Your Shopify Support Data Is Worth Millions

23:23Our goal is not to rebuild something that exists for many years unless we can do it better. The only caveat here is sometimes these tools, you know, I don't want to call them legacy tools, but let's call them pre-AI tools. some of these pre-AI tools they may have actual physical architectural limits that does not allow an agentic or an AI first tool like CNA to run its course and you know do these let's say the one-to-one personalization so as long as we can accomplish the delivery through a third party we're going to do that like we would much rather connect hook up to your existing stack and do that when we hit a limit we're going to be like finding ways to build this natively just gotcha that makes sense what's something I mean you talked about like this idea that the support inbox is basically a focus group for learning about your product your brand what's maybe the most surprising business decision you've seen a brand make because of some cx interactions there's there's quite a few of them and because we work so closely customers we get to hear about them one of one of those decisions that I always get back to it's quite fun it's a cpg brand that got on got onto even before C &I Intelligence, we built our early concepts and early prototypes.

24:39So they've been an early adopter from the beginning of all the various iterations of our product. At some point, they made this decision to build, so they sell CPG products and the products are not super expensive, but they're not cheap either. What they saw through C &I by looking at the support conversation data is that customers were either abandoning their carts, churning or requesting, actually like making requests for smaller samples of their product. They were just selling regular, you know, regular size products that it wasn't like it's prohibitive, but also people just want to try it.

25:14Especially if it's a CPG product, you just want to try it. You just want to sample it. You maybe don't want to pay full price. And that little nugget right there led to them a full, basically they made this product decision to build for each one of their products, a small, like think about a sample size version of their products. and they generated, this was happening a few months ago, back in 2025, and they generated millions of those samples, that's sample products, not including the people that upgraded from sample to the full product. And this is all because they saw in the data that, hey, people are outright asking us, hey, can I try it in a sample?

25:49And what's amazing about Sienna, it actually is able to even quantify to some extent. Okay, so there's 500 people asked this in the last 90 days. What if their LTV is this much or this time? Okay, this is the investment. So yeah, that's a real example that happened by looking inward at what customers are saying. So what does that look like? Is there a dashboard of insights or do you ask Sienna for details? Do you ask it questions or does it find some of this stuff on its own and surface it? Or what's that experience look like for a merchant? So we have a few options to interact with your data.

26:26one of them is your traditional dashboard so we do have things like trend on the explorer so you can see different trends for example you're able to take a look at top we do on the back end automatic topic and subtopic clustering so in you know in the old world you'd have human agents label a ticket you know this is a cancellation request and the reason is this you know you'd have to spend time and mental energy doing that plus it's not accurate most of the time so we're doing all that But that data is available for anyone to see in a very simple dashboard. So you can see the different trends.

26:58You can actually see resolution rates. You can see what are the topics that are being automated the most, what are the topics that are not being automated. So it's a hybrid between your full CX picture plus... So basically like themes, like if there's people have like breakage in a product, bad shipping or questions about order timing or whatever, you can see where the majority of the tickets are and then potentially dig into that and more. Exactly, yeah. Is there a specific theme? Sorry, go ahead. Yeah, we do it at two levels of fidelity. You do it in a bigger theme, as you said, and then you can actually go for each theme.

27:34We do some topics so we can go even deeper. So let's say you see a spike in refund requests. So refund requests could be a theme or a topic. And then, hey, this week or this month, we're seeing a spike. Then you can click on that, double click, and then see exactly why. What's the reason? because Sienna was smart enough to figure out there's multiple reasons or there's multiple kind of like. Yeah. Is there any things that merchants find using this topic explorer that is always shocking? Like you might think, I don't know, sometimes we have blind spots as merchants and we overlook things or we get blindness to the same questions.

28:10Like we talk about this all the time. Like when you're in the weeds of something, you don't see it through a new set of eyes, right? Is there any like themes that consistently surprise merchants? when they go into them? Yes, there's always this reaction when we look at the themes and you can look at it for seven days, 30 days, you can go more than that. And then they look and see some sort of a spike or they see some sort of... And let's say that we're doing this live, we're looking at the data live with someone who works in CX. It can be from a support agent to a VP of customer experience and they're looking at this dashboard.

