Cutting the cost of Customer Success by 70% (without layoffs), with Jim Richmond, CCO of Smartling

Speaker A: If you're spending time in a spreadsheet, I want you to be very suspicious of that role. If I get on a bicycle, I can go 20 miles an hour for all day, basically, right? Cover 10, 20, 30x the distance. I no longer need people who are going to show up and spend their day dealing with password reset requests. Right. That's a solved problem. I want everyone to be working on their highest and best purpose, and I don't think that can be faked.

Speaker B: Folks, I have an incredible guest for you this month. Our Guest today has 15 years of experience in customer success. He has held five executive positions in the last decade. He founded a company that was backed by Y Combinator, and Today he's the CCO of SmartLink, a translation platform for B2B companies. He's one of the sharpest minds that I know on what it takes to scale a CS Org when revenue stakes are real. Our guest today is Jim Richmond. And if you ever had to build customer success in a company sitting anywhere between 50 to 250 million in revenue, especially in technology, Jim has lived this journey more than once, and we are going to go deep today. We're going to talk about what scaling CS actually requires when growth is the mandate. We're going to talk about AI and not the hype version. We're going to talk about what is changing in CS right now because of it, and we discuss what the CS team looks like in the next three years. So if you're navigating the gap between where your CS Org is today and where it needs to be, this episode is for you. So go grab your own issues, get your headphones, and let's get started. Jim, it's so good to have you here in the podcast. I'm so excited for our listeners to get to know you, and I'd love to start from the start with your story. Can you introduce yourself and walk us through how you ended up in the world of customer success?

Speaker A: Absolutely. Well, first of all, Daphne, thank you so much for having me. It's a pleasure to be here and, uh, just to have an opportunity to learn and grow, uh, is always a positive thing for me. Um, so I've been in enterprise software for the better part of 25 years, and I like to say that one of the things that's unique about me is that I've done almost every customer facing job you can do at a SaaS company. So I started my career a long time ago, uh, at Accenture Anderson Consulting, doing legitimate systems engineering and integration activities. I've worked at gigantic companies like their and Oracle. Um, I got money from Y Combinator and built my own startup from scratch and learned a lot of lessons there too. And I've worked at a lot of companies large, uh, and small in between. But I've been a technical account manager which is sort of what success was before it was cool. I have been a professional services like consultant. I've led those teams. I've carried a bag and sold software, uh, and services before. Um, I've been a solutions consultant and been a demo meister and done all that stuff. Um, and then I've spent a lot of time leading uh, customer success organizations of one size or another. So I like to say that I have a lot of empathy for everybody, uh, in the SaaS ecosystem for what they're going through because I've probably struggled with it and grown through some of that journey as well myself.

Speaker B: Yeah, that is incredible experience and I think so valuable right now as we're trying to figure out this new go to market motion just to know how every piece of the puzzle works. I'd like to ask you maybe a personal question but like what was experience or the thought or the vision that brought into the space of customer success and capture here for me?

Speaker A: I'm somebody who gets bored easily. Daphne. I, uh, I can't do the same job every day. I just kind of, I, I get, I get squirrely and anxious about it. And what I love about being customer focused in, in the SAS ecosystem is that every day is completely different. I have so many different customers that are at different stages of their maturity cycle. I have a bunch of different professionals that I get to work with that are in different stages of their career and, and their own growth journeys. Lots of different escalations happening for a variety of reasons. That is what has captured my attention and engaged me um, for so many years is that I get to do all kinds of interesting stuff and you don't really know what necessarily what's going to come next, but you do know that the work is valuable and is engaging. So I've never struggled with opportunities to grow or with caring about where I've, where I've been working next.

Speaker B: Yeah, Jim, I, I can relate to that so much because um, I think it's the thing that brought me to success as well and kept me here is this, it's how dynamic and diverse it is and how the different customers challenge you in different ways. Uh, and no two days are the same. So I agree with all that experience and all those decades in doing this work, you obviously have seen many waves of disruption. Uh, AI is not your first rodeo. Uh, and we're obviously now in this period where a is fast disruption. Everybody's talking about how things are changing and concerned about their own roles and trying to re engineer their own organizations. I know I'm feeling the pinch of it. I know my team is feeling the pinch of it. You know, with the wisdom of all that experience, like what do you tell a CS leader who's trying to figure out what to do and what to build right now?

