Welcome to the second post of the Loyalty program builders podcast, where we enlist big names in the loyalty space to address the most pressing challenges of running a loyalty program business and technical.
In this episode, we talk with Lia Grimberg about how to make a loyalty program business case. It's a hot topic – with a solid loyalty program business plan, you get buy-in from your stakeholders much more quickly. And that is the ideal path to a customer loyalty program. But to arrive at the “loyal customers” stage, there’s groundwork: choosing metrics, setting goals, aligning expectations, and more.
Who is the Customer Loyalty Expert?
Thankfully, Lia knows her way around loyalty program business cases and is here to help us learn how to retain customers.
As the Principal of Radicle Loyalty, she has over 20 years of experience managing some of Canada's best-known and regarded loyalty programs – think American Express, Optimum, The Home Depot, and other popular brands.
What You Will Learn About Loyalty Program Business Cases
This episode focuses on the loyalty program business case. But we also cover vast ground, ranging from the best moment to start a loyalty program and who should be involved (spoiler: everyone) to providing value to customers who offer you data.
Lia also brings up a real case study from the grocery sector. She walks us through how loyalty data allowed her to understand customer behavior and uncover cross-opportunities – the result: higher customer retention.
And in case you missed it, we also have the key takeaways from discussing how to prepare the ideal customer loyalty strategy.
- The most significant benefit of having a customer loyalty program is generating precious data, which can give your company an edge
- Any loyalty business case includes the upside (assumptions of member growth and lift in sales) and cost (rewards, fulfillment costs, technology, consulting, and departments)
- Use cases that show quick wins and big changes to help entice the C-suite and other departments to the customer loyalty program.
- Forecasts are essential and benefit from different scenarios of customer loyalty programs: best case, worst case, most likely case.
- Suggested business case plan timeline: six to 12 months of market testing, six to 24 months to build the program, then six weeks to three months of test period.
- Customer loyalty programs should not stay siloed in the marketing department. They need participation from all sides of the organization.
- Segmentation is one of the steps to reach personalization.
- If personalization efforts are wrong, existing customers will tell you. Good efforts end up with repeat customers.
Three Actions To Start Today And Craft Your Business Case
- Picture customer loyalty programs as more than profit centers – Think how data collected through a program (current or planned) could benefit your business.
- Meet with your finance team – establish a solid three-year forecast, building different scenarios of enrollment: best case, worst case, most likely case.
- Decide on how to disseminate data and insights – include your team regularly. This has to be a continuous process since data will influence future actions.
Loyalty Program Business Cases Plan Inspiration Corner
“Loyalty programs are the lifeblood of the organization.”
“To design your program in the right way and to get proper alignment, you need to get much more specific into specific customer behavior that you're trying to influence.”
“The really big reason to have a loyalty program is data; it's investing in your existing customers, and it's investing in driving their customer behavior.”
Full Episode Transcript
The following transcript has been edited for clarity.
Irek: Welcome to the Loyalty program builders podcast, where, together with the top industry experts, we discuss the business and technical challenges of implementing and running loyalty programs.
Irek: Loyalty programs are complex. That's why, together with our guests, we make difficult processes easy to understand and provide actionable steps to reach your loyalty program goals. Subscribe to our newsletter and become a part of a community dedicated to loyalty program excellence.
Introduction – balancing data objectives with business goals
Irek: Hey, everyone. Today, we're discussing the key components of a loyalty program business case. The goal of this episode is to help you balance data objectives with business goals.
Our guest is Lia Grimberg, the principal of Radicle Loyalty, where they decode the secrets behind building customer loyalty by unleashing your data to connect with your customers on an emotional level. She has over 20 years of loyalty experience, both from a brand and consulting perspective, at organizations such as American Express, The Home Depot, Earn Miles, Loblaws, and The Bay.
Hi, Lia. It's great to have you on the podcast.
Lia: Thank you so much for having me join.
Irek: Brilliant. So, today we are going to talk about how to prepare a good loyalty program business case. I'm really excited about this one.
Lia: Hopefully, we won't be boring the people with heavy financial chat.
