Episode Transcript
Kyle James (00:01.346)
Hey, welcome to the AI Chronicles podcast. I'm your host, Kyle James. And today we'll be talking about how a software company called Better Pick is using AI inside of their own business. And we'll share the exact steps that you can take in order to implement AI for yourself. Now, before we dive into that, listen closely. Are you looking to implement AI inside of your own company or maybe just struggling to get your AI to stop hallucinating? Speak to GPT Trainer. GPT Trainer literally builds out and manages your AI for you.
eliminating hallucinations for good. Go to gpt-trainer.com. I promise you, it'll be the biggest time saving decision that you've made all year. Trying to set up AI on your own is like trying to build a house from scratch. Sure, you could do it, but the time of frustration is going to take you to get it finished and may not be worth it. It's a thousand times faster and safer to hire professionals. Schedule a consultation today. Once again, that's gpt-trainer.com.
Today I have with me Ricardo Ghekiere is the CEO and co-founder of Better Pick. Better Pick is an AI driven professional headshot imagery company. Since launching back in December of 2023, within the first 15 months, they achieved over 3 million in revenue and climbing all while operating profitably without any external funding. Really excited for this conversation today. Hey Ricardo, welcome to the show, my friend.
Ricardo Ghekiere (01:28.331)
Thank you, Kyle, for the introduction. Thank you for having me today.
Kyle James (01:33.198)
Sure thing, man. So thanks. Been busy for you lately. I know that so, but to give us a little bit of background here, like tell us about better pick. How did that come to be? And like, just give us some context of how you founded the company.
Ricardo Ghekiere (01:46.007)
Yeah, the company actually, so I always have to say I didn't co-found the company in that literal sense. It was not there from the origin. I actually started passing by the newsletter. been looking to buy companies from years ago when I decided to, I always wanted to have a software company, but I realized when I was trying to write JavaScript or I went through these scores, I'm like, am I going to be the best coder in the world? That actually, you know, the answer quickly came like, no.
What am I really good at in the whole marketing and business sense? Yes, but coding, won't work. So just want to know the basics. So I realized, okay, I need to approach this completely different. So this is also when we started the marketing agency. Let's like, let's build some buffer here. Let's get some reading marketing down there and then use that in order to do something on the software side. And when it was on a website called site project, it had been there for like one or two years and I saw something passing by.
It was Better Pick, which basically said AI headshot was for sale for about 20K back in the days. And I was like, oh, that's interesting. And I thought about this news case where I was like, if I would ask myself in five years and my kid would come up and say, hey, what was the process of you going to get your professional headshots? And the reply would be, I need to go to a photographer, that I need to dress different things, and I need to do some makeup and the whole thing, and that takes two, three hours.
That's kind of weird. Like, you don't want to explain it to your kids. So when I saw that, was like, technically, everybody, single person in the world could actually benefit from this. So when I saw that opportunity pass by, was like, OK, perfect. That's the one that we need. So yeah, we reached out. They wanted 20k. I bought it for $1. And that's where we started from.
Kyle James (03:24.13)
Yeah.
Kyle James (03:32.332)
Wait, so you bought it for, they wanted 20 K, but you bought it for a dollar. Like how did you, got, man, I gotta ask, how did you buy it for a dollar?
Ricardo Ghekiere (03:37.249)
Yes, exactly.
Ricardo Ghekiere (03:42.305)
Yeah, so, you know, most people always think about value in the current time, right? What is it worth today? But I approached it from a different angle. It was like, because, you know, we had a good chat and so my co-founder today was the one selling it. He was a CTO, still the CTO today. And I was like, do you really need 20K today or is it just that you don't have enough funding in order to grow the company to the next level?
And he's like, yeah, it's actually the second I really want to do this, but I just don't have enough funding to keep sustaining because it was doing about 1.5K per month, which is like enough to get a little bit of cash, but not enough to reinvest. You're kind of stuck in that cycle. And I was like, here's my approach. I will buy it for a dollar. I will give you back shares accordingly. And I'm going to invest a minimum of 200K into the business.
that to make sure that your shares will be worth a lot more than the 20K that you're asking me today. And so he of course got an offer of 20K as well. he's like, I actually want to think long-term. I believe in the value that you can deliver. Fast forward right now, I think that was still the right choice to do. But yeah, that's how I approached it. I said, let's look at the future value, not at the current value. And about one year and a half later, I would say the share is a little bit more than 20K.
It's in the 20k and that's it.
