Ep #157: From Spray-and-Pray to Predictive Sales ft. Viktoria Izdebska (Founder, Octrace)

Viktoria Izdebska [00:00:02] Mass emails and mass individualized emails. Have never been distributed in such a pace and speed as now. So basically everybody can do spread and pray right now with their target group, which leads to conversion rates, basically dropping to zero. Taylor Kenerson [00:00:19] Welcome to the Hyperengage Podcast. We are so happy to have you along our journey. Here, we uncover bits of knowledge from some of the greatest minds in tech. We unearthed the hows, whys, and whats that drive the tech of today. Welcome to the movement. Adil Saleh [00:00:40] Hey, greetings, everybody. This is the deal, the Hypering Aid podcast. I know that this is this has been trying to make sure that this is long coming for a lot of these GTM tooling. And I know that a lot of our you know, listeners, they're already fed up with, you know, 30 plus GTM tooling in the past three years, and all of them are AI powered. All of them are AI native, AI first. And it is so easy to ride the AI way this time, but you know, that is why we are trying to make sure that we screen the products and founders. And today we have a very special guest anyway to make sure that they are doing some sort of a unique approach towards the lms, towards this conversational ai. They're not just relying on texture or summaries or analysis. They are basically. Giving an cumulative AI 360 view of all the external data sources, because at the end of the day, for any DTM tool, for a, any sales intelligence any customer success platform the more data sources they're able to consume, get context or context around it, the more efficient the outcomes would be at scale. So today we are talking about Octrace. We're talking about. The I would say the mother founder of Octrace Viktoria with us. And she's the brain behind this product that is helping many of the businesses in the past few years you know, building the right sales intelligent engine within their data layer. So we're gonna delve in more with Viktoria. Viktoria, thank you very much for taking the time. Viktoria Izdebska [00:02:00] Great. That that I can be on the podcast. Very excited for it. Adil Saleh [00:02:05] Love it. So, Viktoria, the biggest question, the biggest talk of the town is how to get these AI models more specialized for their use cases. I know it changes with customer to customer segment to segment industry to industry. Of course the way. People perceive value out of your product. If you're a data platform, the biggest concern is like, let's say one platform is using pipe drive as a CRM, another is Salesforce. Within those Salesforce they have like custom objects. You gotta make sure that you flow in those data points and those custom fields. How is that journey going on for you to be able to make I know that it's not easy to, you know, make a one size fits all, but you gotta make sure that you have some sort of a standardization or playbook or something. How big of a challenge was that? Viktoria Izdebska [00:02:47] Yes, very interesting question and let me share a story first on how we got to the insight and how we're working with it right now. Up until now we've talked to over 5,000 customers about their very, very specific detailed target group. So that was quite a multiple We were able to build from the get go and we trained an algorithm based on very specific target group data of their customers. And the insights that we found was that around 70% of those 5,000 companies. Mentioned a very similar, or even the same target group that they all have. So the insight that led us to believe is only a smart small part of all market that is being targeted right now is actually being targeted with outbound activities which leads us to believe that the future of sales is gonna be. Of how it's developing a lot of spray and prey and very low conversion rates. So what we've done is we took this classic data approach a bit different and said, how can we individually for every single customer predict when their exact timing will be, when the customer needs the most? This is what we call predictive intelligence. So basically we've trained an algorithm to tell us at which point in time a company will be most receptive to their specific product. And how we do that is by first taking CRM data, so analyzing what past customers they want and at what time the past customers have been won, to then get all the trigger events. And then also taking in macro shifts of markets. So what industries are usually companies selling to? How's the economic development of those companies? What are technological shifts that we should integrate into the process? And then based on that, we are able to, for each and every single customer, individually, tell them a thesis that we're building up. So a customer will be most receptive when they're currently in the process of TA changing their technology sector, for example, or internationalizing, or building up new production sites. And based on that, our software comes up with its own individual signals. Tailored to the needs of the customer. And based on that, we can outperform the data market currently by consistently over six six x. And that is the underlying predictive infrastructure that we're building for all companies that have to rely on outbound. Adil Saleh [00:04:48] Okay. And this becomes more interesting when you have like different customers in different industries. Like you have to go white club, white glove a lot, and you have to make sure you have some sort of implementation team and go inside their environment or inside their data warehouse. A lot of these SMB to mid-market, even mid-market, they're not tracking the right data points for their customer facing teams. So for them to, you know, adopt to the platform, how big of a challenge was that and what kind of. Initiatives have you taken? I know that you're not too early, like it's been some years. So what do you think? Like what kind of playbooks every founder listening to this investing into data points, investing into product analytics to CRM or engagement analytics to support and qualitative measures like meeting notes and external data sources from lending trunk based trust, private. All of these sources to be well integrated inside their warehouse. Being articulated for the customer facing team, that's been the biggest problem because let's say a customer success or account manager, they see the data, they use amp like platforms like product analytics and all, but that there's a data doesn't drive action for them. It doesn't get translated into their language or maybe in, in the best way that they can take action. So what kind of process you have internally and what kind of, could learn. Viktoria Izdebska [00:06:04] So the two questions that I picked up first, the data, ROI and the second one, the individualization. First the data, ROI. How can we make sure that the data that the companies. Get, actually get them to a certain certain point. I think the most important question every single founder should ask themselves is what's the monetary value that a company derives from the actual data? Is it just insights? Is it just research? Or is there actually on the end of the pipeline revenue that's being generated and what's multiple with which the. ROI is happening for that sales tool. For us personally, that is at the end of the day for firstly the performance of the sales FTE with our data and without our data, which is very clear for us, it's at least three x. And the other thing is how many offers have the company sent potential customers before using us and after using us. The second thing about individualization I see a trend coming, especially in Silicon Valley. We've talked a lot about, developers being sent to customers and individually building their product based on the needs of their customers. We've been guilty for that ourselves. So we started off by targeting very big banks, customers, manufacturing giants, and went to them and said, what kind of data do you need? What kind of insights do you need? Let's build it together. It seems very tempting at first. It seems like a very good startup approach because you're building very close to a customer. But the real issue with that, and the main risk with that is that you're building for a certain customer and you can't really differentiate if this is gonna be something that will be adapted within the mass market. So we've tapped into that at first and we've done a lot of individual projects, which were very much project based, even if the cooperations. Went on for a long time. It was project based for an individual customer, and we tapped out of that. We, the second that we started building the algorithm completely out outside of the customer's needs and just testing on the customers and testing the ROIs on the, of the customers. So that's something that is very tempting, which I try to advise a lot of young founders not to do, is build too close to the client and especially too close to one singular client or to a small group of singular clients. Not to get too. Fed up in the individualization process. Adil Saleh [00:08:10] Yes. Yeah. It is super important. Even if, even when you do it, you need to make sure that it aligns with your product vision, let's say, as you mentioned before, exactly. Like, how many customers in the future are going to have the same problem that we are solving for them, you know, and making sure that and this is quite good interesting strategy as well, like. At the same time you're working for you know, working at a bank with their environments and solving their problems that you are making sure that could be a problem for a hundred other banks. But at the same time, you're releasing some new features, you're releasing some new use cases, and you're testing it out. You're testing the waters with the existing plan, which is good. That is a good validation. I know that it's not. It doesn't always work because of course a validation, the true meaning of validation is validating with the ideal customer profile. But you know, it's still better than not validating at all. So, so, at the end of the day, it is. And data and all these platforms. We are also a data platform. Been there for like three years now. Have customers working closely with them because you know, every customer has a different niche, different product, different customer journeys. They map their customer success differently at different stage. But at. At some point you have to make sure that you standardize, you do it for scale, and you think about at least a good chunk of addressable market when you're solving any problem or consuming