28:47And sometimes we see these reactions like, That makes sense. We knew about that, but there was never, the data was never there to support that argument. So it's almost like sometimes in a pre-AI world, what happens is for CX teams, they see some behavior, they see some trends, but they don't have the data to quantify it. So they could be spending weeks or even months trying to prove something out, but no one is really going to take weeks or months to actually track tickets, like tag them and put them in spreadsheets. And so what this gives them, it's probably like in five seconds, look at that.

29:18Like we knew that returns are increasing or we knew that returns requests have been increasing. And now we can see why. So you can go deeper. And in one click, you can go from that dashboard to actually asking Sienna, hey, can you tell me more what's going on here? So that's always an aha moment where you can quantify something that you maybe felt or your team has anecdotally reported to you. Hey, we're seeing more cases of this product being mentioned or something like that. There's no real way to track it. And when you look at it in that dashboard, you're like, okay, now it's real. We can share this report with our operations team or our product development team.

29:51So say I'm a supplements brand, average size, doing 5 to 10 million a year or something. What's a question I should be asking Sienna of my data? For sure, I should be asking. It doesn't have to be a supplements brand, but can you give some advice on what the best? Because often it's asking the right questions is the key, right? Like you can have data is not the problem anymore. So what are some questions that brands should be asking it? There's levels to this. So that's a great question. And there's levels, right? You can start off with pretty generic questions. One that I always like is take a look at my data.

30:28And of course, we have ways to build prompts in a more robust way. But just riffing here, I always like the idea of, hey, look at all my happy customers. So I would always do almost like a workflow based. So look at my happy customers. What do they love more about them? what they love, what do they love most about our products and why. So give me a summary. Then I would go into, hey, what's some constructive feedback? So look into what are they not liking as much? And then eventually I'll say, what are the business, what are some of the biggest business opportunities for us? And you know, you can replace business with what are some of the biggest product opportunities.

31:01So often like we've seen brands use CN Intelligence as a way to do product development thinking, hey, okay, so we see these many customers asking about this. This is interesting. Oh, like Like, we never thought that we could actually just do this. So anything that, you know, think about it, you have access to this, all of a sudden it's a gold mine. It's like an oil. So you can, you know, you can dig for oil and oil comes out of it. The question is, you know, how do you make this oil actually useful? If it just sits there and you look at the oil, it doesn't really do much. So you have to make, you have to transform into energy.

31:30What kind of questions can you ask? What are some of these like high leverage questions that you can ask? I would start with, what are we doing well? What can we improve? what are I also love this question you know often you grind hard you work hard and you kind of forget hey you have an amazing community that is behind you and people love what you're doing and this is I think quite challenging for many folks that are working in customer experience customer experience for the lack of a better word sometimes equals just like people complaining not always but you reach out to support because you have a problem very you know very limited I guess like the pie chart of people reaching out because they love the product is smaller.

32:07But I also love to show what's possible when you ask Tiana to give you reviews. Hey, show me some positive reviews or another use case that I love. And it's really helpful. And you can, by the way, you can, what's something really cool about this process, you can run it automatically. So you can just schedule it and run it once a day, once a week, once a month. So you don't have to manually always like type in what our customers say. You can just develop your prompt and then that can run on your own schedule. So one of them can be, hey, can you create a list of some of the best testimonials or reviews that my marketing team can use?

32:43And can you give me also the angle that my marketing team can use when it comes to that? So the cool thing about it is the system will know a few things. So it will know what products they reference. It will know the actual customer. It will know the review itself because it looks at review. And by the way, when I say review, it can be a social media comment. It can be an email. It doesn't necessarily have to be a review channel. It can come from anywhere. And it also knows the brand itself. So now you basically have given this AI a task to create a campaign based on customer voice or customer data.

33:17And that's also something that I highly recommend anyone. Hey, what are my loyal people? What's my loyal audience saying about our products? And it's really hard to have a bad day once you see that, hey, we have a lot of customers that love our product. Here's who they are. Here's how much they spend. Even better, you can ask Cina to create a personalized outreach campaign that focuses on something like, hey, you're a loyal customer because X, Y, Z, and then you ask Cina to create that. So the whole idea of hyper-personalization, how I call it, and in the past it used to be personalization, but now you can truly have these concierge type of experiences that you create for your most loyal customers because you know who they are, you know what they care about, you know what they said.

