Multi-touch attribution: What is it & how do you use it?

Today, customers rarely interact with a brand just once before purchasing. They might see a social media ad, read a blog post, and subscribe to an email list before finally converting to your website. This complex customer journey highlights the limitations of traditional attribution models.

That’s where multi-touch attribution comes in. This powerful approach helps you understand the impact of every customer touchpoint with your brand, allowing you to optimize your marketing efforts for maximum impact. This guide will delve into multi-touch attribution, explaining what it is, the different models available, and how to leverage Usermaven to gain valuable insights and boost your marketing ROI.

What is multi-touch attribution?

Multi-touch attribution (MTA) is a marketing measurement approach that recognizes the influence of multiple touchpoints on a customer’s journey to conversion. Unlike single-touch models that credit just the first or last interaction, MTA assigns credit across all touchpoints a customer encounters with your brand before converting.

This allows marketers to understand the complete customer journey, not just isolated interactions. It reveals how various marketing channels (social media, email, etc.) work together to influence customer decisions.

By analyzing touchpoints, MTA helps answer questions like:

• Did a social media ad spark initial interest?
• Did a blog post prove to be the last touchpoint?
• Did an email offer bring the customer toward conversion?

With this data, marketers can gain a more accurate picture of how marketing efforts contribute to overall success.

Benefits of multi-touch attribution

Single-touch attribution models, where credit goes solely to the first or last interaction, leave SaaS companies in the dark. Multi-touch attribution (MTA) steps in to provide a much clearer picture. Here’s how it benefits explicitly SaaS companies:

1. Revealing the entire customer journey

Gone are the days of wondering which marketing efforts truly drive conversions. MTA reveals the influence of all touchpoints, from social media ads to blog posts to webinars. This allows you to see how content and interactions nurture leads throughout the sales funnel, giving valuable insights into which channels are most effective at each stage (awareness, consideration, decision).

2. Smarter marketing budget allocation

No more throwing money at channels with limited impact! MTA data empowers you to allocate resources strategically based on actual performance. You’ll see which channels generate the most qualified leads and conversions, allowing you to invest more in those high-performing areas. This data-driven approach ensures your marketing budget works harder, not spends more.

3. Personalized customer experiences

Understanding which content resonates best with potential customers is crucial for SaaS companies. MTA helps you identify the information and interactions that truly engage your target audience. Imagine discovering that a specific white paper consistently precedes sign-ups. This knowledge allows you to tailor future content to those interests, keeping leads engaged and moving them smoothly through the sales funnel.

4. Reduced customer acquisition costs (CAC)

Acquiring new customers can be costly for SaaS companies. MTA highlights the channels that deliver the most qualified leads. Focusing on these high-performing channels attracts the right audience with the right message, leading to higher conversion rates and a lower overall cost per acquired customer.

Related: A guide to user & customer acquisition Funnel with Usermaven

5. Boosted customer lifetime value (CLTV)

The story doesn’t end at sign-up. MTA can also track how marketing channels influence the acquisition of high-value customers. With this knowledge, you can tailor re-engagement campaigns to this specific segment. This personalized approach keeps high-value customers satisfied and using your product for the long haul, ultimately boosting customer lifetime value.

Types of attribution models

There are two main types of attribution models:

Type	Description
Single-touch	– First-touch: Attributes all credit to the first interaction. – Last-touch: Attributes all credit to the last interaction.
Multi-touch	– Linear: Distributes credit equally across all touchpoints. – Position-decay: Gives more credit to touchpoints closer to the conversion. – Data-driven: Uses algorithms to assign credit based on data analysis.

Single-touch attribution

The single-touch model assigns Attribution based on a single touchpoint in the customer journey.

It has the following types;

1. First-touch attribution

This traditional model gives all the credit for a conversion to the first touchpoint a customer encounters with your brand.

Imagine a customer sees a social media ad about your SaaS product and then forgets about it. Months later, they receive a helpful email and decide to sign up.  With first-touch attribution, all the credit goes to the social media ad, even though the email likely played a more significant role in the conversion.

• Pros: Simple to understand and implement. Helpful in understanding initial brand awareness efforts.

• Cons: Ignores the influence of all subsequent touchpoints. Overvalue initial interactions that may not directly lead to conversion.

2. Last-touch attribution

This model is the opposite of first-touch, giving all the credit to the final touchpoint before a conversion.  In the same scenario above, the email would receive all the credit for the sign-up, neglecting the initial brand awareness created by the social media ad.

• Pros: Easy to implement. It helps understand the immediate trigger for conversions.

• Cons: It ignores the influence of all prior touchpoints that nurtured interest and might overvalue interactions that may not have been the sole driver of conversion.

Multi-touch attribution models

These models go beyond single touchpoints and distribute credit across all customer interactions with your brand before converting. Here are some popular multi-touch approaches:

1. Linear attribution

This model takes the most straightforward approach, giving equal credit to all touchpoints in the conversion path.