Loyalty programs are customer behavior goldmines
Irek: Even though I'm sure it's not going to be boring. So, let's just dive in. Let's just go with that. So, first of all, it's good to start with the “why”. Why do organizations need a loyalty program? What are the possible scenarios? What is your experience in this area?
Lia: Well, the funny thing is not everybody needs a loyalty program. And it's a misnomer that the small loyalty is absolutely driven by the Capital L loyalty program. There are many different ways of actually bringing about. Once you decide you need a loyalty program, you need to know it's a really big commitment and a really big investment.
And it's only organizations that have the buy-in from the entire C-suite and all the different departments and the investment to put behind it and the commitment to actually leverage the data that they actually need for the program. The really big reason to have a loyalty program truly is data, it's investing in your existing customers and it's investing in driving their customer behavior.
If the company is still in the acquisition of customer stages, then I would say the loyalty program is probably a bit too soon for them to start.
Irek: Okay. It's interesting because most people I know, they tend to turn towards loyalty programs as a profit center. But in fact it's about data, right?
Lia: Exactly. And once the organization decides they actually are going to be investing in loyalty, then they need to decide what role the program has to take in the organization. And for different organizations, it would have a different role. And it really doesn't matter which one you choose, so long as there is alignment across the C-suite.
There's different possibilities, it could be a profit center, meaning that it actually has to pay for itself in the behavior that it drives. You can be a loss leader. It doesn't have to. It could be a method of selling more products.
Or my best and my favorite, it's really, truly a single source of the customer behavior across all the different brand interactions. That is particularly important for an omnichannel retailer, as an example, where you have different views of the customer that are not necessarily tied to a single view of the customer, which means that you have different Lias. For instance, a different Lia interacting online, a different Lia interacting at the store, a different Lia interacting with the service department.
Whereas a loyalty program has a unique number, a unique identifier that tracks my behavior across all the different platforms and across all the different channels. That allows you to see exactly what I'm doing so that you can speak to me as a single person, rather than three different people, potentially.
But again, being a driver of customer behavior change and using loyalty as promotional is another potential way of shifting promotional dollars and vendor dollars and merchandizing promotional money into the loyalty bucket. And it also can be a way to offset profitability in that sense.
Best moment to start loyalty programs
Irek: Okay. Thank you. I'm thinking about this perspective of a person who is about to become a loyalty program manager. And basically I'm thinking about people deciding “Is it a good moment to start a loyalty program or not?” Do you have any tips, any suggestions or how to actually recognize if you are ready for a loyalty program?
Lia: I would say it has to come from both bottom up and top down. You need the entire C-suite alignment and you need to narrow down what that loyalty program is going to be doing for you and ensure that that is cascaded throughout every single department. And that “need to believe” is truly alive.
Collecting data is not enough – companies need to provide value
Irek: Okay, cool. Now, I understand that the biggest component or the best part is the data center, the loyalty program being a data center. But I know that companies struggle with using data, especially with things like personalization. It's been here forever. But I think that most companies, they overuse this term. So, what's your take on that?
Lia: Absolutely. It's been the buzzword of the last three years. And we spend so much time and so much money collecting data. And if we don't actually do anything with it, it's hugely wasteful on one hand. And it also makes our customers suspicious that we're doing something nefarious with their data because they know that their data is worth a lot of money and they think that the Big Brother is watching them.
So, it's about striking a really, really fine balance between providing value back to the customer for their data, as well as making sure that we're driving insights and using that data to drive the right kind of behavior.
But what is personalization?
Lia: Defining what personalization is unfortunately not an easy answer, and it'll be different for every brand, every loyalty program manager out there.
Personalization truly is whatever your customer defines it to be. Personalization is the how. Relevance is truly the goal.
What you're trying to do is you're trying to communicate to your whole customer base that you understand them and that you know them and that you have the right solutions to meet their needs, to meet their desires, to meet their challenges, where they're at.
And there's a fine line that we have to walk between cool and creepy. And personalization is not about just getting my name right in an email and personalization is not right is not also using a hundred dynamic fields in an email, it's somewhere in between. And you have to do a lot of surveying and a lot of testing to figure out where that balance is right for your customer.
