What is Multi Touch Attribution Model? | A Complete Guide

Saket Mittal • Last Modified: December 29th, 2022

Multi Touch Attribution Model - Featured Image

Today, the purchasing process is becoming quite complex, which has led businesses to adopt multi touch attribution to make sense of the usual purchase process.

When trying to enhance diverse operations, go-to-market executives want information on crucial variables such as advertising clicked, blogs read, etc. Multi touch attribution is essential in this case. It records consumer touch points for customer journey analytics, assisting marketers in making the best decisions possible. 

Data from these touch points in a buyer’s journey is used in multi touch attribution modeling. Marketers in your organization may utilize this to identify which marketing channels or campaigns should be credited to the conversion and act with various multi touch attribution models.

Multiple multi-touch attribution models assign different touch points to support a specific business model. This allows marketers to optimize their efforts better and gain new customers.

Read along to better understand what a multi touch attribution model is, its benefits, and its types. You’ll also learn the step-by-step procedure to build a multi touch attribution model, and the challenges that you might face while deploying a multi touch attribution model in your organization.

Table of Contents

What is a Multi Touch Attribution Model?

The multi touch attribution is a technique that determines marketing channel performance by analyzing each touch point that leads to a transaction. It is also known as multi-channel attribution. The ultimate purpose of employing a multi touch attribution model is to optimize marketing spend allocation to focus more on the channels that have the most effect on conversions.

Assume a buyer is thinking about buying a new pair of shoes. Company’s ads target their prospects after conducting some study. Companies first display an ad, which people usually ignore. Following that, they see a native ad on your Instagram feed that piques their interest and directs them back to the company’s website. Finally, they receive an email containing a promotional offer with a discount code, prompting them to purchase their product.

Each of these advertisements depicts a stage in the buyer’s journey. The multi touch attribution model enables marketers to link the transaction to the native ad and the email campaign. Your marketers can then notice that the ad advertised was ineffective and abandon that strategy.

Numerous multi touch attribution models are available to marketers to account for user-level data, i.e., the impact that user-level events (clicks, impressions) have on the overall aim. Ad effectiveness is scaled differently in each of these models.

What are the Benefits of the Multi Touch Attribution Model?

Multi touch attribution models are becoming increasingly relevant for marketers, particularly those trying to assess the effectiveness of digital efforts. This is because you get a more detailed, person-level picture than standard aggregate approaches like media mix modeling. 

Below are the benefits of multi touch attribution:

  • Complete View of Customer’s Journey: Multi touch attribution provides marketers with a comprehensive perspective of the customer journey, rather than simply the first or last touch point. This gives a clearer view of the client’s journey and how each touch point fits into it.
  • Insights into Granular Channel Performance: Multi touch attribution delivers more granular data to assist you in optimizing each touch point in the customer journey. Marketers can identify the most influential touch points and alter those that are underperforming. It also helps businesses optimize their marketing mix, allocating most of their budget to the channels that provide the highest ROI.
  • Better Cross-Channel Optimization: Multi touch attribution makes it easier to optimize multi-channel campaigns. It assists marketers in determining which channels are responsible for higher conversions.

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Multi-Touch Attribution Model vs First-Touch Attribution Model vs Last-Touch Attribution Model

First-Touch Attribution Model: The first point of interaction that brought a user to your website is called a first-touch attribution. A link in a social media post, a video with a call-to-action, a banner ad, or any medium that facilitates click-throughs to the product or service website can be the point of contact.

Last-Touch Attribution Model: This marketing attribution model gives 100% credit for a conversion to the last touch point. If no click or visit occurred, a credit would be given to the last impression resulting in the conversion.

Here is a comparison table to help you understand the differences between the Multi-Touch Attribution Model vs the First-Touch Attribution Model vs the Last-Touch Attribution Model.

ParameterMulti-Touch Attribution ModelFirst-Touch Attribution ModelLast-Touch Attribution Model
Touch Point CreditGives credit to all touchpoints and distributes them according to the model specified.It only gives credit to the first touch point.It only gives credit to the last touch point.
Ease of Set UpMulti-touch attribution model is a complex attribution that is hard to implement. Implementing it usually involves a rigorous 5-step procedure.Compared to the multi-touch attribution model, the first-touch attribution model is easier to implement.Compared to the multi-touch attribution model, the last-touch attribution model is easier to implement.
InsightsIt provides a clear and holistic view of the client experience, revealing which efforts impact purchase and which do not.It provides business individuals with insights into the first touch point that convert leads.It provides business individuals with insights into the last touch point that convert leads.

