How to Prove the Value of Your Loyalty Program

Loyalty programs are far from a new concept. If we dig deep enough inside our wallet, most of us will likely find an old, tattered punch card … just in case an opportunity presents itself to finally cash in for that free sandwich.


While many of these programs may look different today — think instant digital redemptions — the original loyalty program value proposition remains: in exchange for repeat business with a brand, loyal customers are given opportunities to earn rewards. Customers tend to recognize the value of these rewards, which helps explain why more than half say they will join a loyalty or VIP program.


Most business leaders also understand the value of loyalty programs, at least in theory. Nearly anyone can tell you that it costs more to acquire a new customer — five to 25 times more, depending on who you ask — than to keep an existing one, and loyal customers tend to spend more with a brand than new customers. In other words, building a loyal customer base should have a significant impact on a firm’s bottom line and stock price over time.


In practice, however, many loyalty finance and marketing professionals have difficulty quantifying this impact, which makes it hard to prove that a loyalty program is indeed creating value. Fortunately, most companies already have the necessary data to measure loyalty program value with more precision. When the data is used more effectively, it becomes possible to communicate program value to your company’s stakeholders in a language everyone understands.  


For the finance team


In any company, the finance team is responsible for measuring financial performance and identifying ways to maximize firm value through financial planning and investment decisions. Since loyalty programs directly influence company value, finance teams can benefit from concrete data and methods that allow them to make better decisions.


One of the most common methods for quantifying firm value is the discounted cash flow (DCF) approach, which says that a company’s value is the present value of its expected future cash flows. Of course, the more predictable a firm’s future cash flows, the more credible the present value calculation.


Some business models have more predictable cash flows than others (subscription-based models in which customers periodically pay a predetermined fee is a prime example). Businesses with active, healthy loyalty programs also provide a wealth of insight into a company’s future cash flow. Why? Because most of their future cash flow comes from current program members.


Taking a step back for a moment, let’s see why the relationship between loyalty program member behavior and a company’s future cash flow holds true. You can apply a DCF-like model to measure the value of a loyalty program by estimating customer future value (CFV), which is the present value of estimated future free cash flow produced by each program member — more precisely, expected future revenues less expected future costs. Summing CFV across all loyalty program members gives you the present value of your program members, also known as member equity.


The Pareto Principle states that on average, roughly 20% of a business’s customers account for 80% of its revenues. While the actual breakdown varies depending on your business model, your most loyal customers always account for most of your future free cash flow.


Therefore, member equity is a good proxy for a large share of the value of your entire organization. And, if customer behavior influences member equity, you can increase organizational value by focusing on the relatively small segment of customers that drive company profits. This notion supports the use of customer-based corporate valuation (CBCV) models.  


The underlying concept of the CBCV model is that unit economics is the number one determinant of lasting business success. Put differently, if customer retention and variable profitability are strong while customer acquisition costs remain low, a business is more likely to succeed long-term than it would with operational efficiencies alone. If you understand customer-level profitability dynamics, you can increase company value by investing in acquiring profitable customers and marketing strategies that influence their behavior.  


The meal-kit delivery service Blue Apron is a great real-world example of how CBCV models can be used to understand and influence firm value. Although the idea of food delivered directly to your doorstep resonates with many consumers, subscription-based models like Blue Apron have not been as financially successful as food delivery services such as UberEats and GrubHub.


By digging deeper into the behavior of Blue Apron’s customer base, company management was able to see that their low customer retention rate combined with rising customer acquisition costs was eroding member equity. Unfortunately, this realization was ill-timed, as Blue Apron’s stock price had already fallen nearly 90 percent since its IPO in mid-2017 — an outcome that Dan McCarthy, a leading CBCV researcher, had predicted using his models. Nevertheless, these insights enabled Blue Apron to redirect firm resources to the portion of customers that drive value.


Since loyalty programs provide rich, member-specific transactional data, CBCV models are powerful tools for analyzing trends in customer behavior and diagnosing issues that limit profitability. This type of data analysis allows finance teams to show the loyalty program’s direct impact on organizational value and company stock price.


For marketers


Since marketing teams are responsible for building and maintaining their company’s customer relationships, they typically lead both strategic and tactical loyalty program initiatives. One of the biggest mistakes companies make is focusing on the near-term cost of such initiatives rather than the long-term value they create. Over time, incremental value can be created even if costs rise. Companies that can quantify this cost-benefit trade-off can more readily determine whether their marketing efforts are successful.


