B (3:30)

Yeah, that's awesome. Thank you. And I like the analogy and it's cool your background in comedy there. And you're right, it's more about just than laughing but understanding people's behavior, you can see that in their body language obviously are they engaged? And your transition to tech and AI, same thing, right. In product, are your customers engaged? What are they really feeling? Are you actually listening to their feedback? I think that's awesome. So I appreciate that. And Ruby Joyous positions itself as a dynamic conversational alternative to legacy tools like Qualtrics and static surveys. What are the biggest pitfalls of traditional feedback systems and how does Joyous chat based model overcome them? What trade offs did you have to make along the way?

A (4:16)

Well, I mean I think it's pretty common knowledge the biggest pitfall of traditional feedback systems and survey systems, whether you're using them in a huge organization the way people use Joyous, or even if you're just a more smaller individual trying to gather some feedback. Right. It's a one time transaction instead of an ongoing conversations. So to me tools like Qualtrics, they produce data that's much more quantitative. So numbers oriented, it's static, it's really decontextualized. You get, I mean think about, you get charts and you get millions of charts but you don't get stories and you certainly don't get enough information to act on. So I think what most people are used to in that kind of context and in that kind of older world is that you kind of, you're sending off some sort of annual survey. Let's just pick engagement. But I mean a lot of people do customer surveys as well. And it's a once or twice a year kind of a thing. And it's the same thing over and over again. And that's really important because businesses and industries and the people that are working there and the work that they're doing is changing and it's changing fast and it's changing sort of dramatically. And so when you're asking me, how does Joyous overcome that? Well, I mean that's what's been honestly just really interesting with joy. As you see, we took like a fundamentally different approach from, from the beginning. We wanted to make feedback conversational. We wanted to make it lightweight and focused on what's like happening at that moment. Not just for the business, but for the employee too. So I guess instead of like a 60 question survey once or twice a year, we really just ask one or two specific action focused questions. And it's like sending a text. So it's very, very easy, except then you're talking to an AI that's dynamically following your lead in the conversation, which is kind of great because it won't judge you, it's not going to penalize you like it would if it was a leader or maybe someone in the company. Or you would fear that maybe even if it wasn't real. And it will be far more unbiased at including your ideas into the results that the executives see. So I think that shift takes feedback from a much more like repeated reporting board level mechanism to I guess like a meaningful operating system that drives both growth and innovation. But really at like a very human level, it just makes people's jobs easier to do. Yeah, and I mean you, I think you asked about trade offs along the way. Well, I guess people are really conditioned to those surveys as much as there are flaws with them. So for us we had to really rethink. Well, they're used to seeing metrics and numbers and like that's their, I guess, KPI. We had to rethink how to measure impact when the signals are way more qualitative because we're looking for the actionable thing to do, we're looking for the action plan, we're looking on how that can impact a business. So the evidence for us is much more about how many actions are surfaced, how many people are contributing ideas, how many ideas are they contributing and then what are the dollar impact of those ideas and how long does it take to realize those. And it's interesting, right, because people don't think of that, of this as a way to use feedback. They've been conditioned to use it for measurement. So I think for us it's been a journey in opening up people's minds to that possibility and for me like getting the technology to do what we wanted to do, you'd think it'd be easy or it was a slam dunk. But the AI side of things has just been such a significant hill to climb, especially with us. We're trying to do something consistently, securely, super high quality, we work with the world's biggest organizations and have been for years and like no one else is doing what we can do today. And that was extremely hard. Yeah, I would say it's been quite a ride, but I think it's a lot better, way better than surveys for sure.

B (8:10)

I absolutely agree on that. Working in this space for a long time doing service desk surveys twice a year, I totally get it but. And that is the traditional pitfall as you mentioned in these systems it's a one time transaction, it's decontextualized, there's not enough information and again it's the same thing over and over again. What I like about your platform though, you're it's that action focused questions, it's feedback, real time using AI. Obviously it'll be a lot more unbiased as well, which I really appreciate. So you're doing a great job there. I appreciate that. And Ruby, the next question, despite leading an AI company you believe human contact will become premium as organizations over automate interactions? Could you elaborate on that tension where automation is smart and helpful versus when human touch must be preserved especially in employee experience or frontline feedback?

A (9:02)

Yeah, it's like such a hot topic for me, like it's on my mind honestly just all the time. It's a real personal bugbear of mine. I mean if you go look at our website, be joyous AI right at the bottom on the footer, we have there that we use AI to help humans and not replace them. And I think that like it's such a risky time for us in the world as I think you have all these, I think a myriad of extremely high value valid applications of AI, particularly around automation of like kind of mundane manual tasks that a human interaction isn't really that important in. But what I do see is, and you will have seen this too, no doubt your audience, so many companies wholesale letting go of for example customer success teams or customer service teams and bringing in AI agents instead. In fact you mentioned Qualtrics before and I always joke to my team about them saying that they're building AI agents to bring empathy at scale and I would say that is a crock off because you can't tell me, let's just Say as a for instance, in a really important critical moment in your journey as a customer, let's say you're about to miss a flight or something really bad has happened and you're very stressed about it and you try to connect with an organization to get yourself through that really difficult moment. The last thing you want to be doing is talking to a bot. Like, I can't think of anything worse. And so I just think there's this huge risk that some people are going to go too far and they're going to let go entire workforces. They're going to go really all in on AI in a way that replaces humans, not supporting them. And I think that entire businesses are going to fall and we're going to see a huge course correction. And honestly, I believe humans are going to become the premium experience, not AI. And I am. This is my prediction. I'm calling it. I think there'll be lots of great applications. Obviously we're an application of AI as well that is quite deep in AI. We have 11 applications of AI chained together in a workflow. So I am saying this is the CEO of an AI company, but it is all wholeheartedly what I believe.

