Speaker 1: 0:03

And we always tell our engineers to whatever you're building this week might not exist anymore in two weeks. So we really can't be married to anything, because I think something that people do wrong not just as early stage founders but also in product management is that we get really married to a solution.

Speaker 2: 0:20

Once again, welcome to the Digital Customer Experience podcast with me, Alex Turkovich. So glad you could join us here today and every week as we explore how digital can help enhance the customer and employee experience. My goal is to share what my guests and I have learned over the years so that you can get the insights that you need to get in touch or sign up for the weekly companion newsletter that has additional articles and resources in it. Go to digitalcustomersuccesscom. For now, let's get started. Greetings and welcome back to the Digital CX Podcast.

Speaker 2: 0:57

This is episode 72. I'm Alex Tergovich. So great to have you back this week and every week as we talk about all things digital in CX, I have a phenomenal guest lined up for you today in Larissa Laika, who is CEO and co-founder of Join J-O-Y-N. Now, a lot of what we talk about in digital is the cross collaboration between departments, departments, and one of the sticking points that we all encounter a lot is that collaboration point between product and engineering or R&D and customer facing teams, and that is precisely what Join is there to do to try to draw those a little bit closer together, keep customer facing teams informed and keep the information flowing. It's super cool stuff and actually, since we recorded our episode, join got a seed round from CS Angels, which we all know and love. So massive congrats to the Join team and I really hope you enjoyed this conversation with Larissa, because I sure did.

Speaker 2: 2:07

Larissa, I want to welcome you to the podcast I've been looking forward to this one and, yeah, welcome to the show. It's good to have you.

Speaker 1: 2:12

I'm very excited to be here and thank you for having me.

Speaker 2: 2:15

Yeah, of course, of course, I don't actually totally remember how we got connected, but as soon as we did and we had, like you know, an initial meeting, I was like oh, you're doing cool stuff, we need to talk, we need to have you on the show, we need to share what you're doing, because it's super cool, um, but also you have a like this fascinating background. Um, and you know we're going to obviously start with the obligatory background question, but tell me about your career as a tattoo artist.

Speaker 1: 2:51

Yeah, I mean, it really started with me Like after school. I was just hanging out in this tattoo studio just like drawing, and eventually they were like you want to like do this, I guess. And I grew up in a pretty like conservative, like defined environment in Germany where your life's pretty much set on a certain path and I was always like that ain't me, but I also didn't really know. It wasn't really any other options. Right when I grew up was like oh, you can be a computer scientist, can run an AI company, like that was not a thing where I grew up.

Speaker 1: 3:29

So for some reason, this like opportunity to tattoo and with that really like do art as a job and the ability to really do it from anywhere was like very appealing and it was also kind of showing my extended family that you can be a rebel and be successful. So that's kind of what brought me to tattooing. And then it brought me like around the globe. I was in Japan, I was in all over the US, germany, so it was like definitely an interesting, interesting experience, challenging in its own ways, but interesting to do, especially as young as I was.

Speaker 2: 4:04

So yeah, it was. It was an escape and it was a vehicle for you to get out.

Speaker 1: 4:10

Basically, right, yes, yeah, and then it very abruptly ended and I had to redefine my path. And now I'm in tech. So there you go.

Speaker 2: 4:18

I mean, would it be safe to say that you wouldn't be in tech if it weren't for tattooing?

Speaker 1: 4:25

Honestly probably not, and there was, like obviously, other things also in my life that kind of led me to where I am now.

Speaker 1: 4:34

But I do think, kind of taking that detour, and then also what happened to me that I had to like kind of figure out something else. Like that combination, I think, ultimately led me to tech and sort of accepting the inner nerd in me that I think I was fighting all along. Since I was like a teenager and a kid I was always like really rebellious in that sense. So then I realized I really like mathy stuff and economics and data science is kind of cool. So I definitely think it was an important step to actually get me to where I am now you started listening to yourself a little bit more yes, exactly, rather than listening to what people told me I was or should be or will be.

Speaker 1: 5:14

I was like nah, I I'm me, I can do my thing and pave my own.

Speaker 2: 5:18

I've got my own path, yeah, yeah there you go yeah, that's cool, um, and then I I saw I mean I think the most extended kind of thing that that you've had in your past in terms of role.

Speaker 1: 5:29

I mean you were, you were at next role for like eight years, something like that, and ascended through that organization, right yeah, yeah, and it's even funny next role actually initially rejected me for it was also like an entry-level role and I later on asked the recruiter why I was rejected and she was like you were overqualified. And I was like I truly wasn't. So I don't know, I don't know why you're saying that, but I think it was like a month or so after I was like oh, this is other position and it was like the first international sales development representative. Basically, I've never done sales.

Speaker 1: 6:06

I was in customer support before that and then operations and then it was like okay, I guess I'm doing this SDR thing. But I was only in the SDR role for, I think, three or four months, but I hit my quota, exceeded my quota, I started getting involved with how we're doing lead scoring and just got really, really intense about it, and I had a really great manager that advocated for me to move me into account management. As soon as I moved into account management, they restructured the compensation and fired all this, like all the sales people left or were fired oh my gosh, I was suddenly am and sales.

Speaker 1: 6:39

But in a way it was the best thing because we ended the customer like we owned it. End to end right, it was like.

Speaker 1: 6:44

I was the one bringing in the deal and then managing the deal, so we had really strong relationships which led to all this revenue growth et cetera.

