Paula: Welcome to Let’s Talk Loyalty, an industry podcast for Loyalty Marketing Professionals.
Paula: I’m your host, Paula Thomas, and if you work in Loyalty Marketing, join me every week to learn the latest ideas from Loyalty Specialists around the world.
Paula: This episode is brought to you by Epsilon and their award-winning People Cloud Loyalty Solution.
Paula: Epsilon has actually just released a guide on the topic of contactless loyalty, which explores how marketeers can create human-like connections with their customers in an increasingly contactless world.
Paula: I would highly recommend you have a look, so to download the guide, visit emia.epsilon.com forward slash letstalkloyalty and you’ll find the guide in the resources section.
Paula: So welcome to episode 76 of Let’s Talk Loyalty.
Paula: And what I personally can’t believe is that we’re already coming to the end of the first month of 2021.
Paula: Now, given the unprecedented year behind us and still seems to be an unprecedented year ahead, it struck me that one of the things that a lot of listeners are probably struggling with is really managing their loyalty program liability modeling at the moment.
Paula: So there is a gentleman who’s probably very well known to many listeners by the name of Len Llaguno, who is the founder and managing partner of a company called Kyros Insights.
Paula: And he joins me on the show to talk exactly about this topic.
Paula: So Len Llaguno, welcome to Let’s Talk Loyalty.
Len: Hey, Paula, pleasure to be here.
Len: Thanks so much for having me.
Len: It’s actually Kyros Insights.
Paula: Kyros, there you go.
Paula: I’m so sorry, Kyros Insights.
Paula: I asked you that and then I got it wrong apologies.
Len: Yeah, no worries, no worries at all.
Paula: Well, and it’s a perfect segue, Len.
Paula: You will absolutely have to tell our listeners, why did you call your company Kyros Insights?
Len: Yeah, sure.
Len: Well, I took a page from how Nike named their company Nike, of Nike obviously being the Greek goddess of victory.
Len: Kyros is a Greek god of opportunity.
Len: And so I thought that would be a fitting name.
Len: We tried to take all the massive volumes of data that loyalty programs generate, which is honestly a gold mine.
Len: And create a ton of opportunity from that and extract the knowledge that can create a lot of value.
Paula: Wonderful, wonderful.
Paula: So a brilliant explanation Len, and I think you’re pretty unique in the world of loyalty.
Paula: You describe yourself first and foremost professionally as an actuary.
Paula: And I know we’re going to discuss exactly what that means.
Paula: And again, all of the kind of financial work that you do do for some amazing loyalty programs around the world, which I think give you some very useful insights.
Paula: But before we get into you and your own career and your work, as you know, we always start the show talking about our favorite loyalty statistics.
Paula: So coming from your perspective, Len, what is your favorite loyalty statistic?
Len: Yeah, I love this question because I’m a numbers guy.
Len: And so I thought long and hard around which one I wanted to bring up here.
Len: And I think I landed on this one.
Len: So what we see time and time again is the members that are gonna cost you the most in terms of redemption are worth five to 10 times more than your casual members, right?
Len: So what that means is these members certainly are gonna be the most expensive with respect to redemptions, absolutely.
Len: But they’re also your most profitable over their entire lifespan by a huge, huge margin, right?
Len: What that boils down to is, hey, don’t be afraid of redemption.
Len: Don’t be afraid of liability, right?
Len: Focus on maximizing customer lifetime value rather than minimizing costs or minimizing liability.
Len: And I think a lot of folks on this that listen to your podcast, Paula, are probably like, yeah, duh.
Len: That’s what we don’t really focus on, minimizing liability.
Len: It’s not really our goal.
Len: But we all know somebody in our organizations that thinks otherwise, right?
Len: And that’s a big barrier that I think a lot of loyalty program managers have.
Len: And a big problem that we try to solve for our customers is bring more transparency into that sort of cost-benefit trade-off.
Paula: Absolutely.
Paula: And it is extraordinary again, that you do seem to be the only kind of consulting agency that specializes in this field.
Paula: So first of all, will you tell the listeners Len, what is an actuary and what is the science that you’re applying to this whole area of loyalty program liability?
Len: Yeah, that’s great.
Len: That’s always the first question we get.
Len: Most people don’t know what an actuary is, and I don’t blame it’s a bit of an esoteric profession.
Len: So let me try to break that down a little bit.
Len: So actuaries, we’re in the profession of predicting over long horizons, and then using those predictions to inform business decisions today, right?
Len: Let me break that down and give you some tangible examples.
