How to Create Effective Multi-channel Attribution Models

Some fishes can be caught by net, some by hooks, and others by very unorthodox methods. The point of this analogy is that effective growth marketing is never a one-size fits all model.

Most times, it demands real-time iterative methods and experiments within the available channels and assets to achieve the needed precision and impact that will drive business growth. Regardless of the methods and strategy, all the moving parts of growth marketing are expected to be managed within defined budgets if things must be kept efficient. Budget efficiency is a huge part of success when it comes to growth success.

One of the most challenging, yet important tasks marketers and businesses face and must deal with is how to accurately measure the return on investment (ROI) not just from the perspective of spend but of growth objectives and other KPIs.

Understanding the impact of the marketing and growth budget in terms of Returns on Investment is crucial not just to stakeholders but to marketers alike as this many times can be an effective indicator for revenue performance and budget regulation.

Growth marketing is a data-driven approach that involves, but is not limited to acquiring, retaining, and engaging customers across multiple channels, such as email, social media, web, mobile, and many more channels, (digital or offline). However, not all channels are equally effective or efficient in driving conversions and revenue.

Marketing Campaign Questions

In alignment with the objectives of any campaign, data must be queried for answers through analytic. To do this, the following are effective questions to ask:

  • How do you know which channels are contributing the most to your growth goals?
  • How do you allocate your budget and resources to optimize your marketing mix?
  • How do you justify your marketing spend to your stakeholders?

Half the money I spend on advertising is wasted; the trouble is I don’t know which half.’ – John Wanamaker.

Though we may disagree with Wanamaker, the problem of the question remains a common pain point that must be addressed, and that’s where Attribution Models come in.

What are Attribution models?

Attribution models are methods of assigning credit or value to different touchpoints along the customer journey. In simpler terms, it is the rule, or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths.

They help you understand how each channel influences the customer’s decision to purchase or take a desired action. By using attribution models, you can evaluate the performance of your marketing channels and optimize your strategy accordingly.

Marketing attribution models help marketers measure the impact of different channels and touchpoints on customer conversions.

Common Attribution Techniques

A marketing attribution model is a way of assigning credit to different marketing channels or touchpoints that influence a customer’s decision to buy a product or service.

A probabilistic model uses statistical methods and machine learning to estimate the probability of each touchpoint contributing to a conversion.

A deterministic model uses predefined rules and weights to assign credit to each touchpoint based on its position in the customer journey. For example, a probabilistic model might use Bayesian inference to calculate the likelihood of a customer buying a product after seeing an email campaign, a social media ad, and a blog post. A deterministic model might use the last-click rule and give 100% credit to the blog post as the final touchpoint before the purchase.

Methods of Attribution

Multi-touch attribution model

This assigns fractional credit to each touchpoint in the customer journey that leads to a conversion. This model helps marketers measure the effectiveness of different channels and optimize their marketing mix.

For example, a customer may see a display ad, read a blog post, attend a webinar, and then make a purchase. A multi-touch attribution model would allocate a percentage of credit to each of these touchpoints based on their influence on the purchase decision.

Single touch attribution model

This assigns all the credit for a conversion to one touchpoint in the customer journey. For example, the first touch model gives 100% credit to the first interaction, while the last touch model gives 100% credit to the last interaction.

This model is simple and easy to implement, but it does not capture the complexity and nuance of the customer journey. A use case for this model is when the customer journey is short and linear, such as buying a low-cost product online.

Practical Variations of Marketing Attribution Techniques

Now that we have understood the techniques and methods marketing attribution, let’s take a deep dive to understand the practical variations of how each model works and probable use cases :

First-click attribution

This attribution assigns 100% credit to the first touchpoint that introduced the customer to the brand. Example: a customer sees a social media ad, visits the website, signs up for a newsletter, and later makes a purchase.

Use case: useful for measuring brand awareness and acquisition, but overlooks other interactions that nurtured the customer relationship.

Last-click attribution

The last click attribution assigns 100% credit to the last touchpoint before conversion. Example: a customer clicks on an email link and buys a product.

Use case: simple and easy to implement, but ignores other factors that influenced the customer journey.

Linear attribution

This attribution assigns equal credit to all touchpoints along the customer journey. Example: a customer sees a blog post, watches a video, downloads an eBook, and then converts.