Speaker 1: 6:52

And then we had this new team which was our competitive intelligence team, which was really all about retaining our most important customers.

Speaker 1: 7:01

And that then got me to really mess around with product and start working with the product team and I was doing these janky reports and A-B tests to kind of prove the value of what we're doing for customers and start taking out competitors left and right and like really growing our retention, which then the company was like how about we just move into product and just build the thing? And that's then what my started my career in product management. I was like a small and mighty team in AI machine learning. I turned into a business unit. So I got to run the business unit where actually my now co-founder oversaw product. And then in my last role I was the chief of staff for product design and engineering and my job really was being the connective tissue between our engineering, product teams and customer facing teams. So held many roles at NextRoll and was given a lot of opportunities and it was definitely an exciting journey, also seeing the company through the growth and trajectory.

Speaker 2: 7:57

So yeah, Right, that's a fascinating journey and one you don't hear very often. Just that kind of shift between different things, I mean I think that one it's cool that they're to just like oh, she can go handle that. Like she's got that, she's a problem solver Like go.

Speaker 1: 8:31

Yeah, and I will say I've never applied for any of the roles I've held at NextRule.

Speaker 1: 8:36

It was always somebody being like I think you should do this, and I was like me what are you talking about? Like makes no sense, which was kind of like I just I had a lot of people that saw potential in me that I didn't intuitively see, and I, coming from Germany too, we have a very hierarchical structure and organizations and how you can move up the ladder, so to me this was like mind blowing. But yeah, I think in the end, the way the company deployed me was this is the most broken thing we know who to put on it, and that's where I then got like deployed to. So that's kind of been my journey and again, it was great because it just gave me so much exposure. I worked in nearly every department, I worked with every department, so it was like the best way to prep me for what I'm doing now is like running my own company. So I'm definitely very grateful to have been there for like eight years, which still seems crazy, Like when I joined I was in my early 20s.

Speaker 2: 9:37

Yeah, well, and those experiences you know it's a variety of experiences, so you got to see how different organizations work and how they work with each other and what the interplay is, and all those kinds of things, which is crazy, crazy valuable.

Speaker 1: 9:50

Yeah, it definitely was. I definitely learned. Learned a lot personally, but also again about departments and also the.

Speaker 1: 9:57

I would say evolution that you go through as a company as you grow, as the things that matter as a company evolve because of you know it's very different like being an early stage startup to prepping for ipo, to being an ipo company, right. Like it evolves so much and with that the way we work together has to evolve as well, and I think that's not always easy for companies to like manage that transition. It's a tough one.

Speaker 2: 10:26

Yeah, I mean. One of my mentors always said you know, go get your MBA if you want to, but go join a startup Like you learn just as much. And it's like practical application, is like real world stuff, it's like boot camp basically.

Speaker 1: 10:47

It is, and I will say say, though, it's definitely not for everyone. I think we always glamorize like startups, but once you're actually in it, you're like whoa, because like the urgency and the pressure, especially of it being your own thing, is like very different, and I always had a lot of urgency and pressure and like high expectations and in any role, but like being in a startup where you know, I know we always are strapped on resources and all these things no matter where we work, but I think, in a startup, the it's all survival, it's like can we just like make it?

Speaker 1: 11:16

and that's truly like the first five years of a startup, but it'll definitely very rapidly teach you a lot of things and, I think, help you identify. Is this actually for me or is this not for me? Because, yeah, it's definitely challenging. I mean, I wouldn't want to do anything else, which I don't know what's wrong with me. I love, though, what we're doing, irrespective of like how hard it is, so yeah.

Speaker 2: 11:39

The entrepreneurial spirit. Well, you know, talk to me a little bit about that. So now you're, you know, co-founder and CEO of Join J-O-Y-N, and what's been your journey into that, Like what led you to, you know, to start that have kind of led me to join, and also I've met my co-founder, kendra, at my prior company, like 10 years ago this year.

Speaker 1: 12:08

So we've been really fortunate to have worked together for a long time and we really always share, you know what we think about culture, how we want to build teams. We really love solving problems where people tell you this can't be solved, especially when they create really meaningful value for the customer, like in a context. Nextro is an ads company, right? So Ken and I were there, like how do we find meaning in ads? You know, just the ads that follow you around the internet? That's what we were doing as a company, so we really focused on you know, in the machine learning business you know it was all about black and white ways Are ads actually doing anything for you?

Speaker 1: 12:44

And it's really a statistical way of measurement, which was a big risk to the business because it actually could tell our customers, no, they're not and honestly, in most cases no, they're not and you waste most of your budget. But for us it was like a way to create really meaningful value for the end customer in the context of advertising, context of advertising, and we had the stickiest contracts, largest contracts, and I think that was like really great to see. So I think that's what always connected us. But then when I was in the chief of staff role and kind of having seen the transition of the company to of you know, now we have all these software tools and everyone has their own ways of working and none of them effectively talk to each other, and again also seeing like our priorities change and having all these departments with their focus areas, I was just like work has just become really hard.

Speaker 1: 13:33

We're spending a lot of time on things now like status meetings or chasing down information and the rift between especially customer facing teams and product teams is pretty steep in a lot of organizations and you have the customer-facing teams that obviously need to know what's happening, what is being released, is this bug being fixed on what's product actually prioritizing. But the larger you grow, the more of a black hole it becomes. And then product engineering is frustrated because they constantly have to report out to these other teams. But what are you going to do? You need to collaborate.

