In this episode of the now ai podcast, Ralph Varcoe interviews Kayne Brennan, now ai’s CTO about the challenges of too much data and how this can be turned into amazing insight through the use of Ai. They cover where the data comes from, how the platform curates it and what the end result is. This end-result insight is what’s passed across to the analyst team (the human intelligence) to contextualise and personalise the conversations into sales intelligence. This podcast is all about panning for gold in a data-overwhelmed world through clever machine learning and ai.

Ralph: Welcome to the Now AI podcast. I’m in my house in Leafy Hampshire, and I’m joined by Kayne Brennan. Kayne, whereabouts are you today?

Kayne: The suburbs of North London.

Ralph: Suburbs of North London. Normally we’d be face to face, having a nice conversation around a table with a cup of coffee, but today we’re having to do this remotely and dialling in over the old telephone. That’s brilliant. Thank you for joining me, Kayne. Can you just give me a little bit of info as to who you are and what you do at Now AI?

Kayne: At Now AI, I’m the CTO, and my role is essentially everything technical that we use within the business, to make sure it all talks to one another, does what we need it to do, supports the business the way we want to support it. My big focus at the moment is obviously building out our AI platform to support our analysts.

I’m one of these people that just likes the internet things. Anything that’s techy or about building platforms or making things work, I love it. I love getting under the skin of it. I love figuring it out. It’s what I loved about the challenge of building the Now AI platform. It’s never been done before. We don’t know anybody and we can’t find anyone that’s using sales intelligence and industry intelligence and company intelligence the way that we’re doing it, right the way down to the executive level. I find it to be fascinating.

I had the chance to get involved at Now AI before it was even Now AI. When the MVP was being built, I was approached by the people who were the Salesforce integrators at the time for Now AI, and Pete had mentioned to them that he wanted to build this platform to do this and they hadn’t secured somebody to do it, but they wanted to do the MVP for funding. I was referred in and instantly struck up a relationship with Pete.

I built the MVP. He contracted my company at the time to do that, and then after that, I moved myself over to Now AI and I’m now the CTO actually running the project and leading our devs into what is going to be a hugely successful and an amazing platform to support this. It’s already showing some real potential.

Ralph: That’s amazing. I was just reading a little bit more about your bio, and tech stuff and internet things weren’t your original bag, were they? What is your background?

Kayne: I think the reason this struck a chord for me – I’ve always been super techy and super geeky. Before I got into sales, and I was in sales for years, I was really into music. I did sound engineering, audio engineering, did music production, and I was putting on huge events. I was always out doing AV and putting more things together. That’s probably something that not a lot of people know about me because I kind of keep it quiet as my misspent youth.

But that’s where my geeky side comes from, and then alongside that I also had a sales career. I started out in sales when my brother and I were estate agents when I was like 16 years old and instantly got the bug. I loved the thrill of closing a deal. I loved the thrill of finding things for people and then them getting what they want and then seeing that sale go through. Watching people buy a home was so emotive. Introducing somebody to it and watching them picture them living in this house – it just really excited me.

So I had these two passions since I was quite young. I really enjoyed music and audio engineering, I was uber-geeky and techy, and I had great fun putting on events. But then during the day, I really loved selling stuff.

I went from estate agency into car sales, and car sales is where I really learned my craft. I worked at Ford Motor Company for 5-6 years. I worked my way up there. I got into sales training and did loads of things around it. I really honed my skills and became, I think, a really good face-to-face salesperson.

I used that and went back into estate and was never really happy there. It was weird. It wasn’t quite the same, and I wanted a change. So I went into central London and a recruiter approached me. It was one of those where I’d put my CV up online and this recruiter’s like, “Look, you’re really into music and events. I can see that from your personal profile. You’ve got lots of sales experience. Have you ever thought about doing corporate events?” I had no understanding of it whatsoever.

I got into a company called the World Trade Group at the time. They’re called something else now. When I went for the interview, it was insane. The buzz on the floor was crazy. There were people standing on their desks, they were shouting at one another, telephones. It was a little bit boiler room, almost, and quite intimidating for a lot of people, but I just thrived. I loved the atmosphere. I was like, “Right, this is me. This is what I’m going to do.”