Len: So most actuaries work in the insurance industry or with pension plans, like 90, probably something like 90, 95% of actuaries work in those industries.
Len: And as an example, in life insurance industry, for life insurance policies, they’re issuing, life insurance companies are issuing life insurance policies today, but they’re not actually going to know the costs associated with those policies for years, decades into the future, not until people actually start dying, right?
Len: Of course, they need to be able to estimate the costs in those policies today in order to be able to run their businesses effectively.
Len: So actuaries are the ones that are doing that long-term prediction to be able to estimate those costs to inform business decisions today, right?
Len: Similarly in pensions, pensions are promising retirement benefits, right?
Len: But they’re not gonna actually know the costs of those benefits for years in the future, not until people actually retire and then subsequently die, right?
Len: So actuaries are doing that long-term prediction, right?
Len: So you sort of break that down and generalize that and what actuaries are doing.
Len: We’re making long-term predictions, right?
Len: And using that to inform business decisions today.
Len: Now, our profession, it’s a very rigorous profession.
Len: Most actuaries sacrifice the majority of their 20s to become credentialed.
Len: And what’s interesting is, consider this, insurance is a trillion-dollar industry globally.
Len: Pension is another trillion-dollar industry globally.
Len: These industries only trust actuaries to do this sort of long-term prediction exercise, right?
Len: They don’t trust accountants, they don’t trust finance folks, they don’t trust data scientists, they trust actuaries.
Len: And the reason being is, we’re the ones that are explicitly trained in the science of predicting over long horizons and managing the risks associated with those long horizons, right?
Paula: Okay, yeah.
Len: Our profession has been doing this for over 100 years.
Len: And my team here, Kyros, we’ve been basically for the past 10 plus years iterating to figure out how do we take the best of actuarial science that was developed in the insurance industry and pension industry, and figure out how to blend it with more modern day machine learning and data science and get it to work for loyalty programs.
Len: And so that’s a big part of sort of the unique thing that we’ve done and that we bring to the table is blending deep loyalty expertise with deep actuarial expertise.
Paula: Okay, so it’s kind of like a crystal ball where you’re gonna help us figure out how it’s all gonna unfold over the years to come.
Paula: Am I right?
Len: Well, yeah, I mean, in some sense, yeah.
Len: We’re trying to make these predictions.
Len: I think that one of the most important things as well, though, is it can’t be a black box.
Len: So I’ll use a bit of a different analogy.
Len: It can’t be a black box because business people need to understand sort of and be able to build a mental model of the cause and effects, right?
Len: And so a big part of what we’ve tried to do is figure out not only how to build these really predictive models and accurate models, but also how to explain it and make it transparent enough that it’s actually useful to create a lot of profit for businesses.
Paula: Absolutely.
Paula: And I know it’s always a sensitive subject, Len, and it’s been debated extensively, I would say, on the show.
Paula: It’s the whole idea of, is breakage a good thing or is it a bad thing?
Paula: So you made the point already in terms of your opening statistics, how expensive some members can be in terms of how much they’re going to redeem.
Paula: So what are you hearing, I suppose, from, I suppose particularly the finance folks that you’re talking to, which as you said, are probably more so the people who really see this as a cost rather than necessarily a good investment sometimes.
Len: Yeah, yeah.
Len: So let’s maybe I’ll preface this conversation by just saying right off the bat, I believe redemption is a good thing.
Len: I don’t think liability is bad.
Len: It’s sometimes when we get into these conversations around costs that my messaging can get lost.
Len: And I don’t want anybody to walk away from this saying, hey, Len thinks that liability is a bad thing and we shouldn’t be encouraging redemption.
Len: Far from it, right?
Len: We know that redemption is good.
Len: We know that the more people redeem, going back to my opening statistic, the more people redeem, the higher their customer lifetime value, right?
Len: And so that’s a really, really good thing.
Len: And it kind of comes back to, I don’t actually even think people should be focusing on the liability, right?
Len: Because you and I both know no good business decision has ever been made by just looking at cost, right?
Len: And liability is effectively a cost metric.
Len: You really need to look at the net economic picture, right?
Len: Which is customer lifetime value, right?
Paula: Yeah, yeah.
Len: And customer lifetime value is basically just breaking down that metric.
Len: It represents the total profit that a customer is gonna generate over their lifespan as a customer with you, right?
Paula: Sure.
Len: That includes profit to date and profit in the future, right?
Len: Or expected future profit.
Len: And we really like to focus on that expected future profit metric, because ultimately that’s what you can influence.
Len: You can influence the profit generated in the past, right?
