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Top 7 Types of Attribution Models for You to Try

Sohan Karuna
Published:
November 23, 2021
Updated:
April 29, 2024
Table of Contents

Top 7 Types of Attribution Models for You to Try in 2023

Understanding the impact of marketing efforts on business outcomes has been an important focus area for marketing ever since the beginning. Marketing attribution models have been a lifesaver for businesses in this respect. 

With attribution models, it is now possible to identify touchpoints in the customer journey and attribute the credit for the conversion to appropriate marketing channels. Marketers can optimize their approach and focus on the channels and tactics that drive maximum ROI. 

However, there are several types of attribution models available. These attribution models provide you with answers to different questions, and depending on what type of question you want to answer, the models change. So you need to know each to understand what works best for your business and use case. 

In this blog, you will learn the different types of attribution models with examples and graphs to understand when and how to use each one. 

TL;DR: 

  • Attribution models help businesses understand the impact of their marketing efforts by assigning credit to different touchpoints in the customer journey. 
  • There are two main types of attribution models: single-touch attribution models and multi-touch attribution models. 
  • Single-touch attribution models assign 100% credit to a single touchpoint, such as first-touch, last-touch, or last non-direct touch.
  • Multi-touch attribution models consider all/ most touchpoints. Multitouch attribution models include linear, U-shaped, time decay, or W-shaped models. 
  • Each attribution model has its own strengths and limitations, and the choice depends on the specific use case. For instance, first-touch models are effective for assessing initial brand awareness, while U-shaped models assess the initial engagement and final conversion stages.

What are attribution models?

Attribution models are frameworks that help analyze the customer journey and assign credit to the various touchpoints prior to the conversion. The method for assigning the credit is different for each attribution model depending on either the position of the touchpoint in the customer journey or a data-driven estimation of the significance of that touchpoint. 

Additionally, businesses may need to configure these attribution models to suit their unique circumstances - such as considering an attribution window of, say, 60 days or 365 days depending on their sales cycle or performing the attribution analysis at a contact or opportunity, or account level depending on their sales motion.

With the help of these models, marketers are able to identify channels and tactics that drive more conversions and revenue, driving higher ROI for the business.

The following are some of the main reasons why attribution modeling is important. 

  • They provide insight into channels and campaigns that drive conversions and revenue
  • They help plan and distribute spending to the right marketing channels
  • Also, they help us identify the most influential channels and campaigns for each stage of the marketing and sales funnel.

There are different types of attribution model available for marketers, and we will dive into each in the coming sections.

Categories of Attribution Models

Before delving into how some of the most popular attribution models work, it’s worth understanding the mechanics of attribution modeling. A general categorization of attribution models would include two types. They are - 

  1. Rule-based attribution models
  2. Data-driven attribution models.

1. ‍Rule-based attribution models

These models use predetermined rules for assigning attribution credits to touchpoints. These pre-defined rules determine the weightage or credit for a touchpoint primarily based on its position in the customer journey. Hence, these models are also called Position based Attribution Models. 

In addition to the position, you can also define custom logic to assign differential weights based on the seniority of the customer representative involved in the touchpoint (say Director and above gets higher weight) as well as the amount of effort expended by the buyer in that interaction (attending a webinar required higher effort from a buyer than clicking on a paid search ad). 

2. Data-driven attribution models

These models assign attribution credits to touchpoints based on an algorithmic estimation of the significance of that touchpoint in converting the customer. Some of the popular algorithmic techniques are Markov Chain models and Shapely value-based models. Whilst data-driven attribution is seen as the north star of Multi-Touch Attribution, they are also more expensive to compute, require a large volume of conversions and touchpoints not to be biased, and are harder to debug. 

Whilst each approach has its own pros and cons, a combination of these models may be leveraged to identify marketing leakage and improve ROI.

What are the different types of attribution models?

Single-Touch attribution models

 Different types of single-touch attribution models

Single-touch attribution, also known as single source attribution, assigns 100% of attribution credit to a single touchpoint (or a single source). While they’re easy to use and interpret, single-touch attribution models may skew your results and affect ROI if used in all situations. 

Some of the most common types of single-touch attribution models include:

1. First-Touch Attribution

In this type of attribution model, your customer's first touch-point — whether that be an ad campaign impression, content interaction, or anything else— is deemed the most critical touchpoint in their journey. Hence, this interaction is assigned 100% of the attribution credit. 

