Customer Loyalty Program Analytics Guide

One common goal in every ecommerce industry is to acquire and retain loyal customers. Customer loyalty is important to fuel the growth of a business, and a common retention strategy ecommerce businesses use is loyalty and reward programs. A loyalty program can be optimized differently in every industry. However, there is one aspect every good loyalty program should offer— analytics.

Viewing loyalty analytics is essential to inform how to shape a business and its retention strategies. Having access to and viewing customer loyalty analytics within a loyalty program allows business owners to understand their customer's behavior and preferences.

The importance of customer loyalty analytics

You need access and an understanding of your customer loyalty analytics to:

Collect first-party data from customers.
Build customer segments.
Analyze engagement.
Predict Customer Lifetime Value (CLV) for customers.

With a well-optimized loyalty program, you can collect first-party data from your customers, such as email addresses, shopping preferences, and more. Loyalty analytics can help you craft a strategy based on this data.

Customer segmentation is essential for categorizing customers based on their behavior, the amount they have spent, whether they’re repeat customers or first-time customers, and many other factors.

One major strategy with access to customer loyalty analytics is viewing the engagement analysis of your customers:

How often are they returning to shop?
How often are they spending earned points or redeeming rewards?

Viewing customer engagement will help you evaluate the effectiveness of your loyalty program and campaigns and identify areas for improvement and optimization.

Using your customer loyalty analytics can help predict the Customer Lifetime Value (CLV) of your customers and forecast long-term customer value. This can help predict revenue, connect the dots with customer experience, identify valuable customers, and make marketing decisions.

Measuring success in loyalty programs

Building a base of loyal customers with a rewards program is by far the best retention strategy for growing your business and building lasting customer relationships. After all, customer retention is about keeping loyal customers, as opposed to acquiring new ones, which is more costly and unpredictable. However, knowing whether your program is delivering the results you’re looking for is key to optimizing its performance and getting the most out of it.

Customer loyalty analytics allows you to examine your KPIs (key performance indicators) to track and evaluate your loyalty program’s effectiveness. Death Wish Coffee’s loyalty-generated revenue increased by 186% YoY with Smile.io simply by optimizing its rewards program and testing gamification techniques. Over the years, Death Wish noticed fluctuations in its loyalty program engagement rates. In June 2023, a low rewards redemption rate signaled the need for optimization.

Death Wish introduced three main strategies to bring its loyalty program back to the forefront of customers’ minds and re-engage them. They completed a full loyalty program rebrand, launched a gamification campaign, and drove revenue with Klaviyo’s email flows and segments—all possible through transparency in their customer loyalty analytics.

Common analytics reports that ecommerce businesses view to make marketing decisions include:

Sales attribution: Report on the ROI of Smile over time as repeat purchases grow.
Engagement analytics: View points, referral, and VIP engagement as customers embrace your program.
Points accounting: Keep a pulse on unused points. Use points expiry to manage the growing balance of points effectively.
Data exports: Export all your loyalty data and any report you need to dive deeper into your data.
Redemption rate: A healthy loyalty program has a constant flow of points being earned and redeemed each month.
Top referring customers: Find out which customers love referring their friends and just can't stop sharing your brand.

Optimizing loyalty programs with analytics (top tips)

Similar to Death Wish Coffee, it is important for ecommerce brands to review customer loyalty analytics to make decisions on how and when to optimize their rewards program. Optimizing your rewards program will lead to greater improvements in usage and customer retention.

Dive into your loyalty program reports on a regular basis. Smile Plus users gain access to more than 25 pre-built reports to identify the metrics that are important to their business.
Focus on the most important reports for your business goals. Discover your loyalty program’s strengths and weaknesses so you can optimize it.
As you iterate, track your customer loyalty analytics to see which changes are affecting your success, or where there is further room for improvement.
Finally, draw conclusions based on all your reports to craft a story about where your next marketing efforts should focus.

Smile Plus for advanced loyalty program analytics

Measure the success of your loyalty program and dial in on performance with instant access to data on Smile Plus. Smile Plus is Smile.io’s plan for high-volume brands looking for a customer loyalty program that will scale with them. Smile Plus was designed so you can have access to 25+ specialized, and curated reports on your customer loyalty analytics. These pre-built reports are based on sales influenced by Smile.io, first-time vs. repeat redeemers, points accounting, and industry benchmarks.

The goal is for business owners to have data at their fingertips so they can optimize key metrics for a healthy loyalty program. Smile.io aims to simplify loyalty program management for growing brands and teams. With these reports, you can create targeted campaigns to keep customers engaged and coming back for more. For example, you can export or connect to Klaviyo directly and build custom segments.

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