Understanding Your Loyalty Program Members


The internet has given customers more choices, and higher expectations, than ever.

In the age of online reviews and viral social media, understanding and optimizing the customer experience must be a priority, especially for loyalty programs. Technology is empowering a more informed consumer, while giving loyalty programs easy access to troves of customer data.

Here, we break down some of the most effective methods of gathering valuable information about your loyalty program members:

Analyze member behavior with analytics

The first place many loyalty program managers go to understand program members is historical data. While past behavior may be indicative of future behavior, it’s also a simplistic (and therefore limited) way of forecasting.

Advanced machine learning and predictive analytics are superior methods of assessing member behavior. By combining transactional information with member preferences, location, characteristics, and usage statistics, acute insights can be made.

From there, your program members can be grouped into categories for tactical and strategic loyalty initiatives.  

Segment members for higher ROI

Advanced technologies such as machine learning and artificial intelligence can help you quickly identify and segment your customer groups. Segments can be based on behaviors, customer value, or engagement rate.

By categorizing customers according to different variables and characteristics, loyalty programs can be more tactical and efficient with each dollar invested in program initiatives.

You can also identify which sets of behaviors lead a person to become a high value member. After all, you’re better off investing in high value members than allocating valuable loyalty program dollars to low value members.

Track metrics to assess performance

Data analysis is only effective if you can generate your desired outcomes: improving the customer experience and generating measurable loyalty program ROI. While customer experience has no defined set of metrics, we can use customer lifetime value and net promoter score as proxies for measuring customer loyalty.

Customer lifetime value (CLV) quantifies historical customer transactional data, anticipated future transactions, and costs. With detailed analytics, CLV can be computed for each individual customer.

Net promoter score (NPS) is a simple survey assessing customer loyalty. It’s assessed with one simple question: Would you recommend our business to someone to know?

Tracking these two metrics over time can provide valuable insight into how your customers and loyalty program members really feel about your loyalty program (and your brand).

Leverage what you’ve learned

Successful loyalty programs foster engaging customers and brand loyalists. In today’s interconnected world, it’s more challenging than ever to create a highly engaging customer experience.

By understanding your loyalty program members today, you can determine — and better control —  the success of your program in the future.

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