How Google Analytics’ Attribution Beta Helps Digital Marketers
by Ron Dod
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Attribution is an essential component in marketing as it helps advertisers to understand the sources that resulted in a desirable outcome for a brand. However, in today’s omnichannel marketing ecosystem, obtaining clear information on attribution can be extremely challenging as multiple channels tend to contribute to advertising outcomes.
For instance, a consumer might see an ad for an exciting product on Instagram, but not convert. Later, that same individual might revisit the item through a promotional marketing email from the company. Several days on, they might decide to search the product through Google, click on an organic link and finally convert.
When establishing attribution, which source was responsible for earning the sale?
Gaining a clear understanding of which channels and campaigns are most responsible for a company’s success online is crucial for establishing profitable marketing strategies that will enable a brand to expand its efforts in the face of mounting competition. Yet, even businesses with exceptional analytics setups can have trouble determining how to attribute performance across a series of consumer interactions accurately.
However, Google is looking to remedy this problem.
In November 2019, Google Analytics users were greeted with a new reporting tab, donning the moniker “Attribution Beta.” While the new feature largely flew under the radar of many marketing news outlets, this new element is a massive development for advertisers as it gives them access to data-driven attribution models.
“The act of assigning credit for conversions to different ads, clicks, and factors along a user’s path to completing a conversion. An attribution model can be a rule, a set of rules, or a data-driven algorithm that determines how credit for conversions is assigned to touchpoints on conversion paths.”
For those fortunate enough to work with the extremely costly Google Analytics 360, data-driven attribution is not a new development. However, for those who are working with the traditional Analytics platform, it is truly revolutionary.
However, to understand why this is such a significant addition to the platform, it is first necessary to cover the rules-based models with which advertisers have been working.
Rules-Based Attribution Models
Most marketers have utilized Google Analytics’ Multi-Channel Funnels as a way of understanding the attribution data for conversions across multiple channels.
Through such rules-based models, marketers and advertisers can gain some insights outlining the buyer’s journey. However, because rules-based models are fixed in their ability to assign conversion credit, regardless of the type of conversion or nuances in user behavior, there is ultimately a considerable knowledge gap.
The fact is that rules-based attribution models ignore user behaviors and conversion types, focusing on the fixed rules in play.
Up until the inclusion of the new data-driven model (which will be explained momentarily), Google Analytics featured five attribution models, including:
First click: This model gives all attribution credit for conversions to the event that generated the first click.
Last click: This is the antithesis of the first click model, providing all conversion credit to the event which resulted in the last click.
Linear: The linear model distributes the attribution credit to all clicks in the path to conversion equally.
Time Decay: Here, conversion credit is time-based. The closer a click is to the time of conversion, the more credit it will receive. However, this model uses a seven-day half-life, meaning that clicks that occurred eight days or more before the conversion will receive half of the credit attributed to those that happened the day prior to conversion.
Position-based: In the position-based model, 40 percent of the attribution credit is given to the first click, 20 percent is provided to the last click and the rest is doled out to all other clicks that occurred.
There are evident shortcomings that result from a rules-based model. However, the data-driven attribution model that has been accessible to Google Analytics 360 users eliminates such deficiencies.
Data-driven attribution provides credit for conversions based upon observable data for each conversion type. Using the data harvested–in conjunction with machine learning processes–this attribution model calculates the contribution weight of each click based on the data available.
While advertisers have long been stuck with the rules-based model accessible through Analytics’ Multi-Channel Funnels, the new “Attribution Beta” tab gives analysts the ability to utilize data-driven attribution models.
Google Analytics Attribution Beta Explained
Google Analytics’ new data-driven attribution model is a machine learning system that evaluates the conversion and non-conversion paths in the buyer’s journey to improve how credit is given to specific events.
Through the Attribution Beta feature, Google is giving marketers a free cross-channel method for tracking conversions in a more accurate and informative manner.
Part of what makes this feature so superior to its rules-based counterpart is that Attribution Beta gives marketers enhanced visibility into the entirety of the customer journey, thereby enabling teams to make more informed promotional decisions.
As Google details on its Attribution page:
“The model incorporates factors such as time from conversion, device type, number of ad interactions, the order of ad exposure, and the type of creative assets. Using a counterfactual approach, the model contrasts what happened with what could have occurred to determine which touchpoints are most likely to drive conversions. The model attributes conversion credit to these touchpoints based on this likelihood.”
As a result of this more detailed and nuanced attribution model, advertisers can acquire a far more comprehensive understanding of how consumers interact with their campaigns and touchpoints. This enhanced clarity will give marketers the ability to better optimize campaigns and generate more significant ROIs.
Some of the notable features that Attribution Beta offers include a project-based UI that enables analysts to access insights across multiple Google Analytics properties and conversion types and new attribution reports.
The reports that marketers can access for their data-driven attribution models include:
Conversion paths: Details a user’s path to conversion.
Conversion path length: Helps analysts to understand the distribution of touchpoint counts.
Conversion lag: Documents the distribution of days to conversion across paths that convert.
Model comparison: Contrasts how alternative attribution models affect the valuation of the marketing channels.
While this is all likely very exciting for advertisers, it is essential to note that there are some requirements for harvesting the insights provided by the data-driven model of attribution.
Fortunately, there isn’t anything special that marketers must do to access this feature. However, since the model is data-driven, this means that the system requires a minimum volume of data before it can be accessed by users.
As Google notes, the minimum requirement to access data-driven attribution is 600 conversions within the past 30 days.
That said, it is important to note that eligibility for this feature is established by the data for each type of conversion, meaning that it is possible for marketers to access a data-driven model for some of their website conversions but not other types.
Moreover, to maintain access to a data-driven model, it is necessary that the system is continually fed an appropriate amount of data. Therefore, if conversions drop below the minimum amount mentioned above, marketers will no longer be able to access their data-driven reports until the requirements are sufficiently met once more.
How to Activate Attribution Beta
Gaining access to this awesome feature is simple but does take some time.
To access Attribution Beta, marketers must locate and click the Attribution Beta tab in the left menu bar. After being taken to the following page, select “Get Started.”
From here, marketers will choose the desired account, property and view. Afterward, click “Next.”
Now, establish the appropriate conversion types and click “Complete Setup.”
At this point, it just becomes a waiting game. It will take Google a minimum of 72 hours to harvest the necessary data for creating the first model. As this page notes, it can take Analytics up to 30 days to develop a “robust” model.
Again, while Google gives these timelines, access to a data-driven model is mostly dependent on the site’s ability to generate conversions for Google Analytics to process.
However, it should also be mentioned that since this feature is still in beta, it is likely that advertisers will rub up against its limitations. For instance, marketers cannot yet utilize Custom Channel Groups in various attribution models or access data pertaining to Google Ads clicks and costs. That said, these features will likely become accessible as the offering moves out of the beta stage.
The new data-driven attribution model in Google Analytics gives advertisers exponentially more insights into how buyers interact with their touchpoints and campaign assets. Through this system, promoters have the potential to optimize their materials to new heights and generate greater returns as a result.
Get your business or clients set up with Attribution Beta as soon as possible. Doing so could mean gaining a significant edge over the competition.
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Ronald Dod is the Chief Marketing Officer and Co-founder of Visiture, an end-to-end eCommerce marketing agency focused on helping online merchants acquire more customers through the use of search engines, social media platforms, marketplaces, and their online storefronts. His passion is helping leading brands use data to make more effective decisions in order to drive new traffic and conversions.
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