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Speaker 1: You're listening to Math and Magic production of I Heart Radio.

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Speaker 1: The scientific laws which are they're not laws like boushaltons,

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Speaker 1: the laws that this is the way the world behaves,

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Speaker 1: so you can make predictions. I think they get wonderful guidance. Hi,

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Speaker 1: I'm Bob Pittman. Welcome to this special episode of Math

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Speaker 1: and Magic, Stories from the Frontiers and Marketing. In this episode,

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Speaker 1: my teammate at I Heeart Media are rather Spectacular CMO

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Speaker 1: and former Gasto Math and Magic Yale Trouberman is going

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Speaker 1: to do a special marketers focused interview with one of

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Speaker 1: the world's great marketing thinkers and researchers, Byron Sharp. He's

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Speaker 1: a genuine marketing guru and he is the director of

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Speaker 1: the Ahremberg Bass Institute and a Professor of Marketing Science

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Speaker 1: at the University of South Australia. His approach is best

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Speaker 1: captured by the view that to break through to the

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Speaker 1: frontier of any field, first you have to navigate the

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Speaker 1: fog of conventional wisdom, the established group think that says

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Speaker 1: these are the rules because this is the way it's

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Speaker 1: always been done. Byron had the intuition to question accepted

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Speaker 1: marketing wisdoms and chart a new path. Born and raised

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Speaker 1: on a sheep farm outside of Auckland, New Zealand, Sharp

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Speaker 1: partners the magic of serendipity. Early in his career. He

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Speaker 1: was a marketing manager who, despite an early aversion to academia,

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Speaker 1: ended up working for an academic institution, the University of

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Speaker 1: Southern Australia. After determining that the business school there was

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Speaker 1: underperforming due to a strategy error, Sharp trusted his gut,

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Speaker 1: took a left turn, and here's where the math comes in.

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Speaker 1: He decided to apply rigorous testing methods to study buyer

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Speaker 1: behavior in a field he would help develop the science

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Speaker 1: of marketing. His discoveries led him to author a surprise bestseller,

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Speaker 1: widely considered one of the most influential marketing books of

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Speaker 1: the last fifty years, How Brands Grow and It's built

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Speaker 1: on his learnings. As the head of the Ahrenberg Bass Institute,

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Speaker 1: the world's largest center for research in the mark marketing

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Speaker 1: at the same University of Southern Australia where he started

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Speaker 1: as a marketing manager, Byron's research provides a wealth of

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Speaker 1: insight on the range of industry topics, including one near

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Speaker 1: and dear to me. Best Practices for CEOs around finding

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Speaker 1: the right CMO. Byron says, the best cmos of the

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Speaker 1: folks who are laser focused on the business needs and

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Speaker 1: the big goals. And in my experience this advice is

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Speaker 1: spot on. In fact, Gail has excelled in her role

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Speaker 1: at I Heart because of her laser focused, goal oriented approach.

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Speaker 1: So time for me to pass the mic over to

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Speaker 1: Gail to lead this conversation with Byron on this evidence

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Speaker 1: based expertise on how brand growth actually works. Marketer to

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Speaker 1: marketing guru. Here's Gale and Byron. Thank you, Bob, Byron,

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Speaker 1: I'm excited to be here with you. Before we get

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Speaker 1: into marketing science and growth, Bob always starts as interviews

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Speaker 1: by giving listeners a picture of you in sixty seconds.

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Speaker 1: Are you ready? I'm ready early riser or night out?

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Speaker 1: Have a later offer my Chisenhun Coker PEPSI I live

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Speaker 1: in a current country. Where's that? You know? The stats?

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Speaker 1: Mac PC, Matt Twitter or Instagram, Twitter, CEO or c MO.

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Speaker 1: Well that's an interesting Christian. I'm not gonna be pissing,

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Speaker 1: but I guess well near in invests. You know, I'm CEO,

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Speaker 1: not see bring your fault springing Becausan is coming call

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Speaker 1: or text taste. It's gonna get a little bit harder.

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Speaker 1: So the smartest person, you know, it's not a prison.

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Speaker 1: I think I have and you would have to be, Andrew.

