Matt Best: Hello and welcome to the Growth Workshop Podcast today, myself and my co host, Jonny Adams, we're joined by Stuart Dale from orbital X.

Stuart, thank you so much for joining us on the on the podcast today.

Stuart Dale: Thank you for having me super excited for the convo.

Matt Best: Brilliant, great stuff.

And look, Stuart, you're a successful entrepreneur and founder led go to market SAS teams and organizations on both sides of the pond, here in the UK and also in New York, and real, fantastic success in scaling all the way from, you know, $0 first to half at half a million, and then in a further two and a half years, only getting from that, you know, half a million up to up to up to 5 million.

So congratulations on your career so far, and as a partner of bliss growth, the startup studio, and also founder, of course, of orbital x, it's going to be fantastic to hear a little bit more about your journey, what you've learned along the way.

And then we're going to start to really unpack some of the kind of cool things around brand, the importance of brand marketing, and you're going to share some frameworks and some approaches.

Sounds good, brilliant.

So, I mean, what would be really great just to start with Stuart, is just understand to understand a little bit about you, like, what, what?

Why did you start?

Where you started?

How have you got to where you are today?

Stuart Dale: Yeah, so it's a funny old journey when you when you break it down.

So I started the age of 12 with a DJ business.

Loved music, so started doing events, started trying to make money, and I was always, you know, very entrepreneurial, but I didn't, I didn't have any idea about software.

And then I heard about Mark Zuckerberg and how he became this, like, multi millionaire.

I was like, sounds like, I don't know, sounds like something that could be done easy journey.

Set up a software company through uni, and obviously had no idea it was like, I was born in Glasgow, grew up there, and the tech scene there, certainly years back behind London, and probably decades compared to New York and San Fran and when that struggled, I kind of recalibrated and thinking like, you know what I want to do?

And I got into a sales job where I was selling coffee machines, taught me the art of cold calling.

And you know what it takes to like, build selfgen and have a book of business and to call and I was selling everything from like sashes of milk to like biscuits.

It was foundationally so important.

And then I went, I actually went back and set up another company, and it was a cybersecurity training platform.

And that was like a much better journey.

Sold some licenses, and actually started to connect software with selling.

But it still didn't make me the millionaire that Zuckerberg was.

I was still the TV program.

It was like, everything was like, yeah, that's still the journey.

And then I heard about the job of a BDR, and I was still in Glasgow, and there was a company called yieldify, which, at the time, had just raised, raised off Google Ventures and SoftBank.

It was considered the fastest growing software company in Europe at the time, and the first investment that Google Ventures made into London, and I was like, right, I'm going to go for it.

So I moved back to London from Glasgow.

It was there that that I learned software, and I learned about SaaS, and I learned about building teams, and I fortunately, got moved to New York and had the most amazing few years of my career, not only professionally, but got got engaged and bought dog and survived covid.

So it was like, it was all very, very important.

And then when that company got acquired, I got invited into the venture studio by the founder of unify.

And the venture studio, simply put, finds the founders, helps with the ideation and helps drive the first revenue from from the potential customers that exist.

And that was incredible.

You know that that was five or six companies that came through.

That first cohort of companies ended up having a market cap of about three, 400 million, right when the market was at as high as through like 21 and 22 and from there, I started to see that there was real growth.

But then we had this challenge of of AI coming through, and then the market started to dip.

And the question at that point was, is AI going to replace everybody and go to market?

We started to leverage AI very deeply within, within the venture studio, with the idea that instead of hiring two BDRs for a business at 100k in revenue, we'll just use AI.

And it started to work, and then it completely imploded.

And it kind of made me think, like, what, like, what is the shift that's going on?

There's going to be certain things where AI is incredibly prolific and incredibly powerful, but there's going to be areas that we still require, the human touch, the human thought leadership, the in person experiences.

And that was where orbital X was born.

And it kind of took all of the learnings from the venture studio, all the learnings from the previous 10 years of my career and maybe beyond, to set up an end to end demand generation business for for software companies globally, which really allows marketers to have access to the diversity of skill sets they need, which is roughly 15 or 16 to deliver on the programs that you want without having to increase your headcount.

And it's been, yeah, super enjoyable.

And, you know, can't wait to break down some of the learnings from it.

Matt Best: Amazing.

