It can be argued that attribution is the most important tool for gauging credit in marketing, as it provides a holistic picture for marketers to understand which channels or campaigns ultimately led to a conversion.
Google Ads attribution models have a very strong influence over resulting conversion data. Google Ads provides us with a few different attribution models to determine how conversion data is tracked in an individual PPC campaign.
In the past, the Last Click attribution model was Google’s default. However, along with Google’s recent pivot from Universal Analytics to GA4, they have introduced a new default attribution model: data-driven attribution (DDA).
This model is significantly more nuanced than previous models, and it’s crucial that marketers understand how it works to get the most out of their conversion data. In this article, we’ll provide a refresher on previous models, explain how DDA works, and demonstrate how to add it to your current campaigns.
Limitations of Last-Click, First-Click, and Linear Attribution Models
Google’s last-click, first-click, and linear attribution models serve individual purposes. However, they also come with inherent flaws. Below, we’ll identify what worked and what didn’t.
- Last-Click: The Last-Click Attribution (LCA) model credits the conversion to whatever the last interaction was before the conversion occurred. Until recently, this remained the default model in Google Ads, despite typically not being an accurate way to track a user’s path to converting. First-Click: This model attributes the conversion to the user’s first interaction before converting. While helpful in crediting top of funnel strategies, it’s also not necessarily the most reflective of the user’s journey to converting. Linear: Linear attribution does take the user’s full journey through the funnel into account, but it spreads the credit equally over all the interactions. This can be inaccurate, especially when trying to determine what in particular is driving conversion success.
How Does Google Ads’ Data-Driven Attribution Model Work?
DDA provides intelligent solutions to the issues with the abovementioned models by considering the user’s full pathway interacting with your ads. Similarly to Linear attribution, DDA credits all of the user’s interactions on the way to converting. The difference is that instead of splitting the credit equally across all steps, it weighs which interactions impact your account’s overall goals most.
Key Characteristics
There are a few characteristics of DDA that differentiate it from other attribution models:
- DDA uses conversion data to determine how much credit each user interaction deserves for a given conversion. It analyzes the interactions your ads get on all Google platforms (Search/Shopping/Display/Video/Discovery) and identifies patterns with users who ultimately convert to identify which platforms are most likely to lead to a conversion. DDA implies more instances of partial conversions compared to Google’s other conversion models.
Data Requirements
Due to the more nuanced and analytical approach to DDA, there are some requirements that must be met in order to utilize this model:
- 3,000 interactions with your ads across all Google ads platforms (i.e., Search, Shopping, YouTube, Discovery, Display, etc.) At least 300 conversions over the last 30 days on the conversion action you’re trying to track
Benefits of Using Data-Driven Attribution
There’s much to be gained by utilizing DDA. The data tracking and analysis it provides give you the insight needed to make smarter decisions in your business’ PPC strategy. Below are some of the key benefits of making the switch:
1. Accurate Attribution
As discussed earlier, DDA provides us with the most accurate understanding of the significance of each step along the user’s journey from top-of-funnel to converting.
2. Making Micro Conversions More Visible
Micro-conversions, defined as actions that indicate a user is engaging with the content on your site and may be interested in becoming a customer in the future, are more easily traceable because partial credit for interactions besides a full conversion are assigned.
3. Improved Budget Allocation
Once you determine how different interactions contributed to the main conversion event, you can use that insight to make more educated budget allocations. For instance, if you see that interactions like creating an account or sharing a post are bringing in a lot of partial conversions, it may be wise to raise the budget of whichever campaign is driving those actions.
4. Data-Backed Decision-Making
DDA helps you to strategize more confidently because it provides you with the data to back up your decisions. Whether it’s adjusting bidding strategies, refining ad creatives, or optimizing landing pages, you can make decisions based on evidence in a way that wasn’t possible previously.
How to Set Up Data-Driven Attribution in Google Ads
We’ll walk you through a few easy steps to switch an existing conversion action to DDA. It’s important to remember that DDA is Google Ad’s current default for new conversion actions.
Step 1: Navigate to the Tools and Settings Menu in Google Ads
Click the “Tools and Settings” option in the top right corner of your Google Ads account.
Step 2: Select “Conversions”
Select the “Conversions” option under the “Measurement” column.
Step 3: Select Conversion Action
Click on the conversion action you want to update.
Step 4: Edit Settings
Click the “Edit settings” button in the bottom right corner.
Step 5: Select “Data-Driven”
Select the “Data-Driven” option in the Attribution menu.
Step 6: Save and Exit
All that’s left is to save your selection!
Choosing Data-Driven Attribution for Your Google Ads Campaign
Choosing an attribution model for your PPC campaign will depend heavily on your business goals and which conversion action you need to track.
If you’re looking for more accurate data on your customers’ pathway through the conversion funnel, we recommend taking advantage of Google Ads’ data-driven attribution to optimize your PPC strategy with more data-informed decision-making.
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