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July 8, 2021 (Updated: May 18, 2022)
Utilizing Google Attribution enables your business to monitor touch points across campaigns and devices to determine the exact path a consumer takes to reach conversion. Similar to Google AdWords and Google Analytics, Google Attribution goes one step further to help you understand your customers’ mindset and improve your ad campaigns for better performance.
Although still in beta mode, Google Attribution brings machine-learning attribution to customers, allowing them the ability to accurately report conversion totals without duplication across all digital channels. Businesses are able to see a consistent and consolidated view of the performance of their advertisements and searches. You can use this information to better understand your brand’s journey and build better ad campaigns for the future.
Google Attribution is a free Google product within Google Analytics that measures conversions across various channels. Marketers typically reach potential customers in various ways — display ads, videos, searches, social sites, and on their site or app — and from multiple devices. In order to accurately attribute a sale, you need to track each touch point along a customer’s journey from interest in a product to the actual purchase. Google Attribution makes this process easy and effective, delivering insights to help you understand and improve your marketing efforts.
Google Attribution is an improvement over previous attribution options, such as Google Analytics attribution or Google Ads attribution features, because it offers multidevice and multichannel conversion tracking.
One of the problems Google ran into when trying to track conversions is the issue of tracking across various devices. People don’t stay logged into Google in the way that they do with Facebook, which has a single sign-on (SSO) and offers much better attribution capabilities.
Lewis Brannon, Paid Search Manager at CPC Strategy says, “It’s interesting in the digital world because SSO is key to being able to reach users as opposed to being able to reach cookies. There’s a big distinction between cookie-based targeting vs. user-based targeting.” The problem is that Google has always targeted searches, keywords, or browsers using cookie information, which leads to inaccurate attribution.
For instance, suppose Linda clicks an ad for bikini bathing suits while she’s on her laptop. Advertisers will now use this data to target her with similar and related ads. But then suppose Linda’s husband John gets onto her laptop to research windshield wiper blades for their car. Not only will John be targeted with bikini ads, which are not of interest to him, but because of John’s activity, Linda will be targeted with advertisements for windshield wipers and car parts. Rather than targeting the user with an SSO, advertisers are instead targeting the browser that performed the behavior.
However, Facebook, with its SSO capabilities, would be able to target Linda and John separately and individually, regardless of whether they are on Linda’s laptop, their own phone, a computer, or tablet. “That single sign in gives advertisers the ability to target individuals rather than targeting browsers based on cookie data,” Brannon says.
Google is getting better at SSO targeting, with a sign in to Google or Gmail becoming common. However, if an individual doesn’t use the Chrome browser, Google is less likely to obtain that individual’s data.
Utilizing SSO, Google is able to use its data-driven attribution in Google Attribution to track conversions across multiple devices and interactions. “Prior to Google’s advances in attribution, we couldn’t really trace the customer journey; we were stuck with last-click only. Now we can do a better job of seeing the holistic view of our campaigns and how they work together,” says Brannon. He adds, “With the data-driven model and machine learning, Google is trying to determine which of those touchpoints was the most valuable and will distribute the conversions in a way that assigns the proper value to each one.”
Google Attribution aims to solve five main problems that marketers face:
To fully understand Google Attribution and the problems it solves, you must first grasp the concept of attribution in marketing. Google defines attribution as: “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 [SIC] on conversion paths.”
In short, attribution helps advertisers know which sources brought in conversion for their brand. In the early days of internet advertising, it was easier to follow the path a customer took from advertisement to purchase since there were fewer advertising channels. However, today we have a variety of marketing options, including social media posts, organic searches, PPC ads, videos, email marketing, and other advertising channels. Therefore, a consumer may see a product on several different platforms before converting.
For instance, a consumer may see a video on his Facebook timeline, but not click. Later, he might receive a promotional email from the company, which prompts him to search the product on Google. He may finally convert after reading about the product’s features on a blog post. So, which source should be attributed with causing him to make the purchase?
