Learn the Ropes of GA4 Attribution Modelling

If you’ve reached that point of no return when you’ve either started to transition to GA4, or you’ve set a date for when to do so, you’ve probably already seen that GA4’s attribution model has leaped forward compared to its predecessor’s. 

Is it better? We dare say so. GA4 now allows you to adjust attribution modeling depending on the one that makes the best sense for your business type. Not only that, but once you transition, you can apply it retroactively across all your Google Analytics reports.

Now that opens up a lot of opportunities. 

If you’re a Marketing Manager, attribution modeling helps you make better business decisions by understanding what channels get the attention of prospects and what channels convert. 

These traffic generating sources  work hand in hand and knowing what budget to allocate to each step of the buying process is eye opening. Because many times it’s not about what channels you should scale down or up, but how much more/less  you should invest in each channel.

What is Attribution?

Before we dive deeper into GA4’s Attribution Modelling, it’s best to ensure we’re on the same page regarding the attribution definition. 

As you’re well aware, the prospect’s road to conversion is paved with multiple touch points. Different attribution models let you decide how much credit each touch point gets for your conversions.  

So, in essence, as Google so wisely defines it, attribution is nothing more than the act of giving credit for conversions to different ads, clicks, and factors along users’ paths to completing a conversion.  

What’s New in GA4 vs. Universal Analytics? 

The launch of GA4 marks the dawn of a new era for digital marketers. An era where you get to pick the attribution model that best serves your marketing efforts. As opposed to how things worked in UA, this smarter and more flexible approach will allows you to switch between different models and watch your reports change accordingly across your entire GA4 property.

At last, you can finally escape the Last Click Attribution model that ruled supreme inside Google Universal Analytics and select any of the models below:

1. Data-Driven Attribution
2. Last Click 
3. First click
4. Linear 
5. Positioned based
6. Time decay
7. Ads-Preferred Last Click

Now, you may be thinking: Didn’t Universal Analytics feature the same attribution models?. 

Your memory serves you right. However, Google’s previous version of analytics offered a very broad Model Comparison Tool where you could see how different models attribute conversion to specific channels. 

However, that was all there was to it. Replacing the default model across standard or custom reports was impossible. Maybe the tool was merely a teaser for what was to come.

One of the ways GA4 is significantly better than its predecessor is it allows you to shift between different cross-channel attribution models. Not only that, but as you change to a different model, some of your reports will change with it – even those containing retroactive data. 

This category includes reports using event-scoped metrics as:

• Source, Medium
• Campaign
• Default Channel Grouping
• Conversions
• and explorations reports

Nonetheless, user and session-scoped traffic dimensions (such as Session source or First user medium) will not be affected by changes to the reporting attribution model.

Speaking of changes, besides letting you choose and experiment with different attribution models, GA4 also lets you adjust the lookback window for the Acquisition conversion events and for all other conversion events. We will go into this in more detail by the end of this article.

For now, let’s discuss attribution – what it is and what’s it good for -, analyze what each model brings to the table, and see which one to use when. 

A GA4 Attribution Model Comparison & When to Use What

Here’s what you need to know first and foremost. You’ve got seven attribution rule sets to choose from here. Each one comes with a different method of assigning credit for the conversion. Let’s see what we mean by that.

1. Data-driven attribution

We’re going to start off by saying up until this year, this feature was only available for the select few that had a Google Analytics 360 account – which was far from cheap. 

Data-driven attribution relies on machine learning algorithms that evaluate both converting and non-converting paths. This means Google includes both users that converted and those who didn’t in determining the conversion probability for each touchpoint.

To do this, this model analyzes up to 50 touchpoints  – as opposed to only 4 touchpoints in Universal Analytics –, taking into account various factors such as time from conversion, device type, number of ad interactions, the order of ad exposure, or the type of creative asset. It then creates a credit score that’s used for each of the channels the user went through before converting. 

When to use it

We’ll start by saying that this is the model recommended by the GA4 team, especially when you think that none of the models we’ll go through next fit your business. 

If you are still skeptical about using it, the best part of GA4 is that you can make your own decision by comparing it with other models. 

However, you’ll most likely use this attribution model if:

• You implement online marketing tactics across a multitude of channels; 
• And/or the buying decision takes more than a couple of days;

2. Last Non-Direct Click

The Last Non-Direct Click was the default attribution model used by GA Universal, and it’s still the default for the Traffic Acquisition reports in GA 4, which reports on attribution at a session level. As the name suggests, it used this to give credit for the conversion to the last channel clicked by the user, ignoring the direct traffic. 

The problem with it is it won’t give you a clear indication of which touch point actually generated the conversions, since it’s only taking into account the last interaction (other than a direct one). 

It’s also worth noting that this is the only last-click model that you can export to Google Ads. We’ll dive into the “Ads-preferred last click” attribution model by the end of this article, which however is only available for reporting purposes.

When to use it:

• If the business has a long buying cycle, and you want to see the effects of the marketing efforts on the long term.
• When you sell fast-moving consumer goods (or FMCG) where the user usually makes the decision to buy without thinking too much about it.

3. First-click

Again, the name speaks for itself. This rule will assign 100% of the conversion credit to the first channel a customer clicked before converting. 

When to use it: 

• if you’re in the stage of building brand awareness and your advertising goals are oriented toward increasing your brand name;
• If you your business is driven by lead generation; 

4. Linear

This one gives equal weight to all the channels the customer clicked before he converted. For example, if someone first clicked a Facebook ad, then an email link, then ran an organic search for your website, all these channels will get 33.33% credit for the conversion. 

When to use it: 

• If each channel proved to have a very clear job in the buying process: 

• Let’s say most of your prospects land on your website through organic traffic
• Then you retarget this traffic and generate leads
• So you can convert them through email marketing.

