Ep. 121 | How Loyalty Programs Accelerate Recovery
This week Len Llaguno, Founder of Kyros Insights joins Allison Hartsoe in the Accelerator to talk about the long-term impact of loyalty programs. While most marketers think only about loyalty programs that keep customers coming back, Len fills the gap by thinking about the long-term value so you can have your CFO say, “Yes!”
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Allison Hartsoe: 00:00 This is the Customer Equity Accelerator. If you are a marketing executive who wants to deliver bottom-line impact by identifying and connecting with revenue-generating customers, then this is the show for you. I’m your host, Allison Hartsoe, CEO of Ambition Data. Every other week I bring you the leaders behind the customer-centric revolution who share their expert advice. Are you ready to accelerate? Then let’s go! Welcome everyone. Today’s show is about royalty program tactics to help you accelerate your business’s COVID recovery. And to help me discuss this topic is Len Llaguno. Len is the founder of Kyros Insights, which is a company that uses actuarial theory to predict redemption costs and customer lifetime value, and that helps you improve loyalty programs. Len, welcome to the show.
Len Llaguno: 00:56 Hi, great to be here. Thanks for having me.
Allison Hartsoe: 00:58 So, I imagine that most people don’t really understand what an actuary is. So when you tell us a little bit about your background, could you also help us understand what an actuary is?
Len Llaguno: 01:09 Yeah, for sure. So, I’m an actuary by training, and most people don’t know what it is as you pointed out. The stereotype is we predict when you’re going to die, which is a very, very morbid thing, of course. Right? But super important if you’re trying to price a life insurance policy or value of pension liability. Fundamentally, if you want to think about what actuaries do, we use data and professional judgment to make predictions over long horizons. And then we use those predictions to inform better business decisions. So that’s kind of what actuaries do in general. It’s in 99% of actuaries work in the insurance industry, and as you pointed out, we do not. We work with loyalty programs. So when I say loyalty programs, think of big frequent flyer programs, hotels, loyalty programs, online travel agencies, loyalty programs, credit cards, loyalty programs. I mean, you name it.
Len Llaguno: 01:51 Every single industry has some sort of program that either issuing points or miles or some type of currency to their members, whenever they buy stuff in hopes of them keep coming back. So those are our customers. So, a bit of a strange place for an actuary to be working, but it turns out that all loyalty programs have to actuarial problems that they need to solve. So, the first one is these loyalty programs are issuing points today, but those points are not going to get redeemed for years into the future. So they don’t actually know the costs of those points that they’re issuing right now. So how do you go about making smart business decisions today when you don’t know the cost of your point? Fundamentally, that’s a long-term prediction problem. And so, it’s an actuarial problem. So that’s the first problem. The second problem that loyalty programs have is predicting customer lifetime value.
Len Llaguno: 02:35 Loyalty is a long game. It’s all about improving retention and having that retention compound period after period after period after period. And so if you want to quantify the value that the loyalty program is creating and quantify it for the CFO, it’s really a matter of trying to put that compounding retention and the effect of that into dollars and cents. And so, to do that, you gotta be able to predict customer lifetime value really, really critical. And so, customer lifetime value or CLV becomes a really important metric to be able to prove that the loyalty program is actually not a cost center, which is a view that’s held by a lot of people. In fact, loyalty programs can generate a tremendous amount of value. And when you think about what customer lifetime value is, it’s again, just trying to predict over a long horizon, what that profit stream is going to look like.
Len Llaguno: 03:19 So it also is an actuarial problem. So that’s kind of how actuaries fit into the whole mix. And I’ve been working with loyalty programs for little over a decade now, and I kind of fell in love with this space because there’s so much innovation, so much room for innovation. Now I’m like insurance, where there’s like a really ingrained status quo, how things have been done for decades and decades and decades. There’s zero status quo with respect to the application of actuarial science, to customer analytics. It’s a new field, right? So, there’s a lot of room for us to be creative, a lot of room for us to innovate and contribute in meaningful ways. So yeah, to date, I’ve mostly been focused on with my customers, the finance side of the house. So, what that amounts to is really predicting redemption costs to help them manage the program liability.
Len Llaguno: 04:03 And I’m sure we’ll talk a little bit more about exactly what that is and do the financial reporting and booking of those liabilities, but also then predicting customer lifetime value to help them understand what are they getting in return for this massive liability that they have on the balance sheet. So that’s been a big part of what we do, but what I’m really excited about kind of thinking going forward from here is what we’re doing in the financial is fantastic. It’s a great work, but what gets really interesting is when you start thinking about the intersection of finance and marketing, I think that there’s something really, really interesting there. CLV doesn’t have to be just a metric for the finance org. I think it could add a lot of value for the folks sitting in marketing. And I think that’s a huge opportunity.
