#CX 50: The Marketing Impacts of Artificial Intelligence w/ William Ammerman

WEBVTT 1 00:00:04.679 --> 00:00:11.910 It's about persuasion, not coercion or deception. It's a simple formula. Most 2 00:00:12.070 --> 00:00:18.910 consumers are willing to be persuaded. As we move into a time when our 3 00:00:18.949 --> 00:00:25.500 business relationships are increasingly driven by and influenced by artificial intelligence and machine learning, 4 00:00:25.780 --> 00:00:31.539 it's important to understand the consequences. It's important to deploy tech in a way 5 00:00:31.579 --> 00:00:36.090 that puts our people in their best position to win. Mightime is Ethan butte 6 00:00:36.450 --> 00:00:42.090 coauthor of the Book Rehumanize Your Business and I also host the CX series here 7 00:00:42.170 --> 00:00:46.729 on b Tob Growth and our guest, William Ammerman, wrote an excellent book 8 00:00:47.170 --> 00:00:52.119 on the ethics and impacts of artificial intelligence. He breaks it down into common 9 00:00:52.159 --> 00:00:57.039 language and he'll get you thinking about what ai means for you as a customer 10 00:00:57.479 --> 00:01:03.000 and as an operator inside a business. Here we go, all right, 11 00:01:03.000 --> 00:01:07.150 I'm opening this episode of the Customer Experience Podcast with a quote, and here 12 00:01:07.189 --> 00:01:11.950 it is. As our interactions with artificially intelligent agents become more human like through 13 00:01:11.989 --> 00:01:18.430 natural language Algorithms, we will begin to have conversations with machines. We will 14 00:01:18.469 --> 00:01:23.540 build empathic relationships with those machines in which we are even more vulnerable to their 15 00:01:23.700 --> 00:01:26.620 influence. Those words come from a book that you should read. It's called 16 00:01:26.659 --> 00:01:32.060 the invisible and marketing in the age of automation, big data and machine learning 17 00:01:32.140 --> 00:01:36.810 and obviously has implications for the entire customer life cycle, marketing, sales and 18 00:01:36.890 --> 00:01:41.329 customer success. But it's author, and our guest today, also covers its 19 00:01:41.370 --> 00:01:46.689 implications for finance and investing, policy and politics, health and medicine, insurance, 20 00:01:46.730 --> 00:01:49.879 education, religion, even sex. It's a book I highly recommend and 21 00:01:49.920 --> 00:01:55.200 it draws on his master's work at UNC Chapel Hill about persuasion as a science 22 00:01:55.480 --> 00:01:59.640 and machine learnings ability to keep our faces glued to our screens. It also 23 00:01:59.680 --> 00:02:04.510 draws on his work at MIT on natural language processing and humans and pathic responses 24 00:02:04.670 --> 00:02:08.229 to our devices. He has years of experience as a VP and EEDP and 25 00:02:08.270 --> 00:02:14.389 digital media and digital advertising. He's currently the Executive Vice President of digital media 26 00:02:14.430 --> 00:02:19.699 at the engaged media portfolio of brands. William Ammerman, welcome to the customer 27 00:02:19.740 --> 00:02:24.340 experience podcast here. I'm glad to have the opportunity to talk about the invisible 28 00:02:24.379 --> 00:02:28.340 brand with you. As I said, I really, really enjoyed it. 29 00:02:28.379 --> 00:02:31.330 I recommend it to anyone who's listening there's a great deal of tension in there, 30 00:02:31.610 --> 00:02:36.530 and by the tension I mean, you know, the human experience machines. 31 00:02:36.569 --> 00:02:39.770 As they get smarter and they know more about us, they can leverage 32 00:02:39.810 --> 00:02:45.840 that against us, potentially in this vulnerability of this empathic response that we have 33 00:02:45.960 --> 00:02:49.120 an all these things just so rich. So, before we get going, 34 00:02:49.319 --> 00:02:55.039 let's cut right to it. is human domination by SUPERINTELLIGENCE INEVITABLE? No, 35 00:02:55.240 --> 00:03:00.830 I don't think so. I think a partnership between humans and machines is probably 36 00:03:00.870 --> 00:03:05.870 a better way of expressing what I view as the future. But I do 37 00:03:06.030 --> 00:03:09.430 think that machines get smarter and smarter and I think that machines will continue to 38 00:03:09.469 --> 00:03:15.699 do things that we associate with human like intelligence and that we are just really 39 00:03:16.020 --> 00:03:20.699 starting to experience it, so that we've just kind of seen the tip of 40 00:03:20.740 --> 00:03:23.740 the iceberg. What are your thoughts? When I see customer experiencing? You're 41 00:03:23.780 --> 00:03:28.889 preparing to come on to the customer experience podcast. What does customer experience mean 42 00:03:28.969 --> 00:03:31.409 to you? I don't have a pat definition, but I think what I 43 00:03:31.490 --> 00:03:37.810 think of the customer experience. I think of the interaction between brands and consumers 44 00:03:38.289 --> 00:03:44.360 and I think about whether or not the consumer has a positive or negative impression 45 00:03:44.400 --> 00:03:50.439 of the brand and I also think about whether or not the relationship feels ethical 46 00:03:50.639 --> 00:03:53.840 and transparent and trusted. So when I think of, you know, kind 47 00:03:53.879 --> 00:03:57.949 of the customer decision journey, which is a phrase that we use a lot 48 00:03:58.069 --> 00:04:02.310 in marketing, I think the customer experience is kind of informing the customer decision 49 00:04:02.349 --> 00:04:08.949 journey throughout the relationship between the brand and the and the buyer, the consumer. 50 00:04:09.590 --> 00:04:13.099 I like that you tapped there one of those kind of tension points that 51 00:04:13.180 --> 00:04:16.540 I felt in reading the invisible brand, which is this the transparency element, 52 00:04:16.699 --> 00:04:19.899 right, like what's inside the black box? Why am I getting these particular 53 00:04:19.980 --> 00:04:24.370 recommendations? Why am I seeing these particular ads and all of that, and 54 00:04:24.490 --> 00:04:29.009 we will get into that. There's one explicit reference to customer experience in the 55 00:04:29.089 --> 00:04:32.569 book, in those words, and it was around a negative experience with a 56 00:04:32.610 --> 00:04:35.930 fifty percent off sale. Do you want to tell that story just quickly? 57 00:04:38.250 --> 00:04:42.639 Oh boy, yeah, so my family was visiting me. I had an 58 00:04:42.759 --> 00:04:46.199 apartment up in New York City and around Christmas time my family came up and 59 00:04:46.279 --> 00:04:51.519 we did some shopping in the city together and my daughter spied a coat in 60 00:04:51.639 --> 00:04:58.829 the window of a Columbia store and in the meat packing district, I guess 61 00:04:58.910 --> 00:05:03.550 we were, and the kind of near Chelsea market. Anyway, the window, 62 00:05:03.990 --> 00:05:09.220 you know, clearly showed a fifty percent off sign with a rack of 63 00:05:09.339 --> 00:05:12.620 coads. We went in, my daughter tried one on, you know, 64 00:05:12.779 --> 00:05:15.939 retail price on it was like three hundred and fifty dollars, which was more 65 00:05:15.980 --> 00:05:19.500 than I was planning on spending on a single present. And but she said, 66 00:05:19.540 --> 00:05:23.370 she pointed out it was fifty percent off and I thought was still pretty 67 00:05:23.370 --> 00:05:26.170 expensive, but you know, she needs a winner code. And okay. 68 00:05:26.569 --> 00:05:30.810 So we took it up to the cash register and they rang it up and 69 00:05:30.730 --> 00:05:34.689 it was not fifty percent off and I said it's on the rack that says 70 00:05:34.720 --> 00:05:39.240 fifty percent off and and the guy you know set up. Sorry, it's 71 00:05:39.279 --> 00:05:41.800 not in the it's not in the system. I said, you know, 72 00:05:41.879 --> 00:05:45.720 as your manager here, and he's you know, we went through the rigmarole. 