I got in there; within 3 weeks, I closed a deal which was one of the largest deals I’d ever closed in such a short time, certainly on one call anyway, and then that was it. My career was made. I was doing sponsorship sales for events. I went from conference events into publishing, into marketing, media, then into writing marketing campaigns.

Then what happened was I got headhunted by a really big publisher to take them from physical events into digital events because they saw I was super techy and they found out that I had been building this online webinar platform for the events company I was working for – and it was hugely successful. I think in the first year, we made like 900,000 or something like that and we were only predicted to make a couple hundred. If we did that, we would’ve been happy. But it just flew.

I went to work for this really big publisher. From scratch, built them almost an identical platform with a few changes to it, and I got really in-depth. I worked with the dev team, I scoped it out, specced it, and I started getting really into it. I started doing courses in UX, UI. I taught myself to code properly. I had an understanding of HTML, but I never really understood it. So I started there and filled in my stats. I got into PHP, and at that time it was things like CodeIgniter and the Laravel frameworks. We started building platforms. I really honed my HTML and CSS skills, and I obviously focus now on what everybody uses, JavaScript really, and got into scripting languages.

After 5 or 6 years of doing that, I got really fed up with the company. I’d achieved everything I wanted to achieve as a sales director, and at the same time established this really techy background, because I was just learning all the time. Sales were going really, really well. I had 40 some salespeople working for me. I spent most of my time either leading the development of the technology platform or motivating sales staff and focusing on them.

What really checked my boxes with Now AI was the fact that when I was a sales director, I was bang on and bang on and bang on at sales guys, but the reason I was always successful as a salesperson was I really understood my customer. I got right under their skin. I really got the pain points for them. I wasn’t ever afraid to ask, “What do you need? Why do you need it? What’s going to make a difference to your business? How can we support you in changing that?”

When you’re working in things like sales and it’s hard and fast-paced, when they came across a salesperson like me who was quite willing to just go, “Wait a second, I don’t want to sell you an exhibition stand. I want to sell you something that’s going to add value to your business,” it’s a different conversation. I would quite often look at their portfolio, understand what they needed, and then I would pitch them on that.

I’d say, “Look, delegates are interested in this. You guys are doing this over here. Come to our event, talk about this. Let’s give you a talking slot so you can show them what you’re capable of doing. Let’s bring a case study on, get your customers to talk on your behalf. Let’s get them talking to their peers. Their peers will relate to that, and you guys will win off the back of it. Then let’s have a really good exhibition stand and arrange you some meetings.”

All of a sudden I started creating these end to end marketing campaigns, and they only worked because of the clients, but my God, did I spend time doing that. I would get in at 8:00 in the morning, and my first two hours of the day would be just research, research, research, research. We had analysts at the company; we were very lucky. It was owned by Datamonitor, and Datamonitor have analysts, so I’d go to the analysts and be like, “Guys, can you do this? What’s happening here?” Just getting an understanding of the market. I would read our own publications to get a really good understanding of the market and the industry.

It was industry knowledge, it was company knowledge, it was knowledge of the person I was pitching – all these things were really important to me. When I came across Now AI, Pete sold me on this dream of, “If you’re a salesperson, what if we could give you the conversation you should have with that executive of that company?” I would’ve passed out 10 years ago when I was doing this. I would’ve been like, “Give it to me. How much do you want? I’ll pay you,” because I knew getting in a room with someone, I could close them if you gave me the right conversation to have. I was never scared of that. I’m confident because I did the research.

But having somebody who could supply me that in quick succession, using AI, using market data – I’m not trained to do that stuff; I’d spend hours doing it – it’s like a dream. And I always used to drum that into the sales guys as well. They used to lose their patience with me. They’d be like, “Kayne, I just want to pitch this guy.” I’m like, “You don’t know what you’re talking to them about. How can you ring this guy up if you don’t know – how are you going to get past his gatekeeper if you don’t have a tangible conversation to have? If you haven’t got a real, genuine reason, you’re just another events company. You’re just another publication. You’re not adding value to the business.”

So I’ve got this weird mix. I’m kind of lucky. I come from a sales director background, but I’m super geeky and techy and happen to love artificial intelligence. It’s just a bit serendipitous that it came together.

