#Neuromarketing 1: What is Neuromarketing?

WEBVTT 1 00:00:04.799 --> 00:00:11.750 Often what people say and what their brains tons is quite different. All right, 2 00:00:11.789 --> 00:00:15.669 welcome back to be tob growth. I'm Eric Hastolic, founder and CEO 3 00:00:15.869 --> 00:00:21.109 of postal dot io and your host for today's episode. Today is our first 4 00:00:21.190 --> 00:00:26.460 of three segments in postals neuro marketing series here on B Tob Growth. In 5 00:00:26.579 --> 00:00:31.179 this episode we start the series off by helping you understand what neural marketing is 6 00:00:31.739 --> 00:00:35.969 and why you should care, helping me navigate this conversation. Today I'm thrilled 7 00:00:36.009 --> 00:00:40.130 to be joined by Dr Michael Platt, who's an endoubt professor of neuroscience, 8 00:00:40.170 --> 00:00:45.369 psychology and marketing at the University of Pennsylvania, and Dr Platt's been for featured 9 00:00:45.490 --> 00:00:49.250 in work in The in York Times Washington Post, while she journal Newsweek, 10 00:00:49.289 --> 00:00:53.880 National Geographic, as well as a bunch of different television stations and shows. 11 00:00:54.240 --> 00:00:57.399 Dr Platt, how you doing today? I'm great. It's great to be 12 00:00:57.520 --> 00:01:00.840 here. It's a beautiful sunny day and Philadelphia, where it's always sunny, 13 00:01:02.359 --> 00:01:07.670 that's awesome. Go Eagles, big big EELS. All right, let's let's 14 00:01:07.670 --> 00:01:10.469 get into it here. Tell once you tell the listener is a little bit 15 00:01:10.469 --> 00:01:14.829 about your background and what got you into the field of neural marketing. Yeah, 16 00:01:14.950 --> 00:01:19.260 so I think my background is pretty unusual. In fact, I don't 17 00:01:19.299 --> 00:01:23.459 have any paper credentials in any of the field or departments in which I'm currently 18 00:01:23.500 --> 00:01:30.060 employed. So my undergraduate th agree was in anthropology, and the reason I 19 00:01:30.219 --> 00:01:34.810 ended up in anthropologies because I was interested in human nature. So basically, 20 00:01:34.849 --> 00:01:41.450 what makes us tick, what makes some people take similarly there's or differently from 21 00:01:41.489 --> 00:01:45.370 others, and what makes us tick in ways that sometimes are similar and sometimes 22 00:01:45.409 --> 00:01:49.280 different to the way that animals take? So anthropologies kind of brought us lens 23 00:01:49.719 --> 00:01:55.079 to to look at human beings through from the perspective of culture and biology and 24 00:01:55.640 --> 00:02:00.000 history. And then my PhD was an anthropology as well, though while on 25 00:02:00.200 --> 00:02:04.790 that path, on that journey, I end up moving into psychology, although 26 00:02:04.829 --> 00:02:09.150 m degree wasn't formally in psychology size and I was working on trying to understand 27 00:02:10.069 --> 00:02:15.460 basically how to monk these think and how do they think about the things in 28 00:02:15.500 --> 00:02:20.020 their environment and how do they find their way back to food? By the 29 00:02:20.060 --> 00:02:24.099 time I've finished at my thesis, I realized what I really wanted to understand 30 00:02:24.460 --> 00:02:28.180 was how all this happens in the brain, and so that I did a 31 00:02:28.259 --> 00:02:31.490 post doctoral fellowship that Yu in our science and that's where, when I was 32 00:02:31.569 --> 00:02:36.569 working with my mental all glamsery, we started cooking up a lot of the 33 00:02:36.689 --> 00:02:45.400 early work in neuroeconomics, basically taking the simplest formal accoms of economics and putting 34 00:02:45.439 --> 00:02:51.120 those into experimental designs where we could try to identify the ways in which the 35 00:02:51.240 --> 00:02:58.909 brain might do code simple things like value or risk and and then that was 36 00:02:59.030 --> 00:03:02.509 kind of part of the foundations of the field of neuroeconomics, which was a 37 00:03:02.750 --> 00:03:07.550 presaged neural marketing. So you know, the goals on neuro economics will basically, 38 00:03:08.229 --> 00:03:14.539 you know, to take take them at matical forms of economics and approaches 39 00:03:14.580 --> 00:03:21.620 of Behavior Economics and experimental psychology and and marry those two neuroscience techniques that allow 40 00:03:21.659 --> 00:03:23.580 you to look under the hood in the brain. And the goal was to 41 00:03:23.659 --> 00:03:29.889 find out how we make decisions. And so it was really about basic understanding 42 00:03:30.210 --> 00:03:31.650 on the one hand, and also, to some degree, that trying to 43 00:03:31.729 --> 00:03:37.090 validate economic models which postulate a lot of things like, oh, there's this 44 00:03:37.250 --> 00:03:40.169 thing called utility that lives in your head and it behaves like a common currency 45 00:03:40.250 --> 00:03:44.599 that allows us to weigh apples and oranges, and it's like that. The 46 00:03:44.719 --> 00:03:50.479 nermal marketing comes along a little bit later, because it's basically saying, well, 47 00:03:50.560 --> 00:03:53.879 now that we have some understanding of what drives decision making, can we 48 00:03:53.960 --> 00:03:59.270 use some the same tools in a very applied way to understand, say, 49 00:03:59.550 --> 00:04:06.669 consumer decision making and in so doing develop some are wise and lift by taking 50 00:04:06.750 --> 00:04:12.180 that data and that knowledge right and, you know, using using that to 51 00:04:12.300 --> 00:04:15.860 do better advertising, for example, or to you know whatever. So you 52 00:04:15.939 --> 00:04:18.980 know, that's kind of the pathway. I mean my you know, my 53 00:04:19.060 --> 00:04:25.689 actual faculty positions. I started out a duke in the Ner Biology Department as 54 00:04:25.730 --> 00:04:30.050 an assistant professor twenty years ago, teaching medical students, doing basic science, 55 00:04:30.569 --> 00:04:34.449 and then along the way I spent fifteen years ado, which we're wonderful, 56 00:04:34.930 --> 00:04:41.680 but my colleagues got metal and I started center from their economic studies at Duke, 57 00:04:41.720 --> 00:04:44.519 which was one of the first, I think one of the first two 58 00:04:44.519 --> 00:04:47.360 or three in the country of the world. Yeah, and along the way 59 00:04:47.399 --> 00:04:50.319 I wentever, and along the way I mean in my final position at do 60 00:04:50.519 --> 00:04:55.389 that was director of the instucent brain sciences and and that kind of put me 61 00:04:55.470 --> 00:05:00.829 on the path. We were into the warden because my task as instry directors 62 00:05:00.870 --> 00:05:03.670 to try to not only connect people who do in your science across. Yeah, 63 00:05:03.670 --> 00:05:10.220 there's connect your science to other decipines like business, law, arts, 64 00:05:11.660 --> 00:05:15.939 humanities and you know, which is a pretty heavy lift. There's some pretty 65 00:05:15.019 --> 00:05:18.579 strong cultural and language varies