Paula: Welcome to Let’s Talk Loyalty, an industry podcast for loyalty marketing professionals. I’m Paula Thomas, the founder and CEO of Let’s Talk Loyalty and also Loyalty TV. If you work in loyalty marketing, you can watch our video interviews every Thursday on www. loyalty. tv. 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. Today’s episode is part of The Wiser Loyalty series, which is hosted by our partners, The Wise Marketer Group. The Wise Marketer Group is a media, education and advisory services company providing resources for loyalty marketers through The Wise marketer digital publication and The Loyalty Academy program that offers the certified loyalty marketing professional or CLMP designation. I hope you enjoy this weekly podcast, The Wiser Loyalty Series brought to you by Let’s Talk Loyalty and The Wise marketer Group.
This show is brought to you by Comarch, a multi country leader in customer engagement tools that help you forge meaningful connections and boost profits, leveraging over 10 years of experience in utilizing AI technology. From immersive loyalty programs to captivating marketing campaigns, Comarch helps you deliver personalized experiences across every touchpoint. Gather valuable insights. understand customer behavior, and watch your brand recognition soar. Comarch, where innovation meets customer satisfaction. To learn more, visit Comarch. com.
Bill: Welcome everyone. This is Bill Hanifin, and I’m here this week with Aaron Dauphinee. Hello, Aaron. How are you?
Hi, Bill. I’m doing well. How are you today?
Good. And we’re teamed up again to do the Wiser Loyalty Podcast, which is An educational series that we’re hosting together with Let’s Talk Loyalty this month.
And if you’ve been with us all year, you probably already know that we’re, we’re tapping into individual course material within The Loyalty Academy curriculum. And so each month, we’ve selected a course that we think is of interest to everyone and. We kind of dig deep, we update the material, we challenge some traditional thinking and Aaron and I get to compare thoughts.
So we, we agree most of the time, but there’s there’s times where we have some different looks at this. So this will be maybe one of those cases today. We’ll find out. But this month, during the month of October, we’re going to be talking about data analytics and loyalty marketing 107, which is introduction to loyalty analytics.
So, in this week’s kickoff episode in this series, Aaron and I are going to talk about the wide range of data sources that are available to marketers today. We’re going to compare some thoughts on whether brands are collecting the right data, ask the question openly about whether we’re collecting too much data, and if in the end, maybe the biggest question is.
This buzzword about having a 360 degree view of the customer. Is that really our goal? Is that the ultimate goal for all of us as marketers? Or could it be something else? So I’m going to kick it off, throw it over to Aaron and just ask what are the sources of data available? It seems like we’ve been good at collecting it, but where does it come from?
And what types are we collecting? What’s it look like this day these days?
Aaron: Yeah, I think there’s a mix of data that’s it’s evolved and out of different sources at this point in our journey is as loyalty marketers over the last, what, plus 30, 30 some odd years. And, but really, when we think about it from a base perspective, in terms of the key category of information that typically comes out of a loyalty program, we’re talking about.
Behavioral data and data and and the transactional data that that comes from interacting with your customers and, and, and having them make purchases in your store or on your in through your ecosystem or wherever that might be. And so, I think that’s the, the critical amount of information that, you know, a loyalty program provides over and above.
What other areas you can get certain, there’s social data, there’s stuff on your website there’s stuff in your, in, in your accounting system if, if you purchase through another mechanism as well too. But the point being the, the way in which, and the time in which, and, and how, and what an individual purchased from you is, is oftentimes collected through that kind of first party data component of the Loyalty two program and.
And we’re talking about things that typically come through, you know, a point of sale or a point of purchase, POP or POS. It’s sometimes debated which one we use on that. When, when you make an actual purchase at a retailer, let’s just use a retailer as an example to make it easy. So you’re talking about things like, you know, the amount of the transaction the location that you might be at the channel of transaction, you know, where, where it’s occurring online or if it’s in person to some degree, you’ve got the SKU level or UPC data.
You’ve got the tender type, you know, which actually source of money is actually being utilized if it’s credit card cash or debit or other and then, of course, the data transaction and all that you need to kind of make the calculation in terms of the reward point system that goes through to, to be debited or put put points to your, into your account.
So, And certainly there’s more of the data you can get from elsewhere. But like Bill, I’ll turn it back to you. That’s kind of my first thought as the low level amount of data that you need at the very base of a loyalty program. But what other sources do you think come into play?
