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 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 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 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 program’s value with more precision, you can use the insights you gain to make better decisions moving forward.

 

 

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

 

Why Your Loyalty Program Needs an Actuary

Loyalty programs are designed for continuous participation from members.

 

But if you’re a loyalty program manager responsible for generating program ROI, it’s not enough to simply understand where you are — you need to know where you’re going.

 

Unless you have a crystal ball, however, you’re likely going to need some help. But where should you start?

 

The answer is predictive modeling. Predictive modeling, which uses statistics to predict future outcomes, helps program managers determine the value each loyalty program member will bring to a company. Unfortunately, accurately forecasting the right numbers is easier said than done.

 

That’s where actuaries come in.

 

While their title may not be the most glamorous, actuaries are the financial experts who can shed light on the future of your loyalty program.

 

How exactly? By forecasting and extrapolating off past and current data, often with great accuracy. In fact, employing actuarial insights is one of the best ways to prepare your program for long-term financial success.

 

Actuaries can help you answer important questions such as:

 

“How can I optimize member acquisition?”

“Who are my highest value members?”

“Is my program strategy driving incremental value?”

 

When you arm yourself with an actuary, you’re taking an essential step towards setting and achieving your loyalty program goals.

 

In this piece, we’ll explain:

  • What actuaries actually do
  • 9 reasons why actuarial insight is useful to your loyalty program
  • Why a data science team isn’t enough
  • What you should look for in a loyalty program actuary

 

Do you know where your program is heading and why? Let’s enter the world of actuarial insight.

 

What does an actuary actually do?

 

To those new to the world of actuarial consulting, actuaries are somewhat of an enigma.

 

The Society of Actuaries labels the profession as “Part super-hero. Part fortune-teller. Part trusted advisor.” While you probably won’t encounter an actuary with a cape, these professionals take on an essential role in accounting for loyalty programs: they manage loyalty program risk by planning for the future and protecting their organization against loss.

 

Actuaries are generally associated with the insurance industry

Most people associate actuaries with insurance, and they’re right: over 50% of actuaries are employed directly or indirectly by the insurance industry.

 

Insurance companies are in the business of predicting outcomes. These companies are required to reserve cash for the policies that they sell, and must set aside money for the claims they expect to eventually pay out on those policies. Given the range of insurance policies, this planning can take on many different forms.

 

For example, when an insurance company issues your car insurance policy, they have to estimate the probability of paying a claim, the size of that claim, and the timing of when it will occur.

 

You pay your policy annually. And maybe someday (hopefully not), you’ll need to draw on your insurance policy to cover the costs of an accident or damage to your vehicle. The insurance company has to ensure, on average, customers are paying more into the plan than the company is doling out. It’s how they stay in business while still providing uninterrupted coverage.

 

Another example is workers’ compensation insurance. Some claims may not be reported until many years later (such as a disease brought about by occupational conditions), but would require medical payments throughout the rest of a person’s life.

 

While auto insurance claims only involve predictions over the twelve months of the policy period, reserving for worker compensation requires the tools to predict expected claims payments decades into the future based on the information available today.

 

When it comes to your loyalty program, this is just the type of information you need.

 

Actuaries have the toolbox for making long-term predictions

Fortune-tellers have crystal balls; actuaries have numbers, data, and statistics. Using statistical analysis, they can evaluate the probability of future events occurring and plan accordingly.

 

In the context of loyalty programs, cash flow (amount, timing) is the primary metric examined. Other metrics can include:

  • Customer lifetime value (CLV)
  • Customer future value (CFV)
  • Customer potential value (CPV)
  • Ultimate redemption rate (URR)
  • Cost-per-point (CPP)
  • Breakage

 

Forecasting over the long term is required for insurance companies, and can be highly beneficial for loyalty programs. Let’s walk through the benefits to long-term forecasting with actuaries.

 

9 reasons why actuarial insight is useful for loyalty programs

actuarial insight for loyalty programs

 

1. Helps predict loyalty program liability

When points are issued, companies must defer revenue for the eventual cost of redemption. This is required by the financial reporting standards ASC 606/IFRS 15. The challenge in estimating liability, however, lies in the number of variables associated with estimating redemption costs.

 

Actuaries can predict what percentage of points will ultimately be redeemed, when those redemptions will occur, and how much those redemptions will cost the company. After all, points can be redeemed many years (potentially decades) after they are earned. The best estimates require long-term forecasts.

 

Adding to this challenge is the reality that loyalty programs are dynamic, constantly evolving entities:

  • Members change their behavior frequently
  • Members are becoming increasingly sophisticated thanks to the availability of online resources on loyalty programs
  • Programs frequently offer deals and marketing campaigns
  • Programs occasionally change program structure – e.g., expiration rules, award charts, accrual charts, etc.

 

Liabilities can be very large, in the hundreds of millions or even billions of dollars – particularly among frequent flyer and hospitality programs. At this scale, CFOs and auditors require proper due diligence to validate liability estimates. Actuarial opinions provide formal documentation from a credentialed actuary stating their professional opinion on the booked program liability. This provides CFO, auditors, and other stakeholders proof of the due diligence.

 

2. Quantifies customer lifetime value (CLV)

While liability is important, the whole point of a loyalty program is to increase customer brand loyalty. (i.e., customers should keep coming back to your company to make purchases). The best way to quantify the value of this long-term loyalty is a metric known as customer lifetime value (CLV). CLV predicts the profits that a given member is expected to generate over his lifetime in the program.

As we’ve discussed in previous articles, CLV and its family of metrics are the most important KPIs to link program management to economic value creation. In fact, you can even use these metrics to proactively create economic value (you can review how to calculate customer lifetime value here).

Properly calculating CLV is critical to loyalty program profitability and requires the ability to predict over long horizons. As you’ll see, CLV and its many applications will unify the rest of this section.

 

3. Identifies high value members

Simply put, members with high CLV are likely to spend more money with your company. Targeting them with special offers will make them feel appreciated and inspire even more purchases, maximizing the likelihood of unlocking their expected future profits.

 

4. Drives incremental value by targeting high potential members

With just a small nudge, high potential members will likely increase their program participation, and, as a result, their CLV. A well-executed, targeted incentive strategy can grow the future economic value of your loyalty program.

 

5. Targets at-risks members with decreasing CLV

On the flip side, loyalty programs can use CLV as a defensive strategy. By identifying leading indicators of declining participation, programs can be designed to proactively prevent loss of economic value.

 

6. Provides enhanced customer service based on CLV

CLV quantifies the value of each customer. This indispensable information enables customer service agents to focus their efforts and spend more time and energy on resolving issues for those members most valuable to the organization. Note that this doesn’t mean that members with a low CLV don’t matter; rather, it focuses efforts on providing services that will keep your most loyal customers happy.

 

7. Optimizes new member acquisition based on value rather than cost

Well-run loyalty programs can become an appreciating asset for any company. Examining CLV as a growth value metric ensures that every dollar spent on acquisition is spent in a way that maximizes economic value, rather than minimizing cost.

 

8. Optimizes program design

Actuaries conduct scenario testing to forecast the impact of various program changes on CLV. By quantifying how these changes impact CLV, program managers can identify and implement the changes that drive the most growth. This ensures that program structure changes are focused on maximizing economic value.

 

9. Aligns marketing and finance around a common set of KPIs to measure economic value creation

Miscommunication and lack of alignment leads to lost time in business. Aligning KPIs across organizations prevents organizational conflict. Using the shared language of CLV, organizations can increase the speed by which they make decisions — a competitive advantage in today’s fast paced world.

 

Why a data science team isn’t enough

In today’s digital world, data analysis is a highly sought after skill. Wherever there’s a large amount of data, data scientists are needed to plug and chug through significant statistical analyses, searching for patterns and identifying solutions.

 

At first glance, data scientists share many skills with actuaries. Both require business intelligence and data analysis skills. And the end result of data analysis and actuarial insight is a best-fit solution to an ambiguous problem.

 

However, these professions are not interchangeable.

 

Data scientists lack domain knowledge

Data scientists know how to build models to make predictions, but not necessarily predictions over long horizons, which is where actuaries excel. Actuaries are also subject to rigorous formal training and credentialing in their domain of focus – whether that be insurance, finance, investments, etc.

 

We can’t overstate the value of domain knowledge.  Consider this example:

Suppose you need brain surgery. Are you going ask your family doctor to do the operation, or a trained brain surgeon? Both are very smart, both are trained in the medical profession, and both probably have the aptitude to do it. But only the brain surgeon has the training, experience, and specific domain knowledge required to do the job correctly.

 

Data scientists and actuaries are similar: both are smart, both are trained in applied statistics, and both have the aptitude to learn to predict over long horizons; but only actuaries have the explicit training, experience, and specific domain knowledge required to do the job right.

 

What makes an ideal loyalty program actuary?

Traditional actuarial models focus on making predictions in aggregate. But the value of CLV lies in its ability to make predictions at the individual member level.

 

Within actuarial consulting there is even more niche domain knowledge required to properly apply actuarial theory to loyalty programs. The most effective professionals combine predictive modeling with expert financial reporting knowledge.

 

Loyalty Program Actuary - Venn Diagram

 

Individual predictive modeling

Loyalty program actuaries need to know how to leverage today’s technology to build predictive models. Traditional actuarial methods were developed decades ago, well before the availability of today’s big data and advanced predictive modeling capabilities.

 

While the basic actuarial concepts underlying traditional methods remain applicable to today’s loyalty programs, the methods themselves need to be redesigned to leverage modern technology and allow for individual member-level predictions. Therefore, you need an actuary with strong predictive modeling skills and experience using modern technology to solve problems.

 

Financial reporting expertise

Given a loyalty program’s complex financial reporting requirements, you not only need an actuary with predictive modeling skills, but also one with a strong understanding of the business dynamics and financial reporting regulations surrounding loyalty programs.

 

ASC 606/IFRS 15 have introduced updated revenue recognition standards and a fresh focus on loyalty program accounting practices. Your actuary needs to know how to properly identify performance obligations when accounting for loyalty programs.


In summary, the ideal loyalty program actuary is adept at predicting behavior over the long term, can build predictive models at the individual member level, and has a nuanced understanding of business dynamics and the financial reporting environment. This combination enables actuaries and loyalty program leaders to translate predictions into real business insight and loyalty program value.

 

Optimize your program with the right actuary

loyalty program optimization

 

Loyalty programs generate more than a significant amount of data. Between engagement metrics, membership statistics and financial results, programs need someone with the skills to discern the meaning amidst all the noise. And while it’s easy enough to turn to any data scientist or actuary, to get the most actionable insight from your data, it’s best to trust those with deep domain expertise.

 

Imagine if each year at tax season, you hired an average accountant with limited personal tax experience. Would you really expect him or her to optimize your taxes and bring you the biggest refund?

 

The odds are that you would sleep better at night (and receive the biggest bang for your buck) if you hired a professional tax accountant with years of experience.