are but that's where it starts to get really exciting, 66 00:05:18.620 --> 00:05:24.649 because those are is that are had been relatively untouched. And so five 67 00:05:24.649 --> 00:05:28.610 years ago I had a great opportunity to come here to Warton and pen yeah 68 00:05:28.689 --> 00:05:38.279 and build those bridges institutionally, to take substantial resources and go big. You 69 00:05:38.360 --> 00:05:41.839 know, I know they would. I don't think they realized how big we 70 00:05:41.879 --> 00:05:45.120 are going to go. But really go big is and and we decided to 71 00:05:45.199 --> 00:05:48.600 be very ambitious and very broad. You know what we're doing at Warton, 72 00:05:48.600 --> 00:05:51.829 which we call the warden science initiative, which is now part of the analytics 73 00:05:51.870 --> 00:05:56.389 at work. So it's all of the science and Beta side. A business 74 00:05:56.509 --> 00:05:59.550 is just in is just in the business school. That's squarely in the business 75 00:05:59.550 --> 00:06:04.100 school, although we partner directly with folks all across campus, from Med school 76 00:06:04.259 --> 00:06:11.339 to arts and Sciences, psychology, computer science, engineering specially interesting and we've 77 00:06:11.459 --> 00:06:15.300 created this, you know, this community where you know, you don't have 78 00:06:15.420 --> 00:06:17.889 to, you know, say you're in marketing or say you're in management. 79 00:06:18.209 --> 00:06:20.810 We yeah, I think some of the biggest banks for the book that we're 80 00:06:20.810 --> 00:06:25.689 going to get this management. You don't have to become in their scientists. 81 00:06:25.769 --> 00:06:29.569 You can. We can partner you with folks you know on campus so that 82 00:06:29.649 --> 00:06:33.040 you can bring your respective expertise together to apply to a problem. And that's 83 00:06:33.079 --> 00:06:40.399 what we do with our educational mission to where we have a curriculum for undergraduates 84 00:06:40.560 --> 00:06:46.509 and MBA's. We have a minor under development for undergraduates in basically applied in 85 00:06:46.550 --> 00:06:50.310 our science for business and one probably a major on the way for as as 86 00:06:50.350 --> 00:06:55.629 well. More than five hundred students in our student society, which is homegrown. 87 00:06:56.029 --> 00:07:00.189 So it's really incredible how much interest there. It was latent, you 88 00:07:00.269 --> 00:07:03.899 know, students were trying to kind of build their still sets on their own, 89 00:07:03.980 --> 00:07:09.540 picking from here and there's the college, and we will consumer behavior a 90 00:07:09.620 --> 00:07:14.420 little, you know, yeah, on whatever. And now we have organized 91 00:07:14.500 --> 00:07:17.569 the song and we've provide a lot of content and you know, we're we're 92 00:07:17.730 --> 00:07:21.329 literally minting students to over the last four years we've gone off to work for 93 00:07:21.410 --> 00:07:26.649 deal sooner they gone off to work. For sure, Google, facebook to 94 00:07:26.769 --> 00:07:30.680 essentially do your marketing. Do Yeah, consumers, consumers, ychology. So, 95 00:07:30.800 --> 00:07:32.879 you know, it's really interesting. In speaking with some of your colleagues, 96 00:07:33.160 --> 00:07:40.480 you know they brought up some of the differences and similarities between the technology 97 00:07:40.639 --> 00:07:46.110 push and AI. Right, so understanding, how can computers essentially understand our 98 00:07:46.230 --> 00:07:51.949 behaviors and then recommend the ways that we can influence people within the business and 99 00:07:53.230 --> 00:07:59.180 the marketing world or verse, Actually Understanding The human brain and what is already 100 00:07:59.220 --> 00:08:07.019 inherently built inside your brain and then influencing people through their ununconscious behavior and how, 101 00:08:07.779 --> 00:08:11.779 if you can bring those two together, it becomes extremely powerful. And 102 00:08:11.939 --> 00:08:15.569 to take a step back, I know a lot of our listeners probably are 103 00:08:15.689 --> 00:08:18.689 thinking, oh my gosh, like how can I use this practically? This 104 00:08:18.050 --> 00:08:22.569 sounds like an academia, you know, discussion. So I think to put 105 00:08:22.569 --> 00:08:28.360 it very basically, to take what good mention is that it's really the understanding 106 00:08:28.399 --> 00:08:31.399 of the brain, how you make decisions, economic decisions, your risks, 107 00:08:31.679 --> 00:08:37.759 your risk profile inside a risking value profiles inside the brain. And then, 108 00:08:37.080 --> 00:08:43.789 if that's neuroeconomics and understanding how you make those decisions, subconsciously. Then neuro 109 00:08:43.909 --> 00:08:48.990 marketing is really taking all of that data that you've mapped essentially within your brain, 110 00:08:50.470 --> 00:08:54.909 and how do you how do you create an opportunity for brands to leverage 111 00:08:54.950 --> 00:08:58.980 that already existing data that's in your brain, or just that that the natural 112 00:08:58.100 --> 00:09:01.899 behavior of someone? Is that a fair yeah, I think that. I 113 00:09:01.980 --> 00:09:07.620 think that's a pretty fair characterization. I mean neural marketing, I think is 114 00:09:09.259 --> 00:09:13.330 important. It can be powerful for several reasons. I mean one I mean, 115 00:09:13.370 --> 00:09:16.730 which is, I think, the easiest to grasp, is you can 116 00:09:16.769 --> 00:09:22.009 kind of provide you can provide a scientific foundation for choosing one way of doing 117 00:09:22.090 --> 00:09:28.279 something versus another. Right, let's just say there's there's two theories in marketing 118 00:09:28.320 --> 00:09:33.360 about how how people respond to brands and and you don't know which one is 119 00:09:33.399 --> 00:09:37.399 right. So you can go to the ner science and say, Oh, 120 00:09:37.440 --> 00:09:41.309 it turns out if you look under the hood, you scan somebody's brain, 121 00:09:41.429 --> 00:09:45.190 it turns out it's this and not that. So that can help you to 122 00:09:45.389 --> 00:09:50.990 make them more educated choice and I think it helps to validate the application of 123 00:09:52.110 --> 00:09:56.259 resources. Putting money into one thing versus another easier to embrace. I can 124 00:09:56.379 --> 00:09:58.740 say, well, this is the way it works in the brain. So 125 00:09:58.899 --> 00:10:03.019 why wouldn't you? You know, we when you take that approach, you 126 00:10:03.139 --> 00:10:05.980 know, I think, the brain right. That's right. And the second 127 00:10:05.500 --> 00:10:09.169 is one where you want to go a step further, which is to say, 128 00:10:09.570 --> 00:10:15.370 well, we can actually acquire some data, new data, to help 129 00:10:15.409 --> 00:10:20.919 us understand, say, the impact of this brand strategy on our customers or 130 00:10:22.000 --> 00:10:26.759 to develop a different metric that is not based on self report, which is 131 00:10:26.799 --> 00:10:33.120 the standard way of testing things in markings. Is Ask people questions. What 132 00:10:33.200 --> 00:10:35.870 people are you thinking about? What made you buy? is how much to 133 00:10:35.990 --> 00:10:41.830 like it, etcetera. Often what people say and what their brains to us 134 00:10:41.990 --> 00:10:45.950 is quite different. Thankful there said. There's a the time. Does that 135 00:10:46.070 --> 00:10:48.629 happen where you know you're doing a user testing and they're saying one thing but 136 00:10:48.710 --> 00:10:52.419 they're thinking another. Is that like we talk of fifty percent or I mean, 137 00:10:54.379 --> 00:10:56.460 that's a I think where you don't know yet because they're you know, 138 00:10:56.539 --> 00:11:03.659 of course it's so very much context dependent and sure there are different market segments 139 00:11:03.700 --> 00:11:07.970 and think that they're really that that are really different to reflect the real differences 140 00:11:07.009 --> 00:11:11.009 in the way people's brains work. But I'll give you an example of churn 141 00:11:11.529 --> 00:11:16.450 in the study that we recently completed and papers under review. And so this 142 00:11:16.649 --> 00:11:20.399 is a study that was aimed at kind of testing part of the notion that 143 00:11:22.120 --> 00:11:28.720 is which is very common in brand strategy, which is that people kind of 144 00:11:28.759 --> 00:11:31.799 think about brands using the same harder in your heads that they used to think 145 00:11:31.799 --> 00:11:35.830 about people, like humanized brands. So we give them personality, traits, 146 00:11:37.110 --> 00:11:41.710 its sexy brand, created brand, etcetera. We develop relationship and ships with 147 00:11:41.789 --> 00:11:46.789 brands love paid and we decide to take that one step further and to say, 148 00:11:46.909 --> 00:11:50.940 well, if we really do develop and these relationships with brands that are 149 00:11:52.340 --> 00:11:56.259 essentially piggybacking on hardware that was already that already evolved to support the way that 150 00:11:56.379 --> 00:12:01.129 we relate to other people and there's a hardwired circuit in our brains that just 151 00:12:01.289 --> 00:12:07.090 does that, okay, then we ought to be able to see responses to 152 00:12:07.289 --> 00:12:13.409 in the brain that look a lot like the empathy and the emotional attachments that 153 00:12:13.610 --> 00:12:16.399 we that we have with our loved ones. Okay, so that's sort of 154 00:12:16.440 --> 00:12:20.320 the idea. So what we did is we brought people to the lab who 155 00:12:20.360 --> 00:12:24.399 were what we do is we focused on smartphones, because those are the thing 156 00:12:24.480 --> 00:12:26.919 that people seem to care a lot about they always have it on them, 157 00:12:28.120 --> 00:12:31.149 spend a lot of money on it, constantly upgrading an extension of them, 158 00:12:31.509 --> 00:12:37.470 extension of themselves. And we focused on the two biggest players in the US 159 00:12:37.549 --> 00:12:41.470 market, which are apple and Samsung. So we got obligate, you know, 160 00:12:41.590 --> 00:12:43.860 apple users and only these apple products. We get Samsung using who don't 161 00:12:43.860 --> 00:12:48.299 use apple products. We brought them to the lab and we scan their brains 162 00:12:48.340 --> 00:12:52.860 while they were getting their heat, reading information about things that were happening to 163 00:12:52.980 --> 00:12:56.820 either their smartphone brand of the other one. That would say some Apple Profits 164 00:12:56.860 --> 00:13:03.370 Sword or, you know, Samsung battery blew up on a plane or jobs 165 00:13:03.450 --> 00:13:05.649 died or whatever. So it sort of good in bad news, with the 166 00:13:05.809 --> 00:13:11.690 prediction that, you know, if you're an apple iphone user and you really 167 00:13:11.769 --> 00:13:15.080 have you really relate to apple as if it's a member of your family, 168 00:13:15.200 --> 00:13:20.039 you'd see what we called rainings, if you'd see responses in reward related there 169 00:13:20.200 --> 00:13:24.799 is when something good happen apple, you see responses and pain related there is, 170 00:13:24.039 --> 00:13:26.909 and you see something bad happen apple, which is exactly what you see. 171 00:13:28.549 --> 00:13:31.110 Say If your child, you know, if you saw your child, 172 00:13:31.230 --> 00:13:35.149 yeah, or yours, about and so we ran this experiment. First of 173 00:13:35.190 --> 00:13:41.190 all, I had to say that all the apple users expressed verbally empathy for 174 00:13:41.230 --> 00:13:43.620 apple, like they said, I felt good. You know that. You 175 00:13:43.700 --> 00:13:46.139 rated. You know they rated feeling very good for good news by Apple, 176 00:13:46.460 --> 00:13:50.379 very bad for bad news by Apple, and not so much so for Samsung, 177 00:13:50.419 --> 00:13:54.620 which is what you'd expect. Samsung users kind of interesting. They expressed 178 00:13:54.620 --> 00:13:58.250 empathy for Samson. I feel good good news about a Samsung, excuse, 179 00:13:58.730 --> 00:14:01.690 bad news about same side. They also evidence a little reverse empathy for apple, 180 00:14:01.769 --> 00:14:05.730 which is important to the story. Like they said, they felt a 181 00:14:05.850 --> 00:14:09.049 little bit good when you hear bad news about apple, if a little bit 182 00:14:09.129 --> 00:14:13.240 that when they were good news at which is important for the story. Because, 183 00:14:13.279 --> 00:14:16.960 okay, so here's here's there. Both groups of customers expressed empathy for 184 00:14:18.000 --> 00:14:20.799 their own break. Yeah, okay, saying they really really feel something for 185 00:14:20.879 --> 00:14:24.509 their brain. So we scan their brains. When we finally found exactly that 186 00:14:24.710 --> 00:14:30.509 in apple customers brains, so boom, you know, reward centers are active 187 00:14:30.629 --> 00:14:33.990 when there's good news about apple and boom, pain centers are active when there's 188 00:14:33.990 --> 00:14:37.950 a bad news about apple. Nothing for Sampson. What happened? We look 189 00:14:37.950 --> 00:14:45.620 at Samsun, good news about Samsun, nothing about Samsung, nothing. So 190 00:14:46.139 --> 00:14:48.779 there's even though they said they felt something, and I don't know where, 191 00:14:48.820 --> 00:14:52.539 that they thought they felt it and they didn't really or they were overstating it 192 00:14:52.659 --> 00:14:54.409 because they were being asked right, and that's a big thing that we know 193 00:14:54.529 --> 00:14:58.929 of in psychology is that people respond to the demands of the experimenter if they 194 00:14:58.970 --> 00:15:03.529 think they're being asked a question for a reason. I don't look like an 195 00:15:03.570 --> 00:15:07.159 idiot like yeah, I think I'm supposed to feel something for my brand. 