Kyle James (05:02.54)
So, so, know, like, initially, like, it's like, you were thinking, okay, I could go and kind of build it from scratch, like do all the scripting and the JavaScript and like all the coding, you just say, okay, why can't I just not, maybe I'll just buy it say, so you bought it for a dollar and the promise of like, Hey, let's build it together. And then you scaled it from there. What did you do? Like starting from the first couple of weeks, months, like even that first year, like, what did you do to really transform it to where it is actually.
working well and selling more than it was before at just 1.5K per month.
Ricardo Ghekiere (05:34.603)
Yeah. So, you know, what every person should do at 1.5K is basically test the product and kind of see what it is. And so I remember that moment. So I bought it first of the summer, 2003. And then, you know, Christmas came along, announced it to my parents. My partner was there. Like my brother with his partner was there. We have this chat around the fire and then like, it's like, announcement, you know, I bought this company. This is what it does. And gave everybody a free code. And I just watched everybody just like,
doing user testing, just sitting there going through the flow. It was horrible. Like it took them 10 to 15 minutes to just create the account, do the settings, get the selfies uploaded. Like it was horrible. And then the results came about, you know, back in the days, was like two hours later, everybody came back and it was like, what the hell is this? Like, I don't even look like this. So the product was definitely bad. Like to quote somebody is like, it looks like a school project.
That was literally the real phrase that I got. was like, that's fine, you know, because if ours looks like that, and the industry is so new, that means other people are also at that stage. So I wasn't worried about that. I always believe in the people and the person that can actually build something and then compound that over time. And so the first thing was just really bad. The first seven months, I called them the valley of debt because the product was so bad. We had a refund rate of 10%.
that people would be shouting and I was like, I don't come like an alien. I live so bad. It's horrible. What is this user experience? And we're like, we know, but you know, we kind of have to go through that phase in order to get to the next promised land in that sense. So yeah, first month's horrible product. And that's also why we couldn't really scale that quickly because we really had to work on the product while also what we call building the foundation. with the marketing team, with the grow team, we really didn't focus on really scaling. We focused on foundational work.
And foundational work for me was a few categories. The first thing, we did a whole re-haul of the website. It went from school project to what you're seeing right now today. That's basically the whole work we did. We had a designer working on it. We had some marketeers building the landing page, building all the blocks. The use case base, so we really built the foundational work. And the second thing is we had a huge implementation of data and marketing automation.
Ricardo Ghekiere (07:52.791)
Every time we would do something in the platform where you would get stuck, you would get an email from us trying to help you out. And then the third one is customer success. We knew that the technology, even now today, wouldn't catch up to a certain point. It would take about two to three to five years to really get to the point where the technology is good enough. So we implemented 20 % customer support just to make sure that we can help people out if they get stuck with the technology.
So I would say foundational work went first and before we could actually go to scale.
Kyle James (08:24.608)
Yeah. When do you think, so making all these changes, I mean, I love the story that by the fire with your family, like, is terrible. I love that so much. Love it and hate it. used to say, but when do you think it, it like making all these changes implementations, when do think it actually like it changed where like, revenue is coming in after like this, this certain checkpoint. was like, boom.
we skyrocketed and it made like it now it was just easy. Like when was that point and walk and kind of paint that picture for me what that was like.
Ricardo Ghekiere (08:54.615)
Yeah, that was September 2024. And the reason why is that we were doing about September, August, we were doing about 10 to 20k over the summer per month in that sense. And so I remember having that discussion and in August 2024, a new model came out, a foundational model, as we call them. And foundational models are basically, it takes millions to build, so you don't build those in house. And it was a foundational model called Flux from Black Forest Labs out of Germany.
And I remember having that discussion with my co-founders, like, this is a new model. Do we want to take a leap of faith and go for it and take a bet that this is the one that is going to be better and improve a product, or do we want to stick with the old? And so I'm always the guy that's like, let's just go all in, basically. So I'm like, if we believe there is a 1 % chance this is better, let's just jump on it, basically. Screw the old model. Let's go for the new one.
You know, at that point, if you're doing about 10, 20k, it's a lot without being a lot. And so you can still screw up and say, OK, it didn't work out. Let's go back, basically. So it was a bad without being like a huge bad. And so we took that path and everything changed. Like the quality was much better. The output was better. The refund rate dropped. And people were actually happy now. They were shouting. And they were, I got the first LinkedIn message saying, hey, this actually worked really well. Thanks. like, yes.
So that's when we did about 30k, then we went to 50k, and our goal was to do 50k by the end of the year, and we closed the year with 110k per month. So that gives a little bit of idea. That's like September to December, it just went up.
Kyle James (10:31.864)
Wow.