For instance, let’s assume that you’re in the market for a project management software and come across an advert for one that catches your attention. The ad prompts you to visit the company’s website. 

After landing on their “features” page, you follow through with more research and come across the company’s weekly blog — before finally signing up for a demo. In this case, the advert you clicked on is your first impression of the brand and product. Hence, a first-touch attribution model would reward the advert with 100% of the attribution credits.

An example of first-touch attribution model‍

The First Touch attribution model is most effective in identifying the channels or campaigns that drove your brand's initial awareness amongst your prospects. This would work best for businesses with low sales cycles or a PLG flow, or if you are trying to assess the effectiveness of only Branding Campaigns and Top of the funnel content. 

In a normal B2B sales process that stretches over weeks and months, it would be presumptuous to assign 100% of the credit to the very first touchpoint.

2. Last-Touch Attribution

In a similar vein to first-touch attribution, a last-touch attribution model assigns 100% of the attribution credits to the touchpoint closest to a customer’s conversion milestone.

This would imply that the last impression made on the customer before their decision to convert was the most prominent in their journey. 

Continuing with the previous example of the PMS, the blog piece you come across before scheduling a demo would be the last touch. And so, out of all the touch points that influenced your decision to sign up for a demo, attribution credits will be solely assigned to the final one.

An example of last-touch attribution model

3. Last Non-Direct Touch Attribution:

This model assigns 100% attribution credit to the last non-direct touchpoint. A non-direct touchpoint is an interaction that is guided by a specific source the business sets up (like an ad, email campaign, newsletter, etc.). 

When your website traffic doesn’t come from a known source, they are considered direct traffic (traffic that came from prospects directly entering the company URL into the browser, for example). 

Let’s assume that a lead interacted with your brand 5 times, each touchpoint is as given below.

  • Touchpoint 1 - Prospect clicks on a PPC ad
  • Touchpoint 2 -  Prospect arrives at your site’s landing page
  • Touchpoint 3 - Prospect subscribes to your newsletter
  • Touchpoint 4 - A week later, your prospect clicks on a newsletter campaign
  • Touchpoint 5 - Prospect directly visits the website and initiates a free trial before purchasing a subscription 

Touchpoints 1, 2, 3, 4, and 5 constitute all the prospect’s interactions with your brand that led to them purchasing your product. Keep in mind that, in reality, businesses deal with numerous prospects interacting with several touchpoints, making the process of mapping the customer journey far more convoluted.

So if we consider the above-given example, this model would assign 100% sales credit to touchpoint 4 or the newsletter campaign clicked on, as that was the last non-direct source before the sale. This model assumes that every interaction is a consequence of the non-direct campaign, hence making it the most influential.

An example of last non-direct attribution model

Is Single-Touch attribution an INEFFECTIVE model?

Many businesses and marketing aficionados are of the opinion that single-touch attribution is not an effective model on its own. It is often considered to be a one-dimensional approach that fails to faithfully represent a customer’s conversion journey down the funnel. 

As we have discussed, while single-touch models may have their own relevant use cases (like for products with shorter sales cycles), it may not be as effective in identifying the most influential touch-point in a B2B customer journey. 

If big data in marketing has proved anything, it's that customer journeys can be non-linear, sophisticated paths spanning several channels and mediums. Assigning 100% of the credit to a single touchpoint will rarely be sufficient.

Multi-Touch attribution models‍

Multi-touch attribution modeling is the holy grail of marketing attribution. As customers’ buying patterns evolve and become increasingly scattered, a model that can track and account for all these interactions would be more representative of the buying journey.

A multi-touch attribution model accounts for all the touchpoints encountered in a customer’s conversion journey. It’s a holistic view that helps paint a substantially better picture of patterns and behavior than single-touch models.

Remember to keep in mind that the goal of multi-touch attribution isn’t just to map out customers’ interactions. It is also employed to understand which touchpoints influence a customer the most, which touchpoints work in conjunction with each other, and the relative probabilities of channel interactions among different customer paths. 

With this established, there is still the issue of assigning credits to many touchpoints. To help illustrate multi-touch attribution better, here are a few of the most commonly used models:

An example of last non-direct attribution model

‍4. Linear Attribution

A linear attribution model assigns attribution credits evenly among all touchpoints. While this model is far more illustrative than any of our single-touch attribution options, it's a relatively simplistic approach when compared to its nonlinear variants. 

Let’s assume that the total number of touchpoints in our PMS example is four: An advert, a blog, a review, and a retargeting campaign. Linear attribution would reward 25% of attribution credits to each of these touchpoints.