Speaker 1: 14:05

But I think that friction was so hard to manage at my previous company as a chief of staff and, as we just looked outside of, like our own experience, my co-founder also her background's in products, so she kind of lived this too. But like wow, this has just become a general problem and I think it actually takes so much time away from the thing that's the most important, which is the customer and building for the customer and creating value. So that's really what led us to join and really focusing on this like how can we streamline this collaboration between, especially, product engineering and customer facing teams like CS, sales and marketing, so we can actually connect the dots strategically and focus on the right things without all this overhead of reporting out or chasing people down to get information? So that's kind of a long story that led us to what we're doing with Join Now.

Speaker 2: 14:54

I mean, it's classic entrepreneurship 101. See, problem solve problem, problem solve problem, like you know, and and and, but but also, like um, everybody talks about sales to post sales, handoff, like that's like the classic, like we have a problem with this, but I I love what you guys are focused in on, which is that you know that rnd to customer team relationship that I you know, doesn't get addressed that often, like it's a problem everywhere, right, and people try to solve it with, like Jira, integrations and things like that, but it's like there's a granularity there and there's still a level of effort that you guys are focused on and trying to remove, which I think is super cool.

Speaker 1: 15:43

Yeah, and I think the side effect of like just having and I've literally tried everything in my previous company like Asana Monday Zapier, like Notion, all of the things it was like, oh my God. But in the end what I ended up hiring was what we like to call more glue people, which was our product operations team, because they would act as this translation. There their job was really understanding Because they would act as this translation there.

Speaker 1: 16:03

Their job was really understanding. Here's our priorities on the business side. Here's what product and engineering is doing. How can I bring these two together? But the problem, even with having glue people, is that a lot of these things aren't rooted in data, right? So then, yes, product operations can flag and be like hey, we have an issue here. Every time we hand something over to marketing, they get stuck for six weeks because the way product writes it and their product brief doesn't meet their criteria.

Speaker 1: 16:27

And then you have to back and forth, but because it wasn't rooted in data, you then have, like me, the chief of staff or whomever, go to the respective executives and flag this, but then the actual accountability to change anything. That's like the thing where usually things fall through and then the only way to keep mitigating it is just like hiring more glue people or just sticking with the status quo Right and we talked to a lot of people that are.

Speaker 1: 16:50

These people, whether it's product marketing or head of biz ops or CS, sometimes Right Like we see this actually in a lot of organizations where CS are these glue people they often hear the worst part of my job is understanding product progress. We hear this so consistently. I was like this is not how it should be, because those are customer facing teams and then product and engineering are the most expensive functions that work on some of the most important things, but if they're disjointed the harm to the business is really, really outsized. Right, it's really bad.

Speaker 2: 17:26

The distraction of all of that is so massive, you know, because, I mean, one of the things that I talk about quite often with digital CS is the fact that, you know, the technology that we implement is not necessarily meant to replace a CSM. It's meant to augment them so that they can focus on what they're there to do, which is to provide value and to drive outcomes, and things like that. And I would say the same thing for product and engineering. I don't want my product managers to be constantly on the hook for updates or you know, or, or to have to build a CS ops. I'd rather focus my resources on people who are building stuff and focused on actually implementing that stuff, rather than like closing off on tickets and doing all those kinds of things Right. So so it's, it's a cool kind of use of technology to again, you know, focus your resources on what's important.

Speaker 1: 18:26

Yeah, and I think the thing that was interesting for us too to sort of observe is that I think for, like, leadership that is further up, and I actually live this too, because I was talking to my prior CTO and I was owning OPR planning, which I think any person that ever owned OPR planning can tell you it's the worst thing.

Speaker 2: 18:46

For the listener. Tell us what you mean by that.

Speaker 1: 18:50

For OPR planning basically right goal planning. Usually you do it annually or quarterly basically right goal planning. Usually do it annually or quarterly. You said company level goals and align key results to it and usually you have it on the company and then each department has their respective goals and our company did this annually and then quarterly yep and my cto was like man okr planning at next role.

Speaker 1: 19:12

It was like so smooth at my company, now it's a mess. And I was thinking to myself man like you literally don't know that I probably had a hundred meetings. I probably sent a thousand Slack messages. I had so many one-on-ones. I was like in Jira, I was in Asana, I was in a hundred spreadsheets and it was like taking up half of each quarter for us to revisit our OPRs, et cetera.

Speaker 1: 19:37

But again, for my job was for the executive to make it seem like everything was going smoothly and he would always had the information he needed. Right To know, yes, things are on track, they're not on track, et cetera. Like he got exactly that. But the reality is that most other people in organization don't have that like for them to get the information to do their job or, you know, prioritize properly. They're the ones that have to lurk in like 80 slack channels or try to decrypt jira, which is like jira is just like so hard because there's so much movement.

Speaker 1: 20:09

So even we're talking to a product manager works at a very large company that has built out all this internal tooling to help them with collaboration and I asked her how much time do you spend in syncs and subsyncs to know where everyone else is at or keep them updated? And she was like 80% of my time and that does not include one-on-ones, so most of my strategic work I do after work. And we talked to someone that manages CS today and he said his CS team spends at least 20 hours per person every week just going through engineering tickets and like figuring out what is actually going on.

