Bill: Welcome everyone. I’m Bill Hanifin and I’m the managing editor of The Wise Marketer. And I’m here today for another episode of Wiser Loyalty Series that we’re sponsoring with Let’s Talk Loyalty courtesy of Paula Thomas.
Thanks Paula. And I’m here today with our CMO from The Wise Marketer Group, Aaron Dauphinee. Aaron, how goes it?
Aaron: That’s good. It’s a really good day here. We’re back from our travels earlier this month. And so finally able to get a little bit of rest and catch up and and finish off the series for this month on analytics.
So I’m excited about it.
Bill: This is good. You know, I love these series because we’re stretching ourselves. We’re challenging some historical beliefs or traditional beliefs in this business and. We’re kind of breaking some new ground. I really enjoyed it. So, for those of you that might be new to this series, every month in the wiser loyalty series, we focus on a course from the Loyalty Academy Curriculum, which, if you go through that curriculum, you’re in the certified loyalty marketing professional designation.
And this month we are. Focusing on course number 107, which is Introduction To Loyalty Analytics. So in every one of these episodes we pick apart some aspect of that courseware and we build on it and we kind of go deep and we offer some examples. And so in, just to give you a little bit history, we talked about the sources of data.
Sources of data. Where does data come from? We talked about analytical approaches, you know, the different types of analytical models that are in play and what their outcomes are. And then we talked, we went deep on 0 party data. And so today we are going to give you some market examples that we talk about.
Some brands are doing a really good job with data and the types of just some types of outcomes that you can experience. So, Aaron’s going to get us started have a fun conversation about some of the good, bad and ugly in the way brands are using data today.
Aaron: Yeah, no, I think I mean, maybe not so much good, bad and the ugly, but a little bit of two to the from for context.
So, yeah, when I think, and I think way back Rusty reference to some Canadian jobs, but I can agree there. But I think way back to Tesco in 1995. When they launched their Tesco club card program, you know, for those of you not familiar, UK based grocery chain. There were some of the first that really started to use data analytics in a savvy way, right?
And so this was well before internet shopping even existed and it didn’t have the ability to collect their data online at a click of the button. So they needed this reward schema called Tesco club card to kind of. Bring things through where, you know, each transaction the customer carried out, they’d present their card, they’d earn some points for in store spend, and then an exchange value came into play where Tesco collected a record on that associate and then and the customer’s name and postcode, and then by virtue of that, was able to send them tailored coupons and offers to nudge their behavior, right?
They rewarded the high end of the file with that spent more and encouraged some casual customers to engage more with the store, but by and large, It was a very strong success early on, you know, within months of launching, I think, and this is you know, it’s been a while since I thought about Tesco, but, you know, they were spending upwards of four or 5 percent more than non club card customers.
So it really started to change the way in which they looked at their customer file to say, hey, we’re going to engage those who are on the card. And we’re going to utilize the detailed data that we have about their buying habits, their favorite products and so on and make some adjustments in terms of how we provide relevancy in terms of the offers for that particular client set.
So it’s just 1 of those things I mentioned. That’s kind of 30 years ago. That’s where we’re at, right? In terms of, we used to think of Tesco is kind of a, you know, a bit of a master class and where we’re at. And now you fast forward. To today’s world where something completely different industry, so not retail, not travel, like outside of the typical of loyalty, that’s getting into utilizing data to provide relevancy.
And I think of what’s on my phone all the time that I use every single day, which is Spotify, right? Spotify doesn’t have a formalized program, but they are collecting and utilizing data and using utilizing loyalty mechanics. To apply and create experiences for their members that are part of the subscription for Spotify.
And I think of the campaign that they’ve done for a number of years, which is Spotify Raps, right? It’s a great example of utilizing data insights on musical tastes for your, from your customer file to do a little bit of a summary at the end of the year that says, Hey, here’s a bunch of stats on what music you consumed over the course of the year.
