#607: Mixing it Up with Analytics-Driven Market Examples

PAULA: And welcome to Let’s Talk Loyalty, an industry podcast for loyalty marketing professionals.

PAULA: I’m Paula Thomas, the founder and CEO of Let’s Talk Loyalty and also Loyalty TV.

PAULA: If you work in loyalty marketing, you can watch our video interviews every Thursday on www.loyalty.tv.

PAULA: And of course, you can listen to our podcasts every Tuesday, every Wednesday, and every Thursday to learn the latest ideas from loyalty experts around the world.

PAULA: Today’s episode is part of the Wiser Loyalty Series, which is hosted by our partners, the Wise Marketer Group.

PAULA: The Wise Marketer Group is a media, education, and advisory services company providing resources for loyalty marketeers through the Wise Marketer Digital Publication, and the Loyalty Academy program that offers the Certified Loyalty Marketing Professional or CLMP designation.

PAULA: I hope you enjoy this weekly podcast, the Wiser Loyalty Series, brought to you by Let’s Talk Loyalty and the Wise Marketer Group.

BILL: Welcome everyone.

BILL: I’m Bill Hanifin.

BILL: I’m the Managing Editor of the Wise Marketer, and I’m here today for another episode of Wiser Loyalty, a series that we’re sponsoring with Let’s Talk Loyalty, courtesy of Paula Thomas.

BILL: Thanks, Paula.

BILL: I’m here today with our CMO from the Wise Marketer Group, Aaron Dauphinee.

BILL: Aaron, how goes it?

AARON: That’s good.

AARON: It’s a really good day here.

AARON: We’re back from our travels earlier this month, and so finally able to get a little bit of rest and catch up and finish off the series for this month on analytics.

AARON: I’m excited about it.

BILL: This is good.

BILL: I love these series because we’re stretching ourselves, we’re challenging some historical beliefs or traditional beliefs in this business and we’re breaking some new ground.

BILL: I really enjoyed it.

BILL: 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.

BILL: This month, we are focusing on course number 107, which is Introduction to Loyalty Analytics.

BILL: In every one of these episodes, we pick apart some aspect of that courseware and we build on it, and we go deep and we offer some examples.

BILL: Just to give you a little bit of history, we talked about the sources of data, where does data come from?

BILL: We talked about analytical approaches, the different types of analytical models that are in play and what their outcomes are, and then we went deep on zero-party data.

BILL: Today, we are going to give you some market examples.

BILL: We talk about some brands that are doing a really good job with data and just some types of outcomes that you can experience.

BILL: Aaron is 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 maybe not so much good, bad, and the ugly, but a little bit of to, to, from, for context.

AARON: When I think way back, Rusty, reference to some Canadian childhood iconography there.

AARON: When I think way back to Tesco in 1995, when they launched their Tesco Club Card program, for those of you who are not familiar, Tesco is a UK-based grocery chain.

AARON: They were some of the first that really started to use data analytics in a savvy way, 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.

AARON: They needed this reward schema called Tesco Club Card to bring things through where each transaction the customer carried out, they’d present their card, they’d earn some points for in-store spend, and an exchange value came into play where Tesco collected a record on that associate, and the customer’s name and post-it code, and then by virtue of that, was able to send them tailored coupons and offers to nudge their behavior.

AARON: They rewarded the high end of the file that spent more and encourage some casual customers to engage more with the store.

AARON: But by and large, it was a very strong success early on.

AARON: Within months of launching, I think, and it’s been a while since I thought about Tesco, but they were spending upwards of four or five percent more than non-club card customers.

AARON: 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 offer support for that particular client set.

AARON: It’s just one of those things of mentioning that’s 30 years ago, that’s where we’re at in terms of we used to think of Tesco as a bit of a master class and where we’re at.

AARON: Now you fast forward to today’s world where something completely different industry, so not retail, not travel outside of the typical of loyalty that’s getting into utilizing data to provide relevancy.

AARON: I think of what’s on my phone all the time that I use every single day, which is Spotify.

AARON: Spotify doesn’t have a formalized program, but they are collecting and utilizing data and utilizing loyalty mechanics to apply and create experiences for their members that are part of the subscription for Spotify.

AARON: I think of the campaign that they’ve done for a number of years, which is Spotify Raps.

AARON: It’s a great example of utilizing data insights on musical tastes 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.

AARON: Your top artists are this, your top genre is this.

AARON: Here’s your favorite songs that you listen to most.

AARON: Just taking that and making it personalized.

AARON: I guess in some instance, we could even say hyper-personalized.

