Ep # 151: Revealing the Million-User Milestone from Day One ft. Simone Macario (Founder of Sharly.ai)

[00:00:02] Simone Macario: We were really not prepared to accommodate this much users. We closed the first year with about a million users onboarding on Sharly, and this was amazing. But [00:00:10] Taylor Kenerson: 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. [00:00:30] Adil Saleh: Hey, good mornings everybody. This is Hyperengage podcast again. Long waited with a lot of new stories very exciting stories because we kicked this button and, and make it really swift in the last three three months because I know that a lot of these new technologies are coming out and, and, and two years from now, three years from now, just like in the past. And even in, in, in a bigger term now, this, this time around they will be you know, really successful businesses that are going to you know, serve two messes. So that's why we are more focused towards you know, startup sitting between the Prese to series in the first three years. Most of them are pre-product market fit. And also you know, we've definitely encouraged team to, you know, come up with, with products that are serving that like unique and less. Tech enabled, AI enabled industries. Previously we had like, you know, product serving and manufacturing, climate change, a lot of this. So, today we have the, the founder of Sharly.ai. It's it's AI first platform that is helping teams to better. Manage their workflows you know, you know, achieve operational excellence with with, with making sure that the information exchange and information sharing becomes seamless for for, for organizations and teams. So, thank you very much. Morning for taking the time. [00:01:41] Simone Macario: Thank you eo. Thank you for inviting. [00:01:44] Adil Saleh: I love that. So I know that it's it's in this day and age, if you are even if you're not technical founder or you have an idea, you, that's something that makes you excited. You live with the problem. It is not hard to, you know, build something. That can deliver value. And, and even though it, even though it breaks three, four downs at scale, you will know and you will have a lot, lot of technical people alongside you that can help you for, for the problems of tomorrow. So how did you come come across Sharly? What was this section? What made you actually jump into this segment? I know that it's challenging because a lot of these competitive, yours are 3, 4, 5 more x more funded than you. The finding teams are more capable or more have more bigger peer group. A lot of these challenges, a lot of these founders doing myself think every single day for, I mean, to get some positive energy, not negative energy, but sometimes you get in that bubble. So how do you cater all of this and how did you start with shirley.ai? [00:02:37] Simone Macario: Thank you for the question Adil. So, first of all maybe I might share that I have a technical background. I thought when, when it comes to the problems that we are facing today in the, in the field of generative, I, of course we have a very smart people. That is always a step ahead of you. So this rush to try to make up with them, it's it's something that you keep bringing inside of you while, while you keep building. So, I answered shortly about a couple of years ago and the idea was was very simple just came out and in a conversation with an investor, we were looking to try to solve one of his. Problem. And the problem was this, he was overloaded about information coming from companies that he invested in. And he had a, and he had the need of having a quick access, a quick way to go through 120 pages of audited financial report from a public estate company or another. And and through this conversation we realized, hey. A tool that acts on top of the knowledge and is able to ensure that every answer is generated strictly from that specific content. But not only is also able to refer to the exact sentence where the knowledge has been created, a source of knowledge has been, has been shared. That would be awesome. And that's what we did. We put up in a couple of weeks, a first prototype of tool that we successfully launch it. Okay, so [00:04:08] Adil Saleh: your, your first customer was actually your investor. [00:04:11] Simone Macario: Yeah, our first customer was our investor. Exactly. And the MVP came out in in a matter of really few days, less than two weeks. Mm-hmm. And and since then we, after the lunch I mean I think I guess it was the right moment and we started to acquire so many users that we could even accommodate all of them. At that [00:04:29] Adil Saleh: time. Absolutely. I love the fact that you know, a lot of these folks back in the years, I would say not long ago, five years ago, it was more like a norm that you have to have customers that can pay you. In the beginning mm-hmm. Then people were shifting more. And now at this time, I think it's just my opinion that your niche customer. Don't have to just pay for, for your product or service, but they need to be desperate for you to build and solve their problems. And and of course it, it's quite a similar story as, as you mentioned, I know that you know, a lot of these use cases that you think. For that particular customer at that point of time, and you're building a prototype and getting it validated for that I know that in, in some it is harder to do it at scale and you go, go up market and, you know, find more people and, you know, go to market becomes the challenge. I, I'll come to that a little later. Now, thinking about the technology that you built. I know that at that time I'm just guessing that two years back Chad, GPT building a layer la large language models on top of those conversation, I was at a point that you can absolutely summarize. You can get achieve some sort of contextual efficiencies to these documentation that that take a lot of time to read. It's a lot of literature, so you get you get, you get your product to summarize it and get the next maybe sort of next sections or key takeaways out of those documentation. That are a hundred percent accuracy, how big of a challenge accuracy was at that time? [00:05:46] Simone