Your top artists are this. It’s your top genre is this here’s, you know, here’s your favorite songs that you listen to most. And so just taking that and making it personalized, and I guess in some instances we can even say hyper personalize, you know, there’s some question about whether or not that’s a good or bad term right now, but the point for me is less about personalization and more about relevancy.
Cause you’re summarizing for me what’s there in terms of my usage of data. And now saying, hey, share this out. And so you get this now spiraling campaign in the social world that says, hey, here’s a summary of who I am as an individual that you can put out into the marketplace with your friends and stuff like that.
And so Spotify knows a lot by virtue of the consumption that you have through their program. And so. I think Spotify Wrap is just like an extreme example that uses data analytics to tell users, you know, if the band that they’re following is, sorry, if one of the bands that their most loyal followers are following is playing nearby, they can start to then push that through to me in terms of connections through the partnerships that they have with ticket producers and stuff as well too.
So just kind of to kick off kind of thoughts of to from a little bit. I don’t know, what about your thoughts in terms of programs you like?
Bill: I love that little tag on to the Tesco stories that I had the opportunity to listen to Clive Humby speak years ago, and he was actually very humble. He said, everybody thinks we’re brilliant.
And what we’re doing is we’re just, and this is before machine learning was really available or being applied. He said, we just run through as many offers as we can. We fail a lot and we wait and see where the patterns start to pop up. And then we dig in on those patterns. And so, you Yeah, now we can do it with a lot more precision, but I think one of the things about data is, and the illustration you just gave us is, what are the outcomes?
So, when we talk about hyper personalization, we were looking for brands that are doing a good job. And I think it’s, I think it’s people have a yearning to say, I’m giving you data. I want you to demonstrate that you’re doing something positive with it. And it could mean, you know, it’s not always offer delivery.
So, people think about just jingle in the pocket and money. Offers discounts that is an element of it. Absolutely. But maybe the more powerful part is even just demonstration of that. You know, me, you know, me 100 percent remember who I am. You actually are tailoring some of your information to me.
Yeah, according to my interest, my express interest. The other thing is that you’re saving me time. You’re giving me convenience and ease in my life. You’re so called like relevant is 1 of those overused terms, but you’re truly relevancy. And I think you’ve got a brand example about relevancy for sure.
So, I mean, maybe we could jump into a couple of examples, like how is the use of data with some of these brands making the loyalty program actually relevant to what you’re doing day in and day out.
Aaron: Yeah, and I think I, and I, the loyalty program itself or a customer program, and I want to be more general about that too, because it doesn’t have to have all of the traditional mechanics of loyalty, but just that you’re collecting information on your customer file and providing relevancy back.
And there I go, using relevancy back again. It’s just, it’s in my vernacular. I love it so much but I liked where you’re setting. It’s not to say, Okay. Providing things that are helpful and that I need, right? And so I think about a health company that we have they’re called Hinge Health, right?
And there’s an adage, I think I read this somewhere there was a quote like from REM, everybody hurts sometimes. Well, what Hinge Health is doing through their virtual physical therapy program is really, it’s taking a look at a new approach of how their app, that has personalized care within it can help reduce the need for unnecessary surgeries and also the use of opioids, right?
So it’s really putting a mind focus on the individual’s health through their, through the app that they have. And so the individuals sign up through the app, they get a tailored, personalized care. physical therapist or and a health coach. They get personalized messages that are sent to them. They get a treatment progress.
They get a bunch of exercises that match through to where their readiness is relative to where their health is at that a given point in their journey or recovery time. And then they’ve made it in a way that, you know, involves deep engagement, aka gamification to some degree, where, you know, individuals can earn points to unlock the next level of a new exercise, or they can win supplies.
It’s like yoga mats or bands or weights and stuff like that. And so it’s really quite cool, quite frankly, in terms of how they’re collecting information assessing it, you know, in, in a world where the individual doesn’t have to go into a physical therapy office, right? You know, that to your point of that doesn’t save people time.