AARON: I know that there’s some question about whether or not that’s a good or bad term right now.

AARON: But the point for me is less about personalization and more about relevancy, because you’re summarizing for me what’s there in terms of my usage of data, and now saying, hey, share this out.

AARON: 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.

AARON: So Spotify knows a lot by virtue of the consumption that you have through their program.

AARON: I think Spotify Wrap is just an extreme example that uses data analytics to tell the users 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.

AARON: Just to kick off thoughts of two from a little bit.

AARON: What about your thoughts in terms of programs you like?

BILL: I love that little tag on to the Tesco stories and I had the opportunity to listen to Clive Humby speak years ago.

BILL: He was actually very humble.

BILL: He said, everybody thinks we’re brilliant and what we’re doing is we’re just, and this was before machine learning was really available or being applied.

BILL: He said, we just run through as many offers as we can, we fail a lot and we wait until where the patterns start to pop up and then we dig in on those patterns.

BILL: Now, we can do it with a lot more precision.

BILL: But I think one of the things about data is, in the illustration you just gave us, is what are the outcomes?

BILL: We talk about hyper-personalization, we were looking for brands that are doing a good job.

BILL: I think people have a yearning to say, I’m giving you data, I want you to demonstrate that you’re doing something positive with it.

BILL: It’s not always offer delivery.

BILL: People think about just jingling the pocket and money, offers, discounts, that is an element of it, absolutely.

BILL: But maybe the more powerful part is even just demonstration of that you know me.

BILL: You know me.

AARON: 100 percent.

BILL: You remember who I am, you actually are tailoring some of your information to me, according to my interests, my express interests.

BILL: The other thing is that you’re saving me time, you’re giving me convenience and ease in my life.

BILL: Relevant is one of those overused terms, but you’re truly ending relevancy.

BILL: I think you’ve got a brand example about relevancy for sure.

BILL: Maybe we could jump into a couple of examples.

BILL: 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.

AARON: 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.

AARON: There I go, using relevancy back.

AARON: Again, it’s in my vernacular.

AARON: I love it so much.

AARON: But I liked where you’re setting.

AARON: It’s not to say providing things that are helpful and that I need.

AARON: I think about a health company that we have, and they’re called Hinge Health.

AARON: There’s an adage, I think I read this somewhere.

AARON: There was a quote from REM, everybody hurts sometimes.

AARON: 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.

AARON: It’s really putting a mind focus on the individual’s health through the app that they have.

AARON: Individuals sign up through the app, they get a tailored physical therapist and a health coach.

AARON: They get personalized messages that are sent to them.

AARON: They get a treatment progress.

AARON: They get a bunch of exercises that match through to where their readiness is relative to where their health is at a given point in their journey or the recovery time.

AARON: Then they’ve made it in a way that involves deep engagement, aka gamification to some degree, where individuals can earn points to unlock the next level of a new exercise, or they can win supplies like yoga mats or bands or weights and stuff like that.

AARON: So it’s really quite cool, quite frankly, in terms of how they’re collecting information, assessing it in a world where the individual doesn’t have to go into a physical therapy office.

AARON: To your point of that doesn’t save people time.

AARON: There’s costs associated with that.

AARON: There’s often lack of motivation to go into a public space to get into your shorts and your shirt to exercise publicly when you’re hurting.

AARON: 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.

AARON: 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.

AARON: I just thought that was a cool example.

BILL: No, it’s a really good one.

BILL: I’ll tell you where something I’ve seen lately that maybe gets into the convenience area and ease and just relevancy.

BILL: But I don’t know if you’ve seen this, and I’m sure it’ll start to become prevalent.

BILL: 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.

BILL: That’s a good curiosity hook right there.

BILL: All you did was scan a QR code with your phone.

BILL: You would log in to your Delta SkyMiles account, and now the TV knew exactly who you were.

BILL: It populated my name, said thanks, had some information about my status, and here’s the best part.

BILL: Usually, I skip watching movies on short flights because I know I can never finish them.

BILL: 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.

AARON: You’re kidding me.

BILL: This is awesome.

BILL: Now, two 90-minute flights turned out, I could actually watch this movie that I wanted to.

BILL: I’m sure they are just scratching the surface because they’re going to be so much.

BILL: I started right away, my mind was spinning.

BILL: What other things could they do with this?

BILL: But it makes the flight like I’m in my seat and I’m at home.

BILL: It’s convenient, it’s fun.

BILL: It starts to change the travel experience in the better way that I’ve been hoping for for a long time.

AARON: Yeah, I know.