Paula: Sure, yeah.
Len: That’s really what you need to be focusing on.
Len: And when you do that, and we can talk more about customer lifetime value and expected future profit.
Len: But coming back to your original question is, is liability good, good, or bad?
Len: When you think about it in terms of those profit terms, it’s not a bad thing at all, right?
Len: Typically, when you see a liability growing, it means that members are earning, you’re issuing points to members that have the intention to redeem them, but just have not yet had a chance to, right?
Len: And if they have an intention to redeem them, that also likely means they’re very engaged and have a really strong customer lifetime value, right?
Len: So if customer lifetime value is increasing, who cares if the liability is increasing, right?
Len: The net economic picture is a positive one, right?
Len: And focusing there is much more helpful than focusing on the liability in and of itself.
Len: So I don’t think liability is a bad thing.
Len: I don’t think loyalty programs should be scared of redemption.
Len: I will say what is bad is bad planning, right?
Len: And I think that’s where a lot of loyalty programs get into a bit of a tough spot.
Len: If you’re not planning and accounting for the loyalty program effectively and accurately, that can create some problems.
Len: And I like to use this analogy here.
Len: So, you know, you, Paula, you and I were talking about it earlier.
Len: I have a two-year-old.
Len: We’re starting to think about saving for college, right?
Len: Eight years, years from now, 16 years.
Len: Oh gosh, 16 years from now, yeah.
Len: You know, she’ll be off.
Len: Here in the United States, that’s gonna, you know, there’s forecasts it’s gonna be several hundred thousand dollars to send her to college, right?
Len: If I’m saving $5 a year, right?
Len: By the time that invoice comes, that bill comes for her tuition, it’s gonna be really, really painful because I will not have saved up enough, right?
Len: So financially, it’s really gonna be painful for me.
Len: But that doesn’t mean I shouldn’t send her to college.
Len: It doesn’t mean that’s still not a good investment.
Len: It’s just, I didn’t plan well for it.
Len: The same sort of analogy works with loyalty programs here.
Len: You’re issuing all these points that are eventually gonna cost you something.
Len: If you’re not sort of planning for it, putting the money away for it correctly, then when those costs come due, that can be really financially painful, right?
Len: You’re gonna have to find the money somewhere, and that can be financially painful for your organization.
Len: And that can often lead to cries for devaluation and whatnot, right?
Len: But none of that’s to say that you shouldn’t have given those points and it wasn’t a smart investment, right?
Len: It probably was.
Len: It’s just you didn’t plan for it correctly.
Len: So what’s bad is bad planning.
Len: Liability in and of itself is not bad.
Paula: And I will share with you something, and clearly the brand will remain nameless, but I did some market research last year, Len, and it was with them just in a couple of different countries around Africa.
Paula: And I was interviewing some very senior loyalty practitioners just to understand the market and all of that.
Paula: And I can tell you, one particular company, I’ll just say it was an airline in Africa, had no liability at all accrued.
Paula: It literally was burying its head in the sand.
Paula: I mean, I was just like, what do you mean, no liability accrued?
Paula: So talk about bad planning.
Paula: I think there’s some instances.
Paula: I mean, maybe it’s an opportunity for you to go to African and help some people like that out.
Paula: It’s unbelievable.
Len: Well, yeah, but I’ll be honest.
Len: I can understand as well why a lot of loyalty programs sort of end up in this position because loyalty program liability is absolutely the most boring parts of loyalty programs.
Len: Nobody wants to think about it.
Paula: I’m glad you said it, Len, not me.
Len: So it’s this boring compliance related thing that you absolutely have to do.
Len: It is super important for the financial health of your program, but it’s boring, right?
Len: So part of, I guess, our value proposition is we say, hey, you don’t want to deal with it.
Len: It’s boring.
Len: We actually love dealing with it.
Paula: Wonderful.
Paula: And give us a sense, Len, because I know you advise lots of amazing companies and public companies as well.
Paula: So some of these liability figures are public information.
Paula: So give us a sense of the type of numbers you’re dealing with, because as I’ve often said, like I kind of grew up in loyalty in Ireland, where we were doing it maybe in new sectors, like telecoms or different areas of business that probably wouldn’t be accruing the same kind of liabilities as an American airline, for example.
Paula: So give us a sense of what you see coming up on balance sheets.
Len: Yeah, I think it’s, for a lot of your listeners, probably staggering.
Len: So if we look at some of the bigger industries where we have like gigantic loyalty programs, American Airlines, for example, they have a liability, it’s eight billion, north of eight billion dollars with a peak.
