The Guide to Data-Driven Attribution in Digital Marketing

When you’re using multiple marketing channels, how can you tell which ones are driving conversions?

If you’re asking this question, data-driven marketing attribution can help. Data-driven attribution uses machine learning to identify how much credit each of your different marketing channels should get for generating a sale, lead, or signup.

Data-driven attribution means you can accurately measure your marketing return on investment (ROI) and optimize your campaigns for the best results.

Join me as I look at how data-driven attribution works, how to manage it in Google Ads and Google Analytics 4, and the benefits of data-driven attribution for your business.

What Is Data-Driven Attribution and How Does It Work?

Data-driven attribution is an attribution model that uses machine learning to analyze your existing marketing data. It then uses this information to determine how much credit a marketing channel (or a “touchpoint”) should get for assisting a marketing conversion. 

By marketing conversion, I mean completing a specific goal like making a purchase, signing up for a webinar, or filling in a job application form.

Data-driven attribution is unique. This means the results you see will be bespoke to your business and the data you gather.

Let’s look at data-driven attribution in action.

Imagine you see an advert on Facebook promoting holiday trips. You go to the website and check out some of the trips on offer, and while you don’t buy, you decide to sign up for an account.

A few days later, you get an email showcasing some of the latest holiday deals. You take a look but still don’t buy.

A week later, you’re on Google and see a search ad promoting the same website. Temptation gets the better of you, and you finally book one of the short vacations you saw in the email.

The question is, which marketing touchpoint would get the credit for the sale? Facebook, the email campaign, or Google Ads?

There are a wide range of different attribution models out there that assign credit in different ways. More on those later.

The data-driven attribution model looks at each individual marketing channel in turn, analyzing your past data and assigning a weight depending on how much sway each channel had in influencing the conversion.

Some of the factors that data-driven attribution takes into account include:

The number of touchpoints

The number of times a customer has interacted with a specific touchpoint

The time between touchpoints

The types of touchpoints seen

The use of different devices (e.g. desktop, tablet, mobile phone)

The customer’s demographics, location, and purchase history. For example, if customers regularly buy after viewing an email campaign, data-driven attribution will give future email campaigns more weight

The fantastic thing about data-driven attribution is that because it uses machine learning, it’s constantly evolving. The more you use it, the more it understands your business, meaning better results over time!

Alternatives to Data-Driven Marketing Attribution

The data-driven marketing attribution model is a very recent development in digital marketing. Before it came to prominence, there were simpler attribution models that marketers could use to assess the customer journey. 

First-click attribution. This model assigns 100 percent of the credit to the first marketing touchpoint.

Last-click attribution. Also known as last-touch attribution, this model assigns 100 percent of the credit to the last marketing touchpoint.

Linear attribution. This model assigns equal credit to all the marketing touchpoints clicked on.

Position-based attribution. Also known as U-shaped attribution, this model assigns 40 percent of the credit to both the first and last touchpoints and splits the remaining 20 percent between everything else.

Time-decay attribution. This model gives the most credit to the last touchpoint and the least credit to the first touchpoint.

What are the benefits of data-driven attribution compared to these traditional attribution models?

While traditional attribution models are easier to set up and analyze, data-driven attribution is more accurate as it considers the whole customer journey. The traditional models often provide overly simplified reporting that doesn’t tell the entire story.

Data-driven attribution is seen as the future of attribution. As a result, some of the more traditional attribution models are being discontinued.

In October 2023, Google removed first-click, linear, time decay, and position-based attribution models from Google Ads and Google Analytics. It recommended that people use data-driven attribution moving forward, although last-click attribution was still an option.

Why did Google make the change? Google claimed that less than 3 percent of conversions in Google Ads used these models and that moving to data-driven attribution would make measurement simpler for users.

Google’s approach to data-driven attribution has received mixed responses from marketers, but it does mean more people can utilize the data-driven marketing model than ever before. I’ll show you how to use data-driven attribution in Google Ads and GA4 later in this article.

Why Data-Driven Attribution Is Everything for Digital Marketers

So, how can data-driven attribution help you if you’re a digital marketer? Let’s look at some of the benefits of data-driven attribution.

It Means You Can Effectively Measure ROI

Measuring ROI is a great way to understand which of your marketing channels are bringing the best results. However, many marketers find measuring it correctly to be a challenge.

For example, fewer than 20 percent of marketers measure their email marketing ROI, with 23 percent of marketers finding measuring social media ROI a challenge.

Data-driven attribution is more accurate than other attribution models. This is because it calculates the actual contribution of each marketing touchpoint rather than assigning credit based on a pre-defined rule.

As a result, you can easily see which marketing channels are leading to more conversions.