Macario: Right. So, I think back then the challenge was was limited to the small context that the LLM was providing. Right? If I don't mistake, the first version of 3.5 was less than 10,000 token in terms of content provided for, you know, acting on, on on, on your content. And, so the fastest way to go back then was implementing a rag system that allow us to overcome the content, the, the context limitation, but also allowing many file types to be processed. Of course, we are talking about the very first month. Of of, of chat GPT and the first, very first month of what Sharly ai was back then. Since then, the industry changed, and of course we, we needed to keep aware about all these changing and try to keep building our value proposition on top of new. The, the, the new upcoming, you know, technology mm-hmm. Or models, et cetera. Mm-hmm. I think I think the problem of context and accuracy is still a very actual problem. It really wants to run your very well, your own evos when it comes to to, you know, provide an experience to a certain content. But as, as, as, as many experts are, are, are stating probably we will, we will, we will be able very easily listen to, to see context that, that, that, that has billions and billions of, of, of token available. So, I think I think it's, it's a problem that we are seeing in this very first phase. Of of of contextualize generative AI experiences. But but it's not gonna be possibly a problem for, for the wars that we envision for tomorrow. So when it comes to building your value proposition, you really wants to look somewhere else. Mm-hmm. [00:07:25] Adil Saleh: Interesting. And while you were actually working with your handful of customers in the beginning post prototype, of course you need to build something functional that can deliver value and integrate data, all of this to become a product, I'm sure. Like how long did it take? Like six months, two year [00:07:40] Simone Macario: to onboard the first customers? Oh, it took, it took hours, I have to say. So, first of all, it is very important for the audience to understand that what Sharly is today, it's, it's completely different than what Sharly was two years ago. And, and the reasons that things are evolving so fast that we are in a constant pressure to keep iterating. So, one of the biggest difference that you will notice is that the char in the first days was a, was a tool that we launched on a consumer level. So immediately after the launch, and it was extremely successful, we started to see thousand and thousand of users using Sharly on a daily basis. And, and, and this was amazing for us because we, we, we. We were not prepared, right? We were really not prepared to accommodate this much users. We closed the first year with about a million users onboarding on Sharly and this was amazing. But then obviously we are not talking about the success that JGPT was having. It was on a different dimension, but for us that we started in a very small, humble, you know, place. It was, it was a pretty great success. Now it's also, it's also fair to say that our first version was a free version, so we run on a free version. So one of the biggest problems that we had after a few weeks running was manage the cost. How do we monetize it, right? How do we manage the cost? How do we monetize it? How, how do we create a business model that enable us to grow, right? But at the same time, it enable us to, to per the our expenses. Et cetera, et cetera. This has been the, the product of a love of iteration, and I have to, to to tell you, we are still iterating a lot asto. Today we are predominantly pushing on a B2B model. [00:09:24] Adil Saleh: Interesting because I was looking at the use cases and they were like more for the, for the B2B companies. A lot of these you know, accounting firms, they can they can leverage Sharly Yep. At, at scale. And a lot of academics institutes they can also do that. Now, thinking about go to market, I know that it, it might have took a, took a while for you guys for a bunch of folks that you had when, when we, you started. To figure out the GTM frameworks, like how to price it, how to, you know, then make sure within that price what's emerging. You know, what's gonna be the server and, you know, cost of these L lambs at scale. You never know, like, is that gonna be a usage base or seat base, or how's that gonna play around in economics and everything? Apart from that like. Who was, who amongst you actually jumped in and, you know, think about like, hey, these are the clear customer profiles that we need to, personas that we need to target. We cannot like go so wide because at the end of the day, we need to validate and we need to iterate, and we need to get it to a point where you can, you know, expand. So. What was that point? What was the challenge at that point? I know I did. Customer profile is not something that you would do it in three months. Hey, no, these are the customers you need to go go after you know, tech companies go after, like agencies go after like, these lawyers and legal firms. So what was that process and hypothesis and how did you guys execute that and what was that, that time period? [00:10:39] Simone Macario: Yeah. Yeah, I think you're absolutely right. When it comes to defining, defining your ICP is not an overnight job. I think that is also an iterating process where still today we look for a better, better ICP to engage with. But back then I think the challenge for us was that we launched it extremely far extremely fast, and we acquire so many users that, the paradox that we fall in was that it was that we had too many datas and our, our customers, our audience was extremely fragmented. Not only geographically, we had a customer from Asia, south America, north America, Europe, et cetera. But also in terms of industry that were operating in. And I tell you the truth deciding which one we should have gone first with, it was extremely painful. Because we had a very engaged customer from academia. For instance, individual researchers, so B2C, B2C type of audience that were extremely passionate and they were writing us emails and they were talking about us in the social media