As the business world continues to become more “data-driven”, organizations are increasingly turning to platforms like Google Analytics to determine which marketing channels are most successful at driving results for their business. And, for good reason! Google Analytics has a diverse collection of reports and tools that can collectively help businesses streamline their digital marketing to both increase ROI and cut waste.
Arguably the most powerful of these reporting tools are the Attribution Modeling reports. These unique reports provide website stakeholders with the ability to assess the impact that different marketing channels/sources/mediums have on their on-site conversions, making it much easier to determine a digital marketing mix with the best possibility for increasing brand revenue.
While all this sounds great, the adoption of attribution modeling by users of Google Analytics is, unfortunately, surprisingly low. From our team’s experience working with thousands of websites owned by hundreds of brand partners, we’ve found that most digital analytics/marketing stakeholders have never heard of the Attribution Modeling reports, or (if they have) feel that they are not relevant to their specific business model.
The latter scenario is especially prevalent with organizations that have historically sold products offline, such as those in the CPG (consumer packaged goods) and FMCG (fast-moving consumer goods) space. Instead, we commonly see users in these organizations opting to make business decisions based on metrics that are featured in Google Analytics’ other collections of reports, surmising that the Attribution Modeling reports are better suited for businesses that have an eCommerce component to their websites.
In reality, Google Analytics’ Attribution Modeling offerings can be incredibly insightful for businesses of all types, even if there are no product sales actually taking place on the website. The key to making these reports valuable for non-eCommerce businesses, however, is to have a good understanding of the data they can provide and knowing the “best” way to use them based on the organizational/site goals for the specific brand.
Understanding the Concept of Attribution in Digital Analytics
Before we dive into the value that the Google Analytics Attribution Modeling reports can bring to non-eCommerce businesses, it’s first important to have at least a baseline understanding of attribution in general.
Now, keep in mind that attribution is a concept that would be worth multiple individual articles by itself, and so I won’t try to write the entire “Guide to Attribution” right here. However, given the low usage of the Attribution Modeling reports in Google Analytics, it’s important that we at least align on the basic definition of attribution in order to properly address its importance as it pertains to digital analytics.
The general definition for attribution is “the action of regarding something as being caused by a person or thing.” Translated over to digital analytics and marketing, the concept is most commonly used to describe the relationship between conversions on a website and the marketing channels/sources/mediums/campaigns that “cause” those conversions.
In reality though, you and I both know that a single marketing campaign typically doesn’t directly cause a conversion. No matter how hard you try, visitors to your website won’t do what you want them to do simply because a marketing creative told them to act. There are any number of influences on a user’s behavior other than just your marketing activities, and so saying that a conversion on your site was “caused” by a single, specific piece of marketing is likely false.
As a result, I would suggest that the data you find in Google Analytics’ Attribution Modeling reports aren’t showing you the marketing activities that caused conversions. Rather, they’re giving you the ability to identify which marketing channels/sources/mediums have been best at delivering visitors to your site that have ultimately completed an on-site conversion activity.
This definition paints an accurate picture of the type of data you can get from the Attribution Modeling reports in both eCommerce and non-eCommerce scenarios. In order to better understand the difference between attribution on eCommerce sites vs. non-eCommerce sites, however, we also need to discuss what a “conversion” represents on each type of site.
The Difference in ‘Conversions’: eCommerce vs. Non-eCommerce
Contrary to popular belief, a conversion on your website doesn’t have to be an eCommerce transaction. In reality, a conversion can occur whenever one of your site visitors completes any key activity on your site—but typically one that is related to your site or business performance goals.
For eCommerce businesses, it makes complete sense that a conversion would include transactions, given the link between a website purchase and the financial strength of the brand.
However, for non-eCommerce websites, there are an almost unlimited number of non-financial conversions that you could have on your website which are completely unrelated to a consumer purchasing a product. Some of the most common ones that we help our CPG/FMCG/multi-brand partners to implement include:
- Newsletter/email signups
- Coupon/offer downloads
- Number of pages viewed during a session
- Total duration of a website session
- Webinar/conference registrations
As a non-eCommerce brand stakeholder, it’s important to understand exactly which activities are important enough to your brand that they should be counted as conversions on your website. Once you know which activities those are, then your next step will be to ensure that these activities/events report correctly as conversions in Google Analytics.
For non-eCommerce conversions, this means you’ll need to set up each conversion event as a separate “Goal” in Google Analytics.
Once you have each of those conversions set up as a Google Analytics Goal, now you’re ready to experience the true power of Google Analytics’ Attribution Modeling reports.
Realizing the Power of Attribution Modeling for Non-eCommerce Brands
For a true example of just how powerful the Google Analytics Attribution Modeling reports can be, let’s look at an example of a non-eCommerce CPG/FMCG website with only a single desired conversion: getting users to sign up to an email newsletter via an on-site registration form. On this particular site, email newsletter sign-ups are vital to overall brand success, as the newsletters are a key way for the organization to build brand loyalty by distributing coupons and special offers that (they hope) will ultimately increase in-store purchases of their products. Offline purchase data shows that their strategy is working, too, as in-store purchases tend to spike 1% to 2% in the days following a new coupon being sent out to their subscribers.
For this brand, the Google Analytics Attribution Modeling reports give them the information to determine which marketing campaigns are doing the best job at bringing users to the site who will ultimately sign-up for their email newsletters. Armed with this information, they are then able to streamline their marketing activities, increasing spend on campaigns that are maximizing signups, and decreasing spend for (or completely eliminating) those campaigns that are falling flat.
This is the type of “win” that we see our partner brands achieve every single day by using Attribution Modeling in Google Analytics. However, it’s important to note that the specific brand in the above example had a lot of prior experience utilizing the Attribution Modeling tool inside Google Analytics, and had already determined which specific Attribution Model was right for their brand and organization.
