Ralph Varcoe: Avoiding wasted sales time helps you sell more

Ralph Varcoe talks to Ian Redfern about how sales teams can avoid wasting time, energy, money by having a consistent approach to sales intelligence gathering.

By using now ai’s sales intelligence platform sales teams can spend more time out selling and less time doing inconsistent desk-based research.

An increase in time selling = an increase in business sold.

Listen to the full podcast here.


Ian Redfern: Intelligence in context drives a targeted conversation

You need your sales team to be as focused and targeted as possible. Why? So that what they say and how they say it resonates with the executive they’re selling to from the moment they engage in a conversation.

now ai delivers context – around the executive, their company and the industry – so that the intelligence is bang on. And this, in turn, helps sales sell more and faster.

Listen to the full podcast here.


Ian Redfern: From impersonal ABM to personalised selling

Ian Redfern talks about how selling a frying pan can be improved with personalised selling!! It’s a really interesting perspective which illustrates really well what now ai does differently (and better).

now ai contextualises and personalises everything so that sales can sell faster because they are more relevant and talk in a way that customers wants to engage with.

Listen to the full podcast here.


now ai podcast episode 4: Executive-Based Selling

In a change from the usual set up, Ralph Varcoe has swapped seats with Ian Redfern, who picks up the challenge of being host and questioner. Ian interviews Ralph about his role as Chief Revenue Officer at now ai and asks – ‘what is this executive-based selling all about?’. The conversation covers topics including the traditional ways B2B companies sell and how those who don’t embrace the concept of putting the executive at the heart of the conversation with true personalisation will find themselves left behind by their competitors who do.

Ian Redfern: Hello, everyone, and welcome to the latest in the series of the Now AI podcast, where today I’m going to be talking to Ralph Varcoe, who’s the Chief Revenue Officer of Now AI. Normally, Ralph would be hosting; he’d be doing the job I’m doing. But today, I’m going to interview him because it’s important that as well as interviewing some of the guests, that we get an insight into some of Ralph’s views on the pressing issues of the day.

Today we’re going to be talking about executive-based selling, but before I get on to the main event and grill him about that, maybe we should start by asking Ralph to explain a little about who he is. Could you just give us a little bit of your background and things you’ve done in the past and so on?

Ralph Varcoe: Yeah, absolutely. Thanks, Ian. Thanks for taking over the grilling job. I’m scared, very scared, but we’ll see how that goes. [laughs] Right, Ralph Varcoe, Chief Revenue Officer for Now AI. In the past, I have run sales teams, marketing teams, strategy, and also partnerships in various different technology companies – the likes of Orange Business Services, Virgin Media, CenturyLink.

I worked for a time in a small startup around the AI space in Spirit AI, which was all about developing AI natural language processing for the games market. That was actually very interesting. It was all about how you can make characters in games talk to you just like they are real people, with the whole natural language processing stuff.

So lots of experience in running sales teams, and I joined Now AI because I thought the time was right to make a move and to come into an organization that I think is doing a fantastically new and different and much-needed thing. It brought together the whole interest that I had in AI and the experience that I have around sales and marketing. It was almost like I liked the company so much, I decided to buy it, that kind of thing. So I’ve really bought into it.

Ian: Who was that? That was a razor company, wasn’t it?

Ralph: Yeah, it was. Was it Remington? Victor Kiam, was that his name?

Ian: That’s it. Definitely Victor Kiam. Oh, you’re taking me back there.

Ralph: I know. And it just shows how old I am.

Ian: [laughs] So how long have you been working with Now AI?

Ralph: I’ve been on board only for the last month and a half, full-time, working out how we’re going to be going to market. I used to do quite a lot of volunteering working with Virgin StartUp, as an example, where they had lots of entrepreneurs who get given a loan, and part of the condition of being given the loan is that they then have to have a mentor. So I acted as a mentor for a number of startups.

Pete Pastides, who is your friend and mine, who’s the owner and founder of Now AI, had come to me last year to say, “We’re thinking about doing this. What do you reckon? Can you give us some advice?” So I did some free advising on what we could be doing, how we could be moving, etc. That’s how I got to understand what Now AI was doing, how it was different, and how this could be changing the face of the B2B selling model, and I thought, “Great. Time’s right. Let’s make a move,” and I decided to make the move literally as the COVID-19 pandemic was locking us all down.

I had a few moments where I was gulping, clenching the buttocks, and going, “Is this the right thing to be doing at the right time?” But the more I thought about it, and the more I thought about the changes that lockdown, COVID-19, etc., were bringing, the more I thought this is exactly the kind of service that companies are going to want to take and make use of in order to give them some differentiation and competitive advantage as we get out of this current situation.

Ian: I think what we’re seeing in terms of interest so far means you’re on pretty safe ground there.

Ralph: Well, I hope so. Time will tell. But it felt right, and it still feels really good. So yes, it’s all really very exciting. I’m really pleased to be here, and I’m enjoying the ride so far.

Ian: That’s great. Thank you very much for spending the time with us today as well. I know the topic, just to restate for everyone today, is executive-based selling. I’m guessing from the last few moments the reason that this means so much to you is not only because you were selling to executives at some point during your time at OBS and Virgin and so on, but you’ve also been the subject of campaigns by other companies trying to sell to you. Probably what Now AI is doing is resolving some of the issues that you saw during those times.

But rather than me stating for you what you mean by executive-based selling, why don’t you just give us your viewpoint on the topic? What’s the framework around this topic for you?

Ralph: That’s absolutely right. I have been on the receiving end of plenty of campaigns, organizations looking to sell marketing software, digital agencies, sales improvement programs – all sorts of things like that. But I’ve also run sales teams where my team members are selling to organizations.

What’s clear to me is – I ask the question: what is the organization if it isn’t the executives? Yes, an organization has a set of capabilities, it has a set of products, it has a set of services, it has a function to provide whatever it does to its customers. But when we sell, and our teams sell, they don’t sell to the company. They sell to the executive. It’s the executives that make the decisions about what to buy, who to buy from.

What has been clear when companies have been selling to me is that I feel like I’m just a number. I’m just an organization and a name that is on a list somewhere, and I’m being sent something, and they’re hoping that I might be caught at just the right time to be looking for the thing that they happen to be selling at that point in time.

Ian: Yes, a bit like Battlefield.

Ralph: Yes, exactly. “Let’s fire and see what we hit, and see what comes back.” As an approach, I can get it, because having run marketing departments, you’re constantly looking at who is your target market, who are the people you want to go after. You know that there’s stuff that you do which is being sold by your competitors into those companies. Typically as a marketer you go, “If the market is a 10 billion pound market, let me take 5% of that and then I’ve got a really compelling business.”

But you’re not quite sure what that 5% is or how you’re going to get there, so you go, “Here are the companies. Let me just go out and say, ‘Hey, we’ve got something. Do you want it?’” It’s quite an impersonal approach. It’s a similar thing with my teams and me going out and selling to other organizations. It’s quite difficult to have the relevant information to drive the conversation into a personalized one, and therefore it tends to be relatively generic.

Ian: Yeah. That point that you raise about what is the organization if it’s not its executives is really smart, I think. My history, as you know, is I used to work for Cisco, and I would regularly get sold to. I found that I was only as interesting as Cisco was. [laughs] Nothing to do with my personality, but they knew that Cisco was for the most part a company that was doing very well and was prepared to invest in things that would improve its operational model.

Therefore, I would get many, many things that were just nowhere near relevant to me as an individual. It was almost like we were the football club with the most money to spend, and therefore the agents would try and sell us every player on the market. That’s how it felt.

Ralph: One of the challenges, though, is that there’s a difference between new business selling on a mass market level and then selling into key accounts. They’re actually quite different beasts. Where you’re talking about trying to penetrate into a new market and you’re trying to drive awareness, you can understand why that model of pushing out lots of messages to lots of people you don’t know is something that’s going to work – because how else do you know who exactly you want to target? Who’s the right organization and which executives are looking to buy at a particular time?

