FAQ: What Is Multi-Touch Attribution and What’s the Process?

By Indeed Editorial Team

Updated June 15, 2022

Published June 15, 2021

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

The buyer's journey is valuable data to a marketing team. Multi-touch attribution models exist to evaluate that data to help promote new ways of advertising that can attract more customers, leads and prospects. Understanding how it works can help introduce your business efforts to new marketing perspectives. 

In this article, we explain what multi-touch attribution is, explore different models and answer other frequently asked questions to help you further your company's advertising reach in the online market.

Related: A Definitive Guide To Using an Attribution Model (With Types and Tips)

What is multi-touch attribution?

Multi-touch attribution is the process of evaluating web pages a customer visits before making a purchase from the company. By placing value on different parts of the buyer's journey, marketing teams can adjust campaigns and increase profits.

What is conversion?

Conversion is when a potential customer becomes an actual customer. For example, when a potential customer views a sign-up page that offers them a free trial of a service, they ‌can convert and become customers by subscribing.

What are touchpoints?

Touchpoints are internet locations that a potential customer visits, which can include anything from a company's social media post to a company's webpage. Touchpoints ultimately lead to pages such as a store advertisement or a subscription offer page where the potential customer decides whether to convert into a customer.

How is multi-touch attribution different from last-touch and first-touch attribution?

Unlike multi-touch attribution, last-touch and first-touch attribution give all the credit from a conversion to the last or first touch point a customer encounters on their buyer's journey. Many marketing teams prefer this model because it gives them concentrated data that's easily trackable and more focused on the result. However, a disadvantage to single-touch models that multi-touch models make up for is that single-touch models don’t encompass an entire scenario surrounding a purchase.

For example, suppose an advertising campaign that uses last-touch attribution uses advertisements that appear in videos on the internet. These videos become popular and start to trend, causing potential customers to search for the company store on the internet. They click the web browser advertisement and make purchases. According to last-touch attribution, the browser advertisement caused the most sales, but in reality, the video ad resulted in the attention.

Related: Creating a Successful Social Media Marketing Strategy

What are the multi-touch attribution models?

There are multiple multi-touch attribution models that each evaluate the buyer's journey differently by attributing values to touch points. Some of these models include:

Lead creation touch attribution

The lead creation touch attribution model gives all the conversion credit to the touch point where prospects become leads. Prospects may browse your company's website or social media and may have also perused your company's store but not purchased anything yet.

A customer lead, however, is a potential customer who has given the company details about themselves or has been a customer before. For example, if someone visits your company's website and signs up for a webinar, they have become a lead. A potential customer who visits your websites, stores and other pages but doesn’t  react to the advertisements that would turn them from a prospect into a lead remains a prospect until they do so.

Related: What Is Marketing Attribution? Benefits, Types, Models and Tips

Last non-direct click attribution

The last non-direct click attribution model gives all conversion credit to the last non-direct click on  the buyer's journey. For example, if a customer looks at a store page because of an advertisement, the model gives all the credit to that advertisement, regardless of what the other touch points are on  this buyer's journey.

Linear attribution

Linear attribution takes every touch point a potential customer makes into account during the buyer's journey. All % the credit evenly divides among the number of touch points made before the conversion, resulting in the percentage of credit that each touch point gets for the conversion. This model is quite common, but not as streamlined as others.

Time decay attribution

Time decay attribution has multiple similarities to linear attribution. The only difference between the two is that the time decay model decreases the value of each touch point over time. For example, suppose a potential customer views a social media post from a company at noon. They click the link in the social media post that leads them to the company website, but they actually follow the website to the store page a few hours later. In the time decay model, the social media post holds the least credit for the conversion, followed by the website.

U-shaped attribution

The U-shaped attribution model is a position-based model that determines touch point value based on the position in the buyer's journey. For example, in the U-shaped attribution model, the first and third touch points are the most valued equally, while the remaining touch points until the end of the buyer's journey are all valued at equal or lesser levels.

This creates a U shape out of the touch point's value when viewed linearly and in order, from left to right, just like on a bar graph. The first touch point's value appears high on the bar graph, while the second and fourth ones are lower. The third one, however, appears just as high as the first one, creating a U shape.

W-shaped attribution

Similar to the U-shaped attribution model, the W-shaped attribution model is another position-based model that values the first, third and fifth touch points in a buyer's journey equally high, while valuing the rest of the touch points equally low. When viewing the buyer's journey touch points linearly and in order, the value attribution resembles a W.

Z-shaped attribution

The Z-shaped attribution model is another position-based model that values the first, third, fifth and last touch points on the buyer's journey. When viewing this model linearly, the shape it creates resembles a Z. The second, fourth and second to last touch points are all valued at equal, lesser levels.

Related: How To Create a Brand Marketing Campaign

What is the multi-touch attribution process?

Multi-touch attribution is the process of determining the value for every customer touch point that occurs before conversion. Multi-touch attribution's goal is to evaluate customer trends with the intent of allocating  future spending toward creating a more efficient customer conversion system. It can gauge a campaign or media channel's effectiveness and importance in the buyer's journey.

For example, suppose a customer who is being advertised a product ignores the product video advertisement while on their computer. Then, while scrolling through social media on their phone, they see an integrated advertisement for the same product, become curious, and they navigate to the website. From there, they go to the online store and eventually make a purchase. Multi-touch allocation evaluates each step of the buyer's journey and determines that in this situation, the video advertisement was less effective than the integrated social media advertisement.

How do teams determine which attribution model is best?

The touch attribution a marketing campaign uses depends on the changes the marketing team is willing to make to increase profitability. Different models benefit campaigns in different ways: 

  • Time decay model: These models are fit for focusing on purchases that have long sales cycles. They’re easier to keep track of and can work together with another model to collect very precise data about your customer's patterns.

  • Position-based model: These models work well when trying to learn about lead-generating customers in addition to what pages cause the most initial reaction.

  • Linear model: Because linear models account for every touch point, this model generates the most data per customer journey out of every other model. However, this model is the most complex of the three and takes the most time to analyze.

Why do companies use multi-touch attribution data?

Companies use multi-touch attribution data to gain a clearer understanding of the buyer's journey, even if the journey takes a long time. By learning the buyer's journey, companies can adjust their marketing campaigns to optimize advertisement use and allocate funds to the campaigns that return the most profit. Even when using a position-based model, marketing teams can gain an intimate understanding of the buyer's journey based on evaluating one touch point alone.

With multi-touch attribution data, a company can almost instantly see how well a campaign is running and how effectively an advertising medium is shortly after its release. Multi -touch attribution is accessible through a wide option of programs and applications. While it is possible for a marketing team to create attribution programs independently, developers continuously streamline attribution programs to make the data as useful as possible.

How is multi-touch attribution data gathered?

In order for a multi-touch attribution model to be effective, marketing teams need data to track. Some ‌ways marketing teams track data from customers include:

JavaScript tracking

Some companies use JavaScript in HTML to both record and improve customer activity in the company's favor. For example, if a customer opens an email advertising a pair of shoes and follows the link inside, certain JavaScript codes can immediately send another email that the marketing team thinks the customer might also enjoy.


Similar to JavaScript, cookies and UTMs help facilitate more opportunities for customer engagement. While not as functionally diverse as JavaScript, cookies and UTMs can continuously track a user's data to see if they’ve visited the company website multiple times or to see what sites they visit overall. Marketing teams can use this data to decide which sites are the most optimal for advertising.

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