Hyper-Personalization & how AI is impacting retail & consumers ⎜ Melissa Drew ⎜ EP 167
Ryan Cramer: What's up, everyone? Welcome to my corner of the internet. I'm your host, Ryan Cramer, and this is Crossover Commerce presented by PingPong Payments, the leading global payments provider, helping sellers keep more of their hard earned money. Hello, hello, everyone. Welcome once again to another episode of Crossover Commerce. This is episode 167, or 167, as we in the biz like to call it, of my corner of the internet called Crossover Commerce. I'm Ryan Cramer, the host of this amazing podcast, where I bring the best and brightest in the Amazon e- commerce industry, but we're going to even expand it even more, more people, just in terms of technology. If it applies back to e- commerce and Amazon, this is the place to be. We go live on this podcast every... I want to say... I always give it a range. It's anywhere from two to six. We've had as many as six episodes in one week, so you're always going to get lots of fantastic content coming from this podcast. That being said, it's my corner of the internet, but I want to go ahead and thank you... send a quick thank you to our sponsor, PingPong Payments. PingPong Payments is a cross- border payments solution helping sellers in any landscape, whether it's on Amazon or on e- commerce, or really just any sort of business in general doing commerce online, helping them send more money and receive money at a cost effective rate. Don't do it anymore through the localized bank accounts, international wire transfers, or anything of the sort. Make sure you go with the solution that's PingPong Payments. It's free to sign up, it's cost effective. It's going to save you money, put it to your bottom line. If you're in a space where you need more money towards your margins, or if you need something that's going to be quick in terms of getting money to your supplier, manufacturer, your VA, whatever it might be, go ahead and contact our team today, and you can actually sign up for a free account at usa. pingpingx. com/ podcast. That being said, let them know that it was Crossover Commerce sent you, and if you have questions, always reach out to us. All the comments in the sections below and our show notes, you're going to be able to link out to that as well. So thank you PingPong Payments for that. That being said, episode 167, let's dive right into it. So I'm really excited to have people... Quick story before we get into more stories. This podcast is amazing because we have lots of people reach out. Our friends of friends of the show who see it on chance and say, " Hey, listen, I have also lots of great content to share with you too," and that's always a fun part of my job as a host. I've been doing this for over a year now. Lots of great people want to share their content and expertise to help other people grow their business. It's not a pitch, it's just something that they want to help people understand a problem in the space, and how either to overcome it or just educate people on it and make their own assumptions. And that's what's the beauty about podcasting. There's a lot of great content that's getting shared, educational. That's what we're all about too. And it's something that you can apply to your business, whether it be in this space, and you can apply it today. That's really what it's all about. So if you have your questions and you're watching us live on the social medias that we're going live, again, Facebook, LinkedIn, YouTube, and Twitter, you can ask your questions live for myself or our guests. And that's what's fantastic about this show in this format, going live, ask your questions that's topical, that's applicable to what we're talking about. We're going to make sure we get those answered for you as well. So if you're listening to us on your favorite channel, you can also just share it or tag the guest, and we'll make sure that there's ways that you can tag the guest. Today's guest... no more longer saying guest anymore. Today's guest is really special because they actually... they're coming from a business with so much background. Her name is Melissa Drew. She works currently at IBM. Yes, IBM, the technology data... you want to call it the software or hardware, whatever you want to call it in terms of technology, one of the leaders in the space that brought digital to the forefront. And that being said, we're going to talk about, today, hyper- personalization, what that means, and really what AI is impacting and how it's impacting retail and consumers alike. Again, technology across the board is going to inaudible in multiple different ways. Retail store, selling online. How is artificial intelligence going to be effectively impacting that, and how do you create a customer's personalization with in mind? But our guest today, Melissa Drew. She has 27 years of procurement and experience in supply chain, believe it or not, and industry and consulting across the board in multiple different companies, maybe countries as well, but she's a global leader in consulting excellence and influence as well. I'm going ahead. We had a little bit of an issue with audio, so I'm fingers crossed that we're going to have all that sorted out. Welcome to Crossover Commerce. Here's Melissa drew, IBM. Melissa, it's nice to be able to hear your voice, hopefully. Fingers crossed.
Melissa Drew: Can you hear me?
Ryan Cramer: And we have you. I've got you right. Perfect.
Melissa Drew: Actually...
Ryan Cramer: We're already on a roll, right?
Melissa Drew: ...your audio is a bit static.
Ryan Cramer: That's what I heard in the last podcast. Let me switch it over too. So, if it's a little staticky, I'm going to go ahead and switch it over my microphone. There we go. You got me okay, Melissa? Can you hear me a little bit better?
Melissa Drew: Perfect. Perfect.
Ryan Cramer: So, I apologize to everyone again. That's the beauty of life. We have some issues. I need to reset my computer, it sounds like. But, hey, welcome to Crossover Commerce.
Melissa Drew: Good. Oh my gosh, 167 episodes. That's fantastic. How many years has that been?
Ryan Cramer: So, for those who are listening, they will know, I say this kind of a bit because I think it's a cool pat on the back. I started this in September 2020, so just over a year when I did the math. That episode, it was honestly... I think I did a podcast. It was live every two business days. So we have lots of consistency here. You don't have to worry about that if you're a guest.
