Add To Cart: Australia’s eCommerce Show

Stop Customer Problems Before They Start: Inside Keeyu’s AI Ops | #578

• Nathan Bush • Episode 578

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In this episode of Add To Cart, Jevon Le Roux joins Nathan Bush to share how Keeyu is turning customer service on its head. Instead of managing complaints, Keeyu’s AI agents proactively detect and fix order issues (like stuck parcels, refund delays, and failed payments) before the customer ever asks, “Where’s my order?”

Today, we're discussing:

  • Why most CX tools are stuck in reactive mode, and how Keeyu flips the model
  • The moment Jevon and his co-founders realized they could automate complaint prevention
  • What a “customer promise” is, and how Keeyu uses it to track every order
  • How AI agents are solving operational issues across 50+ ecommerce systems
  • Why leading retailers are using Keeyu to reduce ticket volume and team burnout
  • Where ecommerce AI is heading, from automation to intent-based prioritization

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SPEAKER_02:

They didn't want to complain. They didn't want to have to chase up something you should have just got right. So we flipped that model completely and we've fixed the problem before the customer even knows it exists. Kiyu is like an immune system. You don't think about it when it's working, but it's constantly defending the experience. We're not trying to re-educate people to shop. We're taking away something they never wanted in the first place.

SPEAKER_01:

Hey, it's Nathan Bush or Bushy, joining you from the land of the terrible people here in Brisbane, Australia. I became really interested in today's guest when I came across their website, and the idea really resonated with me straight away. They were claiming not just to fix customer service, but to prevent it. In an age where AI is claiming to be able to process tickets at the speed of light and to be able to automate a lot of the customer service, this company stood out to me because they wanted to prevent customer service, get to the root of the problems, not just expedite the mess at the end of it. And I think that's really interesting. And I think it follows up well on our episode recently with Emily Elvie, where we dove into customer service really for the first time and we looked at what makes a great customer service team and how to run it efficiently. This episode today is a great build on that. Jevan LaRue is the co-founder and the CEO of Kiyu, an AI-powered operations platform that fixes fulfillment, payment, and delivery issues before customers even notice that there's something wrong. Not only is Jevin the co-founder of this startup, he actually has a really great background in retail, leading brands such as Surfstitch and PE Nation. So he knows the ins and outs of what makes a large-scale e-commerce business. Jevin saw firsthand how disconnected systems and manual processes were, and that they were burning out CX and ops teams at the same time as having a pretty rubbish customer experience. So he, along with his co-founders, built Q to change that. And he's already working with some really big names like Decuba, EHP Labs, and Budgie Smugglers, to change how they think about customer service from a reactive to a proactive approach. In this conversation, we get really practical around what this means. And we talk about what preventive customer service actually looks like in action, the kinds of tasks that you can expect ops teams never to have to do again, thanks to AI and automations, how to measure the impact of problems that might never happen again if you fix them. And what the future of proactive operations looks like as AI agents start quietly running e-commerce in the background by diagnosing problems before they become significant. Now, before we jump into today's episode, I want to say a huge thank you to our sponsors, Shopify and Clavio, who have supported AdDicart all through the year. Thank you for powering the Ad Descart community and helping us bring you these amazing interviews every week. All right, let's get into it. Here is my conversation with Jevin LaRue, co-founder and CEO of KiU. Jevin, welcome to Ad Descart. Hey, Nathan, great to see you, man. Thanks for having me. Oh, I am very much looking forward to this. We had an interesting pre-chat where I had to ask you. I was like, look, I know we've had a few conversations before this, but I've never had to actually ask you, how do I pronounce your name correctly? Is it Jevin? Is it Javon? Is there some other version of it because I'm a bogan and you know, I want to make sure I get it right. And then you said you've come up with a whole new realization that there's a whole bunch of people saying it in a way that you'd never heard before.

SPEAKER_02:

Yeah, yeah. So there's this thing called Jevin's Paradox and that the uh AR world seems to be grabbing onto that goes back to the 1800s. And uh they've been talking a lot about it now. And and it's sort of weird when you've heard your name one way, and then people in Silicon Valley are saying, Oh, Jevin's Paradox, Jevin's Paradox, and how important it is to the world of ALR from, even though it goes back to the 1800s. So, yeah, it's good to hear my name pronounced correctly.

SPEAKER_01:

There we go. And your Silicon Valley bros have just changed the way your name is pronounced for everyone else. Yeah, crazy. Now, we have so much to cover today because you've got a rich history in retail from your first job of selling door-to-door for Billaborn through to managing the teams at PE Nation and Surf Stitch through to developing KiU, which we're going to talk about today. Quite a journey there.

SPEAKER_02:

Oh, yeah. And I and thrown into that a bit of coffee franchising and you know, so like a whole bunch of different stuff, right? But yeah, it's been an interesting journey. I actually started my career as a professional surfer in the uh mid-90s. Yeah, mid-90s competing on the World Tour for like a bunch of years, and that sort of led to Bililong. And yeah, from being a Bililong sales agent in the uh 2000s to building AI agents for e-commerce operations, it's quite a journey and with a few stops along the way with different adventures. And and and that's the good part about building something ground up from nothing, is it's not an unfamiliar place. I've I've sort of had to do it a few times and and it's good fun.

SPEAKER_01:

Yeah, wild. Do you still surf?

SPEAKER_02:

Uh, not as much as my son.

SPEAKER_01:

You pass the gene on.

SPEAKER_02:

Uh yeah, not as much as him. He gets in the water way more than I do.