So from a completely brand new business perspective, that tends to be a way that it happens, and there’s a place for that. But there is also a place for being a bit more targeted and doing the research on which of the companies have got the propensity to buy because there’s a need, then looking at the individuals within that organization who are going to make the decisions. How do you then tailor your conversation to meet the objectives and needs of that individual who works for a company that is operating in an environment, in an industry, that is part of a global cycle of upturn, downturn, and all that sort of stuff?

What we’re trying to do at Now AI is move towards something that actually becomes truly personalized. In the case of key account management, where you’ve got your largest accounts, you’re wanting to look at how you grow your wallet share; that’s clearly an objective you have as a sales engine. You’re trying to work out how to maximize the amount of revenue that you’re making as a business by driving as many of your services through and into them as possible. But how do you do that effectively and efficiently?

Having a service that enables you to clearly understand who the executive is, put them at the center of all of this so that everything else flows from that – that’s the smart way to do it, and that’s the way that business-to-business selling is changing, has been for a little while, and certainly has accelerated because of the pandemic and the lockdown that we’ve had over the last couple of months.

Ian: It’s interesting that in the B2C space, through something like a Spotify model or a Netflix model, it’s entirely based really on getting as granular as possible with the end user about what they like, don’t like, what they like to view, when they like to view it, and so on and so forth. These people who consume Netflix and Spotify are also people that work in businesses, so if they become used to that model at home – it’s like B2B companies have suddenly decided, “It’s okay because as soon as they leave their house, they become robots whose only value is ascribed by the company they work for.”

When you state it like that as you just have, the distance between how well B2C subscription services have dealt with their customers and have developed models for their consumers over the last decade versus what B2B has done – the difference in progress is quite stark, isn’t it?

Ralph: It is. And you’re absolutely right; the consumers in the B2C world are the same people that are buying in the B2B world. They just happen to be buying on behalf of their companies rather than themselves or their families. So the psychological sales model should be the same.

What is the sweetest word in the English language, or the sweetest word in your mother tongue? It’s your own name. I think when we talked before, you said that when somebody calls your name across a crowded room, you hear it instantly.

Ian: Yeah, you’ve got that selective perception for it.

Ralph: When your name is used, it feels good because somebody’s addressing you. And if your name is used and then something is said afterwards which actually relates to you as an individual – either as a consumer or as a business leader who is getting stuff done and organized in a business that you care about and you’re trying to drive objectives for – that resonates, and that lands more easily and better than something that’s just generic, which is a kind of, “Hi, CIO. We understand that CIOs have these problems. We address these problems in your industry by doing this.”

Ian: [laughs] Sorry, I thought you were reading an email I got this morning. Now you’ve got me interested. Let’s see if we can dig a little deeper into this. There are models around that claim to be able to do this. Or at least with my understanding of things, account-based marketing (ABM) and other variants of that, whether they be account-based engagement or whatever, claim that they are doing this. Is that wrong?

Ralph: They claim they’re doing it and some are doing it to a degree, but none is doing it to the level that we are personalizing. It’s a continuum, if you like. You start at one end, where you’ve got traditional business development and you’ve got salespeople that go out and they’ve got their list and they know the companies that they need to go after, so they approach each one of them.

Marketing may send out blanket emails to all of them, which is a call to action around a particular product. Most marketing campaigns in the past, and many still today, are all centered on “We’ve got something new to say. Here’s a new product which we’ve just launched. Come and talk to us about our new product.” And there’s a place for that, but it is all about the company who’s trying to sell the product. There’s no understanding or attempt to demonstrate an understanding about why the people that are being sent this message would care about whether you’ve got a new product that’s available at a particular price point and that does X, Y, or Z.

Then if you look at account-based marketing, which became a real rage a while ago – but actually, what I’m seeing when I’m talking to a number of marketing professionals is it tends to be dwindling a little bit – but it’s still there. Account-based marketing says, Let’s market to the account. Let’s go after Volkswagen in the automotive industry, and then let’s look at what the persona is of the different types of roles within that organization. We know that CIOs think about X, Y, and Z, so it’s therefore realistic to assume that the CIO of VW and the CIO of BMW and the CIO of Ford Motor Corporation are going to be having the same issues, and therefore let’s tailor the message and let’s talk a little bit about the industry, let’s put a little bit in there about the organizations, but basically address it to the persona.

That’s still not personalized. You may go, we know that the CIO of VW is Martin Hoffman, so let’s go “Martin, hi, this is something we know about your organization and we know this is a generic issue that you have” – clearly it’s not stated as a generic issue; it’s stated as “this is an issue that you have,” although it is a bit of a generic one. That’s making it slightly personal, but that’s not personalization.

What Now AI is doing is saying we’re going to start with the executive. We’re going to understand who they are, what their background is. We’re going to look at what their objectives are within the organization that they operate in. We’re going to look at the sorts of things that keep them awake at night that they’re tweeting about, that they’re posting on LinkedIn. We’re going to look at all of those things and then we’re going to tailor a conversation which addresses how the executive is working in their world.

So start with the executive; then look at the context which is around them of the organization they work in. Then there’s a wider context beyond that, which is the industry they operate in and the kinds of customers that they’re trying to sell to, and the wider context still, which is the global economy or the local country economy and the various things that impact those.

Ian: It’s really sitting in the seat of that individual and looking back at your own company as opposed to what is traditionally the way of doing this, which is that the selling company effectively works on its own – agenda is the wrong word, but it has internal cycles of product releases and fiscal times of year and so on and so forth, and that typically is the way the selling company organically plans things.

This is about really sitting in the seat of the executive and looking back at your own organization and saying, “How do I look from his point of view, with all of these filters in between, with his objectives in between, with the situation of the industry in between, the market conditions, the economics? Can he or she even see me from his or her seat given all that’s going on, and are my messages relevant enough for him or her to take notice?” Is that where you’re going with this? It seems like it is.

Ralph: Yeah, totally. It’s about walking in the shoes of your customer. It’s about taking on the persona, the role of that customer and actually thinking, “What is it that I can do to help them?” There’s a television program that’s on Amazon Prime that the kids like called New Amsterdam. There’s a director of medicine in the hospital who walks around, and his stock phrase is “How can I help?” It’s a bit of a joke in the show, but it’s that principle.

But it’s not a principle of just walking up to a customer who you don’t know and going, “How do I help?” and then wasting an hour of their time, an hour of the meeting that you’ve managed to secure, by getting the customer to tell you about themselves. How disrespectful is that? Yes, there can be a conversation because you don’t want to assume you know everything, but you should walk into that meeting, and when you ask, “How can I help?”, you kind of know what the answer is already because you’ve understood it.

Now, there may be some nuances which you hadn’t understood because you’ve got a bit of desk-based research and analysts that have provided you with some stuff, and there’s nothing that replaces talking to the person directly as a way to finesse what you’re doing. But you should be walking in there knowing how you can already help them and saying, “Does this work? How can I help you? Does this work? If I did this, would it be able to…?” So you’ve already got an arsenal of answers because you have really got the research that’s been done on them as an individual, on the company they work in, on the industry they work in, on the global macroeconomics.

Then your product and service set is factored into that so that you know how your cybersecurity widget or your great new sales enablement program actually helps them to drive a bit of an increase on their ROI or a reduction of their TCO or acceleration of their ability to take something to market, with some quantifiable levers that you can show how, when pulled, will actually make a tangible difference and will make their lives better, will make their company’s life better, and will make them feel a little bit like a hero.

Ian: Just bringing a few things together from what we’ve said so far, ABM has been out there, but from my own perspective there’s been limited success. Those that have made it work seem to have made it work pretty well, but even then on a relatively limited number of accounts. But for the most part, it seems to be the gift that never gives for a lot of organizations. One of the reasons for that seems to be that it’s quite heavy lifting.

