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.
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.
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.
[dropshadowbox align=”center” effect=”lifted-both” width=”80%” height=”” background_color=”#ffffff” border_width=”1″ border_color=”#dddddd” ]While breakage can result in unanticipated profits, relying on it solely to underwrite unsustainable advertisement promises can have devastating effect on a company.[/dropshadowbox]
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.
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.
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)
|1. American Express||7.751 billion|
|2. Marriott||4.940 billion|
|3. United||4.741 billion|
|4. Delta||4.118 billion|
|5. American Airlines||2.777 billion|
|6. Southwest Airlines||1.676 billion|
|7. Hilton||1.461 billion|
|8. Intercontinental Hotels||0.760 billion|
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 analyzing 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.
[dropshadowbox align=”center” effect=”lifted-both” width=”80%” height=”” background_color=”#ffffff” border_width=”1″ border_color=”#dddddd” ]The combination of actuarial science and machine learning has proven to be a robust approach to predicting redemption behavior.[/dropshadowbox]
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.
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.
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.
[dropshadowbox align=”center” effect=”lifted-both” width=”80%” height=”” background_color=”#ffffff” border_width=”1″ border_color=”#dddddd” ]Program managers must be wary of trying to encourage an excess of breakage, as doing so involves intentionally disengaging customers from the company.[/dropshadowbox]
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.
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.
Loyalty program liability: what marketing teams should know
Marketers can get broader buy in and investment in their loyalty initiatives by accurately quantifying liability and CLV.
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.
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.
This article has been republished from Kyros Insights.
Len Llaguno is the founder of Kyros Insights, a leader in loyalty program liability solutions. Kyros helps loyalty programs predict member behavior and manage complex financial reporting of program liabilities.