And just on those learnings, when you reflect on that lesson that you learned around sort of full displacement, let's call it and full replacement, I suppose, of teams in place or AI in place of teams.

What was your key learning from?

That like, what?

What you say that failed?

What are some of the component parts of that lesson?

Stuart Dale: Well, if you think about where venture was right, like when, when we were in New York and when we came back to London, the market was really high, we were allowed to spend $5 of venture money to deliver $1 of revenue.

So in simple terms, to go from zero to half a million, it would be okay if you spent two and a half 3 million to do it.

And that's when the market was super buoyant.

So it was like that.

The market was flush of cash.

The average was about 3x of your of your burn on what you were signing in revenue.

And that was like that world, and it was quite predictable.

It's called the Predictable Revenue formula.

You know, you put in these BDRs, you have these sales reps, you have these conversion metrics, and you triple revenue, or you quadruple revenue.

And everybody, everybody understood that, and investors understood that, and it was a risk they were willing to take.

But as the market recalibrated, and instead of pre seed raising 5 million, they raised 2 million, or 5 million to 1 million, all of a sudden, those burn multiples were just completely unacceptable, because you miss one quarter of revenue, you're dead.

Like, it's as simple as that.

So as the llms came out and open AI in particular, there was this question mark of like, Well, surely we can automate email, surely we can automate LinkedIn.

Can we even automate calls and back in '21, '22 that was probably considered, like, a little bit crazy, but it was that was the thought going through the mind, instead of defaulting to the Predictable Revenue formula, which was like, hire the BDRs, have the sales rep, have the conversion metrics, we just went all in on AI.

So we started adopting these tools, I think, far faster than the vast majority of the global market, because we were in the venture studio that we had to learn and iterate much, much quicker.

And it was in there that I remember it like, super vividly, like, you upload this list, the AI builds the messaging, and you hit go, and I remember doing it, and I remember, like, within about 30 minutes, we got a meeting, and I was like, oh my god, this is it like, AI's here forever, guys, it's changed, like, we don't need to hire BDRs anymore.

And then what started to happen was that reply rates started to drop.

And this is over months, right?

Because when businesses started to understand that where previously to send 50 emails that were custom written, you would have to spend two or three days as a human you could kind of do it within 10 minutes of pressing this button.

So all of a sudden, people's inboxes went from, you know, ah, seems like a really good email, to Oh, my God, like, what is going on?

And and all of a sudden, inboxes started getting super saturated, which meant that reply rates were dropping.

And all of a sudden we were kind of looking at the model, going, this doesn't seem to be matching up, because now the reply rates are down.

We don't have a human to call.

We've not really built any relationships.

And it was like, we're not quite ready yet.

And I think, like, email is getting even harder to drive revenue from, because you've now got aI that's able to detect that it's a pitch, it's a cold email.

So it's getting harder and harder, and that's only really come around in the last, like, 12 months, and that was where we had to make the decision of, like, if that's where the world is going, the way Jeff Bezos, you know, you know, frames, it is like, what's not going to change?

And I think if you ask yourself, what's not going to change over the next 10 years, you can start to get your head around, okay, I might not be able to keep up with where AI is going, but there's going to be certain things which are just not going to change.

Human connection, being one of them, in person, experiences this type of stuff that we're even doing.

And that was where orbital x was, was born, to think about like, if that is where the world is going, like, what can we do?

What can we implement?

How do we drive thought leadership without being at the mercy of the machine?

Matt Best: I love that it's like, what's not going to change, what's here for the what's here for the foreseeable future.

And just reckon, I mean, there's going to be a bunch of stuff in that that we don't know yet, but it's recognizing, to your point, what it is you can do now.

And I guess that's helped you in then creating that structure that says we're going to find that appropriate balance.

And you shared an example of some work you've been doing with a recent client, and creation of webinars and using AI to get 70 80% of the way there, and then that last 20 to 30% is the human overlay.

How does that process work?

Stuart Dale: Yeah.

So when we started orbital X, everything has been completely human led.

So we started with the foundation of, like, what would be the sequential journey to build that marketing program?

Like, what's the 100 steps that takes?

And, you know, even the small detail of, like, the size of the creative or the optimal mix of CTA on a landing page on mobile versus desktop.

And that's all been built out, literally, line by line, almost as its own code base, but it's delivered majority by humans.

But as automation and workflows have become more intelligent, your ability to start swapping out the human in certain areas to then leverage the machine is becoming much, much easier.