Allison Hartsoe: 04:42 Yeah, let’s take this from a marketer’s perspective where a marketer doesn’t typically speak actuarial language, and I want to set up my loyalty program, and I’m putting all this program, all these details together in order to help me understand how to get my customers to return when they return and sign up for my loyalty program, and maybe they spend, or maybe they take actions that I want them to do. Isn’t that a good thing? Why would I think about the liability behind a loyalty program?
Len Llaguno: 05:13 Yeah, that is a fantastic question. And maybe we could dive into this liability first and sort of describe and give some context around what that is. So, Allison, I’m sure you belong to all kinds of loyalty programs. You probably redeem points and miles for some free stuff at some point in time, and I’m sure all your listeners have as well. The question is who’s paying for all that free stuff. Somebody is at the end of the day, and it’s a loyalty program. So you can think of the point that a loyalty program issues to their members are basically like an IOU. And so every point that they’re issuing out is just one more IOU to add to the stack. And the accounting standards basically say, Hey, you got to account for that. You’re making this promise. And so you got to basically put a liability on your balance sheet for the sum of all of those IOUs and what a lot of people don’t realize is these liabilities are massive for really big programs.
Allison Hartsoe: 05:55 How massive?
Len Llaguno: 05:56 Yeah, if we go down the list, American airlines, they’re like in the $8 billion range, Delta is in the $6.7 billion, United 5 billion. Marriott’s close to 5 billion. American Express is over 8 billion. So really meaningful numbers.
Allison Hartsoe: 06:10 That’s a lot.
Len Llaguno: 06:11 Yeah, a lot of money. And well, these are exceptional programs. They’re the world’s largest loyalty programs. Massive footprints are selling tons of points. So, like these are definitely on the extreme end, but even for smaller programs, it’s not uncommon to see liabilities in the tens to hundreds of millions of dollars. At the end of the day, these redemptions are expensive. It’s a big expense. And so, when you have this sort of meaningful financial item on your balance sheet, you kind of run into this financial reporting and compliance issue. Basically, you got to convince your auditors, that liability is accurate, and that can be very difficult to do without the right training, to be able to really walk an auditor through the underlying assumptions and why they’re correct and have those assumptions take you to the liability on the balance sheet.
Allison Hartsoe: 06:50 And when you say that they’re accurate, you mean that your predictions of the redemption are accurate.
Len Llaguno: 06:55 Correct, yeah. So, in the case of American Airlines at $8 billion, you know, the auditor’s is going to say, well, how did you get there? How do we know that that number is reasonable? So, you gotta be able to produce the actuarial exhibits to back that up. Typically, the way that that works is like the auditor. Whatever the big four it is, they’ll grab one of their actuaries in house actuaries. And they’ll start analyzing the liability and looking at and saying, does this all jive? Does it make sense?
Allison Hartsoe: 07:17 This just reminds me of like a butterfly flaps its wings in Mexico. And you have to predict a tornado off the coast of New York.
Len Llaguno: 07:25 Right, yeah. Fortunately, actuarial theory is helpful. It lends itself well to being able to solve it, and you can produce the exhibits that really make the argument and show that the liability is reasonable at the end of the day. So, there is some framework here to work with, but that’s one of the reasons why people should care about the liability, right? If there are real financial reporting, compliance constraints, and challenges, but you’re going to need solve for. How would the bigger issue at play, though, is that at the end of the day, the person running the loyalty program has to make business decisions. And it’s very difficult to make more business decisions today. If you don’t know what those costs are, you don’t know how much the points that you’re issuing today are gonna eventually cost you. And if you get that wrong, you could be making awful business decisions today that will eventually catch up to you. And you could be unknowingly, accumulating a financial burden that will eventually come due. And when that does,
Allison Hartsoe: 08:11 a snowball,
Len Llaguno: 08:11 right, it could be pretty detrimental to the business. It could lead to things like program devaluations, which in turn leads to awful customer experience, terrible PR, and frankly, just destroy loyalty at the end of the day. So, it kind of defeats the whole purpose of the loyalty program.
Allison Hartsoe: 08:28 So, is that why we see, I think it was Marriott that devalued their points recently, or maybe it was one of the big companies that went through this devaluation where suddenly 5,000 points wouldn’t get you as much as you had previously purchased. So that’s why we see these devaluations come along once in a while is because these companies are carrying this huge liability from loyalty program, and they have to have a way to pass it through the books.
Len Llaguno: 08:52 Yeah, I think that’s part of it because of how a lot of companies look at it. Now you’ve got this big gigantic glaring liability on your balance sheet. And so, it’s easy to kind of just focus on costs and think, Hey, let’s cost minimize, costs minimize, cost minimize, but that’s not always the right choice. And I mean like understanding redemption costs is good in all, but the truth is that’s not good enough. No good business decisions have ever been made by just looking at cost alone. You’ve really got to look at that.
