Demystifying Marketing Attribution Models for Successful Campaigns

By:

Ashley Levesque

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In a 2023 marketing attribution trends research study, Banzai found that 2/10 marketers do not use an attribution model in their reporting. However, paired with a shrinking marketing budget, today's marketers are feeling significant pressure to prove ROI. Marketing attribution models are a framework that can help marketers prove their impact and optimize their marketing strategies.

What are marketing attribution models?

Marketing attribution models are reporting frameworks that help marketers understand and analyze the impact of different marketing touchpoints on the customer journey. Attribution data measures the marketing effectiveness of channels, advertisements, content, and campaigns. Marketing teams use attribution to learn what's performing within their marketing mix.

Why do marketing attribution models matter?

Marketing attribution models help marketers measure marketing performance. By understanding the impact of each touchpoint in the customer journey, businesses can optimize their marketing efforts, allocate budgets efficiently, and maximize return on investment (ROI). This is especially important in multichannel marketing strategies where marketers need to accurately identify how their marketing channels are comparatively performing.

Single-touch vs. multi-touch attribution

There are two different types of attribution models: single-touch and multi-touch attribution.

Single-touch attribution models

Single-touch attribution models assign 100% credit of a conversion to a single touchpoint in the customer journey. For example, in a single-touch attribution model, if a customer made a purchase after clicking on a Facebook ad, the entire credit for the conversion would be assigned to the Facebook ad. Other touchpoints in the customer journey, such as email campaigns or search ads, would not receive any credit.

Single-touch attribution models are relatively simple to implement and measure, but they can oversimplify the customer journey by disregarding the influence of other touchpoints. They may not accurately reflect the true impact of different marketing channels and strategies on the overall conversion process.

There are two common single-touch models:

First-touch attribution

The first-touch attribution model (also known as first interaction attribution model) gives full credit to the first touchpoint a user interacts with during their customer journey. This model is useful for evaluating the initial impact of a particular marketing channel or campaign. However, it may overlook the influence of other touchpoints that contributed to the conversion.

Pros of first-touch attribution:

  1. Simplicity: First-touch attribution is a straightforward and easy-to-measure model. It assigns 100% of the credit for a conversion to the first touchpoint, which makes it simple to understand and analyze.
  2. Cost efficiency: First-touch attribution allows you to streamline marketing budgets by focusing on the channels or campaigns that generate the first touchpoint. By investing in these sources, you can potentially reduce marketing costs and improve overall ROI.
  3. Power to brand awareness: First-touch attribution recognizes the importance of early touchpoints in the customer journey. By giving all credit to the first touch, it highlights the significance of building brand awareness and capturing initial interest, providing a business case for increased investment in these top of funnel activities.
  4. Easy to implement for certain channels: Some channels, such as email marketing or direct referrals, usually have a clear first-touch element. In such cases, first-touch attribution can be a practical and efficient approach to evaluate their effectiveness.
  5. Time-saving: Since first-touch attribution allocates all credit to the first interaction, it can save time (and headaches) spent tracking and analyzing multiple touchpoints.
  6. Clarity on lead generation: First-touch attribution helps identify the specific sources that generate initial leads, allowing businesses to focus on optimizing those sources and improving lead generation strategies.
  7. Useful for goal tracking: When tracking specific goals or KPIs, such as lead generation or initial brand awareness, first-touch attribution can provide a clear understanding of which touchpoints are driving those goals.

Cons of first-touch attribution:

  1. Inaccurate customer journey: First-touch attribution assigns all the credit for a conversion or sale to the first touchpoint a customer encounters. This disregard for the contribution of subsequent touchpoints may provide an oversimplified view of the customer journey, ignoring the impact of other important touchpoints on the path to conversion.
  2. Limited Understanding: By focusing solely on the first touchpoint, businesses may only consider the initial interaction with the customer and miss out on the subsequent touchpoints that influence their decision-making process. This limited understanding of the customer journey may lead to ineffective marketing strategies and budget allocations.
  3. Overemphasis on Top-of-Funnel Activities: First-touch attribution tends to prioritize top-of-funnel marketing activities, such as awareness building and brand exposure, as they are typically the first touchpoints with customers. Over-reliance on these activities may disregard the contribution of other touchpoints, such as nurturing efforts or customer support, which also play a crucial role in conversion.
  4. Neglecting Customer Behavior Changes: With the increasing number of touchpoints available to customers, their behavior and decision-making process have become more complex. First-touch attribution fails to capture the changes in customer behavior as they interact with different touchpoints throughout their journey. This oversight may lead to misinterpretation of customer preferences and ineffective marketing strategies.
  5. Inaccurate Allocation of Budget and Resources: By attributing all the credit for a conversion to the first touchpoint, businesses may wrongly allocate budget and resources to marketing channels that are not actually driving conversions. This misallocation can lead to inefficient spending and missed opportunities for optimizing marketing efforts.
  6. Ignoring Customer Retention: First-touch attribution primarily focuses on the acquisition phase of the customer journey, neglecting the importance of customer retention and loyalty. By not considering the impact of subsequent touchpoints on retention, businesses may fail to prioritize activities aimed at retaining existing customers, potentially leading to high churn rates and missed opportunities for repeat sales.
  7. Failure to Account for Multi-Channel Interactions: In today's multi-channel marketing landscape, customers often engage with multiple touchpoints before making a purchase decision. First-touch attribution fails to account for the influence of these multi-channel interactions on the conversion process. This limitation can hinder a comprehensive understanding of the customer journey and result in inaccurate attribution of credit.

