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Switching From the Position‑Based Attribution Model

Ready to break free from the limitations of the position‑based attribution model? Let’s explore what’s next in the interesting world of marketing analytics.

Ever wonder which of your marketing moves truly drive results? Did your latest Instagram campaign bring in more customers? Or was it the emails you’ve been sending out? Not knowing can feel like you’re just throwing things out there and hoping something sticks.

There’s good news, though. Attribution models can help clear things up. These tools help you understand how different touchpoints influence customers’ engagement with your brand.

While the position-based model has been a popular choice for offering insights, its discontinuation means you must pivot to other models. Yet, it’s still helpful to understand how position-based attribution worked and see what has taken its place. Read on to learn what you need to know about the recent changes to conversion attribution.   

What is the position-based attribution model?

Many marketing tools like Google Analytics 4 (GA4) and Google Ads use attribution models to show which touchpoints and marketing channels contribute to sales. The position-based attribution model was once a key attribution modeling option.

Also called U-shaped attribution, the position-based model valued the first and last interactions of a customer’s journey the most but still considered the steps in between. Like all attribution models, it used conversion credit—shown as a percentage out of 100—to illustrate each interaction’s role in driving a sale.   

As of June 2023, Google elected to remove all but the data-driven and last-click attribution models. So, you can no longer select position-based, linear, time-decay, or first-click attribution models within their systems.

How position-based attribution worked

Position-based attribution split conversion credit across several key touchpoints in the customer journey. The first and last marketing activities received 40% of the attribution credit each. This might have been an ad the customer first clicked on and the final email that convinced them to purchase.

The remaining 20% of the credit was shared among the other steps in the multi-touch conversion process, like visiting your website or liking a post on social media. These actions keep the customer interested and guide them toward making a purchase. But they’re less critical than the initial and final interactions, so they received fewer conversion credit points.

Advantages of using position-based attribution

Using the position-based attribution model helped you understand the whole story of how your marketing would lead to conversions in the sales cycle. It showed how new customers would move from first noticing your brand to deciding to buy from you. Moreover, it told you how existing customers would re-engage with your brand and interact with your marketing efforts over time.

Despite those benefits, Google discontinued this attribution model due to low usage. It was found that only 3% of web attributions in Google Ads linked back to the position-based, time-decay, first-click, and linear models combined. So, removing them from their systems was an easy choice.

Possible reasons for the poor attribution model usage rates

Although it could offer valuable insights, position-based attribution had its fair share of challenges and pitfalls.

  • Disproportionate credit: Position-based models tend to give too much credit to the first and last touchpoints, ignoring the middle ones. This could cause you to overlook critical touchpoints that influenced the customer’s decision but didn’t result in a sale right away.   
  • Interpretation difficulties: Understanding and applying the model’s findings often proved challenging. This was especially true when determining if the first or last interaction had a greater impact.   
  • Sales team buy-in: If sales teams doubted the usefulness of position-based attribution, they resisted following its advice. So, when data pointed to online ads being key, but sales teams believed in face-to-face sales, they wouldn’t change their approach.

Given these challenges, it’s understandable why the position-based attribution model fell out of favor with marketing teams.

Additional discontinued attribution models

Google phased out several other marketing attribution models to refine its analytics framework and improve insights for marketers. These models include first-click, linear, and time-decay frameworks. Let’s explore how each one worked and how they missed the mark.    

First-click attribution model

The first-click attribution model assigned all the credit for a conversion to the customer’s first touchpoint. This might have included sharing your social media post, clicking on your banner ad, or signing up for your email newsletter.

Also known as the first-touch attribution model, this framework showed what drew people into your sales funnel in the first place. However, it didn’t truly capture the complete picture of what leads to a sale.

The first-click model was likely phased out because it missed how important the later steps are in a customer’s journey. Even though the first touchpoints get people interested in a brand, their later actions are what truly convince them to buy.  

Linear attribution model

The linear attribution model treats every step a customer takes on the conversion path as equally important. Whether it’s clicking on a social media ad, downloading an e-book, or starting a free trial, each action received the same credit for leading to a purchase.

Unfortunately, this view was too simplistic. In practice, not all marketing efforts have the same impact. For instance, a product demo or timely follow-up email may have a much stronger effect on the purchase decision than an initial ad click or social media post. This one-size-fits-all approach failed to highlight the importance of key moments, leading to marketing missteps.

Time-decay attribution model

The time-decay attribution model gave increasing credit to touchpoints closer in time to the conversion. For instance, an ad clicked on yesterday would get more credit than an online chat with sales from last month.

Time-decay attribution tried to show that the closer a marketing action was to a sale, the more important it was. However, this method was also too simple because it didn’t fully consider how complex buying decisions are. It just assumed that the last things customers did before buying were the most important, which isn’t always true.  

The future of conversion attribution

As Google moves past older models like first-click, linear, and time-decay, the future of conversion attribution looks toward more accurate approaches. The following are the models you can currently use to assign attribution.  

Data-driven attribution model

Data-driven attribution is the default attribution model for marketers who want to enhance their strategies with actual data. This model uses your existing conversion data to determine how much credit each touchpoint in the customer journey deserves. It looks at your past interactions and results to understand the true impact of your marketing efforts.

For example, if a customer conducts a Google search using different keywords, visits your website, submits a lead gen form, and then makes a purchase, the data-driven model can analyze this process. It determines which conversion actions played the biggest role and then assigns credit to each one based on its overall influence.