73 00:05:46.040 --> 00:05:50.550 Well, I reached out to their online customer service and I took photographs 74 00:05:50.589 --> 00:05:53.709 of it. I said look, you know, this is a coat hanging 75 00:05:53.790 --> 00:05:58.430 on a act that's clearly marked fifty percent off, and I got to say 76 00:05:58.470 --> 00:06:03.459 they're their customer service department failed utterly. You know, they were unable to 77 00:06:03.699 --> 00:06:06.459 help me at all and in fact, they said, you know, you 78 00:06:06.579 --> 00:06:10.980 really need to talk to the store manager at that individual store because we're just 79 00:06:11.100 --> 00:06:14.420 the online store. And I said, well, you know, I talked 80 00:06:14.459 --> 00:06:16.699 to him and he wouldn't honor the sign that was in his own store that 81 00:06:16.819 --> 00:06:20.170 clearly said fifty percent off, and and they said, well, you'll you 82 00:06:20.290 --> 00:06:24.569 really have to talk to him or his regional manager. And I said, 83 00:06:24.769 --> 00:06:27.290 well, who's the regional manager? And they said, I don't know, 84 00:06:28.810 --> 00:06:31.730 I don't know. This is so it just sound like talking to Columbia. 85 00:06:31.769 --> 00:06:35.399 I'm talking to the actual corporation. WHO's the regional manager? Who Do I 86 00:06:35.480 --> 00:06:41.000 askalate this to? I don't know. They literally failed every step of the 87 00:06:41.079 --> 00:06:46.079 way, and so what could have been an opportunity to build a positive customer 88 00:06:46.160 --> 00:06:48.550 relationship. Fifty percent off, you know, drawing a customer in. I 89 00:06:48.629 --> 00:06:51.310 was on the street, I wasn't planning on going into the store. They, 90 00:06:51.509 --> 00:06:55.029 you know, lured me into the store with their sign. They could 91 00:06:55.029 --> 00:06:58.829 have gathered information about, you know, who I was and how I was 92 00:06:58.949 --> 00:07:02.339 responding to their sales and they probably didn't even bother to figure out that I 93 00:07:02.420 --> 00:07:08.819 was angry about the fact that I had been snubbed and that they're advertising had 94 00:07:08.819 --> 00:07:13.579 been deceptive and that the store manager operating their store was, you know, 95 00:07:13.779 --> 00:07:18.850 clearly using false advertising. And so it's an opportunity lost for a company like 96 00:07:18.970 --> 00:07:24.769 Columbia. They lost my business and in fact I have three children and a 97 00:07:24.850 --> 00:07:28.290 wife who no longer shop at Columbia as a result. It was insulting. 98 00:07:28.329 --> 00:07:30.959 It was a, you know, very poor decision on their part and the 99 00:07:31.079 --> 00:07:36.240 fact that they're, you know, their organizational customer service was so bad that 100 00:07:36.319 --> 00:07:41.199 they couldn't even recognize that they'd made a mistake was humiliating for that. I 101 00:07:41.279 --> 00:07:44.750 mean, you know, it's just a blunder for any corporation to go through 102 00:07:44.790 --> 00:07:48.790 life blind to what it's doing and how it's treating consumers. So lots of 103 00:07:48.910 --> 00:07:54.509 opportunities missed and it ended up in a book right and on this show, 104 00:07:54.910 --> 00:07:57.990 on this show all over, and I'm shy, I would guess others, 105 00:07:58.310 --> 00:08:03.540 all over one hundred seventy five dollars, right, right, just so crazy. 106 00:08:03.579 --> 00:08:05.699 When you think about that long term, I just think you just, 107 00:08:05.980 --> 00:08:09.740 you know, your family alone could purchase en x that amount over the next 108 00:08:09.740 --> 00:08:13.250 five years. Oh in on ski season. Right, there you go. 109 00:08:13.610 --> 00:08:16.370 So, anyway, as soon as I saw that word, I always read 110 00:08:16.370 --> 00:08:20.410 a book with a Pencil and I underline things and put things in parentheses. 111 00:08:20.490 --> 00:08:24.009 Periodically I'll mark things in the column. So when I saw customer experience as 112 00:08:24.050 --> 00:08:26.160 like I'm going to ask him about that. So let's let's getting into the 113 00:08:26.199 --> 00:08:31.079 invisible brand very specifically. Let's start at a high level. What are you 114 00:08:31.199 --> 00:08:35.799 addressing in the book from a brand or company perspective? Like what's going on 115 00:08:35.960 --> 00:08:39.919 at a high level from a marketers or salespersons or companies are a brand's perspective? 116 00:08:39.960 --> 00:08:45.309 Yeah, so let's let's first start with that title, the invisible brand. 117 00:08:45.750 --> 00:08:50.669 I was playing off of Adam Smith's wealth of nations, where he coined 118 00:08:50.750 --> 00:08:54.820 the phrase is the invisible hand, this feature of the economy that operates to 119 00:08:56.059 --> 00:09:00.299 create wealth and in society, and I thought, you know, we're really 120 00:09:00.620 --> 00:09:05.460 onto something new, we're experiencing a brand new force in the economy and I 121 00:09:05.580 --> 00:09:09.330 had to give it a name and I thought the invisible advertise or the invisible, 122 00:09:09.889 --> 00:09:13.929 you know, marketer, and I thought what rhymes with hand, and 123 00:09:13.169 --> 00:09:16.970 then it kind of hit me between the eyes. Invisible brand. But the 124 00:09:18.330 --> 00:09:24.090 reference is very much about revealing something that is hidden and I wanted to kind 125 00:09:24.090 --> 00:09:28.240 of pull back the curtain and show people how the technology that they're using through 126 00:09:28.240 --> 00:09:33.399 their phones and their laptops and even their televisions and cars, is being used 127 00:09:33.440 --> 00:09:41.470 by marketers to gather information, personalize information delivery back to the consumer in such 128 00:09:41.509 --> 00:09:46.149 a way that they build a relationship with you so that they can get you 129 00:09:46.710 --> 00:09:52.629 to be more open to their messaging and ultimately figure out how to use artificial 130 00:09:52.710 --> 00:09:58.259 intelligence to leverage that personal interaction to persuade you and to change the way you 131 00:09:58.580 --> 00:10:03.419 act and think and what you buy. And so kind of pulling back the 132 00:10:03.580 --> 00:10:07.289 curtain on that invisible force in our lives was really the purpose of the book. 133 00:10:07.809 --> 00:10:11.129 And it's all right here. I mean you're not talking. I mean 134 00:10:11.129 --> 00:10:15.529 there are there is some you know, future look throughout, but you mean, 135 00:10:15.570 --> 00:10:18.649 this is all very, very present. So from a consumers point of 136 00:10:18.690 --> 00:10:22.279 view, or because we're all customers as well, as you already established with 137 00:10:22.399 --> 00:10:26.320 your story. They're about your Columbia experience. Talk about this a little bit 138 00:10:26.360 --> 00:10:33.759 from the customers perspective. Yeah, so from from the perspective. Most consumers 139 00:10:33.840 --> 00:10:39.029 have this kind of sensation that they're being watched and followed. They recognize that 140 00:10:39.710 --> 00:10:43.389 they've got this device sitting on their counter that listens to them, that they 141 00:10:43.509 --> 00:10:50.299 talked to. So consumers are kind of aware and they increasingly have this awareness 142 00:10:50.340 --> 00:10:56.659 of being surveiled and and even spied upon. I often say there's a fine 143 00:10:56.700 --> 00:11:01.259 line between marketing and espionage, and so where we are today is that consumers 144 00:11:01.340 --> 00:11:07.169 have this kind of sneaking suspicion that they're being manipulate. But what I was 145 00:11:07.289 --> 00:11:11.009 trying to do in the book is to explain exactly how that works and to 146 00:11:11.169 --> 00:11:16.250 equip people with kind of the knowledge that they can think both about the opportunities 147 00:11:16.330 --> 00:11:20.440 that that this technology presents as well as the risks. And one of the 148 00:11:20.799 --> 00:11:24.960 examples, I don't think I wrote it exactly this way in the book, 149 00:11:24.960 --> 00:11:30.120 but it's kind of a simple explanation. Imagine your operating a pet store and 150 00:11:30.720 --> 00:11:33.269 somebody comes to leave their pet with you. You have the right to, 151 00:11:33.629 --> 00:11:37.230 you know, ask for specific types of information. I need to know where 152 00:11:37.230 --> 00:11:39.269 you're going, I need to know how long you're going to be there, 153 00:11:39.309 --> 00:11:43.029 I need to know how to reach you if, you know, fido gets 154 00:11:43.110 --> 00:11:48.299 sick. So there's this sharing of information where the consumer gives up certain data 155 00:11:48.980 --> 00:11:54.139 that the business owner needs in order for them to have a positive relationship. 