Name: Webinar: From delivery to loyalty
Uploaded: 2026-06-17T19:30:13.286Z
Duration: 57 min 10 s
Description: Webinar: From delivery to loyalty

Transcript for "Webinar: From delivery to loyalty": Hello, everyone, and welcome. Thank you so much for joining us today. We're gonna give it just a few more seconds here before we get started, just to allow everyone to hop on. So stay tuned. Alright. Let's get started. Thank you all again for taking the time to join us today for this unique webinar on how AI boosts satisfaction, cuts operational costs, and drives revenue growth. My name is Jess Miller, and I am a digital commercialization manager here at FedEx. With me on the call, we have John Bishop, product manager of some of our most important digital products here, and Angus Knight, VP of product at Parcel Lab, who are going to be taking you all deeper into today's conversation. For those that do not know, Parcel Lab works with FedEx to power post purchase experiences. For decades, FedEx has been synonymous with dependable global transportation. As supply chains evolve, so does FedEx. While transportation remains at our core, today, we're building on that foundation with our growing suite of digital logistics solutions that deliver greater visibility and intelligence across supply chain, helping our customers make smarter, faster, and more informed decisions that turn insight into real impact. During today's session, we'll be sharing how the post purchase experience is evolving across tracking, return, and communication with AI. Whether you're looking to improve day to day post purchase operations, improve efficiencies, or stay informed on how post purchase can drive engagement and revenue opportunities, you're in the right spot. So a few housekeeping items before I turn it over to our speakers. Today's session is going to be recorded, and we'll be sharing access to the recording shortly after the webinar concludes. You're also welcome to submit questions at any time using the q and a panel on your screen, and we'll address them during our dedicated q and a segment towards the end of the session. If we're unable to get to your question live, we'll be sure to follow-up with you after the call. With that, let's go ahead and get started. I am pleased to introduce you to John Bishop. John, over to you. Awesome. Thank you, Jess. Good afternoon to our audience. Hi there. I'm John Bishop. I'm the manager of a product team at FedEx. We build digital solutions for FedEx customers. You know, my team works at the intersection of digital commerce, technology, transportation. Quick fun fact about me, I actually previously was in the omnichannel retail business myself. I was FedEx's customer for twelve years, so I have sat in the same chair that many in our audience sit in today. Now working at FedEx, my product team gets to solve problems for FedEx customers, which is great. So I will pass it to my friend Angus from Parcel Lab. Fantastic. Thank you, John. Lovely to meet everybody. My name is Angus Knight, and I lead the product team at Parcelab. Parcelab, for those who don't know, who aren't familiar with us, has been working in the post purchase and the return space now for a decade. I've been with the business for about eight years and seen I I would like to say I've seen it all. I don't know if I have seen it all, but it's certainly a rapidly evolving space. And I'm really excited to be digging in deeper because I think now that we're entering this crazy age of AI, there's so many opportunities for brands and for merchants to gain a lot of value within the post purchase, experience within this space, and we're gonna be exploring that today. Awesome. Well, now that you guys have been introduced to John and Angus, I wanna start us off by talking about myself. So when I am I first of all, I have a daughter. She's very young and so she is constantly outgrowing her clothes, which is fun for me, because that means I get to go shopping a lot more often. And because she's so young, I'm shopping online. And I can tell you that the post purchase experience for me when I am ordering online, ordering her clothes, as as soon as I click, you know, send, submit, whatever, my money is tendered. I'm going to my email inbox, and I'm checking to make sure, oh my gosh, did I order the right size? Did I order the right quantity? Did I remove that one clothing item that, you know, I realized was not on sale, that I shouldn't purchase? Otherwise, my my husband would be mad at me. So I would love to hear, the experience that you guys are seeing, perhaps, you know, yourselves as as consumers or or on the back end. So, John, what is your what are your thoughts on that? Yeah. Jeff, I love that you're making it personal. You're making about consumers because at the end of the day, it doesn't matter what any of us do for a living. We're all consumers, right, which I think makes us experts on consumer behavior, or at least I like to think that. But I would challenge our audience. Right? Think about the shoes you wear. Think about the treats and the medicines you buy your dog. Think about the snacks in your pantry, the cosmetics you buy and keep in the bathroom, your favorite streaming service, the car you own, etcetera, etcetera. You know, why do you love the businesses that provide you these goods and services? Because they meet your expectations. They exceed your expectations pretty much every time. You know, they never let you down. Right? So now think specifically about post purchase experiences with businesses that that ship to you. Right? Think about how much you are loyal to those businesses because they don't let you down. And think about how the way they make your experience great even after you've checked out and placed your order. Think about how that, like, influences your willingness to go back again and again, right, with your with your credit card. So, you know, think about how often did you have to check the tracking for updates on that order you were excited about. Right? And and did you ever feel out of the loop about delivery? Was there was there context missing? Maybe if something went wrong and you need to do a return or an exchange, like, you know, did that go smoothly? Right? Did they make it easy on you? So I can speak for myself. I am reasonably loyal to the brands that do this really well, and that's why I feel very strongly about this whole just general topic. Right? Is that as a consumer, I know I spend my money with the businesses that make this stuff easy. They do it right. And so, you know, the magic word here is loyalty. Loyalty equals lifetime customer value for businesses, right, across industries, across verticals even. No secret there. So, the thing we're really wanting to dial in here today is that customers are highly, like, remarkably engaged at the post purchase stage of the bigger shopping journey. So, Angus, gonna pass it to you. I think