A Definitive Guide to Google Attribution

When Google announced that it will be releasing a free, scaled-down version of its enterprise-level Attribution 360 platform, it brought a sigh of relief to many marketers in the industry. With the new free version of Google Attribution, the company is basically seeking to introduce attribution to the masses just as it did with web analytics over a decade ago. Interestingly, there is no need to run a further setup to make use of this new release as it just makes use of data already available through other Google products, as already mentioned below.

Basically, this tool will take the data and features from DoubleClick, Analytics, and Adwords to combine them into a single platform that will allow marketers to effectively integrate their reports without the need of going through the stress of tagging and monitoring performance on a single platform. Contrary to general perceptions, this new form of attribution does not apply only to marketing channels such as display and PPC but it also applies to virtually every channel including direct traffic, social media, affiliate marketing, and organic search.

Ultimately, Google Attribution makes use of other products from Google to provide workable insights into the purchase journey of the customer. Afterwards, other products/programs such as DoubleClick or Adwords receive these insights to support bidding decisions. Before getting involved with Google Attribution, here are some important factors to consider.

More visibility on gateway terms

Under a Last-Click Attribution model, there are keywords that wouldn’t necessarily be given credit despite assisting in driving a sale. For instance, a customer or visitor may choose to use the keyword of a certain product to find a brand or product but may not complete the purchase at that very point in time until a later date. And when he returns, he may rather decide to use the brand term to complete the purchase. Under this model (Last-Click), no credit will be assigned to the product term for the sale even after making a significant contribution to the final conversion.

This is part of the “gateway terms” marketers experience in paid search with this model. But with the new Google Attribution model, businesses will gain more visibility on these terms. Attribution will expose the full scenario to brands and then establish more intelligent judgments that will not only restructure the “gateway” terms but also fit into the organization’s driven value and keyword strategy.

Easier content optimization

Marketers would surely find it easier to get their user experience optimized across each device once they understand how their customers engage with their brand across several devices. This implies that businesses can begin to strategize and organize their content structure to proper optimization for each device. Optimizing content in such a manner can go a long way in helping to maintain the dialogue and engagement they require with their audiences while they move from one device to another.

The elimination of “Last-Click”

In a bid to better reflect modern search habits and do away with ‘last-click’ attribution from AdWords, Google has been working assiduously to transform its platforms. Somehow, the release of Google Attribution marks the end of the reign of the Last-Click model, as suggested by many. Google Attribution is driven by the motive to allow users (marketers) to get used to the full customer conversion journey across all channels and precisely identify the various touchpoints customers interact with from their first engagement to the final conversion stage.

With this new attribution model, marketers get to fully understand how digital channels work thereby giving them the opportunity to holistically think about their central digital strategy necessary for enhancing integration between mediums, devices, and channels. Rather than simply default to the former attribution model (Last-Click), marketers can use this new Google Attribution model to ensure that every channel is assigned with its due credit for each sale, based on the exclusive nuances and habits of consumer behavior that applies to their brand.

Machine-Led Regression Attribution

Just so you know, some versions of attribution have already been provided in other products by Google such as Analytics’ Multi-channel Funnel reports. However, it’s important to understand that these products are based on defined attribution models like last click, first click and linear. Now based on a website’s own data, Google is now giving users the ability to make use of machine learning to analyze what works and what doesn’t and effectively compare purchase paths. Thanks to the introduction of ‘data-driven attribution’, Google Attribution has now taken a new leap toward achieving better leads.

Unlike the ‘regression’ attribution model, data-driven attribution basically seeks to address time which is the major problem with the former model. Rather than employ the historical data to define the weighting of credit that is distributed among touchpoints, the data-driven attribution model seeks to be much more accurate and specific by eliminating those lapses that have made regression modeling less-significant.

In a bid to solve the problem of waiting a long time to collect data, calculate models, and obtain relevant insight, Google Attribution has provided a more precise attribution model that only requires data to provide relevant insight to enhance customer and marketing activity of a business. This has helped to eliminate the need for the manual effort and change user behavior over time.

Not so perfect

Though the introduction of Google Attribution tends to present a significant leap forward, marketers are also cautioned to tread softly as it isn’t without some flaws. As a matter of fact, there are still certain provided models that fail to present the full picture. When an ad is loaded, some models would include “post view” but this may not necessarily be the case when it’s seen. Other models, may fail to incorporate the number of times users view content from channels such as display while focusing strictly on post click activity.

This implies that your reports could present a false sense of a channel working in post view which was never viewed by the user. Also, there are some attribution models that are finding it difficult to fully incorporate cross device attribution. If a user is signed into the platform such as Twitter or Facebook, cross-device activity may only be reported in attribution models. In most cases, attribution wouldn’t necessarily displace cross-device activity between users on Facebook via mobile or on Google with a desktop except the email address used to get them signed in to their Facebook account and Android account correspond.

In case you do not know, Google Attribution is currently in beta with the full version coming out soon. Nevertheless, it is important to understand that the product is already advanced particularly when it comes to applying insights directly to marketing activities from attribution analysis.