156 00:11:54.259 --> 00:12:00.419 And consumers for the most part, believe in that kind of information exchange. 157 00:12:00.460 --> 00:12:05.330 Its transparent, it's open, they recognize that there's a value that they're getting 158 00:12:05.370 --> 00:12:07.850 back, and in this case it's the safety of my pet. But where 159 00:12:09.090 --> 00:12:11.690 we are, you know, ready to draw the line is when we move 160 00:12:11.929 --> 00:12:16.480 from using the information the way we expected to be used to doing something else 161 00:12:16.559 --> 00:12:20.200 with it. You know, in the extreme example here would be you know, 162 00:12:20.399 --> 00:12:22.360 you know I'm going to be out of town this weekend, so you 163 00:12:22.480 --> 00:12:26.759 go rob my house. Okay, now we've crossed the creepy line. I 164 00:12:26.840 --> 00:12:31.629 don't want you roaming around in my house and eating my food and, you 165 00:12:31.750 --> 00:12:37.350 know, stealing my stuff because you've been privileged to receive information about my whereabouts. 166 00:12:37.750 --> 00:12:41.750 And I think that for most consumers they sense this intuitively, that there's 167 00:12:41.789 --> 00:12:48.779 this line that business shouldn't cross. But I think where we have to understand 168 00:12:48.899 --> 00:12:52.379 that, you know, the technology has taken us is that we've gone way 169 00:12:52.419 --> 00:12:58.289 faster than regulatory environments have kept up with that we are in a realm where 170 00:12:58.330 --> 00:13:03.490 data is being transmitted about who we are, where we are, what we 171 00:13:03.610 --> 00:13:07.009 do, what we buy, what we think, and that ownership over that 172 00:13:07.450 --> 00:13:15.279 knowledge is something that there's a an active conversation going on today about, you 173 00:13:15.360 --> 00:13:18.000 know, who really owns that data and knowledge, and some people, Tim 174 00:13:18.080 --> 00:13:22.279 Burners Lee, the father of the Internet, are rather the World Wide Web, 175 00:13:22.799 --> 00:13:26.879 has said openly, you know, we need to have a Magna Carta 176 00:13:26.000 --> 00:13:31.830 for privacy, for a personal information, and I think that to a degree 177 00:13:31.909 --> 00:13:37.629 he's right that there needs to be a real serious rethinking of who owns our 178 00:13:37.750 --> 00:13:41.700 data and who owns information about us. Yeah, and we're starting to see 179 00:13:41.740 --> 00:13:46.500 that roll out a little bit. Obviously, you hit on GDPR and the 180 00:13:46.980 --> 00:13:50.419 California law that's in flight. My understanding is that several other states are kind 181 00:13:50.419 --> 00:13:54.659 of in consideration there. But you know, to your point, there's so 182 00:13:54.740 --> 00:13:58.529 much that hasn't been regulated and honestly, I'm you know, I'm a little 183 00:13:58.570 --> 00:14:01.970 bit skeptical. I wouldn't call myself, I had, a glass half empty 184 00:14:03.049 --> 00:14:07.690 type of person, but I would say on average I would not trust companies 185 00:14:07.730 --> 00:14:11.960 with their own specific motives with my data in a completely unregulated environment. The 186 00:14:13.039 --> 00:14:16.480 other interesting layer here is because, and I was happy to hear the way 187 00:14:16.480 --> 00:14:20.559 you describe the way you approach the book, because I think you really delivered 188 00:14:20.639 --> 00:14:22.639 on your own hopes or expectations for it, at least the way you describe 189 00:14:22.759 --> 00:14:24.909 here, which is, you know, peel it back and put it in 190 00:14:26.029 --> 00:14:28.149 common language. In this is how this stuff works. And so the other 191 00:14:28.269 --> 00:14:33.909 thing too, is that that data can then be paired and used and resold 192 00:14:33.990 --> 00:14:37.429 in all these other things and all of a sudden it's just like long gone 193 00:14:37.549 --> 00:14:41.379 genies out of the bottle, the Pandora's boxes open and all this informations out 194 00:14:41.419 --> 00:14:48.340 there and it's being all matched up, and now people have machine have develop 195 00:14:48.379 --> 00:14:52.500 our developing profiles that know me as well or better than myself, and not 196 00:14:52.700 --> 00:14:54.809 only, I'm getting a little bit ahead of the conversation here, not only 197 00:14:56.529 --> 00:15:00.129 predict what I'm going to do, but but prescribe it to me. So 198 00:15:00.289 --> 00:15:05.889 it is something to be sensitive to. Just stay in the spirit of let's 199 00:15:05.889 --> 00:15:09.240 make this all approachable and walk it down. Just give me a quick again 200 00:15:09.360 --> 00:15:13.320 a few terms here. Just give me some quick, lightweight definitions on them. 201 00:15:13.399 --> 00:15:20.000 Artificial intelligence. I started the book off with a Joke I've heard a 202 00:15:20.039 --> 00:15:24.350 few times, which is artificial intelligence is the art of making machines act like 203 00:15:24.549 --> 00:15:30.269 they do in the movies. And of course you know the the movie making 204 00:15:30.309 --> 00:15:35.059 industry portrays. You know, robots that can easily, you know, blend 205 00:15:35.139 --> 00:15:39.539 into society without being detected. I don't think we're there yet. I think 206 00:15:39.659 --> 00:15:43.820 that, you know, we are beyond the turing test and that you know, 207 00:15:43.980 --> 00:15:48.220 a customer Chat Bot engine can pull off being a human being, but 208 00:15:48.299 --> 00:15:52.690 I don't think we've achieved, you know, what we refer to as general 209 00:15:52.929 --> 00:15:58.570 artificial intelligence. Most of the applications of Ai that are working today are narrow 210 00:15:58.649 --> 00:16:04.120 applications. They offer specific solutions to problems that we would normally think of as 211 00:16:04.279 --> 00:16:08.840 being solved by a human but they aren't general in the sense that they don't 212 00:16:08.840 --> 00:16:12.279 solve all problems. They just solve one narrow type. So when I think 213 00:16:12.320 --> 00:16:18.830 of artificial intelligence, I think of it as the process of teaching computers to 214 00:16:18.990 --> 00:16:23.269 solve problems that we would normally think of as being solved by human beings. 215 00:16:23.309 --> 00:16:30.389 And right now the applications of AI are still narrow. They're very sophisticated and 216 00:16:30.549 --> 00:16:37.019 they're super impressive, but they're still fairly narrow in scope. Super Algorithm, 217 00:16:37.340 --> 00:16:44.860 so unlike a mathematical algorithm, computer algorithm is simply a set of instructions that 218 00:16:44.980 --> 00:16:48.610 you follow, and I in the book I talked about you have an algorithm 219 00:16:48.730 --> 00:16:52.769 for waking up in the morning. Your alarm clock goes off, you turn 220 00:16:52.809 --> 00:16:56.289 the alarm off, you swing your feet out of bed and you stand up 221 00:16:56.330 --> 00:16:59.330 and turn on the light or whatever that is. So there's a sequence of 222 00:16:59.409 --> 00:17:03.120 events that you follow that you could consider an algorithm. Well, it's interesting 223 00:17:03.159 --> 00:17:07.799 about algorithms as they can be packed into other algorithms. That little get up 224 00:17:07.799 --> 00:17:11.279 out of bed algorithm can be paired up with a brush your teeth algorithm and 225 00:17:11.400 --> 00:17:15.710 an eat breakfast algorithm and to go to work algorithm, and all of those 226 00:17:15.789 --> 00:17:18.670 can be nested inside a larger algorithm called, you know, my day, 227 00:17:19.190 --> 00:17:23.910 and the my day algorithm could be nested inside an algorithm called by month and 228 00:17:25.029 --> 00:17:29.509 my year. So you can quickly see how algorithms can pair with one another. 