Dan Martell - How A.I. Will Change The SaaS Landscape with Martin Cloake @ Raven.ai

00:00:00.000 Even as an engineer, if you understand that, you know, your ability to persuade is going to have a significant impact on your personal success, you should invest in it.

00:00:21.360 Martin, how's it going, man? Going pretty good.

00:00:23.380 This is how we start. We just get right into it. Founder of Raven Telemetry. Is it just Raven?

00:00:28.140 Just Raven AI.

00:00:29.300 We got rid of the telemetry.

00:00:30.300 OK, Raven AI.

00:00:32.160 Creator of some of my favorite swag.

00:00:33.880 I told you that.

00:00:34.460 Oh, yeah, there you go.

00:00:35.040 Thank you so much for that.

00:00:35.860 Extra tight.

00:00:36.320 You asked for extra small.

00:00:37.200 I did, yeah.

00:00:37.900 It was so tight that I had to give it to my wife. 0.93

00:00:39.600 And she is more than happy to take the gift.

00:00:44.040 What is it you guys do today?

00:00:46.740 Because I know you guys do augmented AI.

00:00:50.300 Is there management involved?

00:00:52.400 So high level, we help manufacturers

00:00:55.280 do smarter things with all their data.

00:00:57.140 Yeah.

00:00:57.840 And we guide them based on their data to improve.

00:01:00.060 And when you say manufacturers, is there

00:01:02.460 a specific industry or type of use case?

00:01:06.000 Yeah, we pretty much help all sorts of manufacturers

00:01:08.600 from fully manual processes with people putting tea

00:01:11.720 into containers.

00:01:13.800 We work with David's Tea to fully automate it.

00:01:16.360 You can imagine lines with 60 machines connected

00:01:19.820 through conveyors.

00:01:20.400 So we pretty much help all manufacturers

00:01:23.160 with pretty much the same thing, which

00:01:24.640 is how do we help the people that are in the plants

00:01:28.240 do the right thing at the right time?

00:01:29.760 So manufacturing, even though there's

00:01:32.640 a lot of automation out there, it's still fundamentally

00:01:34.760 a people business.

00:01:35.960 And a lot of the opportunity to improve

00:01:37.840 is by helping people know what to do with their time.

00:01:42.320 Cool.

00:01:42.980 And I had Aiden on not too long ago.

00:01:46.600 I believe he's an investor.

00:01:48.520 Correct.

00:01:49.420 Is this your first time raising money for?

00:01:51.140 Yep, absolutely.

00:01:51.820 OK, cool.

00:01:52.780 And is the data component based on their equipment

00:01:59.980 that you pull in feeds?

00:02:01.000 Or where do you get the data from the manufacturer?

00:02:03.260 So basically, what we need to know to improve a process,

00:02:06.260 we need to know two things.

00:02:07.400 So first off, we need to know what the process is doing.

00:02:11.200 So just imagine you're making sandwiches.

00:02:13.620 So we need to know that a sandwich has just come off

00:02:16.120 the line.

00:02:17.500 So half the data talks about the process.

00:02:19.780 The other half is if something's going wrong,

00:02:22.480 We need the person to give us context.

00:02:24.400 So the example I always use is Waze, right?

00:02:26.600 So you're driving along.

00:02:28.340 It's guiding you.

00:02:29.240 And then at some point, you stop.

00:02:31.260 And then it asks you a question.

00:02:32.400 Hey, why are you stopped?

00:02:33.180 Are you stuck in traffic?

00:02:34.360 Is there a roadblock?

00:02:35.580 So that human context is what you need to fill out that idea of what's happened.

00:02:40.580 So effectively, we do the same thing.

00:02:42.040 So we collect data from a machine that says, hey, I just made parts.

00:02:46.360 I'm running at this speed.

00:02:47.820 And if something happens, we ask people questions to get their context.

00:02:52.000 and we stitch these two data sets together

00:02:53.780 to create a timeline of what's happened at that process.

00:02:58.400 And now that we know what's happened in the process.

00:03:01.720 And does Raven ask that?

00:03:02.880 That's right.

00:03:03.400 So we do that.

00:03:03.900 So we ask the questions.

00:03:04.840 So we try and, and the way we talk about asking questions.

00:03:08.280 So in order to get people who are working at a machine

00:03:11.540 to answer questions,

00:03:13.000 you need to ask a small number of smart questions.

00:03:16.980 You can't be pestering them all day.

00:03:18.500 So all our technology is around how do we ask

00:03:21.500 the smallest number of questions

00:03:22.820 to create that perfect timeline of all the things

00:03:25.220 that have happened at a process, whether it be good or bad.

00:03:27.860 Yeah.

00:03:28.360 I remember hearing Elon Musk talk about some AI nerd.

00:03:31.780 Well, I mean, whatever, they're AI people.

00:03:34.140 He was asking about interrupt on self-driving.

00:03:38.180 He's like, how do you get feedback loop on what errors

00:03:42.280 or involvement do you consider an error?

00:03:46.500 And he goes, any time they have to hold.

00:03:49.120 His argument is like, if you had to touch the steering

00:03:51.340 wheel, there was an error.

00:03:53.740 Let's find out why you touched the steering wheel.

00:03:55.660 So in many ways, you build that data set of, OK,

00:03:59.900 there was something that went off from what we expected.

00:04:02.160 You asked them for that.

00:04:03.640 And then, is your algorithm help then automate that?

00:04:07.900 Like, how does the manufacturer then use that?

00:04:10.300 Yeah, so there's sort of two sides to it.

00:04:11.680 So first, we need to know what's happening.

00:04:14.040 So this is kind of, we call this the truth,

00:04:15.860 or you need to know all the activities that have happened

00:04:19.180 or that are happening at a station.

00:04:21.460 And then the next thing is, in order to get value from data,

00:04:24.360 you actually need to do something.

00:04:25.520 I think one of the things one of my co-founders

00:04:28.420 says all the time is that there's fundamentally

00:04:30.420 no value in analysis.

00:04:32.500 There's only value when somebody does something.

00:04:34.240 From the analysis.

