Florence Broderick: The Cutting Edge of Data Sales

In this episode of Selling Signals, we’re joined by Florence Broderick, CRO at General Index, where she is helping scale a commodities data business. Florence has worked across both software and data companies, which gives her a rare perspective on how different those worlds are when it comes to selling, hiring and supporting customers.

We discuss why SaaS is still ahead of DaaS in go-to-market maturity and how AI is changing sales teams in practice. Florence shares what is actually working in prospecting today, how data vendors should think about AI use in customer contracts, and why in-person events may become even more important as more of the sales process becomes automated.

This episode is essential listening for anyone building a data business, modernising a GTM team, or trying to understand what data companies still need to learn from SaaS.

Transcript

SPEAKER_02 0:01

Welcome to Selling Signals, the podcast focused on how businesses actually monetize and sell data. Each episode, we interview an industry insider to hear their experiences and lessons learned.

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SPEAKER_01 0:23

Today we're joined by Florence Broderick, CRO at General Index, where she's focused on scaling a commodities data business. Florence has worked across both SaaS and data businesses and brings a really clear perspective on how different those worlds are, from how you sell to how teams are built, to what customers value. Today we'll get into the SaaS versus DAS debate, how AI is changing go-to-market for data businesses and businesses in general, and what it takes to sell data well today. Flo, it's great to have you on the podcast.

SPEAKER_00 0:51

Great to be here. Thanks for having me.

SPEAKER_01 0:52

Welcome. Well, uh, what you may not remember, Flo, is when we met many, probably a couple of years ago now at an FISD conference. Um I typically tell people I'm from a nicer town in Somerset because no one knows where it is, called Taunton. And it so happened that you were from that town, and I had to tell the truth that I'm actually from the worst town in that region. Um so yeah, that was uh an embarrassing case for me.

SPEAKER_00 1:16

Well, I technically lied too because I'm actually from closer to Western Super Mare, uh, also known as Western Super Mud. I went to school in Taunton. Um, so up for Somerset.

SPEAKER_01 1:26

Yeah, we're we're pro-Sumerset at least. I'm outnumbered. Yeah, you are. You're very outnumbered. Um awesome. Well, what why don't we jump into the to General Index? Tell us a little bit about that. Most of the actually today, a lot of the vendor representatives we've had have been more consumer-based data sets. So help us understand General Index, commodities data, and your role as CRO there.

SPEAKER_00 1:50

Yeah, so uh general index, uh we're in the commodities world, specifically energy, um, and we are decoding energy prices. Uh, and what that means is that traditionally this world of what's the daily price of oil, diesel, gasoline, etc., has been speculated on by journalists. And so this world is kind of run by teams of journalists who kind of function on gossip, really. They call up traders at big oil trading firms, big energy firms, and they write that down in their notebook and they kind of write a daily PDF style report on what's happening to that specific commodity. Uh, and so the founder of our business, our founder and CEO, uh, decided that there had to be a better way to do it. Uh, and that was not necessarily journalism, that was through technology. And so, what we've done is we've built a platform that brings in trade data from across the globe in these commodities and uses a consistent methodology and algorithms to turn out daily prices and forward curves, uh, which are now used by some of the world's biggest energy companies. So, people like Shell and BP. Uh, we're also we also have a strategic partnership with Bloomberg and some of the world's biggest hedge funds use us as well. Um, so uh been in the business for a couple of years now, it's fascinating. I I love it because it's business critical data, as in when somebody decides that they are going to trade hundreds of thousands of barrels, uh, you know, you have to have really high quality data to use in the contract for those barrels. Um, and and that's what we do at General Index. And we're headquartered in London. But because energy is obviously a really global business, we have a hub in Houston and Singapore, and also in Krakow, where we have our development team.

SPEAKER_02 3:26

Just to jump in very quickly, so there's no, I mean, that I'm a complete um on commodities, I really don't know a huge amount. So there's no like stock exchange equivalent at all, anything like that for oil prices or energy prices.