Imagine a customer sees a social media ad, reads a blog post, and signs up for your newsletter after receiving an email.  With linear attribution, each touchpoint (ad, blog post, email) would receive 1/3rd of the credit for the conversion.

• Pros: Easy to understand and implement.
• Cons: It doesn’t account for the varying influence of different touchpoints. Overvalue interactions early or late in the journey.

2. Time-decay attribution

This model recognizes that touchpoints closer to conversion likely hold more influence. It assigns a higher weight to touchpoints that happen closer in time to the conversion.

Imagine the same customer journey as before, but they signed up for the newsletter a month after seeing the social media ad. The email would receive a higher credit than the ad due to its proximity to the conversion.

• Pros: Gives more credit to touchpoints with likely higher influence.
• Cons: It requires choosing a decay rate
  (how much credit diminishes over time), which can be subjective.

3. Position-based attribution (U-shaped or W-shaped)

These models assign more credit to specific positions in the customer journey. The U-shaped model gives higher credit to the first and last touchpoints, with the middle touchpoints receiving less.

The W-shaped model is similar but might allocate a higher percentage (e.g., 90%) to the first, converting touchpoint and last touchpoint, with a smaller share for interactions in between.

• Pros: Acknowledges the importance of initial brand awareness and final nudge towards conversion.
• Cons: Might overvalue the first or last touchpoint and underestimate nurturing interactions in the middle.

4. Data-driven attribution

This advanced model leverages your company’s historical data to assign credit. It analyzes past conversions and assigns weights to touchpoints based on their statistical contribution.

• Pros: Highly customizable and reflects the unique customer journey for your business.
• Cons: Requires a significant amount of data and sophisticated analytics capabilities.

Choosing the suitable model depends on your specific goals and business data. Experimenting with different models can help you better understand your customer journey and optimize your marketing efforts for maximum impact.

How to implement multi-touch attribution?

Implementing multi-touch attribution can be complex, but it’s a worthwhile investment for businesses that want to understand customer journeys and optimize their marketing efforts.

Here are the steps involved:

• Determine your goals and KPIs: What do you want to achieve with MTA? Identify your key performance indicators (KPIs) to measure success.
• Choose the suitable attribution model: Select one that aligns with your business goals and your tracking conversions.
• Set up your marketing analytics software: You’ll need a platform to track user data across different channels and touchpoints.
• Collect and analyze data: Once you have your system, start collecting and analyzing data to identify trends and insights.
• Optimize your marketing campaigns: Use the insights from your MTA data to refine your marketing campaigns and allocate resources more effectively.

How can Usermaven help?

Multi-touch attribution (MTA) clearly shows your customer journey, revealing how various marketing channels influence conversions. Usermaven empowers you to implement MTA and gain valuable insights to optimize your marketing efforts. Here’s a concise explanation of implementing multi-touch attribution with Usermaven:

What Usermaven offers:

• Attribution models: Analyze your customer journey with various models, such as First touch, Last touch, Linear, and Position decay.
• Customization: Set Attribution windows (30 days, 60 days) to match your sales cycle.
• Data-driven insights: Understand which channels and campaigns drive conversions and revenue.

How to use it?

• Go to the Usermaven dashboard and navigate to “Attribution.”
• Create a new report: Name it and choose the conversion event (e.g., sign-up).
• Optionally exclude specific traffic sources or direct traffic.
• Select your preferred Attribution model.

Available models

• First touch: Credits the initial touchpoint (e.g., ad) for the conversion.

• Last touch: Credits the final touchpoint (e.g., email) before conversion.

• Linear: Distributes credit equally across all touchpoints.

• Position decay: Gives credit to first and last touchpoints (U-shaped).

Analyze your results

• Usermaven displays data based on your chosen model.
• See the effectiveness of different traffic sources and channels.
• Gain insights into user engagement within your selected model.

Using Usermaven’s Attribution features, you can optimize marketing efforts by understanding the complete customer journey and allocating resources effectively.

Conclusion

In essence, MTA is a powerful tool that helps SaaS companies see the complete customer journey. It removes the guesswork from marketing and provides actionable data that fuels better decision-making.

By understanding the full impact of your marketing efforts with Usermaven, you can optimize lead generation and customer acquisition and ultimately drive significant business growth.

FAQs

1. Is multi-touch attribution suitable for all businesses, regardless of size or industry?

While beneficial for understanding the customer journey, multi-touch attribution may be more feasible for larger enterprises due to complexity and resource requirements. However, with adaptation, businesses of all sizes and industries can leverage its insights.

2. How does multi-touch attribution differ from other attribution models, such as first-touch or last-touch attribution?

Multi-touch attribution distributes credit across multiple touchpoints, unlike first-touch and last-touch models, which credit only the initial or final interaction. This provides a more comprehensive view of the customer journey.

3. What are the common challenges businesses face when implementing multi-touch attribution, and how can they overcome them?

Challenges include data integration issues, incomplete data, and organizational resistance. Solutions involve investing in data integration tools like Usermaven, educating stakeholders, and regularly optimizing attribution models.