To measure the economic value of a proposed marketing initiative, you’ll need an analysis method that clearly shows the trade-off between costs and anticipated benefits — examples of which can be seen below. It’s important to note that the hypothetical loyalty program in these exhibits is relatively small, consisting of only 100,000 members. For larger programs that have millions of members, the resulting member equity projections can be on the order of several billion dollars.   




Like customer-based corporate valuation models, the exhibits above show the relationship between customer future value, member equity, and return on member equity (RME) — the change in customer lifetime value over time. The goal of any marketing team should be to invest in projects that are expected to generate the highest return on member equity. By breaking RME down between current program members and new members, it’s much easier to see whether marketing is productively spending customer acquisition dollars and changing member behavior to create value for the company.


While ideally you want to see positive RME for both current and new members, detecting negative RME early can still be beneficial, as it signals a need for intervention. If marketing teams can clearly see that their efforts are diminishing company value, they can then redirect these efforts to projects that are more profitable.



With the right set of tools, you can track member equity over time, holding the group of included members constant so that the data isn’t distorted by new member acquisitions. An increase in member equity as indicated by an upward sloping line means your RME is positive, and marketing is increasing loyalty program member value above expectations. The ability to visually demonstrate a successful long-term track record of marketing decisions that add to the economic value of the company can be very meaningful when presenting future initiatives to various stakeholders, including the shareholders of the organization.


Additionally, companies that can dig further into the components of the change in member equity over time gain a better understanding of changes in future revenue compared to changes in future cost. By seeing the cost-benefit trade-off, marketing can focus on maximizing loyalty program value instead of minimizing cost. This may lead to the execution of profitable projects that marketing would have otherwise avoided.



Finally, companies can measure the expected impact of their investments in acquiring new customers to develop strategies that focus on acquiring members through the channels with the highest value rather than the lowest cost. The KYROS Dashboard allows for robust customer and member equity analysis so marketing teams can validate the economic value of their efforts.


For loyalty program managers


Program managers are held accountable for increasing member equity, which some companies refer to as driving incremental value. While there are various methods you can use to measure incremental value, commonly used approaches such as look-alike analysis have shortfalls that prevent you from showing a true picture of loyalty program value.


A look-alike analysis splits customers into two groups — those who join the company’s loyalty program and those who do not — and then tracks the differences in each group’s behavior over time. These differences are considered the incremental value. Unfortunately, there are two major shortfalls to this approach:

  1. For most programs, customers who aren’t enrolled simply cannot have their behavior monitored. 
  2. It is accompanied by self-selection bias — that is, customers who choose to join are inherently more likely to continue spending with a company than those who do not.


Since these shortfalls tend to result in unrealistic estimates of the program’s incremental value, companies need a better way to measure the effectiveness of program management. A different — and arguably more accurate — way to measure incremental value is by calculating return on member equity (RME). RME is similar to look-alike analysis in that it compares member behavior to a benchmark. However, the benchmark in this case is status quo member behavior — in other words, expected behavior if members continue to follow their current behavioral trend.


Status quo behavior tends to be more relevant and easier to track than the behavior of customers who choose not to join the company’s loyalty program, making it a more informative baseline. Under this framework, program managers can present more compelling proof of the economic value their loyalty program creates for the organization.    


The bottom line

Loyalty programs are complicated engines with many moving parts that can drive company growth significantly if managed properly. A well-run loyalty program can dramatically increase the economic value of an organization as continuous investment in the right customer acquisition channels and marketing strategies drives profitability. However, to remain viable, each of the teams responsible for the program’s success—finance, marketing, and program management — must convincingly convey their value-add to senior executives, as well as the company’s shareholders.


You can only prove the value of a loyalty program if you have reliable data and the right measurement tools. Luckily, most companies already have the data they need, it simply needs to be leveraged more effectively. By employing the methods we’ve described above, you can not only measure your loyalty program’s value with more precision, you can use the insights you gain to make better decisions moving forward.




Looking to maximize the economic value of your loyalty program?  Contact us  for a free consultation.


A Professional’s Guide to Loyalty Program Liability

To the great delight of customers, many companies offer loyalty programs. These programs allow customers to receive rewards for the purchases they make, with repeated purchases from the same company resulting in an ever-increasing, compounding array of incentives and kickbacks. Customers become motivated to direct as many of their purchases as possible towards the same organization, and businesses reap the rewards of more purchases and a loyal customer base.  It’s the perfect win-win scenario.


Except when it’s not.


While customer loyalty programs are a tried-and-true method of drumming up consistent business, potential risks must be carefully considered when implementing one into your company’s marketing framework. Loyalty programs can result in more sales, but they also carry what is known as loyalty program liability.