And I think ultimately the question is, at what point do you require in a business where you had, for example, one marketer that's able to manage one market?

Are you now moving into a world where one marketer can manage multiple markets simultaneously because of how these agents at workflows now work, and that's where we see the world going, like we had this meeting, actually just earlier.

Today.

It's like, is the marketing manager gone and it's just the market manager.

It's like, can you manage that market and and is that verticalized, or is that Regional Base?

Like, what is that thing?

And I think that's where we are really excited by the innovation within, within AI.

And like trying to be ahead of it, and crucially, like working with our team to tell them that we want to be the masters of AI, rather than abused by AI, right?

It's like we want to be in control of it and not be the by product.

It's like, if we can train our team to become the most amazing agentic users of everything that's going on, we've got a really exciting opportunity ahead of us.

Because, you know, in our world, specifically, like traditional agencies, to hire another customer requires another head count.

And really the question is, is, like with the existing head count, can you 10x can you 20x by using these agentic workflows?

Jonny Adams: And it's really interesting.

I was reading about the word that you use that I've heard of it being a conductor of AI and being able to be the orchestrator of actually using it, where you're on top of it, rather than in it, and feeling quite overwhelmed by it, just for the audience.

I'm curious, because orbital X is all about demand generation, as you mentioned.

And actually, I love your statement about the things that are always going to stay the controllables effectively, which is what we can do, like podcasts and webinars, just for the audience, just so everyone's aware.

What does orbital x do?

So they might support with webinars, they but what are the other functional things?

Just so they can get a broader spectrum?

Stuart Dale: Yeah, the way we think about it is, we work with businesses to see, like, what is your big idea, right?

Like, what is the narrative that you want to get to the market and own and ultimately to dominate the market?

And most businesses talk heavily on their feature and function, like in B to C, marketing, it is all about brand in B to B.

It's all about my feature.

And one of the things that people underestimate is that if you deliver stories and narratives that emote feeling, overthinking feeling is automatic.

So you can, like, grab the attention of your market super quickly if you if you nail that story piece and that big idea is an area where we have incredible creative leaders within our business that are working with businesses to say, what is that story?

What is that narrative we want to take to market, and how does that become the pillar of all content that we then go on to produce?

So that's like the starting point.

It's like, do we actually know the story we're trying to tell, tell to the market?

Jonny Adams: And that's a great point to start with.

Give me an example.

You don't have to say clients names, but just give us an example.

You've met a client...

Stuart Dale: Yeah, I think, like, the example would be that, let's just take, like, CMOs as an example.

If you tell a CMO that my solution helps you increase your ROAs by 13% it's like, oh god.

Makes me feel like, even saying it is, like, a bit like, Oh, it's so in the weeds of it, versus saying, This is how you own the boardroom.

And it's like, I want to own the boardroom.

I don't want to be in the back.

Well, how do I own it?

And it sparks that curiosity.

And it's like, the way we describe it is thinking more about the core narrative of your business being the thread of your necklace, right?

And the thread of your necklace should remain in every story that you go on to tell.

And the stories that you tell are the beads that hang off your necklace.

So they're all bound by this, this golden thread of narrative.

But you tell these stories which touch upon features at points, but also touches upon case studies, and it touches upon testimonials and touches upon where we think the world is going, and it's all bound though, by that narrative where people can still associate your business with the fact that you help CMOS own the boardroom.

Matt Best: And so does that come across in terms of, you know, in practice for the organizations, the companies that you help in a sort of consulting type fashion, or are you, you grabbing this for them and building this with them?

Stuart Dale: Literally building the program.

So I think, like, webinars are a great example of it.

And whether it's a live stream on LinkedIn that you turn it into or, you know, you turn it into a discussion however you want to frame it, but digital events where we talk about, like educating in public, it's low friction for somebody to engage with this type of content, to learn and to discover and to become more knowledgeable about a particular topic, but you've also got things like master classes.

So like, how do you turn that webinar or that piece of content into something which is like more of a master class?

Let me show you how.

Like, let's get into that, and all of a sudden you can build really successful programs around master classes.

The other question that I would say to the audience is like, what is it that your business knows that nobody else in the world has access to we call it the irresistible offer of knowledge, right?

And it's like most businesses are sat on proprietary data that nobody else in the world knows.

