In this episode of Retaili$tic, Deborah Weinswig explores the transformative impact of AI on retail customer experience with Crescendo's Tod Famous and Mike Ryan. They discuss how AI is revolutionizing customer service, supply chain, and marketing, offering practical insights and future trends.
Key topics
Impact of AI on retail customer experience
Supply chain and logistics transformation through AI
Measuring ROI and success metrics in AI deployments
Chapters
00:00 Introduction to Crescendo and AI in Customer Service
04:31 The Evolution of Customer Experience and Returns
09:33 AI Implementation Challenges and Expectations
14:09 Defining Customer Experience Across Channels
18:36 The Role of AI in Enhancing Customer Experience
26:06 Navigating AI's Potential and Realistic Applications
27:47 Transforming Customer Experience with AI
29:02 Personalization in Customer Engagement
30:59 The Evolution of Consumer Behavior
32:52 The Synergy of Digital and In-Store Experiences
34:39 Empathy in Customer Service
36:38 The Importance of Small Gestures
39:43 Lightning Round: Insights on AI and CX
Philip Moore (00:00)
Welcome to Retaili$tic, the official podcast of Coresight Research for April 21st, 2026. week, our CEO, Deborah Weinswig, dives into the cutting edge of agentic AI with Crescendo Chief Product Officer, Tod Famous, and Senior Vice President, Mike Ryan. They discuss how AI is impacting consumer experience in retail, both in the store and online. But before we hear from Tod and Mike,
Here are some highlights of the research publishing on Coresight.com this week. Our series on supply chain innovations continues with coverage of the beauty and CPG sectors. The U.S. Retail Sales Outlook Report has the latest actuals and predictions, and our Consumer Insights series covers the latest results from our weekly consumer Visit Coresight.com to check out our full catalog of over 7,000 reports, webinars, and data sets.
Now here's Deborah with Tod and Mike.
Deborah Weinswig (00:58)
Thank you so much for joining another episode of Retaili$tic. We are very excited to have Tod Famous and Mike Ryan from Crescendo. So let's start off by getting to know these two folks a little bit better. So Tod, you have a very deep background in infrastructure and product. think, you you've been in product management or chief product officer since day one. Can you talk to us a little bit about what's changed in that world, but also why you started there?
Tod Famous (01:26)
Sure, I've been with Crescendo since the beginning. I was part of the founding team. We're a little over two years old, but I've been in the customer service and the contact center industry for decades in product management. So my background is in really large enterprise customer service and sales contact centers. I worked for vendors in the software space. And we started the company because of AI. mean, basically because
We've been trying for years, our other co-founders for years or decades to make service and customer experience better and only made incremental improvements. But when you look at what's happening with AI, it's going to be dramatic. And so we're very enthusiastic about what's happening now.
Deborah Weinswig (02:06)
And maybe dive into, think you were at Cisco for over 20 years. What was it like to be at a company for 20 years? Because that's like unheard of these days. And what did you see change during your time there?
Tod Famous (02:13)
I think.
So when I was
there, when we started the business, we were the first software group in Cisco actually. And we were the contact center business unit. we, at the time during the sort of internet boom, you will, Cisco was growing very rapidly and looking to expand into other markets. So I got into Cisco through an acquisition started, we were the first network-based contact center system, which know,
Mike Ryan (02:39)
you
Tod Famous (02:40)
crazy thing to do back at back in the day and went from sort of entering the market to first in the in contact center space. So something like, you know, maybe half of the Fortune 500 run on Cisco contact center infrastructure.
Deborah Weinswig (02:54)
And one last question, if we think where contact centers went from and where they are now, what does that timeline look like in terms of what's changed over time?
Tod Famous (03:06)
Well, during those years, mean, we transitioned from digital to network-based or internet and e-commerce and all of those things happened. ⁓ Then mobile happened and then cloud happened. So all of those transitions over my career, they've all been significant. The way you do business has changed from the phone to the web, to mobile over the last few decades.
I would say that they've all been incremental improvements. So a lot of the technology coming from the vendors, and I was on the vendor side and being deployed by the businesses, were incremental improvements. A lot of cost offsets and incremental improvements. To efficiency, cost, mean, cost is a large part of running those sorts of organizations, so efficiency and cost.
Deborah Weinswig (03:39)
it.
Tod Famous (03:47)
but not dramatic, I would say. I'd like to think that customer service is better than it was 20 years ago, but it's just a little bit better. I mean, most people still think that customer experience, whether they're buying or getting support on something that they've just bought is not something you look forward to for sure. so.
And a lot of that has to do with the cost and what's happens on the, on the enterprise side to run those sorts of operations. And so again, with AI, particularly the large language mental AI tech, have a possibility to completely turn things upside down in terms of abundance of, of technology to do customer service.
Deborah Weinswig (04:21)
Well.
I always felt that if customer service was better, we wouldn't have almost a 50 % return rate in apparel, fashion, and accessories, right?
Tod Famous (04:31)
The, I mean, the return rate is actually, it's interesting. We've done a bunch of work in that area where we're using AI to analyze the reasons for returns. Maybe just an anecdote there. had a customer that was in the shoe business and they were getting returns of too large for some, for their boots and too small for their sandals, essentially. They had no idea. They knew return rates, but they didn't know.