33:57and it's all through a simple chat interface. You don't have to go between tools, stitch data together. So it's all in one place. Have you heard of the, probably have of course, the thousand true fan concept? Yeah, like when you start a company and like all you need is to reach. There's that. It's a little bit different. So the, yes, there's the first get your thousand true fans, but there's this concept. I forget the, if you search it on YouTube, it'll come up with the guy that came up with the principle, But what a lot of brands do, this is what comes to my mind when I think of Sienna. Like a lot of brands, they try to solve for everyone.

34:34It's like people have different complaints and they try to solve for, oh, I don't know, say you sell a dog bed or whatever. And some people complain about one thing. Some people complain about another. And you try to solve for anyone. But anyways, his philosophy was that find your true fans. And so you go to the super users, like the people that are leaving five-star reviews, the people that are going to bat for you on social media. If someone says something bad about your brand, they're the ones backing it up. They're the ones posting pictures. They're the ones referring friends to buy. Like you find your best customers and then you interview them.

35:12So Sienna can maybe help with this, but his approach is maybe you only have 17 of these customers. Maybe you have five, maybe you have 50, but everyone has some super fans. then you interview them and you learn everything you can about that customer you learn why they bought it exactly how they're using it because why do they love it so much why have they referred 10 people why are they raving it about on social why have they left five-star reviews what are they how are they using it differently what settings are they using the product in like why are they such big fans understand them and then go out and find more people like them versus trying to fix it for everyone and you end up kind of with this bland product.

35:53And then you get this, it's a little bit more of a narrow focused product, but it solves a very real problem for a certain segment. And then those fans become your growth engine, right? So my mind goes to, maybe there's learnings you could get about, if you could find your true fans, so find all customers that have ordered more than a certain amount of times, have left positive reviews, have done certain actions, tell me everything you can about these customers because I want my marketing to get more of those types you know what's your thoughts on that to me that seems like that would be something I'd love to try would I assume that would be possible yeah I mean you're my my wheels are spinning now because I'm just thinking I'm literally thinking how much of this is already doable with what we could call it the true fan module yeah because that's what you want to build on top of you always I'll put the link in the show notes to that video.

36:46It's about a 10 minute video. I wish I could remember the person's name who came up with the concept right now, but I'll make sure it's in the show notes. But they look at all these businesses and the healthiest businesses are always built on top of their true fans, not trying to fix everyone's problem. And it becomes a mediocre product versus a cat bed for people who have a certain type of cat or whatever. And it's like the best in the world at that or whatever the product is, right? At the top of the show I mentioned, OmniSend can now talk to ChatGPT and Claude. And I want to tell you why that's even bigger than it sounds.

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38:49Something that goes through my mind as I'm hearing all this is it feels to me like even if I have people doing customer support, like humans, I might still want to use Sienna because of the insights I'm getting from it. Like how are most brands using it? Is it a blend of human slash AI? Do you have any that are doing like, humans are still doing the support, but Sienna is this data layer that they can learn from? It feels like you're not trying to say switch your whole support to AI. It doesn't feel like that. Like how are brands, what's that mix look like? Yeah, so we're seeing a wide range of models when it comes to how brands use Sienna and all of our different agents and all of our different products, there's biggest, by far the biggest chunk of our customers are using both.

39:40The support experience is powered by Sienna and now the intelligence is powered by Sienna. And that's because somewhere in their leadership, somewhere culturally, they made this decision that, hey, we want to be as lean as possible and we want to be as smart as possible with what we do. That allows kind of, it's almost like you're building the foundation or that you're building, in this case, a plane. You want everyone to be on board, fly the plane and go really fast. It's not just, hey, we're going to build one room and then the rest is kind of like outside. So they love the idea that they can do both.

40:09And one operating principle that we share inside, like in Siena, and I always say this, one plus one equals three. So if you're really serious about running on AI, like becoming an AI native brand, it's of course easier and best to use both. But there's also, we also work with brands that have very complex systems in the backend where deploying these agents take a little bit of time. So it can take months until you actually reach a level of CNA really being productive in your support experience. So with those, what we see is they already start leveraging the intelligence piece from day one, and they take their time to launch the support experience because, again, you have to connect different tools.

40:57Some tools are available out of the box, like your typical stack, your subscription providers, and then obviously Shopify is available. But a lot of enterprise brands, they have very bespoke setups. So with those, they would kind of like stagger. So first, we do intelligence because it's available day one, and then a deployment will happen over the next few months. And we do have a handful of folks that are using just CNA intelligence for the time being, and they see value because their point is this intelligence layer that sits on top of what you already have. So we see a wide range, but the pie chart with most of this lean towards use both the support agent experience and use Sienna intelligence.