So if we’re now suggesting that organizations need to go even further and they need to go beyond just account-based marketing to executive-based selling – because that’s the progression that’s being recommended – surely we’re going to hit the same wall, which is that there isn’t enough time, there isn’t enough budget. The budgets for doing this kind of business development work are forever being cut at the end of the quarter and being put back into the coffer for margin support, all of this kind of stuff. How do we get around that?

Ralph: It’s a great point. If you’ve got a program that’s being run by a group of people – and typically for ABM, it’s being run by the marketing team; they may have an ABM manager, they may have a bunch of people that are working on that – then that’s doing quite a lot of the heavy lifting, probably with some kind of a tool/software type package which is providing certain insights and lots of data.

With ABM, you’ve got a team of people that are working out what to pull together and how that then addresses the personas and the accounts which they’re going after. This whole executive-based selling is more aligned to sales going out to have those conversations with the executives. Marketing will be able to take the same information and drive it through into some of their marketing programs for sure, but this is about putting the executive at the heart of the selling. That’s why we’re talking about this being executive-based selling rather than executive-based marketing.

Salespeople are brilliant at selling. Some of them are really good at doing research; some aren’t great. We’ve all had people in our teams who have been at different points in that spectrum. It’s going to take a lot of time. The issue is that if you ask your salespeople to do it, there’s going to be a lack of consistency. There’s going to be a lack of the ability to scale.

Ian: And it’s not really why they were hired. They were hired to sell. It’s interesting because you just sparked a thought with me that the ownership of a salesperson of a specific account becomes much higher when they have this level of information. A lot of the time, as you’ve said, it will be the business units or the product group just pushing out new products and services and saying, “By the way, because you’ve done this, we are going to sponsor you with a certain amount of money to go and run an event for these companies.” That’s the business development asset.

At this point, with the information that’s being provided, the example by Now AI, that salesperson is able sometimes to turn round to the business unit and say, “Actually, that’s not right for my account at the moment.” So the overall control and ownership of that relationship very much drops onto the salesperson’s lap in a much greater sense, probably, than it would have been in an old model.

Ralph: That’s right. The ownership within a sales team and a salesperson is definitely going to be higher if they own and feel like they are part of the process and if it’s actionable as well.

Coming back to the point about it not being scalable if you’re setting your sales team on that, actually it can be scalable now. You have all this data that’s available. That data somehow needs to be sifted and collated in a way that’s relevant. That data therefore gets pulled together to become insight. And that’s typically what account-based marketing software programs tend to be about. It’s about the insight into an account, the insight into an industry, even insight into an executive.

We’re taking it a step further. We’ve got the platform, which looks at how we can get the machines to learn, how we can get the artificial intelligence to do its thing, to work out that actually, when we’re going after information about a company, we’re looking at the company rather than necessarily the brand name.

We’ve had examples where a large brand sponsors a sports stadium. Well, if you were to do a search on that large brand, you may well find that the first 100 returns that you get on Google are all about the sports stadium because people read lots of stuff about sports, and therefore it goes up the Google search rankings. But that’s not relevant, necessarily. It could be, depending on the project, but it’s not necessarily relevant to what you’re looking to find out about the organization.

Our platform will weed that stuff out. It will curate, collate, bring that together so that you’re turning data into insight. Let the machines do what the machines are brilliant at with the right algorithms in the center so that you’ve got that insight. What we’re then doing, rather than saying we’ll leave that and we’ll present it in a browser or in an app to a sales or a marketing person as a bit of insight, we’re going a step further and saying we want to turn that into intelligence. Insight on its own isn’t enough. Let’s turn that insight into intelligence.

We use our team of analysts – we’ve got a follow-the-sun model, so we have a team of analysts across the planet who are looking at this kind of stuff who are very well knowledgeable about the technology area, about various industries, about all the industries that we’re going after, and are able to take this insight and craft it into a conversation that a human would have and craft it into a conversation that a human on the receiving end of it would understand and would take and would go, “Yes, that makes sense and that is personalized to me in my situation.”

We can scale that. We can do that quickly because the machines do their thing; we then provide it to the analysts, they do their thing relatively quickly because they’ve got a lot of experience, and there’s capacity to do that, and then we can turn that back to a salesperson as a conversation that they can action pretty much immediately. Yeah, they’ll have to read through it and they will need to make sure they understand it so that they can articulate it and defend the line of argument that they’re going to present to their executive, but we can do that really quickly.

That frees up the time of the salesperson. Instead of them having to do 35% of their time sitting in front of a desk, trying to work out what they’re going to say, looking at all that data, getting overwhelmed, trying to see which bits are relevant, pull that together, and then go, “Hang on a second, how does that relate to the service that I have? Oh my God, there’s all these different things,” we do that for them. Which means we can present it to them, they have less time they have to spend in front of the computer, more time in front of the customer.

A sales director can then say, “Because you’re being more efficient and more effective because of this stuff, but because of the efficiency gains, I can give another one or two accounts to each of my sales team. And with that same kind of information, I can start to see how the pipeline grows a little bit more quickly.”

So there’s an efficiency gain, there’s a pipeline generation gain, and there is a velocity through the pipeline gain as well because this is all done in a scalable and intelligible and intelligent way to furnish the salespeople with something that they can action straight away.

Ian: You’ve said an awful lot that’s got my interest there. Let me just unpack one or two bits. If you can confirm for me that I’ve got these right, what Now AI is doing is essentially – and I don’t know whether it’s 80/20 or 90/10, but the majority of the research, the scouting, the web calling, assessments part of this, this idea of finding new opportunities relevant to the executives, is being done by a machine. And thankfully, because I’ve been on the wrong end of some AI-driven stuff, the balance of that process, an assessment and a relevant check and also turning it into a true conversation, is being done by people. So you’ve got that combination. Is that right?

Ralph: Correct, yeah.

Ian: And there’s capacity in that model, and presumably that model can be turned at a number of different types of problems. It could be turned at selling something specific to raise its numbers by the end of the quarter if you’ve got a product that’s underperforming, or it could be selling a new bundle or all kinds of things. Basically you can point that service at different problems. Is that right?

Ralph: You can point the service at different problems, but always remember that you’re coming at it from the executive first. The product that you may be trying to push because your numbers are down and all that sort of stuff needs to be looked at in the context of the executives that have a need for that kind of thing right now, rather than just a generic push.

Ian: I guess that’s why I find it interesting, because it’s the removal of those executives that would never buy it that is probably the biggest saver of time for the salesperson. They are basically going to be always talking to people who will have an interest, right? That’s the idea.

And if that is true, then I think you may even be underestimating the number of new accounts that an individual salesperson could take on, or even the number of parallel sales engagements within a single account. Different contacts could be taken on. In my experience, you’ve probably got anywhere between seven and eight meetings out of ten that don’t necessarily progress towards a sale. As you said earlier, it’s information swapping with executives and that’s it. It’s not moving things down the pipe.

The idea of having something that removes those targets that will never be interested and focusing the salesperson on spending time with those that will has this lovely efficiency and effectiveness calibration to it that’s pretty cool.

Ralph: Yeah, and just think about the days that salespeople are out of the office. In the days before COVID-19, when people were hopping on flights or jumping in a car, spending a day to get to have a 1- or 2-hour meeting with their customer, the cost of the flight, the cost of the taxi, the cost of the hotel, the cost of the time that it takes to have that meeting, the day out of the office where no other prospecting is being done, where systems and tools and CRMs and what have you in the office aren’t being updated, where they’re not able to do the training – you could draw a whole list of things that are real, tangible, money-out-of-the-pocket costs, and then intangible costs around lost opportunity or lost ability to do other things.