00:04:35.040 From the analysis.

00:04:35.780 Knowing doesn't matter.

00:04:37.140 Knowing doesn't matter.

00:04:38.680 You need to do something.

00:04:39.940 So if you're in your car and you're driving with GPS

00:04:42.040 and you ignore it, it's not going to do anything for you.

00:04:44.700 Even if it tells you all this cool stuff.

00:04:47.620 So that's the key thing here where people

00:04:49.540 are part of the formula here.

00:04:51.680 So I think even to start, you need to know what's happening.

00:04:55.540 You need the truth. 0.99

00:04:56.260 And we can talk about bad garbage in, garbage out. 0.95

00:05:00.280 But just let's take for granted, all of our technology

00:05:02.280 is really around getting to that first phase

00:05:04.560 where we get the data.

00:05:05.580 Now, it's interesting you use the term control loop

00:05:09.500 from Elon Musk.

00:05:11.080 So we think about things in the same way.

00:05:12.860 But effectively, what we're trying to do

00:05:14.440 is to guide people to do the right thing at the right time.

00:05:18.100 And there's two key things that you

00:05:19.660 need to do to guide somebody effectively to do something.

00:05:23.140 The first one is you need to provide extremely clear guidance

00:05:27.960 that is linked to something useful.

00:05:29.800 So hey, go to this machine right now.

00:05:33.580 It's broken.

00:05:35.120 Go to this guy right now.

00:05:36.400 They've been waiting for the inspector for three hours.

00:05:39.700 So first off, give really clear guidance.

00:05:42.100 Clear guidance.

00:05:42.640 And clear guidance.

00:05:43.600 It's not like there's something there.

00:05:44.980 Go do this thing.

00:05:46.240 And basically, if you can't, in some ways,

00:05:49.360 when I think about how we present information to people,

00:05:53.460 I always think our tech could work on a pager from 1997.

00:05:57.760 Or I'm trying to make 95.

00:05:58.700 I forget when pagers were cool.

00:05:59.960 I never had a pager.

00:06:01.980 So basically, in a pager, you're limited to,

00:06:04.320 I don't know how many characters are there.

00:06:05.980 I think what you could put in there.

00:06:06.980 You know what's hilarious is I know

00:06:08.020 that I have a lot of people listening to this

00:06:09.840 that were born in 2001, and they don't know what a pager is.

00:06:13.560 Isn't that crazy?

00:06:15.040 So Twitter.

00:06:15.540 So basically, the old Twitter, right?

00:06:17.520 So if you can't condense it down to a tweet or less,

00:06:22.540 it's too complicated.

00:06:23.600 And one of the things is that trying to guide somebody

00:06:28.380 with a dashboard, it looked pretty.

00:06:31.080 It's beautiful with all the charts and colors.

00:06:34.320 It's not.

00:06:34.940 You need a very simple instruction.

00:06:36.400 So on the pager, 911, call your buddy Mike.

00:06:39.800 It's clear.

00:06:40.480 Like 911, Mike.

00:06:41.440 Yeah, emergency.

00:06:42.940 There you go.

00:06:43.540 So to get people to act.

00:06:45.640 So the first thing is, well, now that you know what's happening,

00:06:49.940 you know what the biggest opportunity is, right?

00:06:52.660 This, you know, then there's two different.

00:06:54.580 Give me a use case of like how a customer, like before

00:06:57.960 and after using Raven.

00:06:59.200 Sure.

00:06:59.780 Very simply put.

00:07:00.540 So a lot of waste in manufacturing

00:07:04.420 is because people are waiting for something.

00:07:06.360 So just imagine that you're a plant manager and you have.

00:07:10.440 One of my favorite books, by the way, is The Goal.

00:07:12.760 There you go.

00:07:14.140 If you haven't read it, if you're a systems guy like me,

00:07:18.140 it's a beautiful, beautiful story.

00:07:20.000 So in that book, he argues of just raw material

00:07:24.580 and retooling manufacturing.

00:07:27.160 It's like that wait time could be the killer.

00:07:29.260 So waiting.

00:07:29.860 So typically, the ratio of supervisors to staff

00:07:33.980 could be one supervisor, 40 staff.

00:07:35.920 So we have one client that has 150 machines, 40 staff

00:07:39.280 looking after that one supervisor who's

00:07:41.320 responsible for all sorts of things so if you were to look at that the truth or

00:07:44.740 that you know what's happened at each station and one of our clients was

00:07:47.440 losing tons and tons of time because people were just waiting for maintenance

00:07:50.800 waiting for support so at some point if you only see data at the end of the day

00:07:56.020 in a chart in a report or you have a dashboard with all sorts of details it's

00:08:00.700 not easy to tease out the fact that you know this machine is down right now and

00:08:05.560 they need support so what we did for those guys was to set an alert

00:08:10.120 specifically to this thing that we'd highlighted as being a big opportunity

00:08:13.500 waiting for maintenance and then the second part to being able to could you

00:08:16.760 predict when the machine might need maintenance the first the first thing is

00:08:19.620 we just we now have we know we now know when they need support the operator has

00:08:24.620 said hey come help me and then the next thing is once somebody starts working on

00:08:30.040 this projects they start working on reducing this you need to provide

00:08:32.980 feedback to them so if if they are putting effort into something you need

00:08:37.360 to provide feedback to them that relates

00:08:40.660 to the work that they've done and their competence.

00:08:43.600 So don't give me some metric that relates to corporate success.

00:08:47.560 If you're asking me to reduce waiting time,

00:08:50.320 tell me how I'm doing at reducing waiting time.

00:08:53.480 So really simple things.

00:08:54.820 So now that we have this data that

00:08:56.500 describes exactly what's happening,

00:08:58.180 and that's really the biggest challenge

00:08:59.540 to get to stitch those two data sets.

00:09:01.120 You call that the truth a couple of times.

00:09:02.660 We call it the truth.

00:09:03.460 I think that's a bit, it's basically

00:09:05.500 Just what, you know, your performance.

00:09:07.500 Yeah.