Ralph: That is brilliant. Actually, you brought up a whole load of things there that are just fascinating. I was on a call earlier today, talking to a former colleague that I used to work with – gosh, about 15 years ago, when I had a bit more hair and a bit less round the middle. He does a whole load of stuff around helping sales organizations transform, all about key account management.

He was just reflecting on the fact that many of the organizations that he goes to, there’s a varied quality, let’s put it that way, in terms of the research that the salespeople do into their accounts. Whereas you might have one or two people who are utterly brilliant at it, and they put the time and the effort in, there are many people who are not great, and there are others that actually, as you say, would rather just go out and talk to the customer and take them for a drink. It was just fascinating that he was reflecting on that, and you’ve picked up on many of those points.

If it’s the case that we can short-circuit the amount of time that it takes for a salesperson to gather that information together – and in fact, in some salespeople’s cases, they weren’t doing it in the first place, so it’s actually giving them something new – it just strikes me that one thing that we’re not short of in the world is data. There’s data everywhere.

So what is this AI thing that is enabling this proliferation of data, this overwhelming amount of stuff, to be consolidated into – let’s call it insight, that can then be turned into intelligence? How does that work? What is this AI thing that’s doing the secret sauce in the middle of the platform?

Kayne: Without giving too much of the secret sauce away. AI is such a cool subject. Ultimately, it’s also known as machine intelligence, artificial intelligence, whatever you want to call it. Essentially, it’s learning from a machine and it’s providing outcomes versus maybe a human or an animal and what they might do as a result of it.

With machine learning or artificial intelligence, what we’re looking for is to pass a series of data through a model, so indexing it, organizing the data, training a model on it, to provide outcomes, which we can then use to make tangible decisions from. That’s ultimately what we’re doing. What we have is a group of very, very intelligent people who work in the business who are our analysts. Instead of them sifting through enormous amounts of data, a lot of which will be irrelevant to them, we’re enabling the machine to automate and speed up that process and actually feed potential predictions to the analysts, who can then take those further and turn those into intelligence.

The insight could come from the machine; the intelligence realistically comes from our analysts. But there will be, over time, the more the model evolves and the more data we train – this is all about big data and data science. The more that we train data or train our model to interpret things, and the more we pass through it, the more intelligence is going to come out of it, and then it’s going to make our analysts’ lives even easier.

It’s about time, it’s about volume of data, it’s about having a really clever model. And I’m no data scientist. I’m working side by side with data scientists to figure out what these models look like and doing an enormous amount of research into it. There are commonalities in the industry. You can look at industry indexes, for example, and you can start running a comparison on those.

You can mark a bunch of companies that you want to monitor and follow, but when you’re doing it at an executive level, there are so many variables. It’s almost impossible because no two company structures are exactly the same. There are commonalities, like – let’s take the U.S., for example, where you more commonly find a C-suite of executives. Of course, we find them here, but if you look in the UK, you could have MD, FD, and stuff like that, whereas in a very similar sized company or organization, you might have a CFO, a CEO, a COO, and so forth. They’re slightly different interpretations. They’re slightly different roles, and they do things slightly differently, and there’s all sorts of differentiations in the way the organization runs and interprets.

Training a model on those things can be quite challenging because there are lots of variables, and you have to organize them without restricting your AI model. You have to have enough variables that you can actually go “there’s enough variables creating a commonality, so maybe we should follow this trend,” and it would predict those things for us.

There’s all sorts of bits around it, but ultimately what we’re doing, without giving away too much, is taking all that stuff that the salesperson would have to trawl through, giving them a much wider net to make a much more intelligent decision, and expediting the conversation to a point where it could be executed upon quite quickly.

Otherwise, even if you did the best research – and I think if you’re a good salesperson, you’re going to know your industry. If you’re a really good salesperson, you’re going to understand the company you’re pitching. If you’re a superb salesperson, you’re going to understand the executive you’re pitching down to the nth degree. That third part just doesn’t exist in most salespeople. They won’t make the effort to go that far. They’ll do account-based selling, maybe, but we’re in a different landscape now. We can’t be complacent with these things.