I’ll use the statistic that you said there. If seven to eight meetings tend to, in the past, be information gathering and don’t really drive towards a sale, just imagine if you could turn that into three or four of the meetings out of ten are not driving you forwards because they’re about rapport building and all the other sorts of things you do – because not every meeting is absolutely geared towards a sale.

You have then slashed your costs and increased the amount of selling, effectively by 100%, because you’ve got something that’s focused and targeted which is relevant to the executive who’s given you a chunk of the time they don’t really have available in their diary for you because they’re so busy juggling so many different balls. You’re making it a much better experience for the executive, you’re making it a much better experience for yourself, and you’re making it much more efficient and therefore effective for your sales director.

Ian: So this really is about getting more from every interaction. It’s a return on every interaction, a return on the overall investment. This is a process which is making every interaction more valuable. I think that’s an interesting way of looking at it.

Ralph: Yeah. Let’s say I’ve got five different things that I could change as levers within my business as a sales director. One is the number of accounts a salesperson can handle, another one is the amount of pipeline hat they can generate, another one is the velocity through the pipeline, etc.

If I could move each one of those by 5% and you compound those against each other, you’ve suddenly started to get something which looks materially different and where an ROI model is quite easy to look at and to prove that an investment of your top ten accounts having the Now Alerts, which provide the salespeople with this great intelligence, putting the executive at the center of it, suddenly starts to return multiples back. It becomes quite easy to justify that incremental spend.

Ian: That’s excellent. Thank you ever so much for speaking with me as I attempt to get my head around this. It feels very much like the way in which sport coaches teach really high level athletes, which is this idea of focusing on the process, and the outcomes will look after themselves. This is a new way of selling based on executives. It’s really putting them at the center, getting a better return from each of the interactions, and driving that ROI. And I’m sure, knowing you, that there will be another podcast episode which looks specifically at the ROI on this. I’m pretty sure that’s coming.

Ralph: It is, yeah.

Ian: That’s great. Thank you very much for spending the time with me.

Ralph: Pleasure.

Ian: Enjoy the lockdown while it lasts, and I hope to see you when we’re out of it.

Ralph: Indeed. I look forward to that.


now ai podcast episode 3: Turning curated insight into targeted intelligence

In this third episode of the series, Ralph Varcoe interviews Jeremy Griggs, Chief Intelligence Officer at now ai. The areas covered include how to move beyond insight to a world where the contextualisation of the industry, company and executive, combined with the product and solutions portfolio become a powerful force for differentiation and greater customer intimacy. This combination of the artificial intelligence within the platform with the human intelligence of the analyst team is where the USP lies for now ai.

Ralph Varcoe: Welcome to the latest edition of the Now AI podcast. Today we are joined by Jeremy Griggs, who is the Chief Intelligence Officer at Now AI. Jeremy, tell me – we’re in lockdown heaven, still, within the coronavirus pandemic. I’m in my house in Leafy Hampshire. Whereabouts are you today?

Jeremy Griggs: I’m on the south coast in Dorset, which is where our family has been brought up over the past 20-odd years.

Ralph: Fantastic. So you’re close to the beaches. You can get rammed in like sardines on the beaches, like some of the images we’ve seen over the last couple of days.

Jeremy: Yeah, I’m trying to avoid that by going down there really early in the morning or late in the evening. Avoid the tourists.

Ralph: You have a dog at home, so are we going to be joined by the dog at some point during this podcast?

Jeremy: [laughs] I can’t promise we won’t.

Ralph: [laughs] The barking at the postman, no doubt.

Jeremy: No doubt, no doubt indeed. Yes.

Ralph: Get the dog to give a nice bark at your phone.

[dog barks]

Excellent. Thank you for joining. Can you just tell us a little bit about your background? Before you joined Now AI, where did you work? What’s your experience? Who is Jeremy Griggs?

Jeremy: I’ve got a 30+ year background in the technology sector. I worked for quite a while with BT, British Telecom, in various roles around the world, focused primarily on the intersection of strategy and products and sales, so that’s always been my focus area. Also spent some time in a dot-com startup, so I’ve worked both large and small businesses. But probably for the last 15-20 years, a big focus on industries and technology transformation in industries.

Ralph: You have the title of Chief Intelligence Officer, CIO. We’re used to a CIO being a different thing, somebody who’s looking at the information, Chief Information Officer. But you’re called the Chief Intelligence Officer. What does that mean?

Jeremy: Best title in the world, I think. Intelligence is what we’re about. It’s how we bring real, actionable insight, something that people can actually drive their business with, and it’s intelligence. It’s my role within the business to bring together everything that we do and then focus it in on our clients so that they have absolute clarity and opportunity to drive their sales.

Ralph: Great. In an earlier podcast, we talked to Kayne Brennan, who is our CTO. He was talking about the platform and developing a platform based on AI, machine learning, natural language processing, all of those amazing things that are in the middle of the platform, and how that platform was taking this incredible proliferation of data, an overwhelming amount, and translating that through lots of clever ways into what I would call insight into companies, executives, industries, etc.

I’m assuming that he pulls all of that stuff together in the platform and then he presents you with stuff you can use. Is that the best way of describing it?

Jeremy: Yeah, that’s spot-on. You’re absolutely right. There is such an overwhelming wealth of data out there. Actually, the challenge is to find the nugget in the mountain. It’s finding those things that are really going to be important to our clients and then serving those up to my team to, if you like, polish it. Take it from a raw material into a finished product.

That combination of the AI and the computer’s ability to just keep processing and finding things, and then with the human element, the analysts in my team’s knowledge of our clients and our clients’ business, knowledge of their markets and their market spaces, can add that human nuance. It’s the combination of the two together which we think is the power behind our business.

Ralph: I remember when I was running marketing for Tata Communications – and in fact, when I was running sales and marketing in a number of other organizations too – we had some amazing tools and programs, account-based marketing type programs and tools, which provided really good insight into the industries that we were selling into and also into the companies that were on our target market list. That insight was really useful.

What is the difference between that kind of insight and what Now AI is providing in terms of intelligence? What’s the difference? Why is it better?

Jeremy: I think there’s a couple of reasons. It’s all around context. If you’re in a sales engagement, you need to be ensuring that what you’re taking to market is pitched against what you can sell. I think the first thing we do is make sure that all our intelligence is contextualized against a specific set of capabilities that our clients are looking to sell. It’s about that sales journey.

But then even more importantly, people sell to people, and the one thing that’s missing in the ABM world is it’s based upon personas rather than actual executives. What we really focus on is, who is the specific executive that this conversation, this sales message, needs to go to? And what is it that they’re about, and therefore how can you position it to them? Really making it personal against the executive and making it appropriate and contextualized against the portfolio of our client.

Ralph: That’s an interesting word you’ve used: personal. To play that back, you’ve got the insight that’s coming out of the platform around industry, around the company, and around the executives. Tell me, how does your team then personalize the information? How do they make it really relevant so that it resonates?

Jeremy: It’s a combination of working closely with our clients and really understanding what they’re trying to achieve, what their portfolio is, and their plans and their aspirations with the particular target accounts. That’s something that the machine and the machine-based, platform-based system can’t completely do, so that combination of AI plus the human is pretty critical. It’s really then about looking at the target executives and their ambitions, objectives, priorities, what they say and how they say things, and that’s how we can personalize the message.

Ralph: So your analysts are let’s say humanizing the message. The machines do what they’re brilliant at, and then the analysts work out actually how to turn that into a conversation that an executive would respond well to that’s delivered in a human way, that a salesperson or an executive within your client would be able to deliver in a human way.

Jeremy: Absolutely spot-on. It is that combination of the power of AI to go wide and throw the net extremely far in combination with the human that understands the subtleties and the nuances that we know is a part of the sales toolkit and skillset.