Melissa Drew: That's fantastic. I recently heard the term podcast phase, where a podcast just starts and then fades out, but this is fantastic. Congratulations.
Ryan Cramer: I appreciate it. Well, not an issue here. I always hear people run into that wall, right? But I actually started and I thought that would be an issue, but believe it or not, lots of people like saying yes to podcasts, but it's also... There's so much that ties into industry specific podcasts, but even you can kind of like draw these great conclusions too, right? Like AI, which we're going to be talking about today. Hyper- personalization. How does that tie back into e- commerce? Maybe if I can answer this question while we're talking with you today because you're an expert in all these different backgrounds, and while you're a consultant to all of these different things, we're talking about hyper- personalization. So, people might be asking why is that something that you like to talk about? So, first and foremost, let's give a quick background on yourself, Melissa. How did you get to where you're at? You're with IBM now, but what's that story beforehand?
Melissa Drew: No, I recognize that no one's path is ever a direct path from where they began to where they started. I started out in management information systems with Auburn University. I was one of those folks that did not raise my hand and said I wanted to be a developer. And then, a year later I am getting federal grant money and developing the first publicly used automated RFX with the Alabama apparel and textile company. So my introduction to data was early on, but throughout the course of my journey, it moved from manual manipulation of that data, and then systems and automation, technology, procurement systems. Then we moved into business and digital transformations, and then now we're at that intersection where we're applying these cognitive technologies. And so, when I define cognitive technologies, it's not the AI that can automatically learn on its own, it's the cognitive technologies like machine language, grammar based natural language processing. This is the technologies where you need a human to program those algorithms and models, and then you need a human to also intervene and adjust as more data flows in. So, I sit there, in that intersection.
Ryan Cramer: That's amazing. So, that might be like a little over people's heads, but I think it's fascinating to see how your use of technology can really enhance how systems work, right? At the core involved, that's what you're trying to do, is making things more streamlined or more effective, right? Would that be the easiest way or simplistic way to say what you do?
Melissa Drew: No, that's exactly right. And when we look at the agile organizations, so the term agile organization was coined around 2015, and the purpose of the agile, the agility, was to imply that customers were changing their demands and their habits more frequently, and as a result, corporations and companies had to be more agile to adjust to that. Well, that was back in 2015, but we still have all these gaps that we've not been able to fully meet. And as a result of these new cognitive technologies, that maybe have been around for a while, but we're now being able to utilize them because our technology has now caught up, where our cognitive technologies can now intersect, so we have faster processing that allows us to support this.
Ryan Cramer: Interesting.
Melissa Drew: So, 2015, where we wanted to be more adaptable to our consumer behavior, now we recognize that it's not just becoming adapted to the consumer behavior, we now have to personalize how we're interacting with that consumer behavior. And that's where hyper- personalization comes in.
Ryan Cramer: Okay, so that makes sense. This would be applicable... So, if I'm a listener and I'm thinking, " Where would this be applicable in my life? If I'm a consumer, where would I be most engaging in this kind of technology?" Is this on a direct- to- consumer side? Or where would I see the effects of this?
Melissa Drew: So, I'm going to start by giving a definition between personalization, something that everybody is experiencing, and then I'm going to define what hyper- personalization is. And then I'll come back and give everyone a real- world example that everyone in this audience would be able to recognize, and probably experiencing right now.
Ryan Cramer: Yeah, no, absolutely. So let's go and start. So, definition between personalization and... Why don't we start there?
Melissa Drew: Yeah. So, personalized. Personalized, you see this all the time. It's your name, your location, it references browsing history on one particular site. So, when you get a personalized email, it's because you went to the Gap where you went to Starbucks, or you went to someplace and it pulled the information on that site. But that doesn't really give you the full breadth of that consumer's experience, and as a company, like the e- commerce companies that we're going to talk about later, that doesn't allow the e- commerce companies to really target your needs. With hyper- personalization, hyper personalization is now going to say, " I'm going to not only get the information from the site you had the Gap, I'm going to get the information from your site at Amazon, I'm going to get your purchasing information at Starbucks. I'm going to look at all the information that you have across your digital footprint, and I'm going to pull all that together so that I can now focus my personalized experience so that it's specific to you, Ryan, specific to myself, Melissa, specific to Joanne, who's in the audience, specific to Tom, who's in the audience." Each one of us has slightly nuances in how we buy, what our reward preferences are, our communication preferences, our personal purchasing history and profile. And this hyper- personalization is only able to really become fully... to its fullest potential, because now we have the ability to take all that data into a single location, and then synthesize it with using these models and these cognitive technologies that allow us to come back with a targeted, hyper- personalized message or hyper- personalized experience in nearly real time.
Ryan Cramer: That's amazing. So, that would be personalization, and I think everyone's experienced that on a day- to- day basis, even nowadays. So, with the other end of the spectrum, like the other definition we're going to talk about, what's the difference and how is that going to apply here?