Paula: Right?
Len: And most of the big airlines and hotel chains are all in that realm.
Len: United Airlines, like five billion, Delta is like, oh jeez, I think Delta is six billion, Marriott, six billion, you know, American Express as well.
Len: They have a huge portfolio of loyalty programs with their credit cards.
Len: They’re also north of eight billion dollars, right?
Paula: Yeah, yeah.
Len: And even if you start going down to the lower, the smaller hotel chains and smaller airlines, you’re still talking about hundreds of millions of dollars pretty easily.
Paula: Yeah, yeah.
Len: So these things can be pretty financially material, and of course at that scale, even just a small change, you’re moving millions of dollars, right?
Paula: Yes, yes, yeah.
Len: Typically, we work with a lot of big brains that have these big liabilities, because at that scale, there is a lot of incentive to be really thorough and diligent with your actuarial analytics.
Len: So some of our customers include Expedia, hotels.com, orbits.com, Radisson Rewards, Global Hotel Alliance, Samsung, what else?
Len: Hawaiian Airlines.
Len: I’m sure I’m missing a couple here.
Paula: Amazing.
Len: But even beyond that, let’s follow my team.
Len: We’ve, our experience has been working with many of the world’s largest hotel and airlines and banks over the past decade.
Len: And yeah, a lot of them, the liabilities can be quite staggering in their size.
Paula: Absolutely.
Paula: Well, I can see, and I’m very glad that you prefaced all of this by telling us how well-educated you had to be to take responsibility for these numbers.
Paula: So again, I have a sense of relief.
Paula: People are in safe hands with that going on.
Paula: I think there’s a lot of listeners as well, Len, that probably aren’t dealing with liabilities of that level.
Paula: And again, we have very much a global audience listening to this show.
Paula: And you did some great stuff recently.
Paula: I saw just like an ebook that you published, which just had some particular tactics that you highlighted as opportunities in this, to use the word unprecedented.
Paula: I think we’re all kind of not happy using that word all the time, but unfortunately we do have to account for things differently right now.
Paula: So I think you had a list.
Paula: I’m gonna just look up the title here, Len.
Paula: And just, I wanted to touch on some of the kind of practical kind of tactics that loyalty program owners could consider that actually the CFO might love.
Paula: Because again, there’s always this kind of like, different departments with the different perspectives.
Paula: We talked about, some people are looking at just cost, and some people are looking at the long-term value.
Paula: So if people are listening and they’re going, okay, we’re not going to bring in Kyros ourselves, what could we do?
Paula: And what could we learn from the work that you do?
Len: Yeah, so let me, I could maybe preface by talking about why is actuarial science useful for loyalty programs, right?
Len: We’ve talked a lot about liabilities and how we support loyalty programs with liabilities, but I think the area that’s much more interesting for loyalty marketers, because we also elaborated on how boring liabilities are.
Len: The part that’s more exciting that I think people might be more interested in leveraging is using actuarial science to understand customer longevity, right?
Paula: Yes, yeah.
Len: So maybe I can start here actually when we try to get into this and elaborate this idea.
Len: Let me ask you, Youpaul, I’ll turn the mic around and ask you, what do you think is the purpose of a loyalty program?
Paula: It’s a great question, and I probably won’t be giving you the answer that you’re looking for.
Paula: To me, it is very much a way for the brands to demonstrate to the right customers how important they are to the business, to take care of them, reward them, recognize them in a way that means they feel connected and will want to do business with the company long-term.
Len: And I think that is right, right?
Len: But I think that’s one pillar of every business decision.
Len: I think, like with everything in business, there’s multiple dimensions to it, right?
Len: And so there’s sort of the customer centricity component of it, which you, I think, very well articulated, right?
Len: But there’s also sort of a economic side of it, right?
Len: Because with any business decisions we make, we got to make sure that we understand the economics and how it fundamentally impacts the bottom line, right?
Len: So what we really focus on is the intersection of that sort of customer mindset, customer first, customer centricity with an understanding of customer lifetime value, right?
Len: Because, and that idea of customer lifetime value is sort of the commercial purpose, the way that we think about it, the commercial purpose of loyalty programs.
Len: So it’s the intersection of those two things that we believe is really, really important.
Len: We believe that the most effective loyalty programs are the ones that are doing, just sort of operating at that intersection.
Len: And so when we think about that commercial purpose, we believe that it’s all about maximizing customer longevity, right?
Len: While doing everything that you described, of course, but with the goal of maximizing customer longevity, with the goal of getting customers to come back again and again, spending more and more year after year after year after year, right?