Bill: But, you know, it’s interesting because we talked in a previous month about cross functional collaboration within the business to make loyalty work a lot better.
And I think at the time we were talking about loyalty finance and we said, marketers need to start talking the language of the CFO and you were talking about data sources. And it made me think that we all need to start understanding each other’s language. Because I, I hear a lot of what you just described if I was in one particular kind of business, they might say.
Okay. Thank you. We just get T log data, T log transaction log you know, other people might say it’s transactional data. Okay, great. And then us as marketers and we talk to ourselves. I think we talk about behavioral data and it just sounds more sophisticated, I guess, but that’s what it is. But it’s, it’s kind of good just to know all these things.
Translated can mean different things, but, you know, beyond just a purchase transaction, there’s a lot of data that can’t be collected. And I think it depends on the industry. So think about it. If you’re in financial services, you have applications, which means you have a plethora of data, some of which you can probably never share for marketing purposes, because it has to do with income and very personal protected kind of PII data, what they would call it.
But, but others like airline, they also have. Incredible, incredible amount of information about you and I, and every customer, because obviously you, you have to give them a lot of data and they have your frequent flyer account most likely. And so when you’re making a travel arrangements, there’s a much deeper level of data.
There then would be in retail, for instance, and retail still many, many are just striving for identification. So all the things that you talked about. Like, if I can identify somebody at the, at the point of sale, then I get those items that you were talking about, but that still only gives me so much. So, you know, I think some marketers combine what they get, maybe through a loyalty program, or even prior to launching with things like opt in campaigns.
So, it could be anything from a warranty program to a sweepstakes. You know, we’re collecting, you know, give me your information and you get that or give me your, your email address and then you know, that sort of thing and join the program. So there’s a range there. And obviously you can append. You can purchase 3rd party data, which would cover demographics and income.
You could get metadata covering weather and all sorts of other. Categories there and then so it seems to me, like, there’s no lack of of availability or volume of data, but maybe there’s a lack of focus. You know, then I was hoping maybe you could bring us back into focus. Like, how would you prioritize what we should be collecting?
And how do we rationalize what we collect?
Aaron: Yeah, well, if I think about what the end use case is oftentimes you’re utilizing this information to create segments or clusters of groups of customers so that you can get some efficiencies in your marketing. We always talk about one to one personalization marketing.
That’s great as a utopia, but sometimes it’s, it’s not the be all end all of you, and you can get to one to some as being more effective in terms of the connection points when you create individuals or gather individuals that, that have similar qualities and behaviors around them. And, and I think. You know, from that perspective, the demographic information, you talked about identity, right?
Name, address, city, state, postal code, email, things like that. Mobile number, you know, those are critical things. I think mobile number is even more critical. Sometimes an email at this point, although email still thriving as a preference for communications these days, I think the variety of information that’s out there.
And then we haven’t even talked about psychographic information and lifestyle data as well to that can come into play. But if you ask me about. Okay. How do I prioritize them? I think the key to prioritizing is, you know, we used to say the old adage, collect it and we’ll figure it out. Well, that’s not the right model anymore.
And certainly with privacy legislation, that is just not even acceptable in some jurisdictions. And so have purpose in terms of why you’re collecting data and what you intended to do about it and how do you intend to utilize it? And then also actually be open and transparent with your members and customers to say, I collected this set of information on you, bill.
Here’s what I’m gonna use it as an offer. I had this information from Aaron. I sent him this offer. Here’s how he responded. Oh, here from Aaron here as to why that’s good. And so that’ll give you some element of ease to use those stories and, and realization of this is the value and the purpose, and, and intent as to why we’re collecting this data and we’re utilizing it.
And, and if you can’t, then you gotta think about why, why you’re collecting it, and remove it out of your system. And by and large, I just think that helps as a whole for data management, even though it’s easy to, you know, store and process data now and much, much different than it was many, many years ago.
But in the interest of good, clean data you know, we want to make sure that we have what we need and, and it’s accurate and it’s not being have a, has a halo around some stagnant data that might be distractionary to the purposes that we want in terms of the interaction with that particular customer.