So I think you have to really understand the person a bit further, because face-to-face is becoming less and less. We’re now relying on tone and conversation. You get a lot less time on the telephone with someone. You get a lot less time in a teams meeting, for example. We’re selling via these devices now. It’s a totally different landscape. You need to stand out very, very quickly.

If you can really relate to the exact pain points that the executive is focused on at that moment in time, and you have a solution that can be perfectly matched to that, I think what you end up with is my favorite part: the no-brainer conversation. The executive will be listening to you going, “This is a no-brainer. You understand me. You know what my problem is. You’ve quite clearly got a solution that solves it. You’ve made the effort to go this far. Let’s talk about it. Let’s talk turkey.” I genuinely think it happens like that, because I think you get the respect of the executive, so you’re that much further down the line.

That’s what we’re trying to do with our AI. We’re trying to put salespeople in that position as autonomously as we can through machine learning and intelligence, and then supported by our little golden nugget, which is our AI plus I part, which is where the analysts come in.

Ralph: It’s fascinating. If I were to talk about a whole ROI model around this, if salespeople pull together that information themselves – I was talking to actually one of our customers about this the other day – they pull the information together themselves, they’ve got to spend a lot of time doing their own research. The time they’re doing their own research is time that they’re not in front of their customers, building relationships. And you can bet your bottom dollar that somebody else from their competition is building those relationships.

So if you’re going to do your own research really effectively, it’s going to take you a lot of time, and that time is spent away from the customer, doing your own desk-based research.

Then you’ve got another set of salespeople who aren’t doing it particularly well, so there is a question mark about, could they accelerate the relationship that they have with their customer, accelerate their pipeline generation, accelerate the velocity of deals through the pipeline, because they know more about the customer? They’re walking in the customer’s shoes, understanding the issue, understanding the executive’s issue. You look at it and think, could you make your sales team more effective by reducing the amount of time they spend in front of their computer by giving them this collated, curated data, which we’ve turned into insight? That’s one set of the people.

Then the other set is, could you give them this information, which means that actually they can start to elevate the conversations and drive things more quickly? There’s a whole speed of execution by us doing what we do in the middle of the platform with all of that AI stuff.

Kayne: You could paint the picture for a sales director, couldn’t you? You can say to a sales director or a CSO of a company, “What would you rather happen in the morning when your sales staff come in for their day? Would you rather they have a whole bunch of actions that are thought out, that are elevated to conversation level with the executives, and they can just get on with it and have those conversations – maybe they might need to do a little research on it or they might need to have a think about how they’re going to approach it themselves with their own sales style – or would you have them come in the morning and try and develop those conversations and those actions themselves?”

What it boils down to is more time on the phone with more knowledge in your back pocket, or more time out on the road with your customers with a far greater knowledge base behind you. There’s two things here. Return on the investment is great. ROI is fine. We can talk about that.

But I always think that what’s more important is ROO as well. What’s the objective here? The objective is simple: make my sales staff more efficient – which does come back to return on investment. Of course it does. But making them more efficient as a company objective has far bigger benefits to the business because the sales staff inevitably will all be happier. Therefore, they’re more productive, they’re doing more with their time and sales. Your KPIs for the business should change. You should be evolving your KPIs to monitor this in a slightly different way, and that should therefore create rewards and a better company feeling.

There’s all these spinoffs. There’s lots of objectives around it. Yes, okay, you’re paying your salesperson – we’ll talk round figure – 24,000 pounds a year, 2,000 pounds a month. Let’s break it down to your hours per day. If you’re giving 8 hours per day, you can work out their hourly rate really, really quickly. If they’re spending 2-3 hours a day doing that research and all of a sudden you’ve given them that time back, and you know that in a day they’re producing let’s say two prospects or two new proposals a day, and all of a sudden you’re giving them an extra 3 hours back out of that 8 hours, you’ll potentially be getting another prospect.

You’re talking about a 30% productivity rate. It’s really simple math. It’s really easy to look at the objective here and go, “I’m going to make my sales staff a hell of a lot more efficient, which actually will then have a knock-on effect to my return on investment model.” Again, it’s that no-brainer conversation. I love it. It’s a really easy sell as a business. Who’s not going to want to make their sales staff more efficient? It’s really simple.