and stuff, but they were less likely to pay. But this will stay longer and using the platform longer, which means our cost on that specific consumer was extremely high. And then we had other segment more in the B2B that were probably using us less, but they were having a, you know, a, a value that was higher in terms of monetization. So, so the choice was not easy. We run a lot of custom interviews to understand which one we wanted to, to go first, and and, and eventually we had we, we took the wrong choice. We went through the customer that were paying less, or maybe it's the right choice because they were loving us [00:12:24] Adil Saleh: the most. I love that. It takes a lot, so takes a lot. [00:12:27] Simone Macario: Exactly. So sticking of cha choosing the customer that were liking us and making monetize, we said, Hey, we need to try to play the longer game. And the longer game means understanding exactly what are the problems that are we solving, and how to unpack the solution in all those steps that bring chaos of information to be analyzed, structured. And, and all the CTIC capabilities that are behind the process. So who better can tell those process than researcher themselves that have lot of, because they're actively using the platform every day, day, the platform there fuel is knowledge. They work with so many documents. So we went for there. And fun fact if now up to date, I wouldn't say that we predominantly sell to them. We still have a user base of researcher that help us all the time, every day on improving the product. That means a lot because I have a lot of respect of people that that is in academia, obviously smarter people in the world, and I love to work with them. [00:13:31] Adil Saleh: Yeah, absolutely. And, and now expanding on this, like, I know that a lot of these professors, researchers, even students in of research doctors a lot of these are individually using Sharly at this moment. So, I know that you have one segment that is there's opportunities big enough. It's just some of regulation or maybe some red tapes. To target these, these institutes that every, every student looks looks up to, like talking about MITs and, you know, Cambridges and Stanford. So how you are thinking around that, like sending it to institutes or maybe some departments within those in institutes? [00:14:04] Simone Macario: Yeah, I do. I think what you're describing is the journey that we went through, right? So, we started to work with the researchers and obviously monetization was mentioned. Is is not easy. They generally pay by their own pocket or ideally is the institution they provide them with tool. But those institution are highly regulated, as you mentioned. So there's a big problem how you enter institution by making sure that you are compliant with your system. That's the journey we went through and after a year of our journey, the first year, we started to sell the institutions and we successfully made it. Wow. How did we solve it? How it was a headache idea. I cannot, I cannot lie. But but the way that we, that we decided to go through is instead of going directly, we started to partner with with the channel partners. Channel partner partners already were connected. They were with institution that happily brought our AI power tool inside of universities. And obviously every country. The complexity of institutions that every country has their own regulations. we started from those that has the lower barrier, right? So, some of the university that we are working on, and we have a great agreement and great relationship with are in South America. In Peru, for example. Peru is one of probably the first country that trusted the technology from from, and, and I'm surprised to say so. And I'm surprised to say so because I come from, from, from a region that is, that is, that's, it's, it's Europe that that it's in a sense from the AI adoption perspective is lower than some other countries that I wasn't expecting they were adopting AI at this stage. Obviously my vision is for, for own institution to embraces, to understand the potential and use it as a trusted partner. But having Latin as a, as a market that, that drove at least our confidence to, to tap into academic institution was was a surprise. [00:15:59] Adil Saleh: Interesting story because you, you, you get to explore and then you find your answers. It's just about it. And, and, and I, I, I, I, I hugely respect the fact that you have you've, you've gone and you've trusted people that, that were act actively using the platform. And the, the product that you have today, they have a greater contribution to it. Not in terms of money, but the way they gave the feedback shared across social media to social message. I know that a lot of these, research teams, they're pretty much work, they pretty much work in, in sync with you know, different institutes. So it, it goes like, it goes like wireless. They like something and it, it's something automative processing. You know, that might be one of the reasons. [00:16:36] Simone Macario: Absolutely. And and, and I, and I wanna share that one of my eureka moment or a moment of extremely excitement came from the realization that our tool was not just helping researchers was having an effect on the world and impact it was way larger than the, I could really even expect it. If you know where you go later, you go on Google Scholar or any. Academic paper repository and you type sharply, you will see how many researchers cited our tool within the contribution and methodology that they use for achieve those researchers. Those researchers. So, that's something that gives a thought because [00:17:11] Adil Saleh: research is all about like publishing. It's all about authority. So if somebody has shown authority on a product like Sharly, it's, it's a really big thing. And you know, now even with ai, like, you know, one of our relatives in, in in, in, in text, no, sorry, in Boston they are doing some research in cloud computing and they're working on, large scale, like, global level projects. And it's all about research. You know, you talk about Facebook hiring some researchers recently, you know, not hiring, they're buying