{"id":265,"date":"2022-06-05T21:19:08","date_gmt":"2022-06-05T21:19:08","guid":{"rendered":"https:\/\/measurebit.com\/?p=265"},"modified":"2022-10-04T14:30:30","modified_gmt":"2022-10-04T18:30:30","slug":"the-definitive-guide-to-google-analytics-attribution-models-2022","status":"publish","type":"post","link":"https:\/\/measurebit.com\/the-definitive-guide-to-google-analytics-attribution-models-2022\/","title":{"rendered":"The Definitive Guide to Google Analytics Attribution Models 2022"},"content":{"rendered":"\n

Google Analytics is a POWERHOUSE for figuring out what’s working and what’s not in your marketing. When configured properly, you’ll gain insights similar to Wicked Reports or Hyros! In this guide, I show how with both Universal Analytics and Google Analytics 4.<\/p>\n\n\n\n

What is Attribution Modelling?<\/h2>\n\n\n\n

An attribution model is a set of rules for defining how much conversion credit is assigned for each touchpoint prospects encounter on their journey to becoming customers.<\/p>\n\n\n\n

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Typical Customer Journey stages<\/figcaption><\/figure>\n\n\n\n

Some campaigns are better at acquiring leads (Top of Funnel). Whereas other channels are better at converting those leads into paying customers (Bottom of Funnel). Attribution modeling allows advertisers to view their conversion data through different lenses <\/em>and gain key insights into how and where their efforts are having an impact.<\/p>\n\n\n\n

Why do you need attribution models?<\/h3>\n\n\n\n

Let’s say traffic is coming to your site via a Facebook ad, a display Google ad, paid search, Google Shopping, content strategy, Twitter, and Reddit.<\/p>\n\n\n\n

Which channels are responsible for making revenue and which ones are losing money?<\/p>\n\n\n\n

Typically, a number <\/em>of channels play a role in converting prospects into customers and each should get a fraction of the credit.<\/p>\n\n\n\n

But each ad network attempts to claim as much credit as possible for conversions they see even when they contribute very little to the end result. The reason they do this is they’re in competition for your advertising dollars.<\/p>\n\n\n\n

The more conversions, the healthier your ROAS, and the more likely you’ll continue spending money.<\/p>\n\n\n\n

It’s why, when you add up the conversions from ad reports, the sum is significantly higher than the actual sales.<\/p>\n\n\n\n

This is important when deciding whether to kill vs scale digital marketing campaigns. Without having an accurate picture of how each marketing effort performs, you risk making costly errors by over-investing in unprofitable channels and underinvesting in profitable ones. Either way, you leave money on the table.<\/p>\n\n\n\n

How do you track marketing attribution?<\/h3>\n\n\n\n

To attribute conversions properly, you need to collect detailed data about traffic sources, transactions, and customer details. Then you need to blend data sets together so you can run sophisticated attribution queries.<\/p>\n\n\n\n

It’s nearly impossible to do this with a spreadsheet application.<\/p>\n\n\n\n

Luckily, Google Analytics makes this relatively easy. All you have to do is feed it the right data format.<\/p>\n\n\n\n

Multi-touch Attribution Models in Google Analytics<\/h2>\n\n\n\n

To unlock the power of multi-touch attribution, you must either have conversion goals or eCommerce enabled in Universal Analytics. Here’s an example of a dataLayer payload for Universal Analytics<\/a>.<\/p>\n\n\n\n

Google Analytics 4 has purchase <\/strong>conversions and Ecommerce enabled by default. So, as long as you’re collecting revenue data, you’ll already have access to the Model Comparison Tool. Here’s an example of a dataLayer payload for GA4.<\/a><\/p>\n\n\n\n

What attribution models are available in google analytics?<\/h3>\n\n\n\n

Google Analytics has a number of excellent models, depending on the version (e.g. UA vs GA4).<\/p>\n\n\n\n

Last Touch Attribution Model<\/strong><\/h4>\n\n\n\n
\"google
Last Touch Attribution Model<\/figcaption><\/figure>\n\n\n\n

