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Are you missing revenue opportunity in your loyalty rewards program?

Risk & Analytics|Corporate Risk Tools and Technology
COVID 19 Coronavirus|Risk Culture

By Manolis Bardis | November 25, 2020

With the sharp decline in travel due to COVID-19, finding ways to maximize revenue from loyalty members will be critical to the finances and liquidity of companies in the travel industry.

Loyalty rewards programs continue to grow in both popularity and scale, and with good reason. They drive increased customer loyalty and engagement and, when well-managed, revenues. But companies that don’t use some of the techniques they’re already using to manage program risks may be missing revenue opportunities.

The other side of loyalty program risk

As loyalty programs were established back in 1980s and 1990s, organizations realized that they represent significant financial risk, with the breakage associated with unredeemed miles or points representing, at times, several billions of dollars of liabilities for the largest programs. Actuaries and quants like myself stepped in to apply our trade: measuring an uncertain liability. I won’t diminish the importance of this analysis – it’s essential to avoid major financial consequences. However, if you only consider engaging analytics for the downside risk of loyalty programs you’re ignoring one side of the equation! 

Large loyalty programs can generate several billions of dollars annually from issuing miles or points to their members. In fact, for some companies, over 60% of annual ticket revenue comes from their frequent flyer program members. Elite members of frequent miles programs can generate one and a half times the annual ticket revenue premium when compared to non-loyalty program members. In a time when travel disruptions caused by COVID-19 are rampant, finding ways to maximize revenue from loyalty members will be critical to the finances and liquidity of companies in the travel industry.

To maximize the value of loyalty programs, compare the revenue implications from the engagement of members versus all associated costs. By identifying and encouraging the most profitable members, management will then be able to maximize the value of their program.

Successful programs work to increase members’ engagement, and that translates into future revenue for the company. The ability to quantify and monitor both a loyalty program’s risk and associated value drivers that increase member engagement is essential to effective loyalty program management.

Given this context, both finance and marketing teams invest significant resources in advanced analytics to understand member engagement and focus on producing forecasts of expected future revenue and cost. Below are some of the ways companies are using advanced analytics to deliver value today.

  1. 01

    Cultivate today’s (and tomorrow’s) most profitable members

    Advanced analytic models can provide an accurate estimate of future earnings and costs at the member level. The comparison of revenue versus cost provides the economic value (EV) distribution of the membership population, from the lowest EV to the highest EV. This enables management to identify and target the most profitable members today and in the future. In addition, it provides a better understanding of the economic performance of the overall membership population, which can be used to inform future program management decisions.

  2. 02

    Optimize spend

    A greater understanding of member engagement enables managers of loyalty rewards programs to more accurately estimate how members’ accrual, redemption and overall engagement would change as the terms of the loyalty program change. For example, this approach would allow a more accurate prediction of how customer engagement and redemption may change if expiration rules are modified or predict the lift in engagement if the awarded points are increased for several earning sources.

    This greater understanding can be leveraged to optimize a loyalty program: If management is empowered with the knowledge of which benefits to offer, then accrual awards and redemption options can be tailored to best meet the needs of the most valued customers and maximize their program’s worth. Ultimately, cutting-edge loyalty analytics will identify members where the marginal benefit is greater than the marginal cost from any specific program change, highlighting opportunities to target the right members and focus spending where it will yield the best return on investment.

  3. 03

    Targeted marketing and communications

    By analyzing earning and redeeming behavior at the individual member level, it is possible to draw deep insights on granular member segments, which is typically not possible when the analysis is initially done at a more aggregate level. Transactional member level analyses provide the knowledge to personalize your program for various segments of the membership population and identify your future highest-value members.

Taken as a whole, an advanced analytics framework provides a richer and more detailed understanding of the characteristics of members’ engagement in loyalty rewards programs. Advanced analytics can guide managers of loyalty rewards programs to make the best decisions to maximize economic value by looking holistically to both the revenue and the cost components of the equation.


Manolis is the co-leader of Willis Towers Watson’s Loyalty Rewards practice. He has led numerous client engagements related to liability valuation and liability management for loyalty programs. He has provided consulting services for loyalty clients in the hospitality, aviation, financial services and online travel agency industries.

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