229 00:17:29.630 --> 00:17:33.099 They can be nested inside of one another group together to solve problems. 230 00:17:33.220 --> 00:17:37.859 So think of an algorithm. Start by thinking of an algorithm as a set 231 00:17:37.900 --> 00:17:42.220 of instructions for a computer. Follow quick follow up there on Algorithm is again 232 00:17:42.259 --> 00:17:47.690 I'm offering this for the listener who doesn't understand these things, much like myself. 233 00:17:48.250 --> 00:17:52.849 Is there a final rule in a set that basically observe, learn, 234 00:17:52.650 --> 00:18:02.240 optimize so that it's self perpetuating and gets more and more effective efficient? Yes, 235 00:18:02.400 --> 00:18:04.880 when we talk about machine learning, we're really talking about the ability for 236 00:18:06.000 --> 00:18:12.390 machines, on one hand, to detect patterns in data and use either supervised 237 00:18:12.390 --> 00:18:22.029 learning or unsupervised learning to more efficiently recognize those patterns and then ultimately learn how 238 00:18:22.109 --> 00:18:26.390 to change outcomes from those patterns. So if you see, you know, 239 00:18:26.630 --> 00:18:30.619 a shopping experience and you watch the customer decision journey from the top of the 240 00:18:30.660 --> 00:18:33.460 funnel all the way through the bottom of the funnel and you can see where 241 00:18:33.460 --> 00:18:38.259 people drop out, you can gather tens of millions of data points about the 242 00:18:38.339 --> 00:18:42.730 customer experience and you've got sixty variables to, you know, play with, 243 00:18:44.049 --> 00:18:47.809 you can start to actually see how a computer would be much more efficient at 244 00:18:47.849 --> 00:18:53.289 not only detecting patterns in that data but then learning how to actually change the 245 00:18:53.329 --> 00:18:57.359 outcomes. If I tweak this, let me watch what happens as a consumer 246 00:18:57.480 --> 00:19:02.160 moves through the funnel. If I tweak this, let me see what impact 247 00:19:02.240 --> 00:19:07.799 that has and ultimately bend the consumer experience towards more positive outcomes. Whatever your 248 00:19:07.839 --> 00:19:12.190 KPI is, whether it's a conversion are, somebody making a purchase or total 249 00:19:12.309 --> 00:19:18.430 dollars, the computer can look at all of those variables that go into the 250 00:19:18.549 --> 00:19:22.789 customer experience and then, at the end start to see, okay, if 251 00:19:22.869 --> 00:19:26.220 I, you know, do x, this happens. If I do why, 252 00:19:26.700 --> 00:19:30.940 this other thing happens, and I can start to actually bend my campaign's, 253 00:19:30.099 --> 00:19:33.980 my marketing, my customer outreach and all of those touch points with the 254 00:19:34.059 --> 00:19:41.089 consumer to change the outcome. So instead of just thinking of the modern computer 255 00:19:41.289 --> 00:19:45.410 experience as just plotting points on a graph and then drawing a line of best 256 00:19:45.490 --> 00:19:48.009 fit so that you can try to figure out, you know, where the 257 00:19:48.089 --> 00:19:51.490 next point will fall, think of it as a bunch of points on a 258 00:19:51.569 --> 00:19:56.680 graph that the computer recognizes and says, okay, if I want the next 259 00:19:56.759 --> 00:20:00.119 point to fall on this line, I have to do x, Y and 260 00:20:00.200 --> 00:20:04.519 see, and that's prescriptive. The computers starting to think about how to actually 261 00:20:04.559 --> 00:20:11.069 change the outcomes rather than merely predict the outcome. Really good. That was 262 00:20:11.109 --> 00:20:15.069 I'm so glad I asked that follow up question. Another one neural network. 263 00:20:17.630 --> 00:20:22.259 Well, the reference to neural is simply organizing a computer network in the way 264 00:20:22.539 --> 00:20:27.940 that a human brain is organized, and I think that that term is often 265 00:20:29.299 --> 00:20:33.660 a little maybe misleading and it's a you know, we're not actually building human 266 00:20:33.819 --> 00:20:37.450 brains, but what we're trying to do is we're trying to suggest that the 267 00:20:37.609 --> 00:20:42.210 interaction of the data through the network is not following a single linear path, 268 00:20:42.369 --> 00:20:48.769 that there's lots of processes that are happening simultaneously and it is the culmination of 269 00:20:48.970 --> 00:20:55.839 lots of simultaneous processes that is generating answers or outcomes, which makes it more 270 00:20:56.480 --> 00:21:00.440 of a neural network. And when we start stacking neural networks, you know, 271 00:21:00.519 --> 00:21:03.880 we can start to create what we think of as deep learning. We 272 00:21:03.960 --> 00:21:08.390 start to recognize new benefits from the complexity of the systems that were leveraging and 273 00:21:08.829 --> 00:21:15.710 that gives us some really powerful outcomes. Good last one, and this is 274 00:21:15.789 --> 00:21:21.539 a term I believe you created in constructing the book. It captures the personalized, 275 00:21:21.700 --> 00:21:26.779 persuasive ability to learn, the anthropomorphic nature of our the way the machines 276 00:21:27.259 --> 00:21:32.380 interface with us, and that is psychotechnology. Feel free to to kind of 277 00:21:32.420 --> 00:21:34.650 run with this one a little bit talk about the elements of it and how 278 00:21:34.690 --> 00:21:38.609 you arrived at that term. Yeah, in the book I define for key 279 00:21:38.730 --> 00:21:44.049 trends that you just mentioned and I'll try to illuminate them just briefly. The 280 00:21:44.170 --> 00:21:48.160 first that you mentioned and I previously mentioned is the personalization of information. If 281 00:21:48.200 --> 00:21:52.039 you and I were sitting next to each other at the airport and we both 282 00:21:52.079 --> 00:21:55.359 had our laptop so open and we went to the New York Timescom we might 283 00:21:55.440 --> 00:21:56.960 see different ads. You might see ads that are tailored to you, I 284 00:21:57.039 --> 00:22:00.670 might see ads tailored to me. So we're seeing, you know, different 285 00:22:00.750 --> 00:22:04.309 information. Your facebook feed is different than my facebook feed. The news you 286 00:22:04.430 --> 00:22:08.869 consume is tailored to you, customized to your you know, wants, and 287 00:22:10.029 --> 00:22:14.430 increasingly we are seeing information reflect back to us, almost like an echo chamber, 288 00:22:14.829 --> 00:22:18.579 of what we have previously demonstrated an interest in, and that's a real 289 00:22:18.779 --> 00:22:25.740 important fundamental idea is that the machine is now equipped to address you ethan a 290 00:22:25.980 --> 00:22:32.250 you bill in different terms. That's the personalization of information and that's distinct from 291 00:22:32.289 --> 00:22:37.289 the world I grew up in, where a broadcast tower delivered a message to 292 00:22:37.410 --> 00:22:41.569 everyone at the same time. Now computers are developing one on one relationships with 293 00:22:41.730 --> 00:22:47.799 individuals. We are even able to write news copy headlines on the fly, 294 00:22:48.640 --> 00:22:52.359 tailored to you and how you are motivated and what things you like to read. 295 00:22:52.880 --> 00:22:59.109 A second is that persuasion has become a science. We are no longer 296 00:22:59.589 --> 00:23:02.750 six people in a room with a wet finger in the air trying to feel 297 00:23:02.750 --> 00:23:04.349 out which way the wind blows. You know, it's no longer kind of 298 00:23:04.430 --> 00:23:08.630 that that simple focus group testing of messages. We are now at a point 299 00:23:08.990 --> 00:23:15.339 where we can ab test messaging across thousands and even tens of thousands, and 300 00:23:15.380 --> 00:23:19.859 if you consider Google, of giant Focus Group, billions of people and and 301 00:23:21.019 --> 00:23:26.779 the ability to persuade really comes down to defining key performance indicators that can be 302 00:23:26.900 --> 00:23:32.809 tracked, watching what messaging people are exposed to and how they behave, and 303 00:23:32.930 --> 00:23:37.170 then seeing can I change those behaviors by changing the messaging? And the answer 304 00:23:37.210 --> 