AI-powered CX, with Lisa Popovici and Sienna AI

Jake Aaron Villarreal: Welcome to our podcast, From The Ground Up, where we interview startup founders exploring their journeys, their success, challenges, and lessons learned. We hope to be inspired in discovering what it takes to build a thriving startup. I'm your host, Jake Aaron Villarreal, and here with us today we have Lisa Popovici, the co-founder and CMO of Siena AI, a company that's changing the customer experience and customer journey for e-commerce companies and others through the use of AI. Lisa, welcome to the show.

Lisa Popovici: Jake, thanks for having me.

Jake Aaron Villarreal: So a little bit more about Lisa. She's a co-founder of Siena AI, an autonomous customer service platform designed for commerce, turning AI into customer service team's favorite super agent. Before launching Siena, Lisa had two successful Shopify business exits, all while studying general medicine for six years. After graduating, she then pivoted to doing what she loves the most: building software for e-commerce. Lisa, so I guess before we dive in here so the listeners know, where are you calling in from today?

Lisa Popovici: Uh, New York.

Jake Aaron Villarreal: Okay, great. And are you originally from there?

Lisa Popovici: No, I am, I actually just moved here three weeks ago. I am originally from Romania. I moved out of Romania around four years ago. I was pretty nomadic in the last years. Um, lived you know, in California, Europe. I actually moved now from London where I spent uh the last six months. But I feel like New York is um, will actually be my base or at least for the next years, and I just want to you know, settle here a little bit more.

Jake Aaron Villarreal: Yeah, great. I lived in New York for five years and love that town, so I think you landed in a great spot. Um, let's go right into this here. So tell me what inspired you to build Siena AI and really talk to us a little bit about the space you're in.

Lisa Popovici: Yeah, um it's a, it's a really exciting space, new space, right? It's still new, new even if it were, you know, since, since ChatGPT came out last year um the adoption curve was, was pretty high. But it's still not you know um, fully uh fully completed in a way. There's still so much uh so much more um education to be done. People that have no idea that these kind of technologies exist, this kind of products exist. So it's very, it's a very exciting space definitely. Highly, highly competitive, very challenging, very fast-paced. If you're literally, if you take a break or stop innovating you're literally going, going to die. So that's not an option.

But what inspired us is the fact that we, we were always very bullish on the ideal customer experience. Uh, Andrei [Mihai] and I have been always building in the conversational commerce space. And a lot of our vision of how this ideal customer experience should look like came from our you know merchant experiences, like actually being in the trenches, doing everything ourselves, talking to customers. Uh and when it comes to customer service and customer experience in particular um, we, we've noticed uh from our previous uh company and talking to our previous customers, that around 70 to 80% of their, of their inquiries, of their conversations were repetitive. So we felt like there's so much human potential that's being lost in that repetitive, tedious work. There's not really a, a career growth opportunity, there's not nothing exciting like just waking up you know, every morning, especially on a Monday morning with a huge backlog of thousands of tickets just waiting there for you to say the same thing over and over again.

And then on the other hand um, when you looked at "okay, like how are these companies currently solving this problem?" they were only you know the traditional automation tools like chatbots or you know, like basic rule-based automation. Very limited, very frustrating, very bad experience, you know, uh that were just not uh not solving the problem. They were mostly just, in a way they were like a patch. But you know like when you have some sort of, like you have a, a problem like with your gut or with your... you have like a headache or every single day you get a headache or you're just like not feeling very well, like what is the problem? I'm not just going to take a pill to solve it on the spot. I'm actually going to get more like, do some digging, do some investigation, see like what is the root cause so I can actually solve the root cause, so this doesn't happen to me every single week or every single day. So it's pretty much, I think it's a good analogy between chatbot and true AI.

Uh so yeah, this is like uh you know, some things that inspired us. And um, that's why we took action and really found that there's so much opportunity and such a big problem to solve in the, in this space that we wanted to, "Okay, let's just go ahead you know, start talking with even more customers, validate all of our ideas, our vision, and just start building."

Jake Aaron Villarreal: That's great. So kind of painting the picture, the focus of your product is for e-commerce companies, is that correct?

Lisa Popovici: Correct, yeah. Siena is a platform agnostic, however, our bread and butter is e-commerce, yeah.

Jake Aaron Villarreal: Okay. And so give us a like a case in point of specifically your, the problem you're solving with your technology. And really if you're an e-commerce store or company in that space or any other software company really, and you need a better customer journey or customer experience, walk us through how your product helps solve that.