196 00:15:07.279 --> 00:15:11.960 So so their brains should absolutely no response to Samson. The only thing they 197 00:15:11.000 --> 00:15:15.639 showed was evidence of this reverse ampathy for Apple. So you see a little 198 00:15:15.679 --> 00:15:18.120 bit of like the word, activity for bad news about an apple, and 199 00:15:18.200 --> 00:15:22.789 will be really interesting Hay, and activity for good news by Apple. And 200 00:15:22.309 --> 00:15:26.789 we went further with this, which just to look at some of the kind 201 00:15:26.830 --> 00:15:31.789 of social brain that circuit try that's involved. And basically apple users brains just 202 00:15:33.590 --> 00:15:37.539 you know, their social brain network is lit up when thinking about apple at 203 00:15:37.539 --> 00:15:39.419 all. So the yeah of like a member of their family. That's exactly 204 00:15:39.460 --> 00:15:43.460 what you'd expect and is very selfrelevant. And when you see any of that 205 00:15:43.899 --> 00:15:48.539 in Samsung. So let's take on message. Take on message is that the 206 00:15:48.700 --> 00:15:50.690 things that apple has been doing for the last twenty five years or longer, 207 00:15:52.289 --> 00:15:56.570 which is the really humanize apple and to build a connection with the customers right 208 00:15:56.649 --> 00:16:00.649 where they do everything through apple. The apple store is is one stop shopping 209 00:16:00.809 --> 00:16:06.759 community experienced all the people who work there where the same shirts, literally, 210 00:16:06.799 --> 00:16:10.559 yeah, which the same color shirts, which we know helps to build a 211 00:16:10.639 --> 00:16:14.720 sense of community. Those things have really, really worked and whatever Samson is 212 00:16:15.120 --> 00:16:19.029 has or has not done has not built this strong sense of the community. 213 00:16:19.110 --> 00:16:25.190 Like I'm part of the Samsun truck. So this is this is extremely interesting 214 00:16:25.230 --> 00:16:27.230 when it comes to the be tob world and so a lot of times, 215 00:16:27.429 --> 00:16:30.590 you know, the research that we've seen in our marketing is really focus on 216 00:16:30.669 --> 00:16:34.860 the BTC. Candidly, you know, those those companies generally have a tremendous 217 00:16:34.860 --> 00:16:40.539 amount of funds to to analyze people's brains to see what the reactions are. 218 00:16:41.019 --> 00:16:45.220 Most of the the academic research is going towards these brands, because it's brands 219 00:16:45.259 --> 00:16:49.929 that everybody knows. But to actually take a look at how you can take 220 00:16:51.049 --> 00:16:56.529 this data and take this research and put it towards your own BEDB marketing strategy, 221 00:16:56.570 --> 00:17:00.919 which are listeners today. What I've found is that you have user testing. 222 00:17:02.200 --> 00:17:06.079 That is very important in product development and you know, whenever you're building 223 00:17:06.119 --> 00:17:10.799 something in the business to business world, specifically hardware software, you know things 224 00:17:10.839 --> 00:17:14.200 that people, the businesses used to get their jobs done and be more productive. 225 00:17:14.799 --> 00:17:18.910 You have this testing that you go through and a lot of that testing 226 00:17:18.230 --> 00:17:22.910 is testing messaging, testing workflows, U wise kind of all the things that 227 00:17:23.029 --> 00:17:29.869 go into that that product. And then marketing a lot of times will not 228 00:17:30.220 --> 00:17:34.460 test messaging. It'll test messaging internally, but it will it might do some 229 00:17:34.619 --> 00:17:41.779 AB testing of messaging out externally to see what converts more effectively. But very 230 00:17:41.859 --> 00:17:47.170 rarely do I see companies taking it to the next level of saying okay, 231 00:17:47.369 --> 00:17:52.289 like I how do I build this brand and how do I provide content for 232 00:17:53.289 --> 00:17:59.640 customers to have as much empathy for me as they do their family? And 233 00:18:00.079 --> 00:18:03.759 that's a very interesting concept when it comes to bed be marketing. You know, 234 00:18:04.200 --> 00:18:08.000 you're a business. Your Business is generally by businesses, right, so 235 00:18:08.079 --> 00:18:14.470 you have like assets that are transferring in the sales process, but salespeople, 236 00:18:14.950 --> 00:18:21.269 good sales people who are an extensive marketing generally can develop empathy because they have 237 00:18:21.349 --> 00:18:26.950 a human connection right with people. So bedb marketing can always it. I 238 00:18:26.220 --> 00:18:30.380 honestly think that the best be to be marketing and sales companies. They have 239 00:18:30.539 --> 00:18:40.220 incredible content that helps the salespeople become epathetic and actually help their customers create relationships 240 00:18:40.539 --> 00:18:44.569 that are trusting, that are transparent, that are lasting, that have empathy 241 00:18:44.650 --> 00:18:48.130 and ultimately that provide value. Right. So I think there's a lot of 242 00:18:48.369 --> 00:18:53.049 information that's out there that can be provided to these be tob marketers. That 243 00:18:53.170 --> 00:18:56.519 has been done on the BBC, but I'd love to get your thoughts on 244 00:18:56.279 --> 00:19:02.599 kind of what you've what you've picked up within you your research. I'm sure 245 00:19:02.599 --> 00:19:06.279 you understand it kind of how the B tob sales and marketing work clothes. 246 00:19:06.319 --> 00:19:11.150 But what are some practical applications that be tob marketers can use in neuro marketing? 247 00:19:11.390 --> 00:19:15.029 If they don't have access to a lab, right, they can't test 248 00:19:15.069 --> 00:19:18.509 their their subjects and there there, there their folks that they're doing these message. 249 00:19:18.509 --> 00:19:21.230 You tell me a little bit about how they actually can use neural marketing 250 00:19:21.309 --> 00:19:23.339 themselves? Well, here's the other thing about neuro marketing. So it is 251 00:19:23.380 --> 00:19:29.579 a very young discipline, a very young field. Maybe it is. It's 252 00:19:29.619 --> 00:19:33.259 been around a decade, but not really. Seriously, it's a really just 253 00:19:33.460 --> 00:19:37.539 in the last replace your ins wow, I mean and and I don't think 254 00:19:37.619 --> 00:19:41.450 anybody really believed a lot of it until the past us. There where where 255 00:19:41.490 --> 00:19:48.089 it had really gotten refined and use is that because of the the scientific mapping. 