SPEAKER_00 3:40

There are exchanges, yeah. So um, you know, we work a lot with ice, the intercontinental exchange. There's also for metals, LME, um, but uh still the data for that world is collected in this very traditional way. Uh, and it's you know, it's it's run by a few journalists who are, you know, could be easily influenced to decide what the daily price is, and that has its problems from a compliance perspective. And that's one of our big USPs uh when you speak to the big energy firms like Shell, BP, uh, what they really want is a more compliant way to do this rather than the opinion of a journalist who has spoken to a few traders and in their company and then sold that data back to them. So, you know, I did not come from this world before, I came from SaaS in geospatial, so completely different. But for me, it was quite shocking that such a huge amount of physical trade happens on these numbers. And uh, you know, I think our CEO's vision on this to use technology to make it better makes so much sense.

SPEAKER_01 4:40

And obviously, recent times, oil has been in the news about the cost per barrel skyrocketing. Is that a good signal for your business? Do you see more demand, or is it fairly uh the interest you get fairly the same across the year respective of macro?

SPEAKER_00 4:56

It's uh it's interesting because you you would think that it's like a really crazy time price, and it is because what's happening in the market is pretty insane uh with what's going on in the straight up for moves. But um actually what can happen is that we sell into the traders predominantly uh and their analysts, and they are so busy trying to work out what on earth is going on with the world's oil price that you know the date new data sources or or looking at contrasting data sources might not actually be their top of priority because they've actually got things they physically need to move uh in that their company. And so actually looking at new data sets might not be the top of the list priority. But in terms of the amount of people that we have kind of logging on to our solution, which is called GXGo, which is an interface for our data, yes, people are extremely interested uh and want to see what's going on because um of the consumer impact, right? You know, if you turn on BBC News and everybody's thinking about what's gonna happen with their summer holiday, what's gonna happen to the cost of living, all of that's affected by oil prices. So um we have had quite a lot of news coverage in the past few weeks due to that.

SPEAKER_01 5:57

Yeah, it is my holiday gonna get cancelled? Are my plane plane flights done?

SPEAKER_00 6:02

Um I you can have to ask Donald Trump that question. Let's be honest, it's all on Donald.

SPEAKER_01 6:08

What one thing I want to delve into before we sort of move on to sort of the SaaS versus DAS uh piece is you've mentioned there that you're working with the big oil companies, the traders. Um that's slightly different to uh maybe the typical ICP of a uh quantitative researcher or a data sourcer. But am I right in saying that actually you can sell to sort of both of those sub-industries?

SPEAKER_00 6:32

Um absolutely. We do sell to both those industries. We also sell to a lot of consultants and analysts as well. Um they are, and we just sell to them in very different ways, right? They're very different personas with different priorities, their day-to-day reality looks really different. Um, but um, that's why it's really important that we have versatile sales teams that understand how the motion of selling into a BP might be very different to selling into a small hedge fund based out of New York. Um, so yeah, it's um it's important to hire talent that is really curious about understanding different ICPs because it's not a kind of rinse and repeat we only sell to HR leaders in the SaaS industry, which is a reality for lots of salespeople.

SPEAKER_01 7:15

And it it sounds like a salesperson in your organization would own multiple ICPs or verticals, if you want to call it that. You don't differentiate between the types of sales reps that would sell into Acorn Hedge Fund or a BP.

SPEAKER_00 7:29

Yeah, we're we've been more geography-based until now, uh, to be honest. So we have somebody covering more North America, more APAC or a Maya, um, rather than verticalizing everybody, uh, so that we can all learn uh from the different nuances about the use cases of our data in the different verticals. Um that said, it's not it might be something that changes over time, um, because I do think there is something to be said about the repeatability of understanding that you know the consultant in a management consulting firm uh in US has a very similar problems from one firm to another. And so understanding what the sales process looks like of a um kind of knowledge team, for example, within a consulting firm, even though there's big similarities to market data in a financial services world as well. Um, but there's there's nuances, and I think there is value for learning that and getting that repeatability in the sales process.

SPEAKER_01 8:21

No, that makes sense. Moving on to the the SaaS versus DAS, then you you have the fortunate experience of experiencing both of those worlds. At a high level, what do you think about the differences between both as a commercial organization?