you have a lot of thoughts. I know your company spends so much time on this, of course. These moments are golden opportunities. Right? This is where AI starts to make, like, a a major impact and deliver real value. So take it away. Yeah. Absolutely. And I love how we've kind of begun this discussion, and it's been a very human experience, something that everybody can relate to. And I think everyone's had those times when they're looking forward to something and receiving it. And they've also had those those horror stories, you know, where everything's gone wrong and they haven't received the item for the big day. So we we know how it feels for it to be this very high attention part of the customer journey. But interestingly, the data that we see kind of on the back end also really supports that message. So anyone who's spent any time in email marketing would be quite familiar with the the typical kind of open rates and click rates you might expect to see. You know, you're targeting a lot of customers, and you'd be having a good day if open rates are hitting 20%. We see benchmark settings just just below that number from a marketing point of view. And then you see a click through rate of potentially up to 1%. Again, that's that's kind of, standard performance. But then when you look at the post purchase journey where a customer has actually been willing to spend money with you, you've got this window of time between that moment of order confirmation and the customer happily receiving their package and potentially even making a return where their level of engagement is extremely heightened. And so here, within this part of the journey, when we look into the data that we have visibility of, which is quite literally billions of these post purchase, touch points, we're seeing an open rate of six 60 to more than 80%, which is showing, you know, an an extraordinary level of engagement. And, amazingly, 20 to kind of 30% of those customers are then actually tracking their package. They're actually going onto the brand's, tracking page from that email communication, and they're tracking their order. And so I think that data really paints a picture of these billions of touch points that we have available to us to to kind of take advantage of. And, obviously, this conversation is also about how do we then layer in AI to do this effectively and to do this at scale. I guess you gave us a lot to already start thinking about. And I I do want to to hit on what you were just alluding to, which is, you know, customer expectations are only continuing to rise, especially in, you know, the fun online shopping environment that we're in right now. Everyone's shopping more and more, you know, online or some sort of hybrid in store online, experience. And, even though customer expectations continue to rise, a lot of post purchase experiences today are still really fragmented just based on all of those inputs, that you've just highlighted from a post purchase space. And it's, I imagine, very difficult to manage. So, John, what are your thoughts? Like, how how can the industry, you know, what is it what is the industry doing as it's evolving? How are how can we, you know, get ahead of everything? Yes. So you use the word fragmented. So I'm gonna, like, play off of that. Right? So the reality is many post purchase experiences are still very fragmented, which makes them less than ideal. I think we all accept that. But I think before I get into the why, I I just wanna sort of make a caveat here that, you know, no business has it all figured out. No business is perfect at this. You know, it's a constant work in progress. Right? And it's easy for businesses, maybe smaller or medium businesses, to think they're behind. Everyone should take a deep breath and understand everyone is challenged by having fragmented experiences that need to be improved. So there's lots of opportunity here, which is the great news. Right? So let's talk about why these experiences are fragmented. The primary reason behind that is because, you know, often the data is fragmented. So think about, you have product catalog data, you have order data, you have customer data, you know, about their buying histories and and such. You have shipment and tracking data from your partner FedEx. Right? And so you have all these different data sources. Will are they all in different places? Right? Have you, you know, really, like, brought them together? And so, you know, AI can be it's a exciting topic, of course. Right? But it can also be scary to a lot of people. And I think the reality is people shouldn't be scared of it because AI is really just about taking otherwise fragmented data sources, bring them together. Right? And this is where things like good architecture come in. You gotta have a good solid, like, data foundation. But, you know, bringing, disconnected data sources together then allows you to use, like, for example, machine learning. Machine learning finds patterns in data that we, as humans, just are simply not going to otherwise find. Right? In fact, FedEx uses machine learning to to make our delivery predictions more accurate for our customers. But, anyway, so you bring multiple data sources together. You can use machine learning. You can find patterns. By connecting these data sources and by identifying those patterns, it allows you to tailor the post purchase experiences. Right? You can also use generative AI sometimes to actually produce customized messaging that is more tailored to your customers. So that way you're sort of meeting them where they're at. Right? And you're you're speaking a language they're familiar with because you're using real data about them and their past experiences to sort of tailor it. Angus, I know this is a space you guys just spend a a crazy amount of time working on at ParcelLab. We'd love your thoughts about, like, what you're seeing in the market with with data and and how AI starts to shape experiences. Absolutely. And and I kinda love where you're going with this. Like, it does start with how do you connect these different bits of data. The question I kind of always start with is, like, why does that matter so much? And you you talked about having product data, order data, customer data, tracking data. It's because when you're actually in the customer's shoes and you're waiting for something, there's there's information that sits in each of these different areas that's part of the puzzle of how do how do you help me understand what's going on. You can tell me something's arriving today, but if I bought multiple different things and they're coming from different places, I'm thinking, well, which part of my order potentially is arriving today? And that's a you know, it becomes a more complex problem for for the customer to to kind of think through. So absolutely, that kind of connective element is is critical. You also mentioned predictive, use of AI, and