00:09:08.080 No, but in software, you know, just in data warehouses,

00:09:11.060 like the record of truth.

00:09:13.440 Like, I think it's an important thing to know, like, you know,

00:09:15.960 what is the, because there's so many systems now that do different things,

00:09:19.000 could do different reports, but you're saying, like,

00:09:20.460 this is the truth of what happened.

00:09:22.120 This is what's happening.

00:09:23.380 And it's because we're asking.

00:09:24.140 Do you make them wear, like, some kind of, like, kind of GPS machine?

00:09:27.700 How do you know that the person's been standing there or the machine?

00:09:31.860 Like, how does it, like, technically work?

00:09:33.720 I'm just curious.

00:09:34.240 Yeah, yeah. So we have a wire that we actually drill in through their scalp.

00:09:40.740 It's not very intrusive at all.

00:09:44.200 One of my first employees is now working for Elon Musk's company there.

00:09:48.920 But no, there's a tablet computer at the station, and the operator-

00:09:53.600 Ask questions.

00:09:54.100 We ask questions.

00:09:54.800 Just like the bathroom, when you leave, it says, how was your experience? You just answer.

00:09:58.100 And it's really the same. In the bathroom, there's five options or three options,

00:10:02.020 so we try and keep it as simple as possible.

00:10:04.240 I'm setting the machine up, I'm waiting for somebody,

00:10:06.980 something's broken.

00:10:08.800 So in the end, I think the bar for us

00:10:10.660 is how could you get a six-year-old to use the system?

00:10:13.300 Well, if you're waiting, it's yellow.

00:10:14.860 If something's broken, it's orange.

00:10:16.660 If you're setting up for the next thing, it's blue.

00:10:18.280 Done.

00:10:19.400 Yeah.

00:10:20.080 I remember one of my friends, he runs a sign company.

00:10:24.280 And he's not a sophisticated AI guy.

00:10:28.460 He just-

00:10:29.280 Is he the premier of Ontario?

00:10:30.520 No, no.

00:10:31.480 He's a guy from New Brunswick.

00:10:33.040 He just gave everybody pedometers, like Fitbits, essentially.

00:10:38.160 And then he looked at who was walking the most.

00:10:41.720 That was his process of saying, we just

00:10:43.720 need to reconfigure our shop floor.

00:10:46.180 And our number, our feedback loop is,

00:10:49.120 you need to walk less per shift.

00:10:51.880 And it was just such a beautifully simple.

00:10:53.940 This is a not sophisticated software person,

00:10:56.440 and he's telling me this.

00:10:57.220 And I'm just like, you know what I would do?

00:10:59.140 I would put that on the supervisor,

00:11:00.900 and I want to see them walk more.

00:11:02.820 Why walk more?

00:11:03.700 I want to see that they're out there on the shop floor.

00:11:05.580 Oh, for the supervisor.

00:11:06.720 For the supervisor.

00:11:07.480 So I'd love to see them walk laps.

00:11:09.860 OK, because you know that if supervisors are walking,

00:11:12.540 they're unblocking their team.

00:11:14.320 And that is, by default, is the best behavior.

00:11:16.820 I remember, so I started my career in manufacturing.

00:11:19.860 So I'm a high tech guy, but I spent three years

00:11:21.700 in manufacturing.

00:11:22.420 And I remember my plant manager, a guy named Alfredo,

00:11:27.800 at some point I was mentioning some processing

00:11:29.680 I wanted to improve.

00:11:30.380 He says, Martin, I want you to learn all 200 names of the people in the plant.

00:11:33.960 And then you can come talk to me about your process improvements, which was like my first experience as I'm a high tech guy, engineer, telecom and all that.

00:11:43.560 But I spent three years in manufacturing for a company called Blinds to Go.

00:11:46.020 And that experience is really what made me found Raven and sort of changed my view of manufacturing and just in leadership as well.

00:11:54.360 That was a really neat experience for me personally.

00:11:57.480 And I saw that, and that was like the first thing you ever did.

00:12:00.960 So absolutely.

00:12:02.220 So in 2003, so I was lined up for a career in telecom.

00:12:06.840 So I worked for JDS Uniphase during the boom,

00:12:08.880 where they were doubling in staff year over year.

00:12:14.400 But when I graduated, telecom was going down.

00:12:16.420 And I got recruited by Blinds2Go, a blind company,

00:12:21.960 and a pretty amazing company back then.

00:12:26.360 One of the neatest things that they do with their teams

00:12:28.800 is that when you start, regardless of your role

00:12:32.600 in the company, you have to go sell blinds in a blind store

00:12:36.600 full time.

00:12:37.220 Do they own the blind stores?

00:12:38.260 They own all the blind stores.

00:12:39.120 They have 100 stores.

00:12:39.800 So I was sent to Totowa, New Jersey.

00:12:42.300 I was there for six weeks.

00:12:44.100 I remember the first few weeks there,

00:12:48.620 calling my wife and saying, this is our girlfriend

00:12:51.560 that at the time, like, so what am I doing here?

00:12:54.080 I'm an engineer from McGill.

00:12:55.600 What am I doing selling blinds?

00:12:57.440 And then, you know, it's pretty interesting,

00:13:00.200 having never sold retail, to go in and sort of see it firsthand.

00:13:04.360 Yeah, go on the other side of the conversation.

00:13:08.280 Well, other side of the conversation, but also, you know,

00:13:10.100 at some point I had, because I know that I'm there until I do well.

00:13:14.920 I think they wanted us to hit.

00:13:16.180 So it wasn't like six weeks.

00:13:17.320 It was like you had to do some volume of sales.

00:13:19.580 You were supposed to, I think the rough target

00:13:21.720 was top three in the region.

00:13:24.960 And some people were there for a year.

00:13:27.780 But in the first week, so I'm thinking, OK,

00:13:29.640 I need to sell as much as possible.

00:13:31.020 Some people would stay doing this

00:13:32.720 if they were like CF finance.

00:13:35.000 100%.

00:13:35.500 They had Harvard MBAs running their stores.