SPEAKER_00 8:38

So I think maybe this is gonna be a bit of a sweeping statement. Um, but I think uh SaaS businesses in GoToMarket are quite a bit ahead of DAS or information services businesses. Um, so because a lot of information services businesses uh have come from um being journalistic business models, like it's it's just slightly different sales motion and the whole idea of using AI in the sales process, having a PLG motion where customers can try your data or your product before, like all of that's just like totally mainstream in SaaS right now. And so there's this whole pool of data companies that I think are trying to catch up, and so they're probably trying to bring talent over from the SaaS world in to bring that modernization of the go-to-market function. Now, that is a sweeping statement, and there are DAS businesses that I think have functioned more like SaaS businesses, but I'm thinking maybe more about like the world that I'm competing in right now. Um, and so there's that modernization piece, but there's also um the differences, for example, in the customer success function. So in SaaS, having a really strong and well-resourced customer success function really matters because if people don't adopt the different features that you're launching on your platform all the time, then you're gonna have a churn problem. Um, now the same can be said for data. If we're launching uh new data sets and new commodities, we need to make sure that the different trading desks in that business know that we've now launched uh European natural gas as an example. Uh but with data, once you are flowing into models and flowing into analysis, there's not quite so much. Look at this new feature. Uh, let me show you how this works. Let me show you how you plug this into your data warehouse. Uh and so customer success is different, I think. And customer success in the data world needs to know the data extremely deeply and that subject matter. So uh we are kind of thinking about how we build out our customer success function at the moment and bringing in people who really understand the world of commodities, I think, will be very important because they need to be able to joust with our ICP. They need to be able to chat to the uh gasoline analyst at one of the world's largest oil trading firms about what's happening in the market and how our data might support that, and what's the methodology and why does that matter, and why is it better than other data sets? Um, so I think those that's the main nuance I've seen so far.

SPEAKER_01 10:58

Going back to your first point about uh the sort of I guess gas lagging behind SaaS in terms of a sophisticated sales motion. How much do you think that that's driven by a lot of the research in recent years that's been published? I think like Challenger Sale, um uh all actually all the work from the those authors has been quite hyper-focused on uh on tech and SaaS. And actually, you're seeing those authors look more into like consulting industries, professional services, and sort of seeing differences in the in in sales methodology and and who's winning. Do you think that's driving that that difference? And should there be more research into the best salespeople in the DAS worlds and what they're doing that's that's different?

SPEAKER_00 11:43

That's a really good point. And it's not one I've thought about too much, to be honest, but it could be the kind of bias of there being more information on sales motions in SaaS world and because there's so many vendors, there ends up being more research because those vendors pump more into it. So um I can see what you mean. I think there's also just something to be said for a lot of SaaS companies sell into SaaS companies and therefore have had to be modern and agile in their approach to differentiate in very busy categories. I also think, and this is quite a plain and simple thing, is SaaS industry pays very well, right? Tech businesses pay very well. You know, what companies like Snowflake might pay compared to a leading data business of a similar size, I think you'd find would be a lot higher, um, and have more aggressive commission schemes, uh, etc. So I think part of it will be that just the kind of bleeding edge talent that adopts AI faster, that innovates in terms of how they they sell, moving away from the kind of old uh sales, I go and take you out for lunch and we have a chat, and then you give me your business. Like there are still businesses that function that way. Um, but you know, that's not really the the SaaS tech way unless you're talking about huge enterprise scale Oracle world where I think the lunches and walking the halls of a business is still a big thing. Um, but I think, yeah, there's the kind of talent that's been attracted to SaaS that means that it's pushed ahead in terms of normalization of sales just uh a bit faster.

SPEAKER_02 13:13

That distinction of compensation, is that a function of the fact that um software businesses are just so far ahead, as you mentioned earlier, uh, of data businesses in their understanding of the sales pipeline, like how the sales process should work and how important your salespeople should be, or is it more uh a function of the uh average contract size in software as opposed to data?

SPEAKER_00 13:37

I guess part of it would be to do with the LTV to CAC ratios of those businesses, right? What you can spend to acquire a customer in a SaaS business is probably higher than what you can spend in some data business, just because purely the margins of the business. Um part of it could be that I also think that you know SaaS had this uh crazy time where everything got totally inflated off the back of COVID and people were getting, there's been a massive adjustment to the market. Um, I'm a member of Pavilion and they have published, they published regularly published benchmarks about what's happening to salaries and comp. And you know, things went crazy coming out of COVID, but then uh things corrected and they corrected very quickly. And I think AI businesses were somewhat immune to that. So I'm sure if we looked at the compensation of people in Anthropic right now, uh and open AI, we'd be seeing crazy things that are just completely on another level to SaaS. So I think there's been a market readjustment, and I think a lot of people were overpaid for a long time in SaaS, and the VCs were were funding that. And then I think the the VCs pulled back and said, uh, can you have a think about your unit economics, please? Because growth at all costs is not going to work here. Um, so so yeah, I think that's part of what's caused this um market readjustment.