You know, there’s costs associated with that. There’s often lack of motivation to go into a public space to, you know, get into your shorts and you’re sure to exercise publicly when you’re hurting, right? And maybe in your prime physical health, you’re okay going to the gym but you don’t want to be doing it when you’re hurting.
So, here, you can do it through the app and do it at home and still have the same type of care and coverage. That makes sense in a real time fashion. So I just thought that was kind of a cool example.
Bill: No, it’s a really good 1. and I’ll tell you where something I’ve seen lately. Maybe gets into the convenience area and ease and just relevancy, but I don’t know if you’ve seen this and I’m sure it’ll start to become prevalent.
But I was on a Delta flight recently and they had a notice on the screen. When I turned on the entertainment console, it said, turn your panel into a smart TV. And I thought, oh, that’s a good curiosity hook right there. So, QR code with your phone. You would log into your Delta SkyMiles account, and now the TV knew exactly who you were, it populated my name, said thanks had some information about my status, and here’s the best part, usually I skip watching movies on short flights because I know I can never finish them, but one of the things it said is, you can pause your movie, and when you get on the next flight, and when you activate your smart TV again, it’ll pick up exactly in that spot.
So you can continue watching that movie and. You’re kidding me. This is awesome. So now 290 minute flights turned out. I could actually watch this movie that I wanted to and I’m sure they are just scratching the surface because they’re going to be so I started right away. My mind was spinning. What other things could they do with this?
But it makes the flight like, I’m in my seat and I’m at home and I’m at and it’s convenient. It’s fun. It just, it starts to change the travel experience and the better way that I’ve been hoping for a long time.
Aaron: Yeah, I know. And I’ve seen some changes on the carrier that I’m homegrown to here at Air Canada, where recently in their app, they’ve had a affiliation with one of the telcos here in Canada that you could do text screening and that for free when you sign in and you just Put your seat in and whatnot.
But recently, they’ve actually now gone the further step to say for those who are at 75 K or 100 K, which is their top two status tiers. You can now log in through your through just putting your seat and you don’t have to go through and log in through your the full mechanism of the app and made. And so that’s a time saving made make convenient because.
The assessing to get on to the Wi Fi when you’re on the plane has not been the easiest pursuit, and sometimes it hangs and it holds, and so now having to not switch between two or three screens to get to actually having access to the internet because you’re a top tier member by just putting your last name and seat number in is a big convenience, but I love that connection.
And because we’ve seen that in travel, I guess, too, right? We think about the hotels with their digital keys like that. They started down that path in terms of making it easier like Hilton’s and Marriott both have digital keys and other hotel chains as well to Renaissance and et cetera and so forth. IHG as well.
You know, there’s mobile. Smartphone keys are helpful in terms of having a one device to kind of let you in and then utilize that for your for the TVs. It’s a smart TV and stuff. And you have all this information that you’re collecting about the customer, but I haven’t seen them extend that into any real significant uses beyond that.
It’s kind of been latent. And so now we see that the airlines coming in and starting to make the connection. Maybe there’ll be a push to kind of quote unquote, no pun intended unlock more from the digital key.
Bill: That’s great. So, so, back to the jingle in the pocket, because we love relevancy. We love ease and convenience.
We love to save time, but we also everybody’s money motivated. Aren’t they? So there’s this element. Also, what you can do with data. That’s so powerful in the area of dynamic pricing. Can you. We’re getting to the, to our time, but maybe can you give a quick synopsis of the dynamic pricing and maybe how it works well and when it might not work so well?
Aaron: Yeah, I mean, there’s a ton of examples of people playing with dynamic pricing. And I think the one that I always go to that’s been longstanding has been Amazon, right? So we’ve known this for, I mean, airlines have always been doing it as a selling tactic to purchase tickets for a long time.
But when I go into the retail space of really who’s been savvy about this. For a long time because of the e commerce platform and then migrated into the retail footprint offline afterwards with whole foods, like, they have so much information that they’ve collected and they’ve got to the point where I recall in a conversation once I think it’s anecdotal, but it’s probably fairly true.