00:13:37.500 So it's just their approach to getting you

00:13:41.800 to understand the front lines of the business is genius.

00:13:44.640 Yeah, brilliant.

00:13:45.820 So the first week I'm there never having sold retail.

00:13:50.380 And I remember I had one customer come in,

00:13:52.460 and they priced out $3,000 of blinds.

00:13:54.280 And I'm like, OK, sweet.

00:13:55.520 This can be an awesome week.

00:13:56.360 And they say, you know, Martin, I'll be right back.

00:13:58.660 And they didn't come back.

00:13:59.640 Oh, yeah.

00:14:00.100 And then my boss comes over and says, Martin, what happened?

00:14:02.800 I said, what do you mean?

00:14:03.840 Like, they said, they're going to be right back.

00:14:05.200 They're going next door for a coffee.

00:14:07.040 And there's two of them, two women who had it priced out. 1.00

00:14:10.000 And so I said, no, no, no, they're, I forget his name,

00:14:12.820 but they're coming back for sure.

00:14:14.500 And then I see them walking by to their cars,

00:14:17.440 and I go up to the front like a puppy dog in the window,

00:14:19.580 and going like, you're not coming back in?

00:14:21.500 He said, Martin, they're not coming back.

00:14:23.440 So it was really interesting to sort of,

00:14:25.680 so he started teaching me about as you're selling,

00:14:28.840 first off, if they walk into a blind store,

00:14:31.100 they're there to buy blinds.

00:14:32.500 So if they don't, so you should be converting 90% of people

00:14:34.700 coming in.

00:14:35.200 So he started teaching me about how

00:14:36.920 do you close off the objections and all that.

00:14:41.820 But I think that experience, basically getting boot camp

00:14:45.020 in sales, like now I'm effectively a sales guy for Raven.

00:14:48.480 That really struck me.

00:14:49.600 Game, capital, customers.

00:14:51.400 Everything, recruiting.

00:14:52.620 And that struck me.

00:14:53.580 And then going to the plants and working as an engineer.

00:14:57.300 And at some point, I was a supervisor.

00:15:00.040 I had 50 staff there on the shop floor.

00:15:03.260 Now you understood the consequence of building

00:15:07.260 the wrong product, it being late.

00:15:10.560 One of the worst things is if you make a blind

00:15:12.600 and it's one inch too big because you screwed up

00:15:14.980 the measurements.

00:15:16.100 And as an engineer, I should not screw up measurements.

00:15:18.280 So then they bring it home, and they try and put it in, and it doesn't fit.

00:15:22.920 So that experience was really interesting on multiple levels.

00:15:27.460 How have you brought that to Raven?

00:15:29.320 I think what that gave me early on was understanding how important sales was,

00:15:36.160 how important the customer was.

00:15:37.260 And I think in all the things that I've done since then,

00:15:41.240 thinking about the customer first, and then also in setting up Raven,

00:15:47.360 And a lot of what I do is, you know, I tell stories that I'm trying to persuade, either, you know, persuade a customer to try us out, try to persuade a customer to take action.

00:15:57.360 Like I said, we're not at the plant, an investor and staff and all that.

00:16:01.660 But I think the understanding the power of persuasion, where in school as an engineer, you don't necessarily, it's not necessarily valued.

00:16:11.420 They don't teach it.

00:16:12.280 They don't teach it at all.

00:16:13.800 But your whole career is predicated on your ability

00:16:16.740 to communicate in person.

00:16:18.000 For everybody.

00:16:18.960 Yeah.

00:16:19.500 It's so funny that they don't.

00:16:21.900 In a previous episode, I interviewed

00:16:25.320 one of the vice presidents of sales at Ripple

00:16:28.320 that sold to Salesforce.

00:16:29.580 And this guy, Daniel Premier, or David Premier,

00:16:34.240 Primer.

00:16:34.980 And he speaks at Harvard on sales because they don't teach it.

00:16:39.300 No.

00:16:40.080 And it's just so crazy because it's such an impactful

00:16:43.780 required skill but but it's interesting the uh in in ottawa the the fresh founders crew which

00:16:48.700 which i know you you know of yeah um that's how i got indoctrinated they flew me out like six years

00:16:54.000 ago seven years ago and it's been yeah so so that's that's the crew's been around for now i

00:16:58.500 think 10 11 years it's kind of neat to see you know um what it's become what it's become but

00:17:02.720 you know i think all of us recognize that especially for us founders and ceos that

00:17:06.260 it's really sales runs everything it's that's that's the you know that's what that's what

00:17:11.760 builds a business you know it's not not it's not devaluing what engineers bring to it um but it's

00:17:16.100 just the product you need to build the product um so like whenever um you know i i uh whenever

00:17:21.760 there's a good book out there one good book that um that was sort of making the rounds was a book

00:17:26.140 called pitch anything by oran klaff yeah yeah fantastic very very um direct his his approach

00:17:33.340 to pitching is very but yeah at some point i'm reading the book and thinking like if i do this

00:17:37.880 wrong i can get punched in the face yeah like it but if i do it right it's gonna be super fun

00:17:41.520 It's going to be magical.

00:17:42.440 Yeah, it's interesting, just how he views things.

00:17:45.200 So at some point, I think my buddy Paul was sort of describing the book.

00:17:51.600 Basically, all the things that he's been doing, it sort of captures it pretty clearly, and it just works.

00:17:56.580 So one of the things is when I go to a meeting and they say, hey, Mr. Cloak, please sit here in the waiting room.

00:18:05.040 We'll be right with you.

00:18:06.240 And in the book, it says, never do that.

00:18:08.200 Never sit down.

00:18:09.920 And never stay in the waiting room.

00:18:11.520 So you don't sit down, you don't stay in the waiting room, you walk around like it's your home.

00:18:15.580 So I'm walking around here, I think at some point it was at Omer's.

00:18:19.320 So I'm not sitting down and I'm not staying in the boardroom, because the book told me not to, and it's fun.

00:18:26.420 But yeah, so we're influenced by Robert Cialdini, there's a bunch of books here.

00:18:31.120 Such a great book, yeah, Micro Commitments.