Kyle James (10:36.888)
So that, that, that I want to, I want to backspace here a little bit. like on, when you made that transition from like the current software you're using and then you're like, Hey, there's this new software, the flux and the black forest labs. Like, like there was hesitation, obviously. I think you would agree with that. Like what risk, like, what was it that, that was on the table as far as like maybe money or time or like of like, Hey, like, I don't know if this makes sense for us to move forward on this. Like, what was that risk factor that you were weighing that was maybe initially preventing you from like.
taking a quick leap into saying yes.
Ricardo Ghekiere (11:09.367)
Yeah, I think, know, in any, especially in the AI space where things move so fast, the risk, there's a few risks that you're taking. The risk is of course, if you're doing this, you're not building the old. So it's like, it's like building a house and then suddenly you're, see an opportunity where, and you're like at the foundations, but you, still, the house didn't finish and then you look to the right and there's like a plot of land. You're like, oh, it just came free and it's much better. I know.
if I would build the house there, there is so much more value I can get out of the house. That's basically the reasoning that you're holding. So the question is then do I stop? And even though you've built on top of that already and have like a little bit of foundation, do you stop that and say, screw that, move to the other one and build there because you believe that's gonna be where the future value of your house is basically. So that was the choice that you're making. Do I stop and put everything on hold and move there or do I continue here?
but maybe the value will never be as great as the house that was built next door. That's the risk that you're taking.
Kyle James (12:10.496)
Ricardo, if you didn't see it the way you saw it back then and you stayed on that current foundation and kept building and didn't jump to that plot of land that you're talking about, do you think you still would have gotten the same results and ended up in the same place?
Ricardo Ghekiere (12:27.145)
No, absolutely not. For sure. Probably would have gotten there because in my head we always win. It's just a matter of time. And we would have gotten there little less faster in that sense. I mean, we would have still won, just not as fast as we wanted to basically.
Kyle James (12:43.118)
Take a little bit, just a little detour. You really don't, it's not scenic either. So walk me through a little bit here on the AI on the back end. like you have this, I got to play around with the software a little bit. It's like I uploaded like a couple of photos and then it generates like all these images. Like, so what is actually like, what's happening that's causing the AI to be able to actually do this and produce these good high quality photos.
Ricardo Ghekiere (12:48.535)
You
Ricardo Ghekiere (13:09.463)
Yeah, I think it starts in what we call three steps, right? The first step is the quality input. It's a little bit like if you want to do a report of any sort of kind, you kind of need to have the good quality input. So probably if you went through a flow, you'll see that we would give you a score per image and we would give you real-time feedback on this is a good image, this is a bad image. So that's the first step. If you put bad quality in, you get bad quality out. Then from there, it goes into a model. create like a little, we call it like a little AI model of you.
We really basically transform your images and we create a new view basically in that sense. And from there we generate a bunch of images. And just like a photographer, like if a photographer would come to you and take some shots, they would come in and do like 200 shots, but they would not deliver you to 200 shots. They would just like rank them on what their favorite is, send them over and say, okay, these are my 50 favorites. We're basically doing the same thing. We take about 200 shots.
We look at them and before we show them to you, we will say, compared to the input that you gave us, this is the one that doesn't really look like you. So we will discard them automatically already. And then we're going to show you the 60 images that we believe fit you the best in that sense. So that's really on a very simplistic way what's happening on our site.
Kyle James (14:26.39)
Yeah. And, and from there, like they say, they identify like a certain amount of photos, like what do they pay for like per photo? Or is it like a group of photos? Like what exactly they do from there? Like once they find the photos that they they've gotten, they like, should say.
Ricardo Ghekiere (14:39.297)
So in our model, I think there's two categories in our game field. So the first one is the apps, I would say, where you pay like a weekly or monthly subscription and you can kind of do like photo shoots. You can transform yourself in a baby or kissing yourself or whatever it is. We're not in that category. We're in the category where we only do one thing and we do one thing very well. And that's professional photography. So with us, because the action of you getting a photograph is just one time.
We don't charge you monthly. We charge you one time fee to get your professional photos. That's it. We don't believe to, we don't really believe to have a recurring model when the action that you're trying to do is not recurring because it isn't one LinkedIn headshot, right? To get it once, upload it, that easy. So you just pay us one time.
Kyle James (15:23.126)
Hmm.
Kyle James (15:30.456)
That's cool. I love that. It makes sense. That's a good concept, like mindset to have there too. Like if it's just the one time that like people need it, like for a LinkedIn or for, you know, some sort of resume or whatever it might be just, or even a speaking engagement, just get it one time they're done. They need to get more. They can always come back for more. So it, and I guess walking into the next couple of years, I mean, you've, you've had a lot going on. you sold your previous company and, you've got your hands in some other, business,
Ricardo Ghekiere (15:47.799)
Exactly.