SPEAKER_01 14:51

I was I can't I can't tell you the source. It was some random podcast that I think my boss had had recommended to me, and they were talking about anthropic and compensation for sales reps. And apparently, well, according to this guy that I can't remember his name, uh he was saying that the comp structure is actually really poor, and what he expects with the new CRO going in is that completely change. Because the amount of revenue these guys are pulling in is crazy, but uh apparently it's uh not a good structure in comparison to um to what's happening. But maybe that changes with with the new CRO, but um but it sounds like they haven't got that quite right.

SPEAKER_02 15:24

Is that in contrast to ChatGPT? As in sorry, OpenAI.

SPEAKER_01 15:28

But it was a comparison comparing it to to standard SaaS models. Um I I don't think there was any sort of real commission, it was more bonus based on um on revenue, I think, and they were looking at changing it. But um anyway, it going to the uh your you're going all the way back to you're mentioning about the specialism and the domain knowledge the that's needed, um and you were looking at more on the the sort of custom success. How do you think about hiring for that role? Is it going to uh you know analysts, sector analysts in in um in in businesses like BP or in a fund and hiring them out? How do you think about sort of the costs of that? Because you're right, I think it's really, really important, but it's not a cheap task.

SPEAKER_00 16:16

Yeah, I think I think with actually with any role in SaaS, you need to be open-minded about it, particularly in early stage businesses, about who you hire. And some of the best hires I've made over the years have been completely unconventional backgrounds. Um, so I think, for example, going to find somebody that is actually a bit sick of being an analyst in a large company and being small fish in a big old corporate pond is is a really good idea because if you could see that they've got the people skills and they understand people and they're curious and ask the questions, because that's really what customer success is, right? Being curious about your customers' problems, solving them, helping them to be successful with your data or your product. Um, and as much as it's nice if they've worked in customer success for five years and they understand what all the tools are and what the cadence should look like around QBRs with customers, etc., you can kind of teach that part, but it's very difficult to teach people curiosity if they don't have it. I think people are either innately curious or they're not. And whether it's a C-suite hire into CRO or your entry-level graduate role in your business, like curiosity is the main thing I look for, and attitude because you just it's difficult to give people that. You can give them the playbook, you can teach them how to use the latest tool. HubSpot's very intuitive to learn. You know, I I'm a that's how I think in my kind of series A, series B experience world. Um, and you know, some of our we we actually started a graduate scheme last year and brought in uh two two grads uh into the SDR function, never done SDR work, and they are fantastic. And um, you know, you you should some people prefer to hire experienced SDRs, but my take on that is if you're really good as an SDR, you work on SDR for long, you end up carrying a quota quite quickly. So actually, experienced SDRs might not actually be the best SDRs available on the market. Um, there are exceptions to all of this, like I'm speaking in broad terms here, but um that's how I feel about the the CS function. Um, and um, you know, they also need to work really, really well with the product team because they need to capture all of that customer feedback and insight. Um, and you know, a lot of that's done by AI tools now like Gong and other conversational intelligence tools that can pull those themes into your product team and say, look, we're consistently losing deals because we haven't got these prices. Or if we had an export functionality that had an integration with this, then we would probably win more deals, etc. You know, AI can put out a lot of that now, but CS gets that nuanced stuff that maybe AI doesn't capture.

SPEAKER_02 18:44

And is that pulling that data directly out of sales calls, SDR call transcripts?

SPEAKER_00 18:50

Absolutely, yeah. Um, so you can pick up on themes. We actually have initiative boards that tell us um, you know, we right now we have over 6,000 prices, um, but there's always a price that you know another customer wants that we haven't quite launched yet. And so being able to quantify that pipeline and say, well, that's come up in our customer conversations in the past six months 18 times, and being able to tie that to an account and an amount uh is is something we think about a lot because it drives our roadmap in a data-driven way.