Len: And so when you think about the commercial purpose or the economic purpose of a loyalty program in that way, and you frame it that way, you sort of recognize, you start to realize, hey, what we’re trying to do is optimize this long-term outcome, right?
Len: You’re trying to optimize customer longevity or the lifespan of a customer.
Len: And what profession is really, really good at quantifying and optimizing long-term outcomes, right?
Len: It’s actuaries, right?
Len: At least that’s what I’m trying to bring to the table here.
Len: So hopefully some other people recognize that as well.
Len: But yeah, and so the actuarials toolbox can be really good once you sort of tweak it and get it working right for this particular domain.
Len: Can be really, really useful to understand the customer longevity and understand how you might be able, what levers you can pull today to maximize it, right?
Len: And so that’s in large part what customers come to us for is they’ll say, hey, I have some long-term metric or outcome that I’m trying to optimize.
Len: And that turns out to be very, very difficult to do without the right skill set.
Len: And it really comes down to the combination of actuarial science combined with more modern day machine learning and big data.
Len: And then when you take that and you combine it with that, the rich data that every single loyalty program creates, you really create a toolbox that is very, very powerful.
Paula: So are you saying then, if I understood you right Len, are you saying that you’re able to isolate, I suppose the key levers that are driving that customer lifetime value?
Len: That’s right, yeah.
Len: And so one of the things that we try to do is we really try to study the relationship between redemption behavior and its impact on long-term longevity, right?
Len: Okay, yeah.
Len: And so when we sort of do customer lifetime value, the really important thing that we do is we predict the expected future profit that a customer is gonna generate, which of course means predicting the revenue that they’re gonna generate over a really long horizon, right?
Len: Five, six years.
Len: We also need to predict out the cost of goods sold, right?
Len: That gets you one step closer to a bottom line profit number.
Len: But then the next cost that you gotta take out, which is really unique for loyalty programs, is of course the cost of the points or the cost of the miles, right?
Len: Which is a meaningful cost for a lot of companies.
Paula: Sure.
Len: And that’s quite difficult to do, but if you can do it correctly, then suddenly you have this true bottom line number, right?
Len: That really takes into account everything, right?
Len: It sort of becomes the ultimate metric because it takes into account retention, a basket size, it takes into account redemption costs, and it takes into account customer longevity, all in a single number.
Len: It’s sort of the complete economic picture in a single number, right?
Len: And so that becomes a really, really powerful metric to be able to look at, to be able to monitor.
Len: And when you build these models in such a way where you can predict the customer lifetime value at the individual member level, that really starts helping you understand, okay, where are my opportunities to generate value?
Len: What are the levers that I can pull to actually influence this long-term outcome?
Paula: And what kind of expectations then do you have to manage in terms of increasing that customer lifetime value?
Paula: Like once, let’s say you’ve done the work, you’ve run the models, and you’ve spent a few months working with, let’s say, a new client, like what do you do then to say, okay, you can leverage these tools, I guess they hold you accountable then almost for saying, okay, this is what you’re telling us, and we’re gonna hold you for that, yeah?
Len: Yeah, I mean, so there’s a process where you don’t just put a model in and just like not look at it.
Paula: Hope for the best.
Len: Yeah, and obviously every month, you’re looking at the performance of the model and understanding what it’s saying, were the predictions accurate and that sort of thing, right?
Len: So there’s certainly a big component of monitoring and ongoing management of the model.
Len: But I think maybe what you were asking was, so you build these models now, right?
Len: What do you do with these models, right?
Len: It’s a good question.
Len: So this is a bit of a long answer, so I’ll try to make it a bit, because there’s literally so much you can do with this stuff, Paul, right?
Paula: Okay, okay, in marketing speak, what do we do?
Len: Yeah, well, so I think there’s maybe three big buckets of things that you can do, right?
Len: So there’s just pure measurement, right?
Len: So just sort of KPIs, really, really powerful for KPIs.
Len: Then there is segmentation, and then there’s scenario testing, right?
Len: So let’s talk about those three.
Len: So just from a measurement perspective, I’ll give you an example that I think might resonate a lot with your audience, which is there’s somebody in your organization, they look at the liability on the balance sheet, they see it’s, hey, it’s, let’s just say $100 million, or maybe for some of your programs, it’s $15 million.
Len: It really doesn’t matter the size.
Len: Somebody is gonna look at that and say, and freak out.
Len: And they’re gonna say, what is this?
Len: Why do we have this?
Len: Let’s devalue the program.