256 00:19:48.690 --> 00:19:52.769 It was at the access to scientific mapping and in the centers they give 257 00:19:52.769 --> 00:19:56.480 it you sort of a lot. There's just a lot of well, there's 258 00:19:56.519 --> 00:19:59.680 a number of things and there's just a lot of research and had to be 259 00:19:59.799 --> 00:20:03.839 done and a lot of finement in terms of the technologies and then, secondarily, 260 00:20:04.559 --> 00:20:11.710 developing better algorithms for relating the data that you do acquire to something that 261 00:20:11.910 --> 00:20:15.829 is of interest, you know, from the marketing perspective. So, for 262 00:20:15.910 --> 00:20:18.910 example, and you know, I think you'll probably hear this from some of 263 00:20:18.950 --> 00:20:23.259 the folks who you'll interview the couple of podcasts from now. Yeah, but 264 00:20:23.420 --> 00:20:29.099 to show that if I take a small group, essentially a focus group, 265 00:20:29.220 --> 00:20:32.380 into the lab, so like I send a lot of money, I'm going 266 00:20:32.420 --> 00:20:34.339 to gather some date on them. Maybe that's brain scans, which is a 267 00:20:34.380 --> 00:20:37.329 little bit expensive, but you can even use each heart rate, things like 268 00:20:37.450 --> 00:20:41.250 that, and to show that I can take that and, with a sophisticate 269 00:20:41.289 --> 00:20:47.450 Algorithm, I can actually predict the behavior millions of people, the purchasing behavior 270 00:20:47.529 --> 00:20:52.160 and millions of people. Okay, that that's powerful right. I can take 271 00:20:52.160 --> 00:20:56.240 two dozen people in the lab and I can forecast what sales are going to 272 00:20:56.279 --> 00:21:00.759 be. I can forecast what viewership is going to be for television shows. 273 00:21:02.599 --> 00:21:07.390 You know, we're talking hundred polticals, people. Political stuff is absolutely so 274 00:21:07.509 --> 00:21:11.950 that's, I think, where we're now. You know that that made a 275 00:21:11.990 --> 00:21:15.150 believer out of me. I mean I think that that can scale up in 276 00:21:15.150 --> 00:21:19.019 a variety ways and for the D to be application. First of all, 277 00:21:19.019 --> 00:21:23.539 I wish you're your listeners could come to my class might that I teach for 278 00:21:23.700 --> 00:21:27.940 NBA students and for undergraduates, which is called introduction brain size for business. 279 00:21:29.059 --> 00:21:33.490 The end project is a new they have to create a start up that will 280 00:21:34.009 --> 00:21:38.690 develop something new, some new application of their size to business, and by 281 00:21:38.730 --> 00:21:41.490 and large it's like, I don't know, eighty percent of the things they 282 00:21:41.529 --> 00:21:45.450 come up with their be to be I mean, and they're great, I 283 00:21:45.529 --> 00:21:48.279 mean they're really cool. By the way, they're going to really lead towards 284 00:21:48.359 --> 00:21:52.279 me to see. I mean that's a let. No student's generally know like 285 00:21:52.559 --> 00:21:55.440 that. If they're yeah, that's that's awesome. But the reason why they're 286 00:21:55.440 --> 00:21:59.200 leading they're really going hard at bet bees. So much more money there. 287 00:21:59.359 --> 00:22:03.990 So there's a ton of a ton of opportunities. One of the creative projects 288 00:22:03.029 --> 00:22:07.990 that I worked on with an NBA student, which leverages a study we did 289 00:22:07.150 --> 00:22:11.150 with brain imaging but doesn't require brain imaging. So now this is sort of 290 00:22:11.190 --> 00:22:15.299 a practical indication. So this was a study where, the brain imaging side 291 00:22:15.299 --> 00:22:21.259 of things, we developed a way to scan people's brains while they were seeing, 292 00:22:21.299 --> 00:22:26.339 say, different brands of the particular product category, like cars. It's 293 00:22:26.380 --> 00:22:30.690 the different car brands for themw etcetera. And we know that if you just 294 00:22:30.809 --> 00:22:34.289 ask people to they're sitting there, you just said write down all the carbonage. 295 00:22:34.329 --> 00:22:38.410 To think of, the order which they write them down is perfectly poorly 296 00:22:38.529 --> 00:22:44.289 with market share. Same for Beers and for whatever. So kind of leveraging 297 00:22:44.359 --> 00:22:48.720 off that brand equity observation, we thought, well, we know something about 298 00:22:48.960 --> 00:22:55.519 the way that kind of concepts are structured in your brain and that two concepts 299 00:22:55.559 --> 00:23:00.029 or two words that are seen closer and meeting have more APP overlapping kind of 300 00:23:00.150 --> 00:23:04.630 representation in your brain. Just the PIXELS, the spots on the brain that 301 00:23:04.710 --> 00:23:10.349 are activated will be much more overlapped than if two concepts are very different from 302 00:23:10.390 --> 00:23:14.700 each other. So we thought a brand that shows more overlap with the word 303 00:23:14.779 --> 00:23:18.380 car is actually going to be one that is more similar to car in the 304 00:23:18.420 --> 00:23:23.420 might of consumer, of a customer, and therefore should that should predict market 305 00:23:23.500 --> 00:23:26.410 share, ball blah, and we also were able to show that that could 306 00:23:26.930 --> 00:23:30.009 lend itself toward brand extension. So this is, I think, a really 307 00:23:30.089 --> 00:23:34.970 interesting opportunity that if we take a different concept like computer and we look at 308 00:23:34.970 --> 00:23:40.609 the mapping between car brains and computer, the car brains that look more like 309 00:23:40.769 --> 00:23:45.839 computer in your brain are going to be the ones that share greater fit with 310 00:23:45.000 --> 00:23:48.759 that idea and in fact, should do better, should be treated by the 311 00:23:49.000 --> 00:23:53.119 average consumer as a better idea of a computer maker. And so it turns 312 00:23:53.160 --> 00:23:56.549 out this true. It's like, what are the ones that have had the 313 00:23:56.589 --> 00:23:59.869 best overlap? Look like they were BMW, which actually turns out to make 314 00:23:59.910 --> 00:24:03.750 a high and gaming computer on the Toyota. What were ones that were the 315 00:24:03.829 --> 00:24:07.349 worst they were like Ford Chrysler would like, are you going to buy a 316 00:24:07.430 --> 00:24:11.460 forward computer? You're going to buy a Chrysler computer. Doesn't sound like so 317 00:24:11.740 --> 00:24:15.980 that sparking the idea in these students that which like wow, you know, 318 00:24:15.339 --> 00:24:21.980 we could use the same approach for mergers and acquisitions. Okay, so this 319 00:24:22.180 --> 00:24:26.210 is pretty cool idea. We didn't look at that mapping, but instead we 320 00:24:26.329 --> 00:24:30.250 used a proxy, which is based on personality. So we had consumers, 321 00:24:30.369 --> 00:24:37.170 we had people, sewers found to sort of personality metrics for different companies that 322 00:24:38.079 --> 00:24:44.359 were involved in acquiring another company. So and basically our hypnosis was if the 323 00:24:44.720 --> 00:24:48.559 personality is in this sort of multidimensional space, little more similar than that, 324 00:24:48.599 --> 00:24:52.589 would be better fit and they would have better sales. HMM. And it's 325 00:24:52.630 --> 00:24:56.630 actually what we found. It's like, so, think about how much money 326 00:24:56.869 --> 00:25:00.269 is involved in a merger, right, and you got failed mergers at some 327 00:25:00.390 --> 00:25:06.750 that are successful. If you could use this