 

An ideal actuary can provide just as much peace of mind — and financial return — to your loyalty program. Select an expert who understands how to model your loyalty program liability, the nuances of customer lifetime value, and the fundamentals of optimizing program ROI.

 

Loyalty programs are one of the most effective ways of driving long-term customer value and ensuring the continued success of your business. When it comes to your program’s financial management, why cut corners?

 

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KYROS provides sophisticated predictive analytics solutions that help companies optimize the financial performance of their loyalty program. Need an experienced set of eyes? Contact us for a free consultation.

Loyalty Program Liability Budgeting: How to Build a Financial Forecast

It’s too late to ignore loyalty program modeling.  

 

Whether you manage a local program or an international program, you likely already have thousands (if not millions) of loyalty program members. In fact, data has shown that 30 – 50% of hotel room nights are purchased by loyalty program customers. And international airlines realize as much as 44% of total revenue from frequent flyer programs.

 

It’s clear that loyalty program liabilities and revenues represent significant balance sheet and income statement accounts. Unfortunately, these financial items are based on member behavior and can be hard to predict and budget.

 

But as the saying goes, failing to plan is planning to fail.

 

For example, it’s critical to accurately estimate breakage (the percentage of points that will ultimately go unredeemed) in order to defer the correct amount of revenue for each reporting period.  

 

Budgeting for your loyalty program draws out important considerations:

  • How will program revenue be recognized over time?
  • How much additional revenue will be deferred this year?
  • How will program revenue impact cash flow?
  • What will be next month’s redemption costs?

 

The solution is to build a financial forecast for key loyalty program metrics.

 

A robust model with prudent assumptions allows program managers to quickly run forecast scenarios, where multiple program variables can be estimated or adjusted as inputs. The result is an intelligent, responsive framework with which to examine your loyalty program’s performance under different breakage rates, member growth, and other key variables.  

 

In this article, we’ll walk you through the steps needed to analyze, build, and assess financial modeling for your loyalty program. These include:

  • Predicting point “runoff” for current members
  • Predicting future point transactions of current members
  • Predicting the URR, CPP, and FVPP of future earned points for current members
  • Predicting point transactions, URR, CPP, and FVPP for future members
  • Bringing it all together

 

Estimating these metrics not only provides you with a clearer picture of your loyalty program, it helps you better predict your program’s financials. To help you along the way, we’ve developed a model financial forecast, found near the end of this article.

 

Let’s get started.

 

 

Step 1: Predict point “runoff” for currently outstanding points

Loyalty Point Run off

 

The first step to building a financial forecast is to estimate when current outstanding loyalty program points are expected to be redeemed (or, in some cases, expire). Point “runoff” refers to one of two events:

  1. Points are redeemed
  2. Points expire

 

The running total of unredeemed and unexpired member points represents your growing program liability. These points will eventually either incur a cost or result in breakage.

 

Calculating ultimate redemption rate (URR) helps identify what percentage of points will ultimately be redeemed. However, it’s important to accurately estimate the timing of point redemptions.

 

A projected redemption pattern can help predict the timing of:

  • The cost to the company of fulfilling point redemptions
  • The recognition of previously deferred revenue
  • The expected pattern of point expirations

 

Robust actuarial analysis can generate a projected redemption pattern which, when summed, equals the URR for those points. The result of this predictive modeling analysis is an estimated runoff schedule of outstanding points – a forecast for when points are expected to be used or expire unspent.

 

For example, consider you have a program with 100 outstanding points and a breakage rate of 25%.

 

This means that the URR is 75% and that 75 of the 100 points will be redeemed. While it’s useful to know how many points will be redeemed, it’s ever more helpful to know when they’ll be redeemed.  A runoff schedule will forecast the cadence at which these points are redeemed or expired (e.g., 5 points in redeemed January, 4 points redeemed in February, and so on). The alternative is looking blindly towards the future.

 

Additionally, the runoff schedule will provide you with an estimate of the percentage of your liability expected to be redeemed within the next calendar year. This split between current and non-current is often reported in company financials, including those for frequent flyer programs and hospitality programs.


Reminder: New standards change performance obligation rules

It’s worth noting, that under the new ASC 606 and IFRS 15 standards, revenue can now only be recognized once the performance obligation has been fulfilled. For example, let’s say a loyalty program member stays 3 nights with a hotel and is rewarded with a free night, as part of the hotel’s promotional deal. Revenue isn’t recognized from the free night until it is actually used by the customer. In other words, transactions associated with the free night remain deferred until the customer utilizes the promotional reward and stays at the hotel.

 

 

Step 2: Predict future point transactions of current members

Predict future point transactions of current members

 

Now that you understand the future utilization of outstanding points as of a given evaluation date, it’s time to predict the outcome of points that have yet to be earned.

 

Predicting future behavior starts with forecasting the pattern of future points earned by current members for each month, extending out several years. For the best results, these forecasts should be calculated at the individual member level. When paired with an estimate of revenue per earned point, this will produce an estimate of future revenue for each member, which is the first component of customer future value (CFV), a key metric for program optimization.

 

In the same way, the pattern of future points redeemed and expired for each current member can be predicted. Note that these patterns will include the redemption and expiration of points that haven’t been earned as of the current evaluation date. This is a key difference from Step 1 and provides a fuller picture of the expected future redemption costs.

 

 

Step 3: Predict URR, CPP, and FVPP for future points earned by current members

Predict URR, CPP and FVPP for future points earned by current members

 

Also essential to this analysis is predicting ultimate redemption rate, cost per point (CPP), and fair value per point (FVPP) of the earned points forecasted in Step 2.

 

When multiplied, future earned points, URR, and FVPP represent the amount of revenue that will need to be deferred in future periods.

 

The product of future earned points, URR, and CPP equals the expected future redemption cost (the second component in the CFV equation).

 

Taken together, Steps 1 through 3 provide a strong foundation for loyalty program liability budgeting with existing members. Steps 1 and 2 provide month by month forecasts of point transactions, while Step 3 projects the ultimate outcome of points earned in each of the upcoming periods for current members.

 

 

Step 4: Predict point transactions, URR, CPP, and FVPP for future members

Predict point transactions, URR, CPP and FVPP for future members

 

Ultimately, accurately forecasting your program liability requires two things: (1) understanding current member behavior and (2) predicting future member behavior.

 

Similar to how we determine current member behavior, predicting future member behavior requires we look at the following:

  • Future member points earned
  • Future member points redeemed
  • Future member points expired
  • Ultimate redemption rate (URR)
  • Cost per point (CPP)
  • Future value per point (FVPP)

 

It’s no secret that loyalty programs generate large amounts of data. Predictive modeling can help you draw actionable insight into each of these aforementioned metrics, while giving you the required understanding to make important decisions about your program strategy as a whole.

 

Build your model from the bottom up, taking a member and channel-specific approach:

  1. Segment members by the channel through which they join (e.g., web, offline, partner)
  2. Forecast metrics for the average member who will join via a given channel in a given month
  3. Multiply this by the expected number of members joining through that channel in each month

 

Segmenting by join channel allows for projecting different scenarios of member growth by channel. Forecasts of member growth by channel are common throughout the loyalty industry, and channel data can provide insights into expected member behavior when transactional data is limited or non-existent.

 

For example, in some programs, members who join via offline channels earn fewer points and have a higher breakage rate than members who join through other channels. If a program intends to scale down its acquisition spend for offline channels, program leaders should expect the overall breakage of points earned in the future to decrease.  

 

Ultimate redemption rate for a given join month should increase over time

Analytics at the individual member level will offer your team key insights into member behavior.

 

As an example, consider the ultimate redemption rate:

 

Ultimate Redemption Rate (URR) = Total points that will ultimately be redeemed / Total points issued

 

URR is weighted by total points. Even a small group of members, if they have have enough points, can have an outsized impact on the overall URR. Members who earn more points tend to have a higher URR. Over time, as these power users earn a larger share of the total points, the overall URR is pushed up.  This phenomenon is known as mix shift.

 

When members first join, however, the share of points between casual and power users is more evenly distributed.

 

For example: suppose Larry (a casual user) and Amy (a power user) are the only two members who join in a given month:

 

Age 1
Age 2
Age 3
Age 4
LarryCumulative Earned Points
50
50
50
70
URR on EP
30%
30%
30%
30%
Amy
Cumulative Earned Points
50
100
200
300
URR on EP
90%
90%
90%
90%
TotalCumulative Earned Points
100
150
250
370
URR on EP
60%
70%
78%
79%

 

Casual versus Power User

Cumulative URR increases over time as power user mix increases

 

The overall URR for the join month starts at 60%, when both the casual and power user have earned a similar share of points. However, notice how the URR increases over time as Amy, a power user, earns a significant share of the overall points.

Viewed on a larger scale, your program URR should follow a similar pattern.

 

 

Step 5: Bring it all together

Bringing it all together

 

We’ve discussed evaluating current and future member behavior. But to truly see the “big picture” of your loyalty program data, we need to combine current and future earned points — and members — to produce a complete forecast of revenue and costs.


Aggregate estimates

In steps 1-4, we calculated the ultimate redemption rate (URR), cost per point (CPP), and fair value per point (FVPP). These estimates for current and future members serve as inputs for financial statement items and program optimization metrics.


Forecast financial statement items

After forecasting behavior metrics for your loyalty program members, it’s time to turn your attention to the actual financial statement. On public financials, the loyalty program liability receives the most attention. FVPP and URR are key inputs to estimating your financial liability (reported on financial statements), while CPP is essential for estimating your economic liability (actual future costs to your program).

Breakage = 1 – URR

Loyalty program financial liability = Outstanding points x (1 – breakage) x FVPP

Loyalty program economic liability = Outstanding points x (1 – breakage) x CPP


Consider program optimization metrics

Many of the metrics discussed serve as inputs towards calculating your loyalty program liability. Conveniently, optimizing your program relies on many of the same metrics.

 

Ultimately, you want to be maximize your loyalty program ROI. Customer lifetime value (CLV) is a reliable measurement. If it’s increasing, your program is likely driving increased customer engagement that encourages revenue growth.

 

Pulling these metrics together into a coherent portrait of your program’s financial future can be daunting, however. Our  downloadable guide provides you with a framework to put the pieces together. It takes you through each step – estimating member growth, projecting the behavior of new members, and forecasting the outcomes for current members – to create a long-term view of key loyalty program cash flows.  Additionally, it allows for scenario testing, giving you actionable insight into the effects of various member acquisition strategies.

 

 

Conclusion

Strategizing and reporting reliable loyalty program liability estimates is a complicated undertaking. Reportable deferred revenue relies on accurate actuarial analysis requiring sound estimates for many program metrics.

 

Bottom-up predictive modeling can build a reliable, robust financial forecast for liability budgeting. It starts with segmenting your members by behavior, calculating relevant program metrics, and considering future member behavior.