Lisa Popovici: Yeah, so I think the main pain points that uh our customers are experiencing and uh what leads them to Siena is first of all, the repetitive tickets that they're getting on a daily basis. Lack of resources or bandwidth to, to deal with uh with this uh load of tickets. And also the fact that a lot of companies are scaling very fast and they cannot keep up with the, the volume, right? And they do not want to over-hire, they might not have you know like huge budgets of like you know, bringing you know hundreds of people just for customer service, right? Um and I think it's also the fact that overall they feel like uh they want to improve the customer experience. Like even the like how you respond to a customer, and the fact that you um keep in mind what has previously been discussed that might, might have been a discussion with another agent, and now you're passed on to another agent so like a lot of context is being lost. There's lack of empathy you know, throughout those interactions because agents need to always like you know, drill down tickets as fast as possible until their shift ends, right? They want to be as productive as possible, so that like personalization layer kind of like fades. Uh it's not because of them, it's just because of time, right? And because of all of these things that they need to work on. And I think this is, these are the main challenges.

And just obviously you know, cost-saving, streamlining operations, becoming more efficient, more productive. A lot of the, the teams that I'm speaking with, they feel like you know, "I we have this amazing team, we have this amazing customer service department, I don't want my team to waste their time on doing unproductive work. I have more important work for them. So like how can we you know bring in this technology to augment our team, help us scale ourselves, become you know like 'work smarter not harder.'" Sometimes you got to work smarter not harder, sometimes you got to you know, do, do both. So I think these are some of the things.

Now to move on to how Siena can help them. So basically Siena is an agent that um takes a seat inside of their help desk, inside of their ticketing system, and works alongside the existing team. So every time there's a ticket, Siena will, based on the data that it has, it will go ahead and assign itself the ticket and respond, solve that problem. It's built for resolution. And if it's not able to, maybe it has a knowledge gap, it will just route it seamlessly to the team. Uh and then it learns from also you know, the agent's best answer, so the next time it will know how to respond. So it's literally like it's, it's another you know, member that you, you're hiring. Um and it helps with a lot of use cases.

So the reason why we have a lot of brands reaching already 80% in automation rate is because Siena goes beyond just basic FAQ automation. You can literally uh have Siena take specific actions, take care of transactions such as tracking orders, changing shipping addresses, uh sending a replacement. Or we work with a lot of companies who sell subscriptions. So I believe that at least 50% of their queries are about, "Hey, can you skip, I'm traveling next month. Can you change the frequency of my subscription, I have too much product? Can you cancel my subscription? Can you reactivate?" All of these actions, Siena is capable of doing them because of our integrations with the subscription platforms like Recharge, Skio, Stay AI, Ordergroove. So yeah, it's like you can do a lot of things um and solve a lot of problems, yeah.

Jake Aaron Villarreal: Yeah, that's great. Um talk to me about the market opportunity um and specific to customer experience with, with AI and kind of how you see it. You went out and you know, you started this company, you got funding. Big picture, where, where do you see the market going with this type of technology?

Lisa Popovici: Yeah. So when you look at e-commerce specifically, um I think again repeating myself, there's still a lot of education to be done. There's still a lot of market and mind share to be acquired. Um the way I see it progressing is when you, when you look at these AI agents in the next 6 to 12 months, they are definitely going to be able to do much more than they are able to do now. So then teams will, will, will get restructured in a bit. Like definitely you're, you're not going to have to waste your time on repetitive tickets anymore, but do more strategic work, take care of VIP customers. Pick up the phone and talk to someone who really wants to speak with you. Uh take care of, of the retention of those loyal customers that you have. Um maybe I don't know, um progress on other departments that you've always wanted to but you couldn't because you just had to do your you know day-to-day responsibilities.

So there's going to be definitely team restructuring and a lot of work will be done on the technology itself versus on the tickets. Uh so this is where, where I'm seeing in the next 6 to 12 months, um and I'm seeing a lot of excitement from, from teams. Also there's still a lot of skepticism, right, because it's such a new, with every single new innovation and technology wave there's been fear, skepticism, there's been maybe some hate sometimes, there's been uh not, folks that are not embracing it or just don't know yet how to. So I think um, yeah, to, to pick up on my thoughts, I think there's still, there's still a lot of opportunity for education. And yeah, I'm seeing a lot of excitement from, from some folks like "oh like I finally can do these projects that I've always wanted to do or I can finally you know improve these metrics that I am responsible for." Because it's not like you know, the AI is going to be reporting to the CEO or you know the manager uh of like "oh yeah I actually reached you know these KPIs this month." No, the human is actually responsible for that technology and for those KPIs. Um yeah, so kind of like this is where, where I'm seeing the next six to 12 months.