some researchers. You know, it's all, it's, it is so much to do with research going forward to solve like big problems with ai. You know, I'm talking about like manufacturing oil and gas as well, like these industries, healthcare as well. So. There's so much of interest after this boom of research. You know, the more you can do, like, Chinese are pretty big at it. I always say like, I'm sure you might have a lot of researchers in China as well. You know, they do a lot of research. They're like so good at research. True, true. [00:18:08] Simone Macario: I, I, I, I can deny. [00:18:10] Adil Saleh: Yes. Perfect. So now thinking about, I know that it's not an easy journey to stick with people that don't pay. But again having the gut and having, having the grit to make sure that you are able to give them a solution and solve their problem when they were small and then they'd be advocate. And, you know, like you mentioned that they, you know, with channel partners, you're now selling it to institute. Now talking about the financial institutes, like, a lot of these, you know, I know that these like big enterprise companies, they don't have it in-house. They have, like, they work with you know, firms they work with outsource you know, firms that do all the bookkeeping and everything. So, and, and also it is also regulated especially in the Europe, European region. So what was what was that challenge penetrating in the, into that industry? [00:18:49] Simone Macario: Right. So, I think financial is the, well, it's a very complex industry. I would say that if I had to go through the ICPs that we are attacking now financial is not one of the major one that we attend directly, but if it happens on a smaller page, we're not working with the biggest one yet. Right. We welcome them. So if the acquisition is organic, I say we are very keen to have a conversation and if the jobs to be done that they're trying to to solve is accommodated by shortly. Absolutely. We, we open up and at least we learn something. But when it comes to ICP that in this moment, we are prioritizing and we are clients. Sharly is looking more into procurement companies. To give you an example, procurement [00:19:33] Adil Saleh: companies [00:19:33] Simone Macario: or manufacturing companies with procurement mentees. And the reason is that they, they, their. Is one of those business function that works with a lot of content, a lot of knowledge that comes from a variety of sources. Could be Yes. An external suppliers, they have to, yeah, [00:19:50] Adil Saleh: they have to restart. They have to source products, they have to hunt products, they have to exactly, you know, create the right vendors. There's a lot of growth. Like you talk about like hundreds of units of different products you know, hundreds of units, [00:20:01] Simone Macario: Coming from different suppliers. And all this. Commentation is never in the hands of a, a single person. You have the category manager, you have the project manager, the operations, and then you get finance, and then you have legal. And each of those has to look at the same knowledge from different perspective. And just to be done, that I have to execute in relation to the knowledge has a variety. Something needs just a quick summary to go through. I don't know, a simple specification. Someone has to extract details, information from proposal. When, when it comes to compliance, you need to validate information from different vendor, right? You need to check what is, the proposal is more convenient. Some proposal comes with some specs and some other, they maybe. The comparisons. Yeah, comparisons. Comparison could be done is tedious. Right? It's, it's, I'd say it takes a lot of time. That's where chart itself, right? It puts everyone looking from different perspective to the same knowledge, but it's struck meaningful insights. They're actionable for each business function. [00:21:01] Adil Saleh: So when you talk about the procurement, the biggest biggest problem that I saw firsthand interacting with some of the, some of the companies myself as a consumer is, is, is the life cycle. The cycle of the entire process is so long, like, you know, is there any ai, whether it's Sharly or anything that you can do or do some magic to make it. At least 20, 30%. That's gonna be a really, really big shift within that industry. And you mentioned that manufacturing all of this, they, they're already suffering with this, like to procure one product from China, like one, like product meaning like hundreds of units for the entire segment. They like take like three to six months minimum. Exactly. To just procure. Absolutely. And that all the comparisons, all these teams and all of this. So how does Sharly, could you just elaborate a little bit more giving some examples that would be helpful for, for me? [00:21:48] Simone Macario: So, as I was saying, in the, in let's say manufacturing, you are in a procurement team. You have to, you know, to be a lot of proposal coming from different supplier. This is mentioned, but let me give you a new example. Even a gov local Go government procurement teams might use Sharly and Y. They have to take decision about anything that needs to purchase for local governments. Like every imagine in Australia or any, take any country, how many CDOs there are, and each of them has its own budget and needs to purchase items, laptops, tables, chairs, et cetera, right? So, making sure that all the, the documentation requires in order to or not. We we in a grant I don't know, accept the proposals you need to, to, to lease a few vendors. Obviously, you cannot just choose whichever you want, et cetera. It's a complex process and you also need to follow each local regulation. So there is there is a regulation layer, compliance that you need to, to follow through. So all the things are, are, are complex, let's say information that, in a normal workflow, a business developer should go through all an operation manager or the category manager better. These, these, those are the, the champions on, in our ICP, they have to go through line by line and making sure that you know. Every line is validated and every information is under control