Best practices for first-touch attribution:

  • Use first-touch attribution to gain insights into which channels or campaigns generate initial interest
  • Combine it with other attribution models for a more comprehensive analysis

Last-touch attribution

The last-touch attribution model (also known as the last interaction attribution modle) gives full credit to the touchpoint that happens immediately prior to the conversion. This model is useful for evaluating the final converting touchpoint but, it again overlooks the influence of other touchpoints that contributed to the conversion.

Pros of last-touch attribution:

  1. Simplicity: Last-touch attribution is easy to implement and understand. It attributes all the credit for a conversion to the last touchpoint before conversion, making it straightforward to determine the effectiveness of specific marketing efforts.
  2. Clarity: Last-touch attribution provides a clear and definitive path to a conversion. It highlights the final touchpoint that directly influenced the conversion, allowing marketers to focus their efforts on optimizing that specific touchpoint.
  3. Cost effectiveness: Last-touch attribution can help marketers identify and allocate their budget more efficiently. By attributing the conversion to the last touchpoint, marketers can easily determine which channels or campaigns have the most impact and allocate more resources accordingly.
  4. Quick decision-making: Since last-touch attribution provides a simple and direct measure of the effectiveness of a specific touchpoint, marketers can make quick decisions regarding their marketing strategy. They can easily identify what's working and what isn't, allowing them to adjust their tactics accordingly.
  5. Enhanced optimization: By focusing on the last touchpoint, marketers can optimize that particular stage of the customer journey to improve conversion rates. They can tweak messaging, design, or targeting to make the final touchpoint more compelling and increase the chances of conversion.
  6. Ease of comparison: Last-touch attribution allows for easy comparison between different channels or campaigns. Marketers can clearly see the impact of each touchpoint, making it easier to determine which channels are performing better and where to invest resources.
  7. Enhanced accountability: Last-touch attribution allows for clear accountability for conversions. By attributing the conversion to the last touchpoint, it is easier to track the effectiveness of individual campaigns or initiatives and hold responsible teams or channels accountable for results.

Cons of last-touch attribution:

  1. Ignores the entire customer journey: Last-touch attribution only gives credit to the last touchpoint or interaction before a conversion takes place. This means that all the previous touchpoints and marketing efforts leading to that point are ignored, resulting in an incomplete understanding of the customer journey.
  2. Overvalues the final touchpoint: By assigning all the credit for a conversion to the last touchpoint, the attribution model may overvalue the impact of that touchpoint. This can lead to misallocation of marketing budgets and inaccurate performance evaluation of different marketing channels.
    3. Neglects the role of other touchpoints: Last-touch attribution implies that all previous touchpoints, even if they had a significant impact on the customer's decision-making process, receive no credit. This can underestimate the effectiveness of those touchpoints and hinder marketing strategies that could have built brand awareness or engaged customers earlier in the buying process.
    4. Not suitable for complex sales cycles: In B2B or high-value sales, the decision-making process tends to be longer and involves multiple touchpoints. Last-touch attribution fails to capture the multitude of touchpoints and interactions that influence the customer's decision, leading to a distorted picture of the marketing efforts' effectiveness.
    5. Inaccuracy in multi-channel marketing: In today's multi-channel marketing landscape, customers often interact with a brand through various channels before making a purchase. Last-touch attribution fails to account for these multi-channel interactions and gives all the credit to the final touchpoint, disregarding the value of other channels that contributed to the conversion.
    6. Lack of granular insights: As last-touch attribution focuses solely on the final touchpoint, it fails to provide detailed insights into the effectiveness of individual marketing actions or campaigns. This hampers marketers' ability to optimize their strategies and make data-driven decisions based on a holistic view of the customer journey.
    7. Doesn't consider the influence of offline interactions: Last-touch attribution primarily focuses on online interactions and often overlooks the impact of offline tactics, such as in-store experiences or customer service interactions. This can lead to an incomplete understanding of the overall marketing impact and customer behavior.
    8. Fails to measure brand-building activities: Brand-building efforts, such as display ads, content marketing, or social media campaigns, play a vital role in creating awareness, shaping perceptions, and influencing purchase decisions. However, last-touch attribution may not accurately reflect the value of these activities, as they often occur earlier in the customer journey and are not directly responsible for the final touchpoint.