Ralph: These analysts that you have, what kind of profile are they? Also, can you give me an idea as to how you work with them across the world? Have they got particular skillsets around industries, or is it skillsets around actually thinking about the psychology of working human to human and translating that? Is it across the world, is it in one place? What does this team look like and how do you manage them?

Jeremy: We use the power of the 24-hour working day to drive the business. We have analysts situated out in the Philippines, and in the future we’ll have analysts situated in the Americas so that we can monitor the world 24/7 because the world never stops, business never stops. So that’s the first thing.

The second thing is we always have two people that have sight of any one particular piece of work. An analyst in the Philippines may start something off, but then we’ll have a researcher based perhaps in the UK that will work and polish it again. So there’s a double opportunity for human eyesight on it.

The analysts and the researchers have experiences in the industries. That’s important. We need them to bring their experience to bear in this and to be able to have understanding of our clients’ businesses themselves.

The second thing is really understanding the technology, because this is about the translation of business need, business strategy, market drivers into how technology will help transform that business because that’s the world we’re living in. It’s a world of digital transformation. So an ability to apply what an industry is doing into how that will impact in terms of technology and the portfolios of our customers is crucial.

We use a blend of skills, but it’s a real focus on understanding our customers, understanding the technology drivers, and using our experiences and knowledge base to add that subtlety and that personalization and context to our client messages.

Ralph: It’s a fascinating approach, having two analysts working on any one piece of conversation or working on one alert which is going to a customer. Do you also actually mix the generations? You and I, let’s be honest, we’re slightly greying. We’ve been around the block a long time. You mentioned at the beginning you’ve got a 30-year career, as do I. We’re in the older age bracket, so we’ve got a perspective on things which come with a little bit of age and experience.

But there’s a huge value in having younger people who are probably more tech-savvy than we are, who are actually looking at these sorts of things as well and putting their perspective on it. Do you mix and match the analysts in that way as well?

Jeremy: Absolutely. You’re absolutely right. We have different perspectives on how technology fits into the world and how technology fits into our life depending upon our life experience of that technology. We remember the days computers arrived and mobiles arrived, and the generation coming into the workforce have never known anything different. That does put a different perspective.

We want to harness that, because as you look at our customers’ clients that they’re trying to sell to, they are having to deal with this changing demographic in the world today, and that has a huge influence on the products they need, the businesses they’re running, and the customer services they’re delivering, and the skills and the workforce they’re bringing on board. All of that plays out into sales opportunities, but outlines are going to get us to go forward. So yeah, absolutely, it’s a critical part of the mix.

Ralph: If you’ve got technology and industry being pulled together, and the analysts have got the information that’s come out of the platform – and as I’ve spoken to Ian and to Kayne about previously, we’re looking at essentially triangulating industry, company, and executive, and then overlaying the product set of our client onto that to try and surface up opportunities for our client to be able to sell into the accounts that they’re interested in, for whom we’re doing this research.

How does the analyst team take all of those elements and then actually turn them into a sales conversation? Because sales is quite a skill. It’s quite an art. Your analysts must be amazingly talented to be able to do all of that and pull that into a structure which enables it to resonate as a logical sales argument that an executive is going to respond well to.

Jeremy: Yeah, and that’s where I think the experiences of the researchers that have spent many, many years in sales and understand the skills of how sales and a sales approach differs from perhaps the need for analyst reports to do product development or for marketing purposes and things like that.

I think that’s absolutely key to why we think Now AI is different in the market space, because we take the classic insights and turn them into the subtleties of a sales conversation through the experiences we have – but also through an approach of we’ve all been through it’s around the situation, what’s the problem, and therefore, what’s the implication, what’s the need? It’s not new, but it’s actually the approach of how, typically, a sales cycle will go.

That’s really what we’re trying to build into those sales conversations. What is the conversation that would enable our clients to position their portfolio in a way that the customers can really go, “Yeah, I get how you can help me” and have a fruitful conversation?

Ralph: We’ve talked about what Now AI does and how you take the insight and turn it into intelligence. We’ve looked at the analysts and where they’re spread geographically and the generations they come from, the different experiences they bring to it. I think it’s clear what Now AI provides and what your team does.

Are you able to give any insight into how it actually lands and resonates with clients that Now AI is working with today? Obviously, if you can’t mention specific client names, that’s fine, but if you can, great – because obviously, the proof of whether this works is how clients and their end customers respond to this and whether it’s actually delivering something of incremental value to them.

Jeremy: Exactly. I think there are a few examples that play out here. For instance, for two different clients, we’re focused on the construction industry. They have a very different portfolio set. One is in the more traditional IT space and one is very much in the specialist software for the construction industry, CAD and BIM and the other capabilities.

You would think that what we’d be delivering is – it’s the construction industry, so in a classic sense, they’re the same drivers, the same customers, doing the same thing. But actually, the output that you get to those two different clients, even from the same article, will be completely different because of the different portfolios of our clients, the different executives they’ll need to sell to, and the different messages, therefore, that they will need to wrap in terms of how their capabilities will impact that client. I think that’s one example of the way it’s different.

The other perspective is the output is delivered directly into our client sale systems. One client tend to use Microsoft Teams as their way of collaborating and working, and we deliver our intelligence straight into the Teams channel so they can consume it in the way that they want to. In other examples we might deliver it into their CRM systems, like Salesforce. Again, it’s exactly where the sales teams need it. They don’t have to go off to anywhere else. It’s against the opportunities that they’re working on. That’s the other power of really working within how the sales teams operate.

Ralph: So it really is personalized. If I can just recap on that, two different clients of Now AI are both selling into the construction space. You’re doing similar research – in fact, it’s the same research about the industry and the drivers, the key trends, the things that are challenged in that area – but you’re then laying over the two different clients in different ways, which then takes a different perspective.

It’s like a Venn diagram, isn’t it? You’ve got the industry that’s the big circle in the middle, and then you’ve got one client that overlaps it on the right-hand side and another client that overlaps it on the left-hand side, because it depends on what they provide, what the challenges are, and where things can be held. Then you overlay a slightly different circle or oval, or whatever shape it is, which is about the executives that each of them is trying to target depending on the bit of the industry they’re focused in on.

You end up actually coming from an industry, from a single point, and then you’re exploding that point into multiple points. It’s almost like a mind map that’s coming from that central point, and you end up with quite different deliverables to each client because you’ve really made it personal to the executive, relating to their company in that industry. The only commonality there is the industry. Is that right? Is that a fair assessment?

Jeremy: It is. It’ll be the industry and potentially even the same client, the same target account that they’re going after. But their output, the sales conversations, given the different portfolios and different executives, will be completely different.

Ralph: You’ve been working with Now AI for a while now, I think about a year or so since it was formed, and a number of clients have come on board in that time. Have you got clients which have bought once last year and have re-signed this year because they’ve seen value?

Jeremy: Yeah, we’re in the process with our client, Bentley. They’re rolling out to new accounts. They’ve seen the benefit in the first set of accounts, and now they’re rolling this out into even more of their client base. So yeah, they’ve re-signed and expanded.

We’re getting very positive feedback from the sales teams about how that’s changing their thinking of how they engage with their clients. It’s helping them to expand into new executive contacts and new business units and expand perhaps the portfolio that they’re selling. They may have been comfortable selling one part of their portfolio, and we’re helping them to position new parts of their portfolio or the portfolio that they haven’t sold into that client. We’re very much helping our clients see the benefit and expand that across their business.

Ralph: That’s fantastic. Repeat business is obviously the greatest accolade you can have, because it shows that there was value and that they’re prepared to continue the investment to drive incremental value even beyond that.

I have another question. If you are looking at an industry and you’re then saying, “Here’s the company within the industry; here are the executives you sell to,” you’ve got a huge amount of not just insight into all of that, but you’ve had to work on developing that intelligence. If one of the services is about saying to a customer, “This is the conversation you want to have with Executive #1 about this particular topic because there’s an issue or a trend or something that’s happening in the industry, and you can service it by talking about your solution area X, Y, and Z which could help them to drive some kind of value out of it” – as a byproduct of doing that, you’ve got a lot of information and intelligence about the industry and about the companies.