we're certainly seeing that, using AI in delivery prediction is having a big impact. We're able to detect much earlier on in the customer journey when things are running behind schedule, than we ever used to before. But we we also see some other uses of AI start to come into this space. And broadly speaking, I kind of tend to categorize these into different ways. We see assistive AI, which is ultimately kind of leveraging AI to help business users actually do more, set up more, and I can share a little bit more about that, shortly as well. And then we we see kind of autonomous uses of AI. And these might be the sorts of things that we you know, our brains initially jump to. It's like, oh, I'll have a conversation with with AI instead of have a conversation with a customer services agent. But, actually, we're starting to go, you know, into a really exciting realm where now the quality of those kinds of interactions and we'll talk about this shortly, but the quality of those interactions is actually really high. So that's that's something that's that's that's certainly changing. But just briefly to kind of loop back to this assistive AI piece, I think from my point of view and and and for any merchants kind of looking at the post purchase experience, and you talked a little bit before effectively about this maturity curve of we're all at different stages of having everything figured out. And and the the punchline is you'll never have everything figured out, but you certainly get to a stage, you know, that that serves the business effectively. When you think about all the different permutations of how a customer journey could go, how could you ever as as kind of a mere human, how could you ever identify all of the options? I think that's that's one of those things that's just never really been possible. So you build for your happy flow because you know that the vast majority of customers are gonna have that kind of experience. Then you start to build for some of your exceptions, the ones that start to crop up more and more often. But what AI is now giving us from an assistive perspective is the ability to handle so many more configurations by just asking questions, you know, of our tooling. What what are the big gaps that I have in my journey? That's a question that before you had to try and figure out, and now you can actually leverage AI to find out. Or what are the best performing communications touch points that I myself am not sending as a merchant? And and and this is starting to really change, I think, the way that we're looking at the post purchase journey. It reduces the energy and effort required as an investment to make this journey effective, and it increases the performance so that you you're basically giving customers better quality information about everything that's going on, and and you're able to give them that at scale and in a way that is much, much more personalized than it ever was before. So I think we're kind of on the precipice of something very, very exciting, and already we're seeing so many of these use cases come to fruition. Angus, thank you for sharing. I I would actually love for us to talk more about AI, but would love to double click into, tracking and how that could be a strategic advantage leveraging AI. So I I know traditionally, at least from the consumer side, you know, tracking is the most important thing for me. Again, I'm constantly checking on where is my package, when is it gonna be delivered, especially if, you know, sometimes you forget some people's birthdays and and so you have to make a very hurried purchase, and then you just hope it arrives on time. And so those tracking updates definitely give peace of mind to consumers. How can we how can, AI transform tracking? John, I'll start with you. Well, first off, Jess, if you're late buying people presents, it's a really good thing you work. at FedEx. But, yeah, what you know, with that said, right, so, I feel like I I broke a record here a bit, but let's again think from the consumer perspective. Right? Consumers simply don't want to play detective. No one wants to have to be the detective to figure out what is going on with my package. Right? No one wants to call in and wait on hold. Right? We as consumers, we as humans, we want quick access to information. Ideally, we want it self-service. You know, I I appreciate when a business has real live humans I can interact with should that be needed. But, honestly, if it's not needed, then let's let's make it fast. Right? And if, an AI powered chat experience can get me what I need, more self-service, even faster, that would be amazing. So the reality is you need to you need to make sure you have a little bit of something for everyone. Right? Because different consumers are gonna have different needs. But, anyway, I wanna point out that tracking experiences aren't purely, you know, making them better is not purely a matter of, like, support and saving money. Right? These are also, like, very high revenue moments. Right? Tracking experiences like like Angus said, these create, lots of clicks. Right? Your shopper is shopping again. And I gotta say as a a representative of FedEx. Right? FedEx, of course, like, we invest a huge amount of money, time, effort into making FedEx's own tracking channels better, whether that be our mobile app, our website, delivery manager, etcetera. But, ultimately, you know what FedEx actually loves? We love it when our customers, the ship with FedEx, make their own tracking experiences for their own customers amazing because what it drives and Angus, I think, is gonna dig into this a little more. What it really drives is more orders. More orders means more shipments, and and everyone loves that. Right? Especially FedEx. So all that to say, you know, elevated tracking experiences, yes, they reduce those WISMO calls, WISMO being where is my order. Yes. Great tracking reduces that. That's lowering support costs. Everyone loves that. But, ultimately, there's also, like, a whole other side of this coin, and that's, like, great tracking as a revenue generator. Right? So, Angus, I think you have some really good stats, maybe some factoids for us about tracking as a revenue generator. Is that true? Absolutely. And I love, like, when you look at this visualization, it's it's so clear because you you've kinda got your down arrows of things you're trying to drive down around cost, and then you've got these up arrows of things that you wanna promote and drive up. And I think even when we look at extremely mature, retailers, e tailers, folks who are selling things online who have a lot of complexity and have tackled that really effectively in the post purchase experience, the core value proposition is still like this. We're still trying to reduce costs and improve experience. And as a result of improving experience and leveraging traffic, we're trying to drive revenue. So I think this is