SPEAKER_01:

Well, I want to start where you are today with Kiyu, and then I've got no doubt that we're going to hear some stories from your background as well, weaved in there. But yeah, when we were chatting, I thought this was fascinating because recently we've had Emily Elvie on the show. And for the first time, we really dug into customer service and she gave us a great perspective on that and how to do that effectively, how to measure it, and how to make sure customers get what they want. And you keep your team happy, especially over peak season. It really caught my interest when we were talking because if you bring up the KiU website and anyone following along at home, KiU as in K-E-Y-U, bring up the website, and the first thing you see is help desk managers complaints. KiU prevents them. And it's a really interesting concept, one that I hadn't seen out there before. What do you mean by that?

SPEAKER_02:

You know, before I dive into that, let's maybe sort of like frame up the crux of the problem we're solving first. So let's just take us back to where a consumer is. And, you know, we've all been there. We order a order a birthday gift online, it never arrives. There's an email, no reply. Make a phone call, no pickup, chat with a bot, no resolution. And finally we get we give up. And, you know, for them, it's a hassle. For the brand, it's a lost customer and a hit to trust. And this happens millions and millions of times a day, right? Each delayed or missing order is a small crack in customer loyalty. Behind the scenes, CX teams are buried in where's my order tickets, chasing data across five, seven silos systems. And that result is always one thing, right? Late deliveries, missed refunds, wasted hours, frustrated teams. So in every single one of those issues costs time, money, and repeat customers. So, really to hit to your question, I guess today, most customer service tools are built to do one thing, react to complaints. A ticket comes in, it's because of a late delivery, a missing item, a refund delay. And the help desk is really built to manage tickets so that customer service teams can triage them, right? Clear tickets as quickly as possible. Clear tickets as quickly as possible. And you measured on first response time, resolution time, customer satisfaction. But because you're fixing something that they didn't want. They didn't want to complain. They didn't want to have to chase up something you should have just got rife. So we flip that model completely and we fix the problem before the customer even knows it exists. So if a parcel hasn't left the warehouse, we catch it and push it out. If a payment fails, we retry. If an item is out of stock, we place it on back order. If a return is stuck, we flag it for resolution. So sort of instead of managing these complaints, we're preventing them. Because if you fix the ops issue at the route, there is no complaint. And that's proactive e-com ops and that's the difference. And it means teams spending less time firefighting and customers never have to ask again, where is my order?

SPEAKER_01:

So let's dive into one of those, maybe pick where is my order? So I think that's a very common problem is that maybe dispatch times get blown out, which leads to longer lead times or longer delivery times for a customer. So instead of it leaving the warehouse within 24 hours, we've had Black Friday, whatever it is, it's blown out to seven days or the item's not available where we thought it was. How do you catch that? And how are you catching that that the WMS or other systems aren't catching?

SPEAKER_02:

Yeah, so we're in a unique position because what we are is an orchestration layer, right? We're not a point solution. And the way orders run today is they captured on a storefront, they process through a payment portal, they go through an ERP, a WMS, pickpack ship, carrier integrations, deliver and return. And each of those point solutions are doing a good job performing their function. But they're not designed to detect if an order doesn't push through, is held up. And so what we do is we connect all those systems together into one centralized platform. And we use the customer promise, which is order before 12, pay express, ship same day, get tomorrow. And we use that customer promise and work backwards along every single touch point and say, oh, this order hasn't progressed to where it should be at this point. And then we flag that in the centralized platform in a very clear, visible way. And that then is either red, as then it's broken the service level, or it's amber, it's about to, or it's blue, it's moving through according to plan. And when it hits amber or red, then uh kicks off a workflow that's associated to resolving that issue that our AI agent then takes on and runs through the resolution uh all the way through. So let's use an outer stock, for example, a lost in transit, for example. We identify that that order hasn't moved between different stages for a certain amount of time, and then that is likely a lost in transit. And then we start the process of finding alternative stock, placing an order, putting it onto Express so the customer gets it next day, shipping it out to the customer, sending them a notification, hey, your order's been lost and transferred, and uh you're gonna get it tomorrow, it's on a different traffic number, yeah, it is. Sorry about that, but we picked it up before you did. And then it goes through the process of sorting that out with OzPost. So fully automated uh where the agent is taking on updating systems, communicating, and facilitating uh resolution.

SPEAKER_01:

So when you hit that amber or red status, is it effectively doing two jobs depending on the scenario? It's one getting ahead of it with customers to give them communication on where you're at to kind of prevent that them adding another ticket through email or chat or phone. It's like they're kept in the loop. But is it also then triggering something in the ORPS to find a solution as well?

SPEAKER_02:

Correct. So an out of stock might have seven ways to be resolved, and it then determines the best course for action and then runs that resolution through all the way to the end. Sometimes things are resolved without the customer knowing. Sometimes the customer is involved, sometimes teams are in the loop, sometimes they're not in the loop. So it really depends on the problem that the agent has to solve.

SPEAKER_01:

And are these all predetermined problems or scenarios with a retailer? And are they unique for each retailer?

SPEAKER_02:

They're all predetermined, and we do work with the retailers to ensure that their ops is uh well taken care of. So we've built an infrastructure that is plug and play that we can easily onboard customers within five days. And that's taken a long time to get that because every retailer is unique. But there really is just a bunch of toolkits, if you want to call it, and you just drag and drop and you connect it all together, and then we do final sort of like customizations based on specific uniqueness per each retailer.

SPEAKER_01:

I wouldn't say it's a radical idea, but it's a different approach to proactive customer service that I haven't seen before, especially here in Australia. Yeah. Where did you come up with the idea? Where were the origins of Kew?