Use case: a fair and simple way to acknowledge all marketing efforts, but does not account for the varying importance of different touchpoints.

Time-decay attribution

This assigns more credit to the touchpoints that are closer to the conversion. Example: a customer visits the website, receives a follow-up email, attends a webinar, and then converts.

Use case: reflects the recency effect and the influence of the last interactions but may undervalue the initial touchpoints that sparked interest.

Position-based attribution

This assigns more credit to the first and last touchpoints and distributes the remaining credit evenly among the middle touchpoints. Example: a customer clicks on a search ad, reads a blog post, views a product page, receives a retargeting ad, and then converts.

Use case: balances the importance of both acquisition and conversion but may ignore the role of other touchpoints in building trust and engagement.

View-through attribution

Much like the term suggestions, view-through attribution is an attribution that is driven by people viewing an ad without actually clicking on it.

However, not all attribution models are created equal. Some models are more simplistic and biased than others and may not reflect the true impact of your marketing efforts.

For example, the last-click model assigns 100% of the credit to the last touchpoint before conversion, ignoring all the previous interactions that may have influenced the customer.

This model may overestimate the value of channels that are closer to the end of the funnel, such as search or direct traffic, and underestimate the value of channels that are more effective in generating awareness and interest, such as social media or display ads. This might even become a blind spot to detecting mobile marketing fraud in some cases.

On the other hand, some models are more complex and sophisticated than others and may require more data and analysis to implement.

For example, the data-driven model uses machine learning algorithms to assign credit to each touchpoint based on its actual contribution to conversion, taking into account multiple factors such as channel frequency, recency, position, and more.

This model may provide a more accurate and unbiased view of your marketing performance, but it also requires a large amount of data and computational power to run.

How To Choose The Best Attribution Models for Business

So how do you choose the best attribution model for your business? There is no one-size-fits-all answer to this question, as different models may suit different goals, scenarios, and data availability. However, here are some general steps you can follow to create effective multi-channel attribution models for measuring your growth marketing ROI:

1. Define your business objectives and key performance indicators (KPIs)

What are you trying to achieve with your growth marketing campaigns? What metrics are you using to measure your success? How do you align your marketing goals with your overall business goals?

2. Map out your customer journey and touchpoints

How do your customers interact with your brand, services and product across different channels and devices? What are the key stages and milestones in their journey? How do you track and measure their behavior and actions?

3. Choose a baseline attribution model that best fits your data and goals

Based on your data availability and quality, choose a simple or complex attribution model that can help you answer your business questions.

For example, if you have limited data or want to get a quick overview of your channel performance, you may start with a single-touch model such as first-click or last-click.

If you have more data or want to get a deeper understanding of your channel interactions, you may opt for a multi-touch model such as linear, time-decay or position-based.

4. Analyze and compare the results of different attribution models

How do different models affect the value and credit assigned to each channel? How do they impact your ROI calculations and optimization decisions? Also, how do they align with your intuition and experience?

5. Test and refine your attribution model over time

Attribution modeling is not a one-time exercise but an ongoing process that requires constant testing and refinement. As your data grows and changes over time, so should your attribution model.

You may also experiment with different models or combinations of models to find the optimal solution for your business.

Building an attribution infrastructure of any kind, from bones to skin, might not be very practical, even for large businesses with technical muscle and resources.

It is, therefore, best practice for businesses and brands that are positioned and driving growth through marketing to work with attribution partners that will help them track and attribute their activities and marketing efforts, engagement, and budget effectively and efficiently,


By following these practices and building a progressive understanding of how to manage and adjust them on the scale, you can create effective multi-channel attribution models that can help understand the holistic value and positions of your channels.

Like an elite soccer team coach, this will give you a bird’s eye view of who your best teammates are; you will know who your best strikers are (acquisition channel), who your best midfielders are (engagement channels and assets), and what makes up your kill squad defense (retention) with this wealth of information you identify growth levers based on channels, tinker and adjust your tactics and strategy you measure and improve your growth marketing ROI for best value and impact delivery.

Attribution modeling is not an exact science but an art that requires creativity, critical thinking, and experimentation. By using data-driven insights and best practices, you can make smarter decisions and drive better results for your business.