 

To improve your program liability budgeting, take the five steps we’ve outlined in this article:

Step 1: Predict point “runoff” for current members

Step 2: Predict future point-earning behavior of current members

Step 3: Predict the point behavior, URR, CPP, and FVPP for future members

Step 4: Predict point transactions, URR, CPP, and FVPP for future members

Step 5: Bring it all together

 

Ultimately, the goal is to build an accurate financial forecast of both member behavior and program liability.

 

But the benefits extend far beyond predicting where your program is headed. Such analysis gives you the insight needed to optimize your loyalty program — not only improving customer engagement, but increasing its ROI.  

 

 

 

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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.

 

Sizing Up the Largest Frequent Flyer Programs

As a consumer, frequent flyer programs are exciting, engaging, and rewarding to participate in. Frequent flyers not only receive discounted airlines tickets, they can redeem their points for everything from overnight hotel stays to car rentals, magazines, and more, thanks to a significant amount of program partners.

 

As a program manager, providing such benefits engages customers and builds brands loyalty. Of course, in an ideal world, the revenue generated from these loyalty programs would exceed their costs.

 

Yet, while loyalty programs have been a staple of the airline industry since 1981, benchmarking data is limited.

 

Last month, we launched a series on loyalty program benchmarks to uncover valuable insights for our readers. The goal: to establish key benchmarks across industries that utilize loyalty programs as essential revenue generation strategies.

 

Our benchmarking series carefully examines the publicly available financial information regarding each of the following program attributes:

 

Loyalty program revenue

  • Revenue from sale of points
  • Loyalty program usage & membership

 

Loyalty program costs

  • Loyalty program liability
  • Loyalty program breakage
  • Current vs non-current liability
  • Program liability sensitivity
  • Loyalty program point expiration
  • Implementation of ASC 606 & IFRS 15

 

The first piece in our series gave readers an inside look into the hospitality industry. Now, we turn our attention to the airline industry.

 

For this installment, we examined a large subset of US and international companies, including:

 

US Airline Companies

  • American Airlines
  • Delta Airlines
  • United Airlines
  • Southwest Airlines
  • Alaska Airlines
  • JetBlue
  • Hawaiian Airlines

 

International Airline Companies

  • Air France – KLM
  • Lufthansa
  • Avios (British Airways)
  • Emirates
  • Air China
  • Qantas Airways
  • LATAM Airlines
  • SAS
  • Avianca
  • Virgin Australia
  • Air New Zealand
  • Copa Airlines
  • El Al Israel Airline

 

In examining the results of this study, we hope you take away valuable insights for your loyalty program.

 

Loyalty program revenue

loyalty program revenue

Revenue from sale of points

Frequent flyer programs add significant value to the airlines that employ them. Although companies are not required to disclose the revenue generated by their loyalty programs, we can get a sense of the magnitude of this value by examining the revenue recorded for the sale of miles to co-branded credit card or other partners.

 

There are generally two revenue elements associated with the sale of miles to partners: the transportation component (the fair value of the miles to the end consumer) and the marketing component (the value to the partner of the airline brand and other advertising). Several US companies report the marketing component of the revenue associated with the sale of miles.

 

Company
Revenue associated with sales of miles (marketing component)
American Airlines
~$2,200 million
United Airlines
$1,183 million
Alaska Airlines
$396 million

 

The marketing component of the sale of miles to partners is a material source of revenue – capable of reaching billions of dollars annually – yet it reflects only a fraction of a loyalty program’s value. Other components include:

  • Revenue associated with the transportation component of the sale of miles (above and beyond the cost of fulfilling the redemptions)
  • Revenue associated with ticket sales to loyalty program members (net of the cost of good solds and redemption costs)

 

International companies tend not to share the revenue related to the sale of miles. However, Air China does publish member contribution information.

 

Company
Loyalty program member contribution
Air China
43.7% of total revenue

 

The percent of total revenue attributable to frequent flyer members for Air China falls within the range of the loyalty program contribution we observed in the hospitality industry. Loyalty program members generate a large portion of these companies’ revenues.

 

However, we still don’t have the full picture of the value of these loyalty programs. Instead of looking at these historical revenue numbers, a more complete picture would require an understanding of the expected future revenue from members, net of expected future cost, and how the loyalty program has increased this expectation over time. This metric is called customer future value (CFV), and the sum of CFV across all members is known as member equity. Unfortunately, this is not something that is often calculated, but can be extremely valuable to managing and optimizing the frequent flyer program.

 

Loyalty program usage & membership

Numbers on airline loyalty program membership is scarce, and current data for US companies is not readily available. However, several international airlines share member count, which is roughly correlated with company revenue.

 

Company
Members
Total 2017 Revenue
Emirates
20 million
$25,139 million
Air China
51 million
$19,044 million
Qantas Airways
12 million
$12,632 million
LATAM
30 million
$9,614 million
SAS
5 million+
$5,118 million
Avianca
8 million
$4,442 million
Virgin Australia
9 million
$4,155 million
El Al
2 million
$2,097 million

 

On the other hand, most US airlines do share information on award redemptions. These redemptions include flight awards, hotels, and other perks. The table below shows that the quantity of award redemptions appears to align with company revenue levels, and that, with the exception of Southwest Airlines, award travel generally makes up between 5% to 8% of total passenger revenue miles.

 

Company
Award Redemptions
Award Travel as % of Total Passenger Miles
Total 2017 Revenue
American Airlines
11 million
6.1%
$42,207 million
Delta Airlines
14.9 million
7.9%
$41.244 million
United Airlines
7.7 million
7.5%
$37,736 million
Southwest Airlines
9.6 million
13.8%
$21,171 million
JetBlue
2 million+
5%
$7,015 million
Hawaiian Airlines
612,000
5% (of passengers)
$2,695 million

 

Conclusion

Selling miles can be a great revenue generator for airlines, with revenues reaching several billion dollars for the largest carriers. But the value of a loyalty program doesn’t stop there. Frequent flyer programs present a mechanism to influence millions of customers and, consequently, millions, or even billions, of dollars in future purchases. Companies that don’t harness this mechanism to maximize those future purchases using predictive metrics like customer future value and customer potential value are missing out on an enormous opportunity.

 

 

Loyalty program costs

loyalty program costs

Liability

Driving customer engagement through loyalty programs leads to a backlog of redeemable miles, points, and rewards. These redeemable rewards can drive significant growth in both revenue and brand loyalty.

 

When looking at financial statements, this backlog of redeemable points is represented as deferred revenue, or loyalty program liability. The account value represents potential performance obligations in exchange for future customer point redemption.

 

Company
Total Revenue
Loyalty Program Liability (Deferred Revenue)*
American Airlines
$42,207 million
$8,822 million
Delta Airlines
$41,244 million
$6,321 million
United Airlines
$37,736 million
$4,783 million
Southwest Airlines
$21,171 million
$2,667 million
Alaska Airlines
$7,933 million
$1,725 million
JetBlue
$7,015 million
$502 million
Hawaiian Airlines
$2,695 million
$322 million

*Restated to reflect ASC 606/IFRS 15 where necessary


In general, loyalty program liability increases along with total company revenue. The table above shows that the US airlines appear to follow this pattern.

 

Company
Total Revenue
Loyalty Program Liability (Deferred Revenue)*
Air France - KLM
$30,941 million
$983 million
Lufthansa
$27,931 million
$2,608 million
Avios
$27,517 million
$1,406 million
Emirates1
$25,139 million
$611 million
Air China
$19,044 million
$530 million
Qantas Airways2
$12,632 million
$1,709 million
LATAM Airlines
$9,614 million
$1,218 million
SAS3
$5,118 million
$213 million
Avianca
$4,442 million
$384 million
Virgin Australia2
$4,155 million
$344 million
Air New Zealand
$3,711 million
$232 million
Copa Airlines
$2,528 million
$50 million
El Al
$2,097 million
$104 million

*Restated to reflect ASC 606/IFRS 15 where necessary
1 Year-ending 31 March 2018
2 Year-ending 30 June 2018
3 Year-ending 31 October 2017

 

For airlines headquartered outside the US, the correlation between loyalty program liability and total revenue doesn’t appear to be quite as strong.

 

This could be driven by the lower maturity of international frequent flyer programs. While the first US loyalty program was established in 1981, European airlines didn’t introduce loyalty programs until 1991.

 

Breakage

A key metric for any loyalty program is breakage. Accurately forecasting your breakage rate is essential to maintain financial statement credibility, and avoid material impacts to net income.

 

While there is no reporting requirement for breakage rates, two US airlines of significantly varying revenues reported an average rate of 17 – 18%.  

 

Company
Total Revenue
Breakage
United Airlines
$ 37,736 million
18%
Alaska Airlines
$ 7,933 million
17.4%

 

This suggests that nearly 1 in 5 airline loyalty points will not be redeemed. However, given the small sample size, it’s unclear if this is representative of the entire industry.

 

Program liability sensitivity

Breakage rates are an essential component to calculating program liabilities carried on financial statements. If estimated breakage rates are too high, liability is underestimated. If estimated rates are too low, liability is overestimated.

 

In both cases, errors in breakage estimation can result in revised financial statements and material impacts to earnings. Understandably so, companies report their sensitivities.  

 

Company
Sensitivity
Total Loyalty Program Liability
American Airlines
1% change in breakage changes liability by $38 million
$8,822 million
Delta Airlines
1% change in breakage changes liability by $34 million
$6,6321 million
United Airlines
1% change in breakage changes liability by $53 million
$4,783 million
Southwest Airlines
1% change in breakage changes liability by $48 million
$2,667 million
Alaska Airlines
1% change in breakage changes liability by $10 million
$1,725 million

 

While US airlines range in their liability sensitivity, on average, a 1% change in breakage estimates will result in a 1% change in liability.

 

Company
Sensitivity
Total Loyalty Program Liability
Avios
1% change in breakage changes liability by $10 million
$1,460 million
LATAM Airlines
1% change in breakage changes liability by $33 million
$1,218 million

 

Only a few international airlines report sensitivities. Among those that do, a 1% change in breakage estimate will result in a 1% to 3% change in liability.

 

Current vs Non-Current Liability

Loyalty program liability can be split into current and non-current time periods.

 

Company
Current liability
Non-current liability
American Airlines
35%
65%
Delta Airlines
44%
56%
United Airlines
46%
54%
Southwest Airlines
60%
40%
Alaska Airlines
37%
63%
JetBlue
23%
77%
Hawaiian Airlines
-
-
Average
41%
59%

 

US airlines show an inclination towards more redemptions occurring outside a 12-month window. On average, 59% of their program liability is non-current.