Mike Ryan (04:51)
Thank
Tod Famous (04:54)
the why or that there was a distinction in sizing over or under on different types of footwear. And so with AI, we actually looked at all those transcripts for all those returns and then we advised them. And by the way, this is the cutting edge of what we're doing. It's not just delivering service, but giving them business insights that were showing that their returns were because of something that they didn't even fully understand from the metrics that they had been collecting.
Deborah Weinswig (05:18)
That's so interesting. mean, returns are one of the things that I focus on quite a bit because it introduces actually, it's a great segue to kind of Mike's background, I have a very deep background in supply chain. And if you start to think about reverse logistics, et cetera, right, that brings up so much. So Mike, I know you spent a lot of time at Project 44, which I know from my supply chain background. you know, it's really interesting with both of you. mean,
It's not often that somebody such as Tod has been in practice whole life and you've been in marketing your whole career. So maybe from marketing feel like that's where we've seen the greatest change in my career. But maybe if you can kind of take us from either...
if it was by company or by era almost, how have you seen things changed as it relates to kind of, you know, whether it's B2C or
Mike Ryan (06:09)
I joined Crescendo in May. And as you said, my background has been supply chain for seven years prior to that. And I also spent some time in IoT, which sounds like a really odd path to a customer experience company. But what I watched happen in those industries gave me, I think, really clear window into where the world in AI was heading. I saw how fragmented the operations were.
right, how complex it actually was to transform manual process, right, logistics and connected devices. It's so ingrained in the way that the industry works. But the thing that kept striking me, think, across supply chain and IoT in my move into Crescendo was how central the customer experience was to literally everything. It wasn't, it's not just a support function ⁓ and the customer interaction was
the most valuable signal in the entire business. tells you what's breaking in your supply chain, what's confusing about your product, what your pricing should be, where your returns policy is wrong. So I think every function of the business should be paying closer attention to what customers are actually saying. And there's too many businesses that aren't. And a big reason for that is the data is trapped in siloed places, right? Where a lot of businesses haven't figured out how to unlock.
unlock that yet. So I looked at where this all was heading. I think the convergence of large language models, voice AI, ⁓ multimodal capabilities, all these things were maturing at the same time to the point where you could actually build something genuinely intelligent in a customer conversation that wasn't possible before. Whereas most of the industry solutions have been built on older logic and technology like decision trees.
So that was, I think, a huge opportunity at Unlock for the industry that I saw and I really wanted to be a part of. I think the other thing that I saw was that vendors were selling software and walking away. Technology has advanced so fast, but there hasn't been the accountability yet for results. so Crescendo thought about this differently and was built around a simple idea that what if we actually took on the risk ourselves?
only got paid when it actually worked and delivered outcomes for the customer.
Deborah Weinswig (08:20)
I think it's really interesting you bring that up because we've had so many of our clients on the retail side, brands, hospitality, who are diving in through our AI council, et cetera, into whether it's LMS, multimodal, agentic. But it's been very difficult for them to measure the ROI. And I think you...
Tod Famous (08:38)
Why are they
diving in? Why are they diving in? Do they know?
Deborah Weinswig (08:41)
I, yes, that's a great, because the board would like them to. So the board applies pressure to leadership. Leadership goes to, right, IT, whether that's CIO or CTO. And then of course they pop up and, know, we need a head of AI. And this is where it gets, I'm so glad you asked that, thank you. This is where it gets, because I can, I can like predict what's going to happen before I go into most people's offices or get on a call.
Tod Famous (08:46)
Yes, exactly.
Deborah Weinswig (09:08)
Then they're going to pop up a head of AI who reports into the business, right? Who's then kind of not going back to silos. I think silos are actually getting worse, not better. Because you then have these very interesting dynamics. I'm seeing it play out again and again and again, where you either have many different solutions running almost in, let's just say, making it
difficult to kind of come up with a single source of truth because everything is looking at different data. And at course, when we were doing a very simple kind of agent to go and fetch data for our clients from our huge database, what we started to realize is something that's so simple that is, what's your projection for 2025 apparel, footwear, and accessory sales? Well, we did that same projection in 2020, 21, 22, 23, right?
And so something that should be so simple is actually much more complex. And then you start to think about across these organizations that have data in many different places, right? Excel, PDFs, et cetera. And everything is labeled a bit differently. And so I think you bring up a very important point, which is why are they doing this? How are they doing this? And who is it that really wants to? And then ultimately,
how do you measure it? And so I don't know if from what you've seen, right, when folks maybe kind of get to your front door, how are they getting there? And is it that the board asks them senior leadership and so they're trying to kind of make something work.
Tod Famous (10:40)
I asked because I think the first most common thing we think is they've heard about AI, need to do AI, which is okay. So that's actually your...
The next level down, which I cringe about is like, we've heard that AI is going to replace all of our people, so it's going to save us money. And the reality is that AI automation can save you money. It can improve productivity.
that is an element of the business case. It's part of the conversation. In my personal opinion, especially in the retail, if that is your motivation, you've sort of lost the narrative slightly. I mean, we deliver sort of cost benefit to all of our deployments, but we don't.