SPEAKER_02:

There's probably two parts to that. My co-founders and I met back in uh 2020 uh at PE Nation, and uh I was the CEO there, and Tracy was heading up customer service, and Tahir was heading up technology. And um, you know, Tracy had spent decades in customer service and e-commerce ops, and she had sort of worked out just because of painful situations, that if she could fix the issue manually before it snowballed, well then it just wouldn't become a complaint. And it wasn't until I moved on from that business and went into another one where there was a lot more pain, uh, and Tracy came along, and Tahir came along and I said, look, guys, we've got to fix this, let's build some kind of system. And and Tahir was like, well, why build a system for a company when we can build a solution for every e-commerce retailer in the world? Because Tracy had had a unique insight that if you manually sift through all these systems and find the she was manually sifting through all these systems, finding that that failure and then manually fixing it, which just took forever, right? And she would look obscene hours and and then we were like, well, hang on a sec, surely if we can find this issue using technology and then automate the resolution, it's saving teams an incredible amount of manual effort. But at the same time, putting businesses on the front foot because their customers will always get what they want on time as promised. And we all know the best customer service is if the customer never needs to talk to you, never needs to call, never needs to complain, it just works. And that's what we're building.

SPEAKER_00:

And this might be a silly question. Is it hard to build?

SPEAKER_01:

Because um I could imagine that as an orchestration layer in the middle of it all you and because you're working with clients like DeCuba, EHP Labs, Budgie Smuggler, everyone will have different systems from front end through to ERPs, through to warehouse management systems, through to shipping carriers, different data, different APIs. It sounds like an absolute nightmare of a problem to solve for me. How do you productize that?

SPEAKER_02:

You know, I think we're probably a bit naive when all in on this. And there were a few really smart people in e-commerce that, you know, have sold their business for hundreds of millions and they're like, this can't work. You know, it's just impossible. Everybody's business is different, and we're like, yeah, it is. But uh Tahir's a real genius. In fact, one of our customers said he's a wizard. And he came up with a way, a way, I don't know, I'm not the technical co-founder, but he came up with a way to be able to build this that you're tumbling all this data in a way that it washes up in a uniform sort of format. And um, yeah, we've got we've got eight engineers right now. Four of them are onshore, four of them are offshore. A lot of building, really aggressive timelines to deliver on a very powerful roadmap. But it took time and and we built in the open. We onboarded our first customer 18 months ago, two of them, and then went to three. And then we kind of hit pause for six months while we built with them and we're learning. We we certainly didn't build a perfect product and then launch. We built in real time, in in users' hands, every single week, making iterations. I remember when we brought in our third customer, the platform couldn't cope with the volume and it just froze. And Tahir had to go into like a radical rebuild and rebuilt the platform ground up. But there's certainly a lot of magic is done because as you pointed out, one, we've got to uh we've built 50 plus integrations now and we're heading towards 100 by the middle of next year. And each one of those have been systemized in a way that we can bring on these brands super fast and be able to connect all the points of data that we need to drive. And we've been able to find that data in a lot of unique ways, either through APIs, webhooks, even browser operator using agents, FTPs, just a bunch of different ways.

SPEAKER_01:

Awesome. So what's the process? So when you're speaking to a new retailer for the first time, I'm keen to understand what discovery looks like in terms of you needing to understand the tech, what integrations you already have, what you need to deliver. But then also from a customer perspective, what problems are you going to start with?

SPEAKER_02:

Yeah, so we're definitely not a product-led sales business. We are a sales-led business. And so there is a bunch of work that's that's done up front in the sales process, a discovery call, a customized demo, then a mutual action plan, and then a scoping call. But for the retailer, it's actually fairly painless. And uh we've built that in a way that it is about three to four hours of their time up front. And what we're looking for from them is three lots of uh three lots of information, yes. What are your your API keys? How do we connect to all your systems? So we define what is your tech stack. Uh so what storefront are you on? What ERP, what inventory management, what warehouse management systems, what are your carrier integrations, who are your carriers? Do you have marketplaces? Do you have ship from store, click and collect, multi-GO warehousing? Do you have a return solution? What's your help desk? So we gather all of the access details and credentials from that, and that takes about one to two hours, depending on the retailer and their responsiveness. And then about another hour where we gather the customer promise, and that can vary between multi-GO, so you know, your or East Coast, West Coast, or Express or per product, or we gather that information and then we work with them around their workflows and determine what are the workflows that they want implemented. That's three to four hours of heavy lifting for them. We go off, we do about five days worth of work. If their tech stack matches the pre-built integrations that we have, if their tech stack doesn't match, it's about 10 or 15 days worth of work. And then we do an onboarding session with them and they they often run in on day one.

SPEAKER_01:

Who's the ideal retailer? Like who do you think this fits? Because obviously there are some retailers, especially in e-commerce, that are set up with a very typical tech stack, Shopify into Clavier, into a gorgeous, out to a ship it, maybe. You know what I mean? Like pretty straightforward system. And then there's some that are very, very complicated. Where do you sit in the world?

SPEAKER_02:

Yes, that's a really good question. I mean, I've I've probably done 50 odd discovery calls over the last three months. And out of those, probably five or ten were just not the right fit. And that was because their business didn't have the volume or the complexity of storefronts or the amount of integrations. And there is sort of a tipping point, but not just the complexity of their business model. It's also the mindset they have. Uh, we've got some retailers that were, you know, they were at the start of program and they didn't have a really complex business. But they said, hey, I'm growing fast and I don't want to have to scale with people. I'd rather scale with automation, is one thing. I don't want to have to be putting out fires and deal with things reactively. So I'd like to have a system that is able to prevent complaints, keep my customers happy, keep them locked in. So there is a bit of a mindset, but we certainly, as you go up to the level of complexity, say the Cuba has, which is multi-geo, multi-fulfillment locations, pick and pack, ship from store, click and collect, same-day delivery, uh, marketplaces. We really do an incredible job pulling that all together and just giving them this single, single clear view of what's going on. But we got everything from retailers doing a couple hundred orders a week to doing tens of thousands of orders a week.