What Types of Multi Touch Attribution Models Can You Use?

There has been a significant increase in the number of attribution models meant to assist marketers in tracking and analyzing consumers throughout their path to purchase. Linear, time decay, U-shaped, W-shaped, full path, and custom are the most frequent forms of multi touch attribution models that we will discuss in this guide.

Linear Multi Touch Attribution Model

The linear attribution model is the simplest of all because it distributes credit evenly across all touch points before conversion. If a consumer has four touch points before the conversion event, each one is worth 25% of the credit.

Linear multi touch attribution models assist in avoiding the arbitrary procedure of identifying more crucial sales funnel touch points and giving them all equal credit. However, this is also its biggest drawback. When focusing on acquisition, the linear model does not provide enough weight to the first touch point.

Linear Multi Touch Attribution Model: Multi Touch Attribution Model | Hevo Data
Image Source: Marketing Evolution

Time Decay Multi Touch Attribution Model

The time-decay attribution model prioritizes touch points closer to conversion. The closer the conversion event comes, the more significant the impact of the touch points on conversion.

Time decay favors conversion-driven touches over top-of-funnel touches. Time-decay attribution model is beneficial for companies with extended sales cycles. However, the time-decay model undervalues the importance of top-of-funnel marketing activities in attracting new consumers.

Time Decay Multi Touch Attribution Model: Multi Touch Attribution Model | Hevo Data
Image Source: Marketing Evolution

U-Shaped Multi Touch Attribution Model

The initial and last touch points receive the most conversion credits in the U-Shape attribution model. The emphasis is on top and bottom-funnel touch points, with less attention on engagement methods in the middle of the funnel.

This model explains which approaches are effective at starting the customer journey and which are effective at converting customers.

U-Shaped Multi Touch Attribution Model: Multi Touch Attribution Model | Hevo Data
Image Source: Marketing Evolution

W-Shaped Multi Touch Attribution Model

Like the U-shaped model, the W-shaped model places a higher weightage on the initial contact, lead conversion touch, and opportunity generation touch points. These three touch points receive 30% of the credit, with the remaining 10% distributed evenly across the remaining touch points.

The W-shaped attribution model’s main advantage is that it highlights the top three marketing attribution transitions in the customer journey.

W-Shaped Multi Touch Attribution Model: Multi Touch Attribution Model | Hevo Data
Image Source: Marketing Evolution

Full Path Multi Touch Attribution Model

A full path model considers all touch points in the customer experience leading up to the point of purchase – not just the conversion event. Consequently, full path attribution modeling delivers a detailed, start-to-finish assessment of all customer journey touch points.

Full Path Multi Touch Attribution Model: Multi Touch Attribution Model | Hevo Data
Image Source: Marketing Evolution

Custom Multi Touch Attribution Model

If none of the preceding models are suitable for your organization, you may design your own multi-touch attribution model. This entails allocating weights to various touch points based on their influence on conversion.

To build a custom multi-touch attribution model, you must first comprehend the data from your various marketing channels. You must also understand how your prospects interact with multiple touch points.

Customizing your multi-touch attribution model is an excellent approach for getting the most out of your marketing data. It enables you to modify the model to your individual needs and guarantees that all touch points are given credit for conversions.

Even though the various attribution models may appear complicated, digital marketers must grasp how various attribution models work. In the upcoming section, we discuss the 5 step procedure to implement a multi touch attribution model.

5 Steps to Implement Multi Touch Attribution Model

In this section, you will understand how to build a multi touch attribution model.

Step 1: Establish KPIs and Models

Marketers must choose various attribution models based on their organization’s goals. Considerations such as the sales cycle duration and the campaigns should be made while selecting these models.

Your marketers must then choose their KPIs. Selecting the right KPIs will allow your marketers to determine success or failure. Marketers who utilize multi touch attribution often attempt to enhance ROI and user experience; thus, these KPIs must reflect what this means for your organization.

