Maximizing ROI from Loyalty & Recognition Programs

By Harry Rivkin

There are many customer loyalty programs out there today. They are offered at your local drug store, grocery store, through the airlines, hotels, and much more. Many people sign up for programs simply for the sake of getting something free, and are not really interested in becoming a member of a loyalty program. With so many consumers joining various plans, there is a need to determine who our “best” customers are.

A recurring service we provide our clients is selecting guests for loyalty and recognition programs. We have found that a tried-and-true direct marketing approach - commonly referred to as RFM, Recency, Frequency and Monetary - is a compelling solution.

In the context of hospitality:

• Recency refers to the recent guest stay at a given property.
• Frequency refers to the frequency with which the guest has stayed over his or her lifetime at the property.
• Monetary refers to the monetary value of all lifetime stays.

Since loyalty and recognition programs are undertaken to ensure guest retention and drive repeat stays, applying the RFM methodology effectively identifies those guests who are most deserving of investment.

Direct marketers have found that the customer’s Recency of doing business is a strong predictor of the customer’s propensity of responding favorably to a “pitch” to do business again. The customer’s Frequency of having done business in the past, is a strong predictor of the customer’s propensity to do business in the future. The customer’s Monetary value over a lifetime is a strong predictor of sufficient ROI from loyalty and recognition programs. The RFM approach identifies guests whom hoteliers cannot afford to lose and, at the same time, have the greatest potential for a lifetime payoff through repeat visits.

How Does the RFM Methodology Work?

The foundation of the RFM approach is a clean and current guest history database that is almost always outside of the PMS database. It is essential that guest history data emanating from the PMS be thoroughly cleansed; duplicate guest records accurately identified and consolidated; and values relating to stays, room nights and revenue, be calculated.

There are a number of RFM scoring schemas that can be applied in this process. Here is one example:

• Look at only guests that stayed in the past 24 months.
• Score the number of months since the last stay (the R value). The more recent the stay, the higher the score.
• Score the number of stays in the past 24 months (the F value). The greater the number, the higher the score.
• Score the M value in two ways: total revenue in the past 24 months (the M1 value); and the average daily rate (ADR) in that period (the M2 value). The greater the dollar value, the higher the score.
• Add the four scores (R+F+M1+M2), rank order guests from highest to lowest on the composite score, and assign guests into segments based upon where they fall in the ranking.

Generally speaking, the segmentation is organized to select a manageable number of guests for a loyalty or recognition program. For instance, a property can focus its loyalty or recognition program on the top 10% of guests based upon the ranking (the “High Value Segment”). In a typical example, the top 10% of guests will represent 2.5 to 3.5 times its weight on key measures - stays, room nights, revenue and ADR.

Remember, the “end game” is to ensure that resources are allocated to maximum advantage in loyalty and recognition programs for guests where the pain will be greatest if lost, and the gain greatest if retained (and rewarded).

Harry Rivkin, IDT Group President, has more than 40 years of marketing database experience across a variety of industries. He taught the marketing curriculum in the Saint Joseph’s University MBA program, and database marketing courses in Cornell University’s School of Hotel Administration Professional Development Program.