That's not the narrative that I think is the big win for AI. I think it's going to be improving customer experience. So like, for example, if you can use AI to save productivity, do you take that to your bottom line or do you expand your hours of operation where you can talk to your customers?
Or do you expand the language capability that you can offer? Or do you expand, and I would say increase the salaries and the quality of your staff. So do better with the savings. Now take some of the savings, but if, if you're solely focused on savings, that's what you're going to get. And you're going to, mean, eventually in a competitive market where you're competing against other retailers or whatnot, you're going to start to lose ground on the customer experience.
Deborah Weinswig (11:58)
You bring up a really interesting point because this is one of the top ones that we have conversations with our clients on a daily basis. you know, the number on the market is, right, if we do AI, we'll save 30 to 40 % in terms of efficiencies. And so either we can bring that to the bottom line or we can do more.
And in many cases, it's what we find is the first half of every year, they want to do more. Then kind of comes like second, you know, and the second quarter. And all of sudden they're like, wow, we've got to like post our results for the year. in the back half of the year ends up being
operating expenses and more about efficiencies. And that's how it's played out in 24 and 25. mean, 23, we're just kind of getting started. So it'll be interesting to see what happens this year. I do think, and Mike, it's really interesting because ultimately, this is about them marketing to shareholders what they've been able to do with AI to transform their businesses.
So
now there's heads of digital and transformational AI. There's all these additional roles. So you're seeing the C-suite is expanding again, but ultimately how they're measured, I think, is a question. so, how do you see companies messaging doing AI and what's working for them, either B2C or B2B?
Mike Ryan (13:28)
Yeah, I think ultimately a lot of this is about trust. think trust that the technology is going to work, trust that the customer experience is actually going to hold up after deployment, trust that when something goes wrong and things do go wrong, that there's someone accountable on the other end. And I think when we see what we see in the back half of the year, pressure describing is actually a symptom of deployments that maybe weren't set up with the right.
outcomes from the start. Because if you define success as resolved customer interactions rather than deflection rate or containment rate, you'd have an easier time defending that at any time of the year. And so think the problem is that deployments don't always start with the right objectives in mind. And yeah, as Tod said, the retailers I think that are most interesting right now are the ones who have stopped treating.
AI as the cost line has started treating it as the customer relationship layer. It's less where it becomes less about what did we save? How do we and more about how do we increase retention, repeat purchase and lifetime value?
Deborah Weinswig (14:30)
It's interesting, I was talking to a head of CX for like a two and a half million dollar retailer yesterday and it was interesting. First of all, everyone defines it differently so that can be a challenge and thus everybody measures it differently. also if an organization, let's call it Unified Commerce, so they have stores, they're online, maybe they're working with a
third party to do last mile to the consumer and that a lot of that's, know, kind of customer experiences, unfortunately out of their hands. And so you, how did both of you kind of define, right? CX because think if we got a group of people together, everybody would define it a little bit differently.
Tod Famous (15:13)
I define it pretty simply. It's what your customers experience from you as a vendor, as a retailer. our business, we're focused on an element of the overall CX. So I don't suggest that CX fits into one particular bucket. mean, if you're a retailer, for example, and you have stores, then how they experience the store is part of the customer experience.
And I guess more narrowly in terms of what we're doing in the AI area, it's handling customer experience from a digital or a mobile perspective where the customer.
reaches out to the brand. speaking of like, say Shopify, for example, they're a great partner and we view that platform as an excellent way to handle the commerce experience. One thing that's very, it can get sort of forgotten by people in my industry is that in a great customer experience, the customer might arrive at a site, they might select something, they might buy it and they never reach out
they reach out to customer service, if you will, is when something goes sideways, like they got confused or such. So customer service, if you will, is always supporting the broader CX and the mission of actually delivering sort of low friction customer experiences. Yeah, again, our particular focus is in the area where those things need assistance. The sort of automated path is the best path. And when the automated path needs a little
bit of help along the way, that's where technology like ours in the AI space gets involved.
Mike Ryan (16:43)
Yeah, it's a great question. think you're right. Everyone defines it differently depending on who you're talking to. And that's maybe part of the problem as well. A lot of companies define CX, right, just as the support function. When something goes wrong or when you're having to be reactive. The way I think about it is that, you know, it's every moment that customer has with your brand where they're actually forming an opinion or forming their perception of you, like when they're trying to find the right product or...
when they're interacting with your support or when they're checking out, like when they need help, when they want to return something. And ultimately like the moment where they decide if they're actually going come back. think in the commerce world, you know, where you've got, as you described, like stores, have brick and mortar stores, have online, you have Last Mile and all those touch points are touching, are reaching the customer. The challenge I think is that like they're all owned by different teams with different metrics. And so
What you don't want to do is have the customer feel the weight of your org chart. You don't want them to have to think about that at all, but it's really the sum of all those moments. And I think the question is whether you're actively managing them as a system or just hoping that each one individually works out. I think that's where AI can unlock, if it's done right, unlock visibility and just a lot of those moments.
holistically and so that you see the whole journey and not just, you know, one piece of it.