Allison Hartsoe: 09:18 Cost-cutting.
Len Llaguno: 09:18 You gotta look at that cost-benefit, trade-off, and figure out, okay, well is the cost that I’m carrying worth it? If so, then, great, let’s continue. And I think that’s an area where a lot of loyalty programs don’t have a lot of insight today. At least that’s been, my experience is really being able to credibly quantify what does the benefit that you’re getting look like and the way you do it, it’s our old friend customer lifetime value. Then I know you love the metric. I also love the metric, and that’s really the metric that’s going to bring transparency to that sort of cost-benefit, trade-off. And that’s really what we advocate for when we’re working with our customers is, Hey, like when they come to me and say, Hey, what’s the right level of breakage. You know, we’re breakages the percentage of points that are just not ever going to get redeemed.
Len Llaguno: 09:55 I said, no, no, no, no. It doesn’t matter. What really you want to be focusing on is customer lifetime value. You want to be growing customer lifetime value. That’s the real metric that you should be focusing on, but I’d say, on the whole, the industry isn’t quite there yet. They’re really just focusing, a lot of it is maybe it’s in silos. There might be some folks that are definitely thinking about value maximization, but on the finance side of the silo, you’ve got this glaring liability. There is, I think, a tendency to focus on costs and view the loyalty program as more of a cost center than a value generator. And I think that’s incorrect.
Allison Hartsoe: 10:23 Yeah. And it does it seem like it’s apples and oranges when you introduce the CLV side versus the redemption cost, is it hard for people to make that intellectual leap, that redemption costs might be the wrong way to measure a loyalty program?
Len Llaguno: 10:38 I think conceptually people are like, when you say customer lifetime value, particularly people in find it, they’re like, yeah, I get that, but that’s a good way to think about it. Right? But I think it’s more of a practical challenge. They have to quantify the costs for financial reporting purposes, but like it’s always upfront, it’s there, but you don’t have to quantify customer lifetime value. In fact, you can’t put the future value of your customers on your balance sheet. It’s just not allowed. So you’re kind of in this situation where you’ve got the costs glaring at you, but you don’t necessarily have that value that benefits the customer lifetime value piece, like staring at you as often as the cost. And I think that needs to be changed. One of the best practices we advocate for is like, let’s just never show the liability without showing customer lifetime value or the sum of customer lifetime value across all your members, which we call member equity similar to the customer equity. So, I think being able to show both of those things, transforms the discussion from loyalty as a cost to a point more as an investment in the members that delivers a benefit. And I think that’s where, where we need to go.
Allison Hartsoe: 11:33 So it doesn’t really change the reporting. So, it doesn’t really change how the reporting gets. You know, the reporting is the reporting. It’s what wall street expects, but when it comes to making smart business decisions, it gives people a broader tool set to work with when they have CLV and the redemption costs side by side. So that they’re not just sitting there saying cost.
Len Llaguno: 11:53 Exactly. I think that’s right. Yep.
Allison Hartsoe: 11:56 Okay. Let’s look at the recent COVID situation, and how that has impacted, how companies are managing this liability, especially I imagine that in the travel space, it’s anything that was projected forward suddenly has to be re-projected. And I’m also hearing that some companies are doing multiple projections trying to figure out what is actually going to be the future. How are you seeing companies relate to COVID and the way that they should be thinking about their loyalty program?
Len Llaguno: 12:24 Yeah. So, let’s start maybe with the liability and how companies are managing that. So, I would say, on the whole, unfortunately, loyalty programs aren’t like the best at predicting redemption costs. And I think one of the big reasons for that is one it’s just difficult to do that. The nature of the problems you have predict over a very long horizon, like member behavior, redemption behavior one, right. And it was just not particularly easy.
Allison Hartsoe: 12:45 Like 30 years or what is a long horizon?
Len Llaguno: 12:47 For sure. Yeah. I’ve done an analysis where I’ve seen points around 30 years ago now getting redeemed, which is, there’s not a lot, but like there’s a long tail there.
Allison Hartsoe: 12:55 Does that incentivize companies to expire them so that they can just kind of take them off the books too?
Len Llaguno: 12:59 Yeah. Companies want to expire them to be able to take them off the books. It makes things a little bit cleaner. We’re kind of seeing a bit of a reversal now where it, kind of comes and goes. Now we’re kind of seeing a bit of a rural where people are like, no, let’s make the expiration rules a little bit last, let’s relax them a little bit. Maybe even let’s get rid of them entirely. So, it kind of comes in waves, but that’s definitely part of it. But yeah, generally speaking, it’s a difficult problem. And frankly, it’s just not the exciting or sexy part of loyalty programs. Like people running loyalty programs. They want to think about customer engagement, customer experience, building relationships, emotional, all of these things, which are absolutely the right things to be thinking about. And so I don’t blame for not wanting to really focus and spend a lot of time predicting redemption costs, but unfortunately, it’s still, still, it’s boring, but it’s an important component of the business model as well.