How are you then leveraging that information to be able to provide great intelligence to others who may just be interested in the industry or the companies?

Jeremy: You’re absolutely right. We build up a wealth of intelligence and insight into the companies in a particular industry and in the industries themselves. Absolutely, by having that, we can package up our services at a company level, and that’s where it’s most powerful, I would suggest, because it’s about individual executives, it’s about individual strategies. But recognizing that some businesses are operating at a slightly different level and perhaps are only starting to think about how they sell into a particular industry space as opposed to a horizontal portfolio.

And yes, we work with clients to help them make that transition and focus on a particular industry and the sort of drivers and opportunities that they should be targeting with their clients in that particular industry space. Perhaps it’s connected car and automotive, and what does that mean for them?

Then we can help not only position that from the start, but give them a constant stream of intelligence that shows how that market is changing and adapting and where the next big trends are coming from, where trends are starting to move from very early phase and innovation into more mainstream, and therefore they should be pitching their sales pitch accordingly. Industry or company, both are very relevant, and we have a depth of expertise and knowledge and experiences and wealth of information to build our services to our clients.

Ralph: That’s great. Thank you, Jeremy, for joining the Now AI podcast. I will let you go now so that you can go and take the dog for a walk on the beach and enjoy the rest of the day.


now ai podcast episode 2: Turning data into insight through ai

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.


now ai podcast episode 1: A new era in B2B selling

Ralph Varcoe interviews Ian Redfern about the shifts in B2B sales. They discuss how COVID has impacted on the sales process, and look at how there were shifts already happening before the hiatus caused by the pandemic. The cover many topics, including the challenges presented in the modern world to the B2B seller, and they look at the best ways to address that. One area of focus is on the Executive, and how the companies which win in this new era are those who align everything to the Executive. It’s a fascinating discussion about the evolution from product and account-based marketing to Executive-Based Selling.

Ralph Varcoe: Welcome, everybody, to this Now AI podcast, the next in the series, where today I’m going to be talking to Ian Redfern. Ian, I know that we’re in this COVID-19 lockdown situation right now. I’m sitting in my house. Whereabouts are you?

Ian Redfern: I’m in West London, and more specifically I’m in a conservatory and the temperature is rapidly approaching 30 degrees, so if I suddenly just disappear, it’s because I’ve gone to get a drink or a shower.

Ralph: Or you’ve collapsed, but hopefully not. [laughter] I should say, to those listening, this is probably the hottest day of the year so far, and it’s only ten past 10:00 in the morning. Well, good luck for the rest of the day in your sweatbox. [laughs] Thanks for joining.

Ian: No problem.

Ralph: What I wanted to do, first of all – today’s topic is a new era in business-to-business selling, a new era in B2B. I’ve asked you to come along to talk about that and have a conversation. What would be really useful first of all is just to give us a little bit of background as to who you are, what’s your involvement with Now AI, how long has it been, and what have you done before you’ve got to this point with us?

Ian: I’m Ian Redfern. I’ve been in and around IT – oh, goodness, for just short of 30 years now, which is a frightening thought. I began working in agency side for 3 or 4 years when I was straight out of university and then moved to a company, which at the time was very small and became very large, called Cisco. Spent the vast majority of my time there – a couple of decades, in fact – and rose to the dizzy heights, if you can call it that, of being a Director for Cloud and Managed Services for Europe, Middle East, and Africa.

Essentially, my time has always been around digital business-to-business data channels and go to market. Of course, working with channels, you come across all kinds of different organizations who are all struggling with this B2B challenge – small organizations, medium organizations, and then the very large ones too.

When I left Cisco, I then took some personal time out to do some projects around conservation and a bunch of other stuff, but came back in with Now AI as a strategic advisor because I think what’s going on with Now AI is absolutely of its time, and the way in which the company is looking at reimagining the B2B process is spot on. That’s why I’ve decided to get involved and stay involved for about 18 months now.

Ralph: Brilliant. You’ve obviously got a lot of history, a lot of experience in the B2B space, selling in a B2B world. Obviously it’s non-consumer; it’s businesses selling to businesses. The topic here, we’re talking about the new era in B2B. What is a new era? Why do we need to even think about a new era? Surely selling to businesses is the same as it’s ever been and it’s going to carry on being so?

Ian: That’s one way of looking at it. If you consider that that kind of approach will never bring you any differentiation from your competition, that’s a fine way of looking at it. [laughs] But I think most organizations have the ambition to be distinct and differentiated by the success of what they’re doing as opposed to just being the same as everyone else.

I’ve had a longstanding belief that simply following the norms of a business discipline is more of a reflection of the fact that you’re afraid to fail than anything else. It’s a way of protecting yourself from the failure of being innovative, from the failure of being different, which is obviously a risk.

B2B has been the same for a long period of time. The process of one large organization selling to another large organization has pretty much been the same for 20-25 years. I was looking at some recent research on where B2B companies are going to be spending their marketing money over the next – this is pre-COVID, so you need to reflect that – and amazingly, tradeshows is still on the list.

I mean, are you kidding me? Tradeshows are effectively the season recap. You get these season recaps on Netflix; tradeshows are for people who didn’t pay attention during the rest of the year. They’ve always been a very, very expensive way of making sure that the people who didn’t pay attention can catch up. And that includes your own people, by the way. But there’s still a large amount of spending going that way. Then automation of sales and marketing is still a big area of investment.

When I was at Cisco, we were putting in systems like KANA for emails in 2001. This is two decades old now. Essentially, the space hasn’t changed, certainly in relative terms to B2C. The area in terms of the thinking around it has not changed for a long time. Maybe the tools have, maybe the digitization has, but really the thinking around it has not. In a situation where that’s the case, it does create this opportunity for those who do things differently to stand out.

That’s what I really mean by a new era, and that’s why the Now AI proposition got me interested. It just looks at things in a different way. And being absolutely honest, this concept, this idea has been accelerated by what’s happening now with COVID. It’s brought everything into sharper focus.

Ralph: You’re right, COVID is one of the issues which is causing a change. But what do you think is the result of this? What’s going to be the legacy of the changes that are happening right now as a result of the COVID pandemic, the lockdown, and the way in which people are having to adapt the way that they sell?

Ian: If I just step back a second, I think the changes that were going to come anyway are just being accelerated by COVID. If you look at the elements of what’s going on in B2B, essentially it’s still perceived as a serial process, as a serial exercise.

Even through ‘new’ techniques like ABM, account-based marketing, it’s essentially still a serial process. It is seen as company produces product, product goes through messaging testing, messaging arrives in email, very simple personalization happens, you mail this to a high priority account, and somebody actually watches what happens as opposed to it just disappearing into a lead management process that nobody knows, understands, or monitors.

The point is that it’s not a serial process. B2B is an ongoing value exchange. It’s always happening. It’s a parallel and multiple series of events. If you want to think of it in dimensions, B2B has always been viewed as this 2D serial process, and it’s not. It’s 4D, with time and all kinds of other things, like politics and emotions and external events and various other things all impacting on how decisions are made in a very, very complex way.

This historical idea that we still cling to that a serial process drawn out and in a little workflow is going to be able to capture that is, in my view, plain nonsense. You need a different way of looking at things.

On top of that, the environment has changed considerably. The customer has changed because of the level of information they can get to on their own, without needing to speak to anyone from your organization. The actual sales and marketing tools that companies are using have changed, and there are been some pluses and minuses to that.

Competition has changed. One of the key things around key accounts is they typically have a plan put together for each fiscal year. The incredulity I have that those plans are put in place once a year and maybe reviewed once a quarter – these markets, the markets in which your customers sit, are now cycling round in days and weeks. They’re moving so quickly because the barriers to entry for new players are low. All kinds of things are happening in these markets on a daily and weekly basis, and we’ve got yearly plans? Are we kidding ourselves here?

