Building a Go to Market Hub That Connects Sales, Marketing and Customer Success with Ronan Bray

Speaker A: Welcome to APAC's B2B Growth Podcast by X Growth. I'm Sheen Hoda and um, on this show we're going to be unpacking trends, busting myths and delivering insights you can put to work today to drive growth in apac. Here's something most marketing teams get wrong about AI adoption. They roll it out top down and wonder why no one is using it. Today's guest learned that lesson the hard way after coming back from two weeks of having taught himself vibe coding, then telling his team to build a project in a week with almost no explanation. That guest is Ronan Bray, head of marketing growth at cloudassess and this is his second time on the podcast. Ronan takes us through how his personal AI experiments turned into a company wide go to market hub connecting sales, marketing and customer success, why his team still keeps humans in the loop on every piece of content and where he thinks AI still falls short from image generation to handing over the keys to a paid ad campaign and account. We cover all of that.

Speaker B: Let's dive in.

Speaker A: Ronan, second time on the podcast, mate. Welcome back to uh, the show.

Speaker B: Thanks so much for having me back and good to see you again.

Speaker A: Last time, uh, was, was a few years ago and I feel like a different world. When uh, when we caught up last time, it was before all this AI stuff and uh, and everything that has kind of changed in the marketing landscapes. I was really excited to kind of get you on the podcast because from memory and the conversations that we always felt like you were at the forefront of it, very practitioner wise, like you were practicing the newest thing, the most recent thing versus you know, people who talk about it or don't talk about it. Right. Or kind of more traditional approach to marketing. I always felt like whenever we chatted I felt like you were uh, you're like, I'm testing this thing and I'm testing that thing and I'm doing this thing with LinkedIn.

Speaker B: Da da da da.

Speaker A: So, uh, really excited to chat a little bit about what you're doing today and I do want to have a bit of a focus on AI and uh, and what is going on in your world today when it comes to AI.

Speaker B: Yeah. God, there's been so much change. Yeah. Appreciate the complimentary sort of words. But I feel like now, whereas sort of felt like I had a good sort of grip on some growth tactics with marketing, now it feels like you're at sort of not even 1% with what's available thanks to AI coming along. But yeah, we've, we've rolled out a load of new AI features and capabilities within our team. But yeah, as you say, anytime you go onto LinkedIn, there's hundreds of new ways that you could be deploying that and exciting things to test out.

Speaker A: Yeah, or, or uh, or a lot of, a lot of uh, kind of hot air as well. I do want to kind of dive into a little bit of your journey and what you've gone through and, and then, you know, where things at right now. But before we kind of do that, can you give me and everyone who's listening a bit of a glimpse of what are you doing with AI today in kind of your marketing function and in the organization?

Speaker B: So uh, I'd say we have a few different sort of streams and it all comes like across our team got team members like across the world operating across like SEO and content, PPC events, product. So we've sort of tackled it in stages. I'd uh, say the biggest one that we've done and being a remote sort of team not only within our marketing function but as a company as well, uh, like we've got, got other team members across like Asia and Europe was about how do we bring everything that everyone's working on together. Uh, and so I'd say that the biggest adoption of AR that we've had in our team is the build of a go to market hub. Um, so that's bringing together sales, marketing and our customer success teams not only with what they're sort of working on to give visibility across those teams, but also this sort of knowledge and experience and intelligence of that uh, to sort of upskill and enable everyone within our company.

Speaker A: I want to dive into this, but not just yet. I want to hear a little bit about, you know, what, what was your journey of kind of getting to here? Right? What did you kind of go through when were you like, hey, I need to give this thing an AI thing a try and really explore this. Um, and what were kind of those stages that you personally went through? Because I think a lot of people who listen, you know, they've either dabbled in ChatGPT or Claude or you know, kind of played around with it and we all see it on Linked of people talking about the amazing things that they're doing. Walk me through that. What was, what was Ronan's journey on getting on the AI bandwagon?