brain, you know, neurosignes 328 00:25:06.910 --> 00:25:11.940 derived approach, but it's not at doesn't involve it. You don't scar anybody's 329 00:25:11.940 --> 00:25:15.420 brain, but anything. It's just it's a derisive of that approach. And 330 00:25:15.500 --> 00:25:19.500 now you yes, so you're drawing correlations it's correlations of the research that's already 331 00:25:19.500 --> 00:25:25.089 be done with the existing opportunities. That's exactly right, and so we based 332 00:25:25.130 --> 00:25:30.210 on this, you could predict the effectiveness, the likelihood that this merger will 333 00:25:30.210 --> 00:25:33.690 actually pay off. What was the confidence right on it? But I don't 334 00:25:33.730 --> 00:25:34.960 remember. I mean we're still in the middle of that paper and reminds me 335 00:25:36.079 --> 00:25:38.799 God and connect, you know, circle back to that. Student. Would 336 00:25:38.839 --> 00:25:41.720 love to hear follow up on that. Yeah, yeah, so it's but 337 00:25:41.839 --> 00:25:45.160 it's, I think you know again, it's a novel concept in a novel 338 00:25:45.799 --> 00:25:49.710 kind of Algorithm Approach. That, yeah, some especially if you have a 339 00:25:49.789 --> 00:25:52.990 technology company and you're starting a business, fake it to your make. It 340 00:25:53.269 --> 00:25:56.710 is obviously that you know what you want to do and and I've done that 341 00:25:56.750 --> 00:26:02.309 quite a few times, but but when you fake it to make it before 342 00:26:02.349 --> 00:26:04.900 you make it, generally what you're looking is what are the established companies out 343 00:26:04.900 --> 00:26:08.339 there doing? One are the best brands within your market doing, and how 344 00:26:08.380 --> 00:26:14.299 can you borrow some of those strategies? Obviously they have a lot more critical 345 00:26:14.380 --> 00:26:18.420 mass to be able to determine like, okay, like this is worked or 346 00:26:18.460 --> 00:26:21.730 this isn't. I don't think it's been based on neuroscience. I think it's 347 00:26:21.730 --> 00:26:25.289 actually just been based on conversion. Right. So internally conversion it said that 348 00:26:25.289 --> 00:26:26.849 they see it is works better than this. Say I should try to explaining 349 00:26:26.890 --> 00:26:32.809 page these words whatever else. So when we think about the the next like 350 00:26:32.960 --> 00:26:38.640 twenty years of neuroscience and neuro marketing, it seems to me that we could 351 00:26:38.640 --> 00:26:45.039 be running into an ethical situation here if we if we map the brain, 352 00:26:45.200 --> 00:26:48.710 if we understand the pleasure centers and the distress centers of the brain and and 353 00:26:49.509 --> 00:26:56.990 we actually are building brands to to obviously build empathy and have and try to 354 00:26:56.029 --> 00:27:00.819 build a brand that you have a personal relationship and we've figured out people's minds. 355 00:27:02.619 --> 00:27:07.059 What happens to choice at that point? What happens to what happens to 356 00:27:07.140 --> 00:27:11.380 the the power of being able to douse? I mean, people have been 357 00:27:11.420 --> 00:27:15.059 worried about this, rightfully so, for a long time and I think the 358 00:27:15.180 --> 00:27:18.450 only thing that's happening here is we're bringing even more, you know, power, 359 00:27:18.730 --> 00:27:22.170 you know, and more different kinds of data to bear on the same 360 00:27:22.250 --> 00:27:29.089 question. I mean, I it's it's something that we're very actively engaged in 361 00:27:29.569 --> 00:27:33.480 the sort of ethical, legal and societal implications of applying our science and business. 362 00:27:33.519 --> 00:27:37.200 In fact, our very first summit that we have a yearly slid for 363 00:27:37.279 --> 00:27:42.680 Wardner Science, was on that very topic. It's important. Scientists don't have 364 00:27:44.549 --> 00:27:48.150 exclusive purchase just on the answers. So I think this is something that we 365 00:27:48.910 --> 00:27:53.509 have to grapple with as a society and as business people. We saw the 366 00:27:53.670 --> 00:28:00.940 fallout right with facebook and Cambridge analytica years ago, because at least some of 367 00:28:00.059 --> 00:28:06.339 the principles that have been articulated in bio medicine and also advertising by the Advertising 368 00:28:06.420 --> 00:28:11.140 Research Foundation that you know, at least consent is super important. Right. 369 00:28:11.140 --> 00:28:15.650 Sure, consent. There needs to be security for their data and their identity. 370 00:28:15.769 --> 00:28:19.410 Those things are a really, really critical but the one that you brought 371 00:28:19.410 --> 00:28:25.890 up, which is choice, which is autonomy and agency, we can't take 372 00:28:25.970 --> 00:28:30.200 that away. I don't think we're going to be in a position where that's 373 00:28:30.480 --> 00:28:33.599 even if we maximized everything. HMM, there's, you know, there's there's 374 00:28:33.640 --> 00:28:38.319 still so much noise in the system that you can, even under the most 375 00:28:38.319 --> 00:28:45.430 controlled conditions, you can get statistical deviations from optimal decisions, etc. So 376 00:28:45.430 --> 00:28:48.789 I think that there's there's enough, there's enough play and enough noise in the 377 00:28:48.869 --> 00:28:52.069 system, that it's not just going to completely remove people's agency in terms of 378 00:28:52.109 --> 00:28:55.349 choice. The other is that, you know, if you're thinking, you're 379 00:28:55.349 --> 00:28:57.299 worrying about like we're just gonna be able to put our finger on the buy 380 00:28:57.420 --> 00:29:00.660 button in the brain and just push it really hard. Yeah, yeah, 381 00:29:02.700 --> 00:29:03.940 that. You know, Amazon is a good jot with that, by the 382 00:29:03.980 --> 00:29:07.099 way. They might, yeah, it might that. That part may work, 383 00:29:07.220 --> 00:29:12.250 but we also have a really, really powerful circuit in our brains that 384 00:29:14.130 --> 00:29:19.690 allows us to learn from experience and learn from mistakes. And if you buy 385 00:29:19.809 --> 00:29:25.279 something and you hate the product or it sucks, presumably not going to buy 386 00:29:25.319 --> 00:29:27.680 it again. But unless that we're not telling your friends or tell your friends, 387 00:29:27.720 --> 00:29:30.000 like, unless it's not. Yeah. So, I mean I think 388 00:29:30.039 --> 00:29:34.720 that's one side of the you know, one side equations to choir customers, 389 00:29:34.880 --> 00:29:38.990 right, yeah, but to hold on to them and building epathy and loyalties 390 00:29:40.029 --> 00:29:42.390 really important for all of that, all hells being equal, but if your 391 00:29:42.430 --> 00:29:48.750 product is terrible, you're not going we're still cognitive creatures. I still understand 392 00:29:48.910 --> 00:29:51.950 like, oh, yeah, this is not working for me, I'm going 393 00:29:51.990 --> 00:29:56.259 to choose out of this. So that that's that's really interesting and I'm sure 394 00:29:56.819 --> 00:29:59.140 you know, we could absolutely go down the route of, you know, 395 00:29:59.259 --> 00:30:06.819 the actually the customer acquisition marketing strategy and the customer retention strategy and the ability 396 00:30:06.980 --> 00:30:11.849 to influence the MPs of your customers and the are they are they how they 397 00:30:11.329 --> 00:30:15.049 how are they reacting to your brand, the product itself, and then are 398 00:30:15.089 --> 00:30:19.210 they telling more people about it, which is obviously the kind of the Golden 399 00:30:19.289 --> 00:30:22.200 Goose of BP marketing. It's like, Hey, how do I make that 400 00:30:22.319 --> 00:30:26.079 happen? So it's really interesting. Well, I'd love to wrap it up 401 00:30:26.079 --> 00:30:30.240 with a a couple of questions here. You know, we're at at postal. 