Even if you’re a salesperson – in fact, it suits the salesperson who doesn’t like to research, who just likes to give it the old wing and a prayer, knows a bit of peripherals on the industry. I used to have some crackers that worked for me. This one particular guy, never forget him, had possibly the worst product and industry knowledge, although talked the best game I’d ever heard. The minute I scratched under the surface, I swept his feet away from him, but my God, everybody loved him.

He was super tenacious, worked really, really hard. Made lots of money. But wasted a hell of a lot of time with dead calls because he got unraveled all the time and then he had to go back round and go back round. It was pure brute force and tenacity that made him a good salesperson. If he’d had this knowledge, he’d have been a different animal because he would’ve been able to sell it better than – he was the best salesperson I had physically, just the worst at actually getting under the skin of things.

For me, that’s how this works. If you’re a really good salesperson who is the opposite to that guy and is willing to do the research – I was that guy. I’d sit down in the morning and there was no problem. And when I was doing it, we didn’t have the benefit of everyone having a PC on their desk. I had stacks of paper that were my leads that were all stapled together. We’d print off of a central printer. It wasn’t very ecofriendly, to say the least.

But it was piles high. I’m not joking around. I’d say to my right every day, I’d have maybe a 30 to 40 centimeter high pile of leads that I’d be getting into, and each one of them would be five or six sheets. I’d have a company overview sheet, industry knowledge, I’d have who I needed to pitch, who the decision-makers were – what the decision-making loop looked like as well, which is always really important as there’s quite often multiple people. Certainly in the industries I was pitching – pharmaceutical, healthcare, oil and gas, defence – there was big decision-making, and I wasn’t pitching a small product. I was going for six figures, very often.

So if you’re looking at things like that, I had this pile, and I was quite literally – my morning would be building that pile up. My midday to afternoon would be running that pile so it moved to the left-hand side of my desk, knowing that I’d called them all. Then the afternoon was basically going back through them or preparing for the next day, or quite often sending out the proposals from the successful pitches I’d had.

If someone had just said to me “Here’s a file” every day, and there was all your conversations to have, I’d have been absolutely away. I visualize that. I can see the pain that I went through that I had to share computers with people. It was insane when I was doing it. Now we’ve got the benefit of we’ve got Google at our fingertips.

But then Google creates another problem. There’s too much knowledge. There’s too much data. How do we refine it? Well, guess what? We’re doing that for you. There’s a sweet spot in the middle, isn’t there?

Ralph: Yeah, and I was going to come back to that. We have got Google. It’s really easy for any of us to do a little bit of a search, find loads of information. We’ve talked about the fact that it takes people time to do it, and because there is such a huge amount of data, actually making sense of it and working out what the relevant bits are in order to create their own conversations – that’s quite a complex thing to do.

We’ve established that the platform pulls all that, collates it, works out what’s relevant, etc., but where do you get the data from? Is it just Google, or is it other places besides?

Kayne: Oh, no, absolutely not. It’s certainly not just Google. There’s two problems with this, though. I’ll answer your question, Ralph, but I’ll add something to it.

How often do salespeople interpret things that they read on the internet, thinking they’ve got it right or thinking they’ve done it, where they’re not subject matter experts? They go in and they look foolish when they drop it the wrong way. That happens. That happens to me millions of times, a million and one times.

This taking it from data and information – and not just turning it into insights, but an actual piece of intelligence that’s been interpreted by somebody who is a subject matter expert is a big step. It’s a massive step there. Where do we go? No, it isn’t just Google. Google plays a massive part in this. We have Google Alerts running all over the place because we’re constantly monitoring things. We’re monitoring the top 2000 companies as a starting point of the business, and there’s lots more to come to that.

But all Google Alerts does is essentially pass us into a place to find the information. Yes, we look at news media, we look at social media, and then we have a network of connections with other intelligence partners who provide raw data – so industry models, industry data – and we pass all of that into our intelligence model as well, and we rationalize, index it, organize it, and then run models against it and run algorithms against it to provide us with an outcome.

So it’s much broader than that. It’s the sort of stuff that sales staff – no offense to any salesperson out there, because there’s some super great salespeople out there, and I’d back myself all day, but I wouldn’t have been able to get anywhere near this level of granularity about a company and have a bigger picture of the industry at the same time in the sort of time that we’re talking about turning these things around.