Jake Aaron Villarreal: That's great, yeah and six to 12 months goes fast. So it looks like a lot of innovation and tools to help the agents, the customer support team, customer service team, but also being able to automate other tasks that will be helpful for a company. Um you, you went out, you raised 4.7 million in funding to develop empathetic AI customer service agents. Walk me through a little bit more about what is empathetic AI.

Lisa Popovici: Yeah, it's a great question. So the reason why we are positioning ourselves [as] empathic AI goes beyond just providing a shiny, nice, personalized response to the customer. Obviously that's like very, very important, that's one of our major key features inside of Siena. The fact that you can uh have this confidence and have this peace of mind that you're finally implementing an AI tool that uh speaks your own tone [of] voice, uh embraces your personality that you've spent so many years building right, you don't want to lose that. But it's more than that. So when you look at empathic AI, you want to make sure that this um, this principle gets applied also internally with the team that works with this technology. So for example, when we think of empathic AI, we think like "how do teams internally collaborate with this AI in a very empathic way?" So like, how can we make it as easy as possible for teams to work with this technology, with this new AI team member uh in a way that's very collaborative, very easy, very intuitive. It feels like you're actually working with a real colleague. Uh and how can we embed this technology into their day-to-day operations so it doesn't feel like you know "oh like another tool" or like "so much work" or like um, "like it's just adding complexity." So I think it's also about that, like integrating this empathic element internally but also externally when it comes to the actual end... the actual interactions with the end customer.

Jake Aaron Villarreal: That's great. Um makes a lot more sense when you describe it like that. Uh the top things that you should look at when buying AI software for customer experience or the customer journey?

Lisa Popovici: Yeah. Yeah, this is a, this is a super important topic and very good question. Um so if we were to, let's go with three, the top three things. There's so many, we're actually writing a piece on this. Like I think you will have more than 10 items. But first of all I do believe that you need to, to find a tool that like, first, first of all you should set a goal. So what are your, what are your biggest goals with AI right? It's not like just you go in there, obviously there might be first exploration, you're just researching to see what's out there, you're educating yourself. But then once you like reach a certain level of confidence and knowledge in this technology and in what's out there in the market, you kind of like, "okay, so I know all of these tools, I know what they are capable of, but what do we actually need? Do we need to automate transactions? Do we need to provide personalized recommendations better in a much like better fashion way, right, like in a concierge way? Do we need to like help our customers [manage] their subscription effortlessly because we want to increase retention?" We're seeing a lot of them drop um and uh cancel their subscription because of how maybe challenging it is to manage their subscriptions. They are lazy, they do not want to go into their portal. They want to just text something and then magically be done for.

So is it your goal retention? Is it your goal becoming more efficient? Is it your goal maybe not over hiring and keeping a lean team, you know, making sure what you're forecasting aligns with what you're actually you know, spending and your budget? So you have to define a goal. And that, set, set some clear KPIs to achieve that goal. And see, "okay, what technology, what is the tool that has these capabilities, these functionalities that actually align with our goals and the KPIs and allow us to, to reach these goals and allow us to track these KPIs?"

So one, one example would be, okay, if I am a company who sells subscriptions and I'm seeing a lot of friction when customer, my subscribers want to manage their subscription, obviously I want to automate subscription management right. So I will search for a tool that has an integration with my subscription platforms, can access my data, can access their you know uh order information, all of their subscriptions, all the products. Can have access to all of this data and it's easy for me to automate all of those things. So first you know, for example look at like the integration capabilities.

Second, you know maybe you're a brand who has had problems with your CSAT scores. So you have pretty low CSAT scores because you just didn't have the right team yet, or maybe the right uh the time or bandwidth to actually go the extra mile. Like always respond super quickly in the first minute or first five minutes after someone reaches out. Uh keeping resolution times low. All of these things that make such a huge impact on you know, if you're a first-time customer, the first impression is the most important thing. So maybe you're struggling with first response time, resolution time, CSAT scores. So you need a tool that has the ability to respond almost instantly and in your brand voice and go the extra mile way. Be very empathic, be very personalized.