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Speaker 1: You're big technology. You can't live without my Santa Sun

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Speaker 1: PROJECTA first job. My first job was actually a Rando

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Speaker 1: send a Minshapa roller Coast operator. Oh wow, secret talent

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Speaker 1: be at Johnson. What are you reading, watching, or listening

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Speaker 1: to right now? I've just finished watching the same man

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Speaker 1: on Netflix, Guilty Pleasure, my wine cell are okay? From here,

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Speaker 1: We're gonna get into why we're here today. In your

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Speaker 1: seminal book How Brands Grow, which has just been the

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Speaker 1: must read bible of marketing in so many ways. You know,

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Speaker 1: I think the major laws of marketing that you've outlined

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Speaker 1: and How Brands Grow, it's probably one of the most

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Speaker 1: underrated or misunderstood marketing laws. What is it really that

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Speaker 1: you think many marketers are just still getting wrong even

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Speaker 1: though you've given them this plaint book. Oh no, I

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Speaker 1: mean not just terribly impressive. I think the profession is

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Speaker 1: terribly imprisson But we are many ways, like so many

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Speaker 1: other disciplines. I used the medical analogy in my book

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Speaker 1: medicine used to be absolute rubishing stakes. You short people's

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Speaker 1: loves in spite of its being well educated and well

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Speaker 1: in teaching and believing that that we was doing right.

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Speaker 1: I used to say I started in PR. It's when

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Speaker 1: I used to say all the time, when people were

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Speaker 1: you know, in that exaggerated marketer fear moment, it was like,

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Speaker 1: it's PR, not R. It's okay, it's gonna be okay.

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Speaker 1: That's true. And particularly people who were really big brands,

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Speaker 1: have established meeting, physical availability and means of nots can't

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Speaker 1: really do that much damage. But there it lies also

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Speaker 1: the problem, and that they can be doing a lot

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Speaker 1: of things that are wrong, but they don't realize they're

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Speaker 1: wasting their time on trivial issues that really aren't kind

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Speaker 1: of build the value of the organization. Yeah, before we

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Speaker 1: go deeper up, we usually dig a little bit into

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Speaker 1: your early life so we'll get a little more sense

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Speaker 1: of who you are if we travel back in time.

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Speaker 1: I read that you grew up any sheep farm outside Auckland. Yes,

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Speaker 1: how about painting a quick picture of your childhood? Well,

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Speaker 1: it was quite ideal, like in the wential great country

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Speaker 1: school my mom was a teacher who several times the years,

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Speaker 1: which is a very good teacher, I think, into a

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Speaker 1: very large high school with no academic pretensions at all.

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Speaker 1: It was quite good though, because you know, I studied

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Speaker 1: well if humanities history and remember an art history. There

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Speaker 1: are only two of us in the class until the

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Speaker 1: other day left in the final year, so he had

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Speaker 1: one on one teaching, which was pretty good. That's amazing.

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Speaker 1: But I didn't want to be an academic, and if

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Speaker 1: you're going to be a history you end up in

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Speaker 1: an academic or something. So I was a business degree.

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Speaker 1: I was pretty put off when I studied the management classes,

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Speaker 1: which I thought that terribly pseudo academic. I love the

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Speaker 1: marketing classes because they talked about customers and the reason

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Speaker 1: why firms existed, making products, working out what you would

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Speaker 1: tell to you know, there's a eighteen year old. I thought,

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Speaker 1: this is a business. This is what I wanted to learn.

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Speaker 1: I knew on accounting and things like that, but I

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Speaker 1: wanted to know how businesses work, and the marketing classes

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Speaker 1: seemed to do that. So that's the first sort of

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Speaker 1: serendipitous all into marketing, and then the other one is,

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Speaker 1: as Bob mentioned, I ended up being a marketing manager

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Speaker 1: for the commercialization company of the university, and that was

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Speaker 1: actually really very useful because, you know, as a market

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Speaker 1: PRIs interesting to do as you go through the books

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Speaker 1: and see where the sales are coming from. And you know,

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Speaker 1: much to my surprise, the business schools rather ship and

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Speaker 1: it was all the revenue was coming into. It was

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Speaker 1: the chemical technology and pharmacists, and the Business school was

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Speaker 1: just selling you know, short versions of its courses and things.