SPEAKER_01:

You were telling me about Clutch the other day. Tell me how they're using, because I think that's such an amazing story.

SPEAKER_02:

Yeah, Clutch is a great brand. I really enjoy working. Well, we all enjoy, our whole team enjoys working with Clutch because they're really pushing this sort of innovation space. And and uh we caught up with them the other day and and we were like, hey, what would it be like if you didn't have TU today? And I I couldn't imagine because I'd just be putting out fires, I'd have to hire three, four more people to be able to manage all this complexity. That's been a good journey because what we came to understand is that they also have a big B2B business. And whilst we entered in on e-commerce, they're like, hey, I got all this B2B pain, and it's the same thing, right? Like when you take an e-commerce, it's got a customer service level to it, customer expectation, but it's the same with a B2B customer. And so now what we've learned from them is the opportunity to build out a B2B offering, which will be launching in February.

SPEAKER_01:

Right. Okay, that's gonna be huge. And how do you measure the impact of proactive customer service when you don't see it? Yeah.

SPEAKER_02:

That is a good question because you know, teams are s have got so good at measuring first response time, resolution time, CSAT, and all of that. And we sort of come in with a new uh metric, which is complaint prevention, right? And um, complaint prevention is how many issues, ops issues did we detect? How many of those ops issues were we able to prevent in real time? How were they resolved positively with the customer? And so, you know, that sort of impact around um how many times do we detect and fix something before the customer noticed, how many inbound tickets were never needed to be logged, how many hours of repetitive work didn't land on the ops team, what's the improvement in on-time fulfillment? We also track other sort of operational metrics like what was the was mode ticket volume, how much manual task reduction was there, time to resolution, cost to serve. And then I think also the most important thing is that retention and customer lifetime value improvement. You know, because if customers get what they want on time, as promised, always, no drama, they keep coming back, right? Like last year, uh according to our post, like one in five shoppers did not get what they want on time. And they they had a they had a raise that you get that was 123 million hours wasted on a customer service course last year. That's a lot of pain, right? And so in some ways, key is like an immune system. You don't think about it when it's working, but it's constantly defending the experience. And for brands, that silent protection is often what drives the biggest impact.

SPEAKER_01:

Do you find that customers with that proactive service turn them into real advocates? It's almost like, and I'm not selling this for you. I just think it's a really interesting concept around it's unique to get a proactive piece of communication from a brand to say, hey, we're putting our hands up, this is gonna be late, or this is lost, or we don't know what's going on here. We're aware of it, we'll get back to you, we're onto it. Does that come back in terms of public reviews or sentiment at all?

SPEAKER_02:

Yeah, well, I think of it, you know, who really nails it well is um Amazon nailed it. Well, like they really nailed it well that an order might be out for delivery, it's not gonna reach you, you get a notification. Hey, sorry, we've let you down, but you're getting it tomorrow. And I think people started shopping online because everyone, it was like, I don't want to go to the mall, don't want to deal with traffic, don't want to deal with cues, there was all that pain, right? Went online, but the anxiety when you hit bar, you don't know if you if it's gonna come on time. Like there's no guarantee, right? If brands can consistently deliver on time and keep customers happy, either because they get what they want on time or because you communicate really well with them, I think it's polite. Like it's like, hey, we've let you down, but we know about it, and this is how we're resolving it, and this is the outcome. They just keep coming back, you know. And out of those one in five that complained, 75% of the one churned every year. And that's a consistent thing, right?

SPEAKER_01:

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SPEAKER_02:

Yeah, so there's probably three lots of people that engage with our product. We've got customer service people that are using it to resolve issues or deal uh to prevent this thing and keeping it in the loop with the agents. And then you've got the e-commerce team, but it moves up to the C-suite where the C suite are actually able to see, well, this is what the health of my e-commerce ops looks like. Oh, that's where a pay point is. Okay, what resources am I going to put on it? And that's the other product that we're busy building out right now, which is the insights, where it's going to be both quantum qualitative, where different people can engage with KiU and get full reporting on the performance or the health of their e-commerce operations, be it for a Monday trade meeting, or be it for a weekly rap, or be it for a monthly board pack or whatever it is, different levels of people in the business will be able to get uh information out of Kiyu that helps them understand where the pain points are and then actually go fix those operational issues. We don't want to come beyond is not about firefighting all the time. It's actually about helping our retailers understand the health of their business and then be able to make effective ops changes to avoid that pain.

SPEAKER_01:

What are some of the most surprising findings or breakages that you found in the retail businesses that you work with? I could imagine that you've uncovered some pain points that retailers weren't even aware of.

SPEAKER_02:

Yeah. You know, I I I I'll give you a real example. One of our customers had a consumer place and order for about$500 for an express delivery. It was really early on when we were like testing this out. And, you know, the warehouse didn't pick up. It didn't pick it on the same day. And normally that would have just got caught until the customer chased up or worse, left a negative review. But key was able to spot that, that delay early. As I pointed out, it hit amber. And then our agent flagged that the pick and pack SLA had passed and auto-notified the fulfillment team, who then escalated it, got it out the door. And the customer received their order on time. And I remember getting that call from that customer, and they were, it saved the situation. And the consumer never knew there was a problem. And that's the shift that we're seeing instead of CX teams digging through these point solutions or reacting to complaints. He's detecting those issues midstream and fixes it before it becomes a drama. And we see this across other flows too, like failed payments that get retried automatically or stuck returns that get nudged through the system. All things ops teams would usually catch too late or not at all.

SPEAKER_01:

And those communications that are sent to a customer, are they sent via Q or are they sent via the help desk software?

