Dispelling Attribution Myths: Why Google Analytics, Google Ads Data Doesn't Always Match

Attribution isn't always easily understood, perhaps because many times the data in multiple platform do not match.

Brooke Osmundson, associate director of paid search at NordicClick Interactive, spoke about tracking and reporting ecommerce data during the virtual Paid Search Association conference on Friday.

The nonprofit organization held its second virtual three-day conference last week, with its third day focused on data, attribution and smart bidding.

Osmundson set out to to dispel several myths. One of the most significant is knowing when and why it’s okay that data in Google Analytics and Google Ads does not match. It's important to track more than revenue and assigned values, and assign different return on ad spend for key performance indicators for campaigns based on intent, Osmundson said.

The key is to not buy into outdated methods and myths -- especially when it comes to attribution, Osmundson said. She discussed one myth focused on the fallacy that Google Analytics tracking must always match Google Ads.

Her first tip points back to the basics, which she said are often overlooked. Marketers need to review and confirm all settings, whether in Google Ads or Google Analytics. A few settings need attention when considering “discrepancies,” including back windows, attribution settings, and multiple Google Attribution settings linked to Google Ads. Others might be filtered views in Google Analytics. These will not match if the marketer removes IP addresses, Osmundson said.

Consumers can have browser preferences to prevent Google Analytics from loading, which would prevent them from being tracked.

In an example provided by Osmundson, the conversion value in Google Ads shows a revenue value of $437,000 with conversions of a little more than 7,300. Looking at the same data in Google Analytics, the revenue is about $470,000 and conversions are just above 7,500.

“It begs the question -- which one is correct?” she said. “It depends on the model that portrays the most accurate depiction of the business.”

It’s all in the settings, Osmundson said. This specific client has their goals imported from Google Analytics, rather than having Google Ads conversions in the analytics platform. The difference is how Google Ads settings are different than in Analytics. It’s important to understand why the data doesn’t match what Google Analytics reports.

It’s also important to understand how Google Ads counts a conversion. If a consumer comes back to the same retailer and makes multiple purchases, Google Ads will only count one conversion for that person.

Google Analytics, by default, shows every conversion. A few key settings can make a big difference.   

Another tip, she said, is to begin reviewing different models to understand the complete picture, with Google Analytics default of the last non-direct click, compared with a position-based model.

It could become a tracking issue when marketers have multiple views into Google Analytics.nFor one client, Osmundson found six different views linked to the platform, which presents issues of duplication. It’s important to get these cleaned up, and the focus is not whether any of them are  right or wrong, but rather understanding which view is the most accurate.

While profit and income are important, it’s not always just about the revenue. Other aspects of the campaign are significant, such as the messaging and what leads to revenue. Knowledge of this gives marketers a better understanding of what influences the sale.

Consumers are not as loyal to brands as they once were, and it can take multiple messages and ads to trip a conversion.

What can marketers track, aside from revenue? Email sign-ups, sample requests, and initiating a chat are just a few, and all can influence return on ad spend, Osmundson said.

How do marketers assign value to these smaller initiatives? It depends on the company. For an email sign-up, marketers can assign a value. For example, each one might be worth $2, whereas catalog requests might be worth $5. Beyond these examples, it's important to assign a true lifetime value for individual companies.

If a marketer has monthly paid media costs of $50,000 and a last-click revenue goal of 150, this brings the return on ad spend to about 300%, she said, calling it a “blended return on ad spend.” Adding in all of the smaller engagements changes everything.

The incremental goals can build on the justification that the consumer will eventually make the purchase. In this instance, Osmundson addresses the search agency, but this could very well be used by marketers inside a company.

1 comment about "Dispelling Attribution Myths: Why Google Analytics, Google Ads Data Doesn't Always Match".
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  1. John Grono from GAP Research, February 23, 2021 at 4:43 p.m.

    I like to equate it to currencies.

    You can say "I have 100 dollars" ... but is that US dollars, Canadian dollars, AU dollars ... maybe Fijian dollars or even Namibian dollars.   The numberd can be very misleading as to the actual value,

    One other thing regarding attribution is to remember that correlation is not causation.   I market and marketing research that applies even more so when you are only analysing one of the verticals in the media spectrum.

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