 

Company
Current liabilityNon-current liability
Air France - KLM100%-
Lufthansa100%-
Avios--
Emirates53%47%
Air China20%80%
Qantas Airways39%61%
LATAM Airlines--
SAS-100%
Avianca145%55%
Virgin Australia100%-
Air New Zealand48%52%
Copa Airlines34%66%
El Al67%33%
Average244%56%
 
Period ending 3/31/2018
2 Excluding companies that place their total liability into one bucket

 

The picture isn’t quite as clear with international airlines. Several airlines group their entire liability into one bucket. On average, the split between current and non-current liability among the remaining airlines is about 44%/56%.

 

Loyalty program point expiration

Expiration rules introduce a clearly defined end to points accumulation and program participation, should consumers fail to log any earning activity.

 

Expiration rule strategies vary by company, but generally they incentivize participation and point usage. Data analytics can help study and assess the optimal expiration period.

 

Company
Required activity period
American Airlines
18 months
Delta Airlines
None
United Airlines
18 months
Southwest Airlines
24 months
Alaska Airlines
24 months
JetBlue
None
Hawaiian Airlines
18 months

 

Most US airlines require activity within an 18 to 24-month period; otherwise points expire. Two exceptions are Delta and JetBlue.

 

United Airlines customers redeem the majority of points within 4 years, with most points used within the first year, and 18% of points ultimately expire. Among JetBlue customers, most points are redeemed within 3 years.

 

Company
Required activity period
Air France - KLM
24 months
Lufthansa
Expire in 36 months
Avios
36 months
Emirates
Expire in 36 months
Air China
Expire in 36 months
Qantas Airways
18 months
LATAM Airlines
Expire in 36 months
SAS
Expire in 5 years
Avianca
12 months
Virgin Australia
24 months
Air New Zealand
Expire in 48 months
Copa Airlines
24 months
El Al
Expire in 36 months

 

International airlines expiration policies are diverse. Most commonly, points expire after 18 to 36 months of inactivity. Several airlines have a strict expiration timeline where points will simply expire as early as 36 months, or as late as 60 months from earning date.

 

Expiration policies among international airlines may be converging closer to the standards of US airlines, however. In recent years, Avianca and Virgin Australia have reduced their expiration period from 24-months and 36-months of inactivity to 12-months and 24-months, respectively.

 

Implementing ASC 606 & IFRS 15

The ASC 606 / IFRS 15 implementation drove several key changes:

  • Removed inconsistencies from reporting
  • Improved the revenue recognition framework
  • Improved the comparability of revenue recognition practices across entities
  • Provided more useful financial statement information
  • Simplified financial statement preparation

 

Net liabilities increase with ASC 606

Effective as of December 2017, ASC 606 drove major revenue recognition changes for US airlines. Many airlines that were following an incremental cost model had to reassess their program liabilities with the deferred revenue model.

 

Company
Model Pre-ASC 606
Post-ASC 606 Result
American Airlines
Incremental Cost
Program Liabilities +216%
Delta Airlines
Deferred Revenue
Program Liabilities +53%
United Airlines
Deferred Revenue
Program Liabilities flat
Southwest Airlines
Incremental Cost
-
Alaska Airlines
Incremental Cost
Program Liabilities +39%
JetBlue
Incremental Cost
Program Liabilities +67%
Hawaiian Airlines
Incremental Cost
-

 

As a result, program liabilities increased across most airlines – primarily due to changing valuation models. Both United and Delta Airlines already followed a deferred revenue model. While United had very little change in liability numbers, Delta Airlines revalued and reallocated revenue categories to be consistent with the new standard.  

 

Slight increase in deferred revenue with IFRS 15

While many US companies experienced substantial liability increases as a result of ASC 606, international airlines didn’t see quite as significant a change under IFRS 15. Most experienced merely a reclassification of revenue, and many had no substantial change in reporting at all.

 

Company
IFRS 15 Changes
Air France - KLM
-
Lufthansa
Higher deferred revenue, reclassification
Avios
Higher deferred revenue; negative earnings impact
Emirates
-
Air China
-
Qantas Airways*
Revenue recognized earlier
LATAM Airlines
-
SAS
-
Avianca
Higher deferred revenue
Virgin Australia
Model change
Air New Zealand
Revenue reclassification
Copa Airlines
+9% liability
El Al
-
 
*In response to AASB 15 – Australia’s IFRS 15 equivalent

 

Copa and Virgin Australia both utilized a residual value model and shifted to valuing performance obligations at the relative stand-alone selling price. As a result, Copa realized a 9% increase in liabilities.

 

Similarly for Avios, the impact of assessing the stand-alone selling prices of the individual performance obligations has resulted in a greater portion of revenue being deferred on issuance, because the stand-alone selling price of the points was higher than the fair value applied under IFRIC 13. As a result of deferring more revenue, Avios experienced a material impact of 399 million EUR to retained earnings.  

 

Air New Zealand will present NZ IFRS 15’s impact on its financial statements for year ending 30 June 2019. Net impact is not expected to be material, but revenue will be reclassified from “other revenue” to “passenger revenue.”

 

Avianca experienced a net increase to deferred revenues. Its loyalty program recognizes only one performance obligation, fulfilled upon redemption of customer miles. Previously, Avianca recognized multiple performance obligations for marketing, branding, and mileage redemption.  

 

Lufthansa’s deferred revenues will increase, with retained earnings being hit negatively by several hundred million euros. In response to IFRS 15, all of Lufthansa’s liabilities were reclassified as current: 1,237 million EUR was reclassified from non-current to current, while 532 million EUR was reclassified from deferred income to contract liabilities.

 

Finally, Qantas Airways will change revenue recognition timing, as well as temporary earnings reductions. For Qantas, AASB 15 (Australia’s equivalent to IFRS 15) provides new guidance for points that are expected to expire unredeemed, which results in revenue being recognized earlier than under current accounting standards.

 

Conclusion

Frequent flyer programs have a material financial footprint on the balance sheet, with the largest programs tying up several billion dollars in deferred revenue. But these liability amounts are based on estimates, and small estimation errors can drive income impacts of tens of millions of dollars.

 

Furthermore, for the average airline, over 40% of these liabilities will be recognized within the next twelve months. This can create a potential cash flow challenge if many of the redemptions are for partner rewards. On the other hand, over 50% of these liabilities won’t be recognized for twelve months. Financially savvy frequent flyer programs can use the free cash flow created by this delayed fulfillment to invest in the program or other assets to generate additional value.

 

Finally, while these liabilities are substantial, it is important to place them in the appropriate context. Focusing on the costs in isolation is suboptimal and will result in suboptimal business decisions. It is critical to remember that the value generated by rewarding customer loyalty can be massive and will almost always outweigh the cost.

 

The best metric to truly assess a loyalty program is customer future value, which considers both the cost and the benefit of giving rewards. Unfortunately, this metric is not often calculated, and it’s certainly not disclosed in financial statements.

 

 

Applying these insights to your program

 

In our second piece examining loyalty program benchmarks, we examined 20 top airline companies.

 

A clear takeaway from this look at publicly available financial statements is that the cost of these loyalty programs is substantial, with liabilities capable of reaching billions of dollars. Even a small change in breakage estimates can drive an income impact of tens of millions of dollars. Given the financial materiality, it is essential that stakeholders have confidence in the deferred revenue balances on the books.

 

Perhaps the most important takeaway, though, is that loyalty programs generate a tremendous amount of value. For many companies, the marketing revenue accrued from selling points can be considerable, upwards of several billion dollars. In addition, significant revenue is generated through the sale of flight tickets to members – for Air China nearly half of its revenue came from program members.

 

What this means is that a loyalty program represents a massive lever to drive financial value, influencing millions or even billions of dollars in future purchases. Unfortunately, effectively using the program to drive this value can be difficult without the proper analytics. For most companies, the program liability is a very visible metric, but the marginal revenue received for holding this liability is less tangible. This can often lead to a focus on cost minimization rather than value maximization.

 

A full picture of the value of your loyalty program includes projections of future revenues net of future costs, also known as customer future value. KYROS Insights builds tools to make it easy to quantify customer future value, allowing you to properly assess cost-benefit trade-offs and ultimately make decisions to unlock the untapped financial value in your loyalty program.

 

_________

Get actionable financial insight and begin optimizing your loyalty program today. Contact us for a free consultation.

Your 9-Step Checklist for Loyalty Program Financial Reporting

Year-end means a lot of things for many people. Holiday music, ice skating, pumpkin spiced lattes.

 

For accountants? The fun starts after closing the year-end books.

 

With the recent changes in loyalty program revenue recognition standards, this process has come under fresh scrutiny. Loyalty program accountants must now incorporate the new reporting standards ASC 606 and IFRS 15, while still optimizing their financial statements for profitability.

 

Rather than get lost in the details (as it’s all too easy to do), we’ve compiled a quick 9-step checklist for loyalty program financial reporting. As you enter the holiday season, we hope this will speed up your processes and bring better financial insight to your program.

 

Step 1: Validate data

Accuracy is everything in accounting.

 

Naturally, the first step is to ensure your records are accurate and correct. Good data is essential.

 

Each accounting period should be checked to ensure that individual transactional data matches with the total outstanding point balance used in the liability calculation. Underlying data for breakage estimates must match with data used for the books.

 

In general, prior period trends should also be consistent. Examine the number of points earned, points redeemed, and points expired each month. Month-to-month point volumes should appear similar when compared to historical years, notwithstanding some exceptions.

 

A few exceptions to watch out for include:

  • Flash promotions increasing redemptions
  • Temporary grace periods decreasing point expiration
  • New expiration rule increasing point expiration

 

Step 2: Allocate redemptions to points earned

Accurate breakage estimates require correctly allocating redemptions to actual point earnings.

 

Loyalty program point allocation has similarities to inventory valuation. As customers use their points, redemption costs should be allocated to specific point earnings. Much like when physical inventory is sold, revenue and costs of goods sold is applied for each unit sold.

 

The industry standard for loyalty programs is First in First Out (FIFO). Under FIFO, point redemptions are tied to the member’s earliest earned points (first in) that remain outstanding.

 

Unlike inventory valuation, there is no required method for point allocation. Some programs might find using FIFO isn’t realistic or advantageous:

  • Programs with expiration rules varying by point
  • Programs whose members choose which points to redeem

 

Regardless of which method you follow, a clean system will tie redemptions to specific point earnings.

 

Step 3: Update breakage and fair value estimates

update breakage estimates

Breakage lies front and center for loyalty program accounting. Your program is optimized for customer engagement and increasing revenue. Breakage is the variable that balances these two goals.

 

Breakage drives most of the financial strategy for a loyalty program. With the new standards, it’s more important than ever to land on an accurate estimate.

 

Updating breakage estimates

Breakage is the percentage of outstanding points that will ultimately go unredeemed. This estimate is used to calculate loyalty program liability.

Breakage = % of points that go unredeemed

Loyalty Program Liability = Outstanding points x (1 – Breakage) x CPP

Cost Per Point (CPP) = Expected cost of each point that will be redeemed

Revenue Recognition Rate = Deferred revenue / future points expected to be redeemed

 

Breakage estimates are updated with each new period, as new customer data rolls in.

