Attribution Models in GA4 for Effective Ad Spend Allocation

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Do you struggle to decide which marketing efforts to boost and which ones to let go of?

We propose using attribution models in GA4 for effective ad spend allocation. 

In all likelihood, you are already using it to track your website’s performance and to create audiences for targeted advertising. 

The data is already there, you just need to look closely in the right places and identify the channels, demographics, and markets to direct your marketing efforts and advertising budget for a higher return on ad spend (ROAS). 

But first, let us look at what the attribution models do for you. 

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What is Attribution Modeling?

Attribution modeling allocates credit to the relevant digital marketing channels for user conversion on your website or app. 

Let us unpack this statement. 

Users find and visit a website from different sources or channels. Businesses need to track those users and the digital channels through which they find them (first visit) and return. 

Some examples of digital marketing channels include:

  • Direct – when a user directly types your website’s URL to find you. 
  • Organic – when a user searches something on a search engine and finds your website on the search engine results page.
  • Paid – when users visit your website by clicking a link in your ads. 
  • Referral – when users arrive by clicking a link somewhere other than your resources. 
  • Social – when users visit by clicking a link on your social media. 
  • Email – when users click a link in a marketing email to arrive on your website. 

Don’t we have UTM parameters to track where the users come from?

Sure, we do. But shopping experiences are not that linear. For example, a user Lucy may have seen a hair care product ad on social media and clicked to learn more about it. She could then wander off to different pages to see what other products this business offers. 

A few days later she finds a social media influencer running reviewing the product and directing her users to her YouTube channel for a full review. So, she goes to YouTube, finds a product bundle from the same businesses there, and decides to visit the website to explore more bundles. 

A week later directly searches for a specific skincare bundle from this business in the search engine, arrives on the relevant page, and purchases it. 

So, where does the credit for this purchase event lie?

To resolve this issue, businesses rely on attribution models to find which channels bring the users, and the actions (clicks, purchases, downloads) of these respective users. 

Types of Attribution Models

Marketers use various attribution models to allocate credit to touchpoints in the customer journey

Types of Attribution Models

  • First Touch: The first-touch attribution model credits the first channel through which the user arrives on the website.
  • Last Touch: It gives credit to the channel later used by a visitor before landing on the website and triggering the key event.  
  • Linear:  The conversion credit is equally distributed among all the channels a customer used, to visit and eventually convert in the linear attribution model. 
  • Time Decay: In the time decay model conversion allocation is distributed among all the channels, with the most credit given to the last channel used. 
  • Multi-Touch: Multi-touch attribution distributes credit among all channels unequally. The U-shaped variant gives the most value to the first and last channels and the W-shaped model gives 30% each credit to the first, leading, and last channel; and distributes 10% in the remaining. 
  • Data Driven: This model uses the website’s user data analytics and artificial intelligence to identify conversion patterns for individual conversion events and use that to allocate credit. 

Attribution Models in Google Analytics 4 (GA4)

Google Analytics 4 tracks the performance of your website or app. This includes tracking any key events, formerly called conversions, on your website or app. 

Note: Google has changed its terminology, so an important event in GA4 is now called a key event. Once a key event is imported into Google Ads, it becomes a conversion. 

To learn more about the difference between a key event and a conversion read this blog

GA4 has dedicated attribution models based on rules and algorithms to assign credit for valuable user interactions like opening ads, clicking a webpage, etc. 

Currently, GA4 is using three attribution models:

  • Data-driven attribution
  • Paid and organic last-click
  • Google paid channels last click

Attribution Models in GA4

Data-Driven Attribution Model

The data-driven attribution model assigns credit for a key event based on user data, advanced analytics, and machine learning. 

It works in a two-stage process:

First, it monitors and evaluates the attribution paths (formerly conversion paths). 

Every path consists of several touchpoints. These are interactions between a user and a website or mobile application. 

Like in our earlier example, click an ad, click a social media ad, return via organic search, and generate a key event. 

GA4 evaluates converting and non-converting paths to identify the marketing touchpoints and patterns that typically result in a key event. 

It considers factors like the type of ad creative, order of exposure, number of ad interactions, device type, and time from key events.

Then, the initial model is used in an algorithm to predict how exposure to the number of ads along the path could lead to a key event.

Therefore, credit is assigned based on the probability of a user interaction resulting in a key event based on the initial observed model. 

Paid and Organic Last Click

The paid and organic last-click or last non-direct-click model assigns all credit to the channel the customer used last to visit your website and trigger the key event. 

It means all previous interactions, which may have contributed to the final key event, are disregarded.

Only the direct traffic channel is disregarded in this case and key events are credited to the channel used in the previous interaction. 

For example, if a person pays their first visit via a search ad, returns through a social media ad, and converts when they visit as a result of an email ad. Then credit will be assigned to Email only.