00:23:41.799 is yes, we can. You know, that is something as simple as 305 00:23:41.319 --> 00:23:45.000 on your facebook APP on your phone, a little number one that pops up 306 00:23:45.400 --> 00:23:51.640 that causes you to think, hope, somebody liked my picture, somebody liked 307 00:23:51.880 --> 00:23:56.150 my post. Well, guess what? We tend to gravitate toward those things 308 00:23:56.430 --> 00:24:00.710 and compulsively click to open that up and see, well, who liked my 309 00:24:02.109 --> 00:24:06.109 who like my facebook post? That's a form of persuasion. You are being 310 00:24:06.349 --> 00:24:11.059 manipulated, you're being changed by that little number one that pops up and the 311 00:24:11.180 --> 00:24:15.220 reward you get is that little drip of dopamine in your brain that makes you 312 00:24:15.259 --> 00:24:18.740 feel like, ah, somebody loves me. Well, that kind of persuasion 313 00:24:18.819 --> 00:24:23.329 is being deployed in marketing. It's being deployed in video games. You know, 314 00:24:23.410 --> 00:24:26.809 we can keep your kids glued to their video game for seventy hours without 315 00:24:26.809 --> 00:24:32.490 going to the bathroom just to, you know, earn the the last piece 316 00:24:32.569 --> 00:24:36.690 of armor in there, you know, for their night in their medieval war 317 00:24:36.849 --> 00:24:41.039 game. So you know, we were really good at persuasion. The next 318 00:24:41.200 --> 00:24:47.480 is that natural language processing is being deployed with machine learning so that we can 319 00:24:47.599 --> 00:24:53.670 now talk to machines that learn how to persuade US using personalized information. So 320 00:24:53.710 --> 00:25:00.390 I kind of blended the last two together. There's the PERSONALIZASIAN information, persuasion 321 00:25:00.430 --> 00:25:04.230 as a science, natural language processing and machine learning all taken together, other 322 00:25:04.869 --> 00:25:11.019 create technology that we're talking to and we have to be aware that the machine 323 00:25:11.019 --> 00:25:17.099 that we're talking to is listening. It's learning about us in order to persuade 324 00:25:17.140 --> 00:25:22.049 US using our own personalized information, and I thought we need a name for 325 00:25:22.130 --> 00:25:25.250 that. We gotta what do we call that? And I thought about it 326 00:25:25.329 --> 00:25:30.690 really hard. That's technology that is operating on US psychologically. What would you 327 00:25:30.769 --> 00:25:36.680 call psychological technology? You call it psychotechnology, or you could even shorten that 328 00:25:36.720 --> 00:25:42.000 if you wanted to, psychotech. And I am committed to that idea that 329 00:25:42.160 --> 00:25:48.160 this is truly something new and unique and I need to be out there explaining 330 00:25:48.279 --> 00:25:52.230 to everybody how it works, because they deserve to know and understand how it 331 00:25:52.589 --> 00:25:56.869 is impacting them. Already. It's already at work changing you and me. 332 00:25:57.829 --> 00:26:02.910 It is, and you've already cited a couple examples of it just in that 333 00:26:03.069 --> 00:26:04.779 explanation, which is really, really good. I think the way folded those 334 00:26:04.859 --> 00:26:08.259 together made a lot of sense to me and I think it'll resonate with folks 335 00:26:08.299 --> 00:26:11.579 that kind of observe these bits and pieces. But you did is such a 336 00:26:11.619 --> 00:26:15.019 nice job pulling it all together into something that we can kind of wrap our 337 00:26:15.019 --> 00:26:18.289 heads around a little bit. So let's go just for the sake of time, 338 00:26:18.329 --> 00:26:23.009 let's let's do a little bit of a go on kind of the ethical 339 00:26:23.049 --> 00:26:26.730 considerations. You already touched on it a little bit. Trust, transparency. 340 00:26:27.329 --> 00:26:30.210 Companies need to be open, but the you know, their whole M is, 341 00:26:30.730 --> 00:26:34.160 how can I use AI to get people to buy more stuff? Right? 342 00:26:34.599 --> 00:26:38.559 And on the other side you have the customers, who you've already you've 343 00:26:38.599 --> 00:26:41.960 already kind of hinted at. This is like, I'm comfortable giving you this 344 00:26:42.119 --> 00:26:48.549 information in this context because it's an appropriate exchange of, you know, value 345 00:26:48.710 --> 00:26:53.069 my valuable information in an exchange for your valuable service or access to this document 346 00:26:53.190 --> 00:26:56.869 or whatever the case may be. I'm comfortable there, but when I get 347 00:26:56.910 --> 00:27:02.059 that little further peek behind the curtain, I get very uncomfortable. I'm creeped 348 00:27:02.099 --> 00:27:04.940 out, you know, I'm turned off, I'm kind of shocked. And 349 00:27:06.019 --> 00:27:10.779 so there's this expectation management function that it, I think, is around opening 350 00:27:10.819 --> 00:27:15.299 up the black box and being more transparent about what's going on and why. 351 00:27:15.460 --> 00:27:19.009 From the company perspective, at the same time, their motivation is to sell 352 00:27:19.089 --> 00:27:22.569 more stuff using AI. And then at a certain point, I'm getting a 353 00:27:22.569 --> 00:27:26.930 little bit farther ahead, here is, you know, you discussed it at 354 00:27:27.289 --> 00:27:32.599 couple different points in the book, this idea that we won't be able to 355 00:27:32.720 --> 00:27:37.079 recognize the machine or even the data scientists don't totally understand what's going on inside 356 00:27:37.079 --> 00:27:41.799 the black box at times, and so even that is a little bit beyond 357 00:27:41.000 --> 00:27:45.630 the company's control at some level. And so just talk about that give and 358 00:27:45.710 --> 00:27:49.750 take and the creepiness factor. But the you know, we like more targeted 359 00:27:49.789 --> 00:27:55.190 ads. Maybe just talk about that given take. Yeah, so, without 360 00:27:55.230 --> 00:27:59.660 getting too far down the kind of the Sci Fi side of this, let's 361 00:27:59.660 --> 00:28:04.339 just talk about the the consumer experience. If you are in customer service or 362 00:28:04.660 --> 00:28:10.099 if you're a business owner, if you're a marketer, I strongly, strongly 363 00:28:10.220 --> 00:28:18.490 encourage you to write this down. It's about persuasion, not coercion or deception. 364 00:28:18.009 --> 00:28:25.450 So simple formula. Most consumers are willing to be persuaded. We are 365 00:28:25.569 --> 00:28:30.680 all willing to be convinced. Convinced me, tell me that your product is 366 00:28:30.799 --> 00:28:37.960 better, but don't trick me into it, don't deceive me and don't do 367 00:28:37.160 --> 00:28:42.670 anything that is coercive, and I think that keeps you on the right side 368 00:28:42.829 --> 00:28:48.390 of the creepy line. I'll define the creepy line a little bit more for 369 00:28:48.509 --> 00:28:53.190 you as you're as you're thinking about this. There was a terrific example of 370 00:28:53.750 --> 00:29:00.140 what I consider the invisible brand at work. A number of years ago target 371 00:29:00.380 --> 00:29:03.779 had a lead scientist who is asked, can you tell us when a woman 372 00:29:03.859 --> 00:29:07.940 is pregnant? Because at a when a woman is pregnant, she makes lots 373 00:29:07.980 --> 00:29:14.769 of decisions about brands and things that she will purchase that last for decades. 