Speaker B: Yeah, well, I think first off was like through personal adoption when ChatGPT first launched, just using it for everyday sort of tasks. And then it was around like, I think the first sort of big driver was the first time you're logging um, onto LinkedIn and saying this is how I'm using it in marketing or sales, that it starts getting you to think, how else could I be leveraging this right now? I think for a very solid few months I, uh, was like just building up a list of like, I've seen this cool thing on LinkedIn. I, uh, want to test that out. I ended up having a list of like a hundred things and like a hundred bookmark saves from LinkedIn. And then I was reflecting, I was like, how much of this have I actually tested out or done? I reckon maybe 1, you know, 1%. So then it was a matter of, okay, I really need to just focus on, on getting skill in one sort of tool here. And originally that was chatgpt. We were using that at work as well, had like a business plan for that. But then we switched internally to Claude. So yeah, I think it was first really just honing in um, on um, getting skilled in one tool first because there's just so much noise, so much distraction and it does feel like um, all these other people are doing this. Uh, I'm so far behind I'm never going to be able to catch up with that. So I think that that was the first point, like to say, okay, I need to get skilled in just one tool for now. Uh, so that was Claude. And then from there I was using it more for just sort of everyday tasks. And that was really good, like a big efficiency uplift. But then it was like, how can I bring in the knowledge and skills of the other people in my team and then the wider sort of company? And I'd say that was more so over, uh, the most recent like Christmas break that I had two weeks off to really just stop doing all the other sort of day to day work. And that was then more so when I got into like vibe coding again. This was starting to pick up as a new sort of trending thing. Didn't know much about it but I was like, I'm going to dedicate just this full day today to sort of learn around capabilities around that. And again I personally find when I can do something like personally with this, like personal adoption, that's where I can learn very quickly. And so at the time I was really getting up, uh, we just moved into our new house just over a year ago and yeah, maintaining our lawn was a big thing. And I bought, bought all these products and it had all these different like application times, application amounts, it's like across the year, uh, I was like this is too complex. Let's use this as the first project. So that's where I jumped into Lovable as like their, um, vibe coding tool, just to start with that one, and built out this, this tool within like an hour or so that had this whole schedule built out, uh, with like reminders all set that I could share that with my wife and visibility. And I was like, this is so cool. And I think then I spent the next three days just building that out to then build in like a pet care scheduler in there as well and a home care, like maintenance. My wife and I just constantly have like, lists of things like repeats of like vacuuming and all those sort of tasks. So we consolidated this into one platform and that really just opened up like, this can do so much. And then it was like, okay, how can I now build on, um, doing at work into this sort of capability? So that was sort of my journey. And I remember coming back into work on that first day, being so amped to go, and then I'd started working on a tool in the meantime. That, yeah, that was a learning journey as well, because I came back so excited. And I told my team right, by the end of this week, everyone has to build one single project in Lovable from like, their specific areas. And yeah, I, uh, didn't communicate that very well because I had gone through that sort of learning journey in those two weeks, but they had no idea. And yeah, so that was poor communication on my behalf, but it was just. The excitement got. Got the better of me. But that was a good lesson in itself as to, like, how you take someone else on that journey and to where they are now. Like, they're all building out their own tools and coming to me with new ideas. That's the exciting part of it.

Speaker A: Okay, someone listening to this, it's like, this guy is a, like a big time high achiever building lawn management systems and pet care applications. I love this. And, um, and uh, I want to come, come to the team in just a minute. But I think it's such an interesting thing that you bring up where hey do a project that it's, you know, not as rigorous or kind of personal interest. I found. Building applications with Claude code was definitely one of those for me, where just went through that process and built an application for a nonprofit organization that I'm in. And, uh, and then everyone was like, what? And I was like, I learned a lot as well. Right? And then kind of bringing that into the organization. Such a great example. But tell me a little bit about the team. Because, you know, I know I, uh, know this. There's some truth even for us, right? When I kind of go to the team, like, hey, we're gonna, we're gonna all really build capabilities on Claude code or, you know, some other platform. There's always a little bit of resistance, right? Just like you said, you have all this excitement, and you've gone, uh, through this, through hours and hours, right, because you've kind of sat down or I've sat down, and you've worked on something for half a day, which is four hours. You've seen what's possible, that excitement has built. And then you try to communicate that again, multiply that by multiple days, and then you try to communicate that to the team in 30 minutes.

Speaker B: Yeah, tell me.