Len Llaguno: 13:43 So what we end up seeing often is if somebody with zero actuarial training is trying to cobble together an Excel spreadsheet to try to manage a hundred million dollars or billion-dollar liability. And often this is going to be very difficult for them to kind of get it right. And I would argue not really reasonable to expect that they would without the right training and expertise. So that’s kind of been a challenge for a lot of loads for cause even pre COVID. And I think one of the challenging things is the scary part is a lot of programs don’t even realize that they’re not predicting reduction costs well because they don’t have somebody like really diving into the model and tearing it apart with the, has the appropriate experience and expertise. So, they’re not really picking up on a signal that, Hey, this may not necessarily be accurate or reasonable.
Len Llaguno: 14:24 And I think that’s kind of a challenge just from the get-go. And then now COVID comes in and blow everything else up on top of that and makes it even more difficult. So now we’re in the situation where even the best of models is like not going to do a really great job, unfortunately. And so, we kind of got to no model is going to do well. You’re in the situation where it’s inevitable. You got set assumptions. And what it comes down to is just trying to set the smartest assumptions possible. That’s frankly, the challenge and a really good practical way to do this is to recognize that not all members are created equal. They’re all going to be affected in different ways by the impact of the pandemic. And so, this is where you basically have to set different assumptions for different groups of members.
Len Llaguno: 15:02 And this is again where CLV comes back into plan’s really, really helpful. Customer lifetime value, fundamentally, is it’s a tool that allows you to predict future behavior from members. And so, it’s a tool that allows you to segment your members out into let’s just say ten groups where each group has a very distinct behavior, and then you can start setting different assumptions for each segment. And some segments are gonna be easier than others to set assumptions for. So usually on the extremes, that’s a bit easier to set assumptions, like highly engaged members. They’re probably still going to redeem their points. It’s going to be a little bit delayed. Whereas on the other end, really unengaged members, probably just going to expire all of their points. So, it’s really the middle.
Allison Hartsoe: 15:35 Or maybe find a way to get them. Because of the uncertainty, are you also updating the models more frequently than you might have in the past?
Len Llaguno: 15:42 Yeah. You have to basically like set your assumptions and then monitor them pretty frequently because the world we’re living in right now, it’s so fluid and dynamic, like you’re not going to get your assumptions, right? So, every month that goes by, you’re getting more information and learning more. So, you got to tweak those assumptions.
Allison Hartsoe: 15:56 Are you correlating them directly to the cases or deaths or like, I imagine there’s probably a sense of as cases go up, there’s a certain, I guess, depends on the industry. But if it were the travel industry, then I would immediately be thinking that as cases go up, maybe my redemptions go down. But if my business is e-commerce, maybe as cases go up, my redemptions go up.
Len Llaguno: 16:18 It varies. You got to take your professional judgment right into play to try to figure out like, what assumptions do I want to set part of it too, is you want to have stability in your estimates because particularly when you, when it comes to financial reporting, you want to be drinking the numbers around a lot from period to be quick if there’s a reasonable set of assumptions to make that suggest, Hey, over the long horizon, things are going to kind of play out in this fashion. There’s a good reason to be able to set your assumptions that way.
Allison Hartsoe: 16:42 Better to have a straight line and then some under, over to determine, okay, well, you could justify the under, over, based on this factor as opposed to moving the slope of the line over and over again.
Len Llaguno: 16:54 Yeah. So, you’d be a little bit cautious and kind of really jerking it around over time kind of waiting for more information to emerge over time.
Allison Hartsoe: 17:00 Yeah. Okay. So, we think the models are obviously wrong now cause we’re in a pandemic and we know we have to make some more assumptions about the model when we make assumptions about different segments of the population. Is it important to group them into as many buckets as possible, a small number of buckets as possible? How do you think about grouping the people to properly reflect CLV?
Len Llaguno: 17:28 Yeah. So, when you think about the customer lifetime value, the models should be at the individual member level. Um, you absolutely want them to be there, but when it comes to sort of managing underlying assumptions for financial reporting and the liability you kinda got, like you can’t set assumptions for each individual member, right?
Allison Hartsoe: 17:43 The human versus the AI, we’re not completely AI-driven yet.
Len Llaguno: 17:47 Right? So, we roll that up. And we usually as a number that like people are comfortable with nice round number. So, we’ll work with like 10, maybe 15 depending. Right. But that sort of scale and then set assumptions for each individual segments separately. Overall, what ends up happening is by setting assumptions at the segment level. Again, some are easy assumptions for others are less so, but that reduces the overall uncertainty of the assumption setting process because you are able to take advantage of some are easier to set than others. So, less uncertainty compared to if you were to just set one blanket assumption over the entire population. So that’s really, really favorable. And then the other benefit of this is when you set it at a segment level, it becomes way easier to articulate the logic behind your assumptions to say, stakeholders or auditors. And that’s a critical, critical step.