Bottom line is that if your business is in a situation where every client interaction is equally important to its conversion goals, this is the model to use. 

5. Positioned based

In this case, 40% of the conversion credit goes to the first and the last interactions. What happens with the remaining 20%? It gets distributed equally within the rest of the channels. 

6. Time decay

With this ruleset, interactions that happened closer to the time of conversion are credited with a higher score. So, how is this score calculated? 

Well, credit is given using a seven day half life.

Here’s what this means: a click that happens 8 days before the conversion will only get half as much conversion credit as compared to a touchpoint click happening one day before the conversion. 

When to use it: 

• If you have a website that is constantly giving discounts or that runs only on back to back promo, this attribution model may be a good choice.

7. Ads-Preferred Attribution: Last Click

For this model, 100% of the conversion value is assigned to the last Google Ads channel the customer clicked through before converting. 

But what if no ad appears in the conversion path? – you ask. In this case, the attribution reverts back to the old-faithful cross-channel last non-direct click. This means that the last touchpoint channel (which, in this case, was not a Google Ad) on the conversion path gets 100% credit of the conversion.

As Google exemplifies:

• Display > Social > Paid Search > Organic Search → 100% to Paid Search (even if the Organic Search was the last touchpoint, the conversion will be attributed to Paid Search)
• Display > Social > YouTube EVC > Email → 100% to YouTube (same as above)
• Display > Social > Email > Direct → 100% to Email (because there was no Google Ads involved, and the last touchpoint was Direct, the conversion is attributed to Email)

When to use it: 

If your website traffic and revenue is heavily driven by Google Ads campaigns (Paid Search, YouTube, Display), and even when you turn off the ads for a few days you see an obvious negative impact on your business.

How to Choose the Attribution Model and Lookback Window (Step by Step)

Now that we’ve seen how each model works and when each one is best used, let’s shift our focus on how you can pick the attribution model you desire.

Step #1. Go to Admin settings, and click on the Attribution Settings in the Property column.

Step #2. Select the model you prefer form the Reporting attribution model drop-down

Step #3. Once you’ve chosen your model, scroll down and click Save.

Flexible Lookback Window

Most conversions don’t happen during the first website visit. You know this all to well. It generally takes days, weeks, and sometimes even months until a prospect decides to complete a purchase.

That’s why GA4 allows you to adapt the Lookback Window. This tells GA4 the time period during which it can analyze the conversion path and attributions. In other words, this is where you can instruct Google how far back in time you want it to consider if a touchpoint is eligible for attribution credit.

The recommended (and default) windows are 30 days for Acquisition conversion events (​​first_open and first_visit), and 90 days for all the other types of conversions. 

Let’s take an example where we analyze a purchase event – marked as a conversion by default. 

User A makes a purchase on January 30. If the Lookback Windows is set to 30 days, GA4 will only consider the touchpoints that occurred between January 1 and January 30. For a 90 days lookback window, the same purchase on January 30th, would be attributed to interactions happening between November 2nd and January 30th

Pretty straightforward, right? 

Here are the steps you need to follow to change the default setups: 

Step #1. Navigate to the Admin section.

Step #2. From the Property column, click Attribution Settings.

Step #3. Click on the Lookback Window, and select the desired amount of time for each one of the Acquisition conversion events and All other conversion events.

How to Decide and Evaluate Attribution Models Before Making Any Changes

To help you better understand how each attribution model works for your business, Google Analytics 4 offers 3 reports you can explore. Navigate to the Advertising tab in the left panel to reach them.

Now let’s go through each of these reports. 

The first thing you’ll probably want to do is assess the current situation. To do so, look at the All Channels report under the Performance tab category. 

This is where you’ll see the performance of each of your channels. By default, the report shows all your conversions in an aggregated manner. However, we recommend focusing on the most important ones. So, go ahead and select the conversion that is the most important to you (i.e. purchas/leads) by selecting it from the top drop-down. Then, from the top right corner, adjust your time frame accordingly. 

Now let’s move on to the attribution model comparison. Navigate to the Model Comparison Report found below the Attribution tab in the left panel.

This is the most useful way to compare various attribution models. It offers you the possibility to view a side-by-side comparison of two different attribution models by selecting the conversions you want to focus on, the time period, and various dimensions (Default Channels, Source, Medium, etc.). 

Another tip for getting a more solid understanding of how different models work is to use filters. Say you want to evaluate certain devices, geographical regions, or you simply want to narrow the data down so very specific campaigns you’ve run. Filters allow you to do so with minimum effort.  

Third, by looking at the Conversion Paths report, under the same Attribution tab, you can grasp how these models distribute credit for your customer’s conversion paths. 

You can choose different dimensions and attribution model. The graphic lets you quickly assess which channels initiate, assist, and close conversions. 

The same filtering tip as for the previous report applies here as well. Use filters to dig deeper (you can even choose the length of the path, which counts 50 touchpoints by default) and make sure you make the best decision. 

Final Thoughts

Now you know how each model works, which business model each of them fits best, and how you can compare them. You should have more than enough info to weign in your options and pick the one that maximizes your business’s growth opportunities. 

Cross-channel attribution models will  help you understand how different channels work together and give you a clear direction on how you should split your marketing  budget across channels. 

If you still haven’t made the transition to GA4 yet, we highly recommend doing so ASAP. If you don’t have the time, resources, or know-how for doing so, we’ve already helped 500+ businesses transition, so why shouldn’t you be next? 

Data analytics is one of the  things Growth Savvy does best. So, if you need help putting together a reliable and healthy web and app data setup, let’s talk! Book a free strategy call now and let’s see how we can help your business make better decisions and seize growth opportunities as they arise.