Tod Famous (18:01)
I'll give you an example, like ⁓ maybe a contrarian sort of thought example. We were working with a customer who went as an e-commerce customer, gifts, if you will. So customer buy something and they had set up their system such that in seven minutes it leaves the warehouse or goes to the warehouse. And this was sort of like a triumph from their perspective that this flow worked really fast. Now, the problem is that
customers when buying gifts, this is kind of a funny thing in the e-commerce space. They sometimes put in their address when they're trying to send it to the other party. So when, and we're delivering their customer service and we're looking at their, their inquiries and you know, like 30 % of their inquiries are people who, who are shipping to the wrong address. So we worked with them actually. So this is the counterintuitive part. We told them, stop shipping in seven minutes. It doesn't really matter. Ship in.
30 minutes. So they delayed the, the, the recommendation is to delay the time in which they left the warehouse, which is kind of seems sort of counterintuitive, but to make it possible. So that when the customer fat fingers, the wrong address, and they get that shipping confirmation that they're like, I sent it to the wrong place or I picked the wrong color that they have a window to make that correction with the customer experience team. So they reach in for customer service and they change the address. so
That's understanding CX. It's basically not just mechanically executing e-commerce, but like understanding how customers experience. And when, when we were looking at this customer's work, you could see lots of upset customers because they shipped things in the wrong way. And so the AI is big flashing red light. Customers are unhappy. And the main reason your customers are unhappy is because they can't change the shipping address when they make a mistake. And so it's not actually a complicated fix, but like a
I guess maybe a thoughtful fix in terms of how you think about CX.
Deborah Weinswig (19:47)
You know, it's interesting. at an ML, know, big data company and we would once again, we can ingest and clean in like two months. So this was a few years ago, about 10 years ago. was fascinating is we were just looking at pattern recognition. So I have to say, any job I've loved, it was so interesting, right? Especially from, I'm like.
Because you would see things that companies either couldn't, because they, going back to that single source of truth, they couldn't see in their data, or you're so close to it sometimes you just don't see it. And so it's very interesting to hear how Crescendo, because I've always said to me, it was a huge, I'm required by Xerox, it's a huge problem to solve. And I never really saw a company who kind of picked up where, you know.
Obviously we continue to work inside of Zebra, but independently, because the opportunity there to help companies, and I'm not talking in a consulting, I mean of course there's a consulting aspect to everything you do, but it's, if you're starting to, because ultimately.
customer experience, I've always thought is about recognizing patterns that either create joy or not joy. And I mean, Mike, ultimately, if you're in marketing, that's all that you're doing. And you're trying to figure that out. so mean, if you think about where we are in terms of AI right now, mean, think Opus 47 just dropped yesterday. I I'm down the rabbit hole with everybody else.
the abilities or the capabilities that we all have individually and then maybe as an enterprise, I don't know about you, I'm finding that my tolerance for friction gone thinking about this a lot. I've kind
written it down literally on a piece of paper because I start to worry that things that we used to be able to handle before
we're not going to be able to handle as well because we're like, you know what, I'm just going to kind of like pull the rip cord, exit and go figure this out myself. So like in that kind of a world, how are people changing? What do they expect? And I think marketing is like this idea that brings joy and happiness, right? We're seeing like marketing tied in with music and it's just such an interesting time in terms of, I mean.
just the amount of change, but also I think it's both exogenous and internal as well, how the consumer's looking at it.
So how do you think about it from a marketing perspective? How do you then think about the customer experience with marketing, with your marketing? And how has that changed over time?
Mike Ryan (22:17)
Yeah, the bar has definitely moved. I mean, it's moving every single day with the rate of change that's happening. And I agree with you that think the tolerance for friction is on my tolerance is certainly dropping. I'm feeling that in my my interactions with brands. And it's happening quite, quite frankly, faster than people realize. mean,
Like you said, with Opus 4.7, it's almost a full-time job just keeping up with the changes that are happening in AI. And I think everyone's feeling that. Everyone's also feeling the mandate to implement AI. But when I think about the customer expectations, I do think there's a reset happening. think every interaction, whether it's through
support or through your marketing to be a great experience across every channel. think the bar is certainly raising and most companies haven't really haven't figured it out yet, right? to achieve the potential that we have in front of us. And so I think we're all figuring this out together.
Tod Famous (23:16)
throwback story to ⁓ retail and your return process if you back to the .com and this is I guess a cliche Amazon story, but once they automated the return process so that when you received a product you could return it without calling them, they were the first to do that in the e-commerce space.
And there's a, what's called a transitive nature of customer experience. So once you've experienced that from one retailer, you expect it from all the others. So, I mean, Amazon obviously is a force in retail, but when they're doing something, every other retailer needs to be thinking, not just of delivering customer experience, but how they compare to the.
technologically advanced retail experience, how fast they get shipments, all of those things become comparables, which is what causes that decline instead of, or expectation to increase because the bar raises on one experience, it crosses over into all other expectations.