00:18:32.780 So that's the kind of thing here where even as an engineer, if you understand that your ability to persuade

00:18:38.360 is going to have a significant impact

00:18:39.860 on your personal success, you should invest in it.

00:18:43.120 And it blows my mind that that's not valued more.

00:18:46.520 And in today's world, you said you have a co-founder?

00:18:49.220 Yeah.

00:18:49.520 Is he the AI algorithm person?

00:18:51.180 That's right.

00:18:51.680 So Braden did his PhD at Institute for Aerospace Studies

00:18:57.240 in Toronto.

00:18:58.040 So he was doing unmanned navigation of vehicles.

00:19:00.860 So he's the brain.

00:19:03.860 I always say how lucky I am to have paired up with Braden.

00:19:08.360 You know, we complement each other very well.

00:19:12.440 And, you know, after, I think, four years now,

00:19:15.780 we still get along.

00:19:16.760 And, like, you know, I'm trying to think of other people

00:19:19.780 I've collaborated with for four years.

00:19:21.000 But I'm not the easiest guy to get along with.

00:19:23.140 And we found out we complement each other very well.

00:19:26.040 And maybe he's doing CrossFit every day at lunch

00:19:28.240 that, you know, we can get out our...

00:19:29.300 He gets it, yeah.

00:19:30.380 Yeah.

00:19:30.680 What have you learned about the sales process?

00:19:35.280 I remember last time we were chatting over lunch,

00:19:37.080 You know, you're saying, well, this is the way I like to approach calls and I get them to make commitments.

00:19:41.600 What have you learned about selling technology that other founders can learn?

00:19:46.580 I think one of the things that I find works well and sort of fits well with sort of my personality,

00:19:55.220 and maybe I'll preface this where I think going back to my experience selling in the blind store,

00:20:02.900 in the end, everybody figured out how to sell blinds.

00:20:06.220 It may have taken them a year.

00:20:07.480 I think one of the things that people think

00:20:09.760 is that you need to have a skill set to sell.

00:20:14.040 And I think they prove pretty conclusively that you don't.

00:20:16.400 At some point, if you are given the right tools

00:20:18.280 and you find your own personal style, your own rhythm.

00:20:23.320 So the key thing here is the first part of any conversation

00:20:26.720 I have with a customer is to understand them, get them

00:20:30.580 talking.

00:20:31.440 So typically, if I'm on a half an hour sales call,

00:20:35.840 first 15 minutes, we'll be asking them questions about their business. I'm taking down notes

00:20:40.180 because I want to understand basically what the lay of the land is there. So then when I'm pitching

00:20:45.460 what we can do to help them in the second half of the call, it references all these things that

00:20:52.620 they have mentioned in the first half. Yeah, which tells them you were listening.

00:20:56.020 It tells them I was listening, which is a really good crazy idea. The other thing which I think

00:21:02.120 doesn't necessarily come as naturally is that you know so asking questions you know it's not then

00:21:08.100 i know a lot of people think selling is talking you gotta get them talking like yeah like selling

00:21:13.220 is questions they'll they'll sell themselves into the deal based on your questions yeah

00:21:19.660 sometimes the best thing especially if you're in a room with with a bunch of people and you know

00:21:23.280 you have them and like if i'm shut up shut up just let them talk and if they're talking then

00:21:27.900 you just you just let the silence sit let it sit it's okay yeah they will feel that silence they

00:21:32.360 will feel that silence and you just you sit there with a smile on your face and you're yeah you know

00:21:35.740 i got the deal i got the deal shut up don't lose it don't screw it up just yeah let them talk the

00:21:40.740 other thing so you know get them talking if if you know there should somebody should should develop

00:21:45.440 an app where basically like it tells sales people um if they have gone over the 50 mark of well i

00:21:51.240 haven't seen chorus or um gong gong oh my gosh the ai i mean it's ai it's uh essentially they

00:21:58.380 analyze sales calls automated in an automated fashion and this is even cooler not only will

00:22:03.560 it tell you what percent uh your reps your sellers are talking versus the prospect you can set up

00:22:08.800 keywords where it'll email you as a sales manager to tell you if they did or didn't say words so if

00:22:14.800 you if you know that they need to like here's the process you know step one is this two three and

00:22:19.640 they have to say words like credit card, or proposal,

00:22:23.300 or decision maker.

00:22:25.580 And so just this new level of real time analysis

00:22:30.720 around sales conversation, I think is fascinating.

00:22:32.720 I use it.

00:22:33.200 It's great.

00:22:33.800 It works?

00:22:34.580 It's, I mean, so you, but it works for you

00:22:37.660 because you've chosen to use it for yourself, right?

00:22:39.360 No, I use it.

00:22:39.980 I have sales people who work for me.

00:22:41.920 And they use it?

00:22:42.380 OK.

00:22:42.680 Yeah, yeah, yeah.

00:22:43.100 Well, they don't have a choice to use it

00:22:44.300 because it's automated into their workflow.

00:22:47.280 But I use it as a sales coach because it

00:22:48.920 There's a lot of cool stuff where I can now clip out.

00:22:53.000 So it'll tell me when they're talking.

00:22:55.220 I can look at all the calls where they won the deal.

00:22:58.500 I can listen to when objections came up

00:23:00.420 and listen to their replies.

00:23:01.840 And if it's good, I can clip it, add it to a library.

00:23:05.000 And as I hire new reps, essentially,

00:23:07.220 it's building the hit list of this is the best response.

00:23:10.320 And choose your way to say it.

00:23:11.520 Because like you said earlier, it's

00:23:12.560 really about discovering your type of way to sell.

00:23:17.420 I really believe that your archetypal or whoever

00:23:21.680 you think was this type A salesperson from the past,

00:23:26.300 like women that are introverted are crushing it. 1.00

00:23:29.300 Because people just want to feel heard.

00:23:32.300 And they want to know that my problems,

00:23:36.440 you truly understand them.

00:23:37.640 And you can present a solution in a way.

00:23:39.860 So yeah, I think there's really some neat tech around that.

00:23:43.260 It was interesting.