Melissa Drew: So, I'm going to give you two examples. In a personalized experience, you went to go buy a backpack on your e- commerce site and you got an email that said, " Hey, you left that backpack in... We noticed that you checked out but you never bought it." And because you were on that site, they can track how long you looked at the blue backpack versus the red backpack, so then, maybe two weeks later, you get another email, again a personalized email specifically to Ryan that says, " Not only did we notice that you never bought that backpack, but that particular backpack and the backpack that you were also looking at, they're both on sale in the same color that you were looking at." So, that would be a personalized e- commerce experience. Now let's take the same backpack and let's shift it to hyper- personalized. Same scenario. You get an email that references the backpack, but now the backpack is saying, " Hey, that backpack would be really interesting. It'd be a good time to try that backpack out this weekend on that hiking trail that's two miles from where you live, because we noticed that you went hiking there two months ago." And it would also include a picture of the hiking trail, like a view, to really get that visualized excitement, and it would tell you what the weather conditions are that weekend, so that you would know that it's going to be a good day to go backpacking. So, in the hyper- personalized example, it's pulling information from multiple sites that you visited, and pulling that information together to then really focus just on you, Ryan, that this is a backpack you want, not only is it on sale, but you went hiking two months ago, or two... Yeah, two months ago, and this backpack would be great on that trail.
Ryan Cramer: I think the first-
Melissa Drew: That would be one of... Yeah.
Ryan Cramer: I was going to say I think the first thing I think about is, " Holy cow, that's such a difference in terms of how that message gets delivered." But does that... Maybe the second thing, this is myself, is how detailed you got. Is that something that everyone can have access to, or people just collect that... If you go way too detailed like that, maybe, for example, you might scare away somebody, or you might think somehow you're getting intrusive to me as a person or a consumer. So is there... First and foremost, there's a couple of questions there.
Melissa Drew: Oh, there's a lot of questions here. Yeah.
Ryan Cramer: Yeah, I was just going to say. So, first and foremost, does everyone have access-
Melissa Drew: Let me give you one more example, because I want to make sure that we hit everybody in the audience.
Ryan Cramer: Let's do it.
Melissa Drew: Because not everybody goes and buys a backpack., but I bet you everybody buys coffee.
Ryan Cramer: Oh yeah.
Melissa Drew: So let's look at the personalized experience with Starbucks. And, again, Starbucks can be Dunkin Donuts, it could be Tom's Coffee, it could be any kind of coffee that you buy. When Starbucks was doing the personalized rewards offer, they would send out an email or a reward to your Starbucks app, and it was limited on a very few number of variables. Where you lived, your purchase history, geographic region or city. Now, the challenge with this, and I can attest to this, is two years ago I would receive a reward telling me that, if I bought something, I would get more points. But I'd never bought that item before, or maybe I bought it once a year ago, so those rewards really weren't personalized for me.
Ryan Cramer: True.
Melissa Drew: Well, now, what Starbucks has been able to do is, because again with the ability of collecting a lot of data from multiple areas, those few little variables that we mentioned a couple of years ago, Starbucks now utilizes over 400, 000 different variables weekly to ensure that I am getting a very specific custom message to me. So now my individual, myself, I receive very specific offers on my preferred location, my favorite orders, my spending habits, past purchases. They've even got a note... Your Starbucks app can even recognize that if you're on the highway, driving, and there's a Starbucks within two miles, a reward will pop up specifically for that location because of something that they're currently selling. And, on top of that, you look at it from the consumers... not the consumer's perspective but from the organization's perspective. Starbucks has noted that they've been able to increase... 24% of the total company transactions are now being taken place via mobile app because of these rewards and personalized hyper- personalized offers. Now Starbucks is saying, " Well, because 24% of our total US company transactions are taking place via the mobile app, Starbucks is now spending more R& D on the mobile app, not so much on websites and other marketing media."
Ryan Cramer: That's what's so fascinating, too, when you go at a scale of a company like Starbucks, too. People made the comments of, " Hey..." I mean, because we're a retail... or PingPong is a financial company, just in terms of the amount of money that is sitting in" rewards" in this baking institution, it's become theoretically the largest banking institution because of people putting money into it. And the transactional data, there's so much coming and going but it's all given to them to use, like you said, tens of thousands of data points to be so customization. You touched on geo tracking, you touched on just purchase history, you touched on lots of different... point of sale. There's so much in terms of which the demon now becomes creating a customer avatar, and you can now do an SOP or a standard operating procedure of, " If they bought this during... or in their... in this locale, and they did it on this device, then send offer X."
Melissa Drew: Yeah.
Ryan Cramer: So you can get-
Melissa Drew: And it works. I use it.
Ryan Cramer: And it works. Well, exactly. That's why I think... I had this conversation when I was a guest on a podcast as well. And we talked about the hyper utilization of targeting people. Like you said, you can do it on Facebook now, you can do it on all these different platforms. Is there a point at which it is aligned in saying that it's too far? And at what point is it no longer helpful and almost intrusive to a consumer? Is there a point?
Melissa Drew: Yeah. So, there's... And it's interesting because the industry term at the moment is the creepy factor. I have these conversations with my father, who's 25 years older than I am, and he's just at that barrier, right there on the line, where this is too much information. His culture and his background is that people don't share that much information with people. And while he likes getting recommendations on e- commerce sites, or he likes getting recommendations on the Starbucks, when I explained to him where the data was coming from and the fact that he was giving permission without really recognizing that he was giving permission, it really gave him this really odd feeling that... this creepy factor. Am I being stalked from a data footprint perspective? But then, on the other side, the feedback from the consumers... and Amazon did a huge survey study with their own group, but the feedback from the consumers is they like going to Amazon. They like being able to get those very specific, personalized recommendations about products that they didn't even know the product was out there. Because there's so much data now on the internet and there's so much consumption on the internet, how am I supposed to know if I'm in my little world of the internet, how did I know that what I was looking for, somebody else was selling it that far down... I mean, so the Amazon... the way they're doing those personalized recommendations is they're sharing information with you about products that you buy, that maybe you didn't realize were already on the internet somewhere else.