Speaker A: I think that the way I try to look at, uh, you're right. So we've been through at least in my career, right? The advent of the Internet and like putting databases onto the web, uh, um, mobile technology when that came along, like there's been a number of meaningful disruptions. I think that the latest AI one is, I'm having a lot of fun with it because it's happening so quickly, right? With uh, with the advent of, of the World Wide Web, for example, like it took five to 10 years to, for the technology to get to fully mature and, and fully penetrated. And with AI it's, it's you know, months if, if that. And so it's, it's a very aggressive kind of time cycle. And so everybody is going through that, crawling up that learning curve and learning at the same time. And so I would advise my peers and the folks I'm working with to first of all like, don't treat it like it's a fad. It's very clear that this is here to stay and that uh, and that the fundamentals have changed. But also like, be patient with yourself and understand that, that we're all in this together and everybody's, everybody's going to struggle and stumble a little bit. One of the things that I'm coaching my teams to do. You've heard the old saying that uh, the best time to plant a tree is 20 years ago, but the second best time is today. One of the things that I'm coaching my folks to do is just get out there, vibe, code something, challenge yourself, find, find a problem, even if it's a small one, and, and start scraping up your elbows and, and learning how to do it and that and that and making it okay for people to, to experience a little bit of waste or a little bit of failure in terms of doing that in order, in order to build skills and, and to keep the momentum moving in the right direction. I think that's a lot more important to get started anywhere than it is to worry about waiting for the right platform or the right framework to come along to make everything perfect. Like it's messy right now we're all learning. That's okay.

Speaker B: Yeah, you know, that resonates because uh, I do think especially inside enterprises, people are very precious about the systems and the tools and the stack and you know, people want it to be, to be perfect or you know, at least as close as you can to being, to being really robust. And right now I don't think we have the luxury of that. We do have to try stuff and it will be messy before it's organized. It will be a little scramble before it's coherent. Uh, so I totally agree with that. I've been getting my hands dirty with so many things. I've been in Lovable, I've been in Replis, I've been with QuadCode and uh, to all different degrees of skewer success. But it's been a journey and it's actually has helped me shape my perspective uh, as a leader of what is possible and how we can use these technologies. So I agree people should be getting their hands dirty and trying and not being afraid of maybe breaking a few eggs in the process of learning.

Speaker A: One of the big uh, unlocks for us at Smart League in our journey was I heard you rattle off a bunch of names of different tools. Same. I've been out there trying a lot of them. One of the big unlocks for us we're so, as I think a lot of your listeners probably are, we're so cautious and conscientious about our customers data and making sure that uh, security are there. And the big unlock for us was selecting a vendor and getting our IT ops folks to bless that and say you can trust this with your data and it's okay because previously like you know, you get encouraged by your boss to go out and get into Lovable and make an app or to go use one of the slide creator tools and, and power out your QBR deck in a different way. But every time my finger would kind of hover over that button and I'd be like I'm not ready yet to, to you know, share part of a customer list or something like that because I don't know where it's going and I never felt comfortable with it. And so for us, um, formalizing a relationship with and, and, and choosing to trust ah, a platform has, has created kind of a renaissance internally where we can finally really start building now that we have some trust established.

Speaker B: I love that point. Uh, Because I think yeah, everything that you build without having that it blessing and data foundation can be very interesting mocks and can help you again train and get used to the new skill that you have to develop. But for it to actually be integrated to the work and for you to feed your customer data, which is so precious. You're right. Uh, it's company ip, but it's also like you are the steward of that data, which sometimes is literally your customers first party data. So very, very important to do that. Am I being cheeky if I ask you who did you guys decide to go with?