00:23:43.960 So just the all, I'll mention it later.

00:23:47.100 But I'm particularly interested in,

00:23:50.680 because ultimately you're trying to influence their behavior.

00:23:54.600 But doing it by mandating the measurement, which is fine,

00:24:00.480 then there's a lot of theory around gamification theory,

00:24:04.220 which is based on self-determination theory

00:24:06.360 around what is the most effective way to get people

00:24:09.880 to be engaged and do the right thing.

00:24:12.900 And there's a bunch of theory around,

00:24:15.000 Some people want to compete with others.

00:24:18.760 Some people don't, right?

00:24:20.880 And I think the core parts of self-determination theory are people need to feel like they have the autonomy to turn on different parts to help them improve.

00:24:33.560 You need to recognize them for achievement, but that's in the way that they're comfortable with.

00:24:40.240 But the autonomy thing is key here where people have to feel like they have the ability to apply their own strategy to make things better or worse versus mandating that strategy.

00:24:52.800 And in gamification, you know, I think, you know, it's not a game if you're forced to play it.

00:24:58.800 So there's a lot of theory around there.

00:25:00.320 if you can actually get them hooked into seeing it in the right way

00:25:03.700 and adapting those three components of autonomy, mastery, and community.

00:25:11.200 Is this from Daniel Pink's book, Drive, or where is this?

00:25:14.380 It's just from self-determination theory.

00:25:16.100 It's from, I don't know, I'm married to a psychologist,

00:25:17.940 so I get free info at home.

00:25:19.800 But self-determination theory is the theory behind what motivates us to take action.

00:25:24.200 A lot of gamification is based off of self-determination theory.

00:25:26.980 Do you use some of this in the product to help your customers?

00:25:29.940 absolutely and how does that show up in your product so at some point if there's options to

00:25:35.400 have a leaderboard or not having a leaderboard here um if some you don't just put everybody on

00:25:39.960 the leaderboard okay um at some point give people the the ability to get feedback in a way that

00:25:45.360 you know is it works best for them private um so i think that's really important here where you know

00:25:51.300 if if you're trying to move you know entire plant here you know you don't just want to motivate the

00:25:57.420 top two percent this is true for any business if you just motivate the top 10 percent you know that

00:26:02.180 may even have a negative impact on the rest so if you're trying to move everybody you know similar

00:26:06.120 to her i don't know if you uh you ever heard of peloton the peloton bike i re it's funny you

00:26:10.200 mentioned that um at the hotel on matt they have one in the gym and i've done three days in a row

00:26:15.140 it's fantastic first time yeah and it's like i got high five the other day oh yeah it's like this

00:26:20.100 and i'm like but i was watching replay class but i guess it was somebody that saw me doing the we

00:26:25.020 were both doing at the same time and like the leaderboard the interface today i mean i'm a data

00:26:28.840 nerd too so it's like oh my gosh this is really good she's like minimum output should be this and

00:26:32.960 i'm like game on yeah so some people want so i i want to like i think right now if i if i go like

00:26:39.240 a lunatic and almost kill myself yeah i can be in the top one percent yeah um so then i'm going on

00:26:44.780 or i want to beat myself my previous score but some people don't necessarily want to be you know 0.72

00:26:49.040 competing they just want to see themselves yeah right i i won't you know i want to beat people

00:26:53.500 who have annoying names, you know, like there's a name.

00:26:57.100 I thought it was like Hamburger or something.

00:26:59.020 I was like, what are you?

00:27:00.280 Hamburger 25, I just don't like you.

00:27:02.200 That guy. 0.98

00:27:02.740 I'm going to beat you. 0.56

00:27:03.820 Yeah.

00:27:05.380 All he does is ride Peloton all day.

00:27:07.300 But it's addictive here.

00:27:08.720 But there's been points here where I'm almost passed out

00:27:11.540 on the bike because I just want it so bad.

00:27:13.320 Yeah.

00:27:13.900 It's so much fun.

00:27:14.620 So you're saying it works for some people, other people,

00:27:17.080 that might actually have a negative consequence

00:27:18.700 because they might just opt out of playing.

00:27:20.020 Absolutely.

00:27:20.520 And if you're trying to move, like, the whole group,

00:27:23.260 you need to think about how to make it adaptable for the whole group, right?

00:27:27.280 So, you know, a video game that's just impossible, people aren't going to play.

00:27:31.940 And so the mastery component of this self-determination theory

00:27:35.780 is recognizing when you've reached a new level, right?

00:27:38.680 So your new level may be different.

00:27:40.880 Like, do you CrossFit?

00:27:42.120 Yeah.

00:27:42.420 Yeah, so I go CrossFit all the time, but you're probably lifting more than me.

00:27:46.020 But if I get recognized personally, you know, to see that,

00:27:49.060 hey, I got a new PR for deadlift.

00:27:51.440 That's what I love about CrossFit.

00:27:52.440 It's compete every day, but it's compete against yourself.

00:27:54.480 There is the group component,

00:27:56.020 but then they do celebrate the individual PRs, right?

00:27:58.580 Yeah.

00:27:59.140 Or there's things that, you know, so the assault bike.

00:28:01.160 I love the assault bike.

00:28:02.100 That's my thing.

00:28:02.900 I'll battle you in the assault bike. 0.89

00:28:04.460 Yeah, the devil's bike.

00:28:04.700 But you're going to, what?

00:28:05.960 The devil's bike, they call it.

00:28:07.600 Yeah, if you want to know what it feels like

00:28:09.600 to have energy sucked out of your body,

00:28:11.020 go get on an assault bike

00:28:12.020 and crank it for a minute straight, nonstop.

00:28:14.300 Love the assault bike.

00:28:15.100 I go on it right.

00:28:15.860 I'm actually missing the assault bike today.