and passes information, package it and pass it to the I don't know, financial teams for them to create whichever charts and strength. So, all this knowledge is always coming from very specific documents, fragmented and passed through one person. The check the channel, it creates insights and then communicates with other people. Imagine how much. Contamination happens through this process. How much bias is this information, how much misunderstanding can be created through this process? Yeah, it's absolutely siloed. It's [00:23:44] Adil Saleh: siloed, like, it's absolutely siloed. Different information with different, it has no context, as you mentioned in the beginning. Like they need to analyze the same information that is that has authority and then they can see it from their own angle. Maybe a CFO looks at it differently. Maybe a, a category manager looks at it differently, leadership then looks at it differently. So this is, you know, so this is important. [00:24:06] Simone Macario: I think, I think you hit the point. And, and our objective, our goal is to create actionary insights for each of them. Doesn't matter which type of business business function they come from. One of the, let's say, most successful example of startups that are, are doing this but in a different in a different industry with a different approach. It's Figma. Think about it, Figma, which by the way is going to publicly sit in a couple of days, if I don't mistake. Yes, yes, yes. IPO they build a tool that is a collaboration tool for product teams. Right. That provides a unified conva for ux, UI designer product designer developer to look into the same information, but receive different sites depending on the function that they have to do. Absolutely. Yes. Yes. And they can take it. [00:24:57] Adil Saleh: It is so collaborate, collaborative, and they can share their, and comment, engage within that. They don't need notion, they don't need, they don't need like asanas or pick-ups. They can integrate within that within that platform and collaborate and share information, even communicate there. [00:25:14] Simone Macario: Exactly. [00:25:14] Adil Saleh: Exactly. [00:25:15] Simone Macario: So we are looking into that direction. This is the, the vision that we are pursuing. But for knowledge, right, for knowledge heavy type of activities. Exactly. And it'll be like, mm-hmm. Canvas, that's for marketing. Think about it. Right? You got marketing teams on board and Canva and collaborating. We are doing it for procurement team, for research teams, for knowledge heavy teams. [00:25:38] Adil Saleh: Absolutely. And all the knowledge that they need, they can have it inside the platform. And all the stakeholders, all the people that need to be collaborative, they are all in single place looking at the information. Even they can engage, they can collaborate like Figma, like Ken, you mentioned. I love the idea. I love you know, is that gonna be a challenge product wise, engineering wise? Uh mm-hmm. How do you see that? [00:26:01] Simone Macario: I, I, I think I think where we wants to win is on the. Experience that we provide to our, our users and our clients. And and if I have and you mention to, to address a technical challenge is that nowadays not only about the user experience, we need to think about agent experience. In the past few months, c Silicon Valley has been all about ncps, right? You cannot be the tool made only for your customers. You need to think about how other agents are gonna use your tool. That's gonna be the challenge. That is something that we're very yes agents, meaning [00:26:38] Adil Saleh: by like co-pilots, like agent agent AI that you're thinking about, like, gen. Yes. So the way, [00:26:43] Simone Macario: so the way that we are looking into and we are preparing for is that today's user customers are businesses, right? But tomorrow's Sharly's customers will be probably agents themself. So it's not just about having a beautiful user interface that provide you a fantastic experience, you as a human person, but this experience you need to be provided to agents that use our tools in behalf of. Okay, perfect. So you, [00:27:15] Adil Saleh: you, to my understanding, it's, it's more like, let's say any procurement teams using Sharly today. Is going to be going to be trained enough as an agent because it's, it's feeding all that knowledge, all that information, all that context for all of their procurement needs. I'm not, I'm not talking about sharing cross sharing the data with customers. I'm just talking about one industry, one customer. They're make, they're basically serving or feeding that information and contacts and training their own agents. To become sort of a, sort of a agentic framework down the road when they can just prompt you know, where they can just prompt let's say an action and it can get done. Is that what you're thinking of? Yeah. [00:27:54] Simone Macario: Yeah. That, that could, that, that could be a way. Another way maybe is you will, you, you will have your AI agent that has your emails and it will have to cross some informations from certain type of documents and generate insights. And to do so, we talk these agents to Sharly, and Sharly we could generate this insight for him and pass it so that email could be sent. These are the type of, just to sim to give it the simplest one. For, for okay. For the one from [00:28:20] Adil Saleh: the set. Gotcha. And you're, you're basically building it specialized for all these industries? Yeah. We're build, [00:28:25] Simone Macario: Not for all industry. Obviously. We are building on, on the side an interface that is let's say it's friendly for agents to be used. Okay. While for our consumer, we, we predominantly work on a, on a UI perspective, ui, ux. Mm-hmm. Which is the [00:28:39] Adil Saleh: user different type of interface. Gotcha. Gotcha. Love that. I mean, I know that we, we got in so deep into the use cases in industries. I, I really mm-hmm. Appreciate that you being pretty much concrete and realistic. Not idealistic. A lot of people, they come up and say, we are gonna lost and we are gonna do this, and it's gonna be a unicorn in three years. Staying grounded