Speaker 1: 20:45

I was like I think executives often don't fully understand the scale and amount of time you spend on it, because there are people that make it seem really smooth for them, but the people that actually sit in those roles get so little time to spend time on the things that actually create value and brings them joy in their job. And I'm like that balance we just have to restore, not only to drive business outcomes, but also like have employees that are like yeah, I'm doing something important here, like it, it matters, and I know why it matters. Right, and I think we've lost it a little bit in the past.

Speaker 2: 21:20

I think also the knock on to that too is, as an executive, a lot of times you may not understand the downstream implications of one of your asks, like you don't understand how many man hours or people hours went into you asking a two sentence question. You know, and and I think that's you know it's, it's all interrelated and so and so. Then all of a sudden you become the person that's keeping your teams from doing the things that they're there to do and they're there to love, and they're starting to hate their lives just because they're weeding through tickets.

Speaker 1: 22:00

Yeah, and I think the buffer people right, like we were talking with someone. He is a director of engineering, also at a large company, and we always ask people what's your most dreaded slack ping? And he was joking my manager, which was like the key of engineering, because usually that means well, something is on fire, something needs to be reprioritized, and he's the one that has to like handle the aftermath right of the team on. Hey, we're not doing this anymore, we're now doing this. And for me too and not everyone has this right like for my cto prior, like he was like a very intimidating person. He's one of the smartest people I've ever met in my entire life. Like I don't understand how his brain can work the way it does, but he also is like very sometimes like impulsive and impatient and that's like cultural things in this, and he doesn't understand that his title weighs a lot.

Speaker 1: 22:57

like yes bto weighs a lot.

Speaker 1: 23:00

So I had an eight year long relationship with him so I knew how to like decrypt what he's actually saying and ran him in and, you know, kind of push back on him and that was like then my job, right, I was the buffer between teams, because if he comes in and it's like, no, we're doing this now, everyone's like, oh my God, we're doing this now because Valentino says this and I was like no, no, no, like let's hold on.

Speaker 1: 23:24

But I think that's also the other thing that, yes, I executives and I think executives are aware of this too the higher up you move, the less context you have, the harder it is for you to make strategic decisions. But it is your job. But then you also don't have insight into all the things your teams are already juggling. So you think, oh, one more ask what is it going to do? And I think, especially in our recent conversations for discovery, for joint executive driven decision making that is uninformed, has been the number one problem statement that really derails teams significantly. So, 100% to what you just said and something to be aware of. In an executive leadership position it just weighs differently.

Speaker 2: 24:06

It really does, and I feel like, though, in an age of really solid generative AI summary capabilities, I feel like my hope is that we're exiting out of this land where an executive question necessitates the use of 50 spreadsheets. You know, it's like train it on the data.

Speaker 1: 24:31

They can ask the question themselves and get the you know, get the actual insights that they need, versus, like this again, this watered down, filtered kind of kind of message that happens quite a bit, unfortunately yeah, and I think that's our hope too in terms of what we're trying to do with join right, root things more in in actual data to keep people informed, but with that also like really empower, understanding, accountability, decision making.

Speaker 1: 25:00

So it's definitely like our intention because I think right now a lot of what we're doing with it's like again these like cumbersome status updates people have to put together and like spreadsheets or in a written way they primarily solve for the fact that somebody doesn't have context because they can't have their hands on everything, and I a hundred percent understand that right, if you're the CEO of a 800 person company like it's impossible for you to keep tabs on everything. So this is like kind of like a, a means to an end, an end to a means, means to an end in terms of right, getting what you need from from a visibility perspective. Again, just the overhead is not well understood. But the benefit now of a lot of our communication happening in tools and progress happening in tools is that there is now a way to have a system that connects all the context and information, understands people, priorities and like can give them the information they need to do their job or make decisions or reprioritize, and that's like the beauty of like you know, how we can now use data and then also how we can use ai to really cater it to each individual at the organization and bridge that gap. So I'm definitely very excited about that, so, yeah, yeah, that's so cool.

Speaker 2: 26:19

Hey, I want to have a brief chat with you about the show. Did you know that roughly 60% of listeners aren't actually subscribed to the show, on whatever platform they're listening to it on Now? As you know, algorithms love, likes, follows, subscribes, comments, all of that kind of stuff. So if you get value out of the content, you listen regularly and you want to help others to discover the content as well, please go ahead and follow the show, leave a comment, leave a review. Anything that you want to do there really helps us to grow organically as a show. And while you're at it, go sign up for the companion newsletter that goes out every week at digitalcustomersuccesscom. Now back to the show, and while you're at it, go sign up for the companion newsletter that goes out every week at digitalcustomersuccesscom.

Speaker 2: 26:59

Now back to the show. So cool, you know quick shift and right turn into that a little bit Because, like you know, you're early stage. I think you know you've got a few customers that are on board and you know starting to, you know starting to work with the solution and whatnot. And I'm curious, I guess the context of like early stage and that evolution of customer facing motions throughout, like early stage startups, where are you guys in that journey? Like, have you, have you brought on folks yet to to really handle those kinds of things? Are you still the one you know engaged with your customer every single day? And then you know, as a connecting point, like, how are you thinking about things digitally from a customer support perspective?

Speaker 1: 27:49

I suppose yeah, yeah, and we're just now at a place where we're kind of like opening up the floodgates more to have more people be able to use Join, but it's definitely all founder-led sales right now and it's a combination of you know, we're doing LinkedIn outreach, battling LinkedIn Sales Navigator, which. Why is it so bad?