Speaker A: Uh, you are free to ask. In this case we work with five of the top five frontier model. Uh, uh, uh, and so it's not appropriate for me to say sort of which ones we're working with and which ones we're not. I don't want to open it up to that. But uh, it's been a big unlock for us because ultimately the business value that you get is associated. Like you don't get business value without putting the real data in there. Like you can't just be cute and sort of make slides or make something that looks nice. It has to actually have business value, which means it has to be trusted and uh, and have reliable data in it.

Speaker B: Yeah, totally agree. Um, let's shift gears and talk about value. Um, you, you kind of already talked a little bit about like, you know, how, how do these technologies bring business value and in your career? You know, as we prepared for this conversation, we talked about your experience and some of the things you've achieved. And one of the things that really stood out for me was the work that you did with the team in Medallia, cutting costs. Um, and you know when most people hear about cost cutting, they think about cutting headcount and letting people go. But you know, I have the feeling that that isn't the full story for how you're able to make that team more efficient. Can you tell us the story of that? Because I think the listeners will be very, very interested. Especially right now when a lot of people are under pressure to do more or less.

Speaker A: Yeah, when I think about the arc of my career, the, my bread and butter, like the places I've been most successful have been at, ah, SaaS, companies that were trying to get from maybe $50 million of revenue to $250 million in revenue. Right. No longer a startup, but need to do something dramatically different in order to scale and get, and get to the next level. Uh, and that was certainly the case at uh, Medallion, where I joined there. They were right, right at about that range. And you know, we, I'm proud of the work we did to get them to a very successful exit a few years later. Um, but so one of the things that we found is that Medallion was in the customer experience management space. Um, so they kind of ate the market from the top down, like doing very large, very sophisticated, um, work with, with big clients. Qualtrics was in there and they ate the market from the bottom up where you could just sign up with a credit card and start the same day. And what we found at, what I found in Medallion was, was that the uh, the pivot that the company was making from like scrappy startup where we'll do anything to make our customers successful, which is such a great energy and something that I really always try and preserve. Um, but that ultimately leads to things not being done maybe the way that they should. And one example of that was the platform is so capable and so robust. And I have a lot of friends that still work at Bedalia and I love the work that they're doing. The platform is so capable and so robust. It has a lot of knobs and levers and requires a fair amount of care in terms of how it's set up and to make sure you get the value out of it on the backside. And so what was happening was that we were not positioning professional services and training and uh, and, and support in the right way, in, in the way that we should have. Right. It was very much, let's focus on, let's go out there and, and win all these deals and we'll figure it out on the back end. And ultimately what, what needed to happen was our sellers and our go to market team needed to make the realization that as we went into these very large enterprise accounts, uh, these are customers that are, that are very used to uh, paying a certain amount for professional services for paying a certain amount for training, for paying a certain amount for Platinum support and so on, um, that they understand the value of those services, they don't mind, they generally have budget allocated for that. And so going through that motion of helping Medallia up, level their go to market play, to position those things as the valuable things that they are as opposed to not positioning them, taking down the deal and then having to invest later, um, to still do that work. Right. The professional services are required to make the platform sing. And so a lot of the cost reduction that we experience was simply driven by repositioning how we face the market to be not whatever you want. Yes, yes, yes. We'll do anything to be more prescriptive and more measured and to take an operational approach to. Let's talk about how we're going to do this and how you actually get the full value out of your subscription. And so a lot of that cost reduction was not about um, removal of headcount or dramatically changing the way that we worked. It was about getting the value graph right between the go to market team and the customer of how do we think about the value of this work that's being delivered? That was a big unlock there.

Speaker B: And you know, I think this is something that a lot of SaaS vendors struggle with, is knowing that there's so much value on the services that get attached to the software in order for the customer to a get set up correctly from the get go, but also have a scalable implementation that you can continue to build on top of that and unlock new use cases. Everybody knows the value of that, but the confidence of selling that to the customer from day one, because it can feel like a friction. You can feel like, oh, you have to pay the software, but there's also this big service cost on top of it. And it just feels like it's like one more thing for the customer to say no to when you're trying to get a deal through the line. And I've seen so many times when customers get sold, uh, without the services that they need or with a, uh, very, very reduced scope for those services and then lo and behold, what happens after is that you have to fork the check to actually deliver those services because you didn't set the right expectations from the start. The customer thought it was going to go a certain way and it didn't. And now you're to savage the account and you're trying to really save when you should have had such a much better experience. So I really resonate with that. And in the age of A.I. now, um, everybody's talking about the forward deployed engineer, which is basically a type of service that you offer to customers. And I think becoming confident with selling the value of these types of services will continue to be important. What do you think?