Ryan Cramer: Right.
Melissa Drew: And people are liking that. And the reason why people... I say that, is because, nowadays, with all the new privacy and the re- visitation of our terms and conditions, they've updated these terms and conditions. And when you say, " Yes, I agree to these terms and conditions," there's new clauses buried in there that says that you are willing to give them this information. You're willing to allow them to pull all the information from other websites as long as that information is being used to personalize your experience. So, at the moment, if you've been... Say you've gotten pushes from an app or from a website when next time you logged on, that says they've updated those terms and conditions, a lot of us still just say, " Yeah, great. I agree,", and move on. They don't take the time to read what was being updated.
Ryan Cramer: Yeah, absolutely. So, I mean, there's a couple of different ways we can go in. In terms of security or in terms of just where is all this data being collected from, is there a point at which... How are these companies getting ahold of it all? There's a lot of different ways, I would say. I'm with you. I think I enjoy the customization of it all. But then there is that industry term we can coin and say the creepiness factor of it all is... you always hear it... of, " Hey, we were talking in a room one time about product XYZ or or trip XYZ, or whatever, and then, all of a sudden, the next time we go to social media or a commerce site..." And I started to see either ads or pop- ups or something like that in terms of, " Hey, you were intrigued by this and how the conversation..." Not in those terms, but it references almost a conversation that you had, and people are like, " What the heck?" And it can come from different ways. It comes from audio, obviously, if you're talking or engaging on a podcast like we are, or it could be something as your search history, right? Is there a point at which... I'm going to go the security route... Is there a point at which that data is not being collected to create a customer avatar, no matter whom it might be for, at this point in time?
Melissa Drew: At the moment, the updates within those terms and conditions specifically added in the terminology that the data that's being collected will be used specifically to improve your experience, to improve your recommendations. If you find that your data's not being used for that purpose, or you find that you're getting information that doesn't seem relevant to you, that doesn't make any sense, then, based on our privacy laws, you can immediately unsubscribe or decline. And those companies are now... it's mandatory, a federal requirement, that those companies have to remove you off list within 30 days.
Ryan Cramer: Sure. Makes sense. I mean, yeah. And you would need to be protected in that regards. Obviously because we've seen data being sold and repurposed and whatnot, consumer... I mean, we've had it, right? There's been lots of data collecting in terms of general... in terms of making relevant information possible. For example, I know people say the cookie- based ecosystem with Apple and whatnot, that's... and Google having all these different kind of back and forths, and how much information you're going to be able to release or get now in terms of those outside third party issues now. People have always been requesting data like this. For example, in the mail yesterday I got the Nielsen report. That is something in terms of data, like viewing habits, how often are you going to be viewing such programming in your specific area? In theory, they're paying you for that information. The$ 2 bills that they gave us yesterday in terms of just, " Hey, we're buying information from you in that regards for feedback and customer journey." So, either opting into it or, by definition, agreeing to the terms... I won't put quotes around that... there's lots of different ways people are still garnering information from you to create that hyper- personalization experience.
Melissa Drew: But I agree with you that sometimes it goes too far. And I said I had a story for you.
Ryan Cramer: Please do, yes?
Melissa Drew: I play Township with my daughter. It's something that we... We go together, we build, we township.
Ryan Cramer: The mobile app, correct?
Melissa Drew: The mobile app, yeah. And what surprised me is, I'm used to getting requests for my data from e- commerce websites, from Starbucks. I get that from the online bookstore. But what really surprised me yesterday is I got a push notification from Township, asking me if they could collect data from multiple sources on my phone for their purposes. And I immediately... I paused and I was like, " Am I reading this correctly? This came from the game." Now, in my scenario, I declined because I'm playing the game with my daughter so I don't want any additional... But it's the first time I've really experienced someone asking me about being able to collect data from multiple sources beyond the game for the purposes of a video game, and that surprised me. So, for me, I'm starting... I see. I've experienced where maybe some of that data requirement is expanding into multiple areas beyond what I thought would be the norm.
Ryan Cramer: Wow.
Melissa Drew: And then the other-
Ryan Cramer: crosstalk. Go ahead.
Melissa Drew: Oh, I...
Ryan Cramer: I was going to say... Yeah, go ahead. Sorry.
Melissa Drew: No, you're fine. Go ahead.
Ryan Cramer: No, I was going to say I was speculating in that regards. I'm assuming that'd be for ad purposes? If that would ring true to you, of, " Hey, we want to make sure that we're sending you the right ads?" Again, in theory, for the best purposes and they can serve targeted ads to you for people to purchase through their ecosystem. But, again, I understand. It's a little tricky in terms of the game...
Melissa Drew: I'm not exactly sure, yeah.
Ryan Cramer: No, sure. I don't care what ad I see in a mobile game. I don't think I want it to personalize to me. That's not why I'm here.