Speaker 1: 28:14

I'm like, I mean I understand For how expensive it is, so bad I'm like I I mean how expensive, it is, so bad, and it I mean I get it linkedin. Only linkedin has the data, so they kind of have to do their minimum because it's the only way for you to access data. But I'm I'm like I can't believe it. And then you know, we work obviously a lot with operators and engineers. They live in a lot of like communities, so that's been a big thing for us to figure out, alongside things like content strategy, which I'm not gonna lie like, we have one of our investors and she is very adamant on like you have to post on linkedin at least once a week. She had either once or twice a week and I just I it's just I don't know. I did the thought leadership thing. I'm just like it's just not my energy, but we've been starting to do that as well. So there's like a few things now that we're kind of figuring out and now go to market.

Speaker 1: 29:02

We're looking into some other tools as well to help us streamline things, because initially it was like a smaller scale, right, because we needed very little customers. Now it's more like how are the ways that we can have more repeatable motions? But in terms of the people that we're already working with. Kendra is extremely my co-founder extremely hands-on with them because they're very like, still early beta customers, right. So we're working with these really early advocates that are giving us feedback and they know the product's still not 100 there. So she built really strong relationships through calls and, like you know, also bringing other people in the organization on board and just, yeah, so we're still at this place.

Speaker 1: 29:44

I think we'll be there for a while longer because, like, we're really only looking to bring on like another 10 customers like in the quarter. So you know, we're not at this like crazy scale yet where it's not manageable to us, and I think for us now, having these really close relationships with the early advocates is exactly what we need to then figure out. Okay, now we have the product, we understand the ri, we have the message, we have the sales motions. Now how do we support them at more scale? Right, right now it's all product, it's all how we're creating value through the product and how we're helping them tell the story of join to other teams that they're working with. So that's kind of been our biggest focus right now. Still a lot to do.

Speaker 2: 30:28

Yeah, of course, of course, it's a marathon not a sprint, it definitely is yeah, what has your? Have there been any kind of unexpected things that have happened or any kind of, you know, challenges that you've encountered, customer facing wise, where you were like should have done that differently or, like you know, like any light bulb moments?

Speaker 1: 30:56

You know, like any light bulb moments. Yeah, I think our biggest misstep because I don't want to call it a mistake, because everything's learning- you learn from everything.

Speaker 1: 31:05

Because you literally don't know anything. I think initially, we were like oh, let's go like very focused, like a specific use case, work really tightly with a narrow group of people, and that was like an easy way for us to get into the organization, because it's like oh, you have like maybe two stakeholders, sometimes three. Problem, though, is if it's a very narrow use case and we're saying we're like reducing the noise across like product progress, so like the teams informed, our value creation just wasn't as extensive as we wanted it to be right.

Speaker 1: 31:39

Because, the more data we kind of like skim through and like give context and contextualize in a personalized way, the more value we're actually creating. So what we instead realized is like no, no, no, like let's not go super narrow. Our approach really should be give us as much data as possible and then we'll contextualize it and really write, skim it down to what you actually need to know, depending in the role that you're in. So now that we were onboard people, it's not like just add us to this one Slack channel and this one Jira board. Now it's like, add us to all Jira boards, add us to all the Slack channels where, you know, product development conversations happen, and like now we're able to create a lot of like value because we have access to more data that we're contextualizing.

Speaker 1: 32:25

So I think we initially went like let's go as narrow as possible, and that didn't really make sense. We're still narrow with, like the use case, but we're not narrow with the data and in terms of like what we're taking the noise out of. So I think there was like a big learning for us and where we had to just shift our strategy and did that pretty rapidly because it was unfortunately the people we worked with when we asked them to expand. You know usage and the data we have access to, like they weren't bored with it.

Speaker 1: 32:53

So fortunately, we were able to then scale it and create the value that is, the value of join. But that was a big learning for us.

Speaker 2: 33:02

Yeah, I can imagine and yeah, I guess the beauty of it is you can pivot quickly when you're you know when you're that size and everything. I think everything you do is like a building block that informs how you do it the next time.

Speaker 1: 33:18

right, 100%, and we always tell our engineers too whatever you're building this week might not exist anymore in two weeks.

Speaker 1: 33:25

So we really can't be married to anything, because I think something that people do wrong not just as early stage founders, but also in product management is that we get really married to a solution and we're like, no, this is 100% problem, this is the solution to it that we actually start losing sight of.

Speaker 1: 33:42

Well is it, though? Because, honestly, you should constantly validate? Is this just a narrative you're telling yourself because you've lived it right? Like even when we're doing discovery, like we're trying to like not ask leading questions as much as possible to kind of confirm our own biases, but if you get too married to, you notice is this is how it has to look, like you might miss really important signals that actually lead you to the right direction, and like how joy looked like in the beginning is so different to what it looks like now, and I think it speaks to especially kendra and her ability to really have a pulse and see through what people are saying, because we also get a lot of people that are like super excited, but then it's like are you actually gonna pay for it, though?

Speaker 1: 34:26

and it's like no, okay, whatever. So, like, I think she's been really good to like read signals properly, but then also adapt really quickly and not be married to anything we're building or attached to it, because again, again, it can be like completely, we build a whole dashboard, and our biggest value add is that nobody has to go to the dashboard because we're pushing everything into the tools that they're already using. Right, so there you go.