Mike Ryan (24:11)
Right. And one more piece on that, Deborah, like the, you know, I think that's certainly relevant as we talk about logistics. And now we have the technology to start to piece these things together. But when I think about supply, the supply chain world I came from, you know, we spent, you know, spent billions, know, there were billions of dollars spent trying to optimize the flow of physical goods. Right. You're trying to reduce waste. You're trying to reduce.
returns, you're trying to reduce friction in the supply chain. And the whole time, the most valuable data moving in the wrong direction are literally, again, getting back to customer experience or sitting in your support ticket. the data fragmentation piece has made challenging problem to solve.
And making that connection is probably the biggest opportunity that we have. returns, as Tod said, it's really not just a logistics problem. It's an information problem and managing the flow of information to the right places.
Deborah Weinswig (25:09)
I mean, I will didn't realize the supply chain was going to be kind of hot for like, you two weeks during the pandemic. And then, everyone was back into like store tech and all that. But in those two weeks, to me, what was shocking was everyone's like, where's my stuff? And I'm like, what do mean, where's your stuff? Right, it's in the container somewhere. But they're like, but where? And I'm like, what?
And so this inability for companies to find their own goods, let alone the customer's purchase.
These were some of the things that you were like, how is this going back to logistics? How have we not enabled this? And to me, really think when you survey consumers, yes, the number one thing they ask is like, where's my stuff? And when is it going to arrive? And then if it's a gift, that was such a great example because I think we've all done that. Did the gift end up, right? Because sometimes I'll realize that I'm like,
I was expecting like some kind of thank you or whatever. Then all of sudden the gift shows up. I was like, gosh, the company was so nice. They sent me one. They sent my friend one. then all of a sudden you're like, no, I didn't do that. But of course you did. And it's interesting in supply chain, right? There have been many different technology solutions that have kind of been enabled. One of them that I loved was a
Mike Ryan (26:17)
You
Deborah Weinswig (26:28)
Supply AI and
They, if they saw you ordering things in let's say extra small, small, medium, they would call you and they'd be like, you know, we just wanted to make sure that, you know, you had meant to order all that. And of course they, in many cases they did. I remember being on the receiving end, I got a call from like Bloomingdale's and I didn't usually order whatever product. I was buying like some, I don't know, some stuff for travel. And they're like, you know, did you mean order all this? I'm like, oh yeah. I'm like, I'm traveling. Like I just want to make sure I'm getting it. But, but I will say,
Mike Ryan (26:54)
Thanks.
Deborah Weinswig (26:58)
from a customer point of view, I was like, I and I knew it was driving the call, but the fact that they inbounded that customer experience, it went up kind of a few notches for me. And I thought that was incredibly interesting. mean, Tod, as you think about the problems that you're solving and then the ones that you can solve.
How do you kind of like think of those on like a continuum? Because what I'm finding with AI will do things, either people are incredibly like narrowly focused or they're like all over the place. Because it's kind of like, I can do this and I can do this and I can do this. So how do you kind of keep things sequential and realistic?
Tod Famous (27:36)
We use AI.
I actually, and I'm serious about that. The, ⁓ one of the things actually, I'll give you a quote from a customer that we were talking to back in February. We launched a sort of this insights dashboard, which was basically, and where you could traditionally using data science and pattern recognition. Okay. But you can imagine, with like a large language model, AI technology, it's conversational. So, you can ask.
anything about the data. just, I know I had to say it like three times, but just imagine that every customer conversation you have in data. Now imagine that you can talk to something that has knowledge of every one of those conversations at the same time at once, and you can ask it anything about anything. And we rolled out this insights dashboard where you could have this conversation and ask anything.
And one of our customers said, this is amazing. And then they were like, I'm now going to really have to think about what to ask. Cause I don't know like what I should ask. Like what, if I, if I'm not constrained by IT or what was set up, you can ask anything to an agent. Then you had to find out what to ask. And you might've experienced that kind of situation with like whatever a consumer product like chat, GBT, one of the unlocks, the next unlocks is to ask AI what to ask.
I know it's sort repetitive, but you can say things like to our technology, can say things like, what are the things that I should be concerned about related to CX? So in a traditional software stack, in the technology again, several years ago, you would have had to as a business define what are the KPIs, what you want to track, what you're looking for.
And then wait for project deployment and data science and reports and SQL databases. And they would have produced the metrics that you wanted. But when the turnaround time is instantaneous, you can begin the conversation with what should I ask? And then you can like really wander down certain paths. Like, I'm really interested in how consumers are thinking about ordering birthday cards this year. And is that, you know, is that something that we should maybe
adjust our customer experience related to that. So you can sort of wander down any path you want with AI. again, you can ask the AI what you should be concerned about. You can just say what your role is and ask it what it thinks. And you'll get interesting things. It's like your experiences with the consumer products. It's really good at brainstorming.
You know, you need to go back and forth. It's not like it's just going to one shot and solve all your problems. But when you brainstorm and you interact, you can actually get to really good places, especially when you bring your experience into the conversation.
Deborah Weinswig (30:16)
I think one thing that you kind of like just unlocked is, right, every company has different, you know, you know, demographic psychographics of customers. And so what we've found is when you treat everyone the same, because it's, you know, a matter of cost or bandwidth, that...
you know, if everybody's Jane and Jack and Jane, that can be a challenge. But now that you can have multiple kind of personalities and, you know.
