Accurately calculating your loyalty program liability is not only critical to your company’s bottom line, but also for measuring loyalty program ROI as a whole.
To the average customer, loyalty programs simply mean getting ‘freebies’. Whether it’s points, discounts or added benefits, they’re getting something for free (or at a reduced cost). While it’s free to the customers, ultimately, rewards programs do cost someone something.
As a business, loyalty program liability is an essential factor to consider. Because, each time loyalty currency (whether points, credit or discounts) is given, you’re making a promise to provide some product or service in future. And fulfilling that promise will result in a cost to the company.
It gets tricky from an accounting perspective. Since the cost is not incurred until the customer redeems their rewards, it’s tempting to think that issuing the rewards won’t affect the present financial health of the company. But it does.
Which is where forecasting loyalty program liability comes into play.
Why forecasting loyalty program liability is challenging
The moment that you issue loyalty currency, that cost needs to be posted on the balance sheet. This cost is the loyalty program liability.
Estimating loyalty program liability is challenging because you’re trying to estimate events that may or may not occur far into the future. You can’t predict when points will be redeemed, if at all.
However, because the value of points can dramatically impact your company’s bottom line, it’s important to estimate the liability accurately. It’s common for loyalty program liability to be one of the largest on the company’s balance sheet, making it even more essential to get right. Because it plays such a pivotal role in your company’s profitability, your accountants will need to answer some tough questions about liability. That means being able to forecast redemption behaviour over a long period, and convince stakeholders that their predictions are accurate.
How to forecast loyalty program liability
While predicting the future is never easy, some tools and models can assist. Ultimately, accurately forecasting requires understanding current member behaviour and predicting future member behaviour.
Luckily, rewards programs generally generate large amounts of data. You can use this data in predictive modelling to help gather insight into how your members are engaging with your program.
Here are the key calculations that you’re going to need to form the base of your predictive modelling.
Calculate the breakage
Breakage is the percentage of points that will eventually go unredeemed. They’ll either expire or are simply never used.
- Determine the total number of points that have not been redeemed.
- Determine the total number of points issued ever, including expired points.
- Divide the total number of points that have not been redeemed by the total number of points allocated.
While unredeemed points may at first seem better for your bottom line, high breakage rates are bad for customer loyalty. They indicate that your customers aren’t engaged with your brand or your program.
Calculate the ultimate redemption rate
The ultimate redemption rate (URR) helps you to forecast how many points will ultimately be redeemed under several conditions.
There are three types of URR:
- URR on earned points – Percentage of earned points that have already, or will be, redeemed.
- URR on outstanding points – Percentage of outstanding points that will eventually be redeemed.
- Current month URR – Percentage of earned points in a given month that have already, or will be, redeemed.
Here’s an example of how to calculate URR. Let’s say you have a loyalty program with 100 outstanding points and a breakage rate of 30%. This means that the URR is 70% and that 70 of the 100 points will be redeemed.
While the number of points that will be redeemed is useful to know, it’s more important to accurately estimate the timing of point redemptions.
Predicting the timing of redemptions will 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.
To most accurately calculate the URR, you need to consider the individual behaviours of your loyalty program members. Their previous actions can help predict their future actions. Analysing these individually can help you develop forecasting databases that give insight into how likely individual point-holders are to redeem their points.
Calculate the cost per unit and fair value per unit
The cost per unit (CPP) is the expected cost of each point that will be redeemed in the future. While the fair value per point (FVPP) is the expected fair value to the customer of each point that will be redeemed.
Calculating these quantities requires you to predict what people are going to redeem their points on, and the associated cost of these redemptions.
Together with the URR, the CPP and FVPP make up the basic figures needed to calculate your loyalty program liability. These numbers provide a strong foundation for loyalty program liability budgeting with existing members.
Get your forecasting right
Accurately calculating the liability of your loyalty program is not only critical to your company’s bottom line, it’s also an important factor in measuring loyalty program ROI as a whole.