SPEAKER_01 19:21

Maybe this is a good segue into sort of AI and um and go-to-market teams, but in terms of your tech stack, it sounds like you're using some type of gong-like uh uh uh tech that's recording these calls and able to do these analytics. But uh in your opinion, how how's that changing with with AI and um what are some of the tools that you're finding that are really, really supercharging your teams at the moment?

SPEAKER_00 19:49

So I think there's kind of old AI in sales, and then there's the new AI. Uh maybe it's not even that new anymore. Um but the old AI is uh conversational intelligence style stuff, right? Like Gong, uh new solutions like Glyphic, um Giminy is another one that's out there. And essentially that's the whole creating core transcripts, turning that into next step summaries. I mean, anybody that's got their salespeople still writing notes into the CRM is you know, such a waste of a seller salesperson's time when they could be prospecting with customers at events, whatever it might be. You know, that has to be automated now, and that's really easy to do. That's been completely commoditized. People have been doing that for five, six years now in SaaS, I would say. I think the new world is actually more on the prospecting side. Um, and a lot of people talk about AI SDRs, and I think everybody imagines kind of robots messaging people. Um, but I actually like to think about AI-enabled prospecting, um, which is not kind of letting letting the AI SDRs loose on your TAM, because if you haven't got a big TAM, that can burn your TAM very, very quickly. But actually having a smaller team of SDRs and AEs who very astutely use Claude, Perplexity, ChatGPT uh in an integrated way within their outbound motion. Um, that's how we're doing it because I haven't yet kind of pulled the trigger on let's go all out on something like Clay or Unify. Um, because if it's working and just with the AI-enabled approach, then you know maybe you could speed things up and go a bit faster with some of the other tooling that's out there. And that's something I'm completely open-minded to. And there's lots of business doing that very successfully. I think it depends on how big your total addressable market is and how much uh great information is out there on the World Wide Web about your accounts. Um, but something I'm seeing is that some of the best data is not out there and available to LLMs, and so it can't prospect quite as astutely as your best prospectors can. Uh so some of the best data um out there is often behind a paywall. So I I spoke to a founder recently. They run a business. Uh, it's selling into kind of refineries and plants within oil and gas. And they look at databases of where there have been certain types of incidents in those refineries or plants. Um, and that data set is not something that's easily available. There's there's news articles about there having been incidents in plants, but there's actually databases that you can buy which aren't available. And so, you know, there there has to be if the data's behind a paywall is not available on the world web, you need smarter ways to bring that into your motion. Um, and I think the businesses in the clay world that do that best and start to make it easier to bring in proprietary data sets into the prospecting motion, I think will be the ones that win in that category. Um, but yeah, that's a whole world. And I I in the CRO dinners that I go to in at Pavilion, I don't know very many people that have got AI SDRs working at scale very well. It's a very limited number of people at this point in time.

SPEAKER_01 22:58

I keep seeing the post going around about anthropic hiring a an SDR manager. Um but I I guess if the one of the leading AI companies is is hiring for that function, then the function must still need to exist.

SPEAKER_00 23:10

Well, I think it's like the emer the emergence of this uh GTM engine engineer role, which um, you know, I think the SaaS industry is is is awesome at making up names for roles, right? So it's like um head of revenue marketing. And I'm like, what marketing are you doing that isn't for revenue? That just makes no sense. If SaaS these flashy titles, it's the same thing with GTM engineer. I think GTM engineer is the evolution of the RevOps function to be more focused on being integrated within the sales motion and not being stuck behind I'm a Salesforce admin and I do deal desk and I make sure that the invoices go out on time and the renewals, blah, blah, blah. But it's actually like how does RevOps work more closely with sales and that intersection and make sure that uh we're using all of the tooling that we spend a lot of money on per year to effectively drive pipeline. Um and I think, yeah, people, I'm sure there's lots of people that have managed to pivot to that GTM engineer thing and get a massive salary hike just by being in the right place at the right time because a company said, ah, Clay, we need a GTM engineer. Let's go.

SPEAKER_02 24:10

And that that go-to-market engineer, are they generally a former SDR, a former salesperson, a former RevOps person in your experience? Or could it be really, really anybody who's up for it?