Len: Let’s get rid of the program altogether, right?
Paula: Yeah, yeah.
Len: You and I both know, and everybody listening knows that that’s a bad idea, right?
Paula: Sure, sure.
Len: But we all probably know somebody that thinks that way.
Paula: Yeah, of course, definitely, yeah.
Len: Customer lifetime value is a really good metric to help put that liability into context, right?
Len: Because now we can say, hey, you know, we can’t just look at the cost, the liability.
Len: We gotta look at that net picture.
Len: If we see customer lifetime value increasing over time, who cares if the liability is increasing?
Len: Economically speaking, we’re doing the right thing, right?
Len: And so from a measurement perspective, it can be really, really powerful to show the sort of value that the program’s creating.
Len: So that’s the first one.
Len: Mm-hmm.
Len: What was the next one?
Len: Segmentation.
Len: The other one there, Paula.
Len: So segmentation is really interesting.
Len: So if you really wanna do, use customer lifetime value to its full extent, you gotta be able to predict customer lifetime value at the individual member level, right?
Len: So what that means is taking everything you know about a customer and using that to predict what their expected future profit is going to be, net of redemption cost, right?
Paula: Yeah, yeah.
Len: Right?
Len: And obviously difficult to do, but that’s sort of the type of thing that we’ve seen time and time again can be incredibly powerful if you do it right, right?
Len: What you end up getting is you basically can segment your members into, I’m just gonna simplify here, three buttons, right?
Len: You can segment them into your extremely high value members, right?
Len: These are people just gonna, they love you, they’re gonna spend a ton with you.
Len: You can segment them into high growth members.
Len: These are people that may not necessarily spend a lot with you now, but you can actually, you can increase their expected future profit.
Paula: Drive that value, yeah, brilliant.
Len: Drive that value.
Len: Then there’s basically everybody else.
Len: Right.
Len: And so this is how you can use this sort of three-pronged segmentation scheme to really drive the ROI of the program.
Len: Number one is stop investing in the everybody else bucket.
Len: These are members that are just like not going to deliver the ROI.
Len: So by eliminating expense in an area that’s not going to give you the ROI will immediately improve your program performance, right?
Len: That doesn’t mean ignore them and treat them bad.
Len: It just means don’t go above and beyond for them because it’s really not going to move the economic needle.
Paula: Yeah.
Len: So that’s sort of number one.
Len: Number two is invest even more in the members where you can grow.
Paula: Absolutely.
Len: And that’s obviously going to improve the overall program performance because these are the members that are actually going to drive an ROI.
Len: Now that you can identify them, you can focus your efforts on investing in those members instead of sort of spray and pray and investing in places where you’re not going on as well.
Len: So that’s obviously a relatively straightforward.
Len: And the third bucket was your high value members.
Len: These are members that already love you.
Len: You don’t necessarily need to invest a lot in them.
Len: You just need to give them attention, right?
Len: So you can actually defend a lot of future profit by just paying extra attention to these high value members, right?
Len: What’s interesting here is most of the time, these high value members are not who you think they are, right?
Len: When we do this analysis, what we end up finding is a large share of your highest value members are hidden away in your lowest tier, right?
Len: Yeah.
Len: And so most loyalty programs don’t have an effective way of identifying who those people are and then proactively sort of engaging them, right?
Paula: Okay.
Len: The segmentation is a very, very powerful tool.
Len: EFP allows you to pull out who these people are, the high value, the high potential and everybody else, right?
Len: And then you can use that to drive program performance.
Paula: Absolutely.
Paula: So how do you isolate those people?
Paula: And I’ve mentioned it once before, in fact, a couple of times, Len.
Paula: I remember in my days in British Airways, we did have a segment called Rocket Blues, and there were indicators where we could see, and maybe airlines is a little easier, but what kind of indicators would you be looking for when it’s not pure tier status?
Paula: That’s something that’s very obvious that somebody has progressed up.
Paula: Is it the speed of engagement or what would you be looking for?
Len: Yeah, we look at everything we know that’s available about a customer.
Len: So every single loyalty program, honestly, they’re sitting on such a rich data set, because they have transactional data going back years and years and years of everything that a customer did.
Len: Every time they earn a point, there’s a transaction.
Len: Every time they redeem, there’s a transaction.
Len: Every time they expired, there’s the transaction.
Len: And so you can actually look at all of that historical data, not only their cadence of activity and their sort of earning and redemption behavior, but also what they’re buying, right?
Len: What they’re choosing to redeem on, where they’re at in their journey, all of that.