Melissa Drew: No. Yes, that's true. And you talked about privacy. I wanted to go back to that one because there's limits... I see some really big gaps in what we're doing with those terms and conditions. You mentioned a minute ago around not only collecting data for the purposes of supporting your recommendations and your personalized habits and rewards offers, but also potentially selling that data to the parent company. Or your parent company is where you currently have that relationship, and as part of your terms and conditions, they're saying that they can use this data not only to support, say, e- commerce within one of those... I hate to keep using Amazon but it's such a normal, common thing. But not only to be using it with that company that you have the relationship with, but also to use all of that with maybe a subsidiary or affiliate that they have some investment or stake in. And, for me right now, a lot of these terms and conditions, when I started reading them, it's all or nothing. If I want to do business with them, I have to accept the entire terms and conditions, and not only allow them to collect the data to support me with that relationship, but in some cases it's expanding that footprint into their subsidiaries. What needs to happen is more of a... Let's go this way, a hyper- personalized view of my terms and conditions. Absolutely Amazon can take my information because I love what they're doing with it, but absolutely not do I want Amazon to share that information with a company that they happen to own.
Ryan Cramer: Right. So you can go down the route of... we're using Amazon. For example, Amazon owns lots of different companies for lots of different things. Their industries span into video streaming, to grocery shopping, to... obviously their subsidiary companies that they actually outright purchased. So you're saying...
Melissa Drew: Like Zoox earlier this year.
Ryan Cramer: Right. So, in theory... that exactly. So, if you're purchasing... If you agree to those terms and it's all or nothing, in all you can share that information with, for example, Zappos. com, which is a shoe and footwear e- commerce company. So, in theory, if you're buying lots of different apparel or stuff like that, you can, in theory, start sharing that information and say, " Hey, customer XYZ buying lots of shoes. Send a targeted email or mailer or something like that to them for a coupon." Or, " Hey, start shopping as well on Zappos or CPM," or anything that they might have. So t's interesting to say all or nothing. So, where do people go from there? Is it just the share... Like on the apps right now, I think... I have an Android, and you can just share your targeted information, just let this app this one time, or forever when you open the app, or at all times. Is that where you start to get more hyper- personalized in that regards, or what are the steps to go there?
Melissa Drew: At the moment, the organizations are responding to the consumer, and the consumer is not having any challenges or pushing back on accepting the updated terms and conditions. So, at the moment, we're kind of at that stabilization point where some of us are kind of seeing the foreshadowing of the future, where it's getting a little... the creepy factor, or maybe it's going to go a little bit too far. But, at the moment, majority of the people that are online shopping are signing off on those terms and conditions, and those are the individuals that are saying, " I'm okay with this as long as the data's being used to support me in my experience." I think what's going to happen is, because those terms and conditions are all or nothing, people are going to start pushing back, not right now, but in the near future. And then we're going to start seeing changes in those terms and conditions that are a little bit more, " You agree? Check yes here if you agree that we can use your data for this website for your experience. Check here if you're okay that we send your data to other companies that we own or have an affiliate with. Check here if you're okay that we use your data for the mailing, direct mail, the catalogs that you get in the mail." Amazon just sent me a catalog yesterday. I didn't even know they had catalogs.
Ryan Cramer: They do. For Q4, they start sending those out. Like the good old, I always say Toys R Us holiday shopping guides. It's probably the holiday shopping. I'm excited to hopefully maybe get one today, too, now that you mentioned it. I'm sure I will.
Melissa Drew: And it's very personalized. It has lots of... This is really good marketing. The catalog, when I sieved through it yesterday, about every 30 pages there's an activity for my children. There's a coloring activity, and then 30 pages later, there's a crafts activity. 30 pages later, there's a puzzle, 30 pages later, stickers. They've actually got two options of stickers in there. Which is interesting because, even though it was sent to me and has my name on it, it's really been marketed to get my children into the catalog so that they can play but also see things that they want for the upcoming holidays, and say, " Hey, mom, this is what I want. This is what I want. This is what I want." I mean, it was really, really creatively done from a marketing, e- commerce kind of sales perspective.
Ryan Cramer: I was going to say, is there a step further, where there's a QR code there, where it can send you directly to that on the app if you scan it?
Melissa Drew: I don't know. See, now I feel like I need to run in there and go grab it.
Ryan Cramer: No, it's okay. No, this is getting people on the hook, for all of our listeners here, at least in the United States, I would say be on the look out, maybe, for a targeted Amazon... I think it's so fascinating, too. I would agree. I know when I was a kid, I would always, in that regards, circle everything and say, " This is what I'm intrigued by." It's almost like my wishlist, and I was creating an offline wishlist. It would be interesting to see, instead of just search, find, buy, essentially, now it's, " Hey, send directly to the product listing." And that's a point of contingent where you can gather that information as well, know how many people are driven to that page and purchase from there. So, again, another data point, and say, " How effective is that marketing that we did? Quite well and the success rate is high. Now I can sell space in this a hundred page catalog now for brands who want to be successful and get in front of people. We'll send out the mailer, but, hey, you have the ability to convert a high percentage of your sales simply through that. So that's interesting that they're reverting back to almost the" old mentality" of circle and tell mom and dad, " This is what I want for Christmas or holidays."