SPEAKER_00 24:22

I've seen a real mixture of things. I've even seen like developers going in to the like developers that really get the customer and get sales processed and maybe watched it from the other side of the business. I've seen that happen. I've seen the kind of techie data savvy SDR pivot to that position. I've seen people come out of RevOps. Um, so you know, you know, but I I still only think it's about maybe five to ten percent of SaaS companies right now that have made the GTM engineer higher. Um, so it's still relatively new. Um that said, I've been on MatLeaf for a quarter now, so you know, things might be changing in the industry. Um, but um, but yeah, I think we'll only see more of it.

SPEAKER_01 25:00

I want to jump into a bit more explicitly with with AI and understand a bit about how you're helping your teams be more efficient. So could you maybe walk us through some explicit examples of uh some automations that you're using? She mentioned clawed code, but what are they building with clawed code that um that is making something easier for a sales rep?

SPEAKER_00 25:21

Well, um to be honest, uh top down, I I don't try and like I my team is super creative and they constantly come with new ideas about how we could be using these LLMs uh to to do better prospecting, right? One example would be one of my A's who built out with Perplexity a dashboard for kind of what um commodities or products were being created at different refineries and how that was increasing or decreasing at different refineries so that he would have an idea of when he prospected into uh the refinery planning team for that refinery, you know, what's going on in their world, so that his messaging would be super relevant. And he had a full dashboard around it that PerplexT built out, which is amazing. You know, previously that would have been a real kind of data wrangling process, and then building out a dashboard in Looker or Tableau or whatever, whereas just in you know, minutes you're you're building that with AI. So that's one example. I think it also um, you know, we we we've spoken in the past about how uh should you hire people from outside the category in sales? I think one of the great things about AI now is that you can get to know your persona so much faster than ever before. So, you know, previously your ramp as a salesperson might have been three to six months, whilst you really learnt uh how do oil traders think and oil traders work. But now, you know, every time you've got a target account and you really want to understand, okay, how does an oil trader, VTOL, think about the world? What are their priorities? What what what what kind of sources do they trust? You know, you can use your Chat GPT, Claude, as your co-pilot to understand that much faster. Previously, you might have had to have gone to somebody in your product team and say, hey, you used to work at this company. Tell me, how does how does this guy, Ahmed, and this team, think about this and what would be relevant for me to say to him? You know, now that's a a single prompt away. Uh, and honestly, it does a really, really good job, particularly as you start to. So I use folders within Chat GPT and I feed uh our sales playbook, our master sales deck, and loads of our case studies into that folder so that it's not just looking at like what does Reddit tell you that oil traders do? Because frankly, there'll be lots of incorrect information on Reddit about that, but actually internal sources that we've worked on and spent a lot of time on, so that um, you know, we met that information definitely gets to people ramping within our organization. Um, I actually was so my husband works in finance and he likes to uh share with me the worst SDR emails that he gets. Um and you know, he's he's not done outbound prospecting loan that way himself. And so what I said to him the other day when he read pretty pretty pretty bad one out to me was that's not the fault of the SDR or the account executive that's done that prospecting. That is the fault of the revenue leader, whether that's the CRO or the CMO, who have not given that person the right documentation or the right understanding to really get that persona. And that is not just sat at your desk, it's having conversations, it's going to events, going to webinars. And if you go to an event, you do not just stand by the booth and wait for people to come along and have a chat. Go into the sessions and hear from the four heads of market data or the five traders that are speaking on that panel, listen in, take notes, and absorb because uh that is that's how you learn and you become much more knowledgeable and you become not just that salesperson that's trying to sell somebody something, but something like can actually give some nuggets of information back and be educational in some way, which might seem crazy for a 28-year-old account executive to be uh helping an oil trader understand something that might be going on in the market. It's not going to be about the their specific oil part, but it'll be about the data part of their world. And I think if you can be valuable to the people you're selling to, uh, you know, that's what that's what you need to aim for as a salesperson. And there's no excuse for not setting up your team for success with that type of knowledge and materials to be successful.