And I would always go and ask our analysts. I had the privilege – we had them in-house, so I would go and ask one of our subject matter experts, “Am I getting this right?” The amount of times they said to me, “No” and I’ve gone, “All right, so what is the reality here?” [laughs] And not everyone’s that granular, I think, in their approach. I might’ve been a rarity, I don’t know, but there were other guys at the organization that definitely did it because I could really have intelligent conversations with them.

I surprise people sometimes when I talk about oil and gas. I know a hell of a lot about that industry because that was my baby when I was at the two companies I was working for, doing it. I loved oil and gas. Obviously it’s not that good for the environment, and I’m glad to say I moved over to a greener side of things, and I moved on to electricity and greener power generation. But I loved that industry. I absolutely loved it.

I would go to conferences. I was one of the only salespeople flown around the world to go to conferences and exhibitions because I could hold a really intelligent conversation with an executive at a company because I made the point of learning it. At our company, other salespeople used to get really pissed off with me. They’re like, “Why does he get the budget to do that?” “Well, you know as much about the industry as he does, and we’ll send you away.”

That is the thing that we will do for salespeople. We will give them that level of granular intelligence that they can bold as brass go up to any executive in the world and have a tangible conversation with them about something they’re going to connect with. They’re going to say, “You know, you’re right, that is exactly what I need. And you can do it, can you? Tell me more.” That’s what you want. “Tell me more.” Get them selling at themselves.

Ralph: It’s a fantastic point. Actually, when you were working, you did your own research, but you also talked to analysts that you had in-house that were able to give you that kind of stuff. If you think about the salespeople of today, for them to get access to the raw data that we can pull, they’d have to do their own Google searches and put Google Alerts in place. They’d have to have a subscription to D&B Hoovers or Global Data.

Kayne: You’ve mentioned the company I was working for. [laughs] To give you an idea. And their reports are expensive. These things don’t come cheaply. If you want to subscribe to reports from people like Datamonitor, just a report alone will set you back 5,000-6,000 pounds. Then you add that to your cost of sale, how many sales are you going to get out of that one report? If it’s used well, hopefully a few, but if it’s not used well, if you don’t know how to interpret it, if you don’t know how to do with it, you’ve got a real problem there because that insight is useless.

Ralph: Basically, you need a lot of cost to gain access to the information. Then you’d need the time and the capability as a salesperson to interpret it and turn that into something which is usable and useful to engage with your client, which is, as we’ve said before, going to take quite a lot of time. So there’s a cost barrier to having access to that data in the first place, and then there’s a time barrier and possibly even a capability barrier to turning that data into something that’s really going to move the needle.

Kayne: Yeah, absolutely. Creating desire with somebody to want to buy something from you – and there’s all these old sales models that talk about creating desires is the thing that you need to do – you have to have the desire to want to do that, and you have to have the capability do it. And it’s not there for everybody. It’s not possible for everyone. But it can be, because we live in an age where there’s so much data and intelligence at our fingertips. All it needs is interpreting and put to a point where it’s usable.

I think insight is not enough. Insight is not far enough, and that’s what I love about what we’re doing. We’re not talking about insight here because lord knows there’s enough noise in the market of insights. Insights into this, insights into that. Top 10 companies doing this, top 10 companies doing that. That’s great; it’s good to know that, but why does that matter to you as a salesperson? What can you do to add value, and where does that create an opening or an opportunity in the market for you? You’ve got to figure that out for yourself.

That’s research in itself. That’s “So-and-so, I’ve just seen a press release about so and so company doing this.” Okay, that’s great. So now you’ve got to figure out how you can take advantage of that press release. “In our industry they’re buying this tech at the moment.” Okay, do you sell that tech? “Yeah, I do sell that tech.” So who’s the buyer? What’s going to really push that buyer’s buttons? What’s their pain point? If they’re buying that tech, is there an opportunity for you to piggyback it? Is there a partnership opportunity? Is there this, is there that? There’s lots of variables there. That’s a lot for a salesperson. It really is. It’s a lot for anyone.