Speaker 2: 34:54

There's a couple of things you just said that are are are really fascinating, I mean. I think the first the first one, I think, is a lesson for just about everything in life is like don't be afraid to like, pivot hard and just throw stuff away if it doesn't work. You know like build stuff, learn from it. If it works, great, if it doesn't work, pivot, throw it away, do it again, do it differently, you know, and learn from their mistakes. I think that's huge.

Speaker 2: 35:19

But then that last bit that you just talked about is really top of mind for me, which is like getting the info and the data into the place where your customer is, and that, I think, is something that a lot of, especially more mature, larger organizations overlook. They're like oh, we're just going to send this email, or we're just going to do it in our community or whatever, and well, guess what? Half your users aren't in the community and your executives don't really read email. So what's your take on that Like reaching the customer where they are? Is that something that's top of mind for you?

Speaker 1: 36:00

Yeah, and I mean for me too, and how I'm thinking about this with our customer base. Right Like, when I was the chief of staff, I had this internal knowledge. I was like, okay, this person needs Y, this person needs this, this person I need to remind X amount of time. Right Like I had all this like web of, oh, here's how I get to this person in the most effective way to get what I need.

Speaker 1: 36:23

And the reality is that, yeah, now you know, with engineering teams, they live in slack and they live in jira, then a lot of marketing teams live in asana and then you have cs that lives in zendesk and, yes, we have this connection between tools, but they're still not really like effectively speaking to each other in a way that you immediately have the context you need on something.

Speaker 1: 36:43

Right like, even when we talked to this person in cs, like he was saying his one of the cs people, they basically give like status reports on tickets customers submitted on their like high value customers, and he showed us the status report and it was like 20 tickets she was giving really granular updates on.

Speaker 1: 37:01

But the way she had to do is like slack people, you know, look into jira, go into zendesk and it was just like insane so for her to spend this amount of time to get the context she needs to send to the customers a really highly important customer and I think that was our realization. For us, too, it's like I truly believe and I know larger companies hate this but people have their ways of working in a specific tool stack and communication that works for them, and I really don't think that there will be tools that rule them all. And, like you know, companies have tried to move all teams to operate in Asana, or they've tried to move them to Notion, but it just doesn't work and I think we kind of have to make peace with that. But this is again where AI gets really exciting to kind of be this horizontal layer right that can take information from everything and then meet people in their ways of working where they already are.

Speaker 2: 37:53

So I think that's been a big thing for us, the aggregator of things, which is huge. One of the tools I've started using instead of Google a lot recently is perplexity Cause I mean it's they kind of call it an answer engine. You know, when you search Google or whatever, you get like links to stuff and you still have to go click into each link and you know they try to summarize stuff but it doesn't really work too well. Perplexity is like it. Like you ask it a question, it'll give you a nice Gen AI summary and it actually, you know it cites sources and you can go there if you want to, but it's like a no-brainer. And I see more of that kind of stuff in BI. And replacing like business intelligence tools really, where you just feed it a bunch of stuff and it'll summarize it for you, and replacing business intelligence tools, really, where you just feed it a bunch of stuff and it'll summarize it for you and those executives can ask those questions without needing to bug somebody else for it.

Speaker 1: 38:50

Yes, 100%, and for me too. I was actually just thinking about this recently around. What do we even still use Google Search for? And it's usually just a restaurant or something Just like a habit. Yeah, because now we go to Per perplexity or claude or or gemini. But google is obviously trying to combat it, because now when you do google search you have the gemini that like gives you the answer on top and you can text gemini now.

Speaker 1: 39:14

But I agree, it's like it's really interesting to see how things will be reshaped. Obviously, the data thing is, I think, the thing we talk the least about in AI. I think people have this perception of just magically feed data into AI and all your problems are solved. But there is so much data and like so much noise. So actually understanding the data and understanding what data actually matters before it even goes into an LLM is really critical, because otherwise you just get really bad outputs, and that's the thing. That's a learning for us too. It's like people that come on board with us now to kind of trust us to create that kind of value for them.

Speaker 1: 39:49

Right, I get this personalized summaries, like know what you need to know, but if we're like three times sending a summary, that's like super irrelevant or just like too high level or too detailed. It's like such a fine balance of what does value actually look like and what is the information you need, and that's like for us our job to actually understand this and think about it in terms of our data infrastructure and the knowledge graph that we're building, because it's not this magical thing, but it can be right. Like the responsibility is really on the companies in terms of like what data and signals are they looking at? And obviously, like security and like ethical approaches to AI are really critical and we just saw this with Google the integration with Reddit that just went really not that great there's a lot of things at Google that haven't really gone too great, like the whole.

Speaker 2: 40:38

You know premature launch of their agent chatbot, you know virtual assistant kind of thing that wasn't real at all, that they admitted to later. It's like okay, and then open ai swoops in. They're like yeah, you can talk to our stuff and you actually can I mean right now.

Speaker 1: 40:55

The ai race, especially with the big players, is like pretty crazy right like looking at, like elon musk's company, which he's my enemy, he doesn't know me, but like, looking at like elon musk's company, which he's my enemy. He doesn't know me, but just so you know elon musk's my enemy. But then also I get open ai gemini. Right, they're all racing. Yeah, to be that. But to me again, I'm the firm believer of like ai will be a commodity, will all be aiabled, companies and individuals. It'll be probably bigger than the internet was for society. But I agree, these very large players that will be very critical. There's responsibility that they have in terms of, yes, this is a race, but also we have to be thoughtful of how we're winning this race, because AI is a little scary if we're not taking into consideration these ethical concerns just because of how we're winning this race. Because AI is a little scary if we're not taking into consideration these ethical concerns just because of how AI works. Right, it's informed by humans.