Allison Hartsoe: 18:29 I understand. Okay. So, it talks about the liability side. Let’s talk about the let’s flip over to the driving recovery driving value side. How do you think loyalty programs can be used to drive recovery?
Len Llaguno: 18:43 Yeah, so I think loyalty programs are really an incredible tool to help add momentum to the recovery. When we really internally like start seeing the recovery really, really happening the situation here with most companies is they basically revenues dropped to almost nothing, but we still have overhead and expenses. So, all that boils down to is there’s a serious crap cash crunch for a lot of companies. The nice thing about loyalty programs is they have really favorable cash flow implications, particularly in the current environment, whenever a member earns a point, there’s no cash outflow that’s happening, would that earned point? And in fact, you might actually get some cash inflow. If you’re actually selling the points, the cash outflow actually only happens at the time of redemption, which could be years into the future when hopefully, all the pandemics done and the cashflow the constraints are removed. So that suggests that loyalty programs are a really, really great tool for companies to engage with their members because they can find ways to get their members to earn points. Now they’re engaging with their members, they’re saying top of mind, and they’re not further exacerbating the cashflow problem.
Allison Hartsoe: 19:43 Smiling, because I’m also thinking that this is mutually beneficial to the customer who may be worried about their own personal cash flow and that they might be able to enjoy more benefits by spending a smaller amount and having points to redeem in the future when they might have less, or they might not have enough now. And they could use points that they’ve accrued in the past. So, in either case, the points can be reasonably well if you call it.
Len Llaguno: 20:09 Yeah, no, I think that’s a great point, right? And another reason why these points are super helpful to really accelerate the recovery when you start getting momentum in that direction, right? Because if you’re encouraging members to earn points now when the recovery really gets the momentum, they’ve got more points in their count than they would otherwise happen. That’s a really good incentive mechanism to get them come back and spend money. So, I think that’s a great point, but I think CLV comes back into play here as well. Because if we do this, we get points and members’ accounts. And then we start really seeing the recovery happening. CLV could be a great tool to be able to like prioritize how you’re going to then spend your marketing dollars. And I’ll give you two examples of how it can be useful. So first, you can use CLV model to identify pent up demand.
Len Llaguno: 20:50 So, you know, pent up demand the way we define that as basically saying, okay, before the pandemic happened, I could make it use my CLV models to make a prediction for how much somebody was going to spend. And then I can then compare that to how much they actually spent through the pandemic. And that Delta is a good proxy for pent up demand. So being able to then focus your marketing resources to try and, and your time and energy to try to engage that set of members that has really large pent up demand is probably a really good thing. You’ll probably get a really good ROI, by focusing your energy there. So that’s a really good example of how you can use CLV. And another example here is being able to use CLV models to identify which members really valued your points, where the points really do change behavior.
Len Llaguno: 21:29 For these members, it could be really, really useful to offer like rich point multiplier earn point multiplier offers to drive behavior. And the beauty of that, again, coming back to the sort of the cashless thing is when you offer earn point multipliers, the customer is still paying full freight for whatever they’re buying, but they’re getting like a perceived discount because they’re getting extra points, but there’s no cash outflow because of that perceived discount. Not yet, not until the points are redeemed. So, you’re still getting maximum cash coming in at the time of sale. And when you position that in contrast to discounts, when you give a discount, somebody gets like a discount on the price right away. And so, there’s less cash coming in right away.
Allison Hartsoe: 22:05 Yeah. I’m not a fan of discounts. And in fact, it’s a talk topic I’ve been thinking about a lot because I’ve seen things like 85% off sales that I’ve never seen before. That just makes me horrified of what they’re doing to the customer base, what they’re teaching the customers to think about. You offer that kind of discount. And I’ll wait again until you offer me another 85% like a training ground. But coming back to what you said about points, there is a school of thought in customer lifetime value that your highest value customers don’t necessarily need points. Maybe they want something that is more emotional, more special. A special floor they go to a special person that helps them a concierge, whatever the experience is. Is that also something you think about when you’re looking at your CLV splits and how to use those points?
Len Llaguno: 22:52 Oh, for sure. So, when you think about CLV, I think there are two steps to using right. Is, is, okay. CLV helps you like segment and identify the members. So, you can like pull out those high-value folks, but then there’s still another problem of saying, okay, what’s the best way to engage these people? Like what do they really want? And that’s a separate question altogether. CLV helps inform that because now, you know, how many dollars are at stake? How much you might want to invest in a certain member or whatever, but it doesn’t necessarily answer, like give him points. It doesn’t suggest that. I think you’re right. You got to cater to what they want, and their wants and needs are. And when you think about loyalty, the points, the points are probably going to be the most effective as a motivator for people that are maybe in the middle of the spectrum.