374 00:29:15.049 --> 00:29:18.289 She will be you know, she raises her babies with the same kind of 375 00:29:18.769 --> 00:29:22.210 dishwashing to terge at, the same kind of toothpaste, the same kind of 376 00:29:22.849 --> 00:29:26.759 laundry to tergeon. And in the process of making those decisions she makes a 377 00:29:26.839 --> 00:29:30.160 lot of new decisions. He tries a lot of new products during the point 378 00:29:30.400 --> 00:29:36.279 where she's pregnant and then soon after when she has young children. And so 379 00:29:36.599 --> 00:29:41.029 for marketers it's a very strategically important part of a woman's life is to figure 380 00:29:41.029 --> 00:29:42.630 out how do I know when a woman is pregnant? Well, it turns 381 00:29:42.670 --> 00:29:47.549 out that target has a lot of data in their system and from your basket 382 00:29:47.549 --> 00:29:49.509 of goods, of what you're purchasing, they can actually do a pretty good 383 00:29:49.549 --> 00:29:53.819 job of determining when your pregnant. Surprisingly so, and the story goes, 384 00:29:55.019 --> 00:29:57.740 and this is now a famous kind of marketing, oneonone story. They sent 385 00:29:57.740 --> 00:30:02.859 out a mailer to women who were pregnant and one of those mailers went to 386 00:30:02.940 --> 00:30:07.059 a young woman who was sixteen years old and her father received it and was 387 00:30:07.250 --> 00:30:12.450 incensed the target would have the nerve to send his sixteen year old daughter information 388 00:30:12.529 --> 00:30:17.650 about pregnancy. She's too young, of course. And you know, surprise, 389 00:30:18.089 --> 00:30:21.839 it turned out that she was actually in fact pregnant and the algorithms that 390 00:30:21.960 --> 00:30:26.039 target knew it before dad did. And that's not the end of the story. 391 00:30:26.160 --> 00:30:29.960 The end of the story is the fact that target recognized that for that 392 00:30:30.200 --> 00:30:33.920 consumer they had crossed the creepy line. That consumer didn't need to know that 393 00:30:34.240 --> 00:30:37.869 his daughter was pregnant before he did, and the fact that a, you 394 00:30:37.950 --> 00:30:44.150 know, corporation could deduce from the basket of goods that you were purchasing that 395 00:30:44.269 --> 00:30:48.150 your daughter was pregnant was something very startling to that particular individual. And the 396 00:30:48.309 --> 00:30:55.220 learning from that that that target took away is don't be so obvious. So 397 00:30:55.460 --> 00:30:59.660 learning that they they gathered from it was, okay, we're going to put 398 00:30:59.700 --> 00:31:03.650 gas grills and golf clubs into the into the mailer so that it's not all 399 00:31:03.769 --> 00:31:07.970 just baby stuff. And oh by the way, if you're happening, to 400 00:31:07.089 --> 00:31:11.849 look past the gas grills and golf clubs and there's some you know, some 401 00:31:11.970 --> 00:31:15.450 pregnancy stuff in there. That's nice, but but please don't think that we 402 00:31:15.690 --> 00:31:19.039 sent you a pregnancy mailer or a baby mailer. So there was this degree 403 00:31:19.079 --> 00:31:26.200 of obfuscation that they started crafting into their marketing so that it wasn't so obvious 404 00:31:26.319 --> 00:31:30.759 to consumers when they were crossing the creepy line. I think where that leaves 405 00:31:30.839 --> 00:31:36.630 us today is that, as consumers, we are suspicious that we are being 406 00:31:36.869 --> 00:31:41.470 stocked and preyed upon, but we are also suspicious that the corporations are hiding 407 00:31:41.670 --> 00:31:45.630 and masking what they do. It's something I call Google Noia, which is 408 00:31:45.670 --> 00:31:51.779 kind of a combination of Google and paranoid, and this creeping Google noia that 409 00:31:51.900 --> 00:31:56.460 we experience suggest to US somehow that, you know, all of these search 410 00:31:56.579 --> 00:32:00.569 engines and all of these recommendation engines and the ads and everything is really ganging 411 00:32:00.690 --> 00:32:06.170 up on us and and stocking us and persuading us in ways that we don't 412 00:32:06.170 --> 00:32:09.170 understand. And in fact a lot of that is actually happening. That is 413 00:32:09.289 --> 00:32:14.490 the case, and for consumers the trick is you better not let me know 414 00:32:14.690 --> 00:32:20.319 it and and so for for marketers, the simple rule is persuasion, not 415 00:32:20.519 --> 00:32:23.400 coercion or deception, and I think that if you stay on that side, 416 00:32:23.440 --> 00:32:29.599 if you know and recognize the persuasion is fair, consumers are willing to be 417 00:32:29.759 --> 00:32:37.309 persuaded and that you offer a transparent value exchange your data in exchange for these 418 00:32:37.470 --> 00:32:40.670 benefits, that you, as a company, will be more often than not 419 00:32:40.869 --> 00:32:45.380 on the right side of the creepy line. I like it. It's it's 420 00:32:45.579 --> 00:32:50.019 you know, golden rule obviously applies here. Or could you justify this decision 421 00:32:50.019 --> 00:32:52.500 or this behavior to someone you love and respect, like a family member or 422 00:32:52.619 --> 00:32:57.299 close friend? You know, it's easy to sit around and make decisions in 423 00:32:57.420 --> 00:33:00.970 the company's interests inside a closed setting, but to be able to justify it 424 00:33:00.130 --> 00:33:04.329 externally and explain it to people. If you're willing to do that, then 425 00:33:04.329 --> 00:33:07.089 you're probably on the safe side of it. I really love to another that 426 00:33:07.250 --> 00:33:12.289 that that target pregnancy story would like kind of broke into the mainstream, as 427 00:33:12.369 --> 00:33:17.480 did that Google Duplex. The AI assistant scheduling a haircut appointment in the interesting 428 00:33:17.559 --> 00:33:20.799 resolve of getting you did a drive by on that in the book. The 429 00:33:20.920 --> 00:33:25.000 interesting resolve there is that Google ended up based on customer feedback or your peep, 430 00:33:25.160 --> 00:33:30.349 you know, consumer feedback. This idea that the machine will present itself 431 00:33:30.390 --> 00:33:34.869 as a machine acting on behalf of a human. Again, like this transparent 432 00:33:34.910 --> 00:33:38.349 step so as not to act as if like acting as if it's a human 433 00:33:38.390 --> 00:33:40.980 but it's not a human. It's funny. I had a conversation about live 434 00:33:42.059 --> 00:33:45.819 chat and chat bots here on the show and and what the gentleman observed was 435 00:33:45.980 --> 00:33:52.299 that so often the people will ask directly into the chat exchange, are you 436 00:33:52.420 --> 00:33:55.210 a person? You know, like where are you? You know? Are 437 00:33:55.569 --> 00:33:59.450 It? Because people want to know that too. So it's interesting. Even 438 00:33:59.490 --> 00:34:04.809 in the interactions we want to have that level of transparency. What are the 439 00:34:04.970 --> 00:34:07.650 marketing jobs of the future, and I asked this with you know, you 440 00:34:07.769 --> 00:34:13.719 talked about you already mentioned new stories that right themselves, email copy that is 441 00:34:13.800 --> 00:34:19.239 going to optimize itself, adds that create run and optimize themselves. Where does 442 00:34:19.320 --> 00:34:22.559 this leave the marketer when we go more strategic and less tactical, because a 443 00:34:22.599 --> 00:34:27.190 lot of the tactics are knocked down by the machines, which is sensible, 444 00:34:27.230 --> 00:34:30.389 again, putting humans in position to do their best work in partnership where does 445 00:34:30.429 --> 00:34:36.389 that leave the human marketer in x number of years? Yeah, so the 446 00:34:36.469 --> 00:34:43.579 definition I typically apply to marketing is anticipating consumer demand and then finding products that 447 00:34:43.739 --> 00:34:47.739 can deliver on that demand profitably, and I think when you start to unpack 448 00:34:47.940 --> 00:34:52.449 that, that's a pretty sound definition of marketing. That isn't going to change. 449 00:34:52.570 --> 00:34:57.849 What's changing are the tools, as you said, the tactics. I'll 450 00:34:57.889 --> 00:35:04.610 give you one very clear example. That's happening today and I would extol encourage 451 00:35:04.769 --> 00:35:09.280 marketers to take this very seriously. You might remember twenty years ago, you 452 00:35:09.360 --> 00:35:14.760 know, the infancy, the dawn of kind of search and search engine optimization. 