a great way to be kinda looking at it. Digging into some of those stats then and some of the kind of drivers and things that sit behind this, we talk about the post purchase experience as being a high engagement channel. And I feel like sometimes just saying high engagement channel is is almost not doing justice to just how high engagement that is. So the the the shipment tracking page in, honestly, countless customers that I've been fortunate to be able to go behind the scenes with and see their Google Analytics dashboard with my own eyes, often the top visited page is the order tracking page. What that tells you is that customers really care during this part of the journey, and and they're they're voting with their clicks as well here. So, you know, many people are coming through to track. Then when you start to or you continue to look at that data, it continues to tell a story of high engagement. So on the website, there you would have a conversion rate that you would expect to see of the average shopper. And broadly speaking, in the post purchase, space, customers continue to transact in that way. And then when you look over over the kind of the whole customer journey, you might be sending three, four, five high engagement touch points. Those are then driving this stat here that you see, the 1.1 average times a customer visits a tracking page per order. So per order, the customer is visiting the tracking page ever so slightly more than once on average, which means that you get you gotta really and this is a very consistent and reliable figure as well that we see. And then they're transacting, and you can see this two to 3% is is quite typical in the fashion space. This would be the number of those customers that then go on to make another purchase, and they usually do that at the average order value. Now you don't have to, have a degree in maths to to do these sums and realize that you're getting back just as much traffic as the customers that bought from you, and then you're you're effectively increasing GMV by potentially 2% through, additional purchases that these customers are making. So so this whole space is very impactful, but it's it's not only the revenue side. And I know that the the the tracked revenue is only one part of this, but, it might have to be a full day session for us to go line by line through each of the the things. But there's also, you know, an amazing kind of cost reduction aspect here. And this is an area where AI is really stepping in to to start to make a huge impact. So we talk about Wisma or where is my order. In returns, it's Wisma, where is my return. But but looking at Wisma, it continues to be one of the highest contact drivers that we see. It's almost invariably within the top three contact drivers. And when you think about, like, your customer services organization, the people that sit in it, depending a bit on the brand, you know, some of those people have been with the business for many years. They have a great understanding of the products. They understand the customer. They know the whole proposition. Often, they would want to actually spend their time selling, advising, and selling. And those people have too much skill and value to offer to simply be spending all day responding to whereas my order queries that will often involve a very repetitive kind of, you know, look at the order, understand what's in the order, try and find the tracking information, and then commute that communicate that back to a to a nervous and anxious customer. And I think this is a scenario where it's important to be able to get get to the people at the right point in time, but actually often these queries don't don't need these, skilled people who could be spending their time helping other customers faster. And this is this is the area where AI is being hugely disruptive. So when we look at scenarios around where is my order, we're seeing that slightly more than 80% of those queries are relatively straightforward transactional queries that can be answered by AI if AI has access to all of the data around that order and transaction. So it's not just access to the tracking feed. It's also an understanding of what was in the order and what is the customer saying to us about what they're worried about. They might be asking about one particular part. If they've got an event at the weekend, they might have ordered many outfits, but, actually, it's one particular outfit for that event that's the crucial one. And here, it's it's absolutely within the capabilities of AI, to be able to identify the intent that that customer comes with and to find out the specific status of the bit that they're asking about and then communicate that back in a way that that's impactful. And if that can happen within seconds or minutes of of a contact being raised, then it saves an enormous amount of money for the merchant, but it also is an incredible experience to have as a customer. Because it and it goes beyond the, I think, the traditional chat experience that from five years ago, we all used to hate, which was just a repetitive answer that would tell you the same thing again and again. And then kind of the icing on the cake is that those sort of 18% of queries that cannot be answered simply because they they require something that goes beyond the data that AI has access to, those queries can then be quickly escalated. And so the the same customer services organization that may have previously been kind of swamped by those is able to focus on the ones that actually have a a high level of value. So this is this is, I think, you know, some of the numbers that sit behind, what what's on offer in this space. Yeah. Angus, I'm really glad that you highlighted that because I do think that while, AI will absolutely change, and already has started you changing WISMO, it's also about the important purchases, you know, the the bride to be that's looking for the wedding dress for her wedding, where you you still wanna talk to someone. With with something that important, you still wanna talk to a human to make sure that that the wedding dress gets to the destination, in in a timely manner. But the agents still can be empowered by AI and get that information to your point. So then that way, that resolution can happen faster and, and the bride feels satisfied with the conversation and with the level of detail. Yeah. Absolutely. I think it's it's just this, like, you wanna spend the energy where it makes the most sense, and, we're in a different position to make to make those decisions, and that varies by merchant as well. And so that's where it's so important to offer up the ability to the merchants to kind of also really input into that decisioning. Again, something that the AI is really facilitating now. I know we could talk so much about AI and tracking. You did tease out return. And so I do want us to shift gears and and talk about how intelligent