Len: And of course, if you also have demographic information like age, gender, marital status, profession, that sort of thing, that can also be helpful.
Len: But we look at that complete picture of each individual member to predict what their expected future profit is going to be, right?
Len: And that allows you a great deal of granularity between your customers and differentiation between your clusters, significantly more than if you’re just using tier, for example, right?
Len: So that’s how we can identify people that potentially are in your lowest tier that have a large expected future profit.
Paula: And basically, they need to feel the love.
Len: Yeah, they need to feel the love.
Len: I mean, they’re extremely valuable to you.
Len: They’re going to generate a lot of profit for you.
Len: So it’s worth it.
Paula: Absolutely.
Paula: Yeah.
Paula: And they’re going to be responsive because I think there’s nothing worse from, you know, my perspective or anyone listening, I think from the marketing side, you know, when you are doing, you know, a lot of work and, you know, there’s only a limited number of people responding.
Paula: So if you can isolate and focus on those, it definitely just improves the metrics, not just for the whole program, but just every single campaign.
Paula: I think you just, I guess, you’re testing and learning from each one.
Len: Yeah, exactly.
Paula: Wonderful.
Len: Paula, the last one there that we talked about, I’ll wrap up quickly here on this.
Len: I know it’s a long segment.
Len: V is scenario testing.
Len: You know…
Paula: Okay, go on.
Len: They’re always looking for levers that they can pull to optimize program performance, right?
Paula: Yeah.
Len: You got changing expiration rules, adding a new redemption partner or whatever, right?
Paula: Yeah, yeah.
Len: They’re changing tier definitions.
Len: You know, these are all things that loyalty programs are looking into.
Paula: Yeah.
Len: And you can use these models, these customer lifetime value models to help you scenario test the financial implication of these program changes.
Len: So we do this often where, well, both programs will come to us and say, hey, for example, we want to get rid of expiration rules.
Len: How is that going to impact their liability today?
Len: And how is it going to, more importantly, how is that going to impact customer lifetime value, right?
Paula: Sure.
Len: And the nice thing about it is then customer lifetime value really becomes a, again, a really good economic metric to you to help you sort of objectively decide whether or not you want to make these changes, right?
Len: Because if it grows economic lifetime value, it’s a really, really good thing, right?
Paula: Absolutely.
Len: And you can make a strong economic argument that you should be doing it.
Paula: So Len, the last thing I wanted to just go back to was this ebook that you did recently.
Paula: Again, bearing in mind the context and changing times and COVID, and we all know the story, but there’s a lot of loyalty programs and businesses, I guess, that are under a completely different framework, I suppose, in terms of what profitability might look like and how they’re going to leverage their loyalty program and again, manage that liability.
Paula: And to your point earlier, I suppose plan better for the scenarios that may come ahead.
Paula: So I’d love you to just touch on a couple of the tactics that you recommended that CFOs would love.
Paula: That I think are probably typically used for loyalty program managers, but might be particularly useful at this time.
Len: And I’m going to get into a bit of a finance lingo here, but loyalty programs are sort of remarkable businesses because they have really positive cash flow impacts, right?
Len: Because whenever you issue a point to somebody, there’s actually no cash going out at the time of issuance, right?
Len: Cash only goes out when the redemption actually happens, which could potentially be years in the future, right?
Paula: Sure, yeah.
Len: And a lot of loyalty programs today, they’re kind of struggling with a cash flow, or businesses, forget the loyalty programs, business holistically are struggling with cash flow because sort of the spigot of revenue coming in has been turned off, right?
Paula: Sure, yeah.
Len: And we’re really trying to spur that demand, and we need a mechanism that can do that without exacerbating that cash flow problem.
Len: Loyalty programs are that tool, right?
Len: And so being really generous about trying to leverage the points and use them to generate that demand makes a lot of financial sense, right?
Len: We also know that loyalty programs, that points are an incentive mechanism, right?
Len: So the more points somebody has in their account, the more likely you can use those points as an incentive to get people to come back, right?
Paula: Mm-hmm, sure.
Len: So with that backdrop, an obvious one would be, hey, let’s just not allow any points to expire during this time, right?
Len: That’s sort of a very customer-friendly, right?
Len: Which is obviously an important goal, but also makes a lot of financial sense, right?
Len: Because now you have a stronger financial incentive mechanism to get people to come back when the royalty starts to wane, right?
Len: Let’s start issuing bonus points, right?
Len: Because, again, it’s not gonna, from a cash flow perspective, not gonna hurt us, but the more points we can get in people’s accounts, the more likely, when they have demand again, they can travel again, they’re gonna come back, right?