your team or resources for anything. So, perfect. So you mentioned one segment, which is like, banking and all of this. What kind of segments that are kind of a sweet spot for you guys? Viktoria Izdebska [00:09:35] Yeah, banking, logistic, manufacturing, and energy are the segments where we've seen a lot of ROI for the customers, especially because those segments are not allowed to do spread and pray. A bank that comes to you is not allowed to acquire customers based on mass emails or cold calling. They have to have a strategy where they target the companies very specifically. So in general, a company that. Is allowed to have high customer acquisition costs. Also usually goes hand in hand with not being able to do, spread and pray. So they need a solution where they can pinpoint exactly when a customer needs the most and then act on it. Another thing you mentioned about the individualization, I think taking it a bit from a different approach and talking about the go to market of companies oftentimes how it's currently done is I see a lot of companies a attracting early adopters first and then having a wake up moment with a very high churn because they've attracted a lot of. Sa tech savvy customers that are willing to pay very password tools but jump off straight away and they have adapted the tool to those customers that they have jumped up jumped off straight away. So I think a very strong tool in general is getting a lot of Lois in, for example, a market that you wanna tap in when you're a bit farther in the process of building your company and then getting the ground running and based on what many companies told you of, what they would be willing to pay. And then adapt the tool and adapt the process. Yeah. Does not necessarily work. Adil Saleh [00:10:54] I mean, thing is I'm all about like going for the enterprise and bottom line will follow to be very honest. And it is so hard to build something for enterprise. So who deals with the long sales cycles and you know, the red tape and everything? Viktoria Izdebska [00:11:09] Like. For us it's been winning strategy where we have a sales team that is suddenly focused on enterprise sales. For us, high ticket enterprise sales allowed us to basically bootstrap and build up the whole software and get to to good seven digits. So that was our, our winning strategy. Yes. Adil Saleh [00:11:25] Okay. Okay. Perfect. And I mean, there is a biggest question, like, I have it, my team asking that too, like, it's in my notes. A lot of these SaaS companies, whether they built for enterprise market or SMBs, they're trying to go multi-product. They're trying to serve adjacent use cases. Let's say A CRM is trying to be also be a customer success platform, or they're also trying to build agents for customer support. A customer success platform is trying to be a GTM tool marketing team, trying to be a sales tool as well, because all of these use cases are pretty much adjacent and with AI and its capability. It's kind of shrinking and a lot of these going going, like, I assume that it's going to commoditize, like, you know, the categories are shrinking. There's gonna be like some new players coming into the market that are serving a lot of adjacent use for mid-market to enterprise will be the last two, you know, exit, but. SMB to mid-market. I think the, there's a huge downsize or layoff of tooling such as like, as expensive, like tools like you know, CRMs like Salesforce, you know, HubSpot, they're like $2,500 a month plan that gives you all the tracking, you know, user mapping and everything. So compared to like tools like a polo, clay, how do you see this internally for your team as well as, for, from a industry ship standpoint the downsizing and the tooling tooling, giving a lot of adjacent features to serve adjacent markets and great trying to tap it to more markets going, multi-product building agents, all of this. Viktoria Izdebska [00:12:59] Yes, you've tapped into a very interesting topic that I've been reading into a lot. I strongly believe that the future is a lot of enterprise clients and also a lot of SMDs will have their specialized SaaS stack that they have maybe even coded themselves. And the question for me is, where is gonna be the real mode in upcoming software as a service companies? Is it gonna be go to market? Is the new mode gonna be who is distribution and builds a specialized model on that? Or is the mode gonna be still having a very specialized niche software? I'm a strong believer that if you focus on one thing and one thing only, you're gonna be better than if someone else builds a general tool for themselves very fast. I think if you're. Fixing a very certain pro problem, and you have a network effect as a, so, as a software startup in the background that allows you to get proprietary data that nobody else has access to, then that's the only way of winning. But I do strongly believe that everything that is, doesn't have a technical mode and doesn't have a distribution mode, is gonna have a very hard time competing against just companies, five coding tools for themselves and just using their own specialized tech stacks. Adil Saleh [00:14:04] Interesting. And the, I could put it this way as well, like, a lot of these sbs, they try to do more with less startups, trying to do more with less cut researches, optimize the cost. Number one reason is