Speaker A: I completely agree. I think it's seductive to take that shortcut, to say, listen, we're going to make it really easy, just buy this thing and away you go. Um, it's seductive to take that shortcut. It's a bad choice in the long run because if the onboarding doesn't go smoothly like you're, it makes retention very difficult. It makes getting the full value out of the platform wrong. It's a much better choice to just come correct with the right mix of services and success and everything else that you might need that you think the customer actually needs. Because ultimately what the customer is buying is a set of outcomes. And if you're not delivering those because the price was a little bit lower, that's not a win. The customer doesn't necessarily want to save money in that way. They just want the pain to go away to get, to get the outcomes that they were promised.

Speaker B: Yeah, yeah. And I've heard you describe this, uh, before, that clients don't want to buy software, they want to solve problems. And you just kind of talked a little bit about that here. It's a situation, it's a simple concept. Right. But it's something that most SaaS companies find hard to admit. There's a little bit of ego around the product. Right. We're the coolest product, we have the best features, we have the best brand. You can get wrapped around your own product and forget about customer value. How do you build a CS team that's focused on value, not just on, um, talking about value, but also delivering that value?

Speaker A: Yeah, a couple of threads I want to pull on there. The first one is, uh, one of the core elements that we try to bring to our approach with our customers at Smartling is this idea of empathy, of putting ourselves in their shoes and more specifically making them the hero of the story. It's such a natural default setting for every professional in western society that I know where you and your company are the center of the story. Right. That's the sensorium that you're part of. And it's so important to take a step out of that and really think about, okay, I'm customer X and what does my day look like? The Smartling BR that we've been working up to and really getting excited about presenting to them is like 90 minutes in an otherwise jam packed day. And when you think about the typical Martech stack has like 70 something vendors in it. What I'm talking about is not the center of their universe. Right. And so the way that I choose to articulate value and to engage with these customers is to, is to be humble and consider that I'm one of 70ish. And so how, how do I make their life easier? How do I get their attention and fit in with their day? Um, so the way that we do that in terms of being focused on value is first of all we're very disciplined about our ICPs, our ideal customer profiles. So who Are the, we've got four at Smartling, who, who are the people that tend to buy from you that make the decisions about whether or not they're going to keep, keep the subscription going or not. And those different ICPs, even though it's the same use case, they think about value in very different ways. I was having a coaching conversation with, with my boss Brian Murphy, the CEO a few weeks ago and we were going back and forth about the ROI calculator and all that and he gave me some great advice. He said let's, let's just shelf the ROI spreadsheet for a minute and let's go back to first principles. Why would someone buy our product? Now Smartling is a company, we're an AI company that makes uh, high quality translations available to uh, anybody at the right balance of cost and quality and speed that's important to them. And we're disrupting a very long standing marketplace of translation solutions that typically took a lot longer and cost a lot more. And so I uh, say all that to say the reason why someone would buy Smartling because they want to translate stuff from one language to another full stop. Like we, we can forget the, the, the pivot tables and all and all that kind of stuff. Let's go back to okay, for a marketing user, what do they value in terms of translating stuff from one language to another? And that is quality is probably most marketers number one thing they care about because they understand brand value. They're the custodians of that. And even a small translation error can be pretty embarrassing and, and, and erode that brand trust. That's very expensive and time consuming to build. If you contrast that with a product owner, this is somebody who is responsible for all of the strings that populate all the menus and all the buttons inside of an app. Um, their values are probably pretty different, right? If the button says submit versus uh, send, I don't know, like that doesn't damage the company's brand in most cases. Right? That's a relatively small uh, and so what they're much more worried about than quality might be um, integratability. I want, I want all the strings to flow through very seamlessly and very quickly. They might be concerned about cost. Um, can I get things pulled into figma and see stuff in a left to right language and a right to left language and make sure that it all works. All that to say the value graph for these different ICPs is pretty different. Even though we're providing the same fundamental service at the absolute bottom and so the way that I try to think about value and demonstrate that on a recurring basis to my customers, I want that to vary based on who they are and what I know that they care about. The last thing that I'll say, uh, Daphne, is that I try to attend a lot of right along with my CSMs on a lot of their customer interactions. Not all of them, but. But I want to pop in whenever I can. And always when we present our, you know, our kernel sort of core value conversation, I stop the conversation and I say to the, to the decision maker on the other side of the table, is this even right? Like, do you care about these numbers? Do they, do they impact you at all? And what are the numbers that you're being held accountable for to the board? And you'd be surprised how often they say, this is interesting, but it's not necessarily what I wanted. And that's. I love to hear that, because that's the jumping off point for a much more valuable conversation, which is, tell me what gets you promoted and how do I help, and how do we articulate things in a way that is balanced and gets them what they need?

