How to Calculate Loyalty Revenue Attribution and Program ROI in 2024

Many brands have a love-hate relationship with loyalty programs. As we’ve spoken with many Chief Marketing Officers, it often boils down to one critical question:

How do you accurately attribute revenue to a loyalty program?

While research shows that loyalty programs are effective, demonstrating their ROI and value for a specific brand can be challenging. Traditional loyalty revenue attribution methods have been inadequate, making accurate ROI calculation difficult. Let’s explore why this is the case and how AI has improved loyalty attribution, enabling trustworthy loyalty program ROI calculations.

The Flaws in Traditional Loyalty Revenue Attribution

Across service providers and brands, we typically see two flawed methods for attributing loyalty revenue. Both methods share the same fundamental issues.

Method 1: Simple, Overstated Revenue Attribution

Loyalty Revenue = Total revenue of all loyalty members

This overly simplistic method assumes that all revenue from loyalty program members is due to the program. It ignores a crucial aspect: if the program didn’t exist, would these loyal customers have purchased or engaged anyway?

Method 2: Simple but Attempting to Measure Revenue Uplift

Loyalty Revenue = Average AOV of Members vs. Average AOV of Non-Members

The comparison of measuring members against non-members is a step closer to accurate attribution but has two significant problems:

• It’s too broad, spanning all members and non-members.

• It doesn’t account for scenarios where loyal customers are already taking action.

The result is a less overstated but still inaccurate measure of loyalty revenue. Being transparent, this is where we started at Raleon. It felt like tossing a giant net into a pond and hoping we were accurate enough.

But we weren't satisfied with just casting a wide net. While ads are by no means perfect, we wanted to give marketing teams the kind of firepower they’re used to with ads, but for loyalty.

The Theory Behind Accurate Loyalty Program Revenue Attribution

At Raleon, we use AI to overcome these flaws in traditional loyalty revenue attribution (and ROI calculations as a result). This approach not only provides a better understanding of loyalty program ROI but also allows for fine-tuning the program based on what’s working. Here's how we approach it:

Behavioral Segmentation: Using machine learning, we categorize customers based on their behavior, distinguishing between new, growth opportunity, dormant, and loyal customers. This segmentation is tailored to each brand’s unique characteristics and purchase patterns.

Loyalty Behavior Segmentation: We further segment loyalty customers based on their behaviors, differentiating between “normal” activities and “program” activities. This distinction is crucial for accurate attribution.

Incremental Revenue Analysis: After segmenting customers, we perform uplift comparisons on true cohorts. For instance, we compare the behavior of the most loyal non-member customers to that of highly engaged member customers within each segment.

This takes us closer to more probabilistic attribution you see with the likes of Meta and others today. In the case of loyalty, this approach also yields a more accurate measure of loyalty revenue.

What are the results?

When we’ve run loyalty attribution this way we see revenue inflation reduced often by more than 50%. But we’ve also seen something else: loyalty programs when done right are very effective.

In addition to seeing good, accurate loyalty revenue results, we often see other increases like a 20% to 50% lift on LTV as a result of loyalty programs on Raleon.

Practical Implications of Proper Loyalty Program Revenue Attribution

Let’s make this actionable. Why is it so important to make sure you can properly attribute your loyalty program revenue? It goes beyond ROI.

Understanding Key Metrics: Proper loyalty revenue attribution is foundational for understanding loyalty’s impact on other key metrics like:

• Lifetime Value (LTV)

• Average Order Value (AOV)

• Repeat Purchase Rate (RPR)

Personalization is Key: Treating loyal customers the same as new customers can backfire. Loyal customers expect recognition and tailored rewards. Measuring loyalty revenue attribution per segment helps identify which personalization efforts work best. Our AI-driven platform ensures that loyalty programs are as personalized as email marketing campaigns, delivering better results.

Testing and Adaptation: Just as you wouldn’t run a single ad and hope for the best, loyalty programs must be continuously tested and adapted. Our platform allows for granular testing, ensuring that every change is data-driven and impactful.

How to Calculate Loyalty Program ROI

Now that you can accurately attribute loyalty revenue, the program ROI calculation becomes easy.

Loyalty Program ROI = ((Incremental Loyalty Revenue - Program Costs) / Program Costs) x 100

We’ve covered the best way to calculate incremental loyalty revenue, but we haven’t talked about program costs. Thankfully, they’re much easier. Depending on how specific you want to be, program costs often include:

• Reward/Promotion cost

• Marketing expenses

• Platform cost (such as Raleon)

Given marketing expenses are often shared, most brands simplify it down to the cost of rewards that were used, plus the cost of the software platform itself (like Raleon).

How Raleon Helps with Loyalty Program ROI and Revenue Attribution

Whether you’re running personalized loyalty or a generic program, understanding loyalty program revenue attribution is critical. Without it, you cannot accurately calculate the ROI outlined or fine-tune your program effectively.

At Raleon, we've built our platform to address the gaps in traditional loyalty strategies. Leveraging AI, we provide more accurate revenue attribution and ROI calculations based on the principles outlined above. By understanding and responding to the unique needs and behaviors of different customer segments, brands can create more effective loyalty programs that truly drive value.

As the world goes personal, loyalty programs must evolve. The future of loyalty is here, and it's personalized, data-driven, and AI-powered.