and realistic is, is, is, is the real way that keeps you laser focused and you know, it's always, you know, grinding and you know, working really hard in a silent mode. Perfect. So now thinking about your go to market I know it has so much been talked around like, you need to acquire more customers. You need to find a way to. Get, get the customers the lowest cost, you know, to find the challenge. What do you think, what's your viewpoint on retaining the revenue? Because I, I see that retaining the existing customers is, is become a more of a challenge than acquiring new customers. You know, that you can do like with funding and, you know, all of that. But when it, when it comes to retaining the same amount of customers year in year, that has become the real challenge. So what kind of efforts are you guys you know, driving towards. Customer success side of things, post-sales, how much data is involved. I spoke to the team at Gong, actually the, the CCU at Gong when we started this podcast three years back. And he said like, when we were as small as six people, we started investing into data. And ever since then, now we are like big as like hundreds. We are still making every single decision. Data driven around customer success, US g customers officer. So he had like all of these teams under him. So how you are thinking around that, you're kind of at the same stage. What we, we talked about at Gong, and I know there's not a lot of better playbooks when it comes to GTM or it comes to growth Dan Gong. So how do you see it customer success side of things. [00:30:23] Simone Macario: Yeah, I, I think obviously you always want to leverage on data. You want to be as much the driven that you, that you can. And I thought the role, the, the, the fund, the role of the funder is also providing a little bit of intuitions. And he is, he is larger view on the things, which most of the times he's wrong, but it requires a certain level of speed on, on validating or, or the opposite. I think I think we are now. A very interesting moment of, of historical moment for testing a lot of different things. And also when it comes to go to market strategy compared maybe with a couple of years ago you can really test a lot of ways to acquire consumer. Faster than ever. You could implement a quick workflow using make do com for instance, in infection of updates and just run your workflows and and try to, to see if a certain activity or a campaign works or not. As simple as that. There's, there's, there's a, I don't think that we, I don't think that. There's such a challenge as acquiring customer yet today, because we are a really early stage of AI adoption. You would, you, you, you would be surprised to, to know there's a lot of companies that we are talking to is the first time that are approaching AI at all. [00:31:41] Adil Saleh: Mm-hmm. And [00:31:41] Simone Macario: some of those, some of those, they, they probably don't use even charge GPT or if they use this, they don't use it as we use it. That is probably 90% of our time we do coding using either charge GPT or CLO LA model. Right. A lot of company. I mean, there's a lot of business working in a different direction and, and there are not necessary how to say, onboarding in this new type of infrastructure that we call ai. Right? So, market acquisition, I wouldn't say is the, is the biggest is the biggest challenge yet we are still in a phase with a lot of company. Even, maybe, maybe it is fair to say outside of, of, of the valley, outside of the United States is still an exploration phase, if not the education phase. So there's a lot of process in the customer success in the customer success funnel to, to ensure that they fully grasp the entire value. And they don't only focus on a single jobs to be done that we provide, but they are able to explore multiple way to approach our tool. [00:32:45] Adil Saleh: Yes. So now how do you measure it? Like, do you have any kind of, like, if you talk about like post onboarding process mm-hmm. Like how you ensure time to value, to mitigate as, keep it, cut it off as much as possible, and then making sure they're well adopted to the platform and they let's say use it actively weekly, whatever success matters that you have, how you ensure that mm-hmm. To you, like, do you guys have like any kind of customer success organization or any kind of data model the customer feels. [00:33:10] Simone Macario: Yeah we, we, we use a few tools to obviously monitoring all the usage and and try to intervene when we see that there's a, there's a place that it makes sense to, to, to act. But I'd say our advantage in this moment is that at these very early. Stage we're working with great channel partners and they really help us through this process. So, they don't only help us to engage and onboard the clients, they feel accountable and they feel ownership for the client themselves. So, these activities done on on the two of us. Right where we make sure that we engage with the customer and understand that what are the problems that they need and how we really can accommodate their, their, their, their, their needs with our solution. Well, the channel partners really take cares of all the communication process, et cetera. We do a lot of you know, during the onboarding we do a lot of, tutorial. We, we provide a lot of tutorial documentation. We, we do this. I would say on that side, in this moment, probably we are two standards. We are going two standards to really be able to, to share with you something that is unique. But but definitely it's extremely important, especially because and it should be a more important, another talk with you because I think, I think. A lot of competition and a lot of variety of tools is coming out. So if onboarding a client is not tough what It might be tough, I thought we haven't experienced yet. Luckily, maybe we're doing something good is retention of those customers. Right? So you want to ensure that the lifetime value of this yes. Of this business is larger possible. Yeah, that's true. Yes. But you know what from. My focus, and I think we are still in the face, that it should be this way. Is product is building, building, building. We