41:37Gotcha. Okay, so you mentioned when you were setting up, you said something like as you get more comfortable with Sienna. So is that the typical on wrapping? You have Sienna answering 5 % of tickets, then 10, then 15. Is that how it? It's a great question. One of the things that is unique about, I think, support AI in general is it really mimics the philosophy and the processes and the tool stacks of each individual brand. So sometimes I'm being asked, how long does it take to launch C &O? It's really hard for me to give like a, like, of course, we can look at the average, but the average may not apply to you.

42:15So we've seen brands go live and have a productive agent that already resolves more than half of the support conversations in two weeks. And it's doing it better and more consistent in terms of quality than human agents. That's another thing that's available and possible with Ciena Intelligence to spin up a QA agent. So not only have your support agent, you can spin up and use Ciena QA as a way to QA not just Ciena, but your whole team. And then you can see reports. how is Sienna doing against humans and how are humans doing amongst themselves? So we're replacing, we're completely replacing these pre-AI QA tools because everything is integrated.

42:53So that is very important when it comes to AI. The fun thing that it's like an interesting perspective is there's two types of agents in general. There's human in the loop and there's fully autonomous agents. Human in the loop, Cloud Code is a perfect example, or it's an agent, it's an LLM that does some work, but at some point comes back to you and asks you, okay, do you want to continue? What do you want to do? So you're always constantly prompting that agent. The other type is fully autonomous. AI agent for support. If it's running on large-end model, it's in practice fully autonomous. What that means is once you configure it in a specific way, once you train it, you give it tools, you give it access to what it needs, it will carry on the task fully autonomously with no human intervention.

43:38And for that, it's really important that when we deploy the agent, it really works well. So we have extensive testing happen. We have built a lot of AIs and systems internally to make this deployment as fast as possible and as good as possible. But accuracy and making sure that the AI is doing the best work possible is incredibly important. And that's why, you know, in the beginning phases of AI, there's a lot of companies trying to do AI for support. This is back in like 2023, 2024. There's so many different players trying to do this. And if you look around, there's not that many that are still around because it's actually quite complex.

44:15So deployment can be a matter of days or weeks or it can be months. It can be truly months. And then there's another variable, which is how big is your operations in the backend already? Like how many different tools? How many different agents do you have? How many systems? How many brands you have? That's another thing. Like you have multiple brands. So all these, it's almost like different complexity knobs. Now, you know, when someone comes to us and we start a process, we start a deployment process together. there. We already have a pretty good understanding complexity. We can estimate, okay, this is probably going to take a month, two months.

44:48Internally, we're quite aggressive around building more and more tools, more and more ways to make this process more seamless, more easy. But it also requires a lot of human judgment on the brand side. That's why one of the things that I always share as an advice is try to set up your goals, try to set up your structures so that it aligns incentives with deploying an AI and having an AI run in your company. If something like Sienna, it's just like a cute pet project for someone and doesn't really have any real tangible goals or anything like that. We've seen these deployments fail in the past because no one really cared.

45:25Oh yeah, we use AI. We have a chatbot. It's okay. It is a very different mindset versus now we need to reach this percent of automation rate in the next 90 days. Who's responsible? How do we work as a team to get there? And then everything works better once you have that sort of mindset. Speaking of which, I saw, I think this was a case study somewhere, Hexclad increased automation 65%. I don't know if this is like outdated, maybe it's even higher now. But they, and they cut tickets to humans by 20 % in 60 days. So they seem like, obviously Hexclad is an amazing brand. They do a lot of things right.

46:01What did they do that was so great to get these results so fast that maybe other brands skip? It all starts with the operating team, who's in the driver's seat for getting Sienna up and running. And specifically with HexCloud team, they have an incredible team. And we work really close with a few folks there. And there's obviously an owner that oversees Sienna. But their whole team is bought into AI. And that made it, it's almost like a domino. If the team and everyone is bought into Sienna, is bought into AI, everything runs so much smoother. versus if there's friction, if someone out there doesn't really believe in AI or feels like AI is just a crutch or it's just like a whatever trend or it's not going to work, you're never going to see incredible results.