But if it’s handed to you on a platter by an analyst who’s a subject matter expert, who’s got machine learning coming out of his ears through our Now AI platform, you’ve stepped over that. You’ve given yourself a huge competitive advantage. You only have to look at the conversations and the way they’re going to fall, and it’s really easy to see – as an executive, you get pitched several times a day. It happens.

Let’s say, since I took on this role, on LinkedIn, I updated my LinkedIn profile, “CTO at Now AI.” What was the first thing that happened? Every recruiter on the planet pitched me for developers. And one I had a conversation with because he actually bothered to work out what I was trying to do. He didn’t just offer me a generic “We’ve got developers coming out our rear.” H actually looked at what we were doing, worked out that I was going to need people in a certain space, mainly machine learning, and actually pitched me on machine learning. I really appreciated that. Kept the guy’s details, only one I added on LinkedIn.

That’s the difference. It was the right conversation to have with me because he figured out I’d gone to a company that was in AI. I’m not just a CTO. I’m the CTO of an AI company. I’m going to want a certain type of person. I’m going to need a certain type of person, and he bothered to ask a question. “Are you doing it in-house?” Before he even tried to pitch me, “Are you doing it in-house? Will you have a need for people in the machine learning space? I believe you’re building an AI platform at the moment.” He got me. I said, “Yeah, I like you. That’s good enough for me.”

It’s such a small microscale. He’s taking the time to do it. He’s going to get a return on that investment, I’m sure, at some point or another when we need more heads. But we’re cutting all of that out for him. He could’ve had an alert in the morning that said, “Hey, Kayne Brennan just took on a CTO role at Now AI. They do this, this, this, and this. You can recruit this person, this person, this person. This person in your database is the perfect candidate for them because they’ve worked for other AI companies that do this, this, and this.” That’s matching. That’s pulling it all together. Anyone can relate to that.

Ralph: Cool. Just one other question. Once the data has come through the platform and the AI has done its stuff and the machine has learned and it’s collating it into the right areas and throwing out stuff that’s not relevant, is the information at that point, as it comes out of the platform, ready to be consumed by the salesperson? Or does it have to always have the analyst lens put over it on top?

Kayne: The analyst lens is really important. It’s really, really important because it is the difference between insight and intelligence. So yeah, what you need is that analyst to take that and deliver the intelligence to you as a business. The answer is yes.

There are other services that Now AI will be introducing over time that will help sales functions position themselves to make strategic decisions. For salespeople to broaden their knowledge of an industry and have a good understanding of what’s happening, we have our Now Index that we’re focusing on at the moment, which looks at what’s happening in the market, the volume of data that’s being generated within certain themes and certain spaces versus the conversations that we’re seeing happen on our platform and that we’re generating.

What’s really interesting about that is if there’s lots and lots of information and data being turned out every month – let’s say an IT thing like cloud services – but yet we’re not having any conversations on cloud services, none of our clients are asking us about cloud services, but there’s lots of activity in the market of cloud service, somebody should be filling that gap. Somebody should be coming to us, looking at that index, going, “Oh my God, tell me, what can we be doing? What’s an opportunity for us? What can we do? Look at us, look at them, help us. Create a conversation for me. I’m keen, and it’s clearly backed in the market.” It’s a really simple gap analysis.

On the flipside, you could also be looking at it and going, “You’ve got 200 bits of data that have come through this month in cloud services; you’ve got 75-80 conversations happening in cloud services, which is more than anywhere else across the network as an individual thing. That must mean my competitors are doing this. Why am I not in the mix yet? What’s happening?” You’re right, your competitors are having a conversation; you should be having them as well.

That intelligence helps people position themselves. There’s all sorts you can do with that. Yes, ultimately, I would say the intelligence comes from our analysts. It really does. But it’s really well-supported by the AI and the machine learning that we’re running with at the moment and the models we’re training that gives them the ability to do that at pace.

And that’s the key thing: its pace, its speedy turnaround, its fast response. You don’t want to come to us and say, “Analyze this now” and we come back in 3 months’ time with a report. What good is that to you? The market’s moved on. Someone’s bought something already. There’s no opportunity anymore. We’re talking same day, next day, same week, within a month, turning around big, really useful, powerful conversations. And it’s our analysts that turn those conversations around.