It Helps You Optimize Your Marketing Channels

When you use multiple marketing channels, you want to know which ones bring the most conversions. This means you can focus more of your time and budget on the high-performing channels and shut down the poor-performing ones.

Data-driven attribution makes it easy to see which marketing channels are most effective and helps you make better business decisions.

It Provides Valuable Insights into Customer Behavior

The data-driven attribution model lets you easily analyze the data from all the touchpoints a customer has with your brand, from website visits and ad clicks to email opens.

This helps you identify patterns and trends and see all the different ways customers interact with your brand.

For example, let’s say a customer who converts after seeing an ad on Facebook is more likely to visit a specific page on your website before making a purchase. If your Facebook ad doesn’t already link to this page, redirecting it will likely increase your conversion rate.

Data-Driven Attribution in GA4

Earlier in 2023, marketers had to make a move from Universal Analytics (UA) to Google Analytics 4 (GA4).

If you want more details on the changes, check out my article: GA4 vs Universal Analytics.

The GA4 migration provided a significant advantage to users—it made data-driven attribution more readily available.

Before the launch of GA4, only a select few digital marketers could take advantage of data-driven attribution. They had to:

Be a Google Analytics 360 user

Have a Google Ads account with at least 600 conversions over the last 30 days

Meet the minimum conversion threshold over the space of 28 days

GA4 eliminated these requirements. This meant all users could access data-driven attribution regardless of the number of conversions or whether they had a Google Ads account.

Google Analytics 4 also offers cross-channel data-driven attribution, which takes data-driven attribution one step further. While data-driven attribution assigns a value to different touchpoints, cross-channel data-driven attribution looks at how different marketing channels work together and influence each other.

This is great from a marketing perspective as it provides additional insight into how different marketing channels build awareness and the dependencies between them.

Setting up Data-Driven Attribution in GA4

To set up data-driven attribution in GA4, you’ll need to start by setting up your goals so you can track conversion data.

Data-driven attribution is now the default attribution model in Google Analytics. You can check your settings by accessing the Admin panel and clicking Attribution Settings.

You can choose the channels that receive credit, as well as the conversion window. This determines how far back in time a marketing touchpoint is eligible for credit.

Once you’re happy with the settings, you can access the data-driven attribution report by going to Advertising and Attribution.

It may take up to 24 hours before you start receiving data.

Data-Driven Attribution in Google Ads

Data-driven attribution is also an option in Google Ads.

Let’s say a customer sees an ad for your business on YouTube and visits your website. They then see remarketing display ads following them around the internet. They finally do a search in Google for your brand, click the corresponding ad, and make a purchase.

Data-driven attribution in Google Ads lets you see which type of ads are most effective in driving conversions. If you use an automated bid strategy, Google Ads will redistribute ad credit so the better-performing campaigns, ad groups, and keywords take precedence.

Not all Google Ads accounts are eligible for data-driven attribution. You need to have goals set up and need to have a certain amount of ad interactions and conversions. This depends on the goals you want to track but is typically 3,000 ad interactions and 300 conversions over 30 days.

You can see if data-driven attribution is set up by doing the following:

Click on Goals.

Select the Conversions drop-down

Choose Summary.

Click the conversion you want to edit

Click Edit settings and select Data-driven from the drop-down menu.

Save, and you’re done.

You can view your Google Ads attribution reports by clicking the tools icon, going to Measurement, and selecting Attribution.

How to Get the Most Out of Data-Driven Attribution

Data-driven attribution is a powerful tool, but it’s important to optimize the process from start to finish to ensure the best results.

Here are some of my top tips for getting the most out of your data-driven marketing:

Set clear goals before you start. For example, do you want to make better choices about allocating your marketing budget or understand which channel provides the best ROI? This will help you understand what to do with your data.

Ensure good data hygiene. Data-driven attribution relies on a large amount of high-quality data. Ensure you’ve got clear conversions in place and have set up UTM parameters to help identify the right touchpoints.

Check your data regularly. This means you can make sure you’re happy with the results, identify any issues, and amend your marketing strategy accordingly.

Be patient. Your data-driven attribution model will take time to learn and assign value to your marketing channels accurately.

FAQs

What is data-driven attribution?

How does data-driven attribution work?

Data-driven attribution vs last click: which is best?

Is GA4 Good for Data-Driven Attribution?

Conclusion

Data-driven attribution isn’t an option for every business. However, if you receive a large amount of conversion data and want to know which marketing channels drive results, it’s a fantastic way to steer your marketing strategy.

If you’re not already using data-driven attribution, it’s a great time to start. Set things up in Google Analytics and Google Ads and use the results to optimize your marketing mix.

Do you use data-driven attribution? What lessons have you learned from analyzing the data you receive?