AARON: 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 an affiliation with one of the telcos here in Canada.

AARON: That you could do text screening and that for free when you sign in and you just put your seat in and whatnot.

AARON: But recently, they’ve actually now gone the further step to say, for those who are at 75K or 100K, which is their top two status tiers, you can now log in through just putting your seat in.

AARON: You don’t have to go through and log in through the full mechanism of the app.

AARON: That’s a time-saving, made inconvenient because the assessing to get on to the Wi-Fi when you’re on the plane has not been the easiest pursuit.

AARON: 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.

AARON: But I love that connection and because we’ve seen that in travel, I guess too, right?

AARON: We think about the hotels with their digital keys.

AARON: 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 too, Renaissance and et cetera and so forth, IHG as well.

AARON: These mobile smartphone keys are helpful in terms of having a one device to let you in and then utilize that for the TVs, it’s a smart TV and stuff and you have all this information that you’re collecting about the customer.

AARON: But I haven’t seen them extend that into any real significant uses beyond that.

AARON: It’s been latent and so now we see that the airlines coming in and starting to make the connection.

AARON: Maybe there’ll be a push to quote unquote, no pun intended, unlock more from the digital key.

BILL: That’s great.

BILL: 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?

BILL: There’s this element also what you can do with data that’s so powerful in the area of dynamic pricing.

BILL: We’re getting to our time, but maybe can you give a quick synopsis of dynamic pricing and maybe how it works well and when it might not work so well?

AARON: Yeah.

AARON: 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 long standing has been Amazon.

AARON: We’ve known this for, 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 it’s been an e-commerce platform and then migrated into the retail footprint offline afterwards with Whole Foods.

AARON: 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’s 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 you know this?

AARON: And they created a system where they put a bit of a governor on it in early days.

AARON: I don’t know if that governor is still in effect now as it’s more of an expectation because it shouldn’t have to be.

AARON: I mean, on that front with dynamic pricing, I think there’s the two things.

AARON: One, if you’re utilizing the data 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 your meeting my needs, that’s what I seek.

AARON: 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, and I’m going to be like, wait, now I don’t like that.

AARON: The real critical thing to think about here as you’re utilizing this data and it’s easier said than that, I recognize I’m not trying to sit from an ivory tower here, is that you have to get it right.

AARON: The test and learn model sometimes isn’t as free as it used to be when we’re starting to integrate a bunch of other different analytics sources.

AARON: 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 and my partner’s beside me doing something similar to search for the same things, because we both realize we’re out of toothpaste and TP, and then all of a sudden the price point is different for me than it is for my partner.

AARON: That raises my eyebrows.

AARON: Maybe on everyday products, it’s not the end of the world.

AARON: But imagine if you’re planning for a trip, and your price is doing sorts and one’s doing it through the airline app, and another one’s doing it on Expedia or another travel consolidator.

AARON: The price points come up very differently.

AARON: You got to ask yourself a question there, what’s going on?

AARON: 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.

BILL: This could be an hour-long webinar.

AARON: We haven’t even touched the AI use for a lot of these as well too.

AARON: There was a little bit in Hinge had an AI component and a few others.

AARON: That’s a whole other bastion of how that clean datasets, if you have clean datasets, you can use JAN AI and natural language processing to really up the customer experiences that you’re providing for your members.

BILL: No, absolutely.

BILL: Reluctantly, we’ll wrap it up on that note.

BILL: Just thank everybody for being with us for this month and digging deep into the course number 107, which was Introduction to Loyalty Analytics.

BILL: I’d say we went well beyond the introduction space, so we might need to end the course, I think.

BILL: But this has been really good, a great discussion and love some listener feedback on any of the questions that we’ve talked about or any of the examples we’ve cited.

BILL: 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.

BILL: But for now, we’ll say goodbye until next month.

BILL: 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 with now numbers around a thousand, a little bit beyond a thousand at this point in time, that you can just find everything you need by going to the loyaltyacademy.org.

BILL: Ask us and we’ll help you to do what you need to do to get to the next step in your development in this business.

BILL: And if you want to listen to any of our previous podcasts, you can find them at thewisemarketer.com or letstalkloyalty.com.

BILL: Next month, we’re going to kick off and I believe Aaron talked about Loyalty Technology, which would be course number 109.

BILL: So we’re looking forward to that.

BILL: And until then, join us next week.

BILL: And as always, stay loyal always.

BILL: Thanks.

AARON: You’re welcome, everyone.

PAULA: Thank you so much for listening to this episode of Let’s Talk Loyalty.

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