Speaker A: Yeah, if that. It's like 15 minutes. Uh, now you guys go, hey, this is slack message. This is a tool. Go ahead, build a project. Tell me a little bit about kind of adoption across the team. And, you know, obviously the starting point was Ronan's really excited. Go build a tool with lovable. What happened from there?

Speaker B: Yeah, that's pretty much exactly what it was like at the end of a, uh, team meeting, I was like, right, this is the task for this week. And there was that, uh, I, uh, wouldn't even call it hesitation. It was more uncertainty. Like, where do I even start? I'm not opened this tool before. Like, you're saying it's really easy, but I don't even know where to start here. The way I went around that about that was completely wrong. But how I've gone about it since with the team is understanding. Like, I asked them to list out, like, where are you spending the most amount of time in your day or week? And what here is repetitive and most importantly, like, what information would you love to have that would really help you do your job a lot better? Are, uh, there, like, blockers that you've got? Are you waiting for someone else in another part of the world in the company to get back to you on things like, what are those things and what's the ideal end state here? And don't think about, like, what I think, you know, this, this might be possible or not. What is, like, this is the absolute ideal outcome, uh, here. So I had them sort of working like that, and then based on that sort of scoping out what that sort of build and project could look like. Uh, and then also leveraging, like, we use Claude across the company, leveraging that to, like, sort of map out your idea, get some feedback, and also Important thing there is like what have I not thought about this? Like prompting Claude or Lovable or whatever tool you're using. Like what else have I not thought about here? That would be a really helpful feature because that spins up some great ideas as well. Um, so yeah we've, we've done that uh, per sort of department or team. So like we've now got one for our ah, content and SEO team, uh, uh, or uh, paid marketing team and uh, then one for our uh, events and uh, product team as well.

Speaker A: When you say we've done this for X Department, are you saying like you ran some sort of a workshop of like hey, what is the, is that, is that what you mean? Like when you say we've done this

Speaker B: for these departments, we're pretty much just working out of like a Google Doc or from a meeting session like this, just like brainstorming ideas and getting it ultimately into like on Google Doc of like here's the tools where I get that sort of data from. Here's the actual data or information that I care about here. Here's what the ideal outcome or end state of that would be. So for example, that each week I'm getting a slack message with a summary providing all insights of deal reasons coming through, where those leads have come from. What's the amount, what's the breakdown by segment? Are there any trends this week uh, as opposed to what we're seeing last week or last month? That would be ideal for me. Right. That's where we sort of got to like what's the end point? We're trying to get to here and then leveraging AI to sort of work back from that endpoint as to where do we need to sort of plug in what those sort of gaps are. And so that's what we've done successfully across the sort of AI tools and platforms that we've built.

Speaker A: And is the format that you're talking about, is that something that you iterated on of the way that you would run the, whether it's a workshop or you know, on the Google sheet, was that kind of different from the beginning or you had to kind of iterate on that and there were things that you're like, oh this doesn't work, we should, we should modify it in this form format.

Speaker B: Uh, I wouldn't say it was even that structured like just to a basic of like what tools are you using the data you want? What's the outcome here? Like that is the simplest sort of format we were working from. And of course like we've had multiple iterations on each of these builds since then. But you find out over time, like even week to week, like I'd love to have now this data as well. And then. So you're just building on that. So yeah, it wasn't even anything more than that, like a, uh, 3 dot point format of. That's the information you need, uh, output you want. Yeah. So super simple.

Speaker A: So take me a little bit through. What does the stack look like right now? Right, like what is, what is a team? You've talked about Lovable, you talked about Claude. Are we talking about, you know, the chat? We're talking about Cowork, we're talking about Code and if there is anything else from a stack perspective. And is this stack different across different

Speaker B: teams within the marketing team? The two main sort of tools that we're using are Claude and Lovable. So, uh, I'd say Claude more for your, uh, everyday sort of use. And that we've built like um, the equivalent of our custom GPTs or Gemini gems that we've built those sort of custom projects or like a cowork build, but where it's involving multiple team members. That's where we turn to Lovable that we're collaborating on Lovable, like individual projects there.

Speaker A: Tell me a little bit more about that. Why that, why that is.

