Marketing Attribution Models: Pros and Cons of Each Type

9 Min Read

Marketing attribution models are essential for understanding how your marketing efforts contribute to conversions and sales. Accurately attributing credit to different marketing touchpoints allows you to make more informed decisions about where to allocate your resources. 

This comprehensive guide explores various marketing attribution models, their pros and cons, and how they can impact your marketing strategy.

What Are Marketing Attribution Models?

Marketing attribution models are frameworks that define how to assign credit for conversions and sales to various touchpoints in a customer’s journey. These touchpoints can include email campaigns, social media interactions, PPC ads, organic searches, and television ads. 

The goal is to identify which of your marketing efforts are giving you the most bang for your buck.

Why Are Marketing Attribution Models Important?

Attribution models help with the following: 

Data-Driven Decision Making

Modern ad campaigns can’t rely on guesswork. You need detailed insights about which formats and content are making the most significant impact on your audience. Attribution models help you determine where conversions are coming from so you can allocate your budget more efficiently and avoid wasting precious marketing dollars. 

Budget Allocation

Attribution models help you understand which channels deserve more investment and which ones may need to be reevaluated. This ensures that your marketing budget is spent wisely — resulting in a stronger return on investment (ROI).

Optimization and Campaign Improvement

Accurate attribution data facilitates continuous campaign optimization. You can make necessary adjustments to improve reach and efficacy by identifying which touchpoints are underperforming. This ongoing optimization leads to better performance and higher conversion rates over time. 

Customer Journey Insights

Each attribution model sheds light on a specific leg of the customer journey. Understanding a customer’s path from brand awareness to conversion is vital for creating effective marketing strategies. 

Attribution models help you learn how consumers interact with your brand across different channels and touchpoints. Use this information to create more personalized, targeted marketing campaigns that resonate with your audience.

ROI Measurement

Measuring and maximizing your return on investment is key to the long-term success of your marketing efforts. Attribution models enable you to calculate the ROI of your marketing efforts accurately. When you know which touchpoints contribute the most to conversions, you can ensure that your spend delivers the desired returns. 

First-Touch Attribution

First-touch attribution assigns all credit for conversion to the first interaction a customer has with your brand on their purchasing journey. 

Pros

The first-touch model represents one of the simplest attribution frameworks. Whatever interaction occurred first gets 100% of the credit for a conversion, regardless of how many other touchpoints took place before a purchase was made. 

First-touch attribution highlights the effectiveness of top-of-funnel activities. It’s useful for understanding the initial engagement channels and how customers get to know your brand.

Cons

The only real downside to first-touch attribution is that it doesn’t reveal which ad was the final touchpoint. However, it does account for the fact that the first ad engagement eventually led to a sale or transaction. The initial connection between a customer and your brand is the most important, as no subsequent touchpoints could have occurred if not for that initial engagement. 

Last-Touch Attribution

The last-touch attribution model is the exact opposite of the first-touch framework. Under this model, the final interaction that occurs before conversion receives 100% of the credit for the transaction. 

Pros

The last-touch model is simple and straightforward. It emphasizes the importance of closing the deal after you’ve effectively nurtured a lead and generated intrigue in your brand or services. This model helps identify effective closing strategies while also accounting for the importance of nurturing. 

Cons

The last-touch model disregards the impact of earlier interactions. It does not provide any insights into how a customer became aware of your brand in the first place or what nurturing activities they participated in along the way. 

Last-touch attribution can undervalue the importance of the initial interaction, and you’ll have little to no insights about how someone entered the sales funnel. 

Linear Attribution

The linear attribution model spreads credit across all touchpoints equally. For instance, if a customer interacts with your brand ten times before making a purchase, each touchpoint would receive 10% of the credit. 

Pros

Linear attribution treats all interactions as equally important to the sales funnel. It provides a complete look into the customer journey and can help you better understand factors that influence a person’s decision. You should consider this model if your campaigns consistently incorporate the same touchpoints. 

Cons

The linear attribution model is almost too simple — it doesn’t adequately reflect the complexity of many customer journeys. While all touchpoints have some impact on the customer’s decision-making process, they don’t carry equal weight. Equally distributing credit to every interaction may not highlight particularly influential touchpoints, such as the first and last. 

Lead-Conversion Touch Attribution

The lead-conversion touch attribution model assigns credit to the touchpoint that directly leads to a conversion. It is pretty similar to the last-touch model. However, you aren’t required to give 100% of the credit to the final touch. 

Pros

The lead-conversion model focuses on the final influence before a conversion. It highlights the effectiveness of your closing strategies and can help reveal which channels are most impactful at converting customers. 

Cons

This model has two major flaws. Unless you customize it to account for earlier interactions, it neglects how someone first became aware of your brand and how those experiences shaped their future behavior. 

More importantly, lead-conversion attribution might cause your budget to be skewed toward closing touchpoints while neglecting brand awareness and lead-gen activities. 

Time-Decay Attribution

Time-decay attribution is one of the more complex conversion analytics models. Under this framework, you’ll give a larger portion of the credit to the touchpoints that occur close to the conversion event, and less to earlier interactions. 

