Why we care about marketing attribution modeling

Attribution modeling is what many marketers use to help determine the comparative value of a marketing or advertising channel. Understanding the value of these channels and the type of benefit they bring to a campaign helps determine budget spends, traffic sources and how to optimize campaigns. 

Below, we will introduce the basic concepts around attribution modeling and ways to get the most out of it. 

Table of contents

  • What is attribution modeling? 
  • Why is attribution modeling so important?
  • The different types of attribution models
  • How to choose the right marketing attribution model
  • Skepticism about the viability of attribution modeling
  • Additional resources

Estimated reading time: 5 minutes

What is attribution modeling?

Your prospects and potential customers can take a range of pathways to interact with your content and make their way through the buyer’s journey. These pathways are specific touchpoints throughout that journey, such as:

  • Opening an email.
  • Clicking on an ad.
  • Commenting on a social media post.

Attribution modeling in marketing allows you to determine how beneficial each of those touchpoints is along the buyer’s journey. With it in place, you can identify which marketing channel best helps to convert a lead from a mere browser to a loyal buyer.

By assigning a particular value based on interactions with a marketing channel, marketers can decide where time, energy and money should be spent. Knowing what touchpoint actually converts a lead can make a great difference for both sales and marketing professionals.

Why is attribution modeling so important?

Attribution modeling is critically important for several reasons. We will discuss them below in the form of some questions you can ask.

What improvements can I make to the buyer’s journey? 

When attribution modeling is in play, you will start to see what works and what does not. Underperforming areas can likely be improved, and you will dig deep into the data to find out why and how to do so.

What is the real ROI from a channel? 

Understanding the parts within the buyer’s journey that push your prospects to convert can help you see the channel’s or sub-channel’s value. It will also allow you to determine whether you should spend more (or less) of your efforts and resources there.

Can I craft better content for my ideal client? 

The answer, with attribution modeling, is a resounding yes. Tailor more of your marketing campaigns to the working channel(s) and the ideal client most likely to buy from you.

The different types of attribution models

There are several different types of attribution modeling. Each model looks at the various channels you are using but may apply varying degrees of weight to them.  

Multi-touch attribution modeling takes into account each touchpoint and channel within the buyer’s journey from start to finish. It will determine which channels were the most beneficial and effective in influencing a customer’s decision to convert.

First-touch attribution modeling focuses on the first touchpoint or channel that the client interacts with within the buyer’s journey.  

Last-touch attribution modeling focuses on the very last touchpoint or channel that a prospect entered before making the decision to convert.

Time-decay attribution modeling gives equal consideration to each touchpoint and channel but gives the highest points to the touchpoint that was interacted with closest to the conversion.

Cross-channel attribution modeling is a form of multi-touch modeling that looks both at touchpoints within each channel and also at how channels work together.

Linear attribution modeling is a form of multi-touch modeling that gives equal range and weight to all channels and touchpoints throughout the full cycle of the buyer’s journey. 

These attribution models can be used in marketing campaigns based on your pre-determined goals and KPIs. The answer to what is working and what is not working may change based on the type of attribution model that you’re using. 

How to choose the right marketing attribution model 

Before settling on an attribution model, you may want to test them to see which one works best for your campaigns. There isn’t necessarily one that stands out above all others.

Consider your campaign goals and how quickly those goals were reached. This can help you determine what model might best be used.

In addition, as your marketing campaigns evolve, you may need to switch the attribution model you use. Stay agile and allow the tool you use to move flexibly with you and your team. Here are a few questions you can ask before picking an attribution model:

  • How many touchpoints are within the journey for the prospect?
  • What are the goals of the campaign? 
  • What does the overall funnel look like? 
  • What is the end result or expectation of the campaign?
  • Will I be using a tool, or can Google Analytics give me what I need?

Skepticism about the viability of attribution modeling

While most marketers find attribution modeling an essential part of their toolkit, some skeptical voices argue that traditional attribution modeling cannot cope with today’s vast proliferation of channels and touchpoints and the complexity of today’s customer journey.

“At the end of the day, people have to give up the fantasy that [marketing] can ever be completely predictable,” says marketing strategist Kathleen Schaub.

The skeptics say it is not feasible to hit a certain ROI target by a specific date. Instead, the suggestion is that marketing analytics should be treated as a kind of GPS, where routes and even destinations can be optimized along the way.

Dig deeper

Want to learn more? Here’s some further reading that may be useful: 

  • How can we understand and fully embrace attribution modeling? Let’s find out in, Modeled behavior: A future-proofed new measurement strategy.
  • Opinions on addressing attribution in digital and physical marketing campaigns are sparking a debate among marketing OGs and professionals.
  • Do you need a marketing attribution and predictive analytics tool? It could be that you do.  

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