But at the end of the day, you'll never go wrong with good offers that are relevant, with good product recommendations that are relevant, and the right content that is relevant for me to meet me where I am.
Starting personalization by listening to the customer
Irek: Oh yeah, definitely. That makes total sense. But I still haven't seen so many good examples so I don't feel really comfortable with that yet but I'm pretty sure that definitely there is so much room to experiment, to test, to improve. So, what would be your suggestion? How to start with personalization?
Lia: I would say your customers will tell you when you get it wrong. Personalization should be seamless to your customers. Personalization is really only noticed when it's done over the top or you get the algorithm wrong. Where you'll notice that personalization is done right is in the response rates that you're going to get.
If you're doing a proper test and control methodology, you're going to be able to see whether your personalization is actually driving the right kind of click throughs and more importantly, conversions. Because if your product recommendation is right on the money, it's going to drive better conversions. It'll allow you to determine what's the right level of investment at a per customer level.
And a good place to start would be to figure out what it is that you're trying, what kind of behavior you're trying to drive, for which customer segment. And then create different tests: to test product, test offer, test communication channel, test content, etc., to see what resonates.
Irek: So, I believe that it needs to start with actually the internal process in the company with a sort of an alignment. And we need to figure it out together. Like “What do we need this loyalty program for”? And then we could basically create those use cases, right?
Lia: Exactly. And you also want to make sure that you have the right technology to drive that level of automation to make it less onerous for the team to actually execute.
Aligning benefits from specific goals and use cases
Irek: Okay. So, I'm going to ask a lot of basic questions, if you don't mind. What is a good way to align the C-suite? And what is a good way to create this cross-functional team within the organization? I'm thinking about the team that really understands what the goal of the loyalty program is and what are the possibilities. What would you recommend here?
Lia: Well, my challenge is, once you figure out what the goal of the loyalty program is, it's really broad. “We want to drive sales” as a statement doesn't necessarily help you. To design your program in the right way and to get proper alignment, you need to get much more specific into specific customer behavior that you're trying to influence.
And it's about painting a picture of where you can get both quick wins and where you can truly move the dial in terms of driving that kind of behavior and closing the gap. And, as you mentioned, showcasing those use cases where you can actually drive that kind of behavior and get the entire C-suite on board and then sell it down department by department to make sure that it lives both in the front lines as well as through all the different levels of the organization.
Loyalty programs must go beyond the marketing department
Irek: Sure. I believe that loyalty programs are not only like an intellectual project of the marketing department, but it is actually something more than that.
Lia: Absolutely. It's the lifeblood of the organization. It's one of the tools in the marketing toolkit, for sure. But if it only lives in the marketing department, it is definitely going to fail.
You need to be vibrant and alive in merchandising and operations. It's very, very much in your operations because your brand ambassadors are going to be your front-line employees. They're the ones that need to be part of the program. They need to be both members and actual sales folks of the organization. They need to live it. They need to be that. They need to be able to explain it and sell it.
And it needs to be very well incorporated into the finance organization because it is a huge expense, potentially liability involved depending on who actually owns the liability for the program.
And then it's an operational and customer service exercise as well, because inevitably it will drive a lot of questions, a lot of potential problems, and even a lot of organizations don't think about it. But fraud, anti-money laundering, and anti-terrorist financing are big components of loyalty programs. Once you get to potential scale, then okay, well, definitely sounds complex and challenging.
Leveraging data to find opportunities
Irek: So, if we could maybe go back to the data a bit. First of all, companies realize that just having your own database is very important because you can't really rely on data from external sources.
I believe that there is this sort of tendency to collect meaningful information about customers. And here, I can see the loyalty program as a sort of a feedback loop between you and your customers.
But how to make sure that we actually use the data? Because I've seen companies use multiple tools collecting huge amounts of data, but not really using it in a meaningful way or even using it not to the fullest for sure. Just a part of it. So, how can we make sure to approach the data in a loyalty program?
Lia: Your data is your truly one competitive advantage. It is something that your competitors cannot duplicate under any circumstances. Everything else can be ripped off. Your data is your own data. And when I say your data, I mean primary data. They collect from transactional behavior and brand interactions with you.