Allison Hartsoe: 23:31 That’s how I always think about it.
Len Llaguno: 23:33 Yeah. You’re going to see; we call it uplift. It’s a metric that we use, which tries to look at the derivative of CLV to point. So, you can say, okay, how does CLV change with each additional point that a person has? And you’ll see a larger derivative there for the middle-frowned folks, but a pretty low derivative for the people at the high end there, because I mean, they’re already engaged. There’s not much more motivation. You can give them; they already have a ton of points. So yeah.
Allison Hartsoe: 23:54 Right, they’re not going to act, but I mean, when you say something like that, it reminds me that the loyalty program is not a panacea. This is not something that we’re saying in order to cover from COVID. You need a good loyalty program. We’re just saying that this is part of the mix of teaching customers, how to relate to your company, rewarding them appropriately without killing your balance sheet. Correct?
Len Llaguno: 24:17 Oh, for sure. Yeah. When we approach our customers, we don’t say, Hey, of all the universe of things to do the loyalty programs, the right thing to do, we’re really saying, Hey, you’re investing billions of dollars in this program, or maybe not billions, but for some programs yeah billion into this program, let’s just make sure you’re getting the most out of it. But there’s definitely still all kinds of other things you could do for sure.
Allison Hartsoe: 24:34 But I, especially like the idea of a loyalty program creating pent up demand. I think that’s a unique feature and the idea that I’m accruing points and pushing those purchases to something in the future that I don’t know about you, but whenever I go to cash in my loyalty program for whether it’s travel or whether it’s clothing for kids or whatever, I always end up buying more than the loyalty program provides for. So there’s this push in revenue that the company is getting, not just by locking, not just by creating the points that allow you to sense pent up demand, but by also giving them a little bit more spending that they can expect in the future as they bring people back through to use something that they’ve been given because we all hate to be given something for free and then not use it.
Len Llaguno: 25:20 For sure. Yeah. Know, I think that’s right. There’s definitely a lot of lift and just getting people to come back and then you can grow, share wallet from there.
Allison Hartsoe: 25:26 So in terms of specific examples where you’ve seen companies who’ve been impacted by COVID or who have used this really well, do you have a case study or two that you want to share?
Len Llaguno: 25:35 Yeah. So, I can give a couple of examples of how these actuarial insights have been useful for helping loyalty programs make business decisions. So, we kind of touched on a little bit earlier around the exploration world. A lot of companies now are either pausing exploration. I’m thinking about relaxing exploration rules or maybe even eliminating expiration altogether. And so, a lot of companies will come to us and say, okay, well question number one. How is that going to impact my liability? Really good question to ask. It probably will increase your liability because if you let’s just say you get rid of exploration rules, it’s reasonable to expect, you’ll see more redemption. So, your liability is probably going to increase, which has all kinds of ramifications as it flows through the financial statements and whatnot. So great question to ask. It’s also going to change the cost of the points you’re issuing today. So, it’s going to change a really important assumption in lie, your business decisions today. And so that’s obviously like important to be aware of, but again, these are all costs related questions, understanding of mum’s good and all, but it’s not good enough. And it keeps saying it no good business decisions ever been made by tests, looking at costs. Right. And so, you gotta look at that.
Allison Hartsoe: 26:34 And I know we can think of a dozen examples there, right?
Len Llaguno: 26:37 Right, so here comes CLV again, a super important metric. If you really want to assess the impact of business decisions for loyalty programs, the question, if you’re changing expiration rules is, Hey, not how much does my liability increase, but how does CLV change? We know ramp Scott is going to increase, but if the amount that people are going to spend with us, if they’re going to become stickier and come back more frequently if that offsets the increase in cost, then yeah, that’s great. You should do it. It makes perfect economic sense to make that decision.
Allison Hartsoe: 27:02 The way you do that calculation is very fine-tuned to the sensitivity of what you’re trying to predict with that formula. Are you also adjusting it for the loyalty program? Like I know time is a factor that we wrestle with all the time in marketing because there’s only so much you want to take off the table when you’re predicting something like CAC to CLV ratio.
Len Llaguno: 27:20 Yeah, for sure. So, with loyalty programs, I think the CLV calculation is a little bit different from other industries or other businesses. The one thing that does share is the fact, whenever you do CLV, you want to do it at a member level. For sure. You got her a customer level. You got to get it to that granular level. That’s where you get the most value, to your point,
Allison Hartsoe: 27:38 average will kill you,
Len Llaguno: 27:39 Averages will kill you, right. So, you had a point to your point is like the horizon over which you want to predict for the context of managing liabilities in the context of managing liabilities and trying to optimize those liabilities. Usually, like a financial horizon makes a lot of sense, like two or three years, something like that makes a lot of sense in the content. If you use a CLV in other contexts, like trying to value a company like CBCV is you probably want to look over infinity until the end of time sort of timeframe. But in this context is much more practical to have a shorter timeframe, I think.