Maybe you also like are a brand... I've just spoken with uh with a very cool brand who like you know is a little bit more quirky. They like to sometimes you know tell some puns or some jokes or like you know, like just you know engage in this like extra like very jazzy you know tone of voice. So how, they can, how can they scale themselves? How can they scale this brand voice? So you need an AI that's capable of actually replicating your voice and it will not sound like a robot, it will not sound like you know like a stupid you know bot who just doesn't understand what you want. And like just when you're interacting with it they just like "I'm, I'm just wasting my time like," you know. So I think first it's very important to set like, to have clear goals, clear objectives, and find tools that can help you achieve those goals. Um yeah.

Jake Aaron Villarreal: That's great, thanks for explaining that. Um you mentioned stupid bot, I mean we uh as consumers always interact with technologies that we think maybe there's someone behind it and sometimes we know there's not and becomes very obvious at some level. So how you differentiate from a bot is more than just communicating, it's also, sounds like it's learning your culture as a company, it's learning your voice, and being able to respond empathetically or empathically based on the conversations you've already had with your customer base, which I think really provides that more engaging experience. Um uh you've talked a lot about your product and I'll just ask it one more time from a different perspective. If you're a company out there thinking about using your product, um with all the innovations going on, how are you differentiating more than others or taking a different angle than other companies? Because I think what you've been building is incredibly important for, for companies to, to look at.

Lisa Popovici: Yeah. There's three main elements that make Siena unique. So first of all is the fact that it was trained like a human. So it's not based on rules, it's not based on keywords. It's literally trained like humans think. So when let's say you're a customer service agent or a manager and you get a ticket from a customer and has a lot of like questions, it's a very complex ticket. So what do you do first? You first apply comprehension to understand what's going on, what does the customer want. Second, you apply reasoning. And then third, you apply decision, decision-making to see what's the best course of action to take based on everything that you, that you know about that customer. So Siena was built on the same three principles, and this is how it, it, it, it operates. Also it's very contextual, it has that contextual understanding, it's able to read through the lines. Even if it's a you know, a, a very complex message with a bunch of questions, with like a lot of frustration, Siena is able to understand everything, respond to everything, and also do it in your brand voice in a very empathic way. It literally never gets annoyed, like you know. Sometimes we are human, we're like, "Oh god this customer is saying the same thing and they're not accepting our you know offer or our you know way of solving this like, what can I do? I'm so annoyed like maybe..." And that might come across through the interactions without you even realizing because we're humans, right? But like, with AI you have this cool benefit of like, you can literally like you know, tell like very bad things and you will never get upset. Like it will be even more, even more friendly or match like, just be very, very cool with it. So that's one thing.

Um uh second thing is the fact that he's very, you know uh empathic and personalized. So one of the coolest things where the magic happens at Siena is our Persona Studio. So what you can do is you can literally create your ideal, let's call it like ideal agents. And you can have for example you know Katie, which is very professional, educational, down to earth for email, she's assigned for email. She has a specific set of attributes, she has a specific set of instructions. And then you have Joey that's I don't know, likes to tell jokes or likes to share best practices or some healthy recipes based on obviously, if you're you know food and beverage company, on social media in the DMs or in the comments, right? So Joey has different instructions, Joey has different you know uh guidelines, different like commands that he needs to follow. So this is very, very cool because you can literally uh scale your team in a very strategic way. And it's like adding these agents into your team that will literally follow everything that you tell them to do. And when you're interacting with Siena today it's like, it's pretty, it's very, very challenging to tell that it's an AI. So like 99% of customers cannot tell. And this is also because our customers are giving Siena... when they create those personas they give it a human name because it's their own choice. You can literally disclose it or not. Uh and it's just so beautiful to see like the reviews from the end customers that they give to Siena after they interact with Siena. So they say like "oh my god this the best customer service, Siena is amazing" or it's like the name of the persona, and like "oh wow like Katie solved my problem in such like, such short time like wow, like this is my favorite company!" So it's like you can literally see the impact those interactions have. So I think yeah, this is the second point.

