Ret__l: Helping you put AI in retail

Thank you, everybody, for joining us for our webinar, Reit Ol, helping you put AI in retail, presented by TTEC and Microsoft. Our agenda today, we are going to do a quick introduction on TTEC Digital and who we are, assuming you have a pretty good understanding of who Microsoft is. We will then go into some retail industry trends. From there, go into AI's role in delivering exceptional customer experience, and then we're gonna wrap with, going into a real world case study. The presenters today are myself, Cliff McCartney, vice president of digital sales at TTEC Digital, Erin Schroeder, director of AI and analytics solution at TTEC Digital, and Doug Adams, special guest, general manager from business applications in the retail and consumer goods space with Microsoft. So a little bit about TTEC Digital and who we are. TTEC Digital is a leading global customer experience consulting and technology services firm. We offer experience consulting, software, and technology services at the intersection of contact center, CRM, and AI and analytics tools. We refer to this as the point of conversation, and that that intersection is represented by a speech bubble that you see at the center of our badge here on the screen. We do this to create shareholder value for our clients through revenue growth, cost reduction, and productivity improvement. To go one level deeper, TTEC Digital has best in class Microsoft capabilities that's been recognized in many ways, from being a multi time winner of Microsoft's global partner of the year in Dynamics three sixty five to being recognized as an inner circle partner for both business applications and AI. Now our deep expertise in AI and analytics helps our clients personalize the customer journey, augment agent productivity, increase revenue, and improve operation of operating efficiencies. We have helped deliver on many global initiatives across multiple industries with a very strong presence in the retail and consumer goods industry with a few examples here on the bottom right of the screen. So now I'd like to hand it off to Doug Adams, general manager of business applications in Microsoft's retail and consumer goods business, and he's here to here to share a little bit more on today's retail challenges and top priorities. Doug, over to you. Thanks, Cliff. Always a pleasure and great to see you, and thank you all for joining today. Retail and consumer goods are facing, you know, unprecedented challenges. We thought our our challenges were over when COVID, quote, unquote, disappeared. But, really, it's never been true. Our our customers and and you all are facing new challenges. So how do you grow top line acquisition, top line revenue? In an era today coming out of post COVID, we had the option to go to multiple places. Oftentimes, our true our choice to go to individual locations was based off of inventory. And when inventory is there, awesome. We're having a great time. But to grow that top line revenue today, what we're seeing is that you have to drive a better loyalty strategy and really think about how you can utilize AI to understand and personalize each and every one of those messages. How do you drive cohorts back into the store? How do you use things like omnichannel to understand who the customers are and where they are? So it's really taking this concept of understanding our data and maximizing it, turning it into revenue. And as we understand that revenue, how do we meet customers where they are to change their own shopper's journey? The more people that are are driving through, through omnichannel, we're seeing an increase in revenue across that journey itself. And then, of course, things go wrong in retail. Things go wrong in consumer goods. How are we thinking about that from a talent acquisition and retention perspective? If we're not thinking about our employee experience, we're also leaving out the customer experience. So, fundamentally, what we're seeing is a number of, challenges. It's around driving loyalty. It's around driving top line revenue through, through the use of AI, but also through the use of some of the traditional stories that we're seeing in the marketplace. It's about understanding the data, transforming that customer experience, using that customer experience around where customers are, where they're going, how they're getting there to really transform again the, supply chain side of things. So if we know where customers are interested in, we know the products that they're interested in, we know to make sure that they're on hand, we know how to, to understand what might be impacted by a storm. How do we redirect inventory? How do we see that inventory as as low in one area but high in another? All pulling together a single point of pane of glass to really help us understand that overall experience. And then as we're doing that, we think about that talent and acquisition piece. Our employees we're seeing absolutely have seasonality into what they do and where they go and how they do it. But how do we maintain that steady guidance throughout the process? Oftentimes, and you'll hear through the case study today, it's about how do we get them from onboarding to the to the floor faster? How do we help understand what those barriers are in that hiring process? More often than not, it's an internal barrier that we face, which is our own calendar. How do we find the time to meet with those prospective employees? And so what you'll hear today is an area that we've been able to dive in together with TTEC to really help help transform that process. And that's not all. Right? When we think about the numbers behind these stories, it's about a six hundred and sixty billion dollar productivity gain for organizations that are