they're not getting a lot of funds because the investors that they were choosing, they. They've invested in hundred other AI tools. A lot of them are, yeah, sitting in their competition as well. So not getting funded, not being able to optimize the resources using AI to do that. So, and optimize the bandwidth and everything is one of the reasons. And then that actually drives them, you know, to, you know, build something on rep, play, lovable, and, you know, quoted on cursor. Something do internally for them to optimize their workflows and building internal tooling. Like maybe use tools, a lot of tools that are there in the market and build something on top of it. Perfect. So how do you play internally in terms of using technology, optimizing the bank? I know that you guys are not pretty lean team. Not as big as like. 20, 25 people less. So, what is your, like, kind of for operat physical, how you guys operate, what kind of culture that you see within people coming in and, you know, tell us more about the vibe at, Octrace. Viktoria Izdebska [00:15:11] Yes, the vibe at Octrace is enormously good. I love being here. I love seeing the team. And we have a lot of fun building predictive intelligence. So what we we always my CTO and I have a big focus on keeping the team as small as possible, outsourcing. What is project based and working with a lot of AI agents, we've built a team internally for ourselves as well. An AI agent team that basically sets up the thesis, generates the thesis, all of that. My question would be coming a bit back to the previous topic. What's your take on mos? 'Cause I think that's always very interesting to see. How do you think MOS will develop? What do you think a mode could be in the future for. Software companies in general, or do you think they will even have a mode or do you think modes will be harder to get than anything else? Adil Saleh [00:15:54] Yeah, it depends. It depends. Like a lot of these, like talking about CRM category, that's biggest in our SaaS space. You think about Salesforce first movers and they define customer success. So, Salesforce versus HubSpot, it was quite true a year and a half back. HubSpot was more Chas into SMBs and the cutting down on customers. Salesforce was still big in the enterprises and all it is so hard to, you know, it's Salesforce so sticky enough for big owners and to get get rid of. And now the shift has changed. Now I've seen, I know these big enterprise companies are moving towards a t towards even HubSpot. Yes. As well. So that, like category is basically shrinking. So this drives the number one thing, which is. Building their own agents to capture, let's say a sales team sitting inside Salesforce works with a customer success or product team as well, a marketing team as well. You know, so, if Salesforce, the biggest GTM that they have right now based on how they do market and how they acquire customers is. If they're able to invite that marketing team, that support team, that product team inside Salesforce building, all like agents that go-to for them, like they can build agents because they have data, because they have of course funding they can do it really good too. It's not just about doing it, you know, it's you know. They have launched one and it's, it is working pretty cool for their customers only. And they don't care about you know, the biggest c all the categories, the biggest thing would be not acquiring customers is to retain their revenue. The net dollar retention is going to be the next big thing. And it's not, I'm not saying this because you know, I want to see this customer success like gain size into Tangos and Catalyst category. Moving ahead. I'm just saying that customer success is a function. Will step as an analog with sales and marketing. And it could be, you know, built inside a platform like Clay could be built inside a platform like let's say platforms like CRMs, you know, platforms like these plan hats and all these kind of platforms as well. So there has to be shrink in every category in the GTM tooling, especially because a lot of the GTM toolings, they're. There is no other team that works closely as, as close to sales and marketing. You get my point. So a lot of these GTM tooling, I'm talking about more than like 120 billion of market cap. The sales and marketing, you know. So a lot of these toolings, they're basically going to merge. They're going to train, they're going to like, and whoever does it fast and really good is going to win. Exactly. And there are some examples you're going to see by the startup beginning of next year. Viktoria Izdebska [00:18:23] I see the same way and I think. When it comes to the established ones, like you mentioned Salesforce, I totally agree. The current customer base and keeping the customer base, keeping it like a castle and trying not nobody letting nobody in. The interesting part for me is gonna be the upcoming tools and how fast they're gonna distribute and who's gonna win distribution games. Because I think the more proprietary data they're gonna get out of their customers, that they win as fast as possible, the more data they have to build up on and the higher their level of mold will be to break that. I strongly believe that the ones who are gonna have that building is gonna get more and more commoditized. Tech, having a tech mode is gonna be very hard and