Jane and Jack and Julia and Joe and all that. What we've started to find is that companies are starting to think about, this customer lives in the suburbs or they're rural and they are, let's say they're avidly on TikTok or they're right. so what is the kind of going back to it's really always about experience, but experience product, how do they want to be spoken to? And
I still dream about in the physical world, but the they can meet me where I am. I mean, I've said this on stage for years. I want to...
I mean, I've shopped many times at Target, right? I just want to walk through the doors. I want to have kind of opted in. And I want them to bring me a car with a cup holder with a bottle of water, right? And I'm happy to pay for that. they should know I've been into their stores hundreds of times. And so this idea, I think this goes back to the friction, is that I think that consumers are only going to be so patient.
And I do believe with AI, and I've said this from day one, that there is a first mover advantage. I mean, let's look at ChatGPT. Not going to say anything. I like to talk in the positive world. But there are definitely other competitors out there who may be better. But because everyone started there, that's kind of what everyone still is centered upon.
And I think that for retail, especially right now, if you start to change, let's say the humans change their own workflows, right? And so how I order groceries, maybe I download the Instacart app into Chachipi Tea, and then I'm like, okay, I need lemons and I limes, right? I'm like margarita mix, whatever. And so I'm starting to change my behavior at an exponential pace. And then the idea that I even have
to talk to Alexa or Google Home or whomever is here in my house with me. And so there's that. But then when I go to the store, I expect a phenomenal experience. And so I think that.
And the consumer, right? Consumer traffic is up. I mean, it's been up in 22, 23, 24, 25. I mean, you talk to the mall operators, they're shocked at what they've been seeing because it goes back to, I think the more you remove friction from the online piece, in some ways it frees up the customer's, know, kind of mind or time. And they go to the stores to write like, discover, be, let's just say, you know, whether it's finding something that they didn't know existed or finding kind of like the perfect color.
And then they'll go back oftentimes and purchase that online because they want to think about it But all of that is really changing and it may be subtle for now, but I I do think that it gets it it Changes right it's like this and then until it's like that and so how do you guys and am I kind of throw this one to you? How how do you help? companies, and I don't know if
I assume you're working across hospitality, right? Like those who are consumer facing industries, how do you help them think about, right? This kind of timeline and what they need to do at what point in the game so that they are not left behind? Because that's what I worry more about right now than anything.
Mike Ryan (34:01)
Yeah, it's such a powerful. I love that anecdote. It's such a powerful insight. It completely reframes how you think about digital CX too. It's not just, you know, it's not competing with the store. They're working, you know, it's feeding it, right? They're working together. And I think when the online experience is effortless, like when the, your questions get answered instantly, the orders, right? You know, what you're looking for is in stock. You know, in some cases, if the return is painless, you know, you don't feel as drained by the brand and people feel good about that.
And I think the goodwill shows up when you also walk in the store. I think it's about removing that friction from the digital experience so that you're not taking away the customer's mental energy. Because you're right, it's a lot easier to do that when you have somebody in person. I think the brands that get the digital experience right are doing those things. That's certainly what we're building towards at Crescendo. It's not just better support. And it's definitely not just lower costs. Those are benefits, but it's really about
the customer who leaves every interaction or support ticket with your brand, and they're feeling a little bit better about it when they started. I think there's evidence of this too. We're seeing this in deployments where obviously there's a lot of places as a consumer where you can go and leave your thoughts, peer review sites like TrustPilot or other online review sites, Google reviews. We're seeing that our
customers, customers are going to those sites and talking about how great of an experience they had with our AI, right? And that's unheard of. We haven't seen that before. So, you know, it's something we're certainly, you know, focused on, but I think it's, you know, starting with those highest friction moments and, you know, fixing and pulling the results forward ⁓ online as well.
Tod Famous (35:47)
I hate to say the bar we set so low as an industry over the past 20 years, like we're, Mike was referring to one of our customers who had massive TrustPilot jumps when we went live. And the thing that did, which is actually quite small, but basically when a customer wanted to return the product, let's say they sent an email for return before they were getting a canned response.
And so when we had the AI write the response, and if you've worked with these technologies, you know how beautifully they write. So this is a really simple problem, basically. So they write, I'm very sorry that your such and such broke, you know, that must've made it difficult for your son's birthday or whatever. Just a short, like one sentence of personalization in front of the, here's your options. Do you want a replacement? Do you want a refund? By the way, second part, quickly. So not like four hours later, but like a couple of minutes later.
So you send this devastating broken product situation and you have to return. You get what feels to you as an empathetic response quickly within minutes as if it was written and it was written with care, although by AI, and it just massively changes your whole worldview on dealing with the business. Like the CX is just completely different by just a couple sentences of personalization.
Deborah Weinswig (37:01)
I, you, bring back a little PTSD where we were helping some companies and we were having conversations with their customers on just how angry they were getting over, different, right? Like the, they were kind of bounced around from person to person. Then the call got dropped.
