Practical Ecommerce

Understanding Google Analytics Attribution Models

Editor’s Note: This article was originally published by Web Marketing Today. Practical Ecommerce acquired Web Marketing Today in 2012. In 2016, we merged the two sites, leaving Practical Ecommerce as the successor.

Does everyone who comes to your site complete the sale on the first visit? Look at the Google Analytics Path Length report in the Multi-Channel Funnels report. Is “1” the only path length shown? If your answered “no” to either of these questions, then you need to know about Google Analytics attribution models.

An attribution model is a set of rules that defines how credit for sales and other conversion goals get attributed to each interaction during the buying process. You can divide these models into “single click” or “distributed click” examples.

If your path length is greater than one then you could have an attribution problem.

If your path length is greater than one then you could have an attribution problem.

Types of Attribution Models

There are seven default attribution models in Google Analytics. Also, you can create up to 10 custom attribution models or import extra attribution models from the Gallery.

Google Analytics Attribution Model Types.

Google Analytics Attribution Model Types.

Last Interaction. 100 percent of the conversion value is given to the last channel before converting. Last Interaction is useful when:

  • Your site gets “bottom of the funnel” sales-ready traffic;
  • Your business is primarily transactional with a short sales cycle.

Last Non-Direct Click. 100 percent of the conversion value is given to the last channel before converting, except when that channel is Direct traffic (URL typed into the browser location bar). When the last channel is Direct, the last campaign or marketing activity before conversion receives 100 percent of the conversion.

  • It’s important to note that is the default model used by all Google Analytics reports except the Multi-Channel Funnels report;
  • By removing the Direct traffic, this model undervalues branding and brand recognition. Instead it gives credit to a campaign even though it may have taken the customer additional visits where they typed your URL in directly to come to your site and purchase;
  • This is why none of the standard Google Analytics reports match the Multi-Channel Funnels reports.

Last AdWords Click. 100 percent of the conversion value goes to the most recent AdWords ad before converting.

  • This model doesn’t provide much benefit for any channel other than Paid Search;
  • It does allow you to optimize your AdWords ads by identifying and crediting the AdWords ads that converted the best.

First Interaction. 100 percent of the conversion value is given to the first channel used by a customer. First Interaction is appropriate when:

  • You are trying to determine which channels provide brand awareness value;
  • Your brand is not well known, and you want to know the keywords or channels that initially engaged the customer.

Linear. Equal portions of the conversion value are given to each channel in the conversion path. The Linear model is suitable for:

  • Campaigns where you want contact throughout the conversion process;
  • Equal distribution along all portions of the conversion path.

Time Decay. This distributed attribution model gives a large part of the conversion value to the channels closest to the conversion. It also provides lesser portions of the conversion value to all channels in your lookback window (default of 30 days).

  • Important to sites where there are short consideration phases or that run short-term promotions;
  • Based on the model of exponential decay, this model has a default “half-life” of seven days. So a channel that engages seven days before a conversion will receive one-half the credit of a channel on the day of conversion. Likewise, a channel clicked 14 days before a conversion will get ¼ of the credit;
  • You can change the default “days prior to conversion” setting based on your Time Lag report in the Multi-Channel Funnels section of Google Analytics.

Position Based. Another distributed attribution mode, this creates a hybrid of first and last interaction.

  • The Position Based model is helpful to give credit to both the “branding” channels that are a customer’s first introduction to your site as well as the “converting” channels that resulted in sales or goal completions;
  • A typical scenario is 40 percent to the first interaction for “branding,” 40 percent to the last interaction for “conversion,” and then divide the remaining 20 percent among the interactions in the middle that “nurture” the customer;
  • Another scenario suggested by Google’s Avinash Kaushik is 10 percent “branding,” 40 percent “conversion,” and dividing the remaining 50 percent among the “nurture” channels. His rationale: “From all my experimentation I’ve found that taking out the last channel (whichever one it is) causes a material impact on the conversion process, so it gets a ‘good amount of credit.’ The middle channels have an important role in driving people to the last interaction, so they are recognized for that. The first interaction deserves some credit for the conversion, but not as much as the middle or last — for obvious reasons.”

Attribution Example

Let’s assume that a visitor comes to your site four times in a month. She initially comes to your site by clicking an AdWords ad. She returns one week later by clicking on a link posted on a social network.

That same day, she comes back a third time via one of your email campaigns, and a few hours later, she returns the fourth time by typing the URL into her browser location bar and makes a purchase. If the conversion value for her purchase was 100, the chart below shows what the value would be for each channel in the scenario.

An example of how attribution models impact conversion values.

An example of how attribution models impact conversion values.

How to View Attribution Models in Google Analytics

First, you need to set up goals or ecommerce tracking in the Google Analytics view that you want to use. You can find more details on setting Google Analytics goals in the article, “Google Analytics: How to Define Website Goals.”

Once you have goals or ecommerce sales in your Google Analytics reports, go to the Assisted Conversions report in Google Analytics at Conversions > Multi-Channel Funnels > Assisted Conversions. Look at the last column: Assisted/Last Click or Direct Conversions.

  • If the value is less than one, then that channel is more likely to drive last click conversions;
  • If the value is greater than one, that channel is more likely to be present earlier in the conversion cycle. These channels are being undervalued in certain attribution models and getting no credit in last click attribution models (all standard Google Analytics reports, for example).
Assisted/Last Click or Direct Conversions is greater than 1, this channel may not be getting the credit it deserves.

Assisted/Last Click or Direct Conversions is greater than 1, this channel may not be getting the credit it deserves.

So what are the best ways to allocate credit to all of our marketing channels properly?

If you scroll to the bottom of the Google Analytics Navigation and select Conversion > Attribution > Model Comparison Tool, you’ll be able to compare the attribution models to see what makes sense for your website.

Google Analytics Model Comparison Tool

With the Google Analytics Model Comparison Tool you see attribution models side-by-side.

With the Google Analytics Model Comparison Tool, you see attribution models side-by-side.

Google Analytics allows you to view up to three attribution models side-by-side in the Model Comparison Tool. This allows you to see how different attribution models impact the value of your marketing channel. Once you know the impact of each attribution model, you can determine which one is appropriate for your specific website.

Sharon Mostyn
Sharon Mostyn
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Comments ( 2 )

  1. Carlos Rivera February 9, 2016 Reply

    This is the first I heard about Attribution Models. Thank you so much for keeping me up to speed on this Google Analytics feature!

    • Sharon Mostyn February 9, 2016 Reply

      Happy to help Carlos! Please let me know if there are other analytics topics that you’d like more information about.

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