Loyalty program liability is the eventual cost to your company of the redemption of all outstanding loyalty points. If accounted for properly, they can be an effectively-wielded strategy for increasing customer engagement and strengthening the consistency of your company’s relationships with clients.


Conversely, failure to properly factor in the impact of these material financial costs  on your company’s balance sheet can have an unexpected financial cost upon redemption of outstanding rewards points.


Fortunately, these financial risks can be mitigated using careful planning and sophisticated analytics tools.  A loyalty program should be viewed as an investment, and, when prudently executed, can return far more than what it cost to implement.


Read on to find out how your company can leverage the benefits of loyalty programs while limiting the risks associated with loyalty program liability.


The basics of loyalty program liability

The impact of customers redeeming loyalty rewards is a balance sheet liability that can cost companies billions of dollars.

Loyalty Program Liability Basics

Though structures vary, the essence of a loyalty program is this: A company offers its clients a certain amount of “currency” per every unit of a designated dollar amount spent. In practice, this might look like Walmart offering shoppers 20 rewards points for every $10 spent, or a pet store offering one “Barky Buck” for every three cans of dog food purchased.


Of course, these currencies mean nothing if they’re not able to be redeemed for products or services, so the second part of the loyalty program formula is to allow customers to redeem the accrued currency for company offerings. Many times, these offerings are simply free or reduced inventory items, but often, the most valued (and desired) options can only be attained by earning enough of the loyalty program’s currency.


In each case, companies are forced to eventually assign the currency real value by making it exchangeable for tangible items. In turn, the delivery of these items in exchange for the rewards points comes at a cost to the company.


For example, that free, steaming hot cup of coffee given by Starbucks to the loyal client actually costs Starbucks some big money. While a single cup doesn’t amount to much, multiply it by the millions of Starbucks customers getting free coffees and the cost skyrockets. And what is this cost known as? That’s right —  loyalty program liability.


What loyalty program liability means to your company

All liabilities matter, and loyalty program liability can impact both the financial health of an organization and the way it’s perceived by the market.


Loyalty Program Liability - Points


The principle reason why loyalty program liability matters is that because, like any other variety of corporate liability, it can negatively impact the financial standing of a company.


The most direct way it can harm the financial health of a company is when companies opt to operate on a model that overestimates breakage. Breakage is the accounting world’s way of describing services that are paid for by a customer but not actually used.


A classic example of this is the sweeping tide of gym memberships that get activated at the beginning of every year by inspired would-be gym goers, bent on finally keeping their New Year’s resolution.


Similarly, every year companies make millions off of unused gift cards for which money is paid, but no products are consumed. While breakage can result in unanticipated profits, relying on it solely to underwrite unsustainable advertisement promises can have devastating effect on a company.


Changes in regulations concerning how companies must classify rewards points are also certain to heighten the impact of loyalty program liability. As of 2018, the International Finance Reporting Standard (IFRS) and US GAAP has mandated that companies categorize rewards points as deferred revenue, considering them separate parts of a sale. This signifies that, at least initially, companies will have to decrease their listed profits from whatever they’ve actually generated to the smaller amount that results after the value of the accompanying rewards points is subtracted. This is particularly true in the US, where the the change in accounting rules is more dramatic.


Although this doesn’t mean that companies cannot eventually incorporate the profits earned from breakage after points expire into their bottom lines, it does mean that, at least in the short term, the value of rewards points must be factored into reports of revenue. For any company, depressions in revenue reports are an important concern, as they affect investor confidence and can change the market valuation of the organization.


Bottom line

Like any other type of liability, loyalty program liability can affect the financial well-being of a company. Due to new regulations, businesses will now be forced to view rewards points as independent occurrences from the event that incurred them, and investors will view them as revenue deferred. This means that rewards points can bring down the revenue reports of a company at any given moment, even if, eventually, they come to increase them.


Most importantly, however, effectively managing loyalty program liability requires measured, strategic, interdepartmental cooperation between accounting, financial and marketing departments — which is where we now turn our attention.



Loyalty program liability accounting

Accounting departments need to accurately hone in on ultimate redemption rates and costs per point to correctly quantify outstanding levels of loyalty program liability.

Loyalty Program Liability Accounting

Accounting departments are pivotal to the management of loyalty program liabilities. After all, in order to properly calculate the direction in which loyalty program liabilities are heading, you need to know where they stand today.