Speaker B: I think one is just the visual element of it and that effectively you've got like Claude models and the other AI models built into Lovable. So you're getting that sort of conversational interaction with it, but then also the visual just immediate. And I'd say it's more so as well that we've, we've picked this one tool. So rather than trying to go with like Claude code that then I need to upskill myself a lot further on that. Like I've built a WordPress plugin with there, but I've not really done much else with Claude code because I've just wanted to focus on one tool, which I've picked Lovable. And now that the team's familiar with that, I don't want to go and say right now go and upskill in this other one if this is already working for us. So I don't want to cause that sort of distraction. And this is why we picked sort of small projects first, that I wanted the team to just build out. And I was expecting like not much at all in that first week of building, but I was really impressed even from the poor sort of communication I gave M to them or sort of training around that what they were able to come up with and then it was about meeting with them to understand, okay, what else can we do from here? So the fact that they adopted it with very poor communication or direction from me immediately, this is the right sort of tool that uh, everyone can pick this up really quickly. So that, that's the reason we've gone that sort of route.

Speaker A: How are you using Lovable for example for generating blog posts, right? Or kind of making sure that it knows your tone of voice and, and your brand guidelines and all that stuff. And it's like here's the, here's the outcome. Are you using it in that format or is it, you're purely using it for vibe coding?

Speaker B: No, we definitely use it for that sort of intelligence. Not to the sort of extent of write this blog post for me or anything like that. It's more for the connector of all the data and sources that we're using, uh, to output it uh, into a sort of format that then is easy to use in that everyday day to day sort of work that we then could use Claude for. So this is where we pull together all of our sort of intelligence, all this sort of how it sort of could look and then if we need to adapt that. So for example we've connected a uh, lovable project to like Google Search Console. We've connected it to our HubSpot as our CRM. We've then also connected it with, to our blog. So it comes with tools like Fire Crawl that can scrape websites as well. And so we've got that set up to be like okay, what sort of inquiries are ah, coming through. What are the reasons that deals are being created from the sales team? Go and look this up against all the blog content that we've got and identify where the sort of gaps or opportunities are. So for example, like you've previously written this blog post but uh, this latest deal which is similar to these other four deals, are talking about this now that blog post doesn't talk about that. So that's a good opportunity to go back and optimize that post. Or uh, we've seen 10 deals come through talking about this specific need. I've gone and crawled your website or your blog, you've got no blog post talking about that. There's now an opportunity to go and write a good post that then is matched to exactly what's coming through and driving sales opportunities for us. So that then gives us the sort of idea and um, we've built that now so that it creates these suggestions and we can add that to a sort of schedule for the next month. But our content and SEO team will then look at that schedule and then they'll use their sort of Claude to map out the sort of outline of what that blog post would look like. But we definitely human intervention in there. It's not. Go and write this blog post for us and auto post it to our website. We have absolutely human intervention with everything that we're doing.

Speaker A: Tell me, tell me, is that because of quality? Is that because you haven't had time to build the system? Is that because you just have seen that that's necessary? Why, why is, why is that one

Speaker B: like you can just tell immediately when something's just AI generated? So, uh, we like having that sort of human touch, especially on M content. We want that to sort of be unique. I think you can constantly be training that around, like, so tone of voice, brand guidelines, and we do have aspects of that in our Claude setup. But I think there's always going to be that part of like human knowledge and intelligence that would be missed with AI until you're continually training that model. But to be like, yeah, I remember several posts I wrote about that that would be relevant here, or this anecdote that I saw on LinkedIn over here, whatever it is, having that human touch, I think is really important just to separate. Yeah. As I say, you can tell when something is this AI created versus human created. I mean, algorithms are changing all the time, but from what I've seen as well, I think that's favored and the algorithms are smart enough to know that this is human intervention on us.

Speaker A: Yeah, I feel like, ah, I feel like I, I squint a lot these days. And what I mean by that is I read something from someone that I know that they usually write themselves, but then I'm like, I don't know. This, this part of it really sounds like Claude. Yeah, it's like really sharp, you know, and, uh, Claude. I feel like Claude has a tone of voice of its own. For example, because I've done a lot of kind of content writing with, with, with Claude, where, you know, for example, I record a video, so all the content is coming from me and I'm like, hey, have a look at my video and repurpose it. And it repurposes it and I'm like, ooh. So I've done multiple of that. Initially it was like, yeah, okay. But as you get more and more comfortable or more and more exposed to it, you're like, ooh, I can see these patterns. And it's not really me. And then you start to see it in other people's posts and you're like, oh, I don't, I don't like this now. I want to, I want to move away. Which is kind of what has happened, what happened with us. I want to hear some use cases, right. Like we touched on some as we were talking but want to dive a little bit deeper. But before doing that is have you had to put any guardrails in terms of like from a security perspective, right. Did you have to put anything in place so that, I don't know, the team is not exposed to prompt injection or you know, or anything else? Was that something that was on your mind? Did you do anything?

