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How to Get Started With Data‑Driven Attribution in Marketing

Learn about the benefits of a data‑driven attribution model and how it compares with the last‑click attribution model.

Scratching your head at Google’s shift to data-driven attribution and why it's now the default attribution model in Google Ads and Google Analytics 4? We've got you covered with this beginner's guide. 

What is data-driven attribution? (DDA)

Google’s data-driven attribution (DDA) model analyzes your account data and gives credit for conversions across these marketing touchpoints:

  • Your brand’s website
  • Physical store visits
  • Organic search
  • Google Shopping
  • YouTube ads
  • Display ads
  • Discovery ads

Unlike rule-based models, which depend on static rules to attribute conversions, data-driven attribution takes a more holistic look at the entire customer journey and how customers interact with your ads.

Have you ever been stumped by these questions? 

  • Which ad gets credit if a customer interacts with multiple ads before buying? 
  • Does our marketing attribution cover the whole customer journey?
  • With today's privacy laws, how can we attribute credit to our digital advertising?

Google’s data-driven attribution model is the answer to helping advertisers understand which keywords, ads, or campaigns contribute the most to their advertising goals. Advertisers can use this attribution model to determine how much each interaction contributed to a conversion, also known as assigning conversion credit.

Benefits of data-driven attribution

Since attribution models help us understand which marketing campaigns perform better over others, what makes data-driven attribution better than last-click attribution? Let’s go over 3 benefits of using data-driven attribution.

Visualize marketing efforts across multiple channels

Research shows consumers interact with brands across a mix of 20 channels on average, and don’t always follow a neat path from awareness to purchase.

A person looking for a new pair of shoes might browse on Google Shopping while commuting, use Instagram to search for customer reviews, and eventually buy that pair of shoes at the nearest store a couple of months later.

But as a marketer, how do you know which campaign to attribute the sale to? Did the Instagram content or casual browsing on Google Shopping create the sale?

Data-driven attribution accounts for these nonlinear customer journeys and analyzes how customers interact with your brand before converting. It’s an attribution model that’s more suitable for people who research products and shop online today.  

Prove marketing return on investment (ROI)

Since business executives want to see every marketing dollar’s return on investment (ROI), accurate attribution becomes even more important to show which campaigns bring in the most revenue. 

A recent survey showed that nearly half of surveyed marketers claimed that ROI was the most important metric at the C-suite level. With Google’s data-driven attribution model, businesses can get access to more accurate attribution results that will show which campaigns were most effective, eventually boosting their ROI.

Optimize your marketing spend based on historical data

Accurate attribution doesn’t just help with strategic decisions. It also helps with day-to-day campaign optimization, like optimizing bids and keyword planning.

Let’s say you’re using Google’s search ads to generate leads for your freelance design services on 2 target key terms: freelance web designer portfolio and freelance web designer for small businesses. With the data-driven attribution model, you can track which ad is more effective at encouraging people to book a consultation.

For example, you may find that customers were more likely to book a consultation if they first clicked on the freelance web designer portfolio ad and then the freelance web designer for small businesses ad. Here the data-driven model assigns more conversion credit to your freelance web designer portfolio ad campaign. With these insights, you can know which ads are more effective for your business, helping you optimize marketing spend.

How does a data-driven model compare to a last-click attribution model?

In April 2023, Google removed first-click, linear, time-decay, and position-based attribution, leaving last-click attribution and data-driven attribution models for advertisers. Let’s compare some differences between the 2 attribution models and understand why Google has made data-driven attribution the default attribution model.

Unlike last-click attribution, DDA doesn’t use fixed rules

Traditional attribution models like first-click attribution and last-click attribution follow fixed rules and assumptions for conversion tracking. With last-click attribution, for example, the last marketing touchpoint a user interacts with before converting always gets the credit, which ignores the impact of earlier touchpoints before the conversion.

In comparison, data-driven attribution analyzes your Google account data to attribute which interactions influenced a conversion. DDA analyzes how customers previously interacted with your brand across devices and channels and whether or not they converted. This is why, overall, DDA is better at letting you track consumer engagement than last-click attribution.

DDA credits conversions to multiple marketing touchpoints 

Using last-click attribution means you’re giving all the credit to the marketing touchpoint before the sale, which ignores brand awareness efforts. Consumers are less likely to buy a product online if they are unfamiliar with a brand or believe it is dishonest. Online research plays a significant role in influencing purchases, and understanding how your brand awareness campaigns perform is just as important as conversion-focused campaigns. 

Data-driven attribution accounts for this attribution gap by looking at how the entire customer journey leads to a single conversion action, instead of assigning all the credit to the last touchpoint before conversion as in last-click attribution. This holistic attribution approach in data-driven attribution more accurately represents how people browse across channels today. 

You may have data requirements to use the data-driven attribution model

For DDA to work effectively, Google says your account needs 3,000 clicks and 300 conversions over the last 30 days to use the data-driven attribution model.[MR1] [JP2]  In comparison, last-click attribution is always available regardless of how many clicks or conversions you have in your account.

Three steps to get started with data-driven attribution

Now’s the best time to adapt to these changes and familiarize yourself with data-driven attribution. Here are 3 steps to get started.

Step #1: Understand your marketing goals and how they relate to business objectives

It’s essential to understand your marketing goals and how they affect your attribution strategy. For example, do you want to know how your brand awareness efforts can complement your conversion-focused Google Ads to help drive business revenue? Or how much your how-to videos influence your customer’s decision to book a discovery call?

Examples of specific marketing goals:

  • Improve conversion rate from Google Ads by 5% each month over the next 6 months.
  • Increase organic website traffic by 10% over the next year.

Going through this essential step gets your clients, stakeholders, and team members aligned around the same goal. It’s easier to connect marketing analytics to business results and get support for access and decision-making.

Step #2: Identify your conversion path and marketing touchpoints

Once you’ve nailed the bigger-picture goal, it’s time to get to specifics. Consider questions like:

  • How do visitors interact with your website?
  • How do customers feel at each stage of the customer journey?
  • Which customer touchpoints drive more conversion actions?  

Besides looking at your platform data and customer journey map, consider supplementing your data-driven attribution efforts with “How did you hear about us?” surveys. These surveys help you understand which marketing touchpoint was the most influential in getting a customer to convert, sign up for your service, or buy a product.

Step #3: Start collecting data across your marketing channels

Data-driven attribution requires proper tracking. First, ensure you’ve set up conversion tracking on your website, Google Ads, and Google Analytics 4 to collect conversion data on how your customers behave on your marketing touchpoints.

Consider creating UTM links in your Google Ad campaigns to track how many visitors come from that link and where they go after interacting with your ads. Once done, enable data-driven attribution in Google Analytics 4 and Google Ads by following these steps from Google.

Make smarter marketing decisions with data-driven attribution

Google popularized last-click attribution with Google Analytics in the early 2000s. But customer journeys now involve multiple channels and devices, and last-click attribution may not capture all the nuances of multichannel conversion paths.

Data-driven attribution is Google’s answer to enhancing customer journeys and optimizing changes in browsing behavior with machine learning. With this guide, you have a starting point for your DDA strategy.

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