So I’ll reiterate it anyway. That they were saying that Amazon sophistication on actually giving you preferences and knowing what it is that you want relative to the pricing was so far ahead that they had to actually throttle it back because it was going to that too creepy line where people were like, Hey, how did I, how did you know this?
And they created a system where they put a bit of a governor on it in early days. I don’t know where that’s, if that governor is still in effect now is. As it’s more of an expectation because and it shouldn’t have to be, I mean, on that front with dynamic pricing. I think there’s the 2 things.
1 if you’re utilizing the data and from a variety of sources, and you’re providing me with products and services at a price point, that is going to hit for me. I’m going to be happy with that because that’s the relevancy. That’s you’re meeting my needs. That’s what I seek. If you’re missing on it, though.
And it’s fairly clear that it’s a sophisticated algorithm to know that it’s going to raise an eyebrow. Right? And I’m going to be like, wait now. I don’t like that. So the real critical thing to think about here as you’re utilizing this data, and it’s easier said than done. I recognize I’m not trying to be sit from an ivory tower here is that you have to get it right.
And so the test and learn model. You know, sometimes, you know, isn’t as free as it used to be when we’re starting to integrate a bunch of other different analytics sources. But if you’re getting it relevant and you’re not creating an environment where I’m sitting at home as a member of Amazon prime.
My partner’s beside me doing something similar to search for the same things because, you know, we both realized we’re out of toothpaste and tp. And then all of a sudden the price point’s different for me than it is for that for my partner. Like that raises some eyebrows maybe on everyday products.
It’s not the end of the world, but if you’re, imagine if you’re planning for a. Right. And your price, you know, doing sorts and one one’s doing it through the airline app and another one’s doing it on Expedia or another travel consolidator. You know, and the price points come up very differently.
Like, you got to ask yourself a question there. What’s going on? So, anyway, total tangent, but a little bit past dynamic pricing into a little bit more of the realities of relevance.
Bill: It’s pretty clear to me, Aaron, that we could be doing this. This could be an hour long webinar.
Aaron: And we haven’t even touched the AI use for a lot of these as well, too.
I mean, there was a little bit in Hinge had an AI component and a few others like that’s a whole nother bastion of how that clean data sets, if you have clean data sets, you can use gen AI and natural language processing to really up the customer experiences that you’re providing for your members.
Bill: No, absolutely.
So reluctantly, we’ll wrap it up on that note and just thank everybody for being with us for this month and digging deep into the course number 1 of 7, which was introduction to loyalty analytics. I’d say we went well, beyond the introduction space. So we might need the course. I think, but this has been really good.
A great discussion and, love some love, some listener feedback on any of the questions that we’ve talked about, or any of the examples we’ve cited. If you’ve got some great examples that you’d like to share with us, please be in touch with us and let us know. But for now, we’ll say goodbye until next month.
Just want to let, you know, and remind everybody that if you’re interested. In becoming part of this community of certified loyalty marketing professionals, which now numbers around 1000, a little bit beyond 1000 at this point in time that you can just find everything you need by going to the loyalty academy.
org ask us, and we’ll help you to do what you need to do to get to the next step in your development. This business. And if you want to listen to any of our previous podcasts, you can find them at the wise marketer dot com, or let’s talk loyalty dot com. Next month, we’re going to kick off and I believe Aaron talk about loyalty technology, which would be course number 109.
So we’re looking forward to that. And until then, join us next week. And it’s always stay loyal. Always. Thanks.
Paula: This show is sponsored by Wise Marketer Group, publisher of the Wise Marketer, the premier digital customer loyalty marketing resource for industry relevant news, insights, and research. Wise Marketer Group also offers loyalty education and training globally through its Loyalty Academy, which has certified nearly 900 marketers and executives in 49 countries as certified loyalty marketing professionals.
For global coverage of customer engagement and loyalty, check out thewisemarketer.com and become a wiser marketer or subscriber. Learn more about global loyalty education for individuals or corporate training programs at loyaltyacademy.org.
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