So the customer has changed, the environment has changed, the level and speed of competition has changed. And of course now, with COVID, we’ve got some other challenges. We’ve got to explain who we are and what we’d like to sell from a distance, and without the benefit of those wonderful tradeshows I was talking about.

Ralph: That’s an interesting thing, isn’t it? We tell our sales teams, “You need to be out in front of your customer. You need to be sitting, looking at the whites of their eyes across a table, having something to eat with them, building a rapport,” and the rapport building, as we all know, is something that you can do effectively if you’re with somebody, if you’re actually there physically with them. But that’s gone in today’s environment.

For the last – I don’t know what it is, eight weeks or so, we’ve all been sitting at home. We’ve all done copious amounts of Zoom calls and team calls and speaking to people on the old-fashioned telephone. You can’t build the rapport and the relationship in the same way, and the amount of time that you have with an executive is seemingly reduced, because I think everybody – and I don’t know whether this is reflected in things that you’ve experienced – but it seems that everybody is actually quite a lot busier than they were before because they’re on back-to-back calls and don’t have as much time.

Ian: I get exactly what you mean. There is now this much more prescient challenge of being relevant and developing a relationship at a distance. One of the reasons why Now AI is interesting – again, and this was happening way before COVID – is the principle is that relevance is more important than anything else. It’s how you quickly get to the point of being relevant and it’s how you stay relevant in this mutual value exchange I’m talking about, this process of an ongoing mutual value exchange. It’s not a point in time; it’s ongoing.

How do you maintain your mutual relevance to each other? Predominantly with you as the selling organization, it’s your job to make sure that you’re providing a level of understanding and a level of relevance in your interactions that these customers want to keep. I’d seen that this is the way in which B2B was moving anyway. It’s less about “can I improve my search engine optimization by another 1.5%?” or “can I go to a big tradeshow?” It’s “what is it that I am saying that means that I am going to stand out?”

If you look at the amount of money that’s going into that as a topic versus how much money is being spent on systems, it’s ridiculous. It’s the wrong way up. We need to be spending much more time, much more energy, much more thinking time in understanding what it is that our customers are going to need from us, and much less time putting in place systems that allow us to communicate with them – may be at a lower cost and maybe with better measurements, but we’re just communicating things that aren’t relevant. We’re basically telling them things they don’t want to know twice as quickly.

Ralph: Or they already know, and so adds no value. It’s a really interesting thing. We talk about context being king. We’ve heard for years that it’s all about content is king. He or she who has the best content, the most prolific amount of content, is pushing it out in multiple channels in multiple ways to reach their audience, is going to be king or queen. Whereas what we’re looking at is, actually, what about content in the context of what’s relevant to the customer? Is that something that you’ve seen too, and does that resonate?

Ian: Yeah, absolutely. Context is a superset of content. You absolutely need content. You need something to say. But there is no point trying to sell shampoo to a bald man, and we spend a lot of our time doing that in B2B. We always have. It’s made worse by the fact that there’s a separation between sales and marketing organizations was ever thus. But the fact that we as a set of very, very smart corporate people have been unable to fix that separation between sales and marketing in what is now about 50 years is something we should all be ashamed of.

We’ve got to get to the point where context allows us to waste less time and waste less effort and waste less money. This process is actually pretty simple. It’s about identifying areas of opportunity through context and through matching up what you have with what the customer is going to need. It’s about assessing whether your offer in that space is going to be unique and valuable enough versus that of the competition, and it’s about executing against that flawlessly every time. That’s basically it.

We’re making it far too difficult for ourselves by not understanding the basic principle, which is: what is it that my customer requires that I can do better than anyone else?

Ralph: How is that different to account-based marketing that exists today? Lots of people are doing account-based marketing, looking at content which is relevant to an account, systems, as you talk about, that are in place to enable that communication to happen. Isn’t it the case that it already happens, that there’s content being created, it’s all around the account, and that’s good enough?

Ian: What I’ve seen is that there are various types of account-based marketing, and they range from something which very closely addresses the things, at least in principle, that we’ve discussed in the last few minutes. But actually, the majority of executions I’ve seen are quite similar to traditional marketing; it just happens to have a fairly low level of personalization. Maybe one or two elements beyond the first name of the person receiving the communication. It’s really not that much different.

Of course, it still suffers from the fact that it is event-driven. It’s based around a new solution or a new product or a new idea for selling into an account, which is driven by the sales side. From a Now AI perspective, the work that we do ultimately should come back as a set of ongoing discussions that don’t feel like a sales engagement. It’s a set of discussions that are continually uncovering ways in which value can be exchanged, and it is, as I said, a full dimensional set of multiple conversations that are happening in parallel. It is not an event-driven exercise like ABM.

Ralph: ABM is looking at the account and then typically is looking at the persona of let’s say a CIO or a CFO or a sales director and creating something that is relevant to the account but is not necessarily specific, or is in general not specific to the executive.

If I think about it from my point of view – here I am; I’m responsible for sales and marketing at Now AI, so I could pull together a set of statements and outcomes which are relatively generic, and I could be pretty sure that a lot of sales directors out there are struggling to get their teams to have enough pipeline cover to be able to hit their numbers. The deal velocity could be better, and any number of other things which are reasonably generic.

I’m pretty sure from the conversations I’ve had with a number of sales directors over the last couple of weeks that I’m pretty much in the ballpark – but they don’t all have those problems, and they don’t all have all of those problems. There are nuances within each of their businesses, and there are nuances within each of their sales teams and the objectives that they have as individuals, which means that the conversation I need to have with them is much more tailored to basically ask the question: “How can I help? How can I make your life as an individual better and easier? Tell me about that, and then let’s work out how to provide the solution.”

Ian: You’re right, and it’s actually in layers. It builds out from the individual to the individual’s role and objectives, through their department, through their organization, out into the competitive space, and then into the open market. We have to build up intelligence that way and we have to start to think of things that way.

Just coming back to answering that question, the previous one, in a single statement, ABM at the moment is like someone trying to sell me a frying pan because they know that I eat. It’s one of the things that I’m going to need because I am a human being and I need food intake.

What Now AI is trying to do, and where I think this new era needs to go, is I want someone to try and sell me a frying pan because they know that I hate washing up. It’s the ability to get to the point where the specifics of the reason I really want a nonstick frying pan is that deep that it’s very, very easy for me to turn around and say, “Do you know what? I’m going to buy a frying pan.”

Ralph: I like that. It’s a nice analogy. It’s a specific but entirely different reason than the assumption being from the generic frying pan salesman.

Ian: Yeah, and it goes back to what I said at the start: you’re not going to fail by trying to sell it to me on the basis that you know that I eat, but you are never going to differentiate. You are never going to get supernormal returns. You are never going to break through into a completely different relationship with your customer if that’s where you stay. You’re just going to be the same as everyone else.

Ralph: And that’s going to make it harder for you to build the pipeline. It’s going to mean that you’re competing on possibly an agenda that a competitor of yours is setting because they are thinking about these sorts of things that you may not be.

Ian: Correct. And in a COVID market, you’re probably going to be driving your margins down because you look the same as everyone else.

Ralph: Differentiation is key, and differentiation happens through the context and focusing in on the executive rather than the company.

Ian: It’s not rather than; it’s putting the executive at the heart of a set of concentric considerations that are all there. But the primary is, what does this person need? What does this person require from me that we can provide to them as an organization better than anyone else? It’s not about just making an individual happy. It has to fit within the context and strategies of the business they’re in and so on. But certainly primarily, “what are the objectives of this individual?” is a place that we should be starting.