returns can also, create a competitive advantage. So, John, I I do wanna start with you. So with returns, it's it's kind of a I'm gonna call it a necessary evil. But I think that is it can actually be a huge benefit. And and if done properly, perhaps even be, a huge growth lever if it's done properly. What what are your thoughts? And I think you have some personal experience with this as well. Yes. I I'm kind of a nerd when it comes to returns. This is the thing I've spent too many years, thinking about. And so, you know, as a as a re an omnichannel retailer from the past, I can tell you firsthand that managing returns well is a huge business driver. So, our business sold golf clubs. Right? Golfers and and forgive me to anyone in our audience who's a golfer. I'm gonna call you out here. Golfers are a pickle lot. Right? Golfers want the newest, latest, greatest thing they see on TV. They wanna buy it. They wanna try it, and in some cases, they wanna return it. Right? And so our business, we had some different subsets of customers. And so we had really like our VIP group. The the customers that spent the most money, they paid full price for the newest stuff. You know, those are amazing customers. You wanna take care of them. Once in a while, they need to do a return. Great. You need to make it easy. If you don't make it easy, they might go somewhere else. Okay. So you need to make returns easy for one group. Then you have another group, and it's those serial returners, the ones who seem to return everything they buy. And so, ultimately, you're you're you're losing money on them because you're giving full refunds and you're you're having to cover return shipping costs. And so you're like, wow. This group costs us money. Don't love these customers. Well, it's a thin gray line between the first group and the second. And then there's even another third gray thin gray line between those groups and the the bad actors. Right? The ones who wanna literally abuse, return policies, for the sake of fraud. And so the the challenge is how do you make returns experiences amazing for the people you wanna make and amazing for? How do you make it easy? Right? How do you make it as self-service as possible? But how do you introduce I'm gonna steal Angus' word, friction. How do you introduce some friction to make sure you aren't getting you know, you aren't losing your shirt over over here? And so, I really just wanna sort of call out that where AI, like, fits into this is that AI and and great returns technology allows you to sort of customize different experiences. So not every group gets exactly the same experience. Right? So, anyway, I if I could, if we had, you know, a camera on all of our audience, I would totally ask for a show of hands. But I am very confident if I said, like, hey. Show of hands. How many people consider returns a real pain point today? We get a lot of hands. Right? And in my book, as a product person now who thinks a lot about returns, so this is great opportunity. Right? If if you consider returns a pain point, then, like, flip the script. Right? So, Angus, I I would love your thoughts. You guys, work real hard for customers to work on those, like, guardrails? I think that's another word you use. Right? How do you introduce some guardrails and make sure you have the right returns experience for the right customer? You wanna, you know, expand upon that? Absolutely. Yeah. You you painted this really clear picture that returns as a kind of a domain has evolved into something that I think it didn't used to be so much. I think there was a time, you know, in in our kind of economy where, merchants were in a position to just throw money at returns and say, hey, returns is our acquisition strategy. Basically, it's our strategy. Just yeah. And I'm, you know, exaggerating a little bit. In certain fashion businesses, that was, a core part of the proposition. And that environment has changed. And when we have a lot of conversations with brands these days, profitability is a term that comes up more and more than and certainly more than it ever used to. We used to have revenue conversations all the time and now it's become, you know, much more split. And when you look at the the detractors from profitability, returns is always on the list. So that is that is exactly the context, you know, where you have to start making these these different decisions. What's what's fascinating is when you begin working with a merchant who's overhauling their returns process, you start having conversations around things like you know, they they might ask, do you recommend that we charge for returns or not? And that is already such a charged question because it kind of implies that you can only do one thing. You you know, you choose a policy and you stand behind that policy for a 100% of your customers. And, of course, you need to advertise a policy. That's that's clear. And you also need to abide by all the legislation in in all of the different markets that you serve. So you do have those kind of legal guardrails or or or, you know, and risk guardrails there. But then within that, you don't have to treat every single customer the same. And I think one of the things that that's fascinating here is you you have a portion of customers that you do want to invest in. They're the customers that have a great track record with you. They spend a lot of money. They love to buy from you. They don't always get it right, or maybe maybe you don't get always get it right in in, you know, there's there's kind of that that moment of, I actually do need to send this back. And, we don't wanna penalize those customers because we we began this whole conversation. And and, John, I'm really glad you used the term customer lifetime value from the outset because for so much of what we see in the post purchase space, that that becomes the North Star. How do we promote customer lifetime value? And we certainly don't promote it by really frustrating our best customers so that when they have their first returns experience, you know, six orders in, they never ever wanna come back and shop again. That that isn't gonna be good. So so that's the scenario where we we start to think, okay, what parts of this experience could we make more appealing for them? Could we give them even more convenient but potentially slightly more expensive returns options, a collection from their their home, for instance? Or do we actually wanna offer this customer an exchange or or even a refund that gets initiated earlier in the customer journey? So we decide we trust them. If that's the case, when they drop their package off, let's just give them the refund already. But you can't do if you've ever tried to get that kind of policy through your finance team, which I'm sure many folks have tried, that is usually met with with a a pretty angry, look. And and therefore you've got to mitigate that risk. And how do you do