Speaker B: You touched on so many things that I think are important there. It's like the understanding of what value is for your customer, but not just at the corporate level, but actually the different, uh, people inside the organization who all have different mandates and different responsibilities. And in order to motivate them, you do actually need to talk about things differently, even though it's the same product. Uh, so I totally agree with all of that. And you jumping in on that call with the CSM to talk about value and stopping the call and asking those questions, that's one of the things that I've done as well. And it's one of those very, very interesting moments where you kind of realize that sometimes CSMs are going into those conversations. They're spending all this time preparing decks and narratives and working the ROI calculator and doing all these things, but they haven't stopped to build on the more fundamental piece of the value conversation or dev value realization journey, which is the early alignment on what value means to them and what metrics are important and all that stuff. Is your team doing something, or whether it's an interaction or has a tool or process for doing that, from the moment that the customer signs and has that business case for why they came on board, are you doing something there? Um, or every CSM is doing something different.

Speaker A: I feel like the holy grail of customer success since the beginning of My career, anyway, might as well be the beginning of time has been this single artifact that spans the entire customer journey. From, uh, the promises that the BDR made when they did their cold outreach at the very beginning of the cycle to the pixie dust that the seller sprinkled as part of the sales cycle. And then the requirements, gathering, conversations and services. Did that flow all the way to where we are today? There's supposed to be a single artifact, a living document that sort of catalogs all those expectations and interactions as they exist. Very, very difficult to achieve in actual reality. And I think that's one of the most exciting things about the LLM AI revolution that's happening right now is that it's never been easier to wire all of those different things together into one coherent document. And that's something that, that we're in the process of building right now, is something that puts together all the notes and data that are in the CRM, that grabs the requirements documents and definitions and stuff from the services engagement, that takes all the CSM notes and puts them all together into one cohesive timeline that sort of shows us, um, the evolution of the conversation with the customer over time. And so I'm so excited about the ability to do that now, which previously was something that required an enormous amount of operational discipline and coordination between a bunch of different departments with a bunch of different incentives. And so, like, now is really a golden era to do a lot of that. And I'm here for it. It's a great change, even though it's a big one.

Speaker B: Yeah, I'm excited about that as well. Like in HubSpot, we have this thing called value plans. And, uh, yeah, it's this single artifact that we're trying to maintain for the life of an accountant. And AI is definitely like one of the key unlocks for us to be able to do it. Um, so I think we're all trying to gather that context and to understand the promises. But as you know, value definitions change as well. You might have sold something for a customer because, I don't know, maybe they had a specific goal in your case, that it might have been that they were launching in a new market and they needed to localize everything that they do into that language, etc. But as their business strategy evolves, there are new projects, new people, new departments that value case also grows and evolves. And to think that the reason why they joined in the first place is the reason that they are still here five years down the line, for example, that would also be a mistake. So it's like, really just continue to have this conversation is so important. Let me move us to another question I wanted to ask you. When you were in Sprinklr, I know you were measured on retention, and we talked about how you and your team were able to manage a, uh, significant lift in your gross retention number. Um, I would love for you to share with the audience, like, what were the things that you did practically with your team to improve retention? I believe it was 10%. Like, how did you achieve that?