00:28:17.440 it's um cardio wednesday so but uh love that and what's an example of like a company that

00:28:25.420 before they use your product and kind of the is it throughput that you guys help people increase

00:28:29.480 what's there's you know for manufacturers typically there's sort of two main things

00:28:33.380 that they're trying to improve the uh the first one is um reduce uh reduce the amount of time

00:28:40.440 they're they're spending not producing barts okay so labor costs more output so people are people

00:28:46.560 are going into a plant and then they leave, how much stuff came out? What's the ratio of effort

00:28:51.100 put in by people? People to output. People to output. So then if the demand is fixed,

00:28:57.760 then it's a cost reduction. If you're not able to keep up with demand, then it's increasing top

00:29:03.200 line. So we work with one of our biggest clients is Danaher. One of our Danaher plants increased

00:29:09.440 output by close to 20% in the first year of using Raven. And again, we provided the

00:29:16.180 information, they're the ones who took action.

00:29:18.580 They're the ones who actually fixed things.

00:29:20.940 And that's why early on, we've been

00:29:23.100 using the term augmented management.

00:29:25.020 And the idea here is that a lot of the talk about AI

00:29:29.140 has been this idea of replacing.

00:29:32.080 And I think where we see the biggest opportunity

00:29:34.420 is really to augment what people are able to do.

00:29:37.260 How do you get them away from Excel?

00:29:38.720 The Go player with the computer

00:29:40.300 versus just the computer, right?

00:29:42.180 That's right.

00:29:43.520 They become better Go players because of the computer.

00:29:46.320 100%.

00:29:46.960 It'll always beat just the computer.

00:29:48.820 It's the person plus the AI will always beat the AI.

00:29:51.840 Plus, in manufacturing, that Go player is spending 80% of their time

00:29:55.480 filling out Excel reports, printing them off,

00:29:57.260 and sticking them on whiteboards.

00:29:58.940 So just imagine all that untapped leadership capacity

00:30:01.660 that we can unlock by allowing them to spend more time actually solving.

00:30:05.860 Walking, saying hi, learning those names.

00:30:07.860 Learning those names and walking.

00:30:09.340 Yeah.

00:30:09.840 That's fascinating.

00:30:13.200 Is it cool?

00:30:14.220 I don't know.

00:30:14.520 I just think that if I wasn't doing software,

00:30:16.940 I'd want to be doing something in kind of manufacturing

00:30:19.200 just because I like building things.

00:30:20.900 Do you get to visit the plants often?

00:30:22.840 Do you get to?

00:30:23.420 I go all the time.

00:30:24.500 Yeah?

00:30:24.860 It's really neat to see.

00:30:26.860 I mean, that's why there's a show called How It's Made.

00:30:28.780 You know, like people like to watch how things are made.

00:30:32.080 The crazy thing is that there is, you know,

00:30:36.220 going to see a plant that makes wings for plants.

00:30:40.900 We have one plant that makes barns. 1.00

00:30:42.940 barns they uh they make barns yeah or they make giant so they said they built something they

00:30:48.460 called a garage mahal which was like a garage for 30 cars okay the other guy was calling it the

00:30:53.340 garage mahal yeah um you know we have we work with tt like all sorts of things it's it's and but the

00:30:59.340 the interesting thing is if you were to grab that excel file that they're spending all their time on

00:31:04.060 they all look kind of the same so how much stuff did you make um how much did it cost in material

00:31:10.060 and labor hours? Did you deliver it on time? So almost regardless of what you're making,

00:31:15.620 that like the formula for manufacturing is the same. So if you can find a way for people to fix

00:31:21.840 the biggest problems as they're happening, put out the biggest fires. And then the next thing is like

00:31:27.360 if all the fires are out, what is the most important thing for you to work on if the fires

00:31:32.240 are out? And maybe it's working on this machine's running too slow. Maybe it's working on why is

00:31:38.140 this guy or this person so much better at this process the bright spot and figure out what

00:31:43.180 they're doing to everybody else and often often the um the the anomalies that pop out in the data

00:31:48.400 that show top performers that's often the most interesting thing yeah i'm always looking for

00:31:53.220 bright spots that and then you and then you caught like as an engineer you copy it yeah it's just

00:31:57.680 like back to the the sales like chorus or refractor or gong it's like once you find that seller that's

00:32:03.820 closing at a higher rate and you listen to how he deals with objections or he does his discovery

00:32:07.640 component at the call clip it teach it reproduce i mean it's um we yeah we had one uh one example

00:32:15.340 that was pretty pretty funny actually not funny the so one client that when in manufacturing you

00:32:21.040 have to set up for another job so just imagine you have like your machine is configured for for a

00:32:26.260 certain thing and then you're making the next thing so you have to change the machine so so

00:32:30.080 this this one operator um was able to set it up twice as fast and so you know the client didn't

00:32:36.480 it until we were helping them so we got the truth of their data and then they said go go see what's

00:32:41.280 up what are they doing so they went over and uh and saw the operator um had this giant drum and

00:32:49.440 he had it tipped over in super dangerous unbelievably dangerous but because he had this drum tipped

00:32:55.600 over he could actually spool this wire and do this thing uh this operation at the same time as doing

00:33:00.960 another operation so first off they said that's super dangerous but hold on why don't we design

00:33:05.280 a little fixture to help you tip it right and then you then you roll that out to the whole plant so

00:33:10.700 that's kind of interesting where you know they saw something that was super ingenious yeah super

00:33:16.080 dangerous but you know that actually changed the process where you know typically if you're just

00:33:20.340 looking at you know that the dashboard you wouldn't see that in a dashboard you wouldn't see that in

00:33:24.480 the daily daily performance because you'd probably pay attention to the worst one right yeah that's

00:33:29.780 really cool and we see that like that that's where you're gonna get that step in creative it's I mean

00:33:34.500 this is what I find fascinating about AI is it's going to get creative regardless of biases or

00:33:43.460 predetermined, like it's just going to look for patterns and that's where we're going to get

00:33:48.660 these step functions of improvements, not these linear kind of paths. And you are helping your

00:33:55.580 customers figure that out. But it's still the, it's the sharing, it's enabling sharing knowledge

00:34:03.360 rather than creating this new ability.

00:34:07.180 Do you see that movie with the guy who scaled that mountain?

00:34:13.520 Alex Honnold.