that? You do that by finding a different segment within your customer base that are not the customers you want to be winning. They're the customers who are regularly returning almost everything that they buy, or they're the customers that, are exhibiting other signs of risk, related to to their purchases. And those customers, you you kind of wanna they're the ones that you do wanna charge, and you don't wanna offer the expensive collection options from. And you wanna wait until you've got that product in your warehouse before releasing the refund on those customers. And so I think this is again, you know, AI absolutely underpins this because there are so many different types of configuration that need to exist in this landscape. But this is the type of conversation that we're having now more than we ever used to, about kinda how how do we actually evolve the returns proposition so that it is effectively able to, to help the business needs, basically. So, yeah, I think I think this is this is kind of some of what we're we're seeing emerging in this space. I I love the thought that we can personalize return options to create more opportunities in order to retain customers and, you know, strengthen the loyalty. At the end of the day, that's that's the whole intent. Right? So it's it's exciting to know. It doesn't have to be a one size fits all. Inga, in the same way that you're able to share some stats from the tracking side, can you can you share some stats from the return side? Absolutely. Yeah. And returning customers is interesting because we talk about it so much as this like a profitability sync, you know, it's expensive, but then when you actually look at these customers, they are a huge opportunity because and I think everyone again, back to being a normal consumer. When you return something, you know you're gonna get a refund. When you know you're gonna get a refund, spending again kind of kind of feels like free money. So there is this psychology to it that sits behind it that means that people are very, willing to transact. And, again, that story is told in the data. So we see when we look at the Google Analytics transaction data from customers who are making a return, who then come to track their return, they are three times more likely to purchase again than those who came to track their order. Now you you can think back to, you know, fifteen minutes ago when we were looking at the stats around order tracking. We've already decided order tracking is a very profitable and revenue driving activity. So the fact that this is is is, again, more powerful per return means that it does represent a huge opportunity. So that that is a very significant revenue stream and then you can also, you know, it compounds when you start to add in other options like returning to store credits. Again, a customer is is is much more likely to return or to to return to store credit than they are to go and buy store credits. And if you add some levels of incentive, you know, a little kicker like a 5% bonus or a $5 bonus to to get their store credit option instead of a cash refund, then you start to see a lot of movement in that direction. And, obviously, you know, that that really moves the needle for for businesses that are trying to retain, revenue within the business. And then I think on the data theme, you know, we we talked a little bit about some of the customers that you might not be trying to win at all costs. And what we see in the data is that there's this kind of 11% of customers that are responsible for about a quarter of all returns. So you have most likely within your own business, a segment of customers that are your your heavy returners. And I think what's what's good about understanding this segment is, firstly, you can speak to these customers in a slightly different way. You can adjust some of the messaging. You can reduce some of the promotional content. You know, there are all sorts of adjustments that you can make. And, again, AI makes these things really fast and easy. You don't wanna be offering up AI predictions to a customer that you know is most likely going to be returning their products. But also what's great is you can you can kind of introduce these gentle aspects of of friction to the journey, but you only have to do that for this 10% of your customer base, because they're the they're the heavy returns drivers. So they're the ones who are introducing cost. So, yeah, this is this is a little bit of the data story about, you know what we're seeing in in this rapidly evolving returns landscape. Thank you. I love that. You know, again, I know we could talk way more than the ten minutes that we just spent on returns, but, you know, I I think I need to wrap this up at at some point just so we can get to q and a and get some questions answered. But before we do, you know, just to summarize, and as you guys have been talking today, the one thing that kind of hit me was, the bummer that what we talked about today, consumer behavior that is, you know, what's what's happening today does not mean that's what it's going to be tomorrow or next week or next month. Consumer behavior will constantly evolve and will constantly change. And so what we figured out today is not gonna be the truth tomorrow. I think that's where what you guys hit on, why it really matters. You know, the AI is going to continuously pull together patterns that we're we have not yet seen with our human eyes. And, the good news is in the post purchase space, there's tons of data between returns and tracking that can populate different patterns and can help us evolve our strategies before we might even realize it. So would love to hear parting thoughts from both of you, before we do get to q and a. John, I will start with you. Sure. Let's see. I gotta make these relatively concise. Right? So, I I I think you alluded to it, Jess. The reality is that everyone should accept post purchase experiences are never done. I know everybody said that once. They're never done. They're constantly iterative. You know, you're, you're you're always going to be trying to improve these things. So at FedEx, honestly, one of the best parts of my job is that FedEx works with every big business brand retailer you can think of, essentially. And so, you know, we see businesses that do tracking experiences. They do returns experiences. They do them really, really well, and they're still coming to us saying, how can we make this better? Right? So it's a constant iterative thing. And we talked on just very quickly about how, you know, bringing data together and applying things like machine learning, they help you find patterns and data you haven't found otherwise. You know, generative AI helps you create, customized tailored messaging and content when you need it, things like that. But AI also helps with things like analytics. Right? Analytics, AB testing, you know, just optimization of of different