Speaker A: Great question. Grr. Gross revenue retention was our North Star at Sprinkler and is today too. I think that's one metric that has really endured, uh, over the years is just what size is the hole in the bottom of the bucket and how do we make it smaller is something that is never going to go away, in my opinion. Um, and like I talked about earlier, Daphne, that arc of my career where I've been sort of most focused on helping companies get from looks like this is going to work, like we're not a startup anymore to mature software company of consequence, typically, uh, stepping in that inflection point in that, in that phase change of, of how they think about their business, they're going through a dramatic amount of growth and things get a little wild. And that's great, right? That's what we want, is a lot of growth like that. But ultimately, what made a big difference and one of the main things that I learned during my time at Sprinkler was operational discipline. There's no substitute for it, and you have to have it in order to scale profitably over time. Um, you have to understand, where are our customers in their life cycle, like, how long until the next renewal, how much is it? And make sure that the fundamentals, the blocking and tackling are there in terms of really having a great CRM that you trust that is in sync with the reality and being able to understand the business that's in front of you. One of the other things that, uh, ties into operational discipline that I think is really important is as you go through a dramatic amount of growth, it's very difficult to sort of get your workforce, uh, aligned with the quantity of work that there is to be done. People are, you're adding people and they have to learn and ramp and all that. Uh, and so as a result, you tend to wind up being a little bit behind the eight ball because you're trying to adapt to growth. And the default motion that a lot of teams fall into is they lurch from fire to fire when you start to get behind, you have to triage things and you have to focus on what's, what's hot at that particular moment. Um, and that, that becomes a challenge. Right? The, the, what you have to do is be willing to take a step back from that to say we're going to let a few of these things go and we're going to focus on what the big rocks are, the pareto of the small number of things that have the biggest impact and go after those. And that was something that we did very successfully at Sprinkler was, okay, foundational. We have to understand the business and have source, uh, systems that we trust and then we need to build a forecast and really understand what we think is going to happen next, what's going to be impactful because of that. And then we're going to go focus on running down those particular things. That is a playbook that I don't think gets disrupted by AI or anything else. That you simply must do that as you scale and move from scrappy. We'll do anything. Startup to mature grown up software professionals.

Speaker B: Yeah, you know, I've also walked this journey. I've been in startups, scale ups, enterprises. I've seen kind of the, I've seen customer success from a few angles and I've seen the different maturities and what I've observed when you're moving from that startup and you're kind of putting your big boy pants on and you're scaling and standardizing, et cetera, is that those operating systems that you need in place, that operational rigor and discipline you talked about, that can be extremely off putting for the people that were there early on. A lot of early CSMs, early professional services people, early sales reps, they don't like the structure. The moment you start bringing in processes and metrics and leading indicators and this and the other, uh, people feel like you're taking autonomy away from them when actually as a leader you're trying to scale best practice and make sure that everybody is delivering the same customer experience, achieving the same results so that you can scale a business. You can't scale otherwise. Having gone through this journey of implementing this OS and driving these efficiencies, like, is it possible to retain all these people from like phase one into phase two? Or is it. You just have to accept that some people are not going to get in the bus as you, as you make these changes.

Speaker A: I think it's a numbers game in terms of the population of folks that you have on board. There are certainly people who are hardwired and just love the startup, sort of wear many hats and go after that motion. And I think you're right. Uh, at some point those people are not going to feel like they're getting the right growth opportunities and they're not going to feel satisfied as you work your way up the maturity curve. That's 100% okay. I think that's the role of a professional manager is to understand the desires and the growth path for everyone in the organization and align the company's priorities with the things that, that are going to make them grow and, and feel valued. And sometimes you can't do that. And that's, that's okay. Like, that's, that's part of my role as, as a leader is to help apply everyone to their task of maximum impact. Right. And if there isn't one, that's all right. Like let's, let's work on finding the right thing for you to work on that does align to the things that you want to do. I, uh, think there's another. So there's, there's a small minority of people like that. There's. The middle is, uh, is folks who are interested in being on a growth journey and can be brought along and are open to coaching. I'm there for that. I love that as well. And then there's, and then there's folks who, who uh, you know, you sort of bring in and are really focused on, on scaling and growth and building those things. And of course they'll come along. Also, one of the things that I talk to my organization about a lot is first of all, you're at an AI company during the AI Renaissance. Like you cannot be at a better place just in terms of watching what's happening around us and going on this growth journey together. But furthermore, if you don't feel challenged and you don't feel like you're growing, um, that is a shared responsibility between you and the company. And we need to be constantly holding each other accountable for that growth or lack thereof and making some decisions about is this the best investment of our limited time?