SPEAKER_01 29:18

Yeah, one of the things I used to try and um impart on to some of the reps I used to manage is that especially when they're coming in as graduates or young salespeople and they're talking to sometimes people that have been in that industry for long periods of time, senior titles, etc., that they feel that there's some level of inferiority in um in knowledge. But actually, you spend so much time speaking to the market and all of their peers that quite quickly you end up having a really good understanding of their problems, how other people are solving it, etc. And I think the amazing thing about AI, and linking this back to your point about clay and it being quite generic in terms of the signals it creates so far, and the next step will be to enable people to be able to personalize the data sources they have, so it's uber uh centered around their business and their product offering, is being able to pull in all of that customer information and conversations where you can quite quickly help a rep understand how people are commonly solving these problems, what these what what problems these people are quite often having. And I'm hoping at some point the ramp becomes a lot quicker, but I guess you still need the engagement from the rep.

SPEAKER_00 30:27

Yeah, you still need that extreme curiosity. And I think more than now more than ever, I think in a world of AI and having you know, people a lot of people talking about how we're not using our brains anymore because you can just ask ChatGPT how to do something. And um, what I think will really differentiate talent now will be the EQ side of things, because yes, IQ matters, and you need to have that curiosity and and maybe an academic background in a certain thing, but actually how you interact with people and how you can build rapport uh is gonna be more important than ever because everybody can just use an LLM. There's no, you know, there's no barrier to entry for somebody to have access to that. It only costs 20 quid a month for the premium package. I I think that's going to keep going up. Uh, but um actually not everybody can get into a room and have a chat with somebody in a natural way and find common ground and get to know them. Um and I think uh I think increasingly that will be an even more important part of the hiring criteria.

SPEAKER_01 31:30

I guess that takes us quite nicely to like in-person events and those sort of things. How important do you see that as part of your go-to-market strategy to break down the noise that you have online at the moment?

SPEAKER_00 31:42

Absolutely paramount in our industry. Um, you know, two of the biggest events in our industry are called uh IE Week uh in London in February and then APEC in September in Singapore. And this is kind of really where all the traders go to talk to each other and all the vendors fund lots of big parties. Um, it's pretty simple. Um, but that is really where big decisions and conversations happen in our in our industry still. Um, also it's true that uh the commodities industry is still quite traditional in many ways compared to kind of some of the more the other worlds of financial trading, right? FX, etc. Um so it's a little bit more old-fashioned. But I think in a world where people are more distributed and people are using AI more, actually that people long for that human interaction. Um, just even at a you know, how do how do you what do you enjoy about your week at work? I this isn't for everybody, but I do really love the interaction with people, and I think a lot of people do want that. They want to have a chat about something and not be given back words on a screen, but actually just engage on something. So I think we're going to see more and more uh events uh and then being successful. Um, so I'm I'm quite bullish on that, to be honest.

SPEAKER_01 32:56

Yeah, me too. And actually, also seeing a lot of uh training programs prop up about how you can make the most of being um a better sales rep at events or in-person elements. Um, because I think there's a probably a lot of sales reps that have sort of come into a sales role organization since 2020, and they've never really had that in-person element. And to be honest, I'm probably one of them. Um I guess unfortunately, the job role that I had, I was at lots of events that maybe enable me to uh improve that skill. But it's really hard going up to people and talking at events and breaking down that wall.

SPEAKER_00 33:31

Yeah, it's it's so true. I mean, it's uh I I really hate some of the stereotypes that get thrown around about Gen Z. Um, and actually the the Gen Z people in my team are the most natural social butterflies ever, so they kind of not suffered that kind of COVID lag that a lot of people have had. But um, it is really important. It's it's at the end of the day, a lot of the generation coming into the workforce now never call a restaurant to book a table that's all on open table or whatever, and all of those parallels carry over to other things in their lives, and so they've not had the same amount of humanity. They probably went through university and didn't get the freshest week because of COVID. So, um, so yeah, I think there can be a little bit of a lag, and yeah, giving people the training and the skills of how to successfully network and not feel like networking and to just, you know, a lot of that comes from I think the way people are brought brought up as well. Um, and I think um it really, really does matter. So uh I um I definitely agree with you there.

SPEAKER_01 34:31

Conscious of time, maybe one closing question. What's one belief you have about the future of sales that most people would disagree with? Difficult question.