have not done building probably will never be done building. And and, and, and this is where I'm trying to, to focus my whole value proposition on other business function. I think they require a lot of attention. I might not be the champion yet, but I'm looking forwards to learn more possibly from you guys and uh mm-hmm. And, and, and see how we can help our customer together. [00:35:15] Adil Saleh: Yes, and retention is, it could be a problem for tomorrow. A lot of founders, they think the same way. And, and, and I appreciate that. But thing is you need to for this is the kind of process. You don't have to do it for scale. You can nail it by doing all things like. Maybe having one account manager taking care of, checking in with every client. They're checking on their usage. If something is dropped, if any customer check champion is not potentially using any power feature or something, just send them a guide. Help guide. Maybe if some client is they not is not actively using the platform just and they're close to renewal, this give the churn signal so you, you know, get, build relationship like old school days. Because you don't have a lot of customers when you have like big customers, when you find a product market fit, you talk about a lot of development that's going on and that makes you excited. And, and it should be like that because you have to beat. The only way that you can beat with an AI first company is by building something really, really good, really, really fast. It's just as simple because people in now that you know, people in China, people in, countries with, with like young population in Pakistan. In India, young population. They're not AI enabled. Like they, they, whenever they grad school, they know about Chat GPT. They don't know about lms. They know how to use like deep research. All of this feature. They're now requiring all this information. They come up with all the ideas and they, they're in numbers. The cost of the resource acquire is, is fraction of the cost as compared to North America, Canada, Australia, central Europe. And they can do it very, very fast. And, and this like this day and age with this capabilities of ai, now this, it's bringing people from like companies, from Asia to the competition as well. So now the competition is, is now more global. It's not just about raising. One and a half million, 2 million funds and you beating them. It's not about that. So a lot of, a lot of things are changing in the go-to market side of things because we've had like more than almost 145 founders talk about go-to market. And over the course of three years, a lot has changed. You know, how you retain the customer and retention has been the biggest, biggest problem. And a lot of these teams, they're recently, like I started this podcast as a customer success podcast. I wanted. I had some hypothesis that I wanted to validate with some people. It was more like an interview style podcast. I brought on these leaders that are doing it at scale, and then I started like jumping into these emerging startups like yourself and a lot of these Y Combinator back companies, Techstars and Chem, all of these, and. What I, what I, what I saw during this full time is that customer success as a category has been on the downhill and it's now merging with with sort of, you know, sales. Like, you know, you talk about customer success. Yeah. The biggest biggest company is barely a billion dollar company. You know, the, the industry leaders, I will name them, but you talk about the CRM category, you have Salesforce, you have HubSpot, you have a DO, you have a lot of, lot of more coming. More coming. So the category as on, on a whole is, is been merged. It's not something that, it's, people don't care about it because it's the net revenue retention is, is the biggest problem. We need to make sure that you retain customers. A lot of these you know, you talk about custom plans and enterprise stands, you're just selling it to, you know, big procurement teams of big oil and gas and manufacturing. Maybe to acquire them, you'll have, like, you'll have to pay the entire value for the year. And then when the renew the next year only then you start making, making some, some, you know, some, some money out of that customer. So it is, it become, it becomes even bigger challenge the customer success. So I love the way that you're thinking about about those and doing it in old school. I would suggest doing it in the way that's, you know. I would say like the, the oldest, like old school Steve Jobs is, but just do it. Make sure that you know, who are your healthy customers? Who are the customers that are going to churn, forecast them. And like, there's like tools that can do it. And and, and make sure your, your your, your customer success. Even product managers, they are absolutely data driven. They already know like. What features actually attract customers and how they align with, with their product vision given by you guys as leaders. So, I love this conversation by the way. Very true. Very true. Yeah. Perfect. So now we are pretty much like, half, like more than halfway down this year. Like what makes excited in 2025? I know a lot of these things, people are not like people that have some tech background, they already perceive. What's coming next? And even now you can really predict like how fast it's coming at you. What makes you excited in terms of ai, like generative ai, conversational AI agent frameworks, all of this. [00:39:42] Simone Macario: Yeah. So, I think well, besides the CPS that we mentioned earlier in in, in this conversation I think there's a lot of tension on what is the next model that opening AI we release is GBT five. There's a lot of thoughts about that and, and. And dimension is gonna be something extremely exciting which, which I'm looking forwards to, to see how we can obviously leverage their capability. So, as you might see Sharly, we, we, we definitely embed LLMs in inside our application. So the more the AI advanced, the more is just the, the things that we can help our customer with, with. So, this is extremely exciting. Besides that. I think I think we're looking into I think we're looking into