When you finally convert a potential customer into an actual customer, they have come to the end of a journey; sometimes a long journey. Where that journey ended, we now know. What we want to know for future campaigns is the path they took that led them to the excellent decision to do business with us.
If we could have a short conversation with each new customer, we’d ask them, “What finally did it for you? What led you to us?”
“Well gee, I think it was that giant chicken on your roof and as I was in the mood for chicken, I pulled into your drive-through.” That’s good information. But what it doesn’t credit is the television ads, the Facebook ads, the coupons in the Sunday paper. What impact did each of those have on our customer’s ultimate decision?
When we have a multi-layered digital marketing campaign, we want to know how much influence each had—if any—on our customer’s journey to us. Maybe they never saw the coupons or the television ads and were instead given a great impression from our Facebook ads which followed them around for a week enticing them to “Eat Chicken!”
Under the default Google attribution model, whichever channel a user touches on their last, non-direct interaction before converting is assigned 100% attribution. That’s the giant chicken. But that doesn’t tell us the whole story.
The big selling point of Google’s free attribution tool is to help marketers make more informed bidding decisions in Google Ads campaigns by letting them capture an ad’s contribution at any point along the conversion path and not just the last click.
It pulls in data from Google Analytics and Google Ads and applies the advertiser’s chosen attribution model, including Google’s machine learning-powered model called data-driven attribution, across channels and devices. That data can then get fed back into automated bidding strategies in Google Ads.
With Google Attribution, now advertisers can finally understand how each of their marketing efforts works together.
Integrations with AdWords, Google Analytics, and DoubleClick Search make it easy to bring together data from all your marketing channels. The result is a complete view of your performance.
Google Attribution also makes it easy to switch to data-driven attribution.
What Is Google’s Data-Driven Model?
Unlike rules-based models, data-driven attribution uses machine learning to evaluate all the converting and non-converting paths across your account and identifies the proper credit for each interaction.
The model considers:
· Number of ad interactions
· Order of exposure
· Ad creative
· Other factors to determine which keywords and clicks are the most effective at driving results
This is Google’s attempt to build an all-encompassing attribution measurement that can be applied to campaigns and immediately start providing actionable data.
In other words, data-driven looks at all the clicks on your search ads, then it compares the click paths of customers who convert vs. the click path of customers who don’t.
The model identifies patterns of clicks that lead to conversions and then they basically overlay that onto your campaigns and tell you how valuable your campaigns are based on this wide array of search behavior.
Google announced in 2017 that they are getting much better at single sign-in targeting. If you’re logged into Google (for example through your Gmail account) on your computer and your phone, then you’re a good target for Google advertisers.
As that pertains to data-driven attribution, the real benefit comes when Google is able to track conversions across multiple touchpoints and devices. 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.
With the data-driven model and machine learning, Google is trying to determine which of those digital touchpoints was the most valuable and will distribute the conversions in a way that assigns the proper value to each one.
It can take a little while before the machine-learning model has enough data to run up to full speed.
How Does It Work?
What makes Attribution stand out is that it gives users better visibility into the full customer journey across all touchpoints. This increased visibility helps users make more informed marketing decisions in an easy-to-use interface. There’s no additional setup or tracking required to start leveraging this feature.
It is a set of rules for assigning credit to the various touchpoints in the conversion path.
· Live Chat
· Pricing Page
A customer finds your website by clicking one of your Google ads. She returns one week later by clicking over from a social network. That same day, she comes back a third time via one of your email campaigns, and a few hours later, she returns again directly and makes a purchase.
In the Last Interaction attribution model, the last touchpoint would receive 100% of the credit for the sale.