402 00:30:30.480 --> 00:30:34.910 You know, were an offline engagement system and we help marketers and sale 403 00:30:36.309 --> 00:30:40.950 sales people engage with folks in the offline world. We know the last your 404 00:30:40.990 --> 00:30:45.150 twenty years have been spent in digital marketing and part of my intention to start 405 00:30:45.269 --> 00:30:48.789 this business was something that had to do with neuro marketing. I believe that 406 00:30:48.349 --> 00:30:53.180 the brands that I was interacting with in the BTC world, so the stuff 407 00:30:53.259 --> 00:30:56.779 that I was being sent or the interactions I had in a retail environment, 408 00:30:57.500 --> 00:31:02.940 whether it be tactile or smell, that I was being influenced in and just 409 00:31:03.099 --> 00:31:07.569 in the brain of this is I want this right, how do I get 410 00:31:07.170 --> 00:31:12.809 and so I was very interested in building an offline tactile experience that can scale 411 00:31:12.930 --> 00:31:18.049 and building technology around solving that big problem. I'd love to get your thoughts 412 00:31:18.250 --> 00:31:25.759 on how people engage two different messages in the brain, from a digital standpoint 413 00:31:26.039 --> 00:31:32.079 to a tactical standpoint, and and where you've seen the differences or comparisons within 414 00:31:32.200 --> 00:31:37.910 those two experiences. I'm a little bit basically, like seeing something on a 415 00:31:37.109 --> 00:31:41.549 screen, yeah, seeing something in a screen versus tact something that holds. 416 00:31:41.710 --> 00:31:45.630 Yeah, yeah, yeah, so there hasn't been a lot of work done 417 00:31:45.670 --> 00:31:48.460 on that. Quite okay. Part of the reason why, I think, 418 00:31:48.500 --> 00:31:53.059 is that for a lot of people, neral marketing is synonymous with brain imaging, 419 00:31:53.099 --> 00:31:56.819 and brain imagings is not led, since you got to lie down and 420 00:31:56.059 --> 00:32:00.099 emory machine and lends itself pretty well to putting a screen in front of your 421 00:32:00.140 --> 00:32:06.089 face see you something digital, but it's not great for moving around, for, 422 00:32:06.450 --> 00:32:08.369 you know, for interacting with something in a you know, a kind 423 00:32:08.369 --> 00:32:13.009 of normal yeah, fashion. I mean I think that's going to change because 424 00:32:13.329 --> 00:32:19.359 many of us in our marketing have moved beyond brain imaging for reasons of both 425 00:32:19.519 --> 00:32:24.359 cost and it's just can't scale very well because and it inhibits you can't put 426 00:32:24.400 --> 00:32:30.349 it on your head and walk around shopping mall. So we use other technologies 427 00:32:30.470 --> 00:32:34.549 like EG which measures brain waves, and then other things measuring and your heartbeat, 428 00:32:34.670 --> 00:32:37.109 things like that, which is really great because you can do that through 429 00:32:37.109 --> 00:32:43.230 wearable devices now, and so you could have somebody in a real world setting 430 00:32:43.390 --> 00:32:49.900 interacting with tactile to actual paper goods, with a yeah, with the physical 431 00:32:49.940 --> 00:32:52.819 layout of a store, of a retail environment. Of fact, we've done 432 00:32:52.859 --> 00:32:57.980 some of those studies, which is I think, and they're super interesting. 433 00:32:58.420 --> 00:33:00.730 But there's only one study I know of that looked at the direct comparison of 434 00:33:00.809 --> 00:33:07.250 digital versus paper and sort of study done by Angelica Democa and the her group, 435 00:33:07.289 --> 00:33:12.329 that Temple Fox Music School. It was a study for the postal service 436 00:33:12.410 --> 00:33:15.119 a few years ago, HMM, and that's exactly what they looked at and 437 00:33:15.839 --> 00:33:19.200 and they use brain imaging. I mean it was kind of hard because you 438 00:33:19.240 --> 00:33:22.279 had to get people interacting with the with the material, but they found that 439 00:33:22.319 --> 00:33:28.430 actually the physical stuff, I mean, which instead it makes complete sense, 440 00:33:28.509 --> 00:33:32.589 the physical stuff having in your hand right you have your activating more sensory channels. 441 00:33:32.829 --> 00:33:36.869 So you see it, you feel it, you hear it. If 442 00:33:36.910 --> 00:33:40.230 the paper Russell's right, it's in your haptic space, which is special in 443 00:33:40.309 --> 00:33:45.019 terms of motor control. And so there was a you know, more of 444 00:33:45.099 --> 00:33:50.180 the brain activated. There was a sort of seemed like greater drive and reward 445 00:33:50.259 --> 00:33:54.180 centers and centers that are kind of involved in attention and engagement. HMM It. 446 00:33:54.500 --> 00:33:58.049 You know, that was an initial study. It doesn't show us at 447 00:33:58.089 --> 00:34:00.650 definitively like one is better than the other. Sure, you know some are, 448 00:34:00.930 --> 00:34:04.569 you know, going to offer. It's all about pros and cons and 449 00:34:05.329 --> 00:34:07.090 and you know how much of your how much of you spend, you want 450 00:34:07.130 --> 00:34:12.239 to put on digital versus something else. We found that it's to that point 451 00:34:12.320 --> 00:34:15.920 real quick that we found that it actually has a lot to do with messaging 452 00:34:15.440 --> 00:34:20.920 and timing based on where you're at within a sales cycle. So if you 453 00:34:21.000 --> 00:34:23.159 get like a random bottle of wine from a wrap and you never heard from 454 00:34:23.239 --> 00:34:28.309 this person before, it's going to be a different experience than like, Oh, 455 00:34:28.349 --> 00:34:31.710 I've seen, I've seen this brand online. They've cookie me. So 456 00:34:31.789 --> 00:34:36.670 I see it everywhere online. Yeah, and then I get an email for 457 00:34:36.789 --> 00:34:39.059 introductions. I've gotten a few phone calls and next thing you know I'm a 458 00:34:39.099 --> 00:34:43.099 decision maker and I get a nice bottle of wine with a handwritten note for 459 00:34:43.179 --> 00:34:45.619 a rep that is going to be a different words of getting. Yeah, 460 00:34:45.780 --> 00:34:49.500 yeah, yeah, totally, they have that. Yeah, that's very cool. 461 00:34:50.099 --> 00:34:54.210 I think this is an area that is really right for for exploitation. 