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Steve:
Personalization has been something we've explored in previous episodes of The CX Leader Podcast, but maybe it's time to take it to the next level.

Melissa:
hyper-personalization is using A.I. with real time data to identify patterns of consumer behavior that can then allow an individual to make a better informed decision to bring value to their customer.

Steve:
A look into hyper-personalization and its role in customer experience on this episode of The CX Leader Podcast.

Announcer:
The CX Leader Podcast with Steve Walker is produced by Walker, an experience management firm that helps our clients accelerate their XM success. You can find out more at Walkerinfo.com.

Steve:
Hello, everyone. I'm Steve Walker, host of The CX Leader Podcast and thank you for listening. On The CX Leader Podcast we explore topics and themes to help leaders like you leverage all the benefits of your customer experience and help your customers and prospects want to do more business with you. hyper-personalization. It's one of the newer buzzwords out there in the business world today, a practice that utilizes artificial intelligence to deliver highly personalized content and experiences in real-time at an individual level. It's just another way for brands to connect with their customers. Just from that short description, most CX pros will instantly connect why it could be another tool in the box for customer experience programs. But we thought we'd like to take a deeper look at this newer concept, and I couldn't be happier to have my guest on the episode this week. Melissa Drew, an associate partner at IBM who has extensive experience in A.I. and other cognitive cloud technologies. Just got to know her a little bit off the air before we started to do the podcast. And I'm really excited to have Melissa with your depth of experience. So welcome to The CX Leader Podcast.

Melissa:
Thank you. I'm really excited about this topic.

Steve:
Well, I am too. And we were talking that personalization has long been kind of one of the basic tenants that we've talked about in terms of customer experience, along with speed and ease of doing business. But one of the things we like to do is hear a little bit more about your background and how you got to this place in your career, just to set a little context for our discussion. So it's always interesting to see people's journey of how they got here to the kind of the customer experience world. So give us a little bit of your background, Melissa.

Melissa:
So I've been in procurement supply chain for 27 years. I've written a book in 1991. I started speaking in 1993. I started my own company just so I can get through college, which really gave me that first interaction of what does a customer need and how do I shape that experience so that I can provide them value but also pay for college and, you know, connecting with the cognitive technologies. I worked with a company in 2004 that created a patented data classification engine, and I had just left the company and worked with them to pull together my expertize around data classification and creating those algorithms through the A.I. Modeling. So I have I am on this perfect intersection between, you know, procurement, supply chain, A.I., cognitive technologies and how that's impacting our customer on a day to day basis.

Steve:
Well, that's a fascinating background and somewhat unique, I think, for those of us in the customer experience realm. You know, a lot of people come up kind of through the market research role or the customer service role. Obviously, you had that, you had the kind of the entrepreneurial bent and along the way. But, you know, supply chain, again, it was heavily quantitative. And now we're trying to really apply those kinds of same disciplines to the experience aspect of it. But, you know, why don't you give us your definition of hyper-personalization? What do you mean when you say hyper-personalization?

Melissa:
Yeah, I, I think you you touched on it briefly. You know, hyper-personalization when we think about it in an industry standard is using A.I. with real time data to identify patterns of consumer behavior that can then allow an individual to make a better informed decision to bring value to their customer.

Steve:
And so we see that again, just from sort of a novice perspective, so, you know, if you're searching the web and then you go somewhere else, you might see a pop up ad, right?

Melissa:
Yeah. So I've I've got this this example that I hear all the time, and then I'm going to take it one step further. There's a scenario around a backpack. So I am I am shopping for my backpack. And suddenly, you know, I put it in my cart, I go to check out and something happens at home and I never check out and I buy it. You know, next thing you know, I get an email saying, hey, reminder, did did you want the backpack? You know, it's still here and nothing ever happens, you know? And then a couple of weeks later, that backpack that I started to buy is now on sale. So now I start getting email messages and notifications saying, hey, by the way, that backpack is on sale. And wouldn't that backpack be really cool? Because this Saturday in your location, it's 98 degrees and you could use that backpack on that hiking trail that you tried three months ago. That's hyper-personalization.

Steve:
Now, I think some people that aren't, as you know, I guess, trusting they find this all a little creepy. Is it creepy?