Speaker B: Yeah. And thinking about like that point of like being in an AI company at a time of AI disruption. I know like there's a ton of conversation around the entry point roles. Right. There's a lot of um, excitement for people who have deep domain expertise to scale themselves with AI, et cetera. But a lot of the bottom kind of like early starting work, uh, we see that in support, you know. Ah, ah, HubSpot. Over 50% of our tickets are now being uh, solved with AI. So you take all of that kind of, let's say early stage, easy, simple work that uh, teams in customer success and support and professional services used to do and you now put in, you think about the career path for people. How do they enter uh, an organization? What's your perspective of what's going to happen here? What happens when we keep being pushed upstream, uh, what happens to the customer success professional and uh, to that ladder that we're so used to pushing people from like you know, associate all the way up to principal or you know, whatever that top title is.

Speaker A: I think that when I think about AI tools, I like to analogize them to a bicycle, right? Like I'm in reasonably good shape. I can walk at about three or four miles an hour and I could probably go you know, 10, 15 miles before I'm really tired and need a rest. Uh, if I get on a bicycle I can go 20 miles an hour for all day basically, right. And cover 10, 20, 30x the distance. And I think the AI tools allow you a similar step change in terms of your output. But at the same time, um, an AI is like a bicycle in the sense that if there's no one on it to pedal it and there's no one on it to steer it, it doesn't go anywhere. It's just a piece of metal and rubber that lies on the ground. And so when I think about entry level work and the basic things that the, the sort of early in uh, your career, jobs to be done, they're still there, they just look very different. Right. Uh, we know I no longer need people who are going to show up and spend their day dealing with password reset requests. Right? That, that's, that's a solved problem. We got that fixed. Uh, however, I absolutely am interested in someone who is earlier in their career and is really gifted with vibe coding things, really understands um, how to interact and engage with these tools to help make them better and to find the next use case and to continue to increase the value equation. And I think that's something that people who don't have all the uh, what do I like? I call it the curse of knowledge. Right? Like uh, who don't have all this baggage around the way things used to be done and how organizations used to work. Um, I'm very open to that. I want, I want those new ideas and I want somebody who is uh, an AI native to show up and break some of these paradigms so that we can keep going. I'm there for it. And I think people who are earlier in their careers, um, and may not have the depth of historical knowledge about the way some of these businesses work or the way that our platform works, that's totally fine because you can ramp yourself now. There's, there's the, the knowledge assets that are available are, are flatly unbelievable. And so you can really have knowledge in your head on a just in time basis in a way that, that wasn't really possible before. So I think that I, uh, I would not abandon all hope if you're somebody who is, who is earlier in their career. And similarly, I think you're right. While the basic sort of entry level job role has changed dramatically, I, I don't think it goes away.

Speaker B: Yeah, no, I don't think it goes away either. I do think it's different. And I like what you said about people who are more AI native thinking about problems differently because I do think that diversity of thought is such an, uh, important thing in a team. And when you have a problem to solve, when you have your veterans that have been there and done that, and then you also have the people who have the domain of, um, the new technologies and just a more kind of malleable way of thinking than the veterans, you arrive, drive to better outcome and a better solution. So that gives me hope. Jim, thank you, thank you for that. Um, one thing to wrap up our conversation. Um, you're in an AI company and I know everybody that is embedding AI into their product or is kind of like starting AI companies. Everybody's trying to figure out how to really communicate the value of AI tools. There's a lot of hype there. You know, there's a lot of promise and potential. But actually, you know, making those value use cases, um, stick and measure them like that is, I think that is a place where people are having a ton of challenge right now. Is there, you know, beyond what we already talked about when you talked about aligning with what value metrics are for the customer and stuff, like, when you're thinking more internally, that conversation maybe that you had with your CEO about like, what value do we deliver? Is there a framework that you use, um, to really think about translating AI capability into what business outcome it drives?