Why does it matter? Clear attribution of a product’s sale is key to a company’s marketing success and future marketing strategies. Many businesses, even ones that gather an exceptional amount of analytical data, have trouble assigning attribution for a sale. That’s where Google Attribution comes in. Google Attribution takes all of a consumer’s activity into account to gain an accurate understanding of which channels are responsible for the sale.
Prior to the introduction of Google Attribution, marketers relied on rules-based models to understand attribution data for conversions over multiple channels. Google Analytics offered five attrition models following this rules-based format. What is an attribution model in Google Analytics? The attribution models in Google Analytics included:
With rules-based models, no matter the type of conversion or customer’s path of interactions, you end up missing important data that is useful in planning your marketing strategy. Rather than focusing on the consumer’s actual behavior, rules-based models base their results on the rules set up in their attribution blueprint. The attribution model in Google Analytics, however, addresses the deficiencies in rules-based models.
Google Attribution’s data-driven model uses machine learning to properly apply credit across all converting and nonconverting paths. The model attempts to determine how touch points may increase the chances of a purchase following a certain sequence of exposures. It uses custom probability modeling to assign fractional credit along each point of a customer’s interactions. With Google Attribution, you can accurately compare the paths of customers who convert with those who don’t, enabling you to adjust your marketing campaign to represent that data.
Google Attribution is currently a beta feature in Google Analytics. In order to effectively use Google Attribution, the platform requires sufficient data. The modeling works at the conversion action level. To be eligible for data-driven modeling, a conversion action must have a minimum of 15,000 clicks and 600 conversions in a 30-day time period. Then, the model will record 30 straight days of information prior to reporting it. It’s possible to set up a micro-conversion situation within your ads if none of your conversion actions meet this criteria. You can then use this smaller sampling to gain an understanding of how the data-driven model of Google Attribution works.
You can access Google Attribution through your Google Analytics reporting view. To get started, follow the steps below.
You will not see immediate data in your attribution project. Google requires a minimum of 72 hours to gather the data for the first model. It can take up to 30 days to get a complete picture of the attribution model; however, results are mostly dependent on your ability to create conversions. The more conversions your site generates, the more data is available for processing.
Google Attribution reports conversion totals across digital channels without duplicating results. It not only provides consolidated reporting from multiple channels, it can use goal conversions and e-commerce transactions from multiple Google Analytics properties in one attribution project. Once the data is harvested, you’ll have access to the following reports for their data-driven attribution models:
Because Google Ads (previously AdWords) and Google Analytics use different attribution models, you may experience inconsistencies in your reporting related to the origin of the conversion.
How does Google Ads data-driven attribution give credit for conversions? Google is working to make Google Ads more flexible from its original last-click platform. In 2017, they moved away from converted clicks to conversions, since conversions work better with attribution modeling types that go beyond the last click modeling. They did show click and conversion data from Analytics, but users couldn’t switch the conversion reporting and bidding model from last click until that change was made.
The attribution tool introduced in Google Ads in 2014 is for search funnels only. This means that it only takes into account interactions on multiple ads but does not consider different channels. Therefore, Google Ads only takes into account the ads in your campaign, while Google Analytics uses other sources, including organic searches. There is also the issue of how conversion paths are viewed. In Google Analytics, all ad conversion paths — keyword path, ad group path, and campaign path — are based on clicks alone, whereas in Google Ads, conversion paths are based on both clicks and impressions.
Google Analytics and Google Ads are integrated to offer users the best of both worlds. Google Ads advertisers can see paid search and Display Network data through the multichannel funnel reporting tool and in the attribution model comparison tool in Analytics. However, Google Attribution offers more details and more touch points through its data-driven model.
The data-driven attribution model of Google Attribution offers much more insights for advertisers than was previously available. You can see how consumers interact with different touch points and then use that data to properly optimize ads and keywords within your web content and blog posts to generate greater ROI for all of your Google campaigns.
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