messaging experiences, the timing of messaging, things like that. AI is putting businesses that never really had the time, you know, manpower, and and expertise to, like, do these things well. AI is allowing them to start to optimize and and do AB testing and really, like, up their game to the level that enterprise businesses are at. So that's really, really cool. But, Angus, you know, as a fellow, like, product management practitioner, I would assume you agree, you know, these post purchase experiences are, like, never done. Right? What's your thought about just the constant iteration and evolutionary cycle here? Yeah, I totally agree. I've got, I've got so many thoughts on this, but I'll also try to be brief. I mean, you're right. They are never done because our customers change and our businesses change and the business needs change. I think there's a really key point to underline here that they're all it's also worth keeping up. We see merchants who have switched from having a solution in the past to kind of reinvesting and and maybe finding a different partner, maybe doing things in a different way, that then see an enormous incremental benefit from the first solution to the second. I think that that that jump is is, like, needs to be underlined, because if you if you feel like you've kind of done post purchase and it was difficult and you don't know if there's anything more there, I can tell you now there almost definitely is. And then John, to your point, you know, yes, AI tooling is just making these things so much easier. I mean, we're all able to well, I don't I don't know if we're all able to, but many of us are able to accomplish more tasks in a day now using AI tooling than we were before, and that same logic applies if you have all of the right tools in place here. So, yeah, I think I think this is you know, we we see the modern business approach this as a a problem space, the post purchase space that needs the right level of ownership. It needs to be owned in the right way. And I think we often see, you know, product management functions also become part of they have a a view over the order journey, the customer journey from from the whole order life cycle. So I think you gotta organizationally be set up to own this in an ongoing way. But then when you when you are set up in that way, continued investment in this space, even from just a portion of your team, it doesn't have to be all day every day, but there are there are so many incremental benefits that could be made. And those things translate into additional revenue. They translate into a better returns experience. They translate into lower cost due to fewer queries, and and I think that's what we what we all wanna see in this space. Well said. I think it's a good way to end things. So thank you so much, Angus and to John. That brings us to the end of our main presentation today. And at this time, we're actually gonna open the floor up for any questions. As a reminder, please feel free to submit them in the q and a, chat panel that's on your screen. If we don't have time to get to your question live, we will follow-up with you guys, directly after the session. I do see a question that I'm just going to go ahead and throw on the table to start us off. So Angus, I think I'm gonna throw this one to you first. You talked about the importance of event detection, but how do companies figure out which moments actually deserve action versus what is just noise? Yeah. I mean, everything everything in this space has to start by by stepping into the customer's shoes. So I think and, you know, one of the number one things that we encourage, the merchants we partner with to do is to to to keep being a customer, keep ordering things, see how that experience looks. So I I think there is an element of you you really have to just follow that flow end to end. Every time you find exceptions and customer friction, particularly if customers alert you to this by getting in touch, double click on those orders. Try and understand, like, what what would have improved this experience, Like, which part of the messaging the proactivity was missing. This is, like, one of the top ways of finding gaps in your notifications and communications that you can then fill if you have the the right, you know, supporting technology in place. And I think that's also then kind of leads us a little bit back into this AI piece. You know? In in a lot of the tooling these days, you can actually just ask, look at this customer's order, you know, the tracking situation, the messages we sent. What were we missing? How could we improve this? And you can often also find these kinds of proactive suggestions. I I would kind of one thing I would also just add is you wanna you wanna focus on, the happy flow that everyone experiences or the the messages that go to a lot of customers. Because if you've got millions of customers and you chain make one change to to your happy flow messaging, it's experienced by millions of customers, so it has a very large impact. And then you also wanna focus on the noisy edge case contact driving scenarios that come up enough that they're on your radar. You know, it's something that that drives friction. It frustrates a lot of people. Anytime someone reaches out to you about a problem, you gotta remember that there's a whole portion of your customer base that are the quiet critters that are not gonna reach out to you, who go through the same kinds of experience. So I think it's this balance of focusing on kind of the majority and what will have a big wide reaching impact, but then also finding some of these particularly noisy edge cases that you can then, delve into and and make improvements around your messaging, how you present things, maybe introduce new touch points, that kind of thing. Great. Thank you, Inge. John, anything to add? Otherwise, I'll I'll hop to another question. Yeah. Actually, no. I think Angus said it beautifully. Right? If you don't mind, Jess, I I plucked a question from the q. and a here. I'll I'll yeah. Let me tee this up. So in a in a nutshell, it says, you know, personalization sounds great in theory, but without perfect data, how do you do it? Right? That's really the question. And so, to to kinda go back to where we talked about fragmentation of data and stuff, understand that you're never gonna have perfect data. Never. I've I've talked to a lot of FedEx, customers, and I don't think I've run into one who said they had perfect data yet. But so you're not gonna have perfect data, but, absolutely, you do want to make sure you have a a good and relatively simple plan to consolidate otherwise disconnected data sources. You do need that foundation. If you don't have that foundation, there's not really any way to build on upon it. Right? So okay. You gotta start somewhere. It's okay to start really, really, really, really small. If nothing else, you know your product