462 00:34:55.050 --> 00:34:58.090 We did decided to get back to what we were talking about before. For 463 00:34:58.210 --> 00:35:06.130 Yeah, Large Enterprise Software Solution Company, where we were monitoring people's brain states 464 00:35:07.050 --> 00:35:13.360 while they were moving through a large conference environment and also going to keynotes and 465 00:35:13.440 --> 00:35:17.119 things like that, so we could get without interrupting them to ask them questions 466 00:35:17.199 --> 00:35:21.949 or mailing them a survey. Afterward, we can continue as read out on 467 00:35:22.469 --> 00:35:24.949 how engaged they were, how much they were liking what they were seeing and 468 00:35:25.110 --> 00:35:30.710 hearing and whatever else was going on. Wow, and it's pretty cool because 469 00:35:30.469 --> 00:35:35.590 we could and we also had tracking trackers on them, and so we could 470 00:35:36.019 --> 00:35:39.659 predict like which booths they would visit and how long they would spend their and 471 00:35:39.739 --> 00:35:45.300 their whole path through this environment, I guess from the brain data, which 472 00:35:45.059 --> 00:35:49.300 I think there's so much potential there in terms of what you could do with 473 00:35:49.380 --> 00:35:52.090 that, in terms of what you invest in. Any could be a retail 474 00:35:52.090 --> 00:35:55.489 environment, you name it, how you lay things out, you know what 475 00:35:55.769 --> 00:36:00.289 looks in terms of driving engagement, which it turned out a lot of that 476 00:36:00.570 --> 00:36:06.440 was social interaction. So something when there's a person there is much more, 477 00:36:06.880 --> 00:36:10.119 you know, motivating and engaging and would drive people in. And the other 478 00:36:10.199 --> 00:36:15.559 thing that was really fun was like watching people's brain activity during keynotes, where 479 00:36:15.559 --> 00:36:21.110 these are all people who are ostensibly kind of this was their company and so 480 00:36:21.150 --> 00:36:27.590 they're sitting there watching keynotes by by the CEO The company, by entertainers like 481 00:36:27.789 --> 00:36:31.630 bear Grilli is sold out of Brian Tim Cook. That's pretty fun because, 482 00:36:31.789 --> 00:36:37.260 like you had some people who are up here in like high engagement, liking 483 00:36:37.300 --> 00:36:39.059 you a lot, like bear grills, you know. Yeah, I'm kind 484 00:36:39.059 --> 00:36:43.500 of like Tim Cook down in this quadrant, like I don't know what they 485 00:36:43.739 --> 00:36:46.690 spent on him, but it was like, you know, low engagement, 486 00:36:46.929 --> 00:36:51.690 want to leave, but I can't yet. He is the most influencial, 487 00:36:51.809 --> 00:36:55.969 apatheticathybasse brand that everybody loves right. Well, I love valid is. They 488 00:36:57.010 --> 00:36:59.610 had to stay there because they had to hear what he was going to say, 489 00:36:59.730 --> 00:37:04.880 but it's they're saying. Really Fun is boring and I really, I 490 00:37:05.000 --> 00:37:09.280 really don't like wow, wow. Well, I mean especially when you're spending 491 00:37:09.480 --> 00:37:15.599 I'm I probably can guess who you're talking about, but you probably can imagine 492 00:37:15.639 --> 00:37:20.110 how much money they're spending on those events to try to engage their customer base 493 00:37:20.190 --> 00:37:23.949 or their employee base and mobilize for productivity or sales or whatever else. So 494 00:37:24.630 --> 00:37:30.539 that's extremely interesting. You know, it sounds like we're just scratching the surface 495 00:37:30.900 --> 00:37:36.300 with what the opportunity is for this space and it's amazing to hear that Wharton 496 00:37:36.860 --> 00:37:40.099 and pain are just are spending the capital needed for the research, for the 497 00:37:40.179 --> 00:37:46.570 resources to really document what the future can be with this. And as much 498 00:37:47.210 --> 00:37:52.010 I did some studies at MIT on artificial intelligence and as much as you know, 499 00:37:52.050 --> 00:37:57.250 I want to love the the the path that a I can take us 500 00:37:57.409 --> 00:38:02.440 in and decisionmaking and recommendation engines and making sense of big data sets, I 501 00:38:02.559 --> 00:38:07.199 think we're missing out and and maybe this is kind of an entry point of 502 00:38:07.800 --> 00:38:13.949 really what is the human brain want and how can you help your customers or 503 00:38:14.309 --> 00:38:20.750 help tail your message to the way people actual behave and the way they think 504 00:38:20.989 --> 00:38:25.269 and what makes them take and that is that is something that's extremely important when 505 00:38:25.269 --> 00:38:29.900 it comes to marketing and I think you know your your research is going to 506 00:38:29.980 --> 00:38:34.179 be imperative today in the future. So I really appreciate you joining me today, 507 00:38:34.500 --> 00:38:37.380 Dr Platt. Thanks so much. Working folks learn more about you, 508 00:38:37.659 --> 00:38:42.690 more about the information that we've been talking today, they should check out the 509 00:38:43.369 --> 00:38:47.090 our website for the warden neuroscience initiative, neurow dout warden. Do you pinned 510 00:38:47.289 --> 00:38:51.889 EEDU? And also analytics at warden. So one of the speaking to the 511 00:38:51.929 --> 00:38:57.960 question of Ai and analytics. In the last couple of years Warton has created 512 00:38:58.039 --> 00:39:05.000 this sort of Uber umbrella that is analyst Warton, and within that lives neuroscience, 513 00:39:05.159 --> 00:39:08.719 lives, people analytics, customer analytics and Ward and budget model, so 514 00:39:08.880 --> 00:39:14.349 kind of all the data driven sciences, and so we are explicitly marrying those 515 00:39:14.429 --> 00:39:19.429 together. So we're saying that, like, you get more by synergizing from 516 00:39:19.550 --> 00:39:23.460 with observable data about what people do and then what we can understand by looking 517 00:39:23.460 --> 00:39:28.139 under the hood in terms of what their brains are thinking and feeling. So 518 00:39:28.300 --> 00:39:31.500 it's like so I so I encourage them. You go to analytux of Warten, 519 00:39:31.820 --> 00:39:36.019 go to work ners science and you're going to find a lot of really 520 00:39:36.099 --> 00:39:39.889 great stuff. That's awesome. This is a been the first part series of 521 00:39:39.969 --> 00:39:45.090 the three segments in postals. Take over from Bob Growth on neuro marketing. 522 00:39:45.130 --> 00:39:49.730 Dr Plot thinks. So much for joining me today and we hope to see 523 00:39:49.769 --> 00:39:52.760 everybody in the next couple episodes like so much. Thank you, it's been 524 00:39:52.840 --> 00:39:59.639 great. This episode is brought to you by Postal di Oh. 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