An intro to marketing attribution modeling and how you can use it

When it comes to digital marketing success, deeply understanding the customer journey from initial awareness through purchase, up-/cross-sell and retention is one of the most critical factors. Knowing which actions influence conversions and how to measure them is a crucial step in optimizing your marketing efforts and increasing ROI and POI. That’s where marketing attribution modeling comes in. 

Attribution modeling is the process of assigning value to various touchpoints in the customer journey. This approach helps marketers better understand which touchpoints are most impactful in terms of conversion, revenue and profit. It also allows marketers to create more accurate marketing plans and optimize campaigns for maximum effectiveness and efficiency. 

In this guide, we will cover the basics of marketing attribution modeling and outline how you can use it in your work.

What is Marketing Attribution Modeling? 

Marketing attribution modeling is a data-driven approach to assign monetary outcomes like revenue or profit to touchpoints in the customer journey. Once touchpoints are measured through UTM tagging, pixels or other tracking set-ups, attribution models take all of these touchpoints across channels and activities, combine them into a customer journey and then credit certain touchpoints completely or partly for the monetary outcomes.

There are many different approaches to attribution modeling, each of which has its own benefits and drawbacks. Allow us to highlight some of the most used, which are also quite basic, followed by some more advanced models. 

Last-touch attribution 

Last-touch attribution assigns all conversion credit to the final touchpoint before a conversion. This method ignores all earlier interactions and is usually used to measure the performance of campaigns that had a direct impact on the conversion. 

First-touch attribution 

First-touch attribution is a method of assigning all conversion credit to the first touchpoint in a customer’s journey. This approach shows which channel was most effective in introducing customers to your brand and leads them to eventually make a purchase. 

Linear attribution 

Linear attribution assigns equal weight to all touchpoints in the customer’s journey. This method is useful for understanding the overall impact of each channel but doesn’t offer much insight into the effectiveness of any particular one. 

Time-decay attribution 

Time-decay attribution assigns greater weight to touchpoints closer in time to the conversion. This approach helps marketers understand the customer journey and how one action affects the next. It can also help marketers identify and remove “noise” from the journey that may be complicating the analysis. 

Markov attribution 

Markov attribution is a relatively new approach that takes into account both the order and the timing of each touchpoint in a customer’s journey. It provides a more accurate picture of the influence of each touchpoint and is useful for tracking complex customer journeys. 

Marketing mix modeling 

Marketing mix modeling is another advanced approach that takes into account multiple channels, campaigns, and customers. It uses statistical models to determine the contribution of various marketing tactics to revenue, allowing marketers to gain a more comprehensive understanding of the effectiveness of their campaigns. With privacy laws under increased attention and cookies on a decline, marketing mix models might make a big comeback in coming years as a preferred way to attribute marketing activities to returns.

How you can use attribution modeling 

Attribution modeling is an essential tool for measuring and optimizing digital marketing campaigns. By analyzing customer journeys and understanding the effectiveness of various touchpoints, marketers can better allocate their time and budget. Attribution modeling can help marketers identify their most effective channels and optimize their campaigns for maximum efficiency. Additionally, it can also provide insights into how different channels interact with each other and which ones have the most influence on conversions. Finally, by accounting for multiple channels and customers, marketing mix modeling allows marketers to create more accurate marketing plans. It also helps marketers more accurately measure the influence of different strategies on revenue. 

What makes attribution modeling difficult?

Besides the obvious need to understand your customers journey, marketers will need to reliably extract customer touchpoint and activity data from different sources and store it in one safe and managed location. Next to that, they will need to figure out a way to ‘connect the dots’ between the available data. Data for attribution modeling will need to come from an e-commerce platform like Shopify or Magento, or from a CRM platform like Salesforce, Hubspot or Pipedrive in case of B2B attribution. These sources will provide the revenue and/or profit side of the equation, while tools like Facebook Ads, Google Ads & Analytics and Google Search Console will provide the cost and activity data. The key is to join all of this data across the customer journey in a consistent and reliable way in order to get attribution models working reliably. This whole process is time consuming and technically complex and most marketing teams struggle to get this off the ground.

Conclusion 

Attribution modeling is an invaluable tool for digital marketers looking to optimize their campaigns and increase ROI. By understanding the customer journey and assigning value to various touchpoints, marketers can better allocate their resources and budget. Understanding the basics of marketing attribution modeling—including first touch, last touch, linear, time decay, markov and marketing mix modeling—is an essential step in driving digital marketing success. Armed with these insights, marketers can create more accurate marketing plans and measure the effectiveness of their campaigns with greater precision.

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