00:34:16.240 Alex Honnold.

00:34:17.480 And it was called, I don't know.

00:34:21.040 But man, my midsections were tingling the whole time.

00:34:24.860 So what's interesting here is that he climbed with basically,

00:34:29.600 like the only modern equipment he had was maybe the shoe?

00:34:32.560 Jared, what was it?

00:34:33.360 yeah what was the movie called come on man you watch all those movies you freak oh free climber

00:34:42.760 free climbers free solo okay so free solo so i i read this article that was describing how

00:34:48.340 you know what he did what he did was amazing um but uh like that could that could have been done

00:34:54.800 200 years ago so but so the only thing the only modern equipment he used was maybe a better shoe

00:35:00.300 right but but what was powerful was the fact that now with you know information technology

00:35:05.640 he had access to all the best techniques and tricks and knowledge so the idea is that it's

00:35:11.760 not that ai is going to be necessarily generating new knowledge but how but enabling us to find

00:35:17.660 um those ingenious ideas and concepts from people and spread it more efficiently and i thought that

00:35:23.720 was really transitions yeah that's a good point so so i think people are thinking oh just throw

00:35:27.740 the data in it and and and it'll tell us what to do and that's that's really not where the biggest

00:35:31.800 opportunity is the biggest opportunity is you know having taking all the the the things that

00:35:37.520 we have found out and and sharing that knowledge more um more freely that makes a lot of sense

00:35:43.680 martin when you look back over the last four years and just you know your career as um somebody

00:35:48.740 that's been irresponsible for like 50 plus people to manufacturing and and leading this business so

00:35:53.340 far um from a personal point of view leadership character who have you needed to become to be

00:36:00.180 you know the ceo that that gets to run this company today from it from a uh just like

00:36:06.600 personal growth point of view you know i i would say um i think one of the things that i learned

00:36:13.440 pretty quick you know when i when i first had people reporting to me is that when you're in

00:36:17.180 a leadership position um you are effectively responsible to act a certain way it's not that

00:36:21.820 you need to be an actor, but that you have a duty to behave a certain way.

00:36:26.520 And so, you know, one of the things I learned early on, you know, if you need to keep your

00:36:33.120 emotions in check, I think, you know, my default MO early on in my career was to be a bit of a

00:36:38.840 bulldozer, right? If somebody was standing in my way, I just run at them harder. And I think

00:36:42.680 learned pretty quickly that that's not the way to get things done. You know, so, you know,

00:36:51.040 I think one of the things is to make sure that, you know,

00:36:56.140 I am thinking about what, you know, if it's a coworker,

00:37:00.880 what they need from the interaction versus what we need the outcome to be.

00:37:06.300 And I think, you know, as you connect with your team,

00:37:09.960 you learn about what makes each person tick.

00:37:12.220 So in the same way where you're, from a sales perspective,

00:37:15.060 learning about, you know, how to, you know, make a customer feel comfortable,

00:37:19.240 I think we, you know, that it's almost, it's some of the same skill set that, that, that

00:37:24.220 skill set per se, persuasion skill set is, is almost used everywhere.

00:37:28.900 I like, I like judo, like how do you work with that energy, but still get the outcome

00:37:34.040 that you want?

00:37:34.800 Yeah.

00:37:34.900 But judo is sort of adversarial, right?

00:37:36.520 Where it's, uh, you know, some of the same idea where like, how do you, you know, how

00:37:40.660 do you, maybe, maybe it's like dancing.

00:37:42.340 Yeah.

00:37:42.920 Right.

00:37:43.120 Yeah.

00:37:43.260 I think that's a better analogy.

00:37:44.440 Um, but there's also opportunity for like at some point, you know, there's always, there's

00:37:49.220 points where you are with an adversary, right?

00:37:51.920 So judo is a little bit more smooth than, say, boxing.

00:37:57.380 You and I are just punching each other in the head, right?

00:37:59.240 So I'd probably get hurt more boxing you than doing judo.

00:38:04.220 But yeah, so I think one of the things

00:38:05.480 is thinking more about what somebody needs from the interaction

00:38:11.960 versus what the company needs as the outcome.

00:38:16.340 And look for that win-win.

00:38:18.620 Yeah, look for the win-win.

00:38:19.460 And also, I think at some point, you know,

00:38:23.040 surrounding myself with people who are better at that than I am

00:38:27.040 and, you know, making sure that people are aligned, you know,

00:38:31.180 teamed up with people, you know, who are good fits for them as managers.

00:38:34.200 Because, you know, managers are, you know,

00:38:36.380 mostly responsible for unblocking and making people feel comfortable

00:38:39.520 versus, you know, assigning tasks.

00:38:42.220 And that's something that, you know, my co-founder Brayden and I

00:38:44.420 have thought a lot about, you know, how it's our instinct

00:38:48.440 to give people space but you know we're figuring out how to do it in a way which

00:38:54.800 is you know not necessarily abdication of responsibility how do we how do we

00:39:00.480 stay close enough to keep people on track but give them enough enough space

00:39:04.340 to run and that's always that challenge to find out you know what what

00:39:08.900 combination of space and guidance each person needs but once once you get that

00:39:13.100 dialed in it's pretty amazing that's where the magic happens one thing I

00:39:17.480 I love, Martin, as we wrap up, is the fact that you're taking stuff that's kind of like the cool word, like AI,

00:39:25.140 but actually like real use case, real customers, especially for manufacturers that a lot of us buy products from.

00:39:34.180 I just find it really cool that your passion for it, and as people have heard through this conversation

00:39:41.000 and other times we've talked, just how much you love doing what you do,

00:39:45.280 And I think it's infectious and it's cool.

00:39:47.160 And I just want to thank you for sharing that and for continuing to kind of like push the standard of, again, great Canadian company.

00:39:56.400 That's just really at the beginning of a pretty cool journey.

00:39:59.660 So thanks for coming on the show.

00:40:00.960 Yeah, thanks for having me.

Dan Martell - April 12, 2021

How A.I. Will Change The SaaS Landscape with Martin Cloake @ Raven.ai

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