using AI in this space. And that comes from understanding who your customers are, where they're going, but also traditional use of AI to understand what supply chain data might be out there, but also thinking about productivity of creating presentations, creating, stories back to the, from a consumer goods into a retailer, from a retailer going back to the consumer goods organization to share what trends they're seeing from a numbers perspective. And then, you know, very specifically, we're seeing about a two and a half times profit increase for, over organizations that aren't using AI today. And the the number that I found here, from IDC was really fascinating. Three dollars and forty five cent return for every dollar spent on AI. And that can, again, it could be across your hiring practices. It could be across your lead gen and marketing campaigns. It could be a loyalty offering that you're using to to be able to transform and understand who might be buying via credit card, but not a loyalty member. How do you drive loyalty? And as you drive loyalty, you get increased benefits back out. And then really thinking about how I can drive productivity my day to day as simple as responding to emails faster and understanding what, new products might be on the floor. And so, we're also seeing AI come into space, around the employee experience relative to things like, what do I do? How do I ask an agent or a bot, you know, a a spill on aisle four? A light bulb is out. There's a hurricane coming. What does that procedure look like? Point of sale is down. All of those things can be utilized through bots and agents to help answer those questions faster, resulting in a time savings and greater productivity. And so all of those things kinda lead to ourselves, to be thinking about how are we helping organizations truly maximize the value of the data, build a an intelligent, real time sustainable supply chain, how do we change that shopper journey, and how do we transform that customer and really that employee experience. And so, Cliff, those are some of the things that we're seeing in the market today, and, I just appreciate you having me on. Absolutely. Thanks, Doug. Really appreciate your insight into the industry there. Now, over to, Aaron. Yeah. I appreciate it. And so to build a bridge here between what Doug's talking about and and some more of what we have to share, you know, we're we're entering this new era of personalization as we call it. So historically, there was there was always this notion that you had a message. You wanted it to receive be received by your customers, and they were gonna follow your process. That was it. That's what you had, and we needed to continue to differentiate. And so, this evolved into the customer's context and your process. So while it's still the steps you you deployed and and had to take in a very serial sequence deliberate sort of manner, you could fold in more about what you knew or or how someone had interacted with you in the past to be able to start to to add some personalization. But really now, we've we've entered this this final state of their context, their journey. So the the serial static processes of old are are no longer the case and that really, you know, as Doug highlighted, represents the immense opportunity here with AI in in this new age. And so when you incorporate, what you know about your customers and and how they want to be interacted with and and allow them to guide it, you're reducing the effort they have to take. You're reducing the friction that they're really going through and engaging with you, ultimately leading to all sorts of better end states, deeper loyalty, stronger engagement, all of that. And we'll talk more about what that means. So here's what that looks like inside of customer insights journeys, for example. So when we say contextualizing and and having these sorts of dynamic journeys, I just wanted to show real briefly what this looks like, you know, in in, an example, loyalty journey and the sorts of inflection points and decisions that can be made or or triggered that allow you to drive this sort of engagement and personalization with the individuals that you're looking to strengthen that loyalty with. So what that means is driving better customer experiences at every stage of the journey. So you're generating more demand. You're closing more sales. Your engagement is superior. Your service goes from an oh no and an angry customer to something that really you can meet them where they are. You can display better empathy and engage with them in the right way at the time where they're having a difficult moment and strengthen the loyalty in the end ultimately. And we've got, a handful of stats here along the bottom, that that illustrate what can be done in in leveraging, AI and analytics to drive this kind of, personalization and improve every step along this journey, whether that is, improving incremental sales, expanding your targetable universe, or even just improving customer response rates to things. You know, that better engagement leads to better lifetime value and better loyalty. And, really, when we describe this as a journey, it's more of a flywheel. So what I've I've got here to to share is the flywheel of CX Insights in Action where you start with the data you have and perform a detailed analysis on that. Learn what you can learn to the best of your ability about, all of your your customers and and everything you have available to you. Be able to move into a phase where you categorize and prioritize these. This is brainstorming. This is soliciting feedback from the front lines but also where you're strategically looking to head to then execute actions. Whether that is employee retraining, whether that's new types of journeys or