Step 2: Gather Your Team

The next step is to assemble all the members who will be involved in the process. Essentially, anyone in charge of gathering and evaluating data from all channels. Marketing analysts and analytics managers may fall under this category. You may need purchase agreements from budget stakeholders who have a voice in whether or not particular activities and costs are approved.

Finally, you’ll need to incorporate your marketing team, who can improve various consumer touch points depending on the data findings.

Step 3: Deploy Marketing Analytics Software

The next step is to deploy analytics software that supports multi-touch attribution modeling. This allows you to collect all the attribution data you need in one location, which is required for successful analysis.

When working with an enormous volume of data, you must be able to filter and collate data into clear, intelligible, and readily quantifiable measures.

You should select an attribution system that provides specific data about distinct conversion channels and broad information about relevant trends.

Step 4: Multi-Touch Attribution Analysis

Once you have your data, you can begin mining your data for crucial insights. You can try to find answers to the following questions:

  • How efficient are your various marketing channels in moving prospects closer to conversion?
  • Are there any channels that strike out as very well or poorly performing?
  • How do multiple channels collaborate to affect conversions?
  • Is there anything that regularly acts as a barrier to conversion?
  • How long does your typical sales cycle last? How does this differ depending on the channel?
  • Is there anything you can do to enhance conversions on your website or web pages?
  • Are there any touch points that cause a significant decrease or increase in engagement?

Once your marketers get answers to all such questions based on the data supplied by their attribution model, they will get a thorough picture of how their campaign worked. They can use those insights to begin course correction in real-time, allowing them to create a more tailored experience.

Step 5: Continue to Test and Optimize

This step is not a one-time exercise. Instead, your marketers should constantly evaluate their multi touch attribution data to refine and test their strategies. Through regular adjustments and tests, your marketers can establish the optimal techniques and marketing sequences to reach their consumers at the right moment.

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Common Challenges of Multi Touch Attribution

While multi-touch attribution models offer more insights than traditional marketing metrics, they are not without flaws. Your marketers might face a few significant problems when striving to enhance their attribution measurements. In this section, you will understand the common challenges of multi touch attribution.

Requires Complex Set Up and Tracking

A multi-touch attribution model is more challenging to set up and track than other attribution methods. It needs more data and more integration from various marketing channels and platforms. The data you need to integrate needs to be clean, and Data Integration is not easy. For reliable Data Modeling, further procedures must be followed, including Data Cleansing, joining, standardizing, and de-duplicating.

Difficult to Assign Attribution Weightings

Utilizing the multi-touch attribution model might be challenging to determine how much weight to assign to each touch point. The touch points with the most significant influence on conversions should ideally receive the highest share of the marketing budget. On the other hand, identifying those touch points isn’t always straightforward, and applying your attribution weightings might be error-prone.

Absence of Visibility of External Factors

Multi-touch attribution model primarily considers user-level insights. Your marketers lack visibility into external factors that may affect marketing efforts and conversions, such as seasonality if aggregate data is not used.

Lack of Offline Metrics for Calls or Meetings

Multi-touch attribution model is primarily utilized in campaigns that leverage digital marketing platforms in tracking customer activities (clicks, etc.). This creates difficulty for the attribution models to include offline data, such as exposure to a television or print ads. These, however, can be critical components of the customer journey.

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Conclusion

This blog gives you an overview of the multi-touch attribution model, including its benefits, steps for implementation, its types, and the challenges you can face while implementing multi-touch attribution model. 

Multi touch attribution model tracks and credits all recordable customer journey touch points. This assists companies in moving away from the narrower details of single-touch attribution or no attribution analysis.

Businesses may then select the model that best matches their specific go-to-market strategy. However, there will be difficulties in implementing the attribution model. Setting up the proper multi-touch attribution modeling takes time to implement and technically deploy.

To analyze the impact of marketing initiatives, data from various platforms must first be merged from all sources and kept in a single area. Building an in-house solution to do the integration will need significant investment and is time-consuming. This is where automated such as Hevo Data comes into the picture.

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You may share your experience of implementing the multi touch attribution model in the comments below.

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