Melissa:
It's it's a it's a balance. And it's interesting because usually when we say creepy, that's becoming that's also becoming an industry word, being used with hyper-personalization, the pros and cons. There's a creepy factor, which is, you know, and there are some friends of mine. When I explained to them the backpack, their first instinct is that's way too much information. Where did they get it from? Well, they got it from you, you know, and the problem that we're having with why this is such a, you know, a pros and cons is as much as it feels like it's creepy, we're also seeing studies directly from the end users, you know, the consumers who are saying, I'm willing to give you more information as long as you're going to use it to personalize information for me or even more specifically, show me items out there that I never would have discovered on my own. So we're still seeing the studies where consumers want us to give them this information and as a result, they're willing to share it. But then when the process starts to happen, it takes it a couple steps beyond and then now suddenly. Ah, well, I feel like you're stalking me on the Internet.

Steve:
Yeah, I brought that up a little bit, tongue in cheek, I got to admit, because, you know, because on the other side of it, we're so used to having convenience and, you know, like, for example, on Amazon, you know, it's so easy to buy and click. And they got all your information there. And so you go to another website and you got to put in your address and your shipping address and your billing address, and then you got to enter your credit card number and, you know, sort of like, well, you know, this this isn't like Amazon, you know. And so and we have to be willing to for convenience and for personalization and things that are really fitting our needs. You know, we have to give to get a little bit. Right?

Melissa:
Right. And it seems to be this circular, you know, the circular conversation. You know, Amazon has made comments where they've asked their own their own consumers, "do you want to share more information if we can personalize the recommendations?" And then on top of that, their own studies show that more people are buying from Amazon specifically because of the recommendations that Amazon is giving them.

Steve:
Right.

Melissa:
So it's it's this, you know, the chicken before the egg. You know, I want it because I want what it does. But at some point, the consumer is saying, I also want a line in the sand where you don't go too far.

Steve:
Yeah. And that's it is always going to be a little bit of a tradeoff. But I think that the benefits of it used responsibly are going to continue to allow organizations to provide better and better experiences. So, you know, A.I. is kind of also a buzz word, I think, to the average person. But you're an expert in this. But and I think this is probably easy question for you to answer, even though it's a difficult question. But but how has A.I. made some of what hyper-personalization can happen. Just explain a little bit more about how it's it's helped this become a reality.

Melissa:
Yes. So I'm going to I'm going to step back and give you some history. So in 2015, Ardent Partners came out with their study, CPO Rising. They come out with this every year. It's a consolidation of all the chief procurement officers who really gauge where they need to go in the future. And 2015 was really particular because it was now decided that the organizations is changing away from the strategic and moving towards the agile. And the whole point of an agile organization was to quickly adjust to the changing needs of the consumer, really focus on the user experience. So organization has been in these agile state for the last six years, but we still hit gaps. You know, we still see a lack in confidence in our data. Our data is inaccurate. We're not able to make really better informed decisions that meet our our consumers needs. Now comes in A.I. So with A.I. technology combining with the company wanting to be more agile to its customers, we're now able to use the A.I. technologies to really analyze large sets of data, analyze the real time data that we're getting from the Internet, and then be able to highlight patterns of what our consumer behaviors are working in and then turn around and give that information back to our our CX professionals so that they can go make a better informed decision. So let me let me give you a real world example. Starbucks. Five years ago, do you have the Starbucks app, by the way?

Steve:
I do.

Melissa:
You do. OK, so if you have the Starbucks app, which I'm in love with Starbucks. Five years ago, they would send out these reward programs where, hey, if you go buy, you know, five sandwiches over the next five days, you get a bunch of rewards. Well, I never use those because I don't eat those sandwiches. I don't like them. I actually go buy my my Starbucks cold brew. So five years ago when they were sending out these programs, they were using about 50 different variants. They were looking at geography. They were looking at some of the past purchases, but they weren't looking at a lot of the information. So these these reward programs were very generic. Nowadays, they have over 400,000 variants. When I go into my Starbucks app now, suddenly I'm getting the rewards that's specific to what I buy. And I've noticed that if I change my patterns in buying those variants and those reward programs will change with me, all to ensure that I'm continuing to consume and spend money with Starbucks in the most profitable way.

Steve:
Yeah, actually, just listening to you, I'm a CVS's person and, you know, I use my card and it's on my app and my phone and they send me deals just constantly. And I you put it right on your phone and you don't have to hassle with it. And it's you know, it really is very, very convenient. I'm also a fan of American Express because they figured out a way to kind of give you things that's right there on your card. And, you know, you don't have to keep track of the deal. They do that for you and then they do a really good job of kind of keeping you up to, you know, up to reminders of of the opportunities that you have out there. And it really enhances the experience.