Kyle James (15:59.682)
business prospects, upcoming AI initiatives, what do you foresee happening in the future and where do see AI playing some of the biggest role in your operations next?
Ricardo Ghekiere (16:12.395)
on the operation side around what we're building next.
Kyle James (16:15.982)
Let's start, let's say what the operations side first and see, then afterwards talk to me about what you're building next.
Ricardo Ghekiere (16:23.767)
I'll give you a very clear example of how we're using AI into our own operational workflow. So we have our, what we call our backend where, you you almost say our customer data lives is connected with GPT. And so our customer support actually just has access to their own GPT. And whenever a refund needs to happen, or they need to have some information about a client or an action has to be taken, they can just chat. They can just say, Hey, this client reached out.
what is an MPS for if it's lower than three, give them a free credit or add X or create a company for them or, you know, this person needs a little bit of more credit for the studio that we have, the I see that we have, please do that. And then the GPT will actually do that and handle that. So that's like a concrete example of how we're using it for customer support or customer success. I think another one of customers says we have a tool called Crisp.
They scan our website every single day. If we do a new article, it's scanned as well. So if people want to like self onboard themselves or kind of self help them, they can just type in the question on our website and they will get an answer from our GPT in that sense. So I think on the customer success side, I think that's where we use AI the most inside, internally in the company.
Kyle James (17:42.35)
Yeah. And on the future side, you talked a little bit about like some of the other companies that you're, you're, building out. what, what, what are those visions that you have planned out? That's worth sharing.
Ricardo Ghekiere (17:50.933)
Yeah, I got this question from Nathan Latka where he's like, okay, as a capitalist, you what's next? And it's like, okay, well, so on the better pick side, that's definitely one, but we always thought about, okay, what, you know, what we have this technology layer right now, where else can we play where we have, you know, a strong advantage in that sense? So we moved into the photography market or in the fashion industry markets, because building photography is something we've been doing for the last one and a half years, two years.
Moving into the photographic market is one more recurrent so people have just new clothes, new things coming in. It's a recurrent model so it's a recurrent need which means that you can actually charge recurring and it's something that is a huge market that is very untackled right now. So that is basically what we're moving in right now and on top of that we're also using Better Pick to move into the virtual try-on. We actually have to compete with Google now which is fun as a small European player. So people are now using
using it at Better Pick to go shopping and see how their clothing fits on them. So that's basically how I spend my weekends. It's like testing out new clothes. Like, that actually suits me well. And then just buy it.
Kyle James (18:53.868)
That's cool.
Kyle James (19:00.95)
Oh, that's cool. I love that. definitely. Good luck to you on competing with Google. I'm sure, I mean, that's the thing, right? If you niche down to your expertise and you know the space, like that's going to give you the leg up. And you know, there's so much market value, especially the reoccurring side of the fashion industry, trying on clothes. And as we start wrapping up, Riccardo, man, it's been awesome having you on the show today. Where can people learn a little bit more about you or maybe a little bit more about better pick that you'd recommend them kind of check out next?
Ricardo Ghekiere (19:31.159)
I think if you want to get like, because we're quite transparent over metrics, we share more metrics on a monthly basis. If you want to do that, connect with me on LinkedIn so you get to follow the journey behind the scenes. What's happening, what's going wrong. Also there, we'll also be announcing our fundraising very soon. Probably August and September it's closed off, but we're just waiting for a few things to close up. So that's also going to happen. And for the rest, just check out Better Pick, get your free headshots. I'll share some codes with you so can distribute them across your members.
to give them a test.
Kyle James (20:02.606)
Cool. Awesome. Love it so much. Great. Having another show, my friend. And let's keep in touch. Hopefully have a good on the show. Probably for future businesses, I can see it happening. Maybe more, uh, uh, conversations around the fire fireplace with your, with the family is showing them some new software. So, and, uh, no, think, I think you will knock it out of the park, man. That's so cool. Well, Hey, thanks so much for being on the show. And remember for those listening in, thank you so much for listening. If you're trying to implement AI.
Ricardo Ghekiere (20:17.303)
I got something new how bad is this? not again.
Kyle James (20:32.344)
Please don't try and do it yourself. The time of stress that the AI could cause, it may not be worth it. Schedule a call with GPT Trainer and let them build out and manage your AI for you. Once again, gpt-trainer.com. Signing off for now, thank you so much, everybody, for listening in and looking forward to seeing everyone on the next episode of AI Chronicles.