For many of the largest loyalty programs, these liabilities can amount to billions of dollars:  


Deferred revenue liabilities from loyalty programs (2017)

CompanyDeferred revenue liabilities
American Express$7.751 billion
Marriott$4.940 billion
United$4.741 billion
Delta$4.118 billion
American Airlines$2.777 billion
Southwest Airlines$1.676 billion
Hilton$1.461 billion
Intercontinental Hotels$760 million


At this scale, even small changes in redemption behavior can drive significant financial impact. For example, if a $1 billion liability needs to be restated by just one percent, that will drive a $10 million hit to income during the period in which the liability is restated.


Proper understanding of the ultimate redemption rate (URR) as well as the cost per point (CPP), is key to getting the pulse of existing liabilities. While many companies believe that URR cannot be properly gauged, the reality is that this rate can be determined with a fair degree of accuracy.  What tends to impede companies from correctly evaluating their URR is their neglect of many valuable data points concerning the individual behaviors of their members.


The previous actions of loyalty members can help predict what they’ll do in the future, and by analysing these individually, companies can develop forward-looking databases that can give cogent insights on how likely individual point-bearers are to redeem the points.  


While this may require the analysis of huge quantities of data points across a large membership base, new techniques are making it easier for companies to wrangle this “big data” and uncover hidden insights. In particular, the combination of actuarial science and machine learning has proven to be a robust approach to predicting redemption behavior.


Financial reporting not only requires an estimate of the liability, but also disclosures about the timing of when the obligations will be fulfilled. This adds another dimension of complexity to the models, since the models must estimate the total number of points that will redeem as well as the timing of when they will burn.


Unfortunately, the methods companies use to estimate URR are often too simplistic to make accurate predictions of redemption behavior in the dynamic world of loyalty programs, and can result in materially biased estimates. These methods include approaches that look solely at aggregated historical data, or analysis by member vintage.


A URR estimate biased high means that you expect more redemptions to occur than actually will. This can result in deferring too much revenue, and never seeing the number of redemptions required to allow you to eventually recognize it. In essence, the revenue is “stuck” in the deferred revenue account.


A URR estimate biased low means that more redemptions will occur than you expect. When these redemptions occur, you may find that you don’t have enough revenue to cover the costs to fulfill the redemptions, causing a reduction in income during this period. Eventually, a true up of the liability may be needed to reflect a more accurate URR. This can be quite painful for companies with large liabilities. As noted earlier, even a small restatement of the liability can impact income by tens of millions of dollars.


Obviously, the outcome of having a URR estimate that is either too high or too low is not desirable. The nature of such risks often results in tough questions by senior leaders and auditors on the state of the company’s loyalty program liability. Having a robust analytic framework that uses sophisticated modeling rooted in actuarial theory, along with leveraging predictive modeling tools, helps mitigate risk and proves to these stakeholders that your estimate are accurate.


Bottom line

Proper accounting and financial reporting of your liability requires an accurate estimate of the ultimate redemption rate and cost per point. One powerful way to accomplish this is to integrate actuarial science with advanced computational capacities of modern predictive modeling techniques.



What finance departments need to know

Though loss of cash and an increase in liability is hardly appealing to the finance department, finding the proper balance of customer engagement needs to be strategically executed for sustained competitive standing.

Loyalty Program Finance

It’s important to note that the financial impact of issuing rewards points is not incurred at the moment at which they’re redeemed, but, rather, at the time of their issuance. The second the rewards points are doled out to participants, the company incurs the accompanying costs associated with “potentially redeemable points,” either as a reduction in revenue or as a direct recognition of expense, depending on how the program is accounted for.


While accounting is often focused on current liability estimates, many in loyalty finance roles are focused on future liability (i.e., how the liability will grow over time). And to accurately predict future liability, finance must have a solid understand of URR and CPP, too.


It’s also important for finance teams to recognize that, as user engagement increases and members graduate from being casual participants to more heavily invested users, rates of redemption will fluctuate upwards. This, of course, can be offset by the arrival of more new members, whose engagement is typically less vigorous.


This means that it should be expected that the URR will change over time. Failure to recognize this in your financial planning could result in material variance in financial performance.


The trajectory of the liability is also influenced by loyalty program changes and loyalty campaigns. Understanding how changes in these programs, such as modifications to expiration rules or earning rules, or the addition of a new co-branded credit card, impacts the URR and CPP is critical to building an accurate financial plan.


A sole focus on costs may drive some to wish for high breakage. This one dimensional view should be avoided. Program managers must be wary of trying to encourage an excess of breakage, as doing so involves intentionally disengaging customers from the company.