Allison Hartsoe: 28:05 I just want to call out for listeners, the reference that you made there was to customer-based corporate valuation, which is the Fader Hardy a, there’s a set of two papers you can download. I think they’re still posted over on the Wharton side or any other number of sites, but it’s customer-based corporate valuation. And that is a whole different way of using CLV.
Len Llaguno: 28:23 Yeah. Fascinating stuff that Pete Fader and Dan McCarthy are all doing with that. It’s super interesting to read everything that they’re coming out with, but yeah, in our context, it’s not tactical. Yeah. It’s a little bit different in our context while we’re trying to do so. What we find is like a more of a finite timeframe is helpful. The big difference, though, when we talk about CLV in the context of loyalty programs, is there’s an additional cost you got to take out of the equation, which is redemption costs. So usually with CLV, it’s still a profit number for other businesses, right? So you take, it looks something like projection of revenue minus cost, a good soul minus acquisition cost and you’re left with some profits. With loyalty programs, there’s another subtraction there, which is the expected future redemption costs. And that’s a really, as kind of, we’ve talked about so far are really material components of the business model.
Len Llaguno: 29:05 So you can’t forget to take that out. So, which kind of means you’ve got to be able to predict for all the points that a member is going to earn over this horizon, like how many are going to get redeemed, and how much is it going to cost you? Or in other words, you can’t really do customer lifetime value for loyalty programs, unless you’re really, really good at predicting redemption costs. So it’s all kind of tied together, but if you can do it, it becomes very, very powerful because now CLV really represents like the net picture really it’s that cost-benefit, trade-off like you’re measuring there and that’s super important.
Allison Hartsoe: 29:32 Well, not just a cost trade-off, it’s a way to measure the performance.
Len Llaguno: 29:35 Exactly. Yeah. It’s a way to put a number on it. It’s a way to kind of capture that long-term performance. And so you’re in a position when, once you do that, you can start seeing how points influence long-term profitability. And you can start seeing things like if a member had extra points, yeah, that’s going to drive more costs. But if that top-line revenue offset that increase in costs, then you’re in great shape. It really puts that into perspective.
Allison Hartsoe: 29:58 Yeah. I think that makes a lot of sense. I know there’s a lot of applications for CLV into marketing. Are there any others that you want to hit on that you think are particularly valuable when it comes to the actuarial point of view or the loyalty perspective?
Len Llaguno: 30:14 Yeah. So now I think we mentioned at the top of the hour here, that’s what’s really exciting is thinking about the intersection of finance and marketing. CLV doesn’t have to be just for finance. I think that there’s a lot of useful ways that it can be used by the marketing folks as well. In my mind, it is kind of like two main ways to think about it. One is improving retention of your current members. And then two is optimizing the acquisition of new members, right? So, let’s maybe dive.
Allison Hartsoe: 30:39 Improving the retention of the customers that you want and not losing good customers to another source, as opposed to approving improving retention of everybody, which I think waits the number unfairly.
Len Llaguno: 30:52 You hit it on the head, right? If you basically need to stratify your members and identify who are the people I care about, who are the people that are really gonna move the economic needle and that’s what CLV does. So, the benefit of that is twofold. One, you’re gonna eliminate waste because you’re not going to be spending marketing dollars on members that aren’t going to move the economic needle. That’s going to drive an ROI by itself then two, you’re focusing more of your resources and the members that will drive the economy. You’re going to get a better ROI because of that as well.
Allison Hartsoe: 31:17 Sometimes I feel like it’s a little bit of heresy when we talk about not every customer is a customer you want because there’s such an ingrained philosophy of more customers, more customers acquire, acquire, acquire, convert, convert, convert that the idea that you wouldn’t necessarily want, all those customers is you run across.
Len Llaguno: 31:34 Yeah. Oh, for sure. I think when it comes to acquisition, most companies are, for sure, focused on volume as opposed to quality. And I think, you know, I don’t blame them, right. They don’t have the tools readily available to kind of really quantify and focus on quality. It’s very difficult to do so, but I think that there’s a huge opportunity there to kind of rethink the metrics we’re trying to optimize when it comes to acquisition. When I say quality, I’m talking about no surprise here. I’m talking about customer lifetime value. So, let’s try to optimize the sum of customer lifetime value for all the members we acquired, as opposed to just the sheer number of members that we’re acquiring. As simple examples, would I rather acquire a thousand members with a CLV of a dollar for a total of a thousand dollars in value or 500 members with a CLV of $10, right? For $5,000 value, right? Which one do I care about more? From an economic perspective, I would much rather have the latter. And again, CLV allows to do that.
