Marketing Attribution Methods 101

Marketing Attribution Methods 101

Even with all the data in the world, you need to be smart with how you use it if you want to get an accurate picture.

Imagine you’re promoting a party in every way you can. The party was a huge success, but it was a LOT of work. You’re sure that some things worked better than others at getting people to attend. The role of marketing attribution methods is figuring out what caused people to come to your event. Assuming you can get reliable data, the critical question is how you assign credit when people were reached with multiple strategies!

Marketing attribution refers to the methods and tools that marketers use to assign value or credit to different marketing touchpoints within a customer’s buying journey. It helps businesses understand which channels, campaigns, or efforts contribute the most to their goals, whether conversions, sales, or leads. The following are the primary approaches to marketing attribution:

1. Last Click Attribution

This is the simplest and most commonly used form of attribution. The last click model gives 100% credit to the final touchpoint that leads to a conversion. However, this model doesn’t consider other interactions that may have influenced the consumer’s decision.

Imagine your customer’s journey to buy your product is like a relay race. The “Last Click” method is like giving all the glory to the last runner who crosses the finish line, ignoring all the other runners who got them there. It’s simple but not always the fairest!

2. First Click Attribution

In contrast to the last click model, the first click attribution gives all credit to the first touchpoint in the customer journey. Like the last-click model, this approach overlooks the influence of subsequent touchpoints.

This is like cheering for the first runner in the relay and then forgetting about everyone else. It celebrates the beginning of the journey but doesn’t consider the rest.

3. Linear Attribution

The linear model divides the attribution equally across all touchpoints. It acknowledges that each interaction contributes to the final conversion. However, it assumes all touchpoints are equally influential, which is rarely true.

Here we’re sharing the love equally. It’s like saying each runner in the relay contributed equally to the race, which isn’t necessarily accurate, but it’s a start.

4. Time-Decay Attribution

This model gives more weight to the touchpoints closer to the conversion. The theory here is that the later a touchpoint is in the customer’s journey, the more influence it has over the decision to convert.

This gives more credit to the runners who were in the race towards the end, based on the idea that the closer you get to the finish line, the more important your role.

5. U-Shaped (Position-Based) Attribution

The U-shaped model gives most of the credit to the first and last touchpoints (usually 40% each), and the remaining 20% is distributed equally among the middle interactions. This model values both the initial interaction that attracted the customer and the final interaction that led to conversion.

We’re giving the most cheers to the first runner who started the race and the last runner who crossed the finish line, with a little applause for those in between.

6. W-Shaped Attribution

Similar to the U-shaped model, the W-shaped model assigns more credit to three key points in the customer journey: the first interaction, the point at which the lead is generated, and the final conversion point. These points usually receive 30% of the credit each, with the remaining 10% spread over other touchpoints.

This goes one step further and celebrates three key runners: the first to start, the one to take the baton halfway, and the last to cross the finish line.

7. Data-Driven Attribution

This approach uses advanced statistical techniques and machine learning algorithms to assign a value to each touchpoint. It considers all available data and adjusts the attribution weight based on what drives conversions. As such, it’s typically the most accurate but also the most complex and resource-intensive model.

It’s like a super-smart coach using all the stats and data to figure out which runner did the most to help the team win the race. It’s the most accurate, but it also requires the most homework!

8. Multi-Touch Attribution (MTA)

An overarching term for models considering multiple touchpoints in the customer journey, including Linear, Time-Decay, U-Shaped, W-Shaped, and Data-Driven models.

This is an umbrella term for any method considering multiple relay race stages. It includes our friends Linear, Time-Decay, U-Shaped, W-Shaped, and Data-Driven.

Selecting the right attribution model depends on your specific business context, including the complexity of your customer journey, the resources available for data analysis, and the specific goals of your marketing campaigns.