An example of linear attribution model

Of course, in reality, the number of touchpoints a B2B customer goes through is significantly higher — so the weights for each one are likely to be far smaller.

5. U-Shaped Attribution

The U-shaped model assigns attribution credits to all touchpoints — but assigns higher credits specifically to the first and last touchpoints. This would imply that your customer’s first and last interactions prior to the conversion milestone are the two most valuable touch-points in their journey. 

Consider the same four touch points as with the previous example (Ad, Blog, Review, and Retargeting campaign). This time, maybe 40% of the credits will be assigned to the first and last touch points each. The two touchpoints in-between will receive only 10% each as they are deemed less influential to the conversion decision.

An example of U-shaped attribution model

The model laid out in a bar graph takes the shape of the letter ‘U’, hence the name.

6. Time Decay Attribution

Time decay attribution assigns attribution credits in an ascending cascade. 

What this means is that each touchpoint is given progressively higher credit, with the first touchpoint having the least credit and the last touchpoint having the most. This is an effective tool in mapping out a customer’s conversion journey. 

The model works on the assumption that touchpoints closer to the conversion were far more influential than touchpoints further away from the conversion. Again, using our handy four touchpoint PMS example, a time decay model would assign attribution credits in this manner: 5% for the advert, 15% for the blog, 20% for the reviews page, and 60% for the retargeting campaign.

An example of time decay attribution model

7. W-shaped attribution

This type of attribution model is similar to the U-shaped model we discussed earlier. 

The first and the last touchpoints are also given importance in this model, just as in the U-shaped model. But during the middle of the sales funnel, if you generate quality leads, then that touchpoint is also considered influential. And therefore is given equal importance as that of the first and last touchpoint. 

So, if there are 5 first touchpoints in total, the first, middle, and last touchpoints will be given 30% each and the rest only 5%.

To give you a clear-cut idea, take five touchpoints. For example, an advert, a blog, a case study, reviews, and finally, retargeting campaign. 

A prospect got in touch with your business through an advertisement, prompted to read your blogs, where they decide to subscribe to your business’s newsletter. Thereby generating a lead towards the middle of the process. The lead then continued to follow up on their research by constantly staying in touch with the business through newsletters. And finally, the lead converts by signing up for a free trial. Following is an example of a graphical representation of the W-shaped attribution model for the given example. 

An example of W-shaped attribution model

Limitations of Attribution Models

Single-touch attribution models (like first-touch, last-touch, and list non-direct touch) are simple to implement but have several disadvantages. They oversimplify the customer journey by assigning credit to a single touchpoint, ignoring the contributions of other touchpoints. Similarly, these models also neglect the aggregate effect of multiple touchpoints over time. What results is inaccurate credit allocation, because the model disregards individual customer behavior and other factors. 

On the other hand, multi-touch attribution models are definitely more complex because they work with complicated algorithms and technology. This often requires expert knowledge and pro- marketing knowledge of marketing software. The impressions from data can be misleading because of shortcomings like wrong assumptions and wrong weightage assigned to each marketing activity. To add on, while multi-touch attribution models are efficient for data- rich digital marketing campaigns, they are not equipped to measure external factors like word-of-mouth, seasonality or pricing.  

Like single touch attribution models, multi-touch attribution models can also miss out on giving the full picture. Linear attribution models assume that all touchpoints have equal influence on customer behavior, which is not always the case. U-shaped, W-shaped and Time-Decay models run the risk of oversimplifying the customer journey since they assign more credit only to some touchpoints, while neglecting others. This could cost the model some valuable insights and paint an incomplete picture. The time-decay attribution model considers the recency of the customers close to the conversion event, but it can still overlook the significance of earlier touchpoints.

Takeaway

Needless to say, all attribution models are not appropriate for all use cases. Different attribution models aid different types of marketing campaigns and can reveal different insights into the customer journey.