Best practices for last-touch attribution:

  • Use last-touch attribution when analyzing a specific part of the customer journey, such as the final touchpoint before conversion
  • Combine it with other attribution models for a more comprehensive understanding

Multi-touch attribution models

Multi-touch attribution models distribute credit across multiple touchpoints. They provide a more comprehensive view of the customer journey and give credit to each touchpoint that contributes to conversion. Here are some common multi-touch attribution models:

Linear attribution

Linear attribution assigns equal credit to all touchpoints throughout the customer journey. It assumes that every touchpoint has an equal impact on the conversion.

Pros of linear attribution:

  • Provides a balanced view of the customer journey
  • Recognizes the contribution of each touchpoint

Cons of linear attribution:

  • May not accurately reflect the true impact of each touchpoint
  • Doesn't consider the varying importance of touchpoints

Best practices for linear attribution:

  • Use linear attribution to get a rough idea of the overall impact of each touchpoint
  • Combine it with other attribution models for a more detailed analysis

Time decay attribution

Time decay attribution gives more credit to touchpoints that are closer in time to the conversion. It assumes that the closer a touchpoint is to the conversion, the more influential it is.

Pros of time decay attribution:

  • Reflects the diminishing influence of touchpoints as time progresses
  • Provides insights into the role of touchpoints leading up to conversion

Cons of time decay attribution:

  • May overlook the importance of early touchpoints that sparked initial interest
  • Doesn't consider the varying impact of different touchpoints

Best practices for time decay attribution:

  • Use time decay attribution when analyzing the influence of touchpoints leading up to the conversion
  • Combine it with other attribution models to get a more comprehensive understanding

Position-based U-shaped attribution

Position-based U-shaped attribution assigns 40% of the credit to the first and last touchpoints, and distributes the remaining 20% across the intermediary touchpoints. It recognizes the importance of both the first and last touchpoints while acknowledging the contribution of intermediate ones.

Pros of position-based U-shaped attribution:

  • Recognizes the value of both the first and last touchpoints
  • Accounts for the impact of intermediary touchpoints

Cons of position-based U-shaped attribution:

  • May not be suitable for all customer journeys
  • Doesn't account for varying degrees of influence among different touchpoints

Best practices for position-based U-shaped attribution:

  • Use position-based U-shaped attribution to gain insights into the crucial touchpoints at the beginning and end of the customer journey
  • Combine it with other attribution models for a more detailed analysis

W-shaped attribution

W-shaped attribution assigns 30% of the credit to the first touchpoint, the last touchpoint, and a middle touchpoint. It acknowledges the impact of the first touchpoint, a crucial middle touchpoint, and the final touchpoint.

Pros of W-shaped attribution:

  • Accounts for the influence of three key touchpoints in the customer journey
  • Provides insights into the initial engagement, middle consideration, and final conversion touchpoints

Cons of W-shaped attribution:

  • May not cover all important touchpoints in complex customer journeys
  • Doesn't consider the varying impact of different touchpoints

Best practices for W-shaped attribution:

  • Use W-shaped attribution when analyzing customer journeys with specific middle touchpoints that play a significant role
  • Combine it with other attribution models for a more comprehensive understanding

Z-shaped attribution

Z-shaped attribution distributes credit across the first touchpoint, a middle touchpoint, and the last touchpoint. It emphasizes the role of the first and last touchpoints and one intermediate touchpoint.

Pros of Z-shaped attribution:

  • Accounts for the influence of three key touchpoints in the customer journey
  • Provides insights into the initial engagement, middle consideration, and final conversion touchpoints

Cons of Z-shaped attribution:

  • May not capture the impact of other important touchpoints
  • Doesn't consider the varying influence of each touchpoint

Best practices for Z-shaped attribution:

  • Use Z-shaped attribution when analyzing customer journeys with specific intermediate touchpoints that have a significant impact
  • Combine it with other attribution models for a more comprehensive analysis

Data-driven attribution models

Data-driven attribution models use advanced algorithms to attribute credit to touchpoints based on their statistical significance and contribution to conversions. These models leverage machine learning techniques to identify patterns and make accurate credit assignments.