SPEAKER_02:

Via the help desk. So every single, we're not yet to replace help desk, even though we say help desk manage complaints, Q prevents, then we're not we're not going after help desks. In fact, they're an important part of the integration. And why? Because they've got customer data, right? And they've got an easy way to communicate. And so when we identify an ops issue, it creates a ticket in the help desk if there is a reach out to the customer. If it's resolved by us, it doesn't. But as soon as we interact with the customer, it's through the help desk system. And the cons are crafted based on a brand, on the brand's guidelines, but also on the customer history.

SPEAKER_01:

So the customer service team can still see all that communication history to that point. So even if there is a problem after that, they can see that the customer has been updated along the journey.

SPEAKER_02:

Yeah, these agents are not fully autonomous. They're being built uh user in the loop. Uh, we certainly like very aware that we had to augment teams so that they're doing less manual repetitive tasks and they sort of are focused on high value interactions with the customer that are driving revenue, not firefighting. And we built Q in a way that you can see every single issue detected in real time and then it being tracked and a full sort of history of what system did it go to, where did it gather info, how did it write that email. And if needed, the user is in the loop fully and can follow that whole thing through the whole chain and be across that detail. And if necessary, it loops in, it loops in the user and says, Hey, I'm stuck, I need your help, got to resolve this.

SPEAKER_01:

I can imagine you've got a thousand ideas around how this can get smarter and more automated in time, especially with new AI capabilities going on. If I was to ask you how Q works in five years' time, what do you think your vision of it then is?

SPEAKER_02:

You know, if we could wave a magic wand and sort of plug in one new data source, I'd say it would be real-time customer intent signals. So right now we track everything operational. So, like when an order is packed, packed, shipped, returned, refunded. But what we don't have visibility or don't have any idea about is what does the customer expect or how are they feeling in the moment. Like imagine if we could combine that operational data with intent signals like this is my birthday gift, must arrive by Friday, or I've contacted support before, I expect faster resolution, or this is my third order this month, I'm a high value repeat customer. That context will allow our agents not to just fix issues, but prioritize based on customer impact because not every late delivery causes the same damage. A delay on a bulk protein reorder might be fine, depending on like how much of a gym bro you are. But like it might be fine if it comes a day late, right?

SPEAKER_00:

Yeah.

SPEAKER_02:

But a delay on a bridesmaid dress for a weekend wedding, you know, that's kind of a disaster. So if we could plug in real time intent and urgency. And customer context, KiU could become even more precise, personal, and preventative. But at the same time, I think there's a real opportunity. We're solving a problem of siloed systems. These point solutions that are good at returns or good at carrier integration or good at inventory management. And they've been built out over time. Like as e-comm's evolved, uh, new categories have been created. Uh order editing wasn't around two years ago. Um before that, easy returns wasn't around or instant refunds or you know, buy now, pay later. These are all new categories that have just made e-comm better and better, but they've added complexity to the order journey. Now we're solving for that complexity. I guess the question is, can an orchestration layer become an end-to-end solution from after the buy button, so after Shopify, to when the customer gets a return? Is that the real opportunity just to provide one end-to-end point solution?

SPEAKER_01:

We actually spoke about this a couple of weeks ago with Sylvan from Gander and Andrew from Convert Digital around the complexity that is coming through at checkout and post-checkout. Like you said, being able to edit your orders, add more items after checkout. It's like checkout isn't the end of the journey anymore. Do you find that it's adding a lot of complexity for teams in the background?

SPEAKER_02:

Yeah, it's certainly a cause to what's it's making the shopping experience better, but it's just one more point solution to have to like manage the order journey and one more point of contact. You know, with order editing, it's super awesome in that it gives the customer a bit of flexibility and it saves some time, but it also creates some downstream pressure too, you know, on the warehouse. Because their fulfillment times get tighter. It's certainly the more siloed systems there are, the more potential points of failure there are. And that's where we come into play, where we're able to detect those system sync issues or waters aren't moving through as they should.

SPEAKER_01:

I love that idea that you said around being able to understand customer intent. And I see that mirroring up nicely with customer service. So, you know, having whatever the future is in five years' time, having a customer agent or your own customer help guiding you through the purchase journey, understanding exactly what you want to buy, what you're using it for, what your budget is to give you something that's really special for you and your purpose. And then almost having that agent that helped you shop drop off and then be your helper within the business after you've placed that order to track it for you and to give you updates if anything's going wrong. It's pretty special to combine that pre- and post-help in one agent.

SPEAKER_02:

Yeah, we're certainly building KiU in a way that other agents can engage with our platform and be able to facilitate outcomes working with us. We we've really clear on this. Like there is a bunch of legacy ERP systems out there that are closed and they're like, we don't want you in. There's even warehouses like we don't want to let you in, and they've got these closed business models. And that's going to be really challenging for them in the future if they're not opening themselves or any solution isn't opening itself up to this onslaught of agents where you know our solutions, we also see the opportunity for our solution to become the point contact for all agents and actually channel an agent work in because we're the only solution that's going to tap into every point solution to be able to solve this problem, right? Like the existing solutions that are triaging customer complaints with AR, they're really they're fixing a complaint and they don't have access to the depth of data that's required to be able to fill this, you know, in a proactive way versus reactive. So we're feeling really positive about being able to ensure our platform is able to communicate with other agents to solve those, whether they're shoppers or or not.

SPEAKER_01:

It's a fascinating space. And we had David Brudnell on a couple of months ago from Decider, and he was talking about agents and his vision for agents is that we have agents in our business where instead of telling them a task to do in terms of go find all the missing orders and update customers, it's we give each agent a mission or a goal. So if you're a customer service agent, your mission is to increase customer spend by 20%. Um say, yes, solve the problem, but then we want to upsell them or we want to introduce them to other things and be a sales agent, not just a customer service agent. Or it could be that you're a marketing agent and your goal isn't necessarily to write meta ads, but your goal is to find X new customers every month. However, you choose to do that. It's gonna be pretty interesting when we take that agent approach, especially those integrated agents that you talk about, from being task-oriented to outcome-driven, whether that's an outcome for the customer or an outcome for the business.