having more and more automation in our business functions to, to handle from market activity to customer support. And we are looking into doing it just by having agents. Helping us rather than scaling up the team as it was the only way to go back in the days I, I, I'd like to say, right? So when, when, when you wanted to scale any scale, any type of, of, of your business function, before you needed to hire, you needed to, to, to kick off a process that is very complex it it solves the problem, but increase the complexity, the complex complexity of your, of your, of your venture. But, but I think we are in a, in a moment where we will be able to double up our number in a very short timeframe with no increase of headcount. And, and this, I think it's really exciting because it, it, it it creates certain level of optimization and potential that yes that is unique. [00:41:20] Adil Saleh: Mm. Yeah. I mean, what, what's your viewpoint of this? Because this three months ago, we our, our software like tech team, product team, we cut their APLs 50%. And we just gave them a goal that we never know. How are you going to achieve this? Now your KPIs are you know, of course you gotta make sure that you gotta do it in 50% less time. You know, so it's, it's on you. So what's, what's the best way to do that? I know that it's something that you can definitely educate, but when it comes to getting on ground, getting your hands ready with the team and making sure, let's say if something that's sitting on the roadmap for the next three weeks, and you gotta get done in the, in, in, let's say five days or three days. How is that process like how to actually enable these teams? This is my challenge as well, so asking it for me. Yeah. So, [00:42:03] Simone Macario: so, so I think, I think I think nowadays if you are working on a product or maybe it doesn't matter where on what you're working on, I think you really wants to have a team that and, and hire people that worship ai, right? You really want people that is certainly committed on adopting AI in their everyday life to do. Almost everything. And I say almost because I don't wanna exaggerate, but but and, and, and I say this because it really happens a lot of times that through conversation with very smart people that that they're not very keen on adopting it or they have doubts about it. And and I'm saying this wrong, I'm just saying that when it comes to productivity. It is everything but making things faster. And to do things faster, you need intelligence that is able to scale, which is not a human one, right? You want to scale intelligence and serial intelligence is in utility. So the question is, we're gonna take this tele intelligence from, right? How do you have access? Intelligence is able to scale no matter your tive status or your individual capabilities. And the answer is ai. [00:43:14] Adil Saleh: Okay, so you gotta make sure you you have, you know, how to smartly interact with AI to improve your capabilities and intellect and all of this. And Yes. Like, and, and, and you could engineering and all of this. Excuse me, I'm sorry. Go ahead. I'm sorry you wanted to say. [00:43:32] Simone Macario: No, I know. We probably, I heard, I heard your last question. I think you need to risk it even further. Vico is a way to, to go, right? We, we, we are talking a lot about Vico being, there's companies that are just building stuff and great stuff with Vico. I think I think it's gonna obviously going to be more and more precisely output of those tools, right? So if it's happening in code, it's happening in marketing any type. Mm-hmm. If it's happening in marketing, it's happening in sales. So any type of process is going to be handled by specific agents in charge of that function, which means you're gonna have your AI engineer that is gonna just mm-hmm. Build back an infrastructure in just. Starting from your natural language and today it might have some flow, it might have some box, it might be the system that are not enough stable or, or, or scalable. But I would say it's really matter of month. I don't even say years, say month, right Month. We're getting, we are getting there and we see already some success stories of companies that has been built overnight using lovable, for instance, and, and, and being able to raise millions and, and has have millions in, in, in. Right. So, I, I would say this is gonna be more and more common and I, I would dare to say that in the po in the, in the next 12 months probably, we start to see the first unicorn made of two people, three people, [00:45:00] Adil Saleh: maybe one [00:45:01] Simone Macario: person. [00:45:01] Adil Saleh: Yes. I was listening to a podcast where what's his name? I forgot the name. I was the founder of he is now the founder of agency. He building a product more for customer success, like sort of co-pilot for enterprise customer success. And he ex HubSpot X Drift, like he exited Drift. He was a VP of engineering HubSpot in the early days. So he says that it's like it, same thing, like it could be a unicorn founded by a single person. Yeah. Yeah. So it, it is near to possible. It's happening. It, it is happening. No doubts. I was extremely insightful conversation with you. Simone, I am sure in October, definitely once you finalize the dates and everything, definitely meet you in person and share more knowledge and gets more information from you and learn from you. That's the primary purpose of me doing this conversations and making them really, really, I would. Genuine and uncensored. Not like, Pierce Morgan, but uncentered conventional to make sure we you know, we share our problems, we share people's problems, and somebody out in, in the dome room or of, of any university or any startup gets help. And that will pay the price for for, for this time. Thank you very much for, for being a part of this. Thank [00:46:13] Simone Macario: I appreciated your time. It was very fun. Have a good day. [00:46:18] Adil Saleh: Thank you. Appreciate it.. Thank you so very much for staying with us on the episode. Please hear your feedback at adil@hyperengage.io. We definitely need it. Uh, 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.