46:47You're never going to see full deployments happen. So in the case of HexCloud, they have really good team, incredible product, and they really care about both customer experience and AI. Those are, of course, the results of various different work streams and various different things that lead to that. plus they're very good with sharing feedback. Back when, a few months back, we, Sienna, are video processing. So we're able to process videos. Not only text, not only images. Sienna can actually, you can send it, upload the video and Sienna will know what's in the video. Yeah, I saw you post that recently on LinkedIn.

47:22Or you or Lisa posted it. So I understand. So a customer, if they're having a challenge, they can record either a screenshot of something on their website or can they record a video of the product? Like it's broken here, this doesn't work and then send it. 100 % And Sienna can understand what's happening in it? Yes. Amazing. So you can think about replacement. You know, let's say you, you know, let's say, you know, you got this glass, you ordered some glasses and it's broken here. Instead of just sending a picture to say, guys, hey, you know, I got this. It's like all over the place. Send that.

47:53And then Sienna will, just like a human, interpret that video and make a judgment call. And that's another reason why Hicks Live was able to increase their automation rate. They, of course, the pens are highly, you know, they're very tactile. You have to, you know, you have to show, hey, there's a little bit of a scratch here or whatever, you know, something's happened here. So video has helped them and us quite a bit with just making it even more powerful. And then I guess the million dollar question, can it detect if it's an AI created video? Because apparently everyone's just making images and videos of their products broken to get a refund these days.

48:28I imagine they can, is there ways to detect? the best way to think about image and video processing is if a human could the ai could as well sometimes maybe even better sometimes maybe even better there's no i mean not today there's not like a built-in watermarking system or something like that but who knows in the future i would say you know high likelihood that the ais will get better at understanding if the video is generate with AI. We do see Sienna working really well with fraud cases. Maybe in this case it's not a video, but it's an image. Someone generates a fake image of a product that's broken.

49:06I don't want to betray the AIs, but you could quite easily do that. We've seen customers use it and they don't have problems. You can absolutely catch some of those. Does Sienna have any insight if a customer is a bad actor on one store and then on your store, do they have any intelligence in that or do you keep a fine line? So that's a great question. Another intelligence layer with the new product that we're building that will have, if you use that product, you will automatically enroll your customers in this cross brand, of course anonymized, but it will be almost like a watch dog. So you'll be able to see, hey, if a customer has submitted 17 returns with over here.

49:46Yes. And then we actually see a lot of input signals from brands trying to find ways to combat fraud by either telling Sienna, hey, look at if they initiated multiple returns. Look if they used in the past multiple addresses, right? Because what they do, it would always change their addresses or like use, you know, Shore Street or N.Shore Street. So there's all these things that people got really creative with. I think the good news here is you'll be able to do a lot more with AI than you can with humans just because AI has infinite attention. You know, it just works in kind of like it can work in parallel with millions of customers if it happens.

50:25So, yeah, we're looking at ways to bring these sort of inputs like fraud detection and stuff like that. It will be more and more important. Yeah. What are you most excited about for Sienna for the next 12 months? If I have Lisa on again in 18 months or so, looking back, like what are you of what you can say? What are you excited about for where Sienna is going and what the future looks like? you know there's this point in time where we realize that we can really our constraints our actual constraints as a company have almost disappeared overnight and this wasn't the case a year ago we had many constraints we still have constraints we specifically don't want to raise a ton of money or we don't want to go the path of just keep raising for the sake of raising so we have constraints but in terms of what we can build and where we can go and where we can take our customers it almost vanished and then what really what there's a few really interesting projects that keep me up at night and get me really excited.

51:20One of them being the whole idea of building your brain inside Sienna, like building your company brain inside Sienna. We're about to launch, depending again when the podcast goes out, we're building Sienna Docs. And what Sienna Docs really is your brain inside Sienna. Not only your brain, but everything internal, your SOPs, your documentation. So think about replacing your Google Docs or your notions or gurus of the world. And on top of it, you're also building a help center inside Sienna. So it's a single place to have all your data. And why this is exciting is because for the first time an agent like Sienna or multiple agents in this case don't exist in an external world where hey, you just spoon-feeded a little bit of data here, but in fact it will sit on the data that your team runs on and we're planning integration with GitHub.