Melissa Drew: Yeah. Before we shift into some of the... I mean, because we've been talking very positively, very forward- thinkingly, very innovative. I want to just emphasize that with some of the statistics. But then I think there's a whole nother side to this, which is are they getting the right data, and...
Ryan Cramer: Right. Great. That's where I would take that to.
Melissa Drew: Yeah. So, right now consumers have this philosophy, " See me, know me, understand me, and show me," and they're emphasizing that with the statistics. 59% of the consumers believe it's extremely important that brands make their needs heard. 85% of the people that were surveyed believe that the brands need to align to their values in a significantly better quality. More consumers are ranking brand reputation, service personalization, and brand loyalty, more important now than they did a year ago. So, every time there's these surveys that are going out there, we're still hitting high numbers, high percentages, where the consumers really... they still want to be engaged by the brands, they want to be engaged with those personalizations. And those personalizations are going back to, the consumer wants you to see them, know them, understand them, and then show them that you know them.
Ryan Cramer: Sure, absolutely. I mean, those are all great statistics and I would agree. You want people to have that engagement factor and people know that they can get in front of you and make their voice be heard. I think that's something that people just expect now, and that will continue to rise as a, " Hey, my voice needs to be heard, whether it's on social media or it's on, you know, just in customer survey or ratings or reviews on Amazon listings." That can be the positive or the negative that hits a brand and can" go viral" or it can impact their sales and whatnot. So I would agree, it's important. So, you alluded to it, there's a negative side to it and there's a scary side to it. What are those things? Help me figure out and explain to the person, " Hey, maybe it's too much at this point?"
Melissa Drew: Yeah. So there's always... There's pros and cons of everything.
Ryan Cramer: Sure.
Melissa Drew: And the reason why hyper- personalization is more available now than it was even a year ago is we've got companies that are collecting multiple data sources. The 400, 000 different variables of data that's being collected for Starbucks to make sure that you get that hyper- personalized experience in the rewards app. I interviewed a company a couple of weeks ago, and they said that the minimum number of data sources that they're pulling to ensure that they have a comprehensive consumer data footprint is 130, 000 data sources. And that's not just the data sources that's being created from their website, that's external data sources. That's collecting Google searches, that's collecting every piece of data that they could possibly come up with, and they've got 130,000 data sources. So one of the things that we've noticed in this is not all data is equal. So, for example, a friend of mine, recently her father passed, and she was out there on the websites looking at funeral services. Next thing she knows, because of her search history with Google, somehow that data got pushed out to other organizations and she was getting flooded with phone calls and mail, and direct mail via email, about caskets and funeral services for herself. She's like, " Man, I'm only 30. This isn't... I don't need this." But she can't find a way to undo it. So part of that experience is, " Yeah, we're out there searching, but sometimes we're not searching for ourselves." Especially if you have a family, you're searching on behalf of somebody else who maybe doesn't have the time to do it, and then that search is now being correlated to you. And then you're getting flooded with all this additional information and content that's not even relevant to you at all, and you can't find a way to stop it. And then the other component to this is, even though we've got 130,000 data sources in this one example, not all data is equal. So I could go out there and search on information around mountain laurels and wondering why there are yellow leaves, but there's so much information out there that I'm overwhelmed with it. Versus the other half is I've got so much information out there, but not all the information is going to be exactly what I need to make the right decision about that individual.
Ryan Cramer: That makes... So, I'm sorry, I'm processing through that and I want to make sure...
Melissa Drew: Yeah.
Ryan Cramer: 130,000.
Melissa Drew: 130, 000 data sources.
Ryan Cramer: Data sources.
Melissa Drew: This one company confirmed, yes.
Ryan Cramer: It's almost... At a certain point, what other... What data makes it differentiating from one versus another? So, part of me is like, " What's relevant..." Like you said, I think relevancy is the biggest thing that I'm really getting hung up on. I can't imagine that there's 130, 000 unique data points about creating an avatar for me, myself, that'd be relevant to inaudible as a customer for us or not, to make those quite honest decisions. You can probably get my age, my, look how I'm married or not, my income. There's no way... I can't even imagine what 130, 000 different unique sources would tell you that would be distinctively different from one to another. Is there anything that would be? Or if I shopped on there, is that a yes or no, that would be a data point. I can't imagine that would be relevant to this kind of thing.
Melissa Drew: Yeah. And that goes back to not all data is equal. Not only is it a lot of data, but then, are these companies actually collecting the right data that's going to make an informed decision, that's going to allow them to personalize the experience for me. And with Starbucks, it's a little bit easier because they're collecting 400,000 variables, 400, 000 data points that, even though I may not need all 400,000 because I think I'm pretty simple with what I order and I'm pretty...
Ryan Cramer: You've got your go- to thing.
Melissa Drew: Yeah. Pretty much got my go-to thing. But the 400, 000 data points is supposed to be able to support the hyper- personalization for all types of buyers and purchasers. Now, we talked about not all data is equal. So let's take this one step further. I don't know if you heard it, it was on the news this week. I think it was Wendy's was one of the... It could be Wendy's, but it was a fast food restaurant that said that they're now going be including AI along with visual recognition at the drive- through, so that you don't even have to talk to a person. It will scan your license plate, your make and model of a car, it will take a visual image of you using visual recognition, vocal recognition, to check and see what your past history of purchases were, to automatically have, " Hey..." As I'm driving up to the drive- thru, " Hey, here's everything you purchased from us last time. Do you still want all this or do you want to change it?"
