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Google Analytics is an indispensable tool in your marketing stack. It is sophisticated enough to provide you with data to help you make sense of your traffic. 

However, e-commerce websites are using Google Analytics to track traffic and sales. In this case, how does one effectively use the analytics tool to determine which traffic source should be credited for a particular sale?

Before asking an expert e-commerce agency to help you make sense of Google Analytics, it’s best to learn it yourself first. Thankfully, this post will shed light on the Google Analytics attribution model, why your business should use it, and how to utilize it properly.

A chart of google conversion models

What is the Google Analytics Attribution Model?

The Google Analytics attribution model refers to how the analytics tool assigns the credit for each successful sale on your website. This is important because it’s possible a user visited your landing page from different touchpoints in your conversion path.

Let’s say a user became your customer from the following touchpoints:

  • First session – Display ads (did not convert)
  • Second session – Paid search (did not convert)
  • Third session – Newsletter (did not convert)
  • Fourth session – Organic search (converted)

From this example, the user first interacted with your site by clicking on a display ad. Then it visited your site again after seeing your paid search ad. The user went to your site yet again by clicking a link on your newsletter.

From the first three interactions, the user didn’t become a customer. During the fourth interaction with your site from organic search, the user finally converted into a customer.

Exhibit 1

Attribution traffic sources

In this case, Google Analytics credits the sale to the organic search’s last touchpoint in this sequence. Even if the initial touchpoints were responsible for convincing the user to convert, the last touchpoint gets the credit nonetheless.

Different Attribution Models

In this example, the standard attribution model Google uses is called the Last Non-Direct Click, which gives credit only to the last non-direct channel. This might not be the best way for some to credit the sales because it disregards the other channels that could have influenced the decision of users to convert into your customers.

Thankfully, there are other attribution models available to help you better understand how each of your channels played a role in the conversion path:

  • Last Interaction Attribution – gives credit only to the last channel, direct or otherwise
  • Last Google Ads Click Attribution – gives credit only to the last Google Ads Click
  • First Interaction Attribution – gives credit only to the first channel in the conversion path
  • Linear Attribution – distributes credit across all channels evenly. As long as the user traverses through these touchpoints, Google Analytics will treat all of them the same
  • Time Decay Attribution – similar to the Linear model, but it gives more value to the channels closer to the point when a user converted into a customer
  • Position Based Attribution – gives credit mainly to the first and last channels while the channels in between split the remaining credit

The first four models only assign credit to a specific channel in the conversion path. The last three are fairer because they distribute the recognition across the different touchpoints the user went through in the conversion path.

Why Should You Use the Attribution Model?

As mentioned, the Google Analytics attribution model helps you make sense of your traffic based on which channels drive the most sales to your e-commerce business.

However, the more important question to ask is which attribution model you should use to determine the effectiveness of each channel in your path to conversion.

By default, Google Analytics shows you the Last Non-Direct Click for your website. This could be disadvantageous for marketers running paid and display ad campaigns for their websites. Whether users visited your site through your ads, this model will always favor non-direct click channels and credit them the sale.

At the same time, this doesn’t mean that you shouldn’t use this attribution model when analyzing your marketing campaigns. It depends on what channels you’re using, how you organized them in your conversion path, and which channels you want to prioritize measuring.

Using the correct attribution modes to measure your campaigns will better understand why they performed the way they did and what approaches you must take in your upcoming campaigns to improve conversions.

How to Measure Your Campaigns Using the Attribution Models in Google Analytics

Before you can analyze your campaigns using Google Analytics attribution models, you must do the following first:

  • Set up goals and transactions on your Google Analytics.
  • Use Google Tag Manager to label your campaigns and help you identify which ones are in Google Analytics.
  • Link your Google AdWords to Google Analytics if you’re running pay-per-click ad campaigns.

Launch your campaign once you’ve set these up and wait for Google Analytics to collect data from it.

Then log in to your Google Analytics account, go to Conversions > Multi-Channel Funnels > Overview, and filter the results to only show Transactions.

Exhibit 2

Multi-channel funnels

Next, scroll down to see the Venn diagram showing the overlapping channels users visited as part of their conversion path.

Exhibit 3

venn diagram of conversion funnels

The overlap among channels results from the default attribution model Last Non-Direct Click. Depending on your goals, the data you will see here may not reflect how your campaign went. 

The next step is to view the transactions using the other attribution models that can help measure your campaign correctly. Go to Conversions > Multi-Channel Funnels > Model Comparison Tool. 

From here, filter only the campaign you want to analyze. Then click on the drop-down menu to select the attribution model you want to use to view the results.

Exhibit 4

Measuring your google campaign

When analyzing the results, click on Source/Medium as the Primary Dimension to view all the different marketing channels you used in your campaign.

After choosing an attribution model, you can select another model for comparison. This is where the fun begins because you’ll be able to analyze the sources using different attribution models to measure their conversions and conversion values from each.

Exhibit 5

image of direct channel results

The direct channel produced over 7,000 conversions in the Last Non-Direct Click model in the example above. This means that more than 7,000 users converted into customers after typing in your site as the final step in their conversion path.

However, the channel got even more conversions in the First Interaction model with almost 8,900. It means these visitors turned into sales after typing in your URL as their first interaction with your site.

With a 26% difference in favor of the First Interaction model, you can conclude that the direct channel fared better when people visit your site by typing it in their browsers. From here, determine which part in your conversion path you advocated for this specific channel and find ways to double-down on it or keep it as is.

At the same time, “(direct)/(none)” could also mean that Google Analytics wasn’t able to track the traffic from this source properly. That means visitors could have gone to your site through channels not included in your campaign.

From here, you need to find potential traffic sources that could have led to conversions and tag them properly in your upcoming plan.

From the example above, we discussed attribution models measuring specific channels. But what if you want to analyze a campaign composed of multiple channels in your conversion path? Doing so allows you to see how the sequence of channels in your funnel affected conversions.

You can do this by using and comparing the Linear, Time Decay, and Position-Based models. These help you understand how effective your campaign is as a whole and how you can improve the different touchpoints comprising it to increase conversion rates.  

Exhibit 6

Linear and Time Decay models

In this example, we compare the Linear and Time Decay models. The difference across sources is not more than 7% except for “groups.google.com / referral” (13%). It means that this source is more valuable in the Linear model where all channels are treated equally.

The source is further away from the conversion point due to lower conversion and conversion values when looking at this source using the Time Decay model.  You could then say that the source belongs at the top part of your sales funnel when visitors are still learning more about you.

Conclusion

If you’re serious about your business, you must drill down into how your website generates conversions by analyzing your campaigns using the appropriate attribution model. It allows you to determine the effectiveness of your marketing initiatives and how each channel and source contributes as sales and conversion paths in your campaign.

While we’ve discussed the Google Analytics attribution model in-depth, there’s still a lot to learn regarding setting up your campaigns and interpreting the results you’ll get when you start comparing each one different attribution models.

So, if you want someone to guide you regarding attribution models, reach out to us at Romain Berg, and we’ll be more than happy to assist you.

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