Everything you need to know about multi-touch attribution

As the average purchase journey becomes increasingly complex, companies are turning to multi-point attribution to make sense of it all.

Marketing leaders need details on critical aspects such as ads clicked, blogs read, and reviews compared when looking to optimize different businesses. The multi-touch assignment plays a big role here. It tracks recordable customer touchpoints for customer journey analysis to help marketers make the best possible decisions.

What is Multipoint Attribution (MTA)?

Multi-touch attribution is the process of determining the value of customer journey touchpoints in generating a conversion event.

A conversion event can be a customer signing up for a free trial, booking a demo request, or making the actual purchase, or all, as some multi-touch attribution tools allow step-by-step attribution of the pipeline.

Multipoint attribution modeling works with data gathered from touchpoints in a buyer's journey. Marketers can use it to determine which marketing channels or campaigns the conversion should be attributed to and act with different multi-touch models.

Different multi-touch models accredit touchpoints differently to suit a particular business model. This allows marketers to optimize their efforts and acquire new customers more effectively.

Multi-channel vs multi-touch attribution

Multi-Channel Attribution (MCA) and Multipoint Attribution are often used interchangeably, but differ in the level of analysis. Multi-touch attribution attributes every contact in an ad campaign and blog post at the cadence of emails. Multi-channel attribution credits are based only on the channels affected, such as paid, organic, email, and social channels.

For a marketing manager, the difference between the two is the level of touchpoint analysis. Multi-channel attribution provides an overview of a channel's overall performance. In contrast, multipoint attribution helps optimize performance across the board.

How is MTA different from single, first and last touch attribution?

Companies often use one-touch attribution on their CRM or marketing automation platform. Attribution to first touch, first touch, and last touch all provide information about the touchpoint that resulted in acquiring or converting a lead.

How is multipoint attribution different from these models?

One-touch models count only one contact in the purchase journey, usually the first or last contact, referred to as first-touch and last-contact attributions, respectively. Anything in between doesn't count for conversions.

On the other hand, multi-touch assignment patterns credit all keys and allocate them according to the pattern chosen. Here is a simple example to illustrate the difference between first touch and last touch versus multi-touch attribution modeling.

Before making a conversion, a customer goes through three marketing touchpoints: a Google Ads click, a LinkedIn conversation ad, and a G2 product comparison ad before requesting a demo. First contact attribution only credits Google Ads and G2 comparison to last contact. However, a multi-touch model distributes credits to all three one way or another.

Is one better than the other? Well, some attribution is better than none, as it gives you insight into data on how your go-to-market activities are performing.

To put it simply, while one-touch models are easy to set up and give revenue managers insight into which touchpoints are converting leads, they only paint a fragment of the bigger picture.

This inconsistent overview makes it difficult to act on the data. Do you then focus only on the last ad or channel hit and ignore other touchpoints? Multi-touch models give you a clearer picture of the customer journey - which efforts affect a transaction and which don't.

Why is multi-touch attribution important?

But why is it important for go-to-market teams? For two main reasons:

Provides clarity in the customer journey. Multi-touch attribution modeling relies on collecting as much customer journey data as possible. This, in turn, offers essential insights into customer behavior and activities throughout the buying journey. It allows you to take into account key indicators such as the time required to convert prospects, the time spent...