And that data can be used to make better business decisions. It can be used to improve marketing, communications, customer experience, real estate operations, staffing, merchandising, pricing, you name it. It could be because it's customer-level and SKU-level. The combination allows you to make better decisions.
There's a book written, "Loyalty Leap," by Brian Pearson that was published about ten years ago or even more that talked about beer and diapers. They did an analysis and they found a high correlation of purchases, particularly in the U.S., of transactions that had beer and diapers, all in a single purchase. And after doing a little bit of analysis and a little bit of thought about it, they found that it was mostly new dads that were purchasing. And so what the insight there was that instead of hanging out with “the boys at the pub”, they now had new babies and they were drinking beer by themselves in their man cave after putting the child to bed or potentially even walking with the child.
So, what that enabled them to do is potentially position the two products necessary, not necessarily in proximity to each other, but have a little stall of one product next to each other. It allows cross-sell, it allows positioning in real estate. It allows you to figure out what hours your store should be open.
Costco uses their data to make every single warehouse different, so it's not necessarily used at an individual customer SKU level, but it's used at a warehouse level, which makes it a much more interesting scavenger hunt type of experience in every single Costco warehouse.
Irek: Cool. Cool. But is it something you learn as you go? Or is it something you plan? Let's say that you plan exactly for some certain correlation between products. What is your approach here?
Lia: You need to dig into your data and then let the data dictate what your approach will be. But what you need to be planning for is how you're going to disseminate the data on a regular basis and how are you going to collect those insights. Because without actually digging into the data and analyzing it, you're not getting any insights out of it.
So, it's a little bit of both. It's 1) how do you process and how do you disseminate and how do you strategically collect insights and share the insights? And then 2) what does the data tell you and then how do you action that data and what do you do with that as an afterthought?
Setting metrics as a way to measure success
Irek: Okay. So, how do you measure success then? Because I get that, first of all, you need to make sure that the whole company actually realizes the full potential of the loyalty program and the data that the loyalty program brings. Then we collect the data. And here, is it an “as much as we can” approach a good one or should it be different?
Lia: It's about prioritization. Where's the biggest bang for your buck and what small tweaks can you potentially make? But again, it goes back to what is the behavior that you're trying to change. Prioritize that as the first, otherwise, there's fortunately or unfortunately a myriad of insights and potential rabbit holes that you can go down on.
It's about being strategic, making sure that you know the problem you're trying to solve and where can you really make a difference with potentially small tweaks that are not necessarily going to disrupt your entire workforce?
In practice: using a three-year forecast
Irek: So, in order to be able to focus on the right things, you need to probably set certain KPIs, right? And just design those proper metrics, how do we define success in this particular program?
Lia: Exactly. Defining success is really, truly about building a proper forecast. Sit down with your finance team and establish a solid three-year forecast, building different scenarios. So, best case, worst case, most likely case. What you're trying to forecast is enrollment into your program, annual growth in members. But the truly important metric is incrementality.
When you have a loyalty program, the bulk of your program assumes you have a base program and a promotional program. For most programs, you need a base. And when I say a base, it's typically a member spends a dollar, you give them something in return. Then you have your promotional dollars that are used sporadically throughout the year.
And the majority of your base program is what we call delusionary. You're giving people money, points, value benefits, in sum, for something they would have done anyway. What you're truly trying to measure is the incrementality, meaning what can you drive over and above the person's regular behavior, what you're trying to. And that again goes back to the goal you're trying to set.
Is it spend? Is it frequency? Is it basket, etc.? And that incrementality will typically vary by the tier of the customer.
So, your best customers may have, depending on your share wallet, they may already be tapped out or they may have the best growth opportunity. Your lowest of the low engaged may not be interested at all in the program or anything.
And so you may not be interested in giving you more of their wallet. But potentially other benefits are decreases in attrition and potentially marketing channel efficiencies. Once you have a good solid three-year forecast, then it allows you to measure success because you're going back against that forecast.