 

For example:

Last Period:

Deferred Revenue Balance = $900

Points Ultimately Expected to be Redeemed = 1,200

Revenue Recognition Rate = $900 / 1,200 points = $0.75

Points Redeemed in Period = 200

Revenue Recognized in Period = 200 x $0.75 = $150

 

Next Period:

New Deferred Revenue Balance = $900 – $150 = $750

Remaining Points Expected to be Redeemed Based on Prior Breakage Estimate = 1,200 – 200 = 1,000

Remaining Points Expected to be Redeemed Based on Updated Breakage Estimate = 950

Updated Revenue Recognition Rate = $750 / 950 points = $0.79

 

Because we now expect fewer points to be redeemed (higher breakage), the revenue recognized with each future point redeemed increases.

 

The dangers of inaccurate breakage estimates

In an ideal world, your breakage estimate is spot on. As members redeem their points, deferred revenue is recognized and your accounts balance out.

 

In reality, estimates require continual adjustment. However, if you significantly over or underestimate breakage, significant revisions will be required:

  • Breakage estimate too high and your deferred revenue will be too low, requiring a one-time (potentially) material increase in program liability;
  • Breakage estimate too low and your deferred revenue will be too high, resulting in stuck revenue.

 

Accurate breakage estimates require predictive actuarial models

The consequences of inaccurate breakage estimates can be avoided with robust actuarial modeling.

 

Actuaries excel at estimating program liabilities from uncertain cash flows and consumer behavior.

 

However, traditional actuarial science methods, such as those used in insurance, are not ideal for loyalty program applications; the loyalty program industry is far more dynamic and fluid than the insurance industry.

 

Predictive analytics and modeling is the best solution for estimating accurate breakage rates. These advanced actuarial models can calculate breakage estimates down to the individual member level.

 

Fair value per point estimates

Fair value per point (FVPP) is a component of calculating deferred revenue for a loyalty program. FVPP is a dynamic measure that can change with each period.

 

A number of variables can change FVPP:

  • Changes in utilization distribution
  • Changes in award charts
  • Temporary promotional rewards
  • Changes in foreign exchange rates
  • Inflation
  • Seasonality in standalone value of rewards (i.e. flights, hotel nights)

 

Assess actual member behavior versus forecasts

Models and estimates are only worthwhile if they are accurate. Each period, assess actual results to your forecasted values for breakage, FVPP, and redemption patterns.

 

Ask yourself questions such as:

  • How did the volume of points redeemed compare to our model predictions?
  • Did members redeemed their points on the award types our model predicted?

 

If your answers aren’t quite what you’d hoped, you’ll need to assess and adjust.

 

In analyzing your model performance, you’ll be able to identify what’s driving changes in your estimates. This is essential to communicate a clear story to your CFO and auditors. A member-level model is particularly useful for constructing a clear narrative.

 

Step 4: Record accounting entries for reporting periods

record corresponding accounting activity

Each financial reporting period will require updating key loyalty program accounts. The following items will change and require the corresponding accounting activity:

  • Points earned
  • Points redeemed
  • Points expired
  • Updated breakage estimates

Points earned

Any new points earned will require an associated entry to deferred revenue. The value should be based on the relative standalone selling value of the points.

 

The amount of deferred revenue recognized should incorporate your latest breakage estimate.

 

For example, if breakage = 10%, each redeemable dollar should result in deferring 90 cents.

 

Points redeemed

Points redeemed during the reporting period will result in recognizing new revenue and reducing deferred revenue liability.

 

The revenue recognition rate represents the proportion of deferred revenue realized per every redeemable point.

 

Let’s take a closer look:

 

Beginning of the Period:

Deferred Revenue Balance = $900

Points Ultimately Expected to be Redeemed = 1,200

Revenue Recognition Rate = $900 / 1,200 points = 0.75

 

During the Period:

Points Redeemed =200

Deferred Revenue Recognized = 200 x 0.75 =$150

 

Points expired

Points expired during the period require no adjustment, as long as the deferred revenue account incorporates point expiration estimates.  

 

Final adjustments

This list is by no means exhaustive. A few noteworthy additional items to adjust include:

  • Adjust deferred revenue balances with latest foreign exchange rates
  • Breakage estimates (with associated updates to the deferred revenue account)

 

Member-level predictive analytic models help quantify the magnitude of exchange rate risk, and aggregate results up to a total currency level.

 

Step 5: Seek an actuarial opinion

Actuarial opinion to certify accuracy

A company’s CFO and auditors are required to certify the accuracy of company financial reporting statements. Given the financial statement ramifications of an inaccurate breakage estimate, actuarial opinions are sought to justify loyalty program liability.

 

An actuarial opinion is signed by a credentialed actuary as proof of thorough review and vetting of loyalty program liability assumptions, and provides the following:

  • Support for booked breakage estimate to auditors
  • Peace of mind for the CFO (booked liability is materially significant to financial statements)
  • Protection against key material risk factors (inaccurate estimates of loyalty liability or breakage)

 

The opinion provided will usually be presented as a range of reasonable estimates, any of which are actuarial justified for booking purposes. Often, actuaries will present their analysis to the CFO and auditors verbally, in addition to a physical document.

Step 6: Prepare financial disclosures

financial disclosure reporting

There’s already a long list of required disclosures for loyalty programs. After ASC 606 and IFRS 15, the list has only gotten longer.

Required disclosures Include:

  • Liability change during the year
  • How much revenue recognized in the period is included within opening liability balance
  • When the company satisfies its performance obligations (e.g., when the reward is used)
  • Nature of the goods and services the company has promised to transfer
  • Estimate of the timing to satisfy the liability
  • Significant judgments
  • Method used to determine transaction price and allocate it to performance obligations

 

A deeper dive (and examples) into the financial reporting requirements is available here.

 

Step 7: Hedge exposure (optional)

An optional but prudent step is to consider your foreign exchange exposure. If your liability is significantly exposed to foreign exchange risk, your modeling and liability estimate becomes much more complicated.

 

An effective currency risk management strategy involving forward contracts can minimize and hedge your exposure to foreign exchange fluctuation risks.

 

Step 8: Assess progress against your financial plan for the year

While Steps 2 through 7 account only for the loyalty program liability, there are additional transactions and measures to track each month. These include:

 

Cash Flow Implications

  • Points earned bring in revenue
  • Points redeemed carry a cost

Forecasting Implications:

  • Forecast liability and cash flow
  • Anticipate year-end financial position
  • Determine budget availability
  • Plan for the medium- to long-term horizon

 

Comparing actual transactions and breakage estimates to forecasts will help identify if your program is over- or under-performing. Of course, random fluctuations can be expected, but large variances should be investigated and understood.

 

Variances can be examined manually, but will be most effectively assessed through drilling down with member-level models.

 

Over time breakage will shift. As frequent customers accumulate more points, they become “power users” (i.e., customers with a larger share of the overall point distribution). It’s worth noting that these power users will tend to push the overall breakage rate down.

 

Step 9: Uncover further opportunities to optimize

identify opportunities to optimize

Finally, it’s worth remembering that the financial reporting process highlights many metrics that can be optimized for better overall performance.

 

Customer lifetime value (CLV) represents another key opportunity. CLV is the present value of all net cash flows expected for each member. This metric can be calculated through implementing a member-level model.

 

CLV represents a member-specific metric to focus on for maximizing the profitability of your customer loyalty program. The goal should be to increase CLV for each member each month. This is achieved through a mix of driving customer engagement and purchases.

 

By implementing a CLV model, program managers can also identify and target new members with a high CLV-to-acquisition-cost ratio.

 

It can be tempting to focus primarily on minimizing your program liability. After all, it’s the only piece of a loyalty program that shows on your financial statements. However, long term profitability and growth depend on maximizing CLV and customer revenue net of cost.

 

Conclusion

As the year winds down, deadlines get tighter and deliverables become more urgent. When assessing your next reporting period, give this 9-step checklist a try:

 

Step 1: Validate data

Step 2: Allocate redemptions to points earned

Step 3: Update breakage and fair value estimates

Step 4: Record accounting entries for reporting periods

Step 5: Seek an actuarial opinion

Step 6: Prepare financial disclosures

Step 7: Hedge exposure (optional)

Step 8: Assess progress against financial plan for the year

Step 9: Uncover further opportunities to optimize

 

As we wind down on 2018 and look ahead to 2019, understanding what goes behind each of these steps will help you continue to improve the accuracy of your financial reporting, and provide valuable insight to your company as it looks for new ways to optimize its financial performance.

 

 

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Turn insight into action with predictive analytics solutions that help you maximize the economic value of your loyalty program. Contact us for a free consultation.

An Inside Look at Loyalty Program Benchmarks for the Hospitality Industry

When analyzing your loyalty program strategy, knowing the financial benchmarks against which you should be comparing the success of your program is vital.

 

Unfortunately, such competitive information is not readily available without extensive research or an expensive team of consultants.

 

In an effort to uncover valuable loyalty program insight for our readers, we’ve taken it upon ourselves to assess the competitive landscape of some of today’s largest loyalty programs.  Our goal: establish key loyalty program benchmarks across industries where loyalty programs play an indisputable role in generating significant revenue — namely, hospitality, frequent flyer programs and finance.  

 

As part of our research, we’ve selected several leading companies within each industry, carefully examining the following:

  • Loyalty program liability
  • Loyalty program point expiration
  • Loyalty program membership
  • Loyalty program revenue
  • Implementation of ASC 606 & IFRS 15
  • Program liability sensitivity

 

We start this series by taking an inside look at the hospitality industry – arguably one of the largest sectors of the loyalty program industry. Companies examined include:

 

  • Marriott International
  • Hilton Hotels
  • Hyatt Hotels
  • IHG
  • Wyndham Hotels
  • Choice Hotels
  • AccorHotels
  • Best Western International

 

We hope these insights prove valuable in guiding you towards better decision making for your loyalty program.

 

 

Loyalty program liability (a quick recap)

 

Loyalty programs are a tactic for increasing customer engagement, ultimately generating additional sources of revenue and profitability for a company.

 

However, establishing and managing these programs also generates new costs. The costs associated with future redemptions make up the loyalty program liability.  

 

Actuarial analysis can forecast your expected liabilities, redemption patterns, and ultimate breakage. This is key to prevent having too much revenue locked up in deferred revenue or liabilities.

 

Within the hospitality industry, loyalty program liabilities are typically recognized as a current or noncurrent liability. All in, these accounts represent the fair value of anticipated redemptions associated with loyalty program points issued to date.