Speaker B: It was definitely a concern but like Lovable has a lot of sort of security like built into it as well. We made sure that for each of these builds, if we were exposing any sort of, or publishing it to any sort of publicly accessible domain that we've got like uh, our Google authentication on it, so it's only accessible and lock that down to our uh, domain and even something like that. I think that sounds pretty scary, but you can literally prompt Lovable to say, lock this down to the domain that is say cloudassess.com that no one else outside of that can access this. And they've continually added security measures to that that you can scan your build and it will identify any vulnerabilities that you can then again through Lovable, just go and bulk update all those. So yeah, it was, it was definitely concerning at the start that we're, you know, pulling in data from all these sources like things like our CRM and stuff like that. But yeah, I think the way that these tools are built, uh, there's some really good security already built around that.

Speaker A: All right, I want to dive in and talk a little bit about use cases. So take me through like what are some of the stuff you mentioned right at the beginning, the Go to Market hub. Let's start there. Tell me more about that.

Speaker B: Yeah, for sure. Like if you want I can do a quick screen, uh, screen share. Just.

Speaker A: Yeah, we're going to have the recording of this as well so make sure to check out the recording of it. But we'll try to maybe explain it if somebody is not, doesn't have the uh, the, the video on. But yeah, please, let's do it.

Speaker B: I can't show you everything here because you know, a lot of this is sensitive information but it should also give a good sort of view of the type of information we've Got in here. So like looking down the left hand side I've built in what our go to market plan was which is our company plan for the whole year that includes like goal tracking like KPIs that we've got set across each department and with that as well say around like net new ARR or return or retention ARR and things like that, we've got all those numbers pulling in live from HubSpot uh so that we can be tracking in real time against those goals around like sales enablement. We've actually built in this deal guidance section uh and even the ability to build sales decks here. So we've got all of our sort of deals like syncing again from HubSpot, be it in an open pipeline or closed one. And this also then goes and references other parts of our uh, platform like case studies, competitor analysis that we've got that our sales team can come in and use that deal guidance or this AI chat down the bottom to say like uh, I've got this prospect or I'm working on this deal, these are their sort of requirements. How can I go and win this deal? And it's then looking across all the data in this platform to say well you've mentioned this competitor, here's our competitor analysis on them. We beat that same competitor in 10 other recent deals. This is the thing to talk about. These are the features that sound relevant to them. So yeah we've got that all mapped out in here as well. So even things like uh, product expert. So this lists out all the different sort of features across our platform. Again this all gets surfaced in that chat. Other areas in here as well like you know events that we've got coming up that we can switch across and get more detail on each of those like webinars and trade shows. Case study is also another big one that often they're published to a website. But for the feedback from our sales team was it's difficult to find 1 the case studies and 2 like what were their specific use cases. So we loaded all of those into here as well. I won't click on these individual ones here but this will also then reference um these are some deals that this is going to be relevant to and then other parts of our business as well like from our product, our product team use uh notion to track all the features they're working on. So we then integrated that with uh, with this platform as well. Uh, that we've got like a roadmap and then we've got feature releases. So if I click through Here we can see like what features are coming out. And then for the sales team or customer success team, you've got like the highlight of what that is. Here's all your enablement material around, like screenshots or videos, uh, linked to in product as well. And then because again we integrated this with HubSpot with this little filter icon, it's flagging. This looks relevant to 56 deals in our pipeline. I can't click on it, but if I click into this HubSpot Deals, the sales team can then filter that feature by deals that they are working on themselves. So it's about like connecting all this intelligence across our company into one sort of location. Yeah, there's a load of capability I'd love to be able to show, but I can't. Uh, but even things like trending, like deals that have been closed one over specific periods, you can apply filters to that and it will give an AI summary or insights of like, we're seeing this sort of trend here, uh, or this is a good opportunity over here. And then we've got this so that the team can make additional requests that if they want more information they can submit it here and that comes through to who we've set as the admins of this platform.