Speaker A: Yes. That's at the core of what we do as a company where historically the primary way you could deliver value as a translator was through human labor. Uh, and that relationship has completely changed now with the advent of technology. Um, it allows us to reuse translations, to find ones that are approximate and mesh them together. Uh, and to automate a lot of the work and have a subject matter expert sort of validate and audit and just make sure that things are perfect. Um, again, it's a bicycle, right? It makes a single human expert much, much more productive as they go through. And so the value equation should, uh, reflect that when we talk with our customers. So we talk about, um, quality, we talk about speed, we talk about cost and optimizing the balance of those, because there are a bunch of different approaches you can take from fully autom to substantial human in the loop interaction. Uh, and so that's. It's a difficult question for you to answer because it's always been kind of the case for us, for us as a company of how do we, how do we deliver a certain level of quality while dramatically, uh, exceeding their expectations on cost or dramatically exceeding their expectations on turnaround time, for example? So that's, that's, uh, that's kind of baked into the approach and why we're even in the marketplace. Um, but I also want to say that I think that there's a big conversation to be had about the value of humanity and the value of this work and what's being done. And ultimately what we're trying to do is to help people be better understood in the languages that are important to them. And so rather than saying, oh, we're disrupting this part of the economy, um, the way I want to look at it is to say that, that, uh, there's an opportunity now with this automation and with this focus on quality, that we've got to do way more. Right. That all of a sudden it's not just Spanish and French, that I can have my product catalog or my privacy policy or my mission statement understood in any of the 7000 languages that exist in the world right now. And that's never been possible before at any amount of scale. And so I think it's. It's unambiguously good and clear the value that can be delivered through some of these AI solutions.

Speaker B: Yeah, I think you're touching on something that I've been hearing, and I'm asking this question to quite a few people. And we kind of just always go back to the same things that are valuable to customers and to enterprises. And it's usually what you said, uh, it's speed, it's quality is cost is revenue. All these foundational ways that we have always thought about value, they are still, at least, they seem to still be very applicable. It's like the AI is the mechanism, and in your analogy, the bike, it's how you get there, but it's not the thing itself. And all of those kind of metrics continue to be very important. And it's what you bring to the cfo, it's what you bring to the CEO, the CEO, whoever that point of contact is. It's not the million metrics you probably have to measure things inside your product in AI, but it's actually the outcome that's driving to their business. And those outcomes, uh, seem to remain the same. Yeah, I like that. And thank uh, you for talking about the value of humanity. I think this is not something a lot of people talk about and I think we feel very viscerally how important it is. The importance of connection, the importance of being understood, the importance of ideas. All of these things are so important and so inherently human. But I don't think we talk enough about that. So thank, thank you for bringing that on.

Speaker A: Sure. There's a lot of anxiety about, about AI and what things are going to change. And the coaching I'm constantly providing to the teams that I support is if you're spending time in a spreadsheet, I want you to be very suspicious of that role. Right. The whole like the big promise of AI is that you're not wasting time on your TPS reports anymore. Right. That, that, that, that's ultimately the goal is I want everyone to be working on their, their highest and best purpose. And that's almost never something that's in a spreadsheet document. I want it to be spoken and engaged and authentic with our customers. And that's where the value is. And I don't think that can be faked and I don't think it's going out of style anytime soon.

Speaker B: Amazing. Jim, thank you so much for spending the time today talking us through this, sharing your experience, sharing your wisdom and your thoughts. Uh, we're so lucky for having had you and I hope you have a fabulous rest of the day.

Speaker A: Thanks for the great questions, Daphne. This was a lot of fun. I appreciate the opportunity to join you.