See whether you're hitting the same assumptions in terms of growth, in terms of enrollment, in terms of incrementality, in terms of attrition. It allows you to gauge whether you're getting payback on your investment and it allows you to have your parameters in place of is this again a loss leader? Is this a profit center?
Establishing a business case for loyalty programs: upsides and costs
Irek: Okay, cool. So, could you perhaps give an example of a solid business case? I realize that is complex. It all depends on the industry. Depends on the company and the customers. And maybe we could also shed light on a few use cases just to use it as an example.
Lia: In any given business case for a loyalty program, you assume a number of members that would be enrolled. You assume how many of those members are going to grow, what the lift in sales is going to be and what the decrease in attrition is going to be. So, that's on the upside.
And then on the cost side, you're going to have the cost of the program, the cost of the rewards, whether it is the liability that you hold on your own or is something that you're paying a third party. Either way, there's definitely a cost.
That cost may be offset by vendor funding, in which case that is something that you could factor in. Benefit costs, you have to estimate your usage. So, let's say you offer concierge services or you offer access to a particular event. What's the cost of that event? You have to figure out what's the percentage of the loyalty rewards members have that are actually going to take up that benefit and going to use it on a regular basis.
Then you have fulfillment costs, and the fulfillment costs could be depending on whether you have actual plastic cards in the program or it could be the cost of your mobile service provider. It could be any higher costs associated with delivering the program to your customer.
Technology and consulting costs, platform cost, customer care, retail headcount as well. So, potentially technology folks, customer care folks, operations, marketing, finance strategy, if you have a separate loyalty department, and all your marketing materials, including the ones that are in physical locations, because you do want people knowing about your what.
Irek: it's quite a lot of factors to take into consideration. And do you plan all those and those as best case, worst case, most likely case scenario?
Lia: Exactly. That way you're going in with eyes wide open. It's something that your finance team should be able to handle on the forecast front and to tune up during the launch to see whether you're hitting your targets. My suggestion would be to be as conservative as possible on the upside part and be as realistic as possible on the cost side.
The timeline of planning a business case and building a program
Irek: Well, okay. So, bearing in mind the complexity of the whole process, what is the optimal timeframe for planning the business case, basically?
Lia: Yeah. You want to plan your business case, and then I strongly recommend a market test. The market test itself should be 6 to 12 months. I would say it takes probably another 6 to 24 months to build the program, depending on the complexity. And then you have your test period and your launch period, which is probably around 6 weeks to 2 to 3 months as well.
So, it's not a light undertaking. You can absolutely do it faster, particularly if you want to test a minimum viable product in the market rather than a fully blown out solution. It also matters whether you're building a program from scratch or you're just revamping and rebuilding it.
Using customer segmentation data do test and experiment
Irek: I have so many questions right now. I wanted to come back to data because I think that we haven't explored it really because, obviously, we know that there is a lot of opportunity coming from collecting your own data. There's a lot of data to collect and there are a lot of hypotheses to test.
Lia: It depends on whether you're starting with a problem in mind or an opportunity in mind. If you're starting with a problem in mind, you want to zero in on what that problem looks like.
For instance, our sales are down year over year. Okay, let's examine it. Where are the sales goin down? Are they down in a particular department? In a particular geographic location, etc.? And then more importantly, let's narrow down to the customers. Is the problem coming from new customers that we're not acquiring? Or is it coming from existing customers who started decreasing their spend? Or is the problem in retention?
Once you figure out which customer segment is driving it, then you can narrow down even more. If the problem is with retention, are we losing really big customers that actually count? Are we losing smaller dollar sales where it doesn't really matter? You narrow down, narrow down, and then you eventually come up with the hypothesis you want to test.
If you're coming from an opportunity, I like looking at customer segments by value. Recency, frequency, monetary is a good first analysis to start with. It allows you to understand who your best customers are.
More importantly, look at trends quarter over quarter, year over year, whatever makes sense for your business frequency. Understand the health of your business.
Are we seeing more upward migration of customers, meaning they're getting more engaged with respect to your brand and sales? Or are they getting less engaged? If they're getting less engaged, figure out who is going down in terms of engagement and what are the leading indicators. How do you stem disengagement and engage customers before it starts? How do you win back those on their way out?