SPEAKER_02:

Yeah, there's that's gonna be a bit of time, right? Because that's gonna require thinking. And um, I don't think the tech's there because right now it's solving mathematical problems. It can't in truly maybe. I mean, I'm not really like I've got my bubble and I've got my lane, and I'm just so focused.

SPEAKER_01:

I've got a lot of little bubbles, but no deep bubbles.

SPEAKER_02:

Yeah, yeah. And we're just like we're deep in this thing, right? And I remember when we had to go hire engineers to build this, we couldn't find anyone that's done anything that to solve this problem. And and my guys are like in the fly figuring this out and going, oh, we can do it this way or do it that way, or do it that way. So I think the specialists will be able to solve the general the you know across the board. But we certainly focused on what we're doing and have a good understanding of how to solve this problem.

SPEAKER_01:

And I guess you're in a really good position too, as an orchestration layer that integrates with all the platforms, in that you're not embedded with any individual platform or solution because they're all changing so much at the moment. And so you just remain that orchestration layer that can adapt to whatever is happening and whatever's moving out in the market.

SPEAKER_02:

Yeah, exactly. And we see ourselves as Switzerland, so to speak. You know, we're not like we're uh providing a service to any retailer that has any combination of systems. In fact, today I had a reach out from someone that's on uh Magento and we haven't built an integration for Magento. So I pick up the phone, hey Tahir, how long is it gonna take us? He looks click through, he goes, 10 days. You know, okay. Yeah, and so we certainly feel like that that is our USP because that does does drive a mode for our business where it took a lot of time. Each integration is five to ten days. So we we've got a head start in what we're building with 50 plus integrations, and that took a lot of time with a bunch of engineers in Pakistan for a while to do that heavy lifting than Ishulli.

SPEAKER_01:

We've all been there, right? Slipping on a great-looking pair of shoes, only to regret it, a couple of hours later. Who knew that blisters could get blisters? Well, the founders of Frankie Ford did, and that's why they've created a line of stylish, podiatrist designed footwear that don't just look good, they actually feel good too. But what began as an online success story quickly stepped into the real world with retail stores opening across the country. And when they moved to the Shopify Plus plan and rolled out Shopify Pods in store, Frankie4 really hit their stride. Now everything works together. From online browsing to install buying, it's one smooth, unified commerce experience for both customers and the Frankie4 team. And with the Shopify App Store, they're able to test new features quickly to see what works. It's paying off too, with 170% increase in site visits, a 25% drop in return rates, and more happy feet than ever. Streamlined, stable, seriously stylish. That's Frankie4 on Shopify. To read more success stories like this, search Shopify Case Studies online. Speaking of moats, you've obviously caught the eye of investors and raised some great initial money there. You're not the typical SaaS model that they might back because it's still uh solution-oriented depending on what retailer is and customizing it for their needs. How did you go about raising money, that initial money with investors?

SPEAKER_02:

Yeah, I think the first start was we got good support from Startmate and they back ambitious founders that have when we got when we got into Startmate at the beginning of last year, we had no product, no customers. We just had a problem, and that problem was clearly messy. So and it was simple to understand. Hey, I buy something online, it's not guaranteed arrival on time, I have to complain, and that's painful. And uh they backed us, I think, also because we're an experienced founding team, uh, lots of experience. They're like, if they believe there's this problem. So we got some traction with them, and then we got traction with awesome early investors like Paul Greenberg, who's got a real good name, and he and he could clearly see it too. And so that sort of first round of funding was a bunch of angel investors that were backing a founding team. We had a vision, we didn't have a product, we didn't have customers, but they're backing a founding team to solve a problem that they knew we were close to. And uh, we've recently done a round uh with institutional investors, some great VCs came on board. And, you know, the the sort of short answer it was a little trickier because you throw in the word e-commerce and they're like, we don't fund e-commerce businesses. Um no, no, we're solving a customer service problem. And so we had to really work hard to get our narrative right. And most investors, I would say, uh out the gate, they could understand where is my order, they they could get that and and and they get the symptom. But what they didn't always see straight away is the operational complexity behind it. And what helped was showing how reactive most CX and ops teams still are, even at scale. And we had a sort of demonstrate, I remember us doing this video, going, Well, this retailer's got eight brands and four geographies, they say 1624, 32 storefronts, 32 tabs on their browser, they're open and they're clicking between all of them constantly all day. So, hey, we're pulling all that data, they're not having to do it manually, they're not having to react to issues. And when we showed a few of them a live demo, when they started speaking to customers, one of them rang up a customer and got really deep into the problem. They're like, oh, this is a real painful problem. Not only is it a painful problem, but it's complex to solve and it's complex to build for. And that's when the investors that back to us this round, they could really see the moat we were building around the messiness of the complexity. Because when we were raising, there was a lot or a lot of AI agents coming out, but they were solving horizontal problems, just simple systems to plug into, not a vertical problem that's got vertical data and complexity around resolution. So we really um got good support this time around. And for us now, it's about getting more customers, getting it out into users' hands, and building that customer base and proving that this is a new way of running e-commerce operations, new way of running post-purchase.

SPEAKER_01:

Why didn't the VCs like that you're an e-commerce? What's the stink on e-commerce with VC at the moment?

SPEAKER_02:

Just remember, I don't understand e-commerce. Okay, great. Well, the ones that backed us, funny enough, had come from an e-commerce background. One of them had actually built a pet supply business and sold it and then went into VC. And the other was super curious and got us speaking to DeCuba, who became a customer and got us speaking to Axen Group, and then said, Hey, we want to speak to your customers. And when they got talking, they were like, Oh, this is not an e-commerce solution. This is a customer service solution. This is solving a real pain.