Melissa:
It does. But A.I. Is the only way that they've been able to to accommodate that in a way that is more convenient but useful for you brings you value, but it allows them to to process all of this so much more quickly. You know, now, instead of it being four or five ways, I'm looking at it. I'm looking at your age. I'm looking at your location. I'm looking at what you've been viewing. Did you search on something I didn't buy for it? Are you suddenly buying something at CVS that you've never bought before? OK, let's change and give you promotions to focus on what you're buying so you can buy more of it. All of that wouldn't be possible if we didn't have the technology to sift through that data very quickly.

Steve:
Hey, my guest on the podcast this week is Melissa Drew. She's an associate partner at IBM and an expert in artificial intelligence. And we've been having a fascinating discussion about hyper-personalization, which is, you know, if it's not something that you've thought about for your CX program, it's something that you ought to be thinking about, because the emerging technologies of A.I. and and digital are really making this more and more part of the competitive landscape in designing the best customer experiences. So we've been talking a lot more kind of how it affects from the consumer standpoint or the customer standpoint. Let's go back to the practitioner or your CX pro inside of your company. Maybe you don't feel like your organization is moving as quickly as it could. What were some of the, you know, first steps or what are the things that organization ought to consider to wade into this and make sure that they're doing it right? What are some of the fundamental positives and negatives that an organization would have to weigh as they ponder this decision?

Melissa:
Yeah, so and that's an interesting question. And I think that's what sparked a lot of the conversation with hyper-personalization and with the use of these technologies. We've now got more things open to us before. You know, your earlier email campaigns weren't really effective. They were effective because they could reach a larger audience, but they weren't as effective because you couldn't get targeted information. Now, with the A.I. technologies and hyper-personalization we're finding on the CX side, we're finding that we can now really utilize email campaigns and marketing that we've never been able to use before. We're able to really look at a full 360 degree brand experience because we can use these technologies to enable channels that we hadn't really focused on. And then it goes back to everything's about the consumer. The consumer needs you, you know, so we've got it. I've got a coin, and to know me, understand me, and then show me. Without the A.I. technology, I could know you, but I could never fully understand you. With A.I. I can know you, I can understand you. And then I can turn around and actually show you using those CVS promotions that you mentioned, you know, using the Amazon and the Netflix recommendations, I'm now able to turn around and show you the consumer that I understand you and here's how I understand you.

Steve:
So really, most of the leaders are really in the B2C side. I mean, we've seen this pattern for years that really that B2C kind of leads in the innovation and then it eventually applies itself to B2B. Can you talk a little bit about how some of these concepts would apply in in more of a B2B aspect?

Melissa:
So Japan Airlines goes out and they work with a market, a supplier who's developed this marketing technology. It incorporates A.I. They pull that into Japan Airlines marketing brand awareness department. They use that combined with the hyper-personalization. And now they are sending out information to their skier's that says, hey, we're going to have an entire flight that's just for skier's to go to this particular mountain so that you guys can ski. So that was that's a combination of a supplier who's built a marketing technology, you know, sells that service or technology to Japan Airlines, who turns around, pulls in the hyper-personalization, and then be able to create a package that before, yeah, they saw that they had a lot of skiers, but they noticed that a lot of skiers were going to this one particular mountain to ski at a point in time. So now to make the experience even better, they're just going to have the entire plane of nothing but skiers. How much more enjoyable to that is to know that everybody that you're sitting on the plane is all going to the same ski resort and all skiers just like you, so much more of an interaction than just sitting on a random plane where nobody talks to each other for two hours.

Steve:
Yeah, that's a great example. You know, let's just go back to the some of the privacy concerns. And I imagine that you have some some good guidelines here. But, you know, what are some of the dos and don'ts with with personal information and and just kind of at a high level, what should people be thinking about as they think about hyper-personalization? How far is too far?

Melissa:
I guess they they need to read the fine print. Laws, the privacy laws around this over the past, gosh, past couple of years globally have made it very, very important that company is legally required. So by law, they have to take you off the list. If you come if you opt in and say that's what you want to do. But when you sign those agreements, if you're not reading the fine print, all of that information that they're collecting is being used to create a more hyper-personalized brand experience for you. So the one thing that I would recommend that even I wasn't doing until just recently is taking a moment to read the fine print and making sure that you're OK, that here's all the data they're collecting and you're comfortable that they are only using it for you. They're not going to sell it to somebody else. They're not going to use it for other areas within their in their company. And then if you opt out, that's fine, but just realize that by opting out, you've also decided that you don't want to read the recommendations, you don't want to receive all those hyper-personalized items of things that you may not have been aware of that you wanted to to purchase.

