Introduction

Welcome everyone! Today we’re going to talk about an important concept in digital marketing — the multi-touch attribution model. You might have heard this term before, but do you really understand what it means?

In simple terms, the multi-touch attribution model is a way to measure the effectiveness of your marketing campaigns by attributing credit to multiple touchpoints that led to a conversion. It’s different from other attribution models like last-click attribution, which only gives credit to the last touchpoint before a conversion. With multi-touch attribution, you get a more complete picture of how your marketing efforts are performing.

What is Multi-Touch Attribution Model?

The multi-touch attribution model is a method used to determine which marketing channels or touchpoints are responsible for generating conversions or sales. Unlike single-touch attribution models, which give all the credit to one touchpoint, multi-touch attribution models take into account all the touchpoints that a customer interacts with before making a purchase decision.

For example, let’s say a customer sees a Facebook ad, clicks on a Google search ad, and then finally makes a purchase after receiving an email. With a single-touch attribution model, only one of these touchpoints would receive credit for the sale. However, with a multi-touch attribution model, each touchpoint would receive some credit based on its contribution to the sale. This allows marketers to better understand the customer journey and optimize their marketing efforts accordingly.

Why is Multi-Touch Attribution Model Important?

The multi-touch attribution model is crucial in today’s digital marketing world as it provides a more accurate understanding of how customers interact with different touchpoints before making a purchase decision. Unlike other attribution models, multi-touch attribution takes into account all touchpoints of a customer journey and assigns credit to each touchpoint based on its contribution to the final conversion. This helps marketers to optimize their marketing strategies by identifying which touchpoints are most effective in driving conversions.

Using the multi-touch attribution model over other models has several benefits. It provides a comprehensive view of the customer journey, allowing marketers to identify touchpoints that may have been overlooked in other models. It also helps to avoid over-crediting or under-crediting certain touchpoints, providing a fairer distribution of credit. According to a study by Econsultancy, companies that use multi-touch attribution models report higher ROI compared to those that don’t. In fact, companies that use multi-touch attribution models report an average increase of 15–20% in marketing ROI.

How Does Multi-Touch Attribution Model Work?

There are several types of multi-touch attribution models, each with its own strengths and weaknesses. The most common models include linear, time decay, and position-based (or U-shaped) models.

Linear models give equal credit to each touchpoint along the customer journey, while time decay models give more weight to touchpoints that occur closer to the conversion event. Position-based models give the most credit to the first and last touchpoints, with the remaining credit distributed evenly among the other touchpoints.

For example, let’s say a customer sees an ad on Facebook, clicks on a Google search ad, and then makes a purchase after receiving an email. A linear model would give each touchpoint equal credit, so Facebook, Google, and email would each receive one-third of the credit for the sale. A time decay model might give more weight to the email, since it occurred closest to the sale. And a position-based model might give more credit to Facebook and email, since they were the first and last touchpoints in the customer journey.

Challenges of the Multi-Touch Attribution Model

One of the major challenges of implementing a multi-touch attribution model is determining which touchpoints to credit for a conversion. With multiple touchpoints involved in a customer’s journey, it can be difficult to determine the exact role each touchpoint played in the conversion. This challenge can be overcome by using data-driven attribution models that take into account various factors such as recency, frequency, and position of touchpoints.

Another challenge is integrating data from different sources. With data coming from various channels and platforms, it can be challenging to integrate all the data into a single platform for analysis. This challenge can be addressed by using data management platforms (DMPs) that help consolidate data from different sources and provide a unified view of customer behavior.