Len: Sure, yeah.
Len: And let’s be smart about who we’re giving those points to, right?
Len: So back to that whole discussion, Paula, around segmentation, you can use EFP models to really figure out who are the members where you’re really gonna get the most bang for your buck by targeting them.
Len: And in particular, there’s another use case for these EFP models where you can actually use them to figure out who’s got the most pent-up demand, which is kind of interesting.
Len: Because you can use these models, they predicted before the pandemic how much people were gonna spend, right?
Len: Compare that to how much they actually did through the pandemic and use that metric as an idea of pent-up demand.
Len: Those are members who really should be targeting, right?
Len: Because there’s a lot of demand there that you might be able to get back.
Paula: Absolutely, yes.
Len: So those are some examples of some of the tactics we talked about in that ebook.
Len: I should also say here, Paula, one of the things that we’re doing, if people are interested in that ebook, please feel free to download it on our website.
Len: But we’re also offering free actuarial roadmaps.
Len: I know this whole actuarial comp is pretty new for loyalty marketers.
Len: There’s my outlook.
Len: I should have closed that.
Len: Apologies for that, Paula.
Len: So we’re offering these free actuarial roadmaps.
Len: I know that this whole actuarial thing is pretty new for a lot of loyalty marketers.
Len: And so this is a great opportunity for us.
Len: We’ll actually look at your program and assess sort of where you are from an actuarial standpoint today and outline a lot of the actuarial opportunities and how it can influence your business.
Len: So for any qualified programs that are interested in doing that, they can also reach out and we would love the opportunity to chat about that.
Paula: That’s super Len.
Paula: So for people listening, so if they do want to get the eBooks or the roadmap, what is the best web address, Len?
Paula: Let’s give that to listeners.
Len: Yeah, it is kyrosinsights.com.
Len: So it’s kyrosinsights.com.
Paula: Wonderful.
Paula: Okay, fantastic.
Paula: And Len, you also do training courses with our friends in the Loyalty Academy, am I right?
Len: Yeah, that’s right.
Len: Yeah, we actually do the courses on liability management.
Len: There’s two courses with the Loyalty Academy where we did those sessions.
Len: I do think the whole actuarial side of loyalty programs is not one where there’s a lot of educational content out there.
Len: And so we’re really trying to do the best we can to put content out there.
Len: I know it’s boring for a lot of folks, but it’s still important.
Len: And so between Loyalty Academy and then on our website as well, we’ve got something called the Kyros Academy where we just put out videos talking about various topics.
Paula: Wonderful.
Paula: And what you do do, Len, I will definitely say is you do make it accessible.
Paula: So I think if it was me again, running a big loyalty program, I’d be like, this guy Len is great.
Paula: And I’d be sending all my finance people over to you.
Paula: So yeah, I’d be sticking with the cool and sexy stuff on the other side.
Paula: So that’s amazing, Len.
Paula: Listen, and that’s everything I wanted to ask from my perspective.
Paula: Was there anything else that you wanted to share before we wrap up?
Len: Yeah, I guess I would just say, if you run a loyalty program and you believe that one of the main commercial purposes for the program is to improve customer longevity, that is get customers coming back again and again, year after year after year, you’re fundamentally trying to optimize a long-term outcome.
Len: And the actuarial toolbox can be really, really powerful to help you achieve that goal, right?
Len: And so if you’d love to learn more, we love talking about it.
Len: So please feel free to reach out.
Paula: Wonderful.
Paula: Listen, Len, I have learned loads.
Paula: As I said, I’m definitely going off to read all those e-books.
Paula: So I just want to say, it’s been an absolute joy talking to you and really simplifying this extremely important area of loyalty programs.
Paula: So Len Llaguno, founder and managing partner of Kyros Insights, thank you so much from Let’s Talk Loyalty.
Paula: This show is sponsored by The Wise Marketer, the world’s most popular source of loyalty marketing news, insights and research.
Paula: The Wise Marketer also offers loyalty marketing training through its Loyalty Academy, which has already certified over 170 executives in 20 countries as certified loyalty marketing professionals.
Paula: For more information, check out thewisemarketer.com and loyaltyacademy.org.
Paula: Thanks so much for listening to this episode of Let’s Talk Loyalty.
Paula: If you’d like me to send you the latest show each week, simply sign up for the show newsletter on letstalkloyalty.com, and I’ll send you the latest episode to your inbox every Thursday.
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Paula: Of course, I’d love your feedback and reviews, and thanks again for supporting the show.
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