Allison Hartsoe: 32:27 Especially, not just from an economic perspective, but I think from a stability of business perspective, because, you know, we’ve all seen these case studies like blue apron, where they acquire, acquire, acquire, and it’s basically to get to a big pop on the exit, and it doesn’t necessarily support the health of the business as opposed to a Spotify, which looks like a very healthy business. And especially now in a time of COVID, I feel like it’s almost criminal for leaders in a company boards, investors to be pushing companies, to overspend for low-quality customers that will not allow the business to be healthy and sustainable. If COVID did anything, it’s forced us to transform to be its forced companies, to be more respectful of what has to be sustainable over time, not just spend, spend, spend until there’s new spending left, which is exactly what happened to Hertz, right? I mean, they had the private equity, lots of spending, all of a sudden there’s no more debt to be had.
Len Llaguno: 33:26 Oh, I couldn’t agree with more kind of tying that back again to our favorite customer lifetime value. You know, everything we talked about here helps bring transparency to that. But also the CBCV stuff is a great way to really kind of pull that out and say, look, some of this stuff, doesn’t make a lot of economic sense from a long-term perspective, right?
Allison Hartsoe: 33:42 I know, I know. It makes sense if you want to make a lot of money in venture capital. So, let’s see, I’m convinced. And I love the idea of looking at my loyalty programs this way. What should I do first, second, third, where should I start?
Len Llaguno: 33:57 So, you know, the exciting thing I think is every single loyalty program has the data to be able to do everything I described today. Like they’re literally sitting on a gold mine of data. So, I’d say step number one is assess your comfort level with your ability to predict redemption costs. As I mentioned earlier, most loyalty programs we find aren’t doing well. There aren’t very sophisticated and not investing a lot of energy into doing that well. So it’s a legitimate question that a company should, loyalty programs should be asking themselves, are they, what’s the implication if you’re not? And I think you’ll realize that, yeah, there’s some pretty detrimental impacts if you’re not doing that well.
Len Llaguno: 34:28 So you really should get to the point where you do feel confident that you’re doing that well, once you get that done, step two, build customer lifetime value model CLV models. Again for loyalty programs, got to make sure that if net of redemption costs super, super important, and you can’t do that, unless you’ve figured out step one first, you can’t get to the metal of redemption costs without having really good models to predict redemption costs. Once you get that done, step three is your CLV as a KPI. It’s a super important metric, brings a lot of information to the table to really assess cost-benefit, trade-off. It’s a great tool to kind of bridge the divide between finance and marketing. So just have it as a KPI to measure performance. And then step four is once it’s a KPI, you can start using the CLV models to really optimize outcomes.
Len Llaguno: 35:10 You can start optimizing retention, and you can start optimizing your acquisition strategy. And if you can do that, there’s a lot of value to be had.
Allison Hartsoe: 35:17 Yeah. Then you’re home free. That’s a great summary, Len. Now, if people want to reach you, how can they get in touch? What would be the best way?
Len Llaguno: 35:24 Yeah. So, you can reach me at I’m mostly on LinkedIn. So, Len Llaguno, last name, LLAGUNO. I think I’m the only Len Llaguno in the world. So, it’s a bit of a unique name, but I spent a lot of time on LinkedIn, or you can email me at len.llaguno@kyrosinsights.com.
Allison Hartsoe: 35:41 Now you also have an Academy program, which actually I get your newsletter. So, I thought that was a really cool thing that you launched. Do you want to talk about that program real quick?
Len Llaguno: 35:49 Yeah, sure. So, you know, there’s just not a lot of actuaries working with loyalty programs. And so, there’s just not a lot of literature or educational content on the internet about how to do the actuarial work for loyalty programs. So, we decided that we would fill that void. So we released something called the Kyros Academy, which is basically just a bunch of free e-courses where there videos that we put together that talk about all kinds of different things related to the application of actuarial theory to loyalty program. So, if you want to learn more and dive into some more of the details, please, please, please check that out. We put it together for the industry, and I hope you find it useful.
Allison Hartsoe: 36:21 That’s a wonderful feature. I’m so glad you did that because there’s just not enough information out there, especially about the angle that you’ve been talking about today. So thank you for sharing all the tips and insights about helping businesses, not just be healthier, but helping them think about their loyalty programs in ways that I’m sure they haven’t thought of before. That mathematical angle is It’s a killer if you don’t know how to get on top of it, and this is such a huge advantage for any business. So, thank you.
Len Llaguno: 36:48 Oh no, thank you. It’s been a pleasure to be here.
Allison Hartsoe: 36:50 So as always, everything we’ve discussed will be at ambitiondata.com/podcast. We’ll include the link to your programs and your link to the Kyros website. So, everybody can have a chance to get over and see the information that we talked about today. Remember everyone, when you use your data effectively. You can build customer equity. It is not magic. It’s just a very specific journey that you can follow to get results. See you next time on the customer equity accelerator.