Speaker A: That is really cool. That's really, I mean the whole, the other like piece that you said, hey, this is, the feature has come up and this is relevant automatically identify. This is relevant to. So is there uh, what, what is kind of the feedback from sales? Is that like a gong or something like that on the sales side that kind of populates the information? HubSpot or you relying on the sales team to kind of put that information in?

Speaker B: No. So our sales team have got extremely good at when they're creating deals, uh, to capture that information, they're actually leveraging AI from that. So when they do like a meeting recording, they're getting the AI transcript from that. And then we have a, uh, methodology for creating a deal that they can automatically pull that sort of information across into that deal creation reason. And then all of that information then gets synced across to this platform. So yeah, like everything it comes down to like how quality is your original data. But I feel like our sales team have got to a place that quality is really good so then we can serve out a lot more insights because of that as well as when they're closing a deal and explaining like how did we win this deal? Who were we up against? What were the features that really separated us? And again that surfaces then in this is the highlights for the past 30 days or 90 days is additional sort of opportunities we should be going after based on that.

Speaker A: Thank you so much for sharing this. I know sharing stuff is always a little bit tricky, um, especially kind of internal organizations data. So thank you so much for kind of taking us, uh, take us through that. The other question that I want to ask is in your journey of kind of get getting to where you are right now as an organization or kind of the marketing function, what are the stuff that you tried that you like? Actually this is not that good. This is, this is not going to do what I thought it would do.

Speaker B: The biggest one for that has been around like image creation and video asset creation. Now I'm testing out a few new things at the moment like with uh, a Higgs Field MCP or even Claude's latest Fable model. Looks pretty advanced around that. But from what I had tested with that it was pretty poor. Like we went through a recent website rebuild, like complete rebuild recently and I was testing it out for that. Yeah, what it was coming out with was, was a long way off. Uh, and I was like there's definitely things that AI is not going to replace humans with anytime soon. I'd say from what I'd seen so far that was definitely an area that felt well short.

Speaker A: Have you tried, you know the other thing trend that you see people talking about is I've connected it to my Google Ads, you know, ad manager and it's now managing everything or to my LinkedIn and it's managing everything. I think you and team do a fair bit of kind of paid advertising as well. Is that what are your experience in that area?

Speaker B: Uh, I would as well say it's not there yet to be replacing that. I don't think from my experience anyway I wouldn't be having AI replace anyone in my team. I want it there as like their assistant. I want it there as their sort of intel and idea sort of prompter. But I definitely want that human intervention. So we, yeah we definitely do a lot from a paid marketing point of view. But again now we've just connected like Google Ads. Uh, we've connected it to other tools that can be like scraping landing pages or competitor reviews and things to surface insights around. Here's some opportunities that we should test out and that that's how we're using that from a paid point of view as well. Like at the moment real focus on like what tests can we be running like every three days from a paid point of view. And again we've Built a lovable tool to do that, that it's again scraping deals that are coming through and leads that are coming through. Data from uh, like Google Analytics, data from our Google Ads to surface. Like here's some potential gaps or issues to address in your account. Here's some new sort of messaging or landing pages that you could be testing out based on what we're seeing coming through from a deal point of view. But I would not be personally trusting it to be like yeah, go ahead and spend whatever you want with uh, our uh, Hooked in account.

Speaker A: Uh yeah, these are my credit carries, my credit card. Go wild.

Speaker B: Yeah, I mean when you've got the owners of like these AI, uh companies coming out and saying you know, it's probably 60, 65% accuracy, I uh, would not be giving it access to any of my accounts, like paid accounts with things. Fair enough.

Speaker A: That's I think Eric, and that's a good call. Tell me a little bit about events. You said you know you've kind of incorporated this into how the team is running events as well.

Speaker B: Mhm.

Speaker A: What is, what does that look like for now?