Attribution Model How It Works Use-cases
First-touch The first touchpoint is assigned 100% of the attribution credit
First-touch attribution is most effective in identifying the channels or campaigns that drove your brand's initial awareness amongst your prospects. This model can help assess the impact of initial brand awareness efforts and gauge the success of activities like advertising campaigns.
Last-touch
The last touchpoint is assigned 100% of the conversion credit
This attribution mode is useful in cases where the final touchpoint is the most influential in improving conversion. For instance, you can use last-touch attribution in cases where customer journeys are short, when the customer's path to conversion is straightforward and quick, or when you need to get a clear understanding of the touchpoint responsible for the final conversion.
Last-touch non-direct
The last non-direct touchpoint is assigned 100% of the attribution credit. A non-direct touchpoint refers to customer interactions that occur outside of direct company communication channels and can influence customer decisions and brand perceptions (like word of mouth or online reviews)  This model helps understand the role of nurturing touchpoints. In customer journeys, there are often touchpoints that play a crucial role in guiding leads towards conversion. This model helps us identify and acknowledge their contribution to the conversion.
Linear All touchpoints are evenly assigned attribution credit. By assigning equal credit to all touchpoints, you can identify the strengths and weaknesses of each channel and make data-driven decisions on budget allocation and campaign optimization.
U-shaped All touchpoints are assigned attribution credits– but higher credits are assigned specifically to the first and last touchpoints The U-shaped attribution model considers the impact of branding and remarketing touchpoints throughout the customer journey. It recognizes the role of initial brand awareness and subsequent remarketing efforts in driving conversions. With this model, one can assess the effectiveness of your branding and remarketing strategies in nurturing leads and increasing conversion rates.
W-shaped Like the U-shaped attribution model, the first and the last touchpoints are also given importance in the W-shaped attribution model. However, if you generate quality leads in the middle of the sales funnel, then that touchpoint is also considered influential And is, therefore, given equal importance as that of the first and last touchpoint.  It helps identify touchpoints that contribute to initial awareness, consideration, and final conversion. This attribution model is beneficial for analyzing the effectiveness of campaigns across various channels, evaluating mid-funnel touchpoints, and optimizing lead nurturing efforts. It helps you identify touchpoints that contribute to building trust, addressing customer concerns, and influencing the decision-making process. 
Time-decay Each touchpoint is given progressively higher credit, with the first touchpoint having the least credit and the last touchpoint having the most. Time decay attribution considers the cumulative effect of touchpoints over time. It recognizes the value of consistent and continuous engagement with customers throughout their journey. This attribution model can be valuable for assessing the impact of ongoing nurturing activities, such as email marketing campaigns or drip campaigns, in driving conversions and maintaining customer engagement.

In the end, a lot of the use cases for these types of attribution models are subjective. The decision to opt for a specific model can be based on several reasons spanning from the nature of your product to the extent of your brand equity. It may also vary based on the specific kind of insight you want to achieve. 

More often than not, you will find yourself using more than just one model with several stipulations and custom values for each variant. Fortunately, the progressive ingenuity of AI and constant innovations around attribution modeling will render your experience less of a trial by fire and more of an intuitive, insightful practice. 

Leveraging the right marketing analytics platform will be the first step in deciding the attribution model required for your company/business. As we said, it's best to rely on more than one model to improve your desired results. And for that, you will need an expert team, like Factors, that understands your requirements and guides you in leveraging the right techniques. 

With Factors.ai, you can easily track the effectiveness of your campaigns and content, identify which channels are driving the most conversions, and optimize your marketing efforts for maximum results. The tool also offers a user-friendly interface and customizable dashboards, making it easy for you to access and interpret your data.

Interested? Sign up here for a FREE trial, or contact our team to get a Free consultation now. Here is the contact email for your reference - solutions@factors.ai

Bonus FAQs

1. How do I choose the right attribution model for my business?

In order to choose the right attribution model, you will need to know the target market, the target audiences, and so on. And once you have everything set, consider the following.

  • Define your business goals. The attribution model you select must align with your business goals. Is it sign-ups? Leads? SQLs? Or just organic traffic.
  • Once you have defined the goal, understand the types of attribution models and how each model allocates credits to the touchpoints.
  • Evaluate the data you have to get an idea of the current touchpoints where your business is driving conversions [goals].
  • Test out different models to see which is more effective.
  • And finally, constantly review the results and update the models according to the business needs. 

2. How do attribution models help find the gap in the customer journey?

As we discussed earlier in the blog, each attribution model provides insights into your customers' touchpoints with your business. Which itself gives the different paths each customer has taken to reach your service. 

Thereby helping you understand the customer journey and find the touchpoints you missed during your initial marketing campaign.

3. How do attribution models help in improving the conversion rate?

Attribution models help improve the conversion rate by identifying which touchpoints in the customer journey are most effective in driving conversions. 

They enable data-driven decisions helping businesses optimize their marketing budget and allocate resources efficiently to boost conversion rates.  

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