This model answers the question, “What’s causing prospects to finally <\/em>buy?”<\/p>\n\n\n\n

This is your Bottom-of-funnel (BOF) traffic. Prospects already know about you and are probably ready to buy. This is the type of traffic that comes from email or retargeting campaigns.<\/p>\n\n\n\n

ALL credit is given to the last interaction, while other channels that assisted in the conversion are ignored.<\/p>\n\n\n\n

Last Non-Direct Attribution Model<\/strong><\/h4>\n\n\n\n
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Last Non-Direct Attribution Model<\/figcaption><\/figure>\n\n\n\n

A big portion of sales will come from direct visitors. But logic tells you these people didn’t suddenly come to your site without some kind of prior awareness.<\/p>\n\n\n\n

Weeks or months ago, prospects could’ve clicked a Facebook Ad, or found you in a Google search.<\/p>\n\n\n\n

Perhaps, at the time, they weren’t in a position to say “yes” to your offer. So, they bookmarked your site and came back later.<\/p>\n\n\n\n

This behavior is typical. So, you gain more insight by looking for the interaction just before<\/em> a direct visit that leads to a sale.<\/p>\n\n\n\n

Similar to Last Touch, ALL credit is given to the last non-direct interaction.<\/p>\n\n\n\n

Last Google Ads Click Attribution Model<\/strong><\/h4>\n\n\n\n
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Last Google Ads Click Attribution Model<\/figcaption><\/figure>\n\n\n\n

This model is similar to Last Non-Direct Touch, except it gives all possible credit to Google Ads clicks. It’s useful for specifically understanding how Google Ads (Google Adwords) are peforming.<\/p>\n\n\n\n

Time Decay Attribution Model<\/strong><\/h4>\n\n\n\n
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Time Decay Attribution Model<\/figcaption><\/figure>\n\n\n\n

In psychology, there’s a phenomenon known as Recency Bias<\/em>, where recent events influence you more than ones that happened a while ago.<\/p>\n\n\n\n

Time Decay models this by assigning more of the credit to recent events.<\/p>\n\n\n\n

First Touch Attribution Model<\/strong><\/h4>\n\n\n\n
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First Touch Attribution Model<\/figcaption><\/figure>\n\n\n\n

This model answers the question, “Where do customers intially <\/em>coming from?”<\/p>\n\n\n\n

This type of traffic is cold and is known as Top-of-funnel (TOF). Prospects are unaware of your business. Campaigns are geared towards building awareness.<\/p>\n\n\n\n

ALL credit is given to the very first interaction, while other channels are ignored.<\/p>\n\n\n\n

Linear Attribution Model<\/strong><\/h4>\n\n\n\n
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Linear Attribution Model<\/figcaption><\/figure>\n\n\n\n

This model gives a broad view across all of your funnel touchpoints.<\/p>\n\n\n\n

It’s useful to gaining a general understanding for where revenue is coming from. Start with Linear Attribution for initial ROI investigations before drilling deeper with the other models.<\/p>\n\n\n\n

Credit is evenly distributed among channels.<\/p>\n\n\n\n

Position-Based Attribution Model<\/strong><\/h4>\n\n\n\n
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Position-Based Attribution Model<\/figcaption><\/figure>\n\n\n\n

This model gives the 40% of the credit to the first and 40% to the last interactions, with the remaining 20% distributed among the other channels.<\/p>\n\n\n\n

Data-Driven Attribution Model (GA4 only)<\/strong><\/h4>\n\n\n\n
\"\"
Data-Driven Attribution Model<\/figcaption><\/figure>\n\n\n\n

Of all the models, the Data Driven is the most sophisticated. (Only available in GA4.)<\/p>\n\n\n\n

GA4 analyses your e-commerce data using machine learning to create a probabilistic model. Each marketing channel is then given a fraction of the available credit.<\/p>\n\n\n\n

Data-Driven gives the most accurate gauge of how various channels and campaigns are performing.<\/p>\n\n\n\n