And then the third point I would say the fact that is um deeply integrated with your e-commerce tech. And this makes it, makes the implementation so much easier. It's a no code, no workflow platform. Everything happens through using natural language, everything is like very close to training a real human, you know. Um giving it the full context over you know all of our policies, giving it instructions, just connecting some things, and then you're, you're good to go. Yeah. So I think these are among the, yeah, among the things. But there's so many other cool things. It's all about... to be completely honest it's, it's so complex what we're building, and it seems very easy but it's so complex and challenging. And it's all about the nuances when you're building an autonomous agent. Yeah.

Jake Aaron Villarreal: Yeah, good explanation. That sounds really... sign me up! I want to try it in our company. And we're not an e-commerce company, but we have a lot of customer support issues that we need to solve sometimes, and you know, we don't have you know a full team dedicated to that, so that would be really interesting to try that out. Um talk to me a little bit about... we're going to switch gears here. You have had a couple companies before this and some solid exits. Um what did you learn in those companies that you've applied now to Siena?

Lisa Popovici: Yeah. I feel like um my previous companies uh were the university, the founder university that you never get to have. Um and the, the success, traction and all of the things that we're doing right now at Siena are in a way the result of everything that we've learned and all the mistakes that we've made. We've made, I, I'd write a book about all of the mistakes, I'm still making mistakes, I'm still learning obviously. But uh for example, you know when it comes to hiring, uh like I've done so many hiring mistakes. Like even when you, when it comes to like maybe having to let someone go because obviously it wasn't the best choice from the very beginning. But you're like, you didn't really know what questions to ask, you didn't really know like you know, you saw like a nice profile or you, you had a nice conversation, but like did you go, like how deep did, did you go? Like do you do, did you actually first before you actually put out, put out that job post, did you actually define what you need? Like what are the, what are our goals with this role? Like what do we want to achieve? What do we need this person to do? You know. And then who, what type of persona are we looking for? So then after you made that hire, you realized you know, very quickly, because in the first two weeks you can kind of tell to be honest, um that okay this is not the right fit.

And like I, I remember my first, my first um, I had to let go the first person ever in my life and it was the most horrible thing for me. And I think I spent on the phone like two hours with that person and it was like I was just like trying to in a way justify everything and oh my gosh, it was horrible. It was so like heartbreaking for me because I never thought that I was you know I was going to do this and I hate doing this. But it's just like no, you should not do this. You should literally just you know do it very quickly obviously, give feedback, uh and think, I think what's very important is that it should not come, come as a surprise if you actually have to let someone go, right. So you should, like they should figure it out, it should be a mutual thing. So this is just one you know thing, it's a good, good story but um. Definitely hiring and then also like priori-, a lot of uh you know uh learnings there.

Um also like a lot of things around when you're actually starting, like how do like, before you actually start writing the first line of code, like do proper validation, right? Not just like follow... obviously you follow your gut, but like you do need to validate. You do need to go on customer calls, you do need to ask the right questions, even like what kind of questions to ask in those, in that validation period that like it's so, so important. Because they're so, it's so easy to like "okay go on a call with someone, you tell them about your vision for your new product right, and you ask very superficial questions, and then at the end 'would you use this?'" This is the worst question that you can ask because obviously they will say, "Oh yeah, I would give it a try." So then you're like super excited, "Oh yes I got another validation! Uh obviously our product is going to work, everyone is going to use it." But when you actually build it, no one is going to use it because they're like, "Oh actually you know I don't really have time. Actually we're using something else, where this is not just not, not [a] very big problem for us." So like the pre-, in a way pre-building period is extremely important. Yeah. And just some, some of the things that come top of mind right now, yeah.

Jake Aaron Villarreal: That's great. I want to go back real quick to the hiring experience you have. One of the things that we do (I've interviewed 20,000 people in my career), one of the things that I always like to do when we hire internally is understand the goals that we want that person to solve when they join the company. But also the very last touch point we like to do is look at the person and decide, "Could I see myself working for them even if it's a lower role than I have for myself? Can I see myself working for them based on their intellect, their communication style, their leadership? Are the things there that others can work under them well as well at some point?" So just um some litmus tests we like to go through in addition to all the basic stuff you look at from a core skills perspective. Um as you look at 2024 as a company in growth, where do you see, see the company going from a people perspective in terms of hiring growth as well as from a product roadmap perspective?