 

Total revenue vs. loyalty program deferred revenue liabilities, 2017

CompanyTotal RevenueLoyalty Program Liability (Deferred Revenue)*
Marriott$22,894 million$4,940 million
Hilton$9,140 million$1,461 million
Hyatt$4,685 million$561 million
IHG$1,784 million$1,066 million
Wyndham$1,347 million$90 million
Choice$1,007 million$128 million
Best Western$380 million$119 million

*Restated to reflect ASC 606/IFRS 15 where necessary

 

These deferred revenue liabilities represent the potential performance obligations that may need to be satisfied in the future. While on a cash basis, the company may have already collected on these obligations, to properly account for loyalty program revenue, revenue is not recognized until these obligations are performed (i.e., the points are redeemed).

 

Generally, the larger the hospitality company, the larger their program liability. There are a few noteworthy exceptions in IHG and Best Western, where we see lower total revenue (comparatively speaking) with a significant percentage tied up in program liability.  

 

These liabilities represent a massive investment in members and, therefore, a huge opportunity to drive value for the organization. At this scale, even a small 1% improvement in the ROI on these liabilities could drive tens of millions of dollars of value creation.  For example, with Marriott’s $4.9 billion liability, a 1% improvement in the ROI would drive $49 million of value creation.

 

Of further interest is the split between current and non-current liabilities.

 

Current vs non-current liabilities for loyalty programs 2017

CompanyCurrent liabilityNon-current liability
Marriott42%58%
Hilton43%57%
Hyatt36%64%
IHG45%55%
Wyndham59%41%
Choice62%38%
Best Western33%67%
Average46%54%

 

On average, a significant piece of these performance obligations is expected to be redeemed after 12 months (the general definition of current vs. non-current liability). Therefore, accurate breakage and ultimate redemption rate forecasting is essential, otherwise current obligations may be underserved.

 

The table above is ordered from largest to smallest based on revenue, and the loyalty programs of larger companies tend to have a higher proportion of non-current liabilities. This suggests as a program grows, redemption behavior is drawn out over a longer time period.

 

 

Loyalty program point expiration

Incorporating an expiration rule into your loyalty program can incentivize members to maintain a regular cadence of activity in your program

 

The introduction of a new expiration rule many increase the uncertainty of liability and breakage estimates. However, as program expiration rules mature, member behavior can potentially be better predicted.

 

Point expiration varies by industry. It is common for credit card and frequent flyer points to be issued without an expiration rule. The hospitality industry, on the other hand, almost universally incentivizes more frequent usage.

 

Expiration policies by hotel, 2017

CompanyRequired activity period
Marriott24 months
Hilton12 months
Hyatt24 months
IHG12 months
Wyndham18 months*
Choice18 months
AccorHotels12 months
Best WesternNone

*In addition to the activity-based expiration rule, Wyndham points expire 4 years after issuance

 

Hospitality expiration policies are generally based on activity, rather than the period of time since the  points were originally earned. They typically require a minimum base activity in order to maintain points and eligibility. This can be as little as using 1 point every 12 months.

 

Hospitality program expiration rules are generally straightforward, with few caveats. They simply encourage regular participation, while not overly penalizing low activity.

 

Taking a look at the table above, about half of all programs cap their expiration rule at 12 months, with the other half expiring after 18 to 24 months.

 

We recently saw the impact of adding an expiration policy when IHG implemented a 12-month expiration policy back in April 2015. Upon recommendation from an external actuary, the implementation resulted in the releasing of $156 million from IHG’s loyalty program liability.

 

Ultimately, the decision on the ideal expiration policy for your program should be based on customer lifetime value (CLV); having a lax expiration policy can be well worth the investment if it results in better engagement and a net increase in CLV.

 

 

Loyalty program membership

 

Strong loyalty program membership can be analogous to brand clout. But it’s not necessarily indicative of a highly functioning program.

 

Loyalty program members vs total revenue as of 2017

CompanyMembersTotal 2017 Revenue
Marriott110 million$22,894 million
Hilton71 million$9,140 million
Hyatt10 million$4,685 million
AccorHotels41 million$2,099 million
IHG100 million +$1,784 million
Wyndham68 million$1,347 million
Choice35 million$1,007 million
Best Western33 million$380 million

 

It’s no surprise that loyalty program membership correlates with total revenue. Larger hospitality companies command greater market share; they simply have a larger pool from which to recruit loyalty program members.

 

Take a closer look at the numbers, however, and you’ll notice that not every chain is capitalizing on the opportunity. With only 10 million members, Hyatt appears to be underutilizing its loyalty program, when stacked against its peers. Increasing program participation appears to be an opportunity to drive revenue growth.

 

Contrarily, Best Western appears to have a very active program. Total membership exceeds or equals that of its larger peers. This may be indicative of high member engagement, or perhaps, easy program enrollment.

 

 

Loyalty program revenue

You’ve heard it again and again: loyalty programs drive customer engagement, leading to increased revenue and more profitable growth.

 

Our analysis confirms this.

 

Loyalty program member contribution, 2017

CompanyLoyalty member contribution
Hilton57% of room nights
Marriott50% of room nights
IHG43% of room revenue
Wyndham~33% of room nights
Hyatt30% of room nights
Best Western44% of room revenue

 

The companies in this table are listed by 2017 revenue, from high to low. Arranged this way, we start to see a trend: loyalty program utilization appears to correlate with higher company revenue.

 

This supports the hypothesis that loyalty programs can be a major source of untapped revenue for a hospitality company. Hotels like Hyatt and Wyndham may be able to drive stronger sales growth by improving their loyalty programs.

 

As a result, opportunity can be uncovered in the analysis of multi-year sales growth and member loyalty program utilization. The analysis could confirm a multi-year trend and provide direct evidence for the top and bottom-line improvements generated by loyalty programs.

 

 

Implementing ASC 606 & IFRS 15

 

ASC 606 was made effective for public entities in December 2017, resulting in significant changes for loyalty programs. Its counterpart, IFRS 15, drove changes internationally.

 

Compliance is now required for all public entities.

 

The ASC 606 / IFRS 15 implementation drove several key changes:

 

  • Removed inconsistencies from reporting
  • Improved the revenue recognition framework
  • Improved the comparability of revenue recognition practices across entities
  • Provided more useful financial statement information
  • Simplified financial statement preparation

 

Before the implementation of these new standards, companies employed two primary methodologies  of loyalty program accounting: the incremental cost model and the deferred revenue (i.e., “multiple-element”) model.  

 

With the change, all companies are now required to report liability using the deferred revenue model, and separate the initial transaction from the subsequent transactions, as loyalty points are redeemed.

 

Limited impact with ASC 606

Many of the US GAAP companies examined in this analysis had already been following a deferred revenue model, and therefore had little to no change in reporting. But in a few cases, companies saw an increase in deferred revenue accounts.

 

Best Western, a privately held company, has until December 2018 to adjust to the new accounting provisions. The company currently follows an incremental cost model, which will be rendered invalid by ASC 606. As is,  Best Western has not shared plans for the transition to the new accounting standards.

 

Net liabilities increase for some companies with IFRS 15

The updates required by IFRS 15 were less significant than those required by GAAP. However, this required adjustments with two of the examined hospitality companies.

 

Prior to IFRS 15, IHG accrued revenue as soon as customers earned points, and a liability was established to cover the cost of redemptions (the reimbursement IHG would pay to the hotel owners). After IFRS 15, they now defer revenue until points are redeemed, based on the standalone selling price of the value of those points to the member. The result has been a net increase in IHG’s program liabilities.

 

Similarly, AccorHotels now views its performance obligation to be unsatisfied until points are redeemed or expire. As a result, revenue associated with their loyalty program is deferred in an amount that reflects the standalone selling price of the future benefit to the member. The accounting change has driven an increase in deferred revenue and, similar to IHG, a net increase in AccorHotels’ liabilities.

 

The increase may be the result of the new fair value requirement. Previously, loyalty programs may have deferred revenue at fair value to the hotel owner. With IFRS 15, hotels must now defer revenue at fair value to the customer.

 

For example, let’s say the fair value to a customer of a free night’s stay at a hotel is $100. The hospitality company has agreed to reimburse the hotel owner $70 for a free night (often, the hotel is not fully booked, so this room likely wouldn’t have rented anyways). Before IFRS 15, the hospitality company would have a liability for the $70 they would owe the hotel owner upon redemption. Now, however, they must defer $100, and can only recognize the remaining $30 when the free night is redeemed.

 

 

Program liability sensitivity

Among loyalty programs, a major point of contention is breakage. Breakage refers to the loyalty rewards points that go unredeemed, and therefore become booked as revenue without a corresponding expense.

 

A company that estimates too much breakage will not defer enough revenue, while a company that forecasts too little breakage will defer too much revenue.

 

Should an overestimate in breakage occur, the resulting revised financial statements could show a material hit to retained earnings. Conversely, deferring too much revenue will result in “stuck revenue,” and tie up valuable funds. To avoid these reporting adjustments, it’s well worth investing in accurate breakage forecasting.

 

While disclosing breakage isn’t a reporting requirement, it’s an essential component of calculating reliable loyalty program liability.

 

You won’t find companies sharing their breakage estimates, but many do report breakage sensitivities. You can gather some directional evidence and benchmarking from how breakage estimates impact the the balance sheet:

 

CompanySensitivityTotal Loyalty Program Liability
Marriott10% decrease in breakage increases liability by $269 million$4,940 million
IHG1% decrease in breakage increases liability by $10 million$760 million
Hyatt10% decrease in breakage increases liability by $30 million$561 million

 

Generally speaking, a 10% decrease in breakage estimates can drive a 5-15% change in program liability.

 

The consequences of having to make a 10% adjustment in breakage could transform a company’s balance sheet. Solvency ratios, liquidity requirements, deferred revenue forecasts, and expense estimates may all be affected.  

 

Make sure you have a robust framework for estimating breakage.  

 

 

Applying these insights to your program

 

Customer loyalty programs are not new. Still, as you explore the world of numerical analysis, you’ll find that limited benchmarking data is available.

 

The hospitality industry is no exception.

 

Our 2017 analysis included top companies.  Future analysis may expand beyond this list.  

 

  • Marriott International
  • Hilton Hotels
  • Hyatt Hotels
  • IHG
  • Wyndham Hotels
  • Choice Hotels
  • AccorHotels
  • Best Western International

 

Compare yourself to the competition (with a grain of salt). While the exact magnitude may vary, the basic rules and trends remain. And start by asking the right questions:

 

What is our ideal breakage rate?

Does our program liability make sense?

Does our program expiration rule help or hurt us?

How does our loyalty program membership compare to that of our competition?

Do our loyalty members drive top and bottom line growth?

Is our loyalty program accounting accurate?

Are we conducting sensitivity analysis on our breakage rates?

 

If you don’t have the answer to all these questions, that’s okay. Knowing which questions to ask, along with the right benchmarks, is the first step.

 

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

 

New Revenue Recognition Standards to Reshape Liability Accounting

Quarter-end reporting can be an incredibly stressful time for any loyalty program accountant. It goes without saying that accuracy and efficiency in completing reporting requirements is of the utmost importance.  