And it's like sat in this confine of a platform, or in the founder's head, or whoever, whoever it is.

How do we tell that story to the market, and how do you tell it in a way that gives them just enough to excite them that they still want to come and engage with you and they want to meet with you?

Think about think about Gong.

Gong's go to market has been phenomenal.

What did they do?

For one year?

They never once published a post about their features or their functions.

What they shared was things like, if you swear in a discovery call, you're three times more likely to close a deal.

They shared things like, if you've got four stakeholders.

Soldiers by call two you're four times more likely to close a deal.

And it was out.

It was pushing out this proprietary data that they'd aggregated from their platform to educate and inspire their audience, but never talking about Gong as a feature and function.

And it's like, that's the type of stuff with with these like irresistible offers of knowledge as we describe them, that if you think about it, it's like, what can we actually tell to the market, where we genuinely help them, but we also become a thought leader simultaneously.

Matt Best: I've worked in some organizations in my in my career who have protected that and seen it as their IP and seen it as their identity and seen it as their only value so it's sort of their only value card.

So they so they just go, no, no, I can't possibly share that, certainly not publicly, for fear of someone else stealing

Stuart Dale: Yeah, by the way, I was the exact same.

And I think, like, if you think about where the LLMs are today, large language models and their ability to aggregate information and deliver it to people super quickly, that information is what's publicly available through the internet, right?

And and the question is, is like, if people can find that, and we talk about the information has become democratized, it's so much easier now to become knowledgeable in Topic X or Y.

It's like, what is the thing that your business knows that nobody else does that?

Sure?

The competition might be like, well, we need to go and find those data points.

And, of course, but you've suddenly started to own that narrative in the market, and you suddenly started to control it and show people that you are the thought leader.

And the really cool thing is that some people might be thinking, Oh, my God, that's too much to give you can actually, like, aggregate it in a way that I would call it, like the trailer to your business is an overall movie, you know.

And you can do it in a way with whether it's through paid ads, whether it's through webinars, whether it's through master classes where it's like, you know, we're going to show you, you know, we've got access to the 100 best ways to close software companies today.

We're going to, we're going to show you three.

And then you show them the three, and you say, if you want the other 97 come and meet us.

Jonny Adams: You sort of teased me earlier with sort of like, things that you do, but just from my understanding, Matt's understanding, and everyone else is like, just break down functionally, like how you would help with a webinar, for example.

Stuart Dale: So the business is built up of data, storytelling and execution.

So firstly, we work with businesses, as we said a little moment ago, on the story.

What's the story that we're trying to tell to the market, and why and how do we orchestrate that?

And that's literally to the level of like coming up with the title, the content, the agenda, like the about even with some clients, we go on to produce the slides that they're going to present, because we can distill their story, often far better than them.

Because we're not in the weeds.

We don't, we don't, we don't really care about the feature and function.

We're trying to think about the broader brand that we're trying to elevate on the audience.

We work with clients to literally build the audience that they're trying to target.

And we use a mixture of proprietary data sets that we've created, but also some of the best LLM technology that exists to build your most perfectly highly curated audience based on your niche, your sub niche, or just your broader, horizontal market.

Most businesses will be using a tool like zoom, info, cognism, which is really good to a certain point, but these are snapshots of LinkedIn, so the misinformation, or there's misinformation in there.

So we solve that issue, you know, both through technology, but also with the the data team that we have.

And the third part is the execution.

So you take the webinar, we've come up with the title, the story.

How the hell do you market it?

How do you build audience?

How do you get people to attend?

How do you build the landing pages?

How do you create ads for Tiktok?

How do you create ads for Instagram?

What should it be in the communities that exist in places like LinkedIn?

We then orchestrate that.

We literally go and build these end to end programs, which includes the fundamental deliverables of an end to end, orchestration of these programs.

Matt Best: And also kind of stepping back, something you mentioned earlier, around the Predictable Revenue formula, and we've talked about this previously, and about how you see that as and I guess we're getting into now a little bit more around right?

Well, what's the what's the future?

What should people out there?

What should those CMOS be thinking about and thinking about, how do they take their brand and do what you've just described, but then deliver that an effective way?

And you you describe the predictive revenue formula as the as the concept of scaling a business through hiring more people, right?

Hiring more.

BDRs, more.

SDRs, bums on seats equals more revenue.

What's your sort of challenge to that, and then what do you think's coming through in its place if that's not working anymore?