If all we’re doing is saying, “We have a new Solution A that is broadly relevant to Industry B against Topic C,” that’s not ABM. That’s not. That’s just making sure essentially that you don’t sound stupid. [laughs] That’s just three layers of preventing failure. There’s actually nothing progressive about that kind of ABM.

Ralph: That all makes sense to me. What, therefore, is the best way to become more specific and to put the executive at the centre of everything that a sales team does?

Ian: I mentioned at the beginning that I spend almost all of my time around data. We are now in a position where the amount of data available to us – without stalking [laughs] – the amount of data available to us as potential sellers of things in the B2B sense is unimaginably large. That’s not just at the level of an individual, but in terms of the openness and the communications that companies have with their market, with their investors, with analysts, in company reports and so on. We’re living in this rich age of data.

But paradoxically, we’re not living in a rich age of information when it comes to B2B. Data has to have a purpose, has to have a direction in order to give it some meaning. Therefore, the answer to your question really is very simple: you collect up as much data as you possibly can about the organization and the industry and the people that you are trying to create this mutual value exchange with. Then you synthesize that through the lens that they would have and the concerns that they would have in their seat about what’s going on in their business and their industry and in terms of their own job role.

Then you plot your offering against what you find after you’ve run that filter, and amazingly, what you come up with is a set of things which only in the most remote of circumstances will not be in the wheelhouse of the person that you’re trying to speak to. It’s incredible how much cut-through a message which has been considered and which is informed and which has a direction to it, a feeling of understanding and empathy and direction – it’s amazing how much cut-through a message like that gets, particularly when the majority of the messages that they get, however they’re served, are not relevant, not timely, do not consider their position, and frankly have no relevance.

It’s like hearing your name called in a crowded room. It just cuts through when you get a message like that. That’s what Now AI is doing, and that’s why it’s unique and important.

Ralph: Touching on the data, there is so much of it, and it’s overwhelming. As you say, data is not something any of us are short of. You just have to do a Google search and get returned with a gazillion bits of information about a company or a topic. The question is, how do you filter it, and what lenses do you use to filter that?

Coming back to your point before, you mentioned the implication of the change in B2B and that doing things the same way as they’ve always been done, there’s wasted time, wasted effort, wasted money. But surely there is also wasted time, effort, and money of getting a salesperson or sales team collectively to do this trawling themselves – probably in an inconsistent way, because some salespeople will be bloody brilliant at it and some won’t be so good, and some probably just aren’t that interested in it. They’d rather do the socializing with customers. We all know that there are salespeople across that spectrum.

But even the good ones that do it won’t do it in quite the same way as each other, and it’s going got take time. Presumably, it’s going to take weeks to gather the right data, sift out the stuff that just isn’t relevant, pull together the bits that are, then look at how that gets pulled together with the portfolio you’re selling in the context of an industry, in the context of a company, around what the individual is looking to do that you’re trying to talk to.

So actually, in today’s world, if you don’t take a service that does all this for you, you’re having a lost opportunity, and there’s a cost associated with that.

Ian: Sure. I think this is where it comes back to looking at why you brought certain people into your sales team or marketing team and what their primary role is. I’m not arguing in any sense that this is the role of a well-remunerated salesperson, to go and trawl into that for weeks and weeks and do this exercise. That’s not the point.

If I was running a sales team right now, I would be teaching my sales teams how to speedread and how to manage an online meeting better than anybody else on the planet. They’re the two things.

The speedreading is because they should be getting fed the type of information that I’m talking about from third parties. There’s a way in which large datasets can be trawled using algorithms and AI to produce at least a first line of relevant content, and then on top of that, you still need human interaction in order to tweak that and make it nice and tight. But once that is done, then the salesperson should be receiving those bulletins or those updates or those ideas, reading them all, and folding them into an overall strategic approach for their customer. That’s what they should be doing, not surfing; they should be thinking about how to strategically manage this mutual value exchange that’s created by these relevant messages, relevant opportunities that have been created essentially through some form of third party service that does that trawling for them.

That means that they are then pinpointed, both in time and skills, on the things that they were hired to do. They spend time with the customer and they facilitate that value exchange. They’re not essentially doing the job that somebody in a call centre could be doing.

Ralph: I agree with that entirely. I think the well-paid, well-remunerated salesperson should be looking at how to develop the relationship, develop the opportunities, push them through to closure, creating mutual value.

I’ve seen in the past, when I was working with ABM type software and processes and tools, that there were companies that said, “We won’t get the salespeople to do that, but we can get a junior, an intern or three in the marketing department, to basically sift through the Google Alerts and other things and then pull that together and give it to the salespeople.” Are you saying that that’s not the right approach either?

Ian: I just don’t think it’s a scalable or sensible use of cash. [laughs] To use your figures, even if it’s just one account, if you think paying that three people, even at junior rates, is going to have the same impact as a worldwide algorithm that is scraping and assimilating and aggregating and ranking and rating it, realigning news stories, data, context information, etc., giving you the relevant score, posting it through to a senior analyst who’s been in the vertical probably for 30 years to run his eye over it, sharpen it, and tweak it – I mean, it’s just not in the same ballpark.

As well as the fact that these three juniors are ultimately going to want to be seniors, so then what do you do? [laughs] From a longstanding strategic commitment point of view, both of the people and the exercise, if you don’t want it to be a money pit and an HR problem, outsource it and get machines to do it. That’s what Now AI is doing, and that’s why it’s really interesting.

Ralph: To summarize, what we’re saying is that there are challenges in the B2B market and things are changing. One example of that is through COVID-19, the fact that we’ve all been in lockdown, businesses have been in hiatus, putting projects on hold, people have been taking the time to reassess the business model that they use – which traditionally in sales has been face-to-face, but has had to move virtual. Actually, we see some companies saying that their teams can remain virtual for the foreseeable future. There is also a suggestion that companies that have got large offices aren’t going to be quick to push people back into those offices.

Those changes are driving a need to look at things in a different way in order that time isn’t wasted, effort isn’t wasted, money isn’t wasted, and for things to be done in a scalable and consistent way that enables salespeople – the really good, strategic salespeople – to spend the time thinking about how they’re driving the business with their customers, looking for mutual value.

One way of looking at that – and the only one, actually, that I’ve seen so far – is what Now AI is doing: to create a platform that pulls together the information, aggregates it, and coordinates it in a way that can be turned into conversations that are served up to the customer in a timely way in order to drive additional value quickly.

Ian: Spot on. It’s a phrase that’s being used too much, but this is a once in a generation opportunity for smart B2B sellers to get ahead, to move ahead significantly. It’s not a pause, but it’s a moment at which thinking about how to move forward can be one.

In all honesty, as I said at the beginning, the B2B space was ready for change anyway. The current situation is just accelerating that need. And if you’re going to be making changes to certain elements, then why not look at the whole model? If your whole model at the moment is based on pretty low-level information being somewhat personalized, event-driven, and serial, you have the opportunity to do the opposite of all of those and steal a march.

You can become relevant. You can have an ongoing, continuous exchange. You can have a sales and marketing strategy which is moving and flowing with the ebbs and flows of the market in which your customers sit and isn’t just created once a year and then put on the shelf. You can do all of those things. And you can actually do it cheaper than you’re currently doing it, with better results. It’s just one of those moments, and people will choose whether they take it or not.

Ralph: That’s fantastic. Thank you, Ian. It’s been a pleasure to talk to you, get your perspective on things.

Ian: Same to you.

Ralph: Thank you, everybody, for listening to this podcast about the new era in B2B. It’s one of a series, so do tune in to one or two or three of the next ones, where we’ll be interviewing a number of people across the business and talking about similar issues and challenges and why contextualized sales intelligence directed towards the executive is the way that business-to-business will be selling in the future, and why we’re talking about this whole thing of a new era in B2B selling.

Thank you, Ian, and look forward to speaking to you again soon.

Ian: It’s been a pleasure. Thank you. Bye.