SPEAKER_00 34:42

That most people would disagree with. I think maybe this is a bit SaaS-specific, and maybe this is kind of biased by my own story, but I think we will see more and more people coming from unconventional backgrounds into sales. So coming from a marketing background into being a CRO, so CMO to CRO is a bit unconventional, right? Because you know, people might look at my CV and say, Well, you you didn't carry a quota for the first X years of your career. Um, what would you know? Um, but actually, I kind of always stayed very, very close to the sale. I went to every trade show, I always did the selling on the stand, and I kind of always felt like I was missing out, not doing the kind of quota carrying side of things, which is what eventually led me to want to carry the number and be accountable for that number. And I I love that. I love being in the driving seat, and that's fantastic. But I think we'll see more and more of that because the traditional sales skills, as important as they are, we do just need more and more people who think of things and systems and use AI and think about how their sales motion interacts with PLG, product-led growth. And so that will require more people to come from outside of the traditional um salesperson uh kind of criteria. Um maybe I'm wrong, but certainly in North America that we're seeing more and more of that um in SaaS businesses in in pavilion, meeting more and more people that are making that transition. So maybe that's controversial, but maybe it's not.

SPEAKER_01 36:14

Yeah, maybe I'm gonna make that make this that sound like a bad answer because uh I don't disagree with you. Um I think the uh well, while I love our conversations in general, and we always find ourselves speaking about sales and where sales is going and sales methodology. I think we're both uh I guess are very, very interested in in the literature side of things. But I I actually I was reflecting on on that move you made from CMO to CRO and more into the quota querying carrying uh uh role. But I actually think what makes you a really good leader is you're very, very uh uh customer oriented. And I think people maybe this is really bad because I am a salesperson, but salespeople can be inherently selfish. And I think because you come from a marketing role where you spent uh a large part of the the early part of your career thinking about somebody else and how somebody else uses your product and how to how to get that in front of them at the right time, I think you kind of have removed that sort of selfish element out of yourself, and it it becomes really clear that you're quite buyer-oriented rather than a selfish sales leader. Um, yeah, I always find your your takes on sales and where it's going really refreshing and forward-thinking. So um, yeah, I always love our conversations.

SPEAKER_02 37:29

Oh I was just gonna jump in with one final question um before we close um from me, because I remember it from the research call, I really wanted to bring it up. Um, you've mentioned multiple times that you're kind of you're obviously at this intersection of data, sales, and now this kind of like new uh AI revolution and how that's kind of breaking into all of these different areas. Um, as a data provider yourself, how do you feel about um that data potentially ending up in a large language model? Because we know, as you were saying earlier, like uh DAS companies sometimes are even reticent to allow for a free trial of their data. So I'd be really interested to hear how you're thinking about the the future of data and data sales in a world where so many people are going to want to inject that into AI. And as you also raised earlier, that's kind of where you're seeing the best results from a sales perspective or a customer success uh perspective, is that proprietary data probably paywalled alongside a human in the loop aided by um some sort of agent?

SPEAKER_00 38:32

Yeah, it's such a good question, and something we've thought about so much in the past year or so. I mean, um a lot of companies are not moving fast enough to give their customers answers on how they can use their data in LLMs. Like, can I plug your data in? Can my employees individually in their co-pilot at work use your data points? Can they upload a CSV into there or not? Uh, would we be in breach of our contract? You know, it's it's a boring T's and C's thing to work out, but it's really important because every single company has hired a chief AI officer and they have a mandate and a lot of budget to make sure that AI is used across that organization. So we have had to pivot very quickly to make sure that we give our customers answers on that. And it's actually a USP because we are pretty flexible about how our data can be used in AI with some guardrails in place. You know, uh, we need to understand whether it's an enterprise license, for example, of the AI uh tool within that organization to make sure that the things are not getting leaked back into a core LLM. Um, but yes, we've had to move very quickly around that and understand what the use cases are. And the most important thing is asking for details on the use cases and learning about them, not just putting up the data usage police and saying, nope, you can't do that, no, you can't do that. Because otherwise you're slowing down your customer. Coming back to your point, Eric, is it it's the customer that matters here and they need to be able to keep pushing their business forward, enabled by your data. Um, so so yeah, it's something we've thought about a lot. It can be a USP for companies, um, and it's important to do the the research on it. Um and yeah, I think um we're gonna see more and more of that over time of loads of diverse use cases so far.

SPEAKER_01 40:12

Awesome. Perfect. I really appreciate you taking the time, Flow. It's been awesome chatting as always. Pleasure. Thank you very much.