Pros

Time-decay reflects the influence and power of recent interactions. It also balances the contributions of early and late touchpoints while acknowledging the recency effect on conversions. 

Cons

Time-decay models are complicated to implement. You’ll have to create a formula or rule for reducing the credit assigned to earlier touchpoints based on the time that has passed. This framework also tends to undervalue significant early touchpoints. 

For instance, suppose that a customer first became aware of your brand six months ago after seeing a Connected TV ad. They immediately followed your company on social media but waited until last week to make a purchase. A particularly creative social media post pushed them over the edge, resulting in a conversion. 

Under the time-decay model, that initial ad would receive very little credit. However, the customer probably wouldn’t have seen your social media content without the early CTV ad. 

U-Shaped Attribution (Position-Based)

U-shaped attribution allocates 40% of the credit to the initial and final touchpoints. It assigns the last 20% to the middle interactions. 

If a customer interacts with your brand on six different occasions before making a purchase, each middle touchpoint receives 5% of the credit. However, if they interact with you dozens of times, the middle interactions receive a minuscule amount of credit. 

Pros

The U-shaped model emphasizes the importance of both introductory and closing touchpoints. This framework recognizes the value of nurturing interactions while acknowledging that open and closing touchpoints are the most valuable. 

Cons

U-shaped models are complicated to set up and analyze, and they may overvalue the first and last interactions. 

W-Shaped Attribution

The W-shaped attribution model allocates 30% of credit to the initial, middle, and last touchpoints. The remaining 10% is then distributed among other interactions. W-shaped frameworks identify the “middle” touchpoint as the one that converts a prospect into a vetted lead. 

Pros

The W-shaped model highlights the three key conversion points and provides a balanced view of the customer journey. It can therefore be useful for campaigns with distinct stages. 

Cons

This model is one of the most complex and difficult to implement. Also, with the W-shaped model determining which event transformed a prospect into a lead can also be challenging. 

Custom Attribution

Custom attribution models are tailored to fit the unique needs of your business and marketing strategy. You can combine concepts from other frameworks to place the appropriate amount of emphasis on each interaction. 

Pros

Custom models are highly flexible and adaptable. You can design them to match your specific goals and customer journey. They provide the most accurate representation of your unique marketing efforts. 

Cons

Setting up a custom attribution model requires significant time and research. You must understand how your audience values each touchpoint so you can assign credit accordingly. Overemphasizing the wrong touchpoints could lead to budget mishaps and underperforming ad campaigns. 

Other Commonly Used Terms in Marketing Attribution

Choosing the right model is only the beginning. You also need to familiarize yourself with common marketing attribution concepts, including: 

Cross-Device Attribution

Cross-device attribution is a method that identifies and tracks a user’s interactions across multiple devices, such as smartphones, tablets, and desktops.

Cookieless Attribution

Cookieless attribution refers to the process of assigning credit to marketing efforts without relying on third party cookies, using alternative data collection methods such as first party data, server-side tracking, and privacy-compliant identifiers.

Multi-Touch Attribution

Multi-touch attribution is an approach that allocates conversion credit across multiple touchpoints in a customer’s journey, enabling marketers to assess the impact and contribution of each interaction.

Multi-Channel Attribution

Multi-channel attribution assigns credit to the various marketing channels that contribute to a conversion, such as social media, email, search, and display advertising.

View-Through Attribution

View-through attribution is a measurement technique that gives credit for a conversion to display ads that a user has seen but not interacted with directly, recognizing the influence of ad impressions.

Click-Through Attribution

Click-through attribution is a model that attributes the entire credit for a conversion to the last ad that a user clicked on before completing a desired action.

Attribution Models and Traditional TV Advertising

Traditional TV advertising poses a challenge for attribution modeling due to the lack of direct interaction data. However, advancements in technology and the rise of CTV have improved the ability to link television ads to specific user actions. 

Traditional television advertising relies heavily on linear attribution, which oversimplifies the customer journey. Connected TV, on the other hand, uses a combination of first-touch models and other data points to provide a better look into the customer’s journey. Learn more about the different TV attribution models here.

How Connected TV Changes Attribution Modeling

Every marketing attribution model provides unique strengths and potential drawbacks. You should choose a framework that aligns with your goals and needs. For instance, MNTN offers a modernized first-touch attribution model, Verified Visits™. It is the best fit for brands engaging in CTV advertising. 

CTV changes the playing field for attribution models because you can gather a wide range of complementary data to support the insights provided by Verified Visits™. These marketing metrics allow you to tie desired outcomes back to specific ads seen by the viewer. 

Schedule a demo of MNTN and learn more about how our solutions help you create more powerful and efficient television advertising campaigns. 

Marketing Attribution Models: Final Thoughts

Marketing attribution models play a critical role in advertising analytics. Choosing a model that’s a good fit for your business and its goals will help you better understand what works, what doesn’t, and how to improve. 

Don’t underestimate the power of a simple yet effective model like first-touch attribution. These models — and especially a modernized version like Verified Visits™ — provide actionable information about the reach and impact of your ads.cceeds by offering a complete solution to utilize source validation and ensure accurate credit allocation.

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