453 00:35:15.039 --> 00:35:19.519 Business is really faced with the challenge and that was, do I divert 454 00:35:19.679 --> 00:35:24.469 resources into search engine optimization? Is this important? Is this a fad or 455 00:35:24.550 --> 00:35:28.510 is this something that's going to affect my business for the next, you know, 456 00:35:28.590 --> 00:35:31.070 multi decades? Then, as we know, you know that the end 457 00:35:31.070 --> 00:35:37.059 of that story is that search engine optimization has been critical and those businesses that 458 00:35:37.260 --> 00:35:40.940 chose to invest succeeded and those that chose to ignore it did so at their 459 00:35:40.980 --> 00:35:46.539 own peril. I think we are at a similar inflection point with voice based 460 00:35:46.619 --> 00:35:51.849 interfaces. We are now talking to our cars we're talking to our television as 461 00:35:51.889 --> 00:35:54.329 we're talking to our cell phones, we're talking to, you know, Alexa 462 00:35:54.409 --> 00:36:00.010 and Siri, and for businesses today they're facing a similar challenge that they did 463 00:36:00.050 --> 00:36:05.719 twenty years ago. Is this something worth investing in? Do I make my 464 00:36:05.960 --> 00:36:10.440 business visible, for audible, if you will, through voice based interfaces? 465 00:36:10.679 --> 00:36:14.199 And so I would ask you, if you're a marketer and LEA, you're 466 00:36:14.239 --> 00:36:17.789 listening to this, ask this simple question. Can My products and services be 467 00:36:19.110 --> 00:36:24.630 purchased today through voice? Go over to Alexa and try to find your product 468 00:36:24.989 --> 00:36:29.989 through Alexa. See if Ciri can locate your business, see if Ciri can 469 00:36:30.429 --> 00:36:35.659 identify the products that you have available for sale and, more importantly, can 470 00:36:35.699 --> 00:36:40.099 you actually make the purchase using voice, because there are a lot of products 471 00:36:40.179 --> 00:36:45.380 that are already being sold using voice. I can sit down in my living 472 00:36:45.420 --> 00:36:47.489 room and I can say, you know, recommend a scary movie in My 473 00:36:47.650 --> 00:36:52.690 TV will pull up scary movies and I can select when. All using voice. 474 00:36:52.090 --> 00:36:57.010 That's changing things. You're driving in your car and you say in a 475 00:36:57.090 --> 00:37:01.760 directions to the nearest Thai restaurant. That's using voice to purchase things. Increasingly, 476 00:37:02.199 --> 00:37:07.079 we are spending money with our mouths. It's easier to spend money with 477 00:37:07.199 --> 00:37:10.639 our mouths that our fingers at this point, and for businesses who are really 478 00:37:10.760 --> 00:37:15.150 thinking hard about where things are going, you've got to recognize that this is 479 00:37:15.230 --> 00:37:20.989 an opportunity for you to either capture market share or get left behind. And 480 00:37:21.429 --> 00:37:27.550 why do I bring up voice? Voice is the consumer facing edge of artificial 481 00:37:27.630 --> 00:37:31.659 intelligence at some of our world's largest and most valuable companies. Think about the 482 00:37:31.780 --> 00:37:37.500 companies that you think of as the world's most valuable brands. Probably on that 483 00:37:37.659 --> 00:37:42.900 list, you're going to say, is apple, it's Microsoft, it's certainly 484 00:37:42.940 --> 00:37:47.489 Amazon. Well, when you think about those and Google, you're naming companies 485 00:37:47.570 --> 00:37:54.809 that have voice based ecosystems. The most valuable brands in the world have Siri 486 00:37:55.170 --> 00:38:01.880 and Alexa and Google assistant and Cortana. These are voice based systems that human 487 00:38:01.960 --> 00:38:07.119 beings are interacting with at increasing ease. You know what I think about? 488 00:38:07.119 --> 00:38:10.079 A story that I tell in the book? My neighbor's four year old son 489 00:38:10.320 --> 00:38:15.190 was able to get Alexa to play music for him and I was thinking, 490 00:38:15.550 --> 00:38:19.469 you know, this is really truly amazing, because a four year old hasn't 491 00:38:19.469 --> 00:38:23.150 necessarily nerd learned how to read they can't now the gate graphical user interface, 492 00:38:23.269 --> 00:38:31.059 but here he is easily using a voice based interface to navigate a complex environment, 493 00:38:31.659 --> 00:38:35.579 in this case Alexa, and I thought, you know, that's really 494 00:38:35.659 --> 00:38:39.219 impressive. Voice is something more innate, it's something deeper in us than reading. 495 00:38:39.300 --> 00:38:42.969 We learned to speak when we're a year, year and a half, 496 00:38:43.449 --> 00:38:45.889 whereas we don't learn to read until we're maybe four, five, six years 497 00:38:45.889 --> 00:38:52.090 old. And so that interface, that voice interface, is something that marketers 498 00:38:52.409 --> 00:38:55.559 today have to start grappling with. What does it mean to your business to 499 00:38:55.639 --> 00:39:01.719 have consumers shifting their attention to an interface which is all voice based? So 500 00:39:01.840 --> 00:39:05.840 these are some of the challenges that marketers face. To bring it back to 501 00:39:05.880 --> 00:39:10.190 your question again, the strategic role of marketing hasn't changed, but the tools 502 00:39:10.230 --> 00:39:16.030 and tactics that are available as changing extremely rapidly and marketers need to be on 503 00:39:16.150 --> 00:39:21.630 top of those changes and learn to adapt. Excellent. I have a several 504 00:39:21.710 --> 00:39:23.940 more questions that I will not be asking you. I again I found the 505 00:39:23.980 --> 00:39:30.260 invisible brand to be fun, easy and very interesting and informative, and again 506 00:39:30.300 --> 00:39:34.099 I recommend it highly to to anyone that's made it this far into the interview. 507 00:39:34.099 --> 00:39:37.420 You know there's so much more in there that we can't pack into this 508 00:39:37.579 --> 00:39:43.250 conversation. So will end here where I always end, which is on our 509 00:39:43.449 --> 00:39:46.889 number one core value at bombombing here on the show, which is human relationships. 510 00:39:47.650 --> 00:39:51.489 So I would love to give you the chance to incor mentioned someone who's 511 00:39:51.489 --> 00:39:54.840 had a positive impact on your life or your career. And counter to where 512 00:39:54.840 --> 00:39:59.440 we started with that retail story, you had maybe give a mention to a 513 00:39:59.559 --> 00:40:02.320 company that you really appreciate a respect for the type of experience they're delivering for 514 00:40:02.480 --> 00:40:07.630 you as a customer. Well, I would be a fool not to thank 515 00:40:07.789 --> 00:40:10.110 the folks that helped me write the book. You know, one of the 516 00:40:10.150 --> 00:40:15.110 things about writing a book is that it is not a solitary experience. When 517 00:40:15.110 --> 00:40:17.550 I got started, I thought this is just me and a typewriter and I 518 00:40:19.070 --> 00:40:22.380 thought I had to like lock myself in a room and not, you know, 519 00:40:22.500 --> 00:40:25.619 peek out. But in the acknowledge riots in the book I listed a 520 00:40:25.659 --> 00:40:30.099 whole Bunch of folks, but very specifically I got bogged down in the writing 521 00:40:30.139 --> 00:40:35.929 process. I recognize that I don't have the temperament personality to be somebody who 522 00:40:35.929 --> 00:40:38.449 can just, you know, knock out eight hours of writing every day until 523 00:40:38.449 --> 00:40:42.889 a book is finished. That I'm you know, I find moments, flashes 524 00:40:42.929 --> 00:40:45.409 of inspiration where I'll write you three, four, five pages and then it 525 00:40:45.409 --> 00:40:50.039 might be a week or two before I get involved with it again. And 526 00:40:50.840 --> 00:40:53.519 I ended up working with a researcher, felon in Darren, who helped me 527 00:40:54.039 --> 00:40:59.199 at a level that I you know, really it unlocked my ability to get 528 00:40:59.320 --> 00:41:02.719 book done because, instead of dreading digesting a, you know, a thirty 529 00:41:02.760 --> 00:41:06.269 page study, I could hand it to him and say, you know what, 530 00:41:06.510 --> 00:41:08.590 I think this is important, I think this is something that we should 531 00:41:08.590 --> 00:41:12.389 include, but I don't want to, you know, spend a whole chapter 532 00:41:12.510 --> 00:41:15.230 on it. Maybe if you could give me two paragraphs and he would do 533 00:41:15.349 --> 00:41:19.739 the drudgery