Custom attribution

Custom attribution models are tailored to a business's unique goals and objectives. They can be based on a combination of various single-touch and multi-touch models, as well as data-driven approaches.

Algorithmic attribution

Algorithmic attribution models use sophisticated algorithms to analyze large datasets and determine the most impactful touchpoints. These models dynamically adjust credit assignments based on the data and customer behavior.

Choosing the right attribution model

Choosing the right attribution model for your business depends on several factors and goals. Here are some steps to help you choose the right attribution model:

Define your business goals

Understand what you want to achieve with your marketing efforts. Are you focused on driving sales, increasing brand awareness, or generating leads? This will help you align your attribution model with your objectives.

Evaluate your buyer’s journey

Analyze your customer journey and identify the touchpoints where customers interact with your brand. This will help you understand how various channels contribute to conversions and where you need to give credit.

Consider your industry and product

Different industries and product types have varying buying cycles and user behaviors. Consider how your industry operates, the typical path to conversion, and the role of different channels in influencing customers.

Analyze historical data

Look at your historical data and assess the performance of various channels under different attribution models. This will provide insights into how each model attributes credit and which one aligns best with your data patterns.

Experiment and test

Consider testing different attribution models on a smaller scale before implementing them across your entire marketing strategy. This will help you assess the impact and effectiveness of each model.

Just decide

I know this is a strange one, but sometimes the hardest part of choosing an attribution model is getting buy in across the organization on which option to choose.

Use machine learning and data-driven approaches

Adopt advanced attribution models that utilize machine learning algorithms to analyze real-time data and attribute credit accurately. These models can consider multiple touchpoints and deliver more accurate results.

Remember, there is no one-size-fits-all attribution model. It often requires a combination of approaches and experimentation to find the model that works best for your business.

Common challenges with marketing attribution

Marketing attribution comes with its fair share of challenges:

1. Identifying and quantifying the impact of each marketing touchpoint: It can be challenging to accurately attribute the contribution of each marketing channel or tactic in driving customer actions and conversions. This is especially true when customers interact with multiple touchpoints before making a purchase decision.


2. Tracking offline and online touchpoints: Attribution becomes complex when customers move across offline and online channels. It can be difficult to link offline activities like TV advertisements or in-store promotions with online conversions, making it hard to measure the effectiveness of different marketing efforts.


3. Reconciling data from different sources: Attribution requires combining data from various B2B marketing tools, including CRM systems, web analytics tools, advertising platforms, and social media platforms. Integrating and reconciling data from these sources can be a challenge due to discrepancies in data formats, attribution methodologies, and accuracy of data.

4. The impact of non-marketing factors: Attribution models often struggle to account for external factors that can influence customer actions, such as seasonality, economic conditions, competitive factors, or changes in customer preferences. Failing to consider these factors can lead to inaccurate attribution results.


6. Time decay and windowing attribution: Determining the appropriate timeframe over which to attribute conversions is another challenge. Different attribution models may assign different weights to touchpoints based on recency, with some giving more credit to recent touchpoints and others distributing credit more evenly across the customer journey.


7. Limited resources and expertise: Implementing and maintaining an effective attribution model requires dedicated resources and expertise in data analysis, statistical modeling, and marketing analytics. Many organizations struggle to acquire and allocate the necessary resources to effectively tackle attribution challenges.

Conclusion

Marketing attribution models are essential for understanding the effectiveness of different touchpoints in the customer journey. By choosing the right attribution model and addressing common challenges, businesses can optimize their marketing campaigns and maximize their ROI.

Frequently asked questions about marketing attribution models

How can I track offline touchpoints in my attribution model?

Tracking offline touchpoints can be more challenging that tracking digital marketing touchpoints. However, it’s certainly not impossible. One way is to use unique customer identifiers or coupon codes that customers can provide when making offline purchases. Another option is to incorporate call tracking software to attribute offline conversions to specific touchpoints.

Can I use different attribution models for different marketing campaigns?

Yes, it is possible to use different attribution models for different marketing campaigns. Businesses can adopt a flexible approach and select the attribution model that best suits the specific objectives and characteristics of each campaign.

How do I measure the ROI of my marketing campaigns with attribution?

Measuring ROI with attribution involves comparing the revenue generated from conversions attributed to specific touchpoints with the cost of the marketing efforts associated with those touchpoints. This provides insights into the effectiveness and profitability of different campaigns and channels.

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