SPEAKER_01:

So obviously you've started with retailers, but do you see KiU expanding out into other industries then?

SPEAKER_02:

Absolutely. Like I said earlier, we we certainly are going to expand into B2B and retail operations, and we're launching that platform uh next February. We've had some companies reach out to us that are in the logistics space saying, hey, could you work with us? But we we feel the e-com, B2B retail, that sort of omnichannel offering is where we want to uh play out initially and build build that out. You know, so so our view is really we would rather focus on owning everything off to the buyer button at some point in the future across B2C and and B2B. And that uh underlying problem isn't retail specific. It really is about like fragmented systems, reactive workflows, a lack of automation across order life cycles. And that's what Kia was really built to solve at the end of the day. Brilliant. We're starting we're starting with retail because because the pain is the loudest, right? Um but the long-term play is much bigger, which is proactive ops across any transactional business. There's there's no reason why we can't expand across into other verticals here.

SPEAKER_01:

And question I should have asked earlier for what's the commercial model here? So if you know there's a bit of work up front to be done, a bit of investigation, maybe some custom stuff. How do you actually price this?

SPEAKER_02:

Yeah, so we don't actually price, uh we've got no integration fee, no custom fee. It's just pure monthly subscription. And we charge a flat monthly platform fee based on uh order volume and AI agent usage. So each plan includes a set number of orders up to 5,000, up to 15,000, 30,000, 60,000 a month, for example, and a block of AI agent resolutions, be it 250, 500, 750, whatever it is. Unlimited users, rebuilt integrations, depending on the tier. And we've really kept it simple to start with. There's four plans, starter grow plus and pro. And so, for example, a brand doing up to 15,000 orders a month would typically go on to our Grow Plan, which is$1,550 a month. And that includes, I think it's like 750 AI agent resolutions in that price. But if they need more agent capacity, say during peak trade, they can top up uh with extra blocks. So they're only having to pay for what they're actually using. But I think the key pieces really in terms of ROI and how we help teams track is in our platform, you can see how many issues keys resolved automatically, the time it's saved versus manual workflows, uh, the drop in support tickets, the drop in inbound support tickets, an increase in on-time fulfillment, and also we track customer lifetime value in real time. We display in the platform you've got X amount of customer lifetime value at risk if you don't fix this issue. So they can see how many issues they've got as a percentage of total orders, the amount of customer lifetime value at risk. And if they fix that issue, how much customer lifetime value they've protected. And so on the platform in real time, you can see all those metrics.

SPEAKER_01:

Brilliant. I've got to ask you, and I'm sure it's a loaded question, for the next 12 months, where's your focus? Because I saw that you just released V3 of KiU. Uh I can imagine you've got a roadmap of developments that you're going to keep the team busy on. Where are your priority areas over the next 12 months?

SPEAKER_02:

So, yeah, we launched V3 of the platform about a week ago, and the day it got launched, we put up a countdown clock of 99 days in the office. And each day that clock comes down to our next launch, uh, which is in February, and the team are like very they come in to work and they're like, there's a cocktail. We've got X amount of this damn clock. They quite like it. It's really energizing, um, uh, really energizing for them. But right now we've got the the core e-com platform and we've got the AR workflows, and so our next 12 months is to increase the amount of workflows and get them across every single customer. We've got about 25 brands on the platform now so to get them uh out to all the customers, and then the next phase uh which is February, we've got three products launching in February, and that is the insights and the AI assistant. So it's ask Q, and that's natural language requests instead of workflows. So you'll be able to solve problems by asking questions and then the B2B part of it. Once we've got that launched in February, we're then gonna really work out on how we can automate the onboarding cycle for customers, how we can get them on using agents so that it's low touch, frictionless, and how do we get this platform to become more useful across the business for every single department? So our sort of focus for the first half of next year is to grow our customer base in Australia, launch new products, but at the same time start focusing on building out some custom traction in the US.

SPEAKER_01:

Awesome. I've got to ask you, what's better? Being a uh tech entrepreneur or a uh retailer leader? I I'm gonna say neither. A surfer.

SPEAKER_02:

A surfer is the best out of the lot. I think neither, to be honest here, it's probably not a good answer. Like I do miss trading, right? Retail's real dirty. You you're like in the weeds, you you're chasing down. It's like every day is every transaction, it's every this, it's every that. There is a lot in that, but I'm really enjoying building a tech company because it's a sort of longer-term play, right? When you're building a retail business, you can generate revenue from day one. Like, you know, we're not generating uh revenue to cover our overheads, that's why we got investment. But it's super fun building something that we know is changing the lives of people. We were uh we were at a customer the other day, and it's like, hey, if you didn't have KyU, what would you do? And she was like, I wouldn't come to work anymore. And then the other one said, Oh, I wouldn't go work for another company if they didn't have Kiyu, and and it's changed my life. And that's really rewarding when you see the positive impact it has on employee engagement. It's not just like customers are happy, brands are happy, but employees are happy too because they don't come to work firefighting anymore.

SPEAKER_00:

Yeah.

SPEAKER_02:

They've got all the tools to do their job awesome, and they're having really good conversations with customers, not negative conversation.

SPEAKER_01:

I love it. There was something that you wrote on LinkedIn last week that caught my eye, and I wrote it down here, and it was linked to what you said there, AI won't replace people, but it will replace problems. And I think that's a really nice way of thinking about what you're doing here. Not that it's all AI, there's a lot more to it than AI, but not replacing people, but replacing problems. Because, like you said, no one goes to work to firefight, and customers don't purchase to follow up. We're doing things that neither party wants to do.