Steve:
Yeah. And your experience might be less than ideal if, in fact, you're super concerned. But that's where it comes back to trust. And and, you know, really the value of a customer relationship. You just you know, so there's a real responsibility on the side of the marketer to to make sure that they take care of that information and use it only for the right purposes.

Melissa:
You brought up something earlier in this conversation that made me think that, yes, on one hand, me as a consumer, I want to get the information. I want to get the recommendations. I want to feel like you're targeting me, that you going back to the you know, the know me, understand me, show me. But I think we're still like this is still very fluid. You know, this whole area of hyper-personalization and the use of data is still very fluid. And I think what we're finding is there is this blurred line between what you've said is trusted versus how far is too far. And it's that blurred line at the moment that we're all still trying to understand how that line is being defined and what is that limit. We haven't gotten there yet.

Steve:
Well, I think COVID accelerated a lot of this. And, you know, for survival, people figured out new ways of doing business that, you know, really leverage the digital platform. And that's happened way faster than people can, you know, figure out how to come up with laws to to control it. So there really is a lot more, I think, just based in the kind of the trust. And, you know, a lot of these emerging business models are really built on transparency. You know, I mean, like take Uber, for example. I mean, you know, if you're a bad Uber customer, you know, nobody's going to pick you up now. And if you're a bad driver, you know, you won't get rides. So and it's it's kind of self-regulating. Right. And that's, I think another kind of benefit of hyper-personalization is, you know, it really does put the consumer gives them and kind of another gear in terms of what they can control as part of their own experience.

Melissa:
Well, for now, consumers like it.

Steve:
Yeah, yeah. No, I think that, in fact, I don't think we would have been able to respond to the pandemic without, you know, some relaxation in some of the regulations around speed at which medical approvals were happening in the use of telemedicine. You know, we had to start to embrace it and some of that. And, you know, how how many older people figured out they didn't have to ever go to the grocery store again?

Melissa:
Well, how many younger people figured out they didn't have to go to the grocery store ever again?

Steve:
Yeah, because I'm older. I kind of think of the older people, but that's my cohort. So, Melissa, we have reached that point in this podcast where I ask every one of our guests to provide our listeners with take home value. This is your best idea or tip that our CX pros can take back to their office. And whenever they go, if it's still today or it's tomorrow or it's next next week, and what can they apply from this podcast that could benefit what they're doing with their customer experience program? So, Melissa Drew, give us your best tip.

Melissa:
Recognize that with the use of hyper-personalization, the interaction with that consumer happens well before someone from your company actually physically talks to that individual. Whether it's through email campaigns, the website, those automated notifications that they're getting – they're going to spend more time through that hyper-personalization then physically talking to somebody. So when we look at that 360 degree brand experience, we just need to step back and and recognize that that the consumer experience is happening really, really earlier and that presales demand generation cycle than than where it was even a year ago.

Steve:
Great tip. And I actually I just wrote that down for my own purposes because, you know, there is there's so much now that people are going to self serve that this this is you know, it's got to be multichannel and you've got to be supporting it on a digital level. So…

Yeah, because of that interaction, consumers are making their decisions. Consumers are almost making their decisions before they even talk to somebody.

Steve:
Right. It's a good point as you may not even get in the game if some of your digital experiences aren't there, because they may say this, this isn't what I'm looking for. Before they even talk to you, so. Well, my guest on the podcast this week, Melissa Drew is an associate partner of IBM, an expert in A.I. and we've been talking about hyper-personalization. Melissa, thanks for being a guest on The CX Leader Podcast. Really enjoyed our conversation.

Melissa:
I thought this was fun. Thank you.

Steve:
Well, you were a great guest. And if people would like to continue the conversation, I think they can find you on LinkedIn, I typed in Melissa Drew I.B.M. or maybe you want to even offer a website or somewhere where they can connect with you.

Melissa:
Now, I think LinkedIn is perfect. I'm absolutely open to connecting. And this year I have offered to make myself available and share as much knowledge as I can to everybody.

Steve:
Great. Well, thanks again. And if you want to talk about anything else you heard on this podcast or about how Walker can help your business's customer experience, feel free to email me at a podcast@walkerinfo.com. Be sure to check out our website, cxleaderpodcast.com. To subscribe to the show, find all of our previous episodes. We organize them by series and by subject matter. You can drop us a note, give us your contact information or suggest an idea for a future podcast. Again, check out Cxleaderpodcast.com. And The CX Leader Podcast is a production of Walker, we're an experience management firm that helps companies accelerate their XM success. You can read more about us at Walkerinfo.com. Thank you for listening and we'll see you again next time.

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