 

Add to this the stress of fielding questions from management, completing precise and timely reporting, and ensuring adherence with the SEC and auditors, and it’s easy to see how even the most seasoned accountants can get overwhelmed.  

 

Understandably so, the balance between accurate loyalty program accounting and the proper recognition of deferred revenue has come under ever more scrutiny with the new revenue recognition standards ASC 606 and IFRS 15.

 

Compliance with the new revenue recognition standards jointly issued by the Financial Accounting Standards Board (FASB) and the International Accounting Standards Board (IASB) in 2014 is now required for public companies.

 

No matter what industry your company is in, if it generates a profit from contracts with customers, you need to change the way you account for revenue. This is especially true if your company has a loyalty program, as you’ll need to alter the way you account for program revenue and liability.

 

The impact this new standard has on your loyalty program will be felt throughout your organization: from greater revenue deferral to alterations in balance sheet liabilities, to additional disclosure obligations in your company’s financial statements.

 

Shockingly, a significant number of companies are not prepared for the major changes in accounting and business operations required by the new revenue recognition standard.

 

In this post, we’ll discuss the new standards, their improvements, how this will affect your accounting program and its estimates, and the key focus for loyalty program accountants going forward.  

 

 

A history of revenue recognition standards

GAAP

U.S. GAAP: ASC 605 and SAB 104

Prior guidance with U.S. GAAP originally fell within ASC 605, and was later modified by SAB 104: Revenue Recognition.

 

For years, ASC 605 was the only guidance for revenue reporting in the U.S. Initially, the revenue recognition guidance was nonspecific. However, it was later clarified by SEC Staff Accounting Bulletin No. 104 (which, coincidentally, was only applicable to public companies; private companies still lacked clear guidance).  

 

The revenue recognition principle from ASC 605 was simple but vague: recognize revenue once realized or realizable and earned.  

 

SAB 104 established the criteria list. When all four criteria were met, revenue could be recognized:

  1. Persuasive evidence of an arrangement exists (e.g., written contract or electronic evidence)
  2. Delivery of goods or services has been completed
  3. Seller’s price to the buyer is fixed or determinable
  4. Collectibility is reasonably assured

 

Because these guidelines offered no specifics for loyalty programs, the FASB formed an Emerging Issues Task Force (EITF) to develop guidance that led to two dominant modeling methods:

  1. The incremental cost model, where companies recognize revenue at time of purchase and a liability is recorded to cover the cost of future point redemption; and
  2. The deferred revenue / multiple element model, in which companies defer the portion of revenue directly related to the earning of loyalty points until the customer redeems them, or the points expire. The deferral amount is calculated using a fair value approach.  

 

Still, despite these piecemeal improvements, U.S. GAAP guidance had two primary shortcomings:

  1. Revenue recognition concepts remained too broad
  2. Over 200 industry-specific guidelines were excessive

 

IFRS: IFRIC 13

International accounting standards followed a more specific approach under interpretation IFRIC 13, issued in reporting year 2008. This provided guidance to entities that grant loyalty rewards points to customers that can be exchanged for goods or services.

 

While its focus was on the treatment of loyalty program liabilities, IFRIC 13 provided additional guidance for the treatment of deferred revenue by introducing two key concepts:  

  1. Deferred revenue / multiple element model:  Revenue related to the sale of a good or service is recognized immediately; revenue allocable to the value of the loyalty points must be deferred until points are either redeemed or forfeited.  
  2. Deferred revenue must be based on the fair value of points to the customer or relative fair value (this was previously optional with ASC 605).

 

In comparison to the old U.S. GAAP and IFRS standards, IFRIC 13 is more closely aligned with the new standards — though it lacks the prescriptive deferred revenue valuation.  

The new standards, summarized

For over 16 years, the IFRS and FASB have worked together to create the newly developed standards, ASC 606 and IFRS 15. Fundamentally, these new standards require companies to accurately recognize revenue as the value anticipated to be received from the transfer of goods or services.

 

This involves a five-step process:

  1. Identifying the contract with the customer
  2. Defining the performance obligations in the contract
  3. Determining the transaction price
  4. Allocating the transaction price to the performance obligations
  5. Recognizing revenue when (or as) the entity satisfies a performance obligation

 

In other words, companies will have to defer revenue for most loyalty programs.

 

This means that not only will companies that previously used the incremental cost model see later revenue recognition, but that the new model has made certain concepts of loyalty program accounting identical for both the U.S. GAAP and IFRS.

 

 

New standard ASC 606: Revenue from Contracts with Customers

Accounting Standards Codification (ASC) 606, titled “Revenue from Contracts with Customers”, became effective for public company reporting periods beginning after December 15, 2017. For 2018, the new standards are applicable and must be reported. The effective date for all other entities begins after December 15, 2018.

Objectives & improvements

The new standards aim to improve the financial reporting of revenue from contracts with customers. Previously, highly specific industry guidelines made comparability difficult, which have been simplified with ASC 606.

 

The standard now provides guidance on many transactions — specifically service transactions — that were previously lacking (non-public entities had to rely on the SEC and other entities for guidance).  

 

The new scope applies to contracts with customers, which are defined as:

“A party that has contracted with a company to obtain a good or service that is an output of the company’s ordinary activities in exchange for consideration.”

 

Exceptions include:

  • Lease Contracts
  • Insurance Contracts
  • Financial instruments

 

Goals of the new standard are more comprehensive:

  • Remove inconsistencies in revenue reporting
  • Create a more robust framework for addressing recognition issues
  • Improve comparability of revenue recognition practices across reporting entities and industries
  • Provide more useful financial statement information
  • Simplify financial statement preparation

 

Recognition & measurement guidance

This applies the new accounting standards to any business that recognizes revenue with the transfer of goods or services in exchange for consideration.  

 

Specifically, if a company enters contractual agreements with a customer (such as through a loyalty program), the company makes a promise of performance obligations. These obligations must now be accounted for separately, and quantified at an estimated or actual transaction price. As the company satisfies its performance obligations, revenue is recognized in an amount equal to the performance obligation.  

New disclosure requirements

ASC 606 requires additional disclosure obligations for customer contracts, including:

  • Revenue recognized from customer contracts (and categorized appropriately)
  • Contract balances (contract assets and liabilities)
  • Performance obligations and program rules
  • Significant judgments

 

New standard IFRS 15: Revenue from Contracts with Customers

The International Accounting Standards Board (IASB) first issued IFRS 15 Revenue from Contracts with Customers in May 2014, after collaboration with U.S. GAAP. The mandatory date for adherence was January 1, 2018. Its focus: developing a high-quality global accounting standard for revenue recognition.

Objectives & improvements

Due to the collaboration with the FASB, the IFRS 15 standard objectives are very similar to ASC 606:

  • Address inconsistencies with and weaknesses in prior standards
  • Improve inadequate disclosure requirements
  • Improve the comparability of contract revenue reporting
  • Provide more clear and comprehensive guidance for revenue recognition issues
  • Enhance disclosures for consumers of financial information

Revenue recognition model

The model establishes a thorough framework for determining when to recognize revenue and how much to recognize:  

“An entity should recognize revenue to depict the transfer of promised goods or services to customers in an amount that reflects the consideration to which the entity expects to be entitled in exchange for those goods or services.”

 

To implement this framework, companies should apply a five-step process:

  1. Identify the contract with the customer
  2. Define the performance obligations in the contract
  3. Determine the transaction price
  4. Allocate the transaction price to the performance obligations
  5. Recognize revenue when (or as) the entity satisfies a performance obligation

New disclosure requirements

In the interest of providing more relevant information to investors, additional quantitative and qualitative information is required:

  • Revenue recognized from customer contracts (and categories)
  • Contract balances (including assets and liabilities)
  • Performance obligations
  • Significant judgment in applying standards
  • Assets recognized from costs to obtain/fulfill customer contracts

 

 

How will these standards affect loyalty program liability accounting?

Breakage and Accounting Standards

For loyalty programs, the key issue becomes one of allocating revenue between the initial transaction in which the customer earned the points or rewards, and the standalone selling price of the option to acquire goods or services in the future through the redemption of the loyalty reward obligation.  The standalone selling price is representative of deferred revenue.

 

The underlying purchase and the subsequent transaction involving the redemption of points for products or services are separate performance obligations, and the recognition of revenue from those separate obligations will be separate in substance (and timing).

 

Specifically, the sum allocated to the loyalty rewards is recognized as a contract liability, and revenue will need to be deferred and recognized when the rewards are redeemed or expire.

 

Each loyalty program has different nuances. A simple method for identifying deferred revenue, on a monthly basis is reflected in the following:

Monthly Deferred Revenue = [Points earned in a month] x (1 – [continuing breakage]) x FVPP

Fair Value Per Point (FVPP) = expected fair value of each point that will be redeemed

 

While the change brought by the new revenue recognition standards might result in more short-term financial decision making, the long-term economics of loyalty programs should see no effect.  

 

 

New revenue recognition standards increase the importance of accurate breakage estimations

Determining the standalone selling price of the points or rewards necessary for compliance with the new standard can be a challenging exercise.

 

A standalone selling price is the price at which a company would sell a promised good or service separately to a customer.

 

In the context of rewards programs, determining this price will involve some degree of estimation that takes into consideration potential customer discounts, variability or changes in costs, and most critically, breakage.

 

When businesses estimate too much breakage, they fail to defer enough revenue. Conversely, when companies underestimate breakage, they will defer too much revenue and depress it more than they need to.

 

Deferring too much revenue can build up to a significant pile of “stuck revenue.”

 

Stuck revenue occurs when breakage estimates are insufficient. An excess of deferred revenue becomes “stuck”, remaining allocated in loyalty program liability accounts.

 

Only by updating breakage estimates can this be corrected. However, many companies rely on vintage-based models (e.g., join year development models) with simplistic forecasts. This leads to underestimating actual levels of breakage, potentially leaving millions in revenue locked up in liability accounts.

 

An ideal breakage estimate model incorporates:

  • Predictive analytics
  • Comparison of monthly breakage actuals versus forecasts
  • Quicker updates
  • Quantifies model estimation uncertainty

 

Don’t leave millions stuck in accounting limbo.  

 

 

Are you prepared for the new revenue recognition standards?

For companies that currently account for their loyalty reward revenues using the multiple-element model, the new standard may not change current practices all that much.

 

However, those businesses that use an incremental cost model under GAAP standards will likely see later revenue recognition for a portion of the transaction price when the new rule is applied.

 

In other words, the new revenue recognition standards will change the landscape of loyalty program accounting, reducing the amount of revenue received at the moment of transaction and making it necessary for companies to insure against the coming wave of member redemptions with reasonably estimated deferred revenue.