SPEAKER_02:

Exactly. I mean, we're taking away the most painful part about e-commerce, the frustration uh the anxiety around not getting something on time, right? No one wants that. Like we're not trying to re-educate people to shop, we're taking away something that they never wanted in the first place. So so tick. Uh and we we thought long and hard about this, like really hard. What are we building here? How's it going to have a positive impact? And that positive impact is that these teams are gonna be augmented, they're gonna have something sitting alongside of them that's doing all that manual repetitive stuff they don't enjoy doing, checking systems, writing emails, waiting for answers, taking it on the chin from a customer, updating systems. They leave work trained and they're not gonna feel that way. You know, when they've got uh key supporting them, they're doing less manual repetitive things and they're just having these high value, positive conversations that are driving revenue, and that creates more jobs. It doesn't take away jobs. We're not there to replace teams, we're there just to augment them so they can be better at what they do.

SPEAKER_01:

Well, you keep this up, you might be Saint Jevon, the patron saint of customer service teams worldwide.

SPEAKER_02:

Oh yeah, my co-founder Tracy, well, she's the spots I'm I'm just the one Iceland.

SPEAKER_01:

Yeah I love it. So if people want to get in touch with yourself, Jevon, or the Kiyu team, what's the best way to go about that?

SPEAKER_02:

Yeah, the best way is to head to kiu.com, which is KWEYU, kiu.com. And we've got a link there that you can book a custom demo with us. We will then run a discovery call and like understand the business. And you can also connect with me on LinkedIn. I think my name should be somewhere over here. Like, click down the bottom there.

SPEAKER_01:

Uh we're not that smart. We can't do picture-in-picture links, but we'll put in the show notes.

SPEAKER_02:

Yeah, connect with me on LinkedIn. Not hard to find my uh search me on LinkedIn, just type my first name.

SPEAKER_01:

Love it. Chevron, thank you so much for joining us today. I've got a feeling we are just at the start of this journey. We're gonna have this chat again in a few years' time, and we're gonna be in a totally different spot with a whole new technology solving, maybe already solve the problem. But it's gonna look a lot different. But I love the trajectory you're on and your mission in the world, especially for those customer service teams who are um battling this every day. So thank you for sharing that with us today on Ad to Cart.

SPEAKER_02:

Yeah, awesome. Thanks for having me on Ad to Cart, Nathan. It's a real, real pleasure.

SPEAKER_01:

Now, if you're anything like me, I'm sure that sparked some big ideas on what the future of customer service and e-commerce operations could look like in the future. I love the idea of talking about how brands can stop firefighting and start forecasting and start fixing problems before they become major, before they even touch a customer and before they even impact our brand. That to me seems like a nirvana that Jevon and the team are really close to executing for a lot of brands. And I'm hoping that in the next few years we'll see a real evolution in thinking rather than clearing tickets to preventing tickets. Here are three ideas that I took from this episode. Number one, the idea of preventative customer service. How could I not go past this? But customer service. No one in retail goes into retail to run a customer service team. And no customer buys a product so they can contact you afterwards with a question or a problem. No one wants it, so why are we not trying to make it extinct? I love that Jevon's point that the best customer service is when the customer never has to contact you. But I think it can go a step further. Because the bar is so low on customer service at the moment, that even when there is an impending bad experience coming up, such as a late parcel or a wrong item or a damaged good, that you can get ahead of the game and tell the customer that you recognize there's a problem and that you're in the process of fixing it. That to me not only reduces workload, but has the opportunity to put your brand above others in the mind of a consumer where they're not having to do the work for you anymore. And they're surprised by that proactive approach that isn't common in e-commerce. There's a real opportunity there. Secondly, proactive operational issue resolution. This is the part of the Q system that I never fully understood before our conversation today, even though we'd had a few conversations about it. I never understood that it was also a diagnosis that it could diagnose internal problems through that traffic light system of green, amber, and red. Being able to understand how big problems are, where the blockages are, and the potential impact of those blockages, that's huge for a team to understand before it gets out of hand. If you can add them to your dashboard and your reporting dashboard, that's gonna save you a lot more money than those incremental improvements could and have a bigger impact on your customer experience than anything else. If you can have that simple framework, green mean running smoothly, amber showing friction, and red signaling something that needs fixing now, I can't think of any other report that I'd want to see first. And third, sometimes it's not just a Shopify app problem. We've had amazing solutions come through at Descartes over the last couple of years where it is as simple as downloading a Shopify app for your store to add a new functionality or a new offering for your customers. And those point solutions are fantastic. But as you heard from Jevon, they've got over 50 integrations now. And they act as an orchestration layer between all the technology for a retailer. This means that often they will have to do some customization and the implementation process isn't a couple of minutes, but might be a couple of weeks or a couple of months to get it right, to make sure it's solving the right problems. But that upfront effort is worth it to be able to be customized for your business and to prevent all those issues where you would be spending time and money down the track. Sometimes, as much as we would love it, it's not as easy as just an install this app to solve your problem. Sometimes the most value comes from going deep and creating a solution that is just for your business to solve those problems. As Jevin put it, the complexity is where the opportunity hides. Now, if this got you thinking differently around how your ops and your CX teams work together and get ahead of issues, make sure to hit subscribe wherever you listen, whether that be Spotify, Apple, YouTube, hit that subscribe button and we're going to bring you plenty more of great e-commerce ideas and innovations for you for the rest of the year and into next year. And as always, if you are an e-commerce professional, whether you are an independent consultant, a retailer, technology provider, come on over to the AdDicart community. We've got over 500 e-commerce professionals in there who are helping solve each other's problems every day. We'd love you to be a part of it. Head into adducart.com.au to apply to join, and we'll see you in there. As always, a big thank you to our partners Shopify and Clavio for supporting Ad ToCart and helping our community keeping these conversations rolling. We'll catch you next time on AdDicard.