Stuart Dale: I think the headline is like, if you are not aware that the Predictable Revenue formula is dead, you're two years behind, because it's like, truly dead.

And the reason it's dead is that all of the the models and all of the way that that you previously built growth and revenue for your business typically followed, especially if it was a sales led motion.

Let's forget about plg, but as sales LED is, as you say, it was headcount to hit this territory that was untapped for me to grow revenue by this amount, and then it was right, and then I'm going to bring in a team to do my expansion and and then I'm, you know, and it was, as it's described, as it was.

Predictable.

What you're seeing, though, is because of the things like the issues that we talked about with email infrastructure and inbox has been noisier than ever because of the speed at which LLM technologies can now be built and spun up.

That formula has just become so outdated in the way that you actually build revenue for your business.

An example would be, is if you've still got 50 sales reps, and they're still working cold outbound like they did two years ago.

That's a major issue, and it's because everything shifted.

What llms have allowed us to do is all of a sudden, aggregate information at a scale that previously was impossible or not impossible, but might have taken you like a year or six months or three months.

It's like a crazy timeline to associate.

Simple example would be, let's say you have three competitors.

You want to track everybody that's engaging with their LinkedIn posts.

When they're thrown out thought leadership or they're throwing out content.

Two years ago, you'd have had a human and it might take them an hour to do 30.

Look at 30, check the profile is this, is this right?

Technologies now with llms, allow you to say right?

These are the 100 competitors that we want to track.

I want you to review the last six months of post engagements on their LinkedIn.

I want you to aggregate everybody that's engaged.

I want you to check it against an ICP audience that I set.

And I want you to tell me if it's a fit, if it's a fit.

I want you to find me their email address.

And when you find their email address, I want you to send this email, and it's done like that.

And that's the shift.

It's like, it is insane, this shift that's going on.

And that's just one example, but I would say, like the whole signal led outbound, or some people are talking about Inbound, led outbound is the move, which means that traditional code outbound is gone.

And I think for anybody listening, it's like, think about signals as forms of intent.

Third and second party signals are things like you can see on LinkedIn that there's a surge in hiring because they've posted five jobs, or they've actually just increased their engineering team by 12% these are publicly available signals that have an interpretation that they are a better fit for your business than are worth it.

So if you only sell well to businesses that are growing exponentially with engineering leads, then that would be a signal that you would take.

But there's all other ones.

Like, for example, communities like, who's joining.

The communities about, for example, how to fix code outbound, right?

People are joining.

That's another signal you pull that in.

The Holy Grail is first party signals.

First party signals are proprietary and exclusive to your business, so none of your competition can see or know that person X is engaged with you.

So think about a demo request being the one that everybody can so that's an example of a first party signal.

Other examples are things like webinar registrations, as we've spoken about, content on your website, you can now track through llms really easily, like, who's visiting your website down to a person content downloads.

And basically, what the best teams are doing is they're turning those signals, aggregating different plays off the back of it.

So, like a third party signal is definitely of a lesser intent than a first party signal, where somebody like downloads your guide or your report.

But how do you deliver plays and outbound strategies to leverage that to actually build your demand, and that's on like a new business standpoint.

But the really interesting one is about account management and expansion.

If you're not leveraging llms currently to help you understand the signals of your customers and users, not only on places like LinkedIn.

Are they moving?

Have they actually just hired somebody that could actually rip out your technology?

The one that's really interesting is your own platform usage.

And previously, like signals within your platform, clicks.

You know, who's doing this?

It used to be quite difficult to do it well, but the technology now makes it super easy.

So like, one example that I heard the other week was somebody clicking 10 times on a button to upgrade, and rather than it taking that person to send an email to then be like, hey, like, I can't upgrade on this.

Can you help?

All of a sudden, it triggered an event into the CRM and automated an outbound message, like, hey, sorry, Matt.

Had difficulty jumping a call, and it's that type of speed to then, that's how you renew, that's how you upsell, that's how you expand, just as a few, like practical examples.

Matt Best: You say if we're not using those LLMs, like, what are some of the examples of the actual technologies, of the way that these have been implemented to support clients that you work with, or how you've supported clients to make the most this, I'm still baffled by, what should you be using in what context, at what time?

Stuart Dale: Totally.

So look, if you remove the LLM from the equation, I think the whole point about signal based outbound or inbound led outbound is do a better job of just identifying what they are.