What’s great about data-driven attribution is that it adjusts to your specific marketing situation. It goes beyond the simple views of older models to offer personalized insights into what really leads to sales. But it’s not for everyone.

The last-click attribution model might be a better choice if you don’t have a lot of data to work with or if you operate in a niche market. Also, Google requires over 300 conversions and 3,000 ad interactions in a 30-day period before allowing data-driven attribution for some conversion types.

Last-click attribution model

The last-click attribution model gives all the credit to a customer’s final step before buying something from you. This could be their last click on a sales ad, the final email they open, or a social media post they interact with just before deciding to purchase.

Last-touch attribution is all about understanding the power of that final push that convinces customers to buy from your brand. It’s how you can tell which messages, offers, or channels push people to the end of their conversion paths. 

Like the first-click model, last-click attribution helps you determine the importance of the first and last steps in the customer’s journey. This approach lets you see what’s working best to close deals, guiding your marketing decisions. 

If you choose last-click attribution, you’re keeping things simple and straightforward. But, in doing so, you might be overlooking earlier interactions that may have influenced customers to complete their purchase. This could mean wasting resources on ineffective strategies and missing chances to improve your results.   

How to select an attribution model in Google’s systems

You can choose your preferred attribution model in the Google Ads and GA4 platforms. The process varies for each system, but the steps are quick and easy if you already have accounts on these platforms. Here’s how to pick the best model for your needs.

Google Ads

In some cases, your conversion actions may automatically change to data-driven attribution. If it doesn’t switch or you prefer the last-click model, follow these steps to make the desired changes.

  1. Sign in to your Google Ads account.
  2. Click on Tools and Settings in the top menu bar.
  3. Click Conversions in the drop-down menu.
  4. Select a conversion action and then click on the Edit settings button.
  5. Click on the Attribution section to view and modify its options.  
  6. Select either Data-driven or Last-click from the dropdown menu.
  7. Click the Save button to confirm the changes.
  8. Repeat this process for each conversion action you want to update. 

Google Analytics

GA4 allows you to make global changes that affect how the system reports conversion credits. Your changes will not impact user and session data, regardless of which attribution model you pick. Follow these steps to make your selection.

  1. Sign in to your GA4 account.
  2. Select your analytics account and property.
  3. Click the Admin button on the left sidebar.
  4. Click Data display to expand the menu.
  5. Click Attribution settings to open the options window.
  6. Go to the Reporting attribution model box.
  7. If changing paid and organic channel attribution, select Data-driven or Last-click. Otherwise, choose Last-click to change the reporting attribution model for your paid channels only.
  8. Scroll down to link your Google Ads account to GA4 or change your conversion window.
  9. Hit the Save button to keep your changes.

Best practices to unlock the full potential of conversion attribution  

Whether you’re leaning toward a last-click or data-driven attribution model, consider using these best practices to maximize your marketing efforts.

Include offline and online touchpoints

A clear view of offline and online touchpoints can greatly enhance your view of the customer journey. To mix these touchpoints, start by linking in-store actions, like phone calls or purchases, with online activities. Use distinct personal identifiers like customer emails to connect these actions together.

Need help keeping track of everything in one place? Use a customer relationship management (CRM) system to organize your data. Many CRM systems can automatically sync your offline conversion data into GA4. For data not automatically captured, you can manually enter the conversion information into the analytics platform.

Incorporate external factors

Factors like holidays, economic changes, or market trends can change how well your marketing works. Understanding the impact of these outside influences is the first step toward accurately analyzing your data.

To begin, figure out which outside events might impact your marketing results. This could be anything from a major holiday to a big sports event. Keep track of when these things happen and make note of them.

Next, use tools like Google Trends to see how these events might change what people are interested in or looking for online. This can help you understand if there’s more interest in your products at certain times because of these external factors.

Then, match up this information with your conversion data. Over time, you’ll learn when to take advantage of these factors by running ads, sending out email sequences, or rolling out special offers at just the right moment.

Segment before analyzing

If your brand serves multiple audience segments, it’s wise to split them into groups before looking at your attribution model data. This way, you can see what each group likes and how they act differently. This ensures you can fine-tune your brand messaging and offers to fit exactly what each group wants.

To do this, create a plan on how to split your customers into segments. You might look at their age, where they live, what they buy, or how they find your website. Through this process, you’ll likely discover certain tactics that each group likes or doesn’t like about your marketing.

After that, review each group’s data on its own. You might find that some customers like getting emails, while others prefer seeing your ads on social media. Knowing this lets you decide the best way to reach out to each group.

Compare attribution model insights

Each conversion attribution model credits touchpoints differently. So, it’s important to compare how each model values the steps a customer takes before purchasing. The insights can be eye-opening, revealing the significance of previously undervalued or overlooked interactions.

Start by examining the data from your current attribution model. This will give you a baseline understanding of how each channel performs according to that model. For example, if you start with the last-click model, you might see that direct traffic gets the most credit because it’s the final touchpoint before a purchase.

Upon switching to the data-driven model, you may develop a more nuanced understanding of your marketing efforts. Maybe you’ll find that an email sent weeks before a purchase kept the customer interested. Or perhaps you’ll discover that social media ads encourage repeat visits that eventually led to a sale.  

Elevate your digital marketing results with conversion attribution

Now that the old position-based attribution model is no longer available, you have the chance to adopt more powerful methods. Shifting your focus to the data-driven model opens the door to deeper insights into your customer journey. This allows you to refine your strategies effectively and allocate resources wisely. With the right approach to conversion attribution, you can make smarter decisions and achieve better results in your marketing efforts.

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