new types of offers or even product feedback loops because you get real time results from all of that that then feeds back in again. And so the entry point can be anywhere here. The the real takeaway is, to start now and to be deliberate about it. This flywheel is really important because, again, it continually, adds value. And so what this looks like, we've got some example Power BI dashboards we've built off of, some of our our datasets here to to just show you that visual analytics is a great component of this and and how you're able to, start with that detailed analysis and insights, be able to understand the kinds of, hidden representations and meaning in that data to then turn it into action. And again, the flywheel keeps running. So bringing this to life a little bit here in a couple, example methods. So, you know, I've talked a lot about, engagement and what, what that means and what that brings. Engagement optimization can take a few different forms. And so whether that's reach and response modeling, do you understand what the potential drivers of engagement are and the likelihood of someone to respond or respond well or respond on a certain, method is very important. Lead prioritization. Do you know who to reach out to? We hear this a lot from our customers. There's a lot of times it's a it's a time constraint. It's I've got a pool of of thousands of people to call and I've only got so many people. How do I optimize that? And so being able to rank that, know, you know, through the analysis of all of your data, who to reach out to when, what is the smarter, ordering of all of that can significantly increase the results you're getting from some of those, outbound campaigns. And finally, channel preference optimization as well, knowing where your customers want to meet you and then proactively meeting them on that channel. And and that can sound really intimidating or something really difficult to folks, but what I put on on the side here is is an example of the no code setup for doing this inside of customer insights journey. So in this example, it's it's sending a discount, a coupon, and you can see, well, what we're looking to do is complete that purchase. And you can see it in there, the email, text, push notification. There's a lot of different ways you can you can meet someone, and sometimes it's multiple. And so being able to set that up and and drive that through in a personalized way, but still in a consistent journey with a meaningful goal that you have, which is completing the purchase, you know, really, brings that together again in a in a more accessible manner than ever before. Now the next one is, loyalty a loyalty refresh. So a lot of our customers, a lot of folks we talk with are undergoing new loyalty programs, are looking to better restructure and emphasize their existing loyalty programs. So loyalty, we have to remember, is an outcome. It's necessarily an an end metric you drive. And so being able to understand who to target for enrollment, who should you be going after with that, you've got to look at that universe of of potential and then be able to identify, who to go after and and, you know, what it means to acquire, individuals into a loyalty program, but then the drivers of it as well. So when we say loyalty is an outcome, it really can be, deconstructed into a few different elements. And the more you understand about what leads to a lifetime of loyalty allows you to better target specific initiatives and and optimize your resource spend and coach your frontline employees and put the right information in their hands to make that possible. And finally, rewards optimization as well. Are you offering the best thing to the right person at the right time? You don't want to sacrifice more margin than you have to when sending coupons out there. If ten percent will do the trick you don't have to send twenty five percent but still knowing what is going to move the needle for them and making sure that they feel understood and valued through that communication and through any of your journeys. So on the far right here, again another no code built in AI model for customer insights data that helps show what leads to customer lifetime value over a certain time horizon. What percentage of customers fall into different groups? And then what were the influential factors on that? And so again the the back to the flywheel notion here, you're starting with a detailed analysis and understanding putting that into action action and then continuing that right back around for for, superior ongoing value. So at this point, I think, Cliff, I'll hand it over to you to talk about how some of these things really became real. Yeah. Absolutely. Well, thank you, Erin, and, again, thank you, Doug, as well for for your insights. Now I get to talk about making it real, right, making it real in retail. So this is a a real world example of how we helped automate a hiring process for one of our clients. So like any good superhero, our application and our story here has an origin story. So so we had a top five national coffee company. They came to us with a problem. So they had a great culture. Whenever they would interview candidates, the candidates would see that. It's very apparent. They can when when offered a job, the candidates would often accept that job. However, there was a big problem. They were missing out on candidates because it was taking them too long to get a job applicant, scheduled for an interview. By the time that their interview was scheduled, it was likely that the applicant might be on their third or fourth interview, somewhere else, or they might have already been hired somewhere else. So so we were, the quote that we were given was, hey. We would love to find a way to reduce the time from