But if the same person had directly typed the web URL and converted, the credit would have gone to the social media ad.

Google Paid Channels Last Click

This attribution model credits the last Google Ads link through which the user arrived on a website before conversion. 

For example, if a user first visited a website after clicking a Google paid ad, then revisited via a social ad, returned via a YouTube ad, and finally converted via an email advertisement, the conversion will be credited to Google paid. 

However, if the same person had used the direct channel to arrive on the website and triggered the key event, the credit would be assigned to the YouTube ad. 

How to Configure Attribution Models in GA4?

Before we discuss how the attribution models in GA4 can help in effective ad allocation, it is necessary to understand how you can choose the desired attribution model. 

Use the following steps to choose the attribution model that suits your needs:

  • Go to GA4 > Admin > Data Display > Attribution settings. 

Go to Admin to set Attribution Settings in GA4

  • In the Attribution settings, you can choose the attribution model. By default, it is set to Data-driven. 

Select Reporting Atrribtuion Models in Atrribution Settings in GA4

  • In the same tab, scroll down to Channels that can receive credit, and check the desired channel. The default setting is Paid and organic channels. 

Select Channels that can receive credit in Attribution Settings in GA4

  • Finally, in the Key event look-back window, you can choose the time frame within which any user interaction on the website or app could be credited. 

Choose the Key event look-back window in the Attribution Settings in GA4

The look-back window is necessary to set how far back a user interaction can receive credit for a key event in GA4. 

Where to Find Attribution Reports in GA4?

With the change in the terminology from conversion to a key event, it could seem confusing where to look for the data for Attribution models in GA4. 

The attribution data is available in the Advertisement reports in GA4. 

  • To explore the Google Ads conversions go to GA4 > Advertisement > Conversion Performance.
    Here analysts can find the contribution of various Google channels in the conversions.
  • However, to look at the full customer journey go to GA4 > Advertisement > Attribution > Attribution paths.
    Since, only the key events in Google Ads are conversions and this report deals with valuable events from all channels, including those outside of Google, it shows the Key events path. 
  • You may also explore the impact of different attribution models in GA4 > Advertisement > Attribution > Attribution models, and experiment to choose one that suits you best. 

Using Attribution Models in GA4 for Effective  Ad Spend Allocation

Attribution modeling in Google Analytics 4 (GA4) provides marketers with invaluable insights into the effectiveness of their digital ad spend. 

Analyzing attribution model data allows businesses to make informed decisions to optimize budget allocation across various channels and campaigns. 

Using Attribution Models in GA4 for Effective  Ad Spend Allocation

Here are some ways attribution models in GA4 can guide ad spend allocation:

1. Understanding the Full Customer Journey

GA4’s attribution models allow marketers to see beyond the last-click attribution and understand the entire customer journey

It allows businesses to evaluate all touchpoints contributing to conversions. Consequently, it helps them identify the campaigns and channels most critical to stages in the customer journey and redirect their ad spend to the touch points most critical to conversions. 

2. Allocating Budgets Strategically

Marketers can allocate their ad budgets more strategically, thanks to insights from attribution models. 

These attribution models can help refine their audience segmentation capabilities, directing their ad budget to the audiences most likely to convert. 

Similarly, businesses could focus their ad spend on high-performing channels and campaigns that drive the most conversions or have the greatest impact on overall marketing goals.

3. Optimizing Campaign Performance

Attribution model data enables marketers to assess the performance of individual campaigns accurately. 

Making the connection between campaigns and their contribution to conversions helps them redirect their resources to optimize their messaging, targeting, and creative assets to enhance overall campaign effectiveness.

4. Identifying Underperforming Channels

Attribution models help marketers identify underperforming channels that may not otherwise be receiving adequate budget allocation

Pinpointing channels with low conversion rates or weak influence on the customer journey can help businesses optimize these channels or reallocate the budget to more effective ones, increasing their ROAS. 

5. Informing Future Strategy

Continuous attribution model data analysis offers insights into long-term trends and patterns in consumer behavior

This information can inform future marketing strategies, including ad budget allocations, allowing marketers to adapt and evolve their approaches to better align with changing consumer preferences.

Conclusion

This blog is about, “Attribution models in GA4 for Effective Ad Spend Allocation”. 

Attribution models assign credit for a key event, or in Google Ads, a conversion to digital marketing channels.

Google Analytics 4 offers three different attribution models. These include the data-driven, paid, and organic last-click, and Google paid channels last click. 

Businesses can explore their attribution data in the advertisement reports in Google Analytics 4. 

These insights can help businesses understand their full customer journeys, identifying high-performing channels and touchpoints critical from a conversion point of view. 

They could then refine their marketing efforts, reallocate their ad spend, refine audiences and ad creatives, and iterate to improve their ROAS.

 

Do you like what you read? Learn more about Digital Analytics on our blog here.

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This article was last updated on May 3, 2024

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