very rare to see. But I think the interesting part is gonna be who's gonna win the GTM games and who's gonna win the distribution games in their certain industries? Go to market. And the only way harder than ever. Adil Saleh [00:19:13] Yes. And the only way to win it for me and for a lot of our tooling that is like more data analytics and all these data first companies, is to go niche down. If we go wide, there's no chance because there's so much of noise. There are companies that have, like, like on average they have like 10, $15 million of funding. And you as a bootstrap startup or a pre-seed startup, you cannot compete there. And now they're spending 70% of their their burn and marketing. Acquisition, you know, and these events, you know, you know, like you are in the valley, right? So it's always chirping on the weekend, always on, on Tuesdays and Friday. Everybody's like getting like 10, 15 people in the corner and having some sort of meetup or some coffee table talks and all because it's, you know, they're investing into it because acquiring a customer is not easy. And this has been the hardest ever because before pre COVID it was easier to, you know, slipping through that pulled outbound or email outreach out today. It's so much strategic. You know, I'm hiring a guy from from from Austin, Texas paying, you know, felty amount of money to send out 36,000 thousand emails a month. 36,000 emails a month, you know, and he's like, it's his job. Like I'm, it's still unbelievable to me. But he said he will. But again, at the end of the day emails, Google, all of these have started tracking down the domains and everything. The marketing team they got a lot of. Hit earlier of last year, like in the first quarter of last year, they started tracking down the domains and everything. So that was the biggest hit to the marketing team. So marketing is the initial funnel. So that doesn't fill in the sales that, that is why the acquisition becomes so harder. And then you will see companies sponsoring like $60,000, $70,000 booth at a, at an event like ary. You get my point. So they're investing into these these events required. Viktoria Izdebska [00:21:04] A hundred percent. And the interesting part is it hasn't always been like that. The reason why outbound actually worked is because very few people did it. There was a time where so few people did cold calls, that cold calls really converted. There was a time where so few people did email campaigns and their email campaigns actually converted. And what we see right now is with a lot of AI SDR agents with a lot of AI email agents, all of that mass emails and mass individualized emails. Have never been distributed in such a pace and speed as now. So basically everybody can do spread and pray right now with their target group, which leads to conversion rates, basically dropping to zero. AI SDR agents are currently fighting for every single customer that they get because they have so bad conversion rates. Coming back to the retention topic, not many people renew that. Not many people work with that because they see the conversion rates are just basically lowering their brand credibility. And being so bad that they don't have a clear ROI on that. So that's also why we're building what we're building because the only, the future that we see is gonna be coming back to pure sales. So only acquiring customers where, you know, upfront before the first touch point that this customer is gonna need you. Because he's currently in a state where he's about to internationalize, where he's about to build up new production sites where he's about to buy certain machines. And based on that, you know that if you're gonna start acquiring this customer. From the outside perspective, you already know this customer is gonna need you, and that's gonna be the only way how sales is gonna be done. Otherwise, outbound sales is gonna die. Adil Saleh [00:22:34] Absolutely. Absolutely. And this is a big topic. It is a part of our panel too, and off record, we'll discuss, like I've got some ideas for our vendor 28 2. I mean, it's hard times, but again, at the end of the day. Keeping a niche down and doing the product very right is still a biggest win. You know, you talk about products like Cana Figma you know, linear notion, you know, these platforms even, you know, there's so much of ai, conversational ai. A writer in writer is a category leader in conversational. You know, I have seen them in front of me. Like, when I started this podcast four years back, the founder provider I think Habi something like this, and she he was the first CEO of the company and they were like. Precede pre product market fit revenue. And I've seen using their product for the first time, having a trial, like 14 days trial, it was not as good as like it's world apart. Like, now of course they have funding, but they're the only platform in conversational AI that is doing conversational AI for enterprise. You check it out, right? Dot. There's so many of them that are doing like a really good product and they have a product led strategy, product led sales, and all of this. In enterprise, it's becomes so hard to do that and we'll have more of these conversations when we meet. So now talking about you know, making sure that at some point, you know, you need to ship the category versus like, and you talked about banking