application submission to the interview being scheduled from days to hours with one hour being the dream. So we developed an application that's built on Microsoft's Power Platform to deliver an experience that was not only gonna meet the organization's needs, but then also deliver an exceptional experience for the general manager and for the candidate. So to give you an example of what that looked like, the the application itself could live on any device. Right? We understand that general managers don't wanna be sitting in a back office in front of a computer all day. Right? They wanna be out with their customers. They wanna be out on the floors with their team. So it needs to be able to be on mobile devices, on on cell phones, on tablets, but still can be accessed in the back office if they do prefer to do that from time to time. So, this is what the manager interview scheduler looks like. Right? The, general manager can go in. They could set their availability based on what store location they were at, based on date and time, have a quick glance of what their availability looks like, again, based on dates, locations, and time. And then lastly, have a really quick view to see what are their scheduled interviews they have coming up for today, for the rest of the week. So they have not only a better understanding of who is coming in and the candidates being interviewed, but then also what's the position, how can you contact them if you need to reach them for any reason. Also can be linked out to the resume so you can, again, have a quick access to that right before the candidate does come in for the interview. But we also understand, like most, most people working today, we still heavily rely on email. So we're gonna send, once the interview is scheduled, the general manager gets a notification that an interview has been scheduled. Also gets, can get updates and reminders, before the actual interview is to take place, because, you know, we've heard horror stories, in in the world where sometimes a general manager might have gotten too busy and forgot that there was an interview that day, and that's not a great experience for the candidate showing up. This is what the candidate experience looks like, right? We wanna meet them where they are. So what the candidate does is, you know, when they were on the website, submitted their application, that application then goes up against the HRIS system for, the the organization we were working with. In this case, it was Workday. Soon as it gets entered into the system, a text message is sent to the candidate, right, because we're assuming that they have their cell phone on them at all times. And it's thanking them for your application. And when you're ready to you might not be ready right now, but when you're ready to, start your interview scheduling process, please let us know. They let them know they're ready. And, in this case, we ask a couple of qualifying questions. First question is, are you able to work weekends? Yes or no. And then the second question is, what's your favorite coffee drink? Because what a great experience it would be as the candidate to show up for your interview, and they have a mocha sitting for you, ready to go. So while you not only asked me that question, but you actually heard me and you presented that to me, it shows me how much you not only care about your potential, employees, but then also your customers because at the end of the day, they're still probably gonna be a customer of the place they're applying. Then they get the question, hey. When would you like to, when would you like to schedule an interview? Any anytime after tomorrow. So you could say Monday. You could say month. You could say September thirtieth. You could put, you know, any format. It will be able to recognize that and then give you the options that are available on the, that the general manager has input into the scheduling tool for that day. Once the candidate schedules that, candidate is confirmed. Hey. You have an interview scheduled with this person at this location at this time. But if you need to cancel for any reason or reschedule, please do so by using, you know, r to reschedule, x to cancel. And then as mentioned, same thing with the general manager for the candidate experience also can send out, push notifications for reminders. Hey. Tomorrow is your interview at nine AM. Please don't notifications for reminders. Hey. Tomorrow is your interview at nine AM. Please don't forget. So going back to the coffee executive's dream, did we deliver? And what the, remember going from days to hours with one hour being that dream. So we can confidently say that we were able to exceed his wildest dreams. So on average, an interview was scheduled in a little bit more than eight minutes from the candidate submitting their application, and then we found that the applicant, actually accepted an offer on average within three days. However, we can't guarantee so we can guarantee the faster scheduling process, but we can't guarantee a job offer because candidate still has to do some of the work themselves. So these factors, resulted together, that would help greatly increase the chances of you being able to hire the right candidate and not miss out on the right candidate due to scheduling delays. This concludes our webinar for today. If you'd like to learn more about TTEC Digital and the great work that we've been doing with Microsoft and AI space, you can follow the link on the left of the screen, or to schedule a thirty minute call to learn more, you can reach out to me directly with my email address here on the right of the screen. Thank you so much again for your time. We look forward to helping you provide exceptional experiences for your customers and employees. Thank you.