Speaker 1: 41:48

So, the people building AI have to be really conscious of it, and there needs to be regulation. I'm a firm believer that AI, ultimately, will have more benefits than risks, but I think the race right now makes people cut corners that we shouldn't go back and unwind and yeah, we'll, we'll see, but yeah yeah, it's, it's a little dangerous.

Speaker 2: 42:12

It'll be interesting to see and and it'll it'll also be interesting to see, like how it, how it becomes more and more of a of a part of our daily lives. Because I mean, right now at least, I feel like I am at least you know, I've been really going deep on AI and unfortunately, what that means for me is I think I'm probably quintuple paying for OpenAI right now, like I've got it here and I've got it there and I've got it there through integrations, and then I pay OpenAI some money too to use their premium version, and I don't know how much longer that's going to fly At some point in the future. Do we take our AI with us? Do I take our GPT with us? Is it mobile? You plug it into different places, I don't know. It's just going to be interesting how the credit of all that works. Yeah.

Speaker 1: 43:06

I mean, I know Notion AI is great, but I'm like I'm not paying for this. That's crazy, it's too expensive, and I generally think it's not because it doesn't create value, but it's because I can also get that value by maybe copy pasting something into Gemini and have it do the same thing, and I'd rather do that because I'm a founder that doesn't have a lot of money. So you know, I got to choose my battles. But to me it's also like and I this is with anything right Like even NextRoll, like we've been using AI machine learning forever. Like, like we've been using AI machine learning forever. Like since we started, that was like integral of, like our product offering, because that's how ads work, that's how personalization works, that's how it knows and do this kind of ad or what image to show you, right, like that's all machine learning. But did customers care? Were they like? What machine learning model are you using? No, what they were paying for is like the ads and the return of the ads. Right, and I think that's also how AI will shift.

Speaker 1: 44:03

I know now every company just charges for this additional AI feature, but in the future it's like no, you're not creating value unless you have this AI feature and it should be free and embedded into the tool. That's like my belief. I don't. I don't call join an AI company into the tool. That's like my belief. I don't. I don't call join an AI company. We use AI as a tool to help us achieve an outcome for our customers and create value, but do they care, like they care that we're using the data in a secure way and where the larger companies are like there is a closed loop, like those things? Yes, they care about, but ultimately, why they will keep working with us is because they'll get value out of it. So I'm definitely interested to see how that will shift in terms of how we, as consumers of AI, will pay for it or not, and like how you know it being more embedded as like the core value prop and how we're able to generate value.

Speaker 1: 45:00

It will just be in like the core offering of the product and like maybe, yeah, your whatever monthly pricing goes up a little bit, but am I going to pay like 40 for notion ai? I actually don't even know how much it is. I'm like, unfortunately not.

Speaker 2: 45:12

I'm also, again, like you know, at some point it has to become a cost of doing business. You know you don't go buy a car without wheels on it, that kind of thing, you know. Look, as we start to kind of wind down the convo, I would love to understand a little bit more about you know what's in your content diet and what you're paying attention to to keep yourself up to speed with things. And or are you, or you know, or a lot of people recently have actually just said I just talk with people and have connections and things like that. So I'm curious as to what that looks like for you.

Speaker 1: 45:48

Yeah, I definitely have hard lines of content I digest just for myself, which is more true crime, podcasts, stuff you should know is where to go. But for like a work perspective perspective, definitely talking to people is a big thing, but I also just follow people on linkedin that are especially in like ethical ai or just generally in like the ai space or customer success or you know, there's like individuals I follow.

Speaker 1: 46:15

I also really like lenny's newsletter, which is obviously more like product oriented, but I think he speaks to topics that are not just product management, because product is so broad, like he also brings on other roles. I also really like deb lu. She speaks a lot to like broader leadership as well in a really tactical way. So there's like a few like newsletters I I like, but I definitely follow people on like linkedin and as much as possible, try to have conversations with people I'm inspired by and talk to.

Speaker 2: 46:43

So, yeah, yeah, that's cool. Anybody you would want to shout out that's doing cool stuff digitally.

Speaker 1: 46:51

In CS or just in general.

Speaker 2: 46:52

In general.

Speaker 1: 46:54

Okay, I want to shout out. Well, I mean I will shout out Lenny, because I do think he has a really unique approach to talking about product in a way that's like not this head of product, it's the best organization ever. I think he speaks to the challenges quite a bit the real, the tea.

Speaker 1: 47:15

Yeah, and I like that Also. Emily Kramer from Market One I actually think she I honestly am often really tired of like LinkedIn influencers, but like her content is so good and so tactical and like combined with like being really funny, so I always read her posts and I always have takeaways from reading her posts. They also have a great newsletter, market One, as well, so I always love the stuff that they're they're putting out as well, yeah, that's cool I'll shout her out too, because she talks a lot about ai application and I loved her recent posts on like what model she uses for what, because I think that's like a really interesting thing.

Speaker 1: 47:56

So definitely shouting her out, because I think she she speaks to ai in a really tangible way, no matter what role you're in or what your level of knowledge of AI is. And that's where I'm going to stop.