What attribution model does Google Analytics use by default?<\/h5>\n\n\n\n

Universal Analytics uses Last Non-Direct Touch… even though its own documentation says it uses Last Click.<\/p>\n\n\n\n

On the other hand, Google Analytics 4 uses Data-Driven out of the box, which is the most accurate of all attribution models.<\/p>\n\n\n\n

What is the default attribution window for Google Analytics?<\/h5>\n\n\n\n

The default attribution window for Universal Analytics models is 30-days. However, you can create custom models with longer periods.<\/p>\n\n\n\n

GA4 applies a 90-day look-back window by default.<\/p>\n\n\n\n

How do you set up multi-touch attribution in Google Analytics?<\/h5>\n\n\n\n

GA4 and UA use mult-touch attribution models by default. There is nothing to set up per se.<\/p>\n\n\n\n

However, you’ll want to use the Model Comparison tool for marketing analysis. (See below).<\/p>\n\n\n\n

Can you change the attribution model in Google Analytics?<\/h5>\n\n\n\n

You can’t change the default account attribution model in Universal Analytics. You can however apply a  different model to a specific view.<\/p>\n\n\n\n

With GA4, however, you can change the model for the entire account. Here’s how you do it:<\/p>\n\n\n\n

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Attribution model account settings for GA4<\/figcaption><\/figure>\n\n\n\n
  1. Go to Admin > Property > Attribution Settings<\/li>
  2. Select an attribution model (Data-driven is recommended)<\/li><\/ol>\n\n\n\n
    \"\"
    The default attribution model for GA4 is Data-driven<\/figcaption><\/figure>\n\n\n\n

    3. Choose the ‘look back’ windows for acquisition and conversion events:<\/p>\n\n\n\n

    \"\"
    You can set the conversion window to a maximum of 90-days<\/figcaption><\/figure>\n\n\n\n

    Google Analytics Model Comparison Tool<\/h2>\n\n\n\n

    Both Universal Analytics and Google Analytics 4 have a Model Comparison Tool.<\/p>\n\n\n\n

    What is a comparison view in google analytics?<\/h5>\n\n\n\n

    The Model Comparison Tool allows you to compare two different or three models.<\/p>\n\n\n\n

    Here’s how to analyze marketing data in Universal Analytics.<\/p>\n\n\n\n

    First, filter by source \/ medium:<\/p>\n\n\n\n

    \"\"
    Source \/ Medium is a most common way to view ad data in GA<\/figcaption><\/figure>\n\n\n\n

    In the image above, CPA for google \/ cpc is $33.44 (Last Non-Direct Click) or $23.12 (First Interaction).<\/p>\n\n\n\n

    This result makes sense… some prospects visit your site without taking action until subsequent visits. That’s why Last Click numbers are lower than the First Interaction ones.<\/p>\n\n\n\n

    You can also change the view to show either CPA, value (revenue), or ROAS.<\/p>\n\n\n\n

    \"\"
    Universal Analytics allows you to study cost-per-action (CPA) and ROAS. GA4 only allows has revenue and conversions view.<\/figcaption><\/figure>\n\n\n\n

    To understand the ROAS of your advertising campaigns, select the Conversion Value & ROAS <\/strong>option from the dropdown.<\/p>\n\n\n\n

    In the example above, the ROAS for Last Non-Direct Interaction is 409%. But when comparing it with First Interaction, we get a figure of 594%.<\/p>\n\n\n\n

    By the way, if you want to see ROAS data for Facebook, Titkok, Pinterest, and other ad networks in this report, here’s how you can import your ad-cost data<\/a>.<\/p>\n\n\n\n


    NOTE – At this point in time, GA4’s model comparison only allows you to view conversions & revenue. So, until GA4 updates this tool, stick to Universal Analytics for analyzing CPA and ROAS.<\/p>\n\n\n\n

    <\/p>\n\n\n\n

    Why use the google attribution model comparison tool?<\/h5>\n\n\n\n

    No single model is ‘correct’. Think of the different models as lenses you can use to answer different questions.<\/p>\n\n\n\n

    Here are some examples of questions you might ask:<\/p>\n\n\n\n