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To reiterate from the previous post, attribution helps marketers get the most from their marketing efforts, by understanding the customers’ journey and identifying valuable touchpoints that lead to conversions. This information is critical to creating more effective ad campaigns and boosting revenue. Data-driven attribution is the state-of-the-art attribution technology that enables companies to accurately analyze marketing performance and optimize campaigns to achieve maximum ROI.

For more from our attribution series:
Attribution Modeling 101: Finding the Source of Truth
Why First-Touch and Last-Touch Attribution Are Out of Style
Designing a Multi-Touch Attribution Model
How to Choose the Right Attribution Model for Your Business

What Is Data-Driven Attribution?

Unlike the rule-based attribution models discussed in the previous post, data-driven attribution doesn’t use a pre-defined model to assign credits to each touch-point. Data-driven attribution uses machine learning technology to create a custom model for each business based on data that reflects the actual customers’ journeys.

Traditional rule-based attribution models only evaluate paths that lead to conversions. In contrast, data-driven attribution models consider both the converting and non-converting paths. This enables marketers to assess how each touchpoint increases the likelihood of a customer converting rather than merely allocating credits to the conversion path touchpoints based upon predefined rules. As a result, data-driven attribution provides a more comprehensive and accurate attribution evaluation. 

What Are the Benefits of Data-Driven Attribution?

Data-driven attribution helps marketers better understand how customers interact with their brands across various channels and marketing programs, and how each touchpoint contributes to conversion. With a clear view of the entire customer journey, marketers can quickly analyze the performance of every touchpoint to determine how effective each step of the campaign is. 

Data-driven attribution requires a robust platform that can quickly automate the analytics and provide useful reports for internal sharing. Gathering the data is just the first step in making sound marketing decisions. Until that data transforms into actionable items that the marketing team can leverage and improve upon, its value will not be fully realized. That’s why the reporting section of your attribution platform is a vital element to assess before signing on to a specific solution. Reports should be easy to understand to ensure your entire company can make sense of the findings and get on board with your marketing efforts.

Here are some ways that your marketing team can benefit from data-driven attribution within a quality platform:

  • Analyze your complete omnichannel campaign performance. Use reporting to gain a quick overview of your campaign performance, along with more detailed reports to understand how each channel and campaign affects the next.
  • Refine your budgeting strategies. Take action on the data you receive by adjusting your goals and optimizing spending. With the precise information provided, you’ll be able to set new budget targets at every level of the campaign — down to the individual channels and ad programs.
  • Get one global perspective. When omnichannel is the norm, it’s important to have a tool that helps you visualize the global view of your marketing efforts, while also making it possible to zoom into the details, as needed. Customize your view to set specific metrics that reflect your goals. That will align your analysis with your priorities to ensure that you get the most value out of your efforts.

How Does Data-Driven Stack Up?

A Google study showed that data-driven attribution helped marketers grow conversions by 30% to 60% while reducing cost-per-conversion rates by 20% to 30% after adding data-driven attribution to its AdWords product. This number increases as you expand your toolset to include platforms, like AdRoll, that can manage omnichannel marketing efforts in one integrated view.

In the past, attribution models were selected based on perceived consumer behaviors and could vary wildly from one marketer to the next, even within the same industry. Meanwhile, most ad campaigns default to last-click attribution models, giving full credit to the last ad that a consumer clicks before conversion. Neither of these methods is ideal for getting accurate data or significantly improving conversion rates.

While other attribution models use basic analytics data, they only provide a template and often fail to account for important steps in the marketing funnel. With data-driven attribution, marketing teams can precisely map their unique attribution model based on real customers’ historical information. This helps to ensure that the correct level of credit is assigned to each touchpoint.

What Do I Need to Know Before Implementing a Data-Driven Attribution Model?

Switching from a standard attribution model to a data-driven attribution model can have a lasting and impactful effect on your ad campaigns. While other models contain built-in bias for specific steps on the customer journey, data-driven attribution allows you to understand which among these touchpoints are performing the best given your sales or conversion goals.

The data-driven attribution model does require a certain amount of traffic to predict these paths accurately. The volume and quality of the information that you use are essential to creating a successful model, so it requires a significant amount of data to get started. Comprehensive and reliable analytics are the critical elements of a valuable attribution model. Here are some questions to ask before getting started:

  • How many visitors and conversions do we have?
  • How many channels and which programs do we want to include?
  • How long is the average customer journey?
  • What is the typical duration of the conversion path?
  • Is the data consolidated, and has it been cleaned?

With high-quality data fueling your attribution model, your analytics will continue to improve over time, yielding better and more actionable results each subsequent month.

Get Started With Data-Driven Attribution

The value that data-driven attribution contributes to your ad campaigns can provide sizable returns that increase the longer you use it. It’s a good idea to start small with the data-driven attribution tools offered by Google and Facebook through their ad platforms. Use these tools to optimize your campaigns within their respective marketing channels. Once you become comfortable with these tools, you can expand to realize the full benefits of data-driven attribution when it’s applied across multiple channels. 

Consider implementing a cross-channel attribution solution, like AdRoll, when you are ready to optimize all of your omnichannel marketing efforts. By leveraging a platform like AdRoll, your company will gain significantly more conversions with impressive ROI. Looking at the full spectrum of marketing efforts together will help you identify platforms, touchpoints, and other marketing components that are your real MVPs and the ones that are lagging so you can adjust accordingly.

While shifting from a standard attribution model to data-driven attribution is straightforward, you’ll likely need to adjust certain items in your ad campaigns. Re-evaluate the keywords that you use along the buyers’ journeys, adjust your bids (especially for search-based ads), and give the attribution model time to flourish. With data-driven attribution, you’ll see results grow stronger as time passes, especially as you continue to refine your strategies.

Jimmy Shang
Author

Jimmy is the Director of Marketing Analytics and Insights at AdRoll which basically means that he’s a professional cat-herder and data nerd. Other than whiteboarding big ideas, he enjoys all manners of food, travel, and woodworking.