 

_____________________________

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

3 Things Every CFO Should Know About Loyalty Program Liability

As the captain at the helm of your company’s finances, it’s critical that you chart a course that steers clear of dangerous liabilities. Not all liabilities, however, can be averted – in fact, some are part and parcel for increasing your company’s bottom line.

 

One such necessary hazard is loyalty program liability. This liability arises from the costs incurred at the moment that a loyalty program member redeems some or all of their outstanding points. It’s a by-product of energized customer engagement. However, with high customer engagement leading to a 90% uptick in purchase frequency and 60% higher spend per transaction, it’s not a liability with which companies can afford to dispense.

 

New regulations have changed the way that accounting teams must allocate revenue to manage loyalty program liability. The principal tenet to which they will have to adhere is that separate accounting will need to be carried out for every performance obligation, and transactions with multiple performance obligations will require that the revenue for each one be logged individually. Most importantly, revenue from the issuance of loyalty points must be deferred and cannot be recognized until either the reward is redeemed, or the customer’s claim to the reward expires.

 

In the event that your colleagues in accounting fail to defer the correct amount of revenue relative to the scale of the liability, it can send your financial reports into a tailspin. Miscalculations that underestimate the amount of revenue necessary can lead to you not having enough to cover the incoming flurry of costs. Conversely, setting aside too much revenue can relegate funds to a state of financial suspended animation known as “stuck revenue.”

 

Read on to discover what every CFO needs to know about loyalty program liability.

 

 

1. These liabilities carry financial impact

Customer Loyalty

 

The financial consequences of loyalty program reward points aren’t felt just at the moment of redemption, but also at the moment at which they’re issued. Once rewards points are granted to program members, the business comes into ownership of the associated costs that accompany points that can be redeemed. Depending on the method of accounting employed by your program, these may manifest either in the form of an immediate expense recognition or as a revenue reduction.

 

Though accounting departments may fixate on current liability levels, the role of finance teams is to know how liability will develop over time. In order to accurately forecast liability levels, the finance department must be equipped with a robust understanding of the cost per point (CPP) and ultimate redemption rate (URR).

 

As the URR changes over time, failures to incorporate its fluctuations in your company’s financial planning could cause material impact to its financial outcomes. Similarly, because URR and CPP are the primary determinants of loyalty program liability, overlooking them in the development of your financial strategy could lead to the liability corroding your bottom line.

 

It’s important to avoid the pitfalls that finance leaders encounter when trying to reduce the imprint of loyalty program liability upon their income statements. One of the most common mistakes finance teams make is trying to reduce liability by driving up breakage. Breakage, or the percent of points a customer earns but does not redeem, can reduce the the strain induced by loyalty program liability. However, what it amounts to are customers opting to disengage from your company and the financial consequences that accompany the drop-off in consumer interest.

 

 

2. As your company gains loyal customers, breakage rates will decrease

brand loyalty

 

The purpose of a loyalty program is to incentivize customers to go to your company first for all of their needs related to your product line. The way it accomplishes this is by rewarding them for their business, and adding in a new variable to consider in their calculations. However, for these rewards to have value to customers, they must be worth something, and the final cost of providing them is where companies incur loyalty program liability.

 

As a result, the more engaged and loyal customers a company has, the higher its liability estimates will be. Though it might seem counterintuitive, bringing up breakage rates can take a massive toll on a company’s finances. With 20% of customers driving 80% of redemptions, increasing breakage can cause the purchasing frequency of some of the company’s most prolific shoppers to wilt.

 

Disengaging from the strongest segment of your company’s customer base will only lead to significantly-diminished returns in the long-term.

 

Instead, a more salient approach is to keep breakage moving down, while using an influx of new customers to offset its impact.

 

Another tactic is to work alongside marketing teams to find ways of driving down CPP. In this way, liability can be decreased without sacrificing desirable customer engagement.

 

 

3. Customer lifetime value (CLV) lets you know what you’re getting out of holding on to the liability

 

When it comes to loyalty program liability, CFOs should always ask themselves, “Is the juice worth the squeeze?” One useful metric for correctly answering this question is customer lifetime value (CLV). CLV takes into consideration costs borne from redemptions, as well as the revenue generated by customers throughout the course of their engagement with the company.

 

One particularly important element upon which CLV focuses is revenue. In contrast to liability, projected future revenue isn’t something you can add to a balance sheet – and that’s why there’s traditionally such an emphasis on cost. However, the goal of a liability program is to increase revenue, so that is a component that should not be left out.

 

By looking at CLV, CFOs can better contextualize their redemption rates, and better decide how to proceed appropriately. Simply stated, without a strong understanding of CLV, it’s impossible to adequately assess the health and viability of your loyalty program.

 

 

The bottom line

Loyalty program liability can have material consequences upon a company’s financial standing. However, CFOs should resist the urge to simply drive down redemption rates, and instead, employ holistic metrics such as CLV to inform their long-term strategies.

 

With careful attention paid to forecasts of customer behavior, finance teams can draft a blueprint guaranteed to keep the company in the black.

 

 

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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.

3 Things Every Accountant Should Know About Loyalty Program Liability

Ever since the roll-out of new accounting standards, ASC 606 and IRFS 15, accounting departments have had to change the ways in which they deal with loyalty program liability. The primary shift in procedure has been that accountants must now defer revenue to cover the liability upfront, and recognize it only at the point of redemption.

 

The easiest way to visualize the role of an accounting department in managing loyalty program liability is to consider the following parallel: If loyalty program liability were a fire, accountants would be the firefighters tasked with putting it out. Wielding deferred revenue as a firefighter would a hose, it’s the job of accountants to carefully select just how much to defer. If they defer too little, the flames of the liability will burn through the company’s income. Deferring too much, however, will flood the company with “stuck” revenue.

 

Fortunately, there are ways for accounting departments to correctly forecast how much revenue they’ll need to set aside in order to mitigate incoming liability without creating a trail of stuck revenue in their wake. Read on to discover the three things every accountant needs to know about accounting for loyalty program liability.

 

 

1. There are new standards to keep in mind

international accounting standards

 

The rules regarding revenue recognition have changed. In a collaborative effort between the International Accounting Standards Board (commonly known as IASB) and the Financial Accounting Standards Board (FASB), an updated method of revenue recognition has been created that eliminates discrepancies between both organizations’ guidelines. This new, conjoined set of accounting standards is known as Accounting Standards Codification (ASC) Topic 606: Contracts with Customers, or, in its short form, ASC 606/IFRS 15 Accounting Standards.

 

How will these new protocols affect Accounting for loyalty programs?

In addition to replacing a variety of prior regulations, this latest standard outlines a five-part model that’s widely considered to be more thorough and prescriptive than earlier statutes. ASC 606/IFRS 15 Accounting Standard addresses the following elements:

 

  • Contract Identification
  • Identification of Performance Obligations
  • Determining Transaction Cost
  • Allocation of Transaction Cost to Performance Obligations
  • Recognition of Revenue

 

One of the biggest changes the new standard will introduce is the elimination of viewing contracts as singular transactions. In the context of loyalty programs, this will signify that both the upfront delivery of a good or service, as well as the fulfillment of any accompanying loyalty point redemptions will be considered distinct events for which accounting must occur.

 

Moving forward, accounting departments will have to consider the performance obligation as their basic unit of account. Performance obligations are typically defined as promises by a company to confer either goods, services, or a combination thereof upon a customer.

 

How will fragmenting the performance obligations within a contract change accounting practices? Principally, it means that companies now must carry out the following:

 

  • Identify distinct performance obligations, and allocate revenue accordingly. Separate margins must be applied for each individual performance obligation identified.
  • Pinpoint the event that corresponds to the eventual recognition of revenue for every individual performance obligation. Depending on the situation, revenue will either be recognized at the point of completion, or once a given interval of time has elapsed (such as when loyal rewards expire). Which of the options will be exercised is a function of how the precipitating service or good is transferred to the client, or the exact verbiage of the governing contract.

 

Equally as important as knowing which parts of a contract to recognize separately is knowing when to recognize them. As they say, timing is everything, and under the new standard, when revenue deferred for mitigating loyalty program obligations can be recognized will be more tightly controlled.

 

 

2. Accurate breakage estimates are essential

loyalty program

 

Now that companies must defer revenue to cover the costs of incoming loyalty points, being able to correctly anticipate breakage is more important than ever. How much revenue a business must defer corresponds significantly to its predicted breakage rates, so it’s essential that accounting departments have a reliable model of how redemptions will unfold.

 

The formula below demonstrates the role of breakage in anticipating loyalty program liability:

 

Liability = Outstanding Points * (1 – Breakage) * Cost Per Point

Outstanding Points = Points that have been issued but not yet redeemed or expired

Breakage = Percent of outstanding points that will ultimately go unredeemed

Cost Per Point = Expected cost of each point that will eventually be redeemed

 

When accounting for loyalty programs, it’s important to note that deferring the wrong amount of revenue can have unfortunate results, and both over- and under-estimations of how much to set aside can place a company in peril.

 

Companies that set aside too much revenue risk setting the stage for an outcome known as “stuck revenue.” This creates an unnecessary depression in revenue, and keeps the “stuck” funds from being applied in more effective ways.

 

In contrast, deferring too little revenue can lead to companies being forced to restate their income as a consequence of not having enough tucked away to cover the incoming barrage of redemptions. Income volatility is something neither companies nor shareholders want, and it’s easily preventable by using reliable breakage models.

 

 

3. Actuarial opinions are useful for justifying booked liability

Accounting for Breakage

 

In much the same way that a company would hire a general contractor to oversee the construction of a new wing for their headquarters, so too should they consult with experts before proceeding with loyalty program accounting predicated upon an ongoing breakage assumption. While redemption rate modeling can be accomplished to a high degree of accuracy, doing so involves taking a constellation of massive, interwoven data sets into consideration and distilling  them into a lucid picture of individual-level member behaviors. Actuaries have the expertise necessary to interpret this data and mine from it the answers your company needs in order to make breakage estimates you can trust.

 

Despite the informal-sounding nature of their title, actuarial opinions must be backed up by a full-scale report featuring graphs, exhibits, and texts that outline how the actuary arrived at his/her calculations. Having a nuanced, granular-level outline of member behavior crafted by actuarial experts wielding potent AI-driven analytics software is an important step towards justifying your company’s booked liability to regulators and auditors.

 

The bottom line

The new standard will bring divergent regulations into alignment and require that companies no longer view transactions as singular contracts.

 

Instead, companies will be expected to defer revenue until all performance obligations have been met or enough time has passed to bring the outstanding liability to a point of expiration.

 

Deferring the wrong amount of revenue can lead to highly undesirable outcomes, so it’s important that your company inform its deferral decisions using breakage estimates constructed using robust, analytics software that gleans future individual-level predictions from big data. An actuarial opinion is a reliable way for your company to obtain this information, and move forward with confidence in its decisions. How will your company ensure its booked loyalty is correct?

 

 

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