Speaker B: Like it's like a person on my team. Helen has, has built out like a custom Claude chat there for how she'll sort of structure the events as well as like for say webinar formats that she'll load it in with all the sort of context and using that as well to generate some decks which are really, really helpful from an AI point of view. How we're doing it more so in our uh, go to market platform is just giving that visibility to the team so they can say like what sort of events are coming up, what's going to be potentially relevant for them to be promoting prospects to attend or from our customer uh success team to invite customers to. So yeah it's more around that visibility from a team point of view in that platform. But Helen on my team, she's using Claude to then use the sort of custom one that she's done around formatting

Speaker A: and deck building, what's coming for what's on your radar and you're like, you know, this is the next thing that I want to do or tool to explore or capabilities to build.

Speaker B: I definitely think that the main one is around like image and video generation. So that's what I'm testing out at the moment because that is what is such an expensive sort of part of marketing and uh, time consuming as well. So just testing out sort of new uh, enhancements and new MCPs and things around that to see how Close we can get that to being quality output as well. And I think as well just consistently finding ways to connect these individual tools that we're building across the team into that one sort of central view which is uh, go to Market Hub and yeah, really consistently asking our team to give us feedback as to what extra information would they like to have and how can we then build and expose that.

Speaker A: I understand, you know, the cost of image and video production, but where are you seeing or planning to kind of use that in?

Speaker B: So our team releases features at a ridiculous rate, uh, like multiple a week. And so we're wanting to improve the communication of those feature releases not only to prospects but to customers as well. Uh, and finding ways to do that in an easily sort of digestible format. And I think video is everyone's preferred sort of media type for that. So yeah, we've, as part of what we've already built, we're capturing what those sort of features are, uh, and loading that into this go to market platform like with automation. But if we can then build that extra piece of like here's all this information converted to a video that's in our brand and tone and style, it's going to be helpful for sales enablement and then also helpful for customer enablement. So that's the sort of next sort of piece that I'd say is being super valuable.

Speaker A: That's so cool. So basically reading what the feature is, potentially logging in, walking through it and then producing that video. That's um. That sounds awesome. That sounds awesome. Yep. Uh, that's great. Ronan, is there anything else that I haven't asked that you think it's important for us to touch on less of

Speaker B: a sort of question and more just from what I've learned, I think just start with one thing. Like I said, I picked a personal project and uh, since then I've gone and built out other personal projects. Like anything you're seeing like day to day, like our friends are like constantly like what any movies or TV show recommendations? So I was like, cool, let's, let's build an app for this. So that's. Yeah. And constantly adding to that, that it's like a Netflix style app now, but you can see recommendations across your friendship group. I just start with something like that. Like start with something small. You can literally use it for free on, on a tool like Lovable or Claude. I haven't done extensive tool builds with that, but just seeing what's possible, then you will start thinking, okay, how can I start translating this? So uh, just Start with like one tool, one idea, and build from there. Rather than doing what I was doing and being like, here's a hundred things I'd love to do. And then you do none of it.

Speaker A: Are you. Have you become known as the. As the guy in your friends group, as Ronan? Ronan has an app for that kind

Speaker B: of guy, that really annoying guy that keeps asking. And then it, um, comes up now, like, someone will message saying, any. Anyone got any recommendations? Like, I build an app for this, so go and, uh, sign up for that.

Speaker A: Are you. Are you getting feature requests from your friends? Is like, oh, actually it would be really cool if we have this feature and if we could upvote these videos or movies and stuff like that.

Speaker B: I've only got one mate who's actually been a good collaborator on that. The rest, like, don't expect me to be submitting stuff here or, you know, submitting my reviews, but I'll absolutely use it. But, yeah, I am that annoying guy in the group that's constantly been like, let's just build an app for this. Uh, getting amped up around that.

Speaker A: So good, so good. Ron, it's been an absolute pleasure having you back on the pod. Thank you so much for everything that you've shared. This is, um. You've definitely put out some very valuable information. I've taken heaps of notes, but, uh, yeah, I just want to say thanks again for coming on the pod.

Speaker B: Absolute pleasure. Thanks so much for having me.

Speaker A: We hope you enjoyed this episode. If you like APAC's B2B Growth Podcast, please share it with your B2B friends and subscribe for weekly insights on B2B growth across APAC. Sign up for the XG Weekly Newsletter. Link is in the description. Description Apex B2B Growth Podcast is produced and edited by Alexander Hipwell and music is by the M. Mysterious Brake Master Cylinder. We'll see you next time.