of digesting that thing and feeding me back to to two paragraphs that 534 00:41:19.780 --> 00:41:23.300 I could easily staple in or, you know, kind of mortar into the 535 00:41:23.420 --> 00:41:29.099 bricks of this larger structure. And at first I thought this is cheating, 536 00:41:29.219 --> 00:41:31.099 this is too easy, but then I realized it doesn't. You know, 537 00:41:31.219 --> 00:41:36.250 you've got to figure out what your own faults are, what your own weaknesses 538 00:41:36.369 --> 00:41:38.650 are, and you've got to be willing to reach out and get help and 539 00:41:38.889 --> 00:41:43.250 so I owe a debt of gratitude to everybody who helped me with the book. 540 00:41:43.610 --> 00:41:46.159 To the second part of your question, who's doing it? My default 541 00:41:46.199 --> 00:41:52.159 answer here is Amazon, and I say that admiringly but also with a degree 542 00:41:52.199 --> 00:41:58.199 of caution. And the admiring is that Amazon has figured out how to connect 543 00:41:58.519 --> 00:42:01.230 the top of the funnel and the bottom of the funnel in a unique way 544 00:42:01.309 --> 00:42:07.070 that facebook and Google can't, and that is that they plant the seeds at 545 00:42:07.110 --> 00:42:08.590 the top of the funnel. They, you know, have that ability to 546 00:42:08.750 --> 00:42:14.630 plant the ideas and to see the market with people who bought this also bought 547 00:42:14.670 --> 00:42:17.539 this. You know you might like this, and in fact they've made tremendous 548 00:42:17.659 --> 00:42:22.980 in roads in digital marketing in terms of the dollars that they're bringing in, 549 00:42:23.539 --> 00:42:29.179 which is very impressive. But they also have something that Google and facebook don't, 550 00:42:29.420 --> 00:42:31.530 which is the cash register. Of course, facebook and Google have to 551 00:42:31.690 --> 00:42:36.969 rely on third party data, but here we have a company, Amazon, 552 00:42:37.329 --> 00:42:39.570 that is the cash registry. You can actually make the purchase right there, 553 00:42:39.809 --> 00:42:45.360 and so what Amazon is doing is their leveraging artificial intelligence to connect, to 554 00:42:45.840 --> 00:42:52.960 create Attu aribution between what you bought and what you experience through the customer experience, 555 00:42:53.559 --> 00:43:00.550 by understanding algorithmically the steps you took along your customer experience. Through their 556 00:43:00.670 --> 00:43:07.710 technology, they're getting better at changing and and molding your purchase behavior, and 557 00:43:07.869 --> 00:43:15.059 that's what's making them so successful is their application of artificial intelligence to the problem 558 00:43:15.539 --> 00:43:21.179 of attribution. And when I say that the attribution problem is by definition, 559 00:43:21.260 --> 00:43:24.500 it's figuring out to what do I attribute this purchase? You know, you 560 00:43:24.619 --> 00:43:28.530 bought a radio ad, you bought a TV Ad, you bought a newspaper 561 00:43:28.610 --> 00:43:31.889 ad and I have no idea which one of those caused you to walk in 562 00:43:32.090 --> 00:43:38.530 today and buy dog food. But Amazon can watch that entire experience through their 563 00:43:38.690 --> 00:43:45.639 portal, and I'm talking about through their movies and through their music and through 564 00:43:45.039 --> 00:43:49.599 all of the things that you're doing when you interact with the range of you 565 00:43:49.679 --> 00:43:53.000 know Amazon prime and all of the you know all the products that they're selling. 566 00:43:53.159 --> 00:43:58.869 You know they are a market place that includes a lot of things that 567 00:43:59.030 --> 00:44:04.510 you wouldn't traditionally think of as customer experiences, and they're able to weave all 568 00:44:04.630 --> 00:44:10.019 that together algorithmically to make observations about your behaviors what you will buy next. 569 00:44:10.699 --> 00:44:17.579 That companies like facebook and Google can't see. So they've really applied artificial intelligence 570 00:44:17.659 --> 00:44:22.420 to better understanding the customer experience and I would have to cite them as kind 571 00:44:22.420 --> 00:44:27.329 of my you know, kind of top company to watch in the space. 572 00:44:27.929 --> 00:44:30.409 Great Call in a great breakdown there. I mean just folding, and I 573 00:44:30.449 --> 00:44:35.369 didn't think about it this way, but folding in what music I'm listening to 574 00:44:35.530 --> 00:44:38.599 and how often, what movies and TV shows I'm watching through prime, what 575 00:44:38.719 --> 00:44:43.000 I'm buying at a whole foods market through the APP, you know, all 576 00:44:43.039 --> 00:44:46.320 the just a personal profile they can build on me is really, really interesting. 577 00:44:46.360 --> 00:44:50.960 Besides obviously going to order this, that or the other thing, you 578 00:44:51.039 --> 00:44:54.110 know, books and whatever else, through the website directly. There's so much 579 00:44:54.190 --> 00:44:58.349 of a profile they can build. I'm going to add one shout out. 580 00:44:58.389 --> 00:45:02.269 The gentleman who brought the two of us together today is Douglas Burdette, Marketing 581 00:45:02.309 --> 00:45:07.619 Artillery and the marketing book podcast. We were both guests on his show as 582 00:45:07.699 --> 00:45:10.500 authors of books that are relevant to marketers and marketing. So shout out to 583 00:45:10.539 --> 00:45:14.900 Douglas. Thanks for bringing us together. Thank you so much for your time 584 00:45:15.019 --> 00:45:19.019 here on the show today. I enjoyed it very much and continued success to 585 00:45:19.059 --> 00:45:21.969 you with folks want to follow up on this. They want to obviously order 586 00:45:22.050 --> 00:45:23.809 the book or connect with you. What are some ways that people can take 587 00:45:23.889 --> 00:45:30.809 this conversation step farther? The simplest thing to do is say Alexa, order 588 00:45:30.090 --> 00:45:36.800 the invisible brand by William Ammerman and it will arrive at their doorstep tomorrow morning. 589 00:45:37.159 --> 00:45:39.440 But if they're not willing to do that, they can simply go to 590 00:45:39.639 --> 00:45:45.119 my website, which is double you for William Ammerman, a m erm a 591 00:45:45.320 --> 00:45:50.510 andcom, and there they can find out or about me and about the book. 592 00:45:51.230 --> 00:45:52.989 Excellent. Thank you again so much for your time. Well done on 593 00:45:53.190 --> 00:45:57.750 the book and I just really appreciate what you shared here. Thank you so 594 00:45:57.869 --> 00:46:02.309 much, Ethan. Great work. If you found this conversation interesting and valuable, 595 00:46:02.550 --> 00:46:07.579 I know that you'll enjoy his book the invisible brand. And if you're 596 00:46:07.619 --> 00:46:12.260 thinking about how to put your humans in the best position to win inside your 597 00:46:12.380 --> 00:46:17.179 company, be sure to check out rehumanize your business. How personal videos accelerate 598 00:46:17.219 --> 00:46:23.489 sales and improve customer experience. You can learn more about it by visiting Bombombcom 599 00:46:23.969 --> 00:46:31.489 forward book. That's bomb Bombcom book, or you can search for humanize your 600 00:46:31.530 --> 00:46:36.480 business at Amazon. My name is Ethan Bute and thank you for listening to 601 00:46:36.599 --> 00:46:43.800 the BB growth show. I hate it when podcasts incessantly ask their listeners for 602 00:46:43.960 --> 00:46:46.869 reviews, but I get why they do it, because reviews are enormously helpful 603 00:46:46.869 --> 00:46:50.989 when you're trying to grow a podcast audience. So here's what we decided to 604 00:46:51.030 --> 00:46:53.630 do. If you leave a review for be tob growth and apple podcasts and 605 00:46:53.829 --> 00:46:59.230 email me a screenshot of the review to James at Sweet Fish Mediacom, I'll 606 00:46:59.269 --> 00:47:01.780 send you a signed copy of my new book, content based networking, how 607 00:47:01.820 --> 00:47:06.019 to instantly connect with anyone you want to know. We get a review, 608 00:47:06.059 --> 00:47:07.219 you get a free book. We both win.