Google it, it will tell you the breakdown, and even if you have to do it manually first, because you don't want to spend money, do it little things like, who's your most recent LinkedIn followers.

Click a button, you'll see it right?

That's a signal that followed you.

Who's the most recent person to like your competitors post, or to even like your other posts like so there's things that you can do without technology, and I think as a crawl, walk, run approach, that's the starting point.

Google it.

Become informed, and look at what you could do out the box yourself super quickly, if you're looking to level up.

Up.

The way that signals work best is that you have your audience.

You identify that my account list is these 500 accounts, which most people will have, and these are the 2000 contacts, and that becomes your like, who you're tracking.

There's a technology called clay.com most people will be familiar with it, where you can upload that list, and then, through the technology, you can put in the signals that you want to track.

For example, you know, is somebody being promoted in a job, but these technologies actually allow you to suddenly start aggregating it in a way that at least you're getting the notification that this is happening.

If you want to get to the more advanced level, it's a lot more custom.

It's a lot more about APIs and scraping and understanding, like, what are the second or third party signals, almost seeing them as like, lead scoring that then says that this person is ready to be approached or not ready to be approached, and the tool that most people are using to enable that, well, the workflow automation is n, e n n, a n.com, but that's like the way that you could get get started.

But I think, like the key bit for anybody listening is likely, if you're not doing some form of signal led outbound, and it's just completely cold, I would imagine month over month, your metrics on meetings boot is dropping, and if it is, it's a great trigger to say to yourself, right?

We need to make a shift in our approach.

And rather than just randomly identifying an account that we're going to target.

How do we try to aggregate more signals?

Third party is better than no signal.

Second is better than third.

First is a holy grail to deliver the outbound performance that you need.

Jonny Adams: Thank you so much, Stuart for sharing that.

You talk about signals.

The signals have always been there.

Two years ago, they were there.

It was just the time it took to pull them together in it.

So that's really interesting, which probably brings people who are listening to that great bit of insight.

It's like a bit of FOMO, potentially, the fear of missing out.

As a percentage, how many businesses are doing it through the LLMs?

Stuart Dale: Yeah, I think, look, I think most businesses probably have signals being aggregated in their CRM right?

The content downloads is a great example.

It's like, you probably know when somebody downloads the content.

The question is, what are the what are the other signals that inform you before somebody downloads content, that they might be more in the market today than ever before, and I think, like most teams have used sales nav as an example.

Show me when there's a surge in hiring.

Like, that's great.

Like, that's and I would imagine the majority of companies are using some form of signal to just give them a bit of a clarification that somebody is a better fit.

I think historically, over the last 10 years, the big one's been firmographic, so that you would, you would look at like a tech stack and say, well, because they're on Shopify, I know I can sell to them, that's a signal.

But what, what's now happened with with the machine, is the scale at which you can aggregate and then analyze and then bring in intelligent outbound approaches has just got exponentially easier.

And I would say we're at the start of this major shift, like, probably companies doing it.

Well, it's like, single percentage, because it's one thing, aggregating the signal.

Can I pull more of these signals?

But the next thing is like, how do I ensure the signals don't just become more noise?

How do I actually use it my outbound How do I train my team on what that signal means?

And you know, there's a whole, whole, whole set of considerations there, but it's easy enough to get started, if you aren't already, and just start embedding some of those processes.

And that's the opportunity.

That's the growth play.

Like that is the play.

And I think it's like, if 99% of software companies today see somebody hiring or somebody's raised funding, how many emails do you get that say, Hey, I saw you raise fund.

Funding.

It'd be great to show you how we do this.

And you're like, that's not how you do it.

But what about if you saw somebody had raised funding, and you've aggregated that they joined these three communities about this particular topic, and when you said you've raised funding, I saw you join this, which means you probably are thinking about this.

Can I show you how our solution you how our solution can help?

All of a sudden, you're in that top percentage of like, yeah, that's that's how you build demand.

And one of the things that's become much more prolific with with this over the last like, couple of years, is the ability to scrape information off the internet much, much faster.

So like places like Companies House or like wherever people want to scrape now, technology enables it, which means that you can, like, aggregate some of these learnings much, much faster with what you're doing.

Matt Best: Amazing.

Thank you so much, Stuart, I'm looking forward to seeing you again on part two of this conversation.