I know that there's so much a big difference between the banking in the US and banking in Europe. So like regulations and all of this. So. How do you find the right balance and the security component of it as well, and serving enterprise V in the value say that, Hey, you need soft type one, you need SOC type two. So how is that playing out too? So how big of a challenge is it, you know, serve in a highly regulated I would say customer segment, which is banking. You know, after healthcare. So how does it feel, like, how do you see it panning out for scale? I know you don't need a lot of numbers, that's the best part about enterprise. But you can spend like months and quarters to, you know, you know, get through the sales cycle and everything. So I. Viktoria Izdebska [00:24:34] Yes. How we did it in Europe first was we got ourselves the biggest bank brand there is. Worked out the whole process with them of regulatory restrictions and all the GDPR compliance, et cetera. And then based on that, we're able to scale within the banking world. So we basically had one. Flagship customer and basically that we were able to spread. In the US it was way easier. So we started cold calling into the US and that's how we got our first banking customers. So basically we had a cold start at first and then started working with referrals. Okay. And based on the fact that we already had to be so regulated to work with European customers, we started with the harder market. Europe is for sure harder to get customers for than in the US. It was easier for us to, to then get new customers in the US. Adil Saleh [00:25:24] Okay, perfect. And of course you're gonna be meeting a lot of these customers in that segment onto our event as well. And there's something that I'm thinking about maybe we can have you a 20, 30 minute session where you can, you know, have like, come up with some presentation or you maybe Q and A or maybe sit in a panel with some other founder talking about these problems. Yeah. Perfect. Yes, perfect. I would love that. Love that. So, Viktoria. My team threw a lot of questions for you. Now thinking about resources, like, there is a new notion that is growing especially in the Silicon Valley because the programmers and engineers has been the most expensive in the world, you know, in the Silicon Valley. So now the founders are thinking like. What are a players, what's the definition of a players? Because if you hire somebody like one in two years of experience in maybe the same industry versus somebody five, six years of experience, that the source of information using LMS and all of this is. You know, kind of, kind of equal and they can figure out troubleshooting and question answers and reasoning and everything. It is so hard to have the right bet on on, on people versus dollar amount. Of course. I know. I don't hate to say it because at the end of the day, the startup problem is to get the best work out the out of the people for the best price. It's as simple as that. So. How do you manage that? How do you basically identify, is there any kind of playbook or any internal kind of evaluation process that you guys have? And what was what actually worked for you for the engineers that you have on your team? Viktoria Izdebska [00:26:53] Yeah, so there are two, two insights that I have that I share with founders a lot. The first one is how we attract someone that, for example, has two offers on the tables. One being joining the Salesforce AI team and one being joining us. If he has stock options, let's say from the Salesforce AI team and the stock options have a strike price and then it's gonna go up and he has these stock options for, from us as well. We can present him that The upside in our case is way higher, not because of the brand name, but because of the pace of our company, the speed of how we're building, the speed of how we're expanding and winning customers. So he will be part of a way. Higher velocity with than working with us and working at a corporate company. The second thing is. I prefer to tend towards generalists with very high values. So we are very value driven at our company. More than if someone has worked at X, Google X Facebook, whatever. Why is that? Because I believe a generalist has a stronger motivation for learning as much as possible. He has the need to learn as much as possible in a very short time. And from what I've realized in the past the people that we had on our team that were x. Insert very well known brand are usually the ones that have other expectations and that come from a different mindset into a company which is not always necessarily a builder's mindset. So for us it worked the best especially in sales, product led growth marketing to insert generalists. That want to focus and learn in a certain topic. And when it comes to engineers, we've usually hired from our network, from the network of my CTO as well. He's been the CTO at many previous companies, was offered before he came to us, a seat at a billion dollar company and decided to come to us. So he has a great network of many great minds that he can attract. Adil Saleh [00:28:41] Absolutely. And also he has like, he's this senior so he knows like, you know who to be technically and make sure that they make the right decision. Exactly. 