I point this out because there are actually seven different “built-in” attribution models that you can apply to your conversion data in Google Analytics. And depending on which one you choose, you can get wildly different results for the reported effectiveness of individual marketing channels/sources/mediums. For reference, the seven built-in models are:
- Last Interaction: Gives 100% of the credit for the conversion to the last marketing touchpoint the user interacted with to arrive on your site. If the user last arrived on your site by directly entering a URL in their browser (or clicking a bookmark), then that “Direct” touchpoint will be given 100% of the credit
- Last Non-Direct Click: Gives 100% of the credit for the conversion to the last “non-Direct” marketing touchpoint the user interacted with to arrive on your site. This model removes the case of a user directly entering a URL in their browser, unless it was the only step in the user’s journey to your site before converting
- Last Google Ads Click: Gives 100% of the credit for the conversion to the last click on a Google Ads ad that the user made to arrive on your site. If there are no Google Ads clicks in the user’s journey, then credit is assigned according to the “Last Interaction” model instead
- First Interaction: Gives 100% of the credit for the conversion to the first marketing touchpoint the user interacted with to arrive on your site. If the user first arrived on your site by directly entering a URL in their browser (or clicking a bookmark), then that “Direct” touchpoint will be given 100% of the credit
- Linear: Gives equal credit to each marketing touchpoint that the user has interacted with in order to arrive on your site prior to completing the conversion. For example, if the user initially found your site via a Google Ads ad, then returned via an organic search result for your site, then returned again by entering your site’s URL directly into their browser – then each of those three marketing touchpoints would be given 33% of the credit for a conversion.
- Time Decay: Gives greater credit to those marketing touchpoints that happened more recently and closer to the conversion taking place. Earlier marketing touchpoints continue to receive some credit, but the amount that they receive is reduced based on how far before the conversion took place that they occurred.
- Position Based: Gives 40% of credit for the conversion to the first marketing interaction, 40% of credit for the conversion to the last marketing interaction, and divides the remaining 20% of the credit between all of the other marketing interactions that occurred between the first and last interactions.
All these options can be a little overwhelming, right? Consider that, in addition to the seven “built-in” attribution models, you can also create your own “custom” attribution model based on specific conditions that you and your organization align on. And to make things even more complicated, some organizations will actually use a combination of multiple attribution models to determine the true effectiveness of their digital marketing on driving website conversions.
At this point, I know what you’re thinking. But, no, there’s unfortunately not a consistent answer to the question of “Which attribution model is best?” The right model for your organization will depend on a number of factors, including your individual brand/site goals and the digital marketing mix you’re using to drive users to your website.
Luckily, though, if your organization uses Analytics 360 (the enterprise-level version of Google Analytics), then you have another, better option for attribution modeling.
[VIDEO: How to Know if Your Organization is Ready for Analytics 360]
The ‘Better’ Attribution Option in Analytics 360
Data-Driven Attribution (DDA) is an Attribution Model that’s found only in Analytics 360, which is meant to alleviate some of the stress and confusion that comes with trying to choose the “perfect” attribution model for your brand. This is possible because the model is not tied to time-based or position-based marketing interactions (as with the other Attribution models that we’ve discussed so far).
Instead, DDA uses the actual conversion and marketing data from your brand’s specific Google Analytics property in order to design a customized Attribution Model for your business using internal algorithms. While this alone is a huge game-changer for your organization, there are several additional benefits to DDA that make it stand head-and-shoulders above Google Analytics’s built-in attribution models if you’re using Analytics 360:
- Allows you to include marketing/campaign data into your customized Data-Driven Attribution model from any Google products you’ve linked to Google Analytics (Campaign Manager, Google Ads, Google Display Network, etc.)
- Incorporates any cost data into your customized DDA model that you’ve uploaded using the “Cost Data Upload” feature
- Includes conversion path data in your customized DDA model from Multi-Channel Funnels
As you can imagine, the Data-Driven Attribution Model can give your team a much more actionable set of data that you can then use to make better decisions about where to invest your marketing resources. The only catch? Google has some pretty specific requirements for who can use the tool. Namely:
- Your organization must have a Google Ads account with at least 15,000 clicks on Google Search and a conversion action with at least 600 conversions within 30 days;
- Your Google Analytics property/view must have 400 conversions per conversion type with a path length of 2+ interactions within the past 28 days;
- Your Google Analytics property/view must have 10,000 paths in the selected reporting view (a single user can generate multiple paths)
These stringent requirements make it all the more important for you to begin identifying your website’s key conversions and start setting those up as Goals in Google Analytics as soon as possible. The faster your Goals are set up and running, the faster you’ll be able to start taking advantage of the powerful DDA model to maximize your marketing ROI and cut waste.
Taking the Next Step
Attribution Modeling is already one of the more complex topics in the world of digital analytics. But it can be even more confusing for CPG and FMCG organizations who traditionally sell products offline instead of directly through their websites.
If you’re a stakeholder for a non-eCommerce site, it’s not difficult to take advantage of Google Analytics’s powerful Attribution Modeling reports to drive actionable insights from your digital marketing data. To get started, have a discussion with your team to identify the key activities that you consider to be “conversions” on your site, and then set those conversions up as Goals in Google Analytics.
Taking these simple steps will give you access to all the different Attribution Models that are available to you in Google Analytics so that you can find the one that’s the best fit for you and your brand.
Finally, if you’re a Google Analytics 360 organization, then the decision gets even easier since Google Analytics’s Data-Driven Attribution uses your site’s specific Google Analytics data to produce an Attribution Model that customized for your individual brand and website data.
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