Ryan Cramer: So I can roll up to a Wendy's drive in, I can... they're going to say, " Your past order was this. Your junior bacon cheeseburger, your spicy chicken nuggets, you got a large coke," just because they can look at facial recognition, and using that-
Melissa Drew: Facial recognition, they'll scan your license plate. We already have license plates being scanned when we go through toll booths. We've completely gotten rid of the people at the toll booth because we can automatically scan your car and your license plate, even if you drive through 70, 80 miles per hour.
Ryan Cramer: Right. The iPay, or whatever, technology. You just have the sensor and it charges your account and whatnot, and then... Yeah. I note that. That's interesting that fast food would do that.
Melissa Drew: Yeah, but there's a story here, though.
Ryan Cramer: Yeah, go ahead. Sorry.
Melissa Drew: The fast food is able to... because then we're going to bring this back to e- commerce. If fast food is able to successfully launch this and remove the individual, then that means that the next time you go to a physical store, they can scan you, they can get your vocal responses. And before you walk in the store, they could have a hologram that pops up and says, " Hey, Melissa, we noticed that online you purchased this sweater," and I'm walking into the Gap and I ordered something online at the Gap. " We actually have the sweater here. Would you like to see it in a different color?" Again, moving that hyper- personalization. Because, right now, hyper- personalization is data- driven, on a website, in an email, maybe in a direct mail catalog, but where the technology's going is, it's increasing that hyper- personalization to be something even more significant than what we're experiencing today.
Ryan Cramer: Right. I mean, you even start to see it alluded to, like the Amazon go shopping thing. For example, if you're tied to your prime store account and whatnot, all you have to do is literally just pick it up and walk out. You don't even have to engage with an individual, they just know what you're taking, who you are because of your data point. You might have to scan something but, I mean, that's on that way.
Melissa Drew: Mm-hmm (affirmative).
Ryan Cramer: So, I guess most of what the... A little bit amount of time we have, we have a little bit left here, you're working on all these components, correct? You're associating where... It's almost like with great power comes great responsibility, right?
Melissa Drew: Yeah.
Ryan Cramer: The whole adage of, we want to use technology for good, not evil. If there's a pro, there can always be a con. So, what's the end game for companies like yours that might be creating these kinds of personas in this technology and availability, for things out there?
Melissa Drew: I think what's really interesting, and we haven't really thought that far out yet, but the whole idea of hyper- personalization is to personalize your experience. But if we continue to go... kind of what the fast foods are doing, and take that same technology for the brick and mortar stores, then that hyper- personalization is actually taking the person out of the hyper- personalization, which is kind of interesting.
Ryan Cramer: Exactly.
Melissa Drew: We're not quite there yet, but the technology is so fluid. I mean, just in the past year, we've really been able to spend more time on vocal recognition, looking at the emotions, reading not only your facial features, but being able to hyper- personalize your experience. Another example, and I'm sorry I keep telling... giving examples, but going back to e- commerce on the website. You go to a website where you're looking to buy something, and through your camera it recognizes that you're not feeling good or you're not smiling, and it might ask you some questions about how you're doing today and how it can help you, even though you're there to buy a sweater online. So it's interesting that we've got all this technology, we just need to, kind of what you said, the responsible AI, AI for good, but really balancing how far is enough going to be, where we've removed the person out of that personalized experience.
Ryan Cramer: Yeah. I would agree. I mean, I think there's the whole adage of technology and how far is too far, and what are you streamlining, what are you removing? Because ultimately that could be at the result of an individual, like personal greeting or... the greeter at Walmart no longer is there, it'll be a hologram, and each person gets their own little greeting and saying, " Hey, Ryan, we know you came in for groceries, and that one item for the party you have later this week," or something along those lines. " That's going to be in aisle seven or eight." That, to me, sounds almost helpful, but then you try to start thinking about, "Well, how did they get that I was going to have a party later this week, and how do they know I was going to do... I'm in here for these things?" So, again, it's that nice line between, are we just accepting of it because now it's being served at some sort of scale and that's just... we're used to it by now. We have lost our feelings or that edge, if you will, that we've always had, like, " Something's wrong. I don't know what it is, but it doesn't feel right." Or we're just kind of numb to it after so... So, if you get used to it over time, maybe you're just numb to it after a while.
Melissa Drew: Yeah.
Ryan Cramer: So, that's where you see it going long terms, right? And so what's exciting for you right now?
Melissa Drew: I think all of this is going to be dictated by the consumer. At the moment, everyone's going to keep moving in this direction until the consumer changes its mind.
Ryan Cramer: So, what's... Yeah.
Melissa Drew: Yeah.
Ryan Cramer: I was going to say, so what's exciting for you right now, as we're wrapping things up? With what's happening, you'll see lots of different customizations, personalizations. Like you said, you got an interest... you got a catalog for that. What's exciting for you in this space right now that kind of gets you up in the morning and excited to work on or talk about as well?