A real case study – grocery clients outgrowing baby market
Irek: Could you share a particular case with us? At this point, we have this big picture, but I would love to dive into details.
Lia: Certainly. I had a client in the grocery space. They had a unique challenge with baby market sales declining year over year. The hypothesis was that they were losing customers, and loyalty data enabled us to understand where the problem was and what the customers were doing.
So, my team had done the analysis and broke it down. We called it the waterfall. We wanted to understand which customers were driving the impact of sales decline. So, we looked at whether they were not acquiring enough customers into the business, were they losing a lot of existing client share of the wallet, or were they truly losing clients?
Interestingly enough, within the baby category, one of the big considerations is whether the kids simply aged out of the category. If they're over the age of two or three, they're no longer considered, quote unquote, babies. The fact that it was loyalty data allowed us to see, based on all their purchases throughout the store, whether they were still within the right age group.
So, what we did was narrow down the entire universe to what we knew to be within the right age group. We found that there were problems in and around every single one of those three pillars: not acquiring enough customers, losing existing customer baskets, and losing customers.
Interestingly, we found that the biggest impact was that they were losing customers but those customers were still shopping within the store, just not within the baby department. That was an interesting insight because it allowed us to understand that it was a cross-opportunity, not a win-back opportunity.
It allowed us to understand where else in the store they were shopping - be it groceries, clothing, etc. It allowed us to create much more tailored promotions between the areas of the store where they were shopping along with the baby department. For example, "Buy X liters of milk and get X percent off diapers" as a promotion.
Irek: Cool. Amazing. Thank you for sharing that. It provides a clear context and brings the potential of the loyalty program to life. I now understand the possibilities.
Lia: It also lets you test what drives behavior. Different levers can work for different people or products. For instance, I may want dollars off commodities, while you might try something new with extra points for a new product or category.
Making the most out of AI solutions
Irek: Okay, cool. Do you see any benefits of using AI-powered solutions here? Like during creating this business case? For instance, from forecasting or figuring out approximate numbers and the potential of the program?
Lia: AI can help you figure out the various moving pieces and assumptions involved in these business cases. It can help you calculate break-even for each metric and assumption, and help you set up reasonable benchmarks for your best, worst, and most likely case scenarios.
More importantly, AI is a powerful tool for personalization. It enables multivariate testing to understand what's relevant to different segments and audiences.
Irek: Absolutely, that sounds like a crucial area for improvement. I've read in one of your blogs that segmentation is one of the steps before personalization. But often people use segmentation and call it personalization because it's a big step forward.
Lia: There's a fine line between many segments and true 1-to-1 personalization. When you have a thousand segments, it's almost like personalization. With three segments, probably not so much. It's a range or continuum.
Tips for managers creating programs
Irek: Right, that makes sense. Any tips for people trying to figure out their own loyalty program from scratch? What to do and what to avoid doing?
Lia: First, figure out if you need a program and whether it should be formal or informal. Get a good consultant to help you through all aspects, from internal operations to financials and program design. It's a big investment that should be well-incorporated into the brand and marketing toolkit. A technology partner can help bring your vision to life.
Irek: Thank you. It's been great talking to you. This is just the first of many episodes to come because I have so many questions. It would be nice if we could meet and discuss them in depth.
Lia: I'm happy to come back if you invite me.
Irek: Brilliant, it's definitely coming. If there's anything else you'd like to share with the audience, now's the time.
Lia: Thank you for listening. Find me at Radicle Loyalty.
Irek: Thank you so much, Lia.
Irek: Brilliant. I hope you found this conversation as insightful as I did. I wonder what your primary case for your loyalty program is. Drop me a line at firstname.lastname@example.org. Now it's time to close with a few housekeeping items. You'll find helpful links in the podcast description. Make sure to subscribe to our newsletter for more valuable content related to this episode and stay tuned for the next one.
Irek: Have an awesome day, everyone. The Loyalty program builders podcast is brought to you by the team at Open Loyalty, the world's most flexible loyalty software for creating personalized loyalty and gamification programs that scale.