Best practice is for companies to focus not just on liability, but more holistically on customer lifetime value (CLV). CLV considers both the cost of redemptions, as well as the revenue generated from a lifetime of loyalty from your customers. This is the most important metric for any loyalty program.


Cost considerations for CLV include items such as acquisition costs and redemption costs. Therefore, the ultimate redemption rate and cost per point are critical to understanding CLV.


The other half of the CLV calculation is related to revenue — in particular, expected future revenue. Unlike liability, expected future revenue from your members is not an asset you can put on your balance sheet, and is a big reason why there is so much focus on cost.


CLV puts liability in the appropriate context. Program strategies may increase the URR, and therefore increase the liability. But if the expected future revenue sufficiently increases more than expected future costs, then the strategy is a smart financial choice. Disciplined loyalty finance professionals should insist on quantifying CLV to fully understand the financial health of their program.


Bottom line

Ensuring accurate loyalty program liability is not only critical to satisfying Wall Street’s demand for accurate financial forecasts, but for measuring loyalty program ROI as a whole. The challenge for the finance team, then, is to get this right amidst the technical difficulties of implementing precise predictive models and constantly evolving loyalty program marketing strategies.



What marketing teams should know about loyalty program liability

Marketers can get broader buy in and investment in their loyalty initiatives by accurately quantifying liability and CLV.

Loyalty Program Marketing

Marketing departments are responsible for the way in which a company engages with its clientele, and are the vehicle through which customer engagement is controlled. When it comes to loyalty programs, these levels of engagement predict corresponding levels of redemption. This means that marketing plays a key role in managing loyalty program liability.


For the most part, a marketer’s primary focus is not going to be program liability. And it shouldn’t be. With that said, they still have stakeholders in finance and accounting that are concerned about it. Understanding the financial implications of their engagement strategies will help get broad buy-in across departments.


Increasing breakage rates indicates a lack of engagement by members and demonstrates that customers don’t see the program as having value. While it may be beneficial for a company to dump its liability in the short run, this will not be a sustainable strategy for long-term customer engagement. It’s safe to assume that most loyalty professionals, regardless if they’re sitting in finance, accounting or marketing, know this to be true.


The challenge for many loyalty marketers, then, is that business cases often require sound logic and quantifiable evidence. This is where accurate liability estimates and CLV are helpful. If marketers can show that their chosen strategy will sufficiently increase CLV, this shows quantifiable evidence indicating that increasing liability will generate the needed ROI. It’s evidence that marketing, finance and accounting can all get behind.


Beyond building the financial case for a given strategy, CLV can also be used to help identify opportunities and new strategies. This is particularly true when CLV is estimated at the individual member level. This allows you to quantify and identify your most valuable members based on their expected future value, rather than their historical behavior.


This predictive view will have the biggest impact on future profit potential. Focusing your efforts and resources on these opportunities will maximize program ROI.


Bottom line

Marketers, finance professionals and accountants are all key stakeholders in a thriving loyalty program. The key metric at the intersection of their objectives is CLV. Accurate CLV requires an accurate estimate of the URR, CPP and program liability.


All loyalty professionals should demand predictive CLV and, consequently, demand accurate liability estimation.



Final thoughts: Keep your business sustainable

Regardless of where you’re sitting in a loyalty program, you need an accurate estimation of  ultimate redemption rate, cost per point, and loyalty program liability.


For accountants, this means needing to comply with financial reporting requirements.


For finance, this means building an accurate financial plan that ensures that smart financial decisions are being made.


For marketing, this means framing programs and campaigns in the context of how they affect liability and customer lifetime value to get needed buy in from accounting and finance.


While all companies must estimate URR, CPP and liability for financial reporting, disciplined loyalty professionals should not stop there. They should insist on evolving those models to provide accurate customer lifetime value estimation.


And accurate CLV cannot be calculated without first understanding URR and CPP at a granular member level. Accurate liability is the starting point.




KYROS provides sophisticated predictive analytics solutions that help companies optimize the financial performance of their loyalty program. Want to maximize the economic value of your program?  Contact us  for a free consultation.


Loyalty Program Finance: The Struggle for Progress

In my previous articles, we talked about some of the struggles loyalty marketers and accountants face when booking loyalty program liabilities.

Now we turn our attention to loyalty finance professionals, who face significant pressure to ensure accurate liability and solid loyalty program ROI.

Unfortunately, there are not many resources for finance professionals that support loyalty programs. This makes a loyalty finance professional’s struggle for progress very challenging.

In this article, we’ll look closer at the progress loyalty finance professionals aim for, along with the obstacles often face.

Read more »

Customer loyalty, predicted

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Customer loyalty, predicted

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