B (11:07)

That's awesome. Thank you for sharing your insights there. And like you mentioned, this is a big topic to you, Antony. I talk to CEOs all the time on this podcast that work in this space. And a trend that I'm seeing you said you're seeing is this. These customer service or success teams are starting to be replaced rapidly by bots. And I agree that could backfire drastically to their business. But I believe in a hybrid approach. I believe in stepping into it slowly, but we'll see what happens. But I would certainly agree with you on that point. Absolutely. Ruby, the last question of the day, looking back on Joyous Journey, what are some failures or blind spots you faced in product go to market adoption or scaling and how did you course correct. And looking forward, what is your vision for the next generation of feedback systems, AI and human systems? And what role will Joyous play?

A (12:02)

Blind spots. There have been many failures as well. I don't think anyone gets to the kind of point that we have with Joyous, which admittedly still has a long way to go, but you got to have made millions of mistakes to get to where we are. And I think probably one of the early blind spots at Joyous was, well, a little bit of. I think everyone does this. Just the assumption that if we put this thing out there, which we did now more than five years ago, that the product would speak for itself and that if we just delivered a better product like adoption would just magically come along and follow us. And it didn't. Also we did something pretty strange for a SAS company or a tech company. We targeted the world's largest organizations as the first thing we wanted to do. So we did not invest in product led growth. We did not try to go to small to medium enterprise and then stretch up to enterprise. We went straight to enterprise. One of our first clients is one of the largest organizations in the world. I'm not sure if that was necessarily the best way to go. I mean we didn't invest at all at product led growth. I mean I'm kind of really happy we followed that lead now and that's caused us to arrive at this honestly insanely killer product we have today. But in retrospect, probably making it more generally accessible a lot sooner would have been possibly a way to go about this a bit faster. But that is what we're doing now. I think the other honestly 101 mistake that we made is we didn't want to associate or compare ourselves to anything else. But even in the chat I've had with you, it's much clearer now that we are comparing ourselves to survey. And that was such a mistake because people just couldn't understand like what are, wait, what are we trying to replace with you? Oh, we're like nothing else you've ever seen doing things no one's done before. And they're like, well, how do we budget for that? So listen, learned on that front, I think you asked what's my vision? Is that right for the next generation systems? Yeah, yeah, let me think about that. Well, I think that what excites me and I think that that's kind of closely aligned with the vision for Joris. And certainly stuff I think about all the time is real impact at scale. So seeing whole large enterprises adopt sort of conversational, actionable feedback, particularly from frontline staff, that leads to real improvements not just in efficiency and bottom line, but in morale and safety. And not just about nice to have. I mean like our goal and what we're already doing is delivering tens or hundreds of millions of savings annually for some of our customers. And kind of saying goodbye to that old school mindset around feedback and surveys. Like forget measurement, it's a waste of time measuring scores. And I guess kind of really rolled into that for me in terms of like the future of feedback is democratization of voice. Like technology can now give voice to people who just Historically haven't had it. And I mean like we are really, really passionate. Joyous is built for field workers, for people out in the fields doing the hard work every day. Like I'm talking about the people out in the trucks doing work in people's houses, doing workout and infrastructure. I'm talking about the doctors and the nurses and the other people really, really out in the front lines. It's the people, in my opinion and in the opinion of everyone at Joyce and all of our great customers, that it's the people out in the front who do the work every single day, who know what it will take and they have that information right in front of them on how to make this business succeed. And I'm just really excited about our advances with AI making not only their voice get raised up but that information accessible to the leaders who's intimidating job it is to make that decision now having like all of this data behind them to ensure that they can leverage these real time feedback loops to just really give themselves a huge advantage. And when you think about it in the context of things, for example healthcare or airlines or whatever industry where you typically have huge workforces, they can actually more successfully deliver those services which can, we're talking saving lives here kind of impact, which is incredible. Yeah. And I mean I think it is kind of happening like certainly like things have shifted for us significantly particularly I'd say in the last 12 months. I think people have been attuned to like this sort of shift is a real thing and it's not hype. And then feedback is actually a really great application of AI to ensure more momentum in an industry and give these people a voice. So I see it in the investment, I see it in the adoption of our product. I see like so many people tossing out those more legacy systems for us almost like with urgency. So I'm not sure how far away this future is and I think it's great.

B (16:45)

That's awesome. I really appreciate that and just highlight a few things. You talked about some of the mistakes you learned, you obviously talked about that. But looking ahead, the real impact at scale and again I'm just paraphrasing but the actionable insights on the front line, millions of savings across enterprises. And of course the thing that I really highlighted and took away is that importance with democratization of voice, people being able to be heard to make those improvements across the customer spectrum I think was probably the most important takeaway that I took there and I really appreciate that. Ruby, it was such a pleasure having you on today and I look forward to speaking with you real soon.

A (17:22)

I really enjoyed the conversation. Those were very good questions and I have loved meeting you. So thank you so much and goodbye from the future.

B (17:30)

Absolutely. Bye for now.