Linear, Time Decay, and Position Based.

Each of these models has a very specific purpose and can be used to weight the importance of the traffic flowing into your website. Digital marketers will want to choose a model based on the goals of a specific campaign.

Let’s break down each model and how to best use them.

Last Interaction: this model is fairly self-explanatory, in that the last thing a user touches/clicks/interacts with before getting to your website is given 100% of the credit for bringing them to you.

Using Last Interaction: this particular model is not used very often in Google Analytics just because of the fact when using this model, a massively high percentage of your website traffic will be credited as direct. In a marketing situation, that is never very helpful because we always want to know exactly where website traffic is coming from.

Last Non-Direct Click: this model is almost identical to the Last Interaction model with the exception of, you guessed it, direct traffic.

Using Last Non-Direct Click: if you are still interested in what the last known campaign or interaction a user had immediately prior to visiting your site, you can use this model to help filter out all of the direct traffic. This model is usually best used in situations where you are seeing a fairly quick conversion cycle.

Last Google Ads Click: this model is also fairly self-explanatory. If you are running a Google AdWords campaign, the attribution model will give 100% credit to the last ad campaign the user clicked on. However, this won’t give you any information about other interactions a user may have made after clicking on your Google ad.

Using Last Google Ads Click: since AdWords has such a clear cost per click available, this model can help you see the return on the money you spent on a particular AdWords campaign.

First Interaction: the same as Last Interaction but instead of focusing on the very last interaction a user had before getting to your site, it focuses on the first.

Using First Interaction: for all intents and purposes, this model is the default for people who want to know how exactly a user heard about their business. Seeing exactly where people are first hearing about you is critically important to building a brand or business.

Linear: this model gives equal credit to all interactions that a user has during their journey to your website.

Using Linear: this model can play a big role for any business that has a typically long conversion cycle, because over that long period of time you want to make sure you know each and every interaction a user has so that you can fully understand their entire journey to your website.

Time Decay: this model will give the most credit to the interaction that occurred most closely in time to when the conversion or sale on your site happened.

Using Time Decay: this model works similarly to the linear model, but will give far less credit to interactions with campaigns that occurred further away from when the actual conversion or sale happened.

Position Based: this model gives 40% of the credit to the first interaction a user had, 40% of the credit to the last interaction a user had, and splits 20% of the credit between all of the other interactions a user had prior to coming to your website.

Using Position Based: if you like the idea of knowing how a user first heard about you while also knowing what potentially finally brought them to your site, this is exactly the model you want to be using.

Custom: once you feel like you really have an understanding of how each of the default attribution models work, but they all leave you unsatisfied and sad inside about their limitations, you can create a custom attribution model right inside of Google Analytics to help you design whatever kind of model you would prefer to use.

A Brave New World

Now that you know the ins and outs of attribution models, you can start to gain a much better understanding of where the users on your website are coming from and what they are seeing to help them decide on choosing your website over someone else’s.

Understanding attribution is a giant leap forward in your marketing knowledge and will propel you into an entirely new world that didn’t even seem possible before.