52:12So we really lean 100 % into how do we make Sienna the first true operating system for CX. That's connected to your cloud code, it's connected to your data, and everything is in one place. That is incredibly exciting. And if you're familiar with skills, what you're building is a repository of skills. So you can now use old use cases that we talked about in this podcast. You can basically package them, put them in a skill, put them in a playbook, and have your whole team run on it. That's pretty exciting. It opens up the world for so many new things, even things like, hey, we're launching a new market.

52:44Hey, Sienna, we're launching a new market. Can you check our current policy? What's our current returns policy? Hey, so it's going to check your website. It's going to check your internal docs. It's going to check the actual agent guidance. So it's going to say, okay, this is where we're at. Can you now create a policy for the UK or for Europe? So everything is in one place. You don't have five systems that are not talking to each other. They just live in a complete silo. Everything is now unified by CNA in the back end and in the front end. And that's really exciting because it means you can get even more insights.

53:14you can do even more with AI. And it opens up a platform, essentially, to build on top of Sienna. So that's quite exciting among all the things that we're building. Amazing. And I imagine as you expand to different, internationally, Sienna can interact in different languages and you can maintain your docs and SOPs in one language and it can then interpret however. Yeah, yeah. Amazing. Just before we end here, is there, like, brands listening want to look into Sienna? Is it for, Do you need to be a certain size of store? Do you recommend it once a store is at a certain level? Is there a path for anyone to get started?

53:50Or where would you recommend stores start with Sienna? And how do they get started? So how to get started, Sienna, I-E-N-A dot CX. So single N, Sienna dot CX. Book a demo, get in touch with our team. We pride ourselves in just trying to learn as much as we can about you and see if it's a good fit, if we can help you. Where Sienna starts to make sense for a brand, we have different agents. So first of all, we have different agents that do various different things and more agents are going to come online. But generally, if you look at your customer conversation data, so not just support tickets, but this includes social media, this includes reviews.

54:23If you're already processing over$2 ,000 a month, probably it's a good time to think about it. And it also depends on how fast you're growing. If you're growing incredibly fast and you project that you're going to 10x or 10x reach out as soon as possible because that's the success story that we've seen with this brand. they reached out when they were growing. They're not as big as they are today, but they're growing. So it was just the right time as they were on their growth trajectory. So yeah, if you're growing fast, yeah. Probably something to be said for if you are getting a million tickets a month, it's a lot harder at a certain, on a growth trajectory, it might be better to get ahead of it early and then scale with Sienna versus bringing it in later.

55:04I would imagine that's an accurate statement right it does it not it can be but not always not always because with the tools that we have in place right now even if you're doing a million tickets a month or a million tickets a year we can see what those tickets are fair enough and then we can kind of like practically we can be one step ahead we don't have to back in the day you have to manually swift through tickets even for us when we launched you have to manually like check what people are saying just because there was not enough fidelity of data. But now we can just ask Ciena, hey, run an analysis over the last 30 days.

55:38What are the main topics? And then, you know, you start training the agent as more like you're working backwards from the reasons that people reach out the most. So yeah, tools are here. We're excited to work with brands that have strong opinions about how they think CX should look for them. But also we're here to share what we see other brands do. We work with brands that are doing billions in dollars and we work with brands that are doing$20 million a year. And we have this knowledge and we have this experience of seeing all across the board what works, what doesn't. And the one constant that doesn't change is the faster you start, the better.

56:12And it's a mindset. It is totally a mindset. Also, it's important to start, but truly try to go all in versus just try an AI. And it didn't work, but we're here and we're excited to learn more and share about automating your CX, but also building your intelligence layer. Yeah, amazing. I think, in my opinion, in five years, maybe sooner, because things move fast, maybe a few years, this will be the norm. I think every brand will be augmenting CX with AI or fully using AI in some way. So I just think for brands listening, get ahead of it now. Like now is an opportunity to move faster than your competitors.

56:53I think when new technologies come out, it's always great to jump on them because it's a competitive advantage now that might be table stakes in five years, but now it's a competitive advantage. So Sienna is, I think, probably the best platform I know to do this. So definitely check them out. Sienna with one N, because I have accidentally typed in two Ns many times. Is that domain for sale? Can you buy it or someone, they won't sell it? We have a host of domains out of which I think, I'm not sure if Sienna would double N.CX. I actually have to take a look. Okay, but we'll make sure it's Sienna with One X.

57:28Check them out. Andre, thank you so much for your time. This was a ton of fun. Thanks, Jay. Excited. Shopify.