Lisa Popovici: Yeah. So from a people's perspective, from an org structure, um we are not fans of all... um we were able to achieve so many things and move so fast because of our lean team, always. But we, we do, we are big fans of hiring the right people, the key people, and work, working with uh great, great talent. So right now I think we are 25 in the team, uh and probably you know next year the, the team will double. But I'm like I'm, I'm not sure that they will go more than double. So this is from a team perspective. We, we even now, even you know until end of year, we still have some key hires to make. We're very excited about that because it will help us you know um scale, scale finally, you know, we're in the scaling phase right now. Still building a lot, there's so much to build, so, so many great products and opportunities. But also like how can we you know enable more uh brands to be successful with Siena faster, you know. Uh maybe um yeah like you know, onboarding brands faster and, and more brands at the same time and all of these things. And just enabling them to be successful in a, in a faster, in a faster uh time frame.

Um and from a roadmap pers- perspective, there's not a lot of things that I can disclose today, but um we are still very much focused on uh continuing our mission of building this autonomous agent. So um we are launching a lot of interesting and very helpful actions that Siena can take. So I've told you about some of the actions that it can take like, like tracking orders, like managing subscriptions, but what about the you know more complex ones like you know issuing refunds or um I don't know creating different kind of um offers or discount codes depending on the customer type, the segments. Like all of these things that obviously we get a lot of these asks and requests from our customer base because they know exactly what they need, they are you [know], in the trenches there, they're seeing those repetitive things over and over again. So we're continuing to double down on you know, I call it, I call these actions like Siena skills. So we're adding more and more skills, more integrations. So you know, as with, with AI it's all a data and information game. So as much data and information you provide to the AI, the better it will perform, and the more context and knowledge, and more like, the more it will be able to do. So doubling down on integrations, finding the right partners to integrate with, and yeah, these are some of the things that we're excited about.

Jake Aaron Villarreal: That's great. Well to wrap up here, I have just three more questions for you. We call these the "Three Questions" because they're just simple questions. Um, for you, where do you go to think big or to brainstorm?

Lisa Popovici: I go to workout.

Jake Aaron Villarreal: Yeah, do that. What advice have you gotten from another founder that has been priceless for you as a founder?

Lisa Popovici: I think, I think a good advice was to find, to find leverage, yeah. To always find leverage and not try to do everything yourself.

Jake Aaron Villarreal: Yeah, yeah, that's great. What works for you in staying positive when the business, business is going through challenging times?

Lisa Popovici: Oh my gosh, well I think I've already built that muscle. I've been through so many challenges and still, like there's so many challenges and stressful days. And like one day you're on top of the world, the other day you feel like the most miserable person. Uh but uh I think there's a combination. So obviously you know, like um the lifestyle, like I, I like having a healthy lifestyle, like working out you know, uh meditation helps. I've bumped up my time from 10 minutes to 20 minutes now and I, I, I'm already seeing better results like I'm just in my focus and memory. So, and then um I think yeah, nutrition. And then I think trying to surround myself with people. I love being around people, I'm a social person. And just like not always be in my head, uh internalize things or you know, I spend so much time with my best friend laptop, which I feel like I'm trying to balance, "Okay, how can I spend more time with, with humans, not just virtually?" So I think yeah, it's a combination of these, these aspects.

Jake Aaron Villarreal: That's great. I never heard that before. I think a lot of people have best friend laptops and uh I'm one of them. So I got to give mine a name. Anyway, um really great to have you on, I appreciate your time here. If uh anybody wants to find you or your company, where would they go?

Lisa Popovici: I think the best place would be you know our website. It's siena.cx, from customer experience. Or on LinkedIn you can find me, it's Lisa Popovici. Or Twitter, pretty be active on there.

Jake Aaron Villarreal: Great. Well Lisa, I really appreciate your time. Thanks for joining and to all our listeners, thanks for listening. Means the world to us that you've spent your time today with us. Good luck here in the new year uh Lisa in '20[24]. Look forward to uh catching up with all the listeners on the next episode. My name is Jake Aaron Villarreal. Until then, everybody take care, cheers.

Before we wrap up, I want to give a big shout out to all the entrepreneurs that have joined to make this podcast possible. And for all the listeners for listening, it means the world to me that you chose to spend your time with us today. I'm your host Jake Aaron Villarreal signing off for now, but can't wait to connect with you all soon on the next episode. Take care.  

This show is sponsored by Match Relevant, a company that helps venture-backed startups find the best people in the market. And they do it in three simple steps. First, they sit down with founders to understand their story. Second, they tell their story into multiple candidate channels. And third, they schedule interviews within 48 hours. Find us at matchrelevant.com to learn more about how we do it.  

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