Google Attribution: The Easy Way To Really Undestand Your Marketing Efforts

Google says goodbye to "last-click" attribution models with their new tool "Google Attribution". It is based on AI and machine learning, and it will help advertisers and marketers to improve their understanding of their customer journey.

Marketers have waited a long time for something like this to be included in the Google suite. The goal is to finally answer the question "are my marketing efforts paying off?" What is it that really influences customers to purchase, so I can focus on it?

Last-click attribution is arguably the most popular method of attribution when considering which effort has lead to a sale. Although there are a couple of alternative models, most marketers credit any sale to the last touch point, the last interaction of the customer with the company before a purchase.
There's no doubt that this strategy is not enough to understand how each customer's decision process happened. The last touchpoint can be completely random and have nothing to do with the moment when the customer made their mind.
We all know that email campaigns, referral programs, ads, reviews and other materials work together to generate conversions. A sale is the result of combined efforts. It doesn’t make sense for only the last touch point to get all the credit.

Related article: <a href="" target=_blank">Digital attribution is broken. Here's how to fix it.

With Google Attribution, marketers can evaluate the individual impact of each marketing action on each device and channel, in one place. Using machine learning and artificial intelligence, it claims to be able to make this very complicated problem not so complex. The amount of data marketers need to handle nowadays is a real headache:

“There has never been a more exciting time to be a marketer, especially online, because [brands] can access their customers at any moment throughout the day as they bounce across devices including tablets, mobile and desktop.

But this has created unprecedented complexity. There is more data, more platforms, more channels. On a daily basis Google Analytics processes half a trillion digital moments across devices. What we are trying to do is use tech and machine learning to help make ad platforms more useful, easier and better connected.”

(Google’s vice-president of product management Jerry Dischler)

Other similar services

Is Google the first company to come up with a convenient tool to track and understand multi-channel customer journeys? Not really.

Other companies and startups have developed similar tools, such as Adobe's Marketing Cloud, BrightFunnel, or Bizible. They all go beyond the last-click attribution model.

Here's a 2017 article by BrightFunnel announcing their own AI-powered marketing attribution, for example.

Despite these other tools being available, Babak Pahlavan claims other solutions are “difficult to set up, require an expert to upload data, lose track of customers when they switch between devices and are not well integrated with bidding tools”. All these, problems which Google Attribution allegedly solves.

How Google Attribution works.

Google Attribution is still on beta version, and it will be increasingly available for advertisers in the following months, so it's hard to get into details at this point, but this is what we know:

To start, Google Attribution is integrated with AdWords, Google Analytics, and DoubleClick Search, combining all the data obtained through all marketing channels in one place, with no additional cost. The attribution model of this tool tracks all the data it receives, from the first click to the last.

“We capture the clicks, as long as there was a click, we can, for example, say how many of the conversations were from the social channel,”
(Babak Pahlavan, Google’s senior director of product management for Analytics and Measurement)

Marketers can evaluate their marketing campaigns on Google Attribution by analyzing in one single space their strategy, how much they're spending, and what's the feedback. They will also be able to launch quick actions from Google Attribution itself, based on the results, to improve the performance of their campaigns.

Google Attribution's model uses machine learning to determine how much credit each touch point in the customer journey deserves. In order to provide this information, it analyzes the individual patterns of behavior of customers, comparing those that lose interest to those who end up making a purchase. The results are meant to be precise, so marketers can direct their actions more accurately.

Attribution 360

The Google Attribution enterprise version is called ‘Attribution 360’. It is said to connect with even more Google products, such as DoubleClick Campaign Manager, it monitors TV ads as hey air, and the reports and data import functionalities are more sophisticated. Google Attribution, on the other hand, is still pretty powerful and will be available for free for all advertisers.

Offline attribution

Google is also trying to tackle offline attribution, measuring TV ads as they air, store visits, and apparently, also credit card purchases, but only in the US. Google captures about three-quarters of the total credit and debit card transactions in the country, allowing retailers to measure their in-store revenue.

"We want to help consumers online find what they are looking for in the physical world."

(Jerry Dischler, Google)

So far, Google has found that "consumers who click on a Google search ad before visiting a store are 25% more likely to make a purchase and spend 10% more on average." (Marketing Week)

According to a case study by Virgin Holidays, the brand doubled profit from its search campaign when considering both online and store sales, not just online sales.

To sum it up:
By using Google Attribution, marketers will soon have a clearer picture of their customer journey, in a tool that is said to be very easy to use, and free.

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