Speaker 2: 48:08

I love that because there are a lot of people who know a lot about AI and it's obvious they know a lot about AI and that is a massive turnoff to a lot of people. And that is a massive turnoff to a lot of people. And then there's a lot of people who know a lot about AI and make it approach% of CS professionals use AI on a daily basis, which some would say is high. I would say it's like super low, and I think a big part of that is just like it's this mythical thing. I don't know where to start. I don't know what to do. I kind of asked Chad GPT to write me an article once and it sucked, so like I gave up on it, like it's this whole barrier of entry that people who know a lot about AI that can make it simple and approachable are like the valuable people right now.

Speaker 1: 49:14

Yeah, I agree, and I love that content too, even though I live it like every day.

Speaker 1: 49:19

I'm like it is really helpful to me because, like even all the language around ai is very technical. It's like, well, you have a prompt, because it's prompt engineering, it's like what you know. So I, I agree, and when people again, with any new thing, you only give it so many chances to get value out of it. But then if it's just like you know, being informed in a way that it's very applicable and tactical to your role or what you're trying to solve, like it can be really powerful, even in like the state it is in today, which is like still a very early state of of ai. Yep, I've used it for the most random things, but it took me a while to get there. Yeah, even though I've been in ai for a decade, but generative ai like still pretty new, right it's a different way of working, like pulling it into your day-to-day.

Speaker 2: 50:06

You know it takes at first. It takes very conscious effort to say okay, I'm. You know, I might ask chat gpt to proofread this email for me. Sure, why not?

Speaker 1: 50:17

and you, notice like little things, because like I'm german and like in in germany, like america's very exaggerated language, like everything's like amazing, incredible, love it, hate it. It's like always the extreme of language. So it's funny sometimes when you have gemini you like, have it. For example, prove, read a linkedin post, make anything would change and the output is like the super high train, like tech bro, and I was like no, like that's not how I talk, and then you really have to tell it you have to train it tone of the original voice and like here's the audience you just have to.

Speaker 1: 50:55

The more specific you are, the better, but yeah, when I would initially see this is like this is dumb and I'm just like I'm better at writing content and obviously you are the better, but yeah, when I would initially see this like.

Speaker 1: 51:01

This is dumb and I'm just like I'm better at writing content and obviously you are right. It's only like a tool that helps you, but you really have to tell it pretty precisely what you want it to do so it doesn't turn you into a high-tech bro from silicon valley yeah, which is not my energy no, I hope anyway.

Speaker 2: 51:19

No, it isn't at all, and that's one of the things that you know you and I have in common. Also, you know we talked about this briefly. Like I was born in Austria, but I have an American mom, which is why I sound so American. But, like, I still have problems with like phrasing of stuff and my wife will look at me sideways sometimes after I said something. She's like I don't think you meant that what you said. And it still happens like all the time. And actually I've, I've gotten, I've started really using generative AI that way to like check myself a little bit on on.

Speaker 1: 51:58

You know how I want to say things to make sure that they're clear and conveyed correctly, because I mix stuff up all the time yeah, this is again the things where it's good for, especially if you specifically tell it what to do and that it shouldn't just make stuff up even though it's been better now, because the early days it was like making a lot of stuff up. Even that to me is like again, it's hallucinating. I like this is not language we should use with people that aren't in AI. It's just like it's making stuff up. It's like inferring something from what you've said and tags it on. And I always had to tell an AI please do not infer anything.

Speaker 1: 52:34

Just stick to it, you know.

Speaker 2: 52:36

It really does.

Speaker 1: 52:37

Yeah, yeah, it's gotten better, but it still happens. So, yeah, yeah, it's gotten better, but it still happens. So, yeah, it's like specificity as much as possible until it like learns more. This is again where notion ai is kind of nice because it obviously has like enough context to understand tone of voice. So usually if notion ai would draft something, it might be more quickly spot on, while with gemini I have to do more specific, like prompting, or claude I have to do more specific, like prompting or quad.

Speaker 1: 53:02

I have to do more specific prompting so yeah, pros and cons to everything.

Speaker 2: 53:05

Still not gonna pay for it. Nope, well, look, I've. I've super enjoyed this convo. Where can people find you? Reach out to you, engage with you?

Speaker 1: 53:15

I'm definitely on, just like LinkedIn. I'm pretty responsive on on LinkedIn so, yeah, I think that's the best way to reach me. I don't have any other social media, so linkedin is the only place to find me.

Speaker 2: 53:27

Yeah, yeah, good stuff. Well, thank you again for joining. It's been enlightening and super fun and, uh, I appreciate it well, thank you for having me.

Speaker 2: 53:36

This was very fun, of course thank you for joining me for this episode of the Digital CX podcast. If you like what we're doing, consider leaving us a review on your podcast platform of choice. If you're watching on YouTube, leave a comment down below. It really helps us to grow and provide value to a broader audience. You can view the Digital Customer Success Definition Wordmap and get more information about the show and some of the other things that we're doing at digitalcustomersuccesscom. This episode was edited by Lifetime Value Media, a media production company founded by our good mutual friend, Dylan Young. Lifetime Value aims to serve the content, video, audio production needs of the CS and post-sale community. They're offering services at a steep discount for a limited time. So navigate to lifetimevaluemediacom, go have a chat with Dylan and make sure you mention the Digital CX podcast sent you. I'm Alex Trukovich. Thanks so much for listening. We'll talk to you next week.