Melissa Drew: I think this is a really interesting topic because, at the moment, we're very focused on hyper- personalization in e- commerce, which is where we've seen this grow quite exponentially in the past 12 months. But now I'm seeing healthcare wanting to look at hyper- personalization for its patients, and using more technology to try to make patient diagnosis and that personalized experience for the patient. So it's interesting. We started in e- commerce and it's going to continue to grow because that's where the consumer demand is, but I'm starting to see the same concepts and technology moving out into other sectors. Healthcare is next, and then I'm seeing it in automotive is probably the third.
Ryan Cramer: Wow. I mean, I'm excited about the future but I think that's so fascinating. Again, where demand is, it's almost where do you want that next step to be helping people. I think that's always the first thing, right, is how do we help solve this problem? But then it has these unforeseen effects, if you will, almost like with social media creation or personalization. It was created to stay in touch with those long time friends. Then you have this underlying effect of all these kinds of other problems that stemmed from that. So, again, with every pro comes cons. Hopefully all this power has come in useful. I think it's really exciting and fascinating. I'm going to say fascinating because that can go either way.
Melissa Drew: It is.
Ryan Cramer: We'll have to keep an eye on it.
Melissa Drew: It's fascinating, but I think what we've highlighted here, if I kind of summarize it, is that not all data is equal.
Ryan Cramer: I agree.
Melissa Drew: And everything that we talked about pushes out even deeper into security and privacy, pushes out even more into data ethics, pushes out even more into data bias. Everything that we've talked about is like the baseline of the e- commerce hyper- personalized experience. But because of some of the things that we've touched on, there's this circular around the heart of that, which is all these other components that we're still trying to figure out and they're still fluid.
Ryan Cramer: Fascinating stuff. I love it. Melissa, I know I've taken way more of your time than I should, but crosstalk.
Melissa Drew: Who knew we could talk a whole hour on this topic?
Ryan Cramer: I told you before we started, pre- show, talking an hour is not a problem for me anymore. This podcast is always super fascinating and I will get every ounce I can with my guests. But that being said, if people... if they want to reach out, they have questions, they want to get maybe a little bit deeper than what we did in this last hour or so, this last episode, how do people connect with you? What are those best ways to ask questions?
Melissa Drew: LinkedIn. I am completely open on LinkedIn. I've communicated multiple times that I am freely open, love virtual coffees, I have no problem sharing my knowledge. That's the whole point of how we're going to be able to move forward together. And then I'm also associate editor for AI Time Journal, so some of these topics that we've talked about, the data bias, we're exploring those deeper in the AI Time Journal as well.
Ryan Cramer: Very cool. I need to be a subscriber to that too, because that's something that I am continuously fascinated by as well.
Melissa Drew: There's a lot to unpack. Yeah.
Ryan Cramer: I'm going to keep using fascinating. But, hey, thank you for hopping on again, now a friend of the show of Crossover Commerce. Melissa Drew, thank you so much for coming on.
Melissa Drew: This was great. Thank you.
Ryan Cramer: Yeah, no problem. Thank you so much. And, again, thinking everyone else who tuned in live or just watched or listened to our podcast. This is, again, my corner of the internet that I like to call Crossover Commerce, where we take the... Again, I explained this on another thing earlier today. Crossover, in the terms of PingPong, is going to be your weakest point of your game, and I think being able to talk about the strengths in the industry and where you can use information like we get from our guests in this space is, they're going to strengthen that part of your" game" in this case, e- commerce in general. Super fascinating stuff. I'm going to keep saying fascinating a lot this episode, and see how many times it can be said, but how does the industry change? How do we use technology for the betterment of, again, consumers? How is the customer going to dictate where technology needs to go or wants to go? I think companies like IBM and other ones in the space as technology develops. Hopefully we don't get numb to it. We still want to have those barriers up that sense, " Hey, this is a little creepy," or" This is a little bit more pushing that boundary. It's too much." Then maybe, in general, as we continue to go down these paths of efficiencies, personalization, hyper- personalization as we like to talk about today, who knows what's going to happen? I think it'll be fascinating to see... Again, there it is again... a virtual assistant coming up to me and saying, " Hey, you don't look so well," or, " You might be feeling ill today," or, " You came back," and they already have my... I'm going to Wendy's and they're taking my order before I even know what I want to order. Because most of the time it's... Maybe they'll know. Maybe Wendy's will know before I will know in that regards. But thank you again, Melissa, for hopping on today. Again, everyone, this is Crossover Commerce, episode 167, presented by PingPong payments. This is my corner of the internet. We have great guests that come on every single week, and tomorrow... today was no exception. Tomorrow will be even better. I won't say better. Also fantastic, because we have... we'll be talking about insights to building a foundation of successful brands online. We're talking with Matt Parker, Pinformative Group. We're talking about Pinterest tomorrow. So, driving traffic from Pinterest, how Pinterest is actually evolving in terms of e- commerce, but also as a social media platform. So we're going to be talking along those lines tomorrow. But if you're a guest of the show, again, make sure you subscribe to our social channels and subscribe to our podcasts wherever you might listen to it. There's lots of great content on as well, and you can find this at usa. pingpingx. com/ podcast. Thanks, everyone, for tuning into Crossover Commerce. We'll catch you guys next time. Take care.
Ryan Cramer of Crossover Commerce talks with Melissa Drew of IBM one-on-one about Hyper-Personalization and how AI is impacting retail & consumers.
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