You know, they were told by some people that it could be fixed, others that it couldn't. And, you know, it goes back to Michael, you said this kind of like exhaustion with the brand, right? By the time you're done, right? And what would have cost them like $15 just to be like, you know what, we'll just credit you for that. don't have to like some very simple things. And so I do think that that very compassionate kind of one line or two lines, can like the value of that, I think is undersold.
in many cases, because if I feel the brand empathizes with me, I mean, we had like a crazy, I live in New York. I mean, I don't know what happened, but I'm a just in time kind of person. And so my daughter, I think was leaving for camp on Sunday. I ordered all her stuff the Tuesday before from Walmart and like none of it showed up. So I call, right? I was like, this is, there's just too much stuff I like now don't have.
And I will tell you, I had to put myself on mute because I was like laughing out loud. The guy was fabulous, by the way. And he's like, you know, in New York, we hear they just throw it out of the truck on the sidewalk. And the people just take it. I was like...
Mike Ryan (38:26)
You
Deborah Weinswig (38:30)
Exactly, there is some order to the system. he was just like, he just, mean, honestly, this is like, I still remember the conversation almost word for word, because he was not only incredibly empathetic, he basically over-eyed everything to me and credited me. It was such a great experience that I was like, and he was just like, he's like, I can't imagine what that experience must be like for you. He's like, you're looking, you're looking. And so, but being on the phone takes time.
Right? So probably what I could have done over email or whatever or with a
agent in a few minutes, right? That was probably about 30 minutes. so it, but I remembered it. And I think that sometimes it's, I've always said, and I believe this personally and professionally, like little things add up to big things. And so you may be able to retain customers or see a greater ⁓ customer lifetime value. If you start to look at just some of these little things. so from a Wall Street perspective, right? We all want to see that companies are doing A
I
And that's important, but it doesn't have to be, it can be something like what we've discussed on this call. We just need an example that companies are moving something forward. It doesn't have to be a complete overhaul of, know, let's say God forbid supply chain. so the, like if I were to, if I were to kind of, for those who are listening, right, it's just about, I mean, I more than enjoy this conversation with Mike and Tod, but
Mike Ryan (39:46)
Mm-hmm.
Deborah Weinswig (39:55)
Sometimes it's just about doing the little things and getting started as opposed to having this kind of, know, ostentatious idea around what you think either Wall Street wants, your customers want, or your employees want. Because I think this is one of those cases where, yes, we're an N of one, but probably what bothers us bothers a lot of other people too. And so thinking about, you know, asking AI, I think Tod is a perfect example, but also just thinking about, what would I want to change in the shopping
experience. First of all, do not show me out of stocks because that like drives me crazy.
You know more than I I'm like all I want is the extra small and the black and and it's it's like the only one that's sold out, right? So I think there's something to that But secondly if if it is sold out and I am like annoyed Certainly having some kind of intervention along the way, right? I understand that that must be challenging, right? We'll give you 15 % off if you'll take the red So I think there are kind of small things that that do add up to big things So we have in our last 10 minutes. We always have
a ⁓ very fun lightning round. So the rules of the game are that either of you can pass and you can also phone a friend and so Mike if I have you can turn over to Tod or however you want to do it so.
We're going to get started so that we stay on time. so once again, whoever wants to answer or whoever wants to kind of phone a friend, it's all anything's game. So number one, most overhyped phrase in enterprise AI right now.
Tod Famous (41:27)
Gentic.
Deborah Weinswig (41:28)
Number two, feel free to agree or disagree as well. Number two, one customer service metric leaders rely on too much.
Tod Famous (41:36)
I mean, I just go with like average handle time, I guess, just because it's leads you such down a dark path.
Deborah Weinswig (41:44)
I think that's great. And number three, one metric they do not rely on enough.
Mike Ryan (41:48)
Customer lifetime value, it's quite hard to measure.
Tod Famous (41:51)
Yeah, they avoid the hard ones. They avoid the hard ones. That's a good point.
Mike Ryan (41:53)
Yeah.
Deborah Weinswig (41:55)
Yeah, I agree with you there. Number four, biggest reason AI pilots fail to scale.
Mike Ryan (42:00)
the human expertise needed to make it work.
Tod Famous (42:03)
Yeah, the cost to maintain.
Deborah Weinswig (42:04)
Let's get number five, more important in CX today, speed or resolution.
Tod Famous (42:09)
I'm a speed guy, that's an opinion, I think. But what do think, Okay.
Mike Ryan (42:14)
Resolution.
Deborah Weinswig (42:16)
Okay,
good, I like this. right. Number six, harder problem, technology integration or organizational change.
Tod Famous (42:22)
or change.
Mike Ryan (42:23)
organizational tension.
Deborah Weinswig (42:24)
I'm with you guys as well. ⁓ Number seven, one thing enterprises still misunderstand about customer expectations. I think there's many, but maybe one.
Mike Ryan (42:26)
Yeah.
Tod Famous (42:35)
That's hard to put into one.
Mike Ryan (42:38)
Well, think, actually, I've got one. I think it's what you were talking about before, which is it's the little things that matter.
Deborah Weinswig (42:43)
That's it.
Tod Famous (42:43)
think that enterprises
overestimate how much customers want to engage. Again, I'm going back to the speed thing. They want things done fast and quickly and easily, low friction, as opposed to lots communications, I'd say.
Deborah Weinswig (43:00)
That's good. All Number eight category you think will adopt AI and CX faster than people expect.