Bill: Right, right and so you know what that’s even more important because I think what we’re trying to do is is loyalty marketers in this business is avoid falling into the social media trap. I call it, which would be labeled as participants in surveillance capitalism. You know, that was a term that was coined by a Harvard business school professor named Shoshana Zuboff and she wrote a book some years ago and coined that term.
And it’s, it was really a term that was Okay. Well, developed in that film, the social dilemma, which, which you had a lot of social media people talking about how they they’ve just you know, monetize people and turn customers into the product and all those sort of things. So, they’re, they’re, they’re 2 balancing efforts.
I think we’ve got to pay attention to one of them is we can be proactive and try to avoid falling into that trap. We can avoid. Making customers feel like they’re being monetized, like, they’re an asset of the of the business as if we own them almost and we just seek their data for some kind of financial gain.
Isn’t it much better if we collect what’s purposeful and we and we use it in a way that’s meaningful. Just like you were talking about. And then. They’ll feel well served. They’ll have higher levels of satisfaction. They’ll feel like their expectations were met. So that’s the part I think that marketers can do on their own.
And the other part is that we should do it because there’s things such as GDPR and CCPA, there are regulatory efforts in just about every market around the world saying, if you don’t use the data correctly and have these sort of protocols in place, then you’re going to be penalized heavily. So. I sort of look at it as though maybe we should moderate the pace at which we collect data, make sure that we’re going to use it, you know, in a meaningful way.
And obviously we have to be compliant with legislation, but we should do it because it’s the best practice in business anyway, so that we serve our customers very well.
Aaron: Yeah, 100 percent agree with that. And I was just actually at a conference down in Brazil. Any about artificial intelligence and one of the questions that was asked to me as I was also on a panel as well as doing the keynote was really around what’s the ethical implications of artificial intelligence and then how we’ll use it as loyalty marketers and my response and answer was, well, it hasn’t really changed for us in the loyalty marketing industry because we all have a responsibility to do ethically strong have part of me have ethically strong customer data principles and practices in place because we are stewards of the data for the customers that are on our file and in our in our database.
And so, the application of artificial intelligence is a technology to help us get better at utilizing the data and providing relevancy. But what we’re finding, and then I think it was a, I might get this wrong, but I believe it was a, a study by Gartner that said that only 4 percent of, of CEOs recognize now that their customer data is in a space where the technology can actually be useful or artificial intelligence to be useful for it.
So they got, there’s a bunch of efforts now in organizations that are trying to implement artificial intelligence to clean up the data set. You know, to have better hygiene practices and make sure the accuracy of the data is strong. And make sure that it’s relevant and current because data is always changing as well, too.
So I think it’s a good, you know, way of technology coming in saying, Hey, if we’re going to get the most out of it, we need to be able to make sure that we’ve got good stewardship and practices in place for how we’ll utilize that once we know more. And then also to make sure that we’re, as you said, compliant with any regulatory bodies that are in place in virtually every jurisdiction, as you noted.
So I think that’s kind of my last comment is, is we’re in a very fun, interesting place in terms of of analytics and being able to calculate through on on things and find out new things about customers and kind of. Respond to their needs in ways that we haven’t been able to before and really get to a needs based type of segmentation that, you know, moves beyond behavioral, psychological, psychographic, as well as demographic and, and you know, for us, it’s an exciting time in analytics.
So, I know, I know we’re probably near the end, I’ll maybe cut it off and we’ll talk about some practices and methods in another segment in the near future.
Bill: That’s perfect. In fact, that’s a great place to land it because yeah, the following we’ve got 3 more episodes this month and I know we’ll talk about loyalty methods and models.
We’re going to talk about zero party data and cookie deprecation. And we’re going to have some market examples. We’re going to share some things that we’ve experienced in some clients that we’ve worked with and some examples of people that are doing this really well. So, hey, as always for anyone interested in joining our community of loyalty marketing professionals, you can learn more.
At loyalty academy dot org about how you can earn your designation and join the nearly 1000 that we have today in 54 countries around the world. If you want to dig into previous podcasts on different topics that we’ve been covering this year, you can access The Wiser Loyalty Podcast series at thewisemarketer.com.
And, of course, letstalkloyalty.com. And with that, we wish you a great week. We thank Paula Thomas and Let’s Talk Loyalty for this collaboration. We love it. And we hope it’s bringing you value. So we’ll see you back here next week everyone.
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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