'cause it has, it, it is harder for somebody like non-technical as like non-technical co-founder, like myself and you to, you know, figure out like let's say that they need sort of a prompt engineer or full stack engineer or backend engineer for next years. I mean, we can evaluate for the motivation, commitment and all the soft skills, but it is equally important to, you know, evaluate them on a technical ground as well. And you guys do some sort of assessments for the technical evaluation or what? Viktoria Izdebska [00:29:17] Especially when it's an important role. We like to start working with a person as a contractor first, seeing their work pace, seeing how they act, seeing what, 'cause usually when someone's. Starts as a contractor. The interesting thing that we see is they come into a company and then they identify all the issues that they wanna solve straight away. And based on what they identify as issues that they wanna solve, we get a lot of insight on how they think about efficiency of certain processes, et cetera. And based on that, we can then reevaluate is it a person that we see ourselves working long term with that we even see ourselves giving stock options to or not. Adil Saleh [00:29:50] Okay. Interesting. Love that. And what about last question that, you not been able to raise fund or you did not raise fund. Is it a good news for you or a bad news for you? How do you want to go? Like, what's you guys like playbook and you want to go bootstrap? I know it comes with a lot of freedom and you know, a lot of things that you have in hand and you can play openly and you can, of course you can pivot the way you want. Versus but not so good of aging investors that push you and sit on top of your head every single day. And you gotta explain and build in reports and sheets and everything. You don't hire A CFO, but you have investor that actually inquires about everything. So how do you see this differently? What's your viewpoint? Viktoria Izdebska [00:30:29] So we've up until now, basically been able to bootstrap. The only people that we have on our cap table are very strategic angels. I'm very happy to say that we have, for example, Nick Davidoff on our cap table who's a super connector in the Silicon Valley. We have an a 16 C Scout on our cap table that helps us with connections, intros, strategic and meaningful insights. So we're very blessed and we've proactively chosen who we wanna work with. It's harder to get someone of the cap table than to divorce someone, is what they usually say around Silicon Valley. So, we've been very diligent about who we wanna work with and who's the person that I wanna call at 1:00 AM saying everything goes downwards or everything goes upwards. Who's the person that I wanna celebrate with? So it's been an active decision to basically bootstrap up until now, but we're open to talking to funds. We have been worked talking to funds and building a network in the VC scene. So we're not necessarily averse against taking on a fund in the future. Adil Saleh [00:31:19] Love that. Love that. Any thing that makes you excited this year? I know we are almost done with the year, like eight, nine months done. So, but what makes you excited? Like in your, like, personal intuition or like, product wise, business wise, commercial standpoint. Anything that makes you excited. Viktoria Izdebska [00:31:35] Yeah, product wise the new developments make me very excited. We're gonna launch the self use tool in a few weeks. So this is something that's gonna, all the product led strategies that we've product led growth strategies that we were gonna implement or something that's gonna excite me the, mentally moving to the US is gonna be something that is very interesting for me as well, which is a process for us getting a network there. I have been in the US for the past two months now. I've built up a network of many great angels, investors, entrepreneurs. So this is something that excites me too. Talk to a lot more like-minded people and love that. Adil Saleh [00:32:05] Love that you, you'll see a lot of overseas. Even I'm an immigrant as well with a business visa. But you'll see a lot of these folks that are, you know, we are still in talks to apply for oh one category, like that Ice Einstein visa. Yes. That is more so like a lot of founders, they actually got it last year. So we can definitely connect you with those folks. So Viktoria, it was very nice connecting with you. And you give me a vibe of like, kind of, somebody that is like a sibling or something like that kind of vibe. It's hard to explain, but I love the way that I like that, that you put in. Energy that you put in and I'll definitely mean October 28th. And thank you very much for your time. And energy was infectious. Viktoria Izdebska [00:32:45] Thank you so much. I had a lot of fun. Adil Saleh [00:32:48] Thank you. Have a good rest of your day. Bye. Thank you so very much for staying with us on the episode. Please hear your feedback at adil@hyperengage.io. We definitely need it. We will see you next time and another guest on the stage with some concrete tips on how to operate better as a customer success leader and how you can empower engagements with some building, some meaningful relationships. We qualify people for the episode just to make sure we bring the value to the listeners. Do reach us out if you want to refer any CS leader. Until next time, goodbye and have a good rest of your day.