catalog and you know what your customers have bought in the past. Right? So use the historical order data and your current catalog data, bring those together. Right? And that allows you to put, like, upsell like, tailored personalized upsell recommendations in, you know, those those branded tracking messages that can also drive revenue like Angus talked about. Right? So, the personalization thing, it it would be easy for it to be really scary. Right? Don't let it be really scary. It's it's okay to start small. It is critical just get the data foundation right. You gotta do that. You gotta bring your data sources together. And then, you know, again, start simple. With the good loyal customers, you have lots of data on them. Start personalizing their recommendations, and then watch the analytics, see how it actually drives, you know, more orders, more average order value, more lifetime value. Right? So, anyway, you gotta get started. And if you're waiting for perfect, you're gonna be waiting forever. So that's just that's just the reality. I think that's where AB testing kind of comes into play that y'all were talking about earlier. So thank you, John. Yeah. Absolutely. So looking at time, I think we might have time for one, maybe two more questions, before we end this. And I'm I'm gonna pluck another question out, if if you guys don't mind. So, what it says, what impact does proactive communication actually have on customer behavior and brand trust? And, Ines, I'll throw it to you. Yeah. I, you know, it's interesting. It seems a really kind of surprising stories here because, you assume you assume a lot. Right? But you assume that a customer that's had something physically go wrong in their order journey is gonna be annoyed regardless of how you tell them. You know, if your package is late, it's late. Being proactive doesn't change it being late, but it does change how it being late feels. And it turns out that people have feelings, and that is a very large part of their engagement with you as a brand. And there was actually one, one particular merchant I have in mind here. They were extremely focused on their customer promise. So the date that they told you when you were in the checkout, they would kind of live and die by that date. You know? It was it was it was really, really critical for them. And they set up a message, using our technology that that was basically looking at that date and kind of constantly tracking whether or not a package was delivered by the end of that day. And, it doesn't sound it doesn't sound groundbreaking. Right? Because with all the predictive things that we have in place today, you know, you could detect this much earlier. But what they were doing is if it didn't arrive, they would send an email that that quite simply said, we're sorry that we didn't meet our promise. Here's, a token, a voucher that you can use on our store for $10 off your next order. And that email was the single highest revenue driving email that that business had ever sent. And I think that I think that paints the picture. And then they started to look at other data. So not only was it that the email was actually causing customers to purchase, then they looked at how do those customers behave again in the future. And what they saw was that the net retention rate of those customers was 3% higher than the net retention rate of the average customer. So that customer didn't receive their package, but they did receive proactive communication, and their customer lifetime value was quite literally higher than the average. So I think if that story doesn't tell the tale of how important being proactive does, you know, is then, then I'm probably out of stories. I that's fantastic. Yeah. And, Jeff, I let me I just wanna interject one quick comment, and then I'll I'll let you close it out. Right? So, you and Angus both spent quite a bit of time in our hour here alluding to, a number of things. I don't know if we actually use the words explicitly, so I wanna do it. Right? Trust and emotion. Right? All of us need to realize that on the other side of these screens, the phone, the the the text, the smart device is a human being. Right? And Angus, I thought, well, you just said it was just amazing. It's a human being. Right? And that human being, you know, they have feelings. So at the end of the day, you can use all this technology. You can build business rules. You can get yourself the right tools. You can you can bring all your data together. You can use AI. You can do all that. But everyone should always remember, at the end of it all, there's humans involved. Right? And they have feelings. And the goal is to manage their expectations, manage their emotions, and build trust. And if you do this stuff, everything we spent fifty three minutes talking about, if you do this stuff really well, it builds a lot of trust. Trust turns into dollars. And I I mean, I'm sure our audience knows that, but it's one of those things. It's just once in a while not a bad thing to hear. So I'll I'll get off my soapbox. But, Jess, I'll I'll turn it back over to you if you wanna close this out. Yeah. It's it's a great note to end on. So thank you, John. And once again, thank you to both you and Angus for taking time out of your day to, to run through, all of these slides. Such great information. You know, before we do close out, I wanted to highlight a great opportunity. So if you guys, are interested in taking a deeper look at FedEx tracking plus and returns plus, we'd love for you to join our new live demo series beginning next week. These are short interactive fifteen minute walk throughs led by our expert solutions consultants, and they're gonna give you a live look at the FedEx digital solutions that bring value beyond the delivery. Our live demos are pitch and pressure free. We just have expert insights and real world use cases for you to see in action. Our first session is going to be kicking off on Tuesday, June 23 at 11AM Pacific time, 2PM Eastern time. We'll take a look at how you can easily create a fully embedded on brand customer experience, different ways that AI can help streamline tracking and returns workflows, and even what the experience actually looks like from your customer's perspective. You'll also have the chance to ask your questions and have them answered live during the session. And this is just the beginning. Every month, we will spotlight a different digital solution so you can join the sessions that are most relevant to your business or you can just follow along for the full series. So if this is very interesting to you, somewhat interesting to you, and you wanna learn more, please feel free to scan the QR code that's on your screen right now to sign up, and we would love to see you there on our first, session on the twenty third. But with that, we thank everyone who is on this webinar for joining and hope you have a great rest of your day.