Tod Famous (43:06)
eCommerce.
Mike Ryan (43:08)
Well, I think I expect e-commerce to adopt quickly. So would say manufacturing.
Tod Famous (43:10)
.
Deborah Weinswig (43:14)
yeah, that's a good one. One part of customer service that should remain human for longer than the market thinks.
Tod Famous (43:21)
I mean, I think that the way I phrased the role of people, we are very focused on people in our ⁓ offer, is ⁓ exceptional work. So not necessarily difficult or even empathetic, but exceptional is where I think automation falls short and people AI.
Mike Ryan (43:41)
Relationship management, think, for high stakes moments in particular.
Deborah Weinswig (43:46)
Yeah, that could even. When it relates to loyalty, etc. That's a really good point. Alright, number 10. I'd love for both of you to answer this one in one word. What will matter most in CX over the next three years?
Tod Famous (43:57)
I mean, I would say AI. I mean, it's what the whole topic is about. I know it's over, it's like overhyped, tell me, believe me, believe me, it is underhyped. What's coming from the technology is unbelievable.
Deborah Weinswig (43:58)
Yeah.
Mike Ryan (44:03)
Yeah
Yeah, I was trying to avoid that one intentionally.
Deborah Weinswig (44:11)
We hosted a
dinner last May, about 35 people there and we're research highs. Come to our dinners, right? We ask you a lot of questions.
It was interesting. I asked, people think that AI was over, under, appropriately hyped? And about two thirds of the room felt it was over or appropriately. And I was, think, one of two people. I'm like, it is completely underhyped. And think about it, we didn't have even agentic then. And so it's, I think it goes back to, right, it's the data, all the data that we have shows that people, probably like the three of us, who are either
Like we're continuing to grow every day through using different, you know, large language models or building agents or whatever, wherever you might be on your path. was told it's 137 hours to be an expert in AI and 13 hours to be a beginner. So I would assume we are all way past expert, but it's, really interesting because I find I keep expecting that I'm going to be working less. I'm actually working more. Right.
Tod Famous (45:15)
Yes,
Deborah Weinswig (45:16)
And then when I'm traveling
Tod Famous (45:16)
totally.
Deborah Weinswig (45:17)
now, I have like a sense of anxiety and I'm not an anxious person because I'm like, I really should be at home, right? Like building things. And so it's really interesting, I think how all of us are kind of thinking differently about the opportunities inside of our companies because it's, know, and especially if you guys, I mean, we're a startup, but you guys are a newer startup than we are. mean, you know, you're still painting, right? Like the lines on the road.
And that's...
Tod Famous (45:46)
It's, it's
exciting. ⁓ team is so excited. They work all the time. And that has ramped up in the last three to six months as the, agentic stuff has come because the, ability for experienced people to have an impact. So you take your experience and you arm yourself with these tools and your impact is just tremendous.
Deborah Weinswig (46:09)
I have thought that from day one, that you would have either, right, the kids who are kind of straight out of school who are using AI and everything they do, it's like, I mean, they're not AI native, but they're as AI native as any of us. And then those people, I mean, we done a bunch of research on this and they showed, I think it was kind of 45 to 55, or just call it 45 and above, right, because you have a certain number of years of experience that...
Mike Ryan (46:22)
Hmm.
Deborah Weinswig (46:34)
you'll be able to see patterns or understand demand signals in a different way. And when you kind of then partner with AI, right? Like it's a really amazing opportunity. So I can talk to you guys for like another hour. This was super fun. I'm really excited about what you're doing at Crescendo. Like I said, I had always felt that there was an opportunity for a company to do exactly what you're doing. And I will be quite honest, you're the only ones that I've seen who are kind of taking it on. So.
I don't even think I need to wish you luck. think it's just about having enough hours in the day to talk to enough customers and tell them what you're doing. So, you know, ⁓ please let our audience know how to reach you.
Mike Ryan (47:08)
Yeah, our website is crescendo.ai. Best place to reach me is probably LinkedIn.
Tod Famous (47:14)
Yes, probably the same, LinkedIn. Very easy to find. I'm the only famous person on LinkedIn.
Deborah Weinswig (47:19)
I will say I'm like, I'm like, wow, with the name different wines, like I don't have that problem because I'm the only one. But I was like, wow, I'm like, some of these names, it's tough. And Tod also some of one D I'm like, it was, you know, you're, an easy person to find, but also a name that like, you just won't forget. So thanks to both of you for being on today. We really enjoyed the experience and I look forward to having you back again soon and good luck with everything you're doing.
Mike Ryan (47:24)
Yeah.
This was fun. Thanks, Deborah.
Tod Famous (47:43)
Great, thanks.
Deborah Weinswig (47:43)
Thanks.
Philip Moore (47:44)
Thanks Deborah, and thank you for joining us this week. Coresight Research serves our members with time-sensitive research on consumer shopping behavior, retail technology innovation, financial outlooks for industry leaders, and trends across every retail vertical. We also facilitate leadership communities, conduct seminars and conferences, provide strategic consulting, conduct technology assessments, and develop proprietary data resources.
Visit us at Coresight.com to learn about all the ways we can support your success. Have a wonderful week.