Ralph: That’s why it’s called a Now Alert and the company is called Now AI, because it’s about the immediacy of providing the intelligence, the strategic and the sales conversations, and then the salesperson being able to utilize them right now. Not having to wait months to do the research and then wait in order to be able to construct it into a conversation. It’s like, “Here’s your Now Alert; take it, digest it, understand it, bang, straightaway to the executive, have that conversation, and see how you can add value to them.”

Kayne: Yeah. It just wouldn’t be possible without this level of AI. We are farming an enormous amount of data. [laughs] We really are. The connections with third-party platforms we’re bringing data in from is enormous. It’s huge. It’s overwhelming, actually, so I’m really glad the machines are doing it. [laughs]

But yeah, it simply wouldn’t be possible for us to get those quick decisions without the platform that we’re building to support it. You would really have to go some. You really would. And scaling the analysts around that is a good problem to have, I think.

Ralph: Perfect. That’s amazing, Kayne. Thank you very much for taking the time today to talk to me, to tell me about your world and what you’re doing within Now AI. Today’s podcast is being called Turning Data into Insight Through AI.

We’re going to be talking to Jeremy Griggs, who is our Chief Intelligence Officer, about how we then take that insight and turn it into the sales intelligence. A lot of the stuff that Kayne and I have been talking about today in terms of surfacing those intelligent conversations and what the analyst team does, I’m going to grill Jeremy on what they do, how they do it, how they make what the machine gives to them human so that the salespeople can take that to the executives and are able to have meaningful conversations.

That’s coming up on a podcast later in the series, but for now, Kayne, thank you very much indeed for spending the time. Back to lockdown heaven up in North London there.

Kayne: I don’t know if it’s worth saying it – when I first met Pete, Pete took me through what they wanted me to achieve. The platform was a little bit different to this. I had my sales director hat on, and I was genuinely like, “No way you could do this.” Just the concept of it really super excited me, which was why I wanted to build the MVP.

And now to actually see it becoming a reality, I’m like, wow, this actually can be done for sales stuff. I find it insane, I genuinely do. That’s why I love these things. From a complete genuine standpoint, I genuinely look at the platform and think, my God, I would’ve killed for this – killed for it – back when I was a salesperson. There’s nothing better – you know how they say about salespeople that if you enjoy what you’re selling, you’ll sell it well, and if you believe in what you’re selling, if you believe in your product, you’ll sell it well? There’s more to it than that.

Because I genuinely believe this and because I can see the benefit it would’ve added to me so many years ago, I get super pumped about it. I get a little bit weird about it, just the reality of it. That’s why training this AI model has become a bit of a personal mission, to make it the best it can be. I’m like, this is amazing. This is genuinely amazing.

There’s very few things that come across your desk when you’re a developer – “Yeah, I’m just building another platform. I’m just building another app. I’m just building another website.” You get a little bit like, ugh. This is the one thing that’s come across my desk in the last 5 years that I’ve been like, “This is excellent.” It just is. It’s really inventive. It’s rethought the way that salespeople should approach selling.

You could really easily mix it up with account-based selling. We really separated ourselves from that and said this isn’t account-based selling. It’s executive-based selling. But it’s not possible unless you have us in your back pocket. And I truly believe that. I truly, truly believe that. I look forward to that epiphany moment where companies start talking about executive-based selling the way that they talk about account-based selling now, because I genuinely believe that’s going to happen. I believe Pete is going to be the centre of those conversations, and Now AI is going to be the centre of those conversations, and people will be going, “We’ve been missing a trick here.”

But it wasn’t really possible until now because we didn’t have the capabilities that Now AI gives us. I genuinely believe that’s what’s going to happen.

Ralph: That’s amazing. Anyone would think that we might have prepared, because one of the podcasts that we’re going to be broadcasting a little bit later is all about executive-based selling – what it is, how it differs from the usual account-based marketing, account-based selling, etc.

There really is a new category here in selling to the executive and actually treating the executive as the key, because actually, what is the company? The company is the executive and vice versa. So it’s all about treating them with the respect they need and walking in their shoes and working out how to help them as individuals who, in turn, are working on behalf of their organizations. Absolutely spot on.