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Speaker 1: The only futures if you make discoveries. The real world

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Speaker 1: wants discoveries, and you've got to do that, got to

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Speaker 1: do research, and so well, you know, in the rest

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Speaker 1: is history. So how did the idea of an institute

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Speaker 1: that focuses on research about marketing actually come about? Oh? Well,

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Speaker 1: that was easy. We were marking people, so we're supposed

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Speaker 1: to do research on that. But the I think the

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Speaker 1: odd thing was we pretty low respect for particularly top

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Speaker 1: American journals. They seemed to be just trivial questions, either

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Speaker 1: showing off long words and the sort of humanities orientered

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Speaker 1: marketing ones, you know, the general consumer research and things,

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Speaker 1: or showing off statistics and obscuring findings. So again it's

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Speaker 1: been inspired by those sort of Victorian scientists who actually

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Speaker 1: got out and got their hands to look to the

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Speaker 1: real world and collected real data and didn't try to

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Speaker 1: obscure the data was ridiculously over fitted models and things.

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Speaker 1: And so I started a journal which is about empirical generalizations.

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Speaker 1: You know, we're doing replications and extensions to see does

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Speaker 1: it hold in winter as a hold in summer? Does

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Speaker 1: a hole in this country? Is it for fast growing rands?

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Speaker 1: Is low growing rands? That sort of replication work, which

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Speaker 1: is the major journals at the time, just did not

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Speaker 1: touch that. That always have that new. Everything has to

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Speaker 1: be new. So the basic work of science wasn't being done.

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Speaker 1: And someone suggested to me, you should ask Andrew Ainberg

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Speaker 1: to be on the editorial board. And it knows is

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Speaker 1: he still alive of and do oh yes, well all right,

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Speaker 1: Andrew any broke back. Immedia is amazing, that's what creates

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Speaker 1: the best. But well, we wanted to not be broken

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Speaker 1: both sides of the Atlantic. So Frank Bass also it

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Speaker 1: was a great proponent of you know, he had the

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Speaker 1: view that we can make the marketing's real world science

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Speaker 1: studies the real world. You should be able to find

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Speaker 1: law like patterns just like everyone else has and we have.

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Speaker 1: One of my favorite things that you talk about is

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Speaker 1: the importance of open mindedness in marketing, right, this idea

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Speaker 1: of science and letting the data lead you any marketing

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Speaker 1: suppositions that you actually thought were right and then we're

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Speaker 1: proven untrue. But started dawning on me that the idea

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Speaker 1: of being differentiated will did not fit with some of

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Speaker 1: the scientific laws, like like couple of jeoparty, I mean,

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Speaker 1: that shouldn't happen. You should have you know, two grands

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Speaker 1: that are differentiated away from the others, that they're sharing

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Speaker 1: more with each other but way less with the others.

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Speaker 1: So yeah, we did some studying and compared patterns ex

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Speaker 1: entublication of purchase with the partial map data and you

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Speaker 1: know the perceptual map data which you can predict right,

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Speaker 1: you know, the high premium brands clustered together and the others.

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Speaker 1: This is for the department stores. When you looked at

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Speaker 1: the actual shopping, the low price and the high price

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Speaker 1: were sharing. Was than you'd expect. And then suddenly we

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Speaker 1: got out an actual map, a map map, geographical map,

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Speaker 1: and then oh it's obvious, it's where the stores are.

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Speaker 1: You realize that geography is a way bigger driver if

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Speaker 1: you're going to go buy a toaster or somebody can

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Speaker 1: buy it or either one and young ruberkan had was

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Speaker 1: part of the cantor the two people to be studied

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Speaker 1: track of things, and they kind of gave us their

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Speaker 1: whole data. Yeah, they had a perceived differentiation measure which

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Speaker 1: had be never been done in academia. Academics always infod

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Speaker 1: differentiation from perceptible maps or that you know, complicated things.

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Speaker 1: This actually just directly ask people in multiple ways, you know,

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Speaker 1: questions like you could just take it or not? You know,

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Speaker 1: it's just been different, is it unique? You know? And

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Speaker 1: schools are really really low, really love so even regular

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Speaker 1: buyers of something like two thirds of Apple users wouldn't

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Speaker 1: even take any of those things. Wow, and this is

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Speaker 1: what the real world is. Mind blowing right, Just that

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Speaker 1: surprises even me. And I was chief creative officer at

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Speaker 1: Microsoft for a while, so competing with Apple was We've

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Speaker 1: been of my existence quite sometime. People know that, you know,

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Speaker 1: the mecan dash is built on a Unix operating system,

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Speaker 1: you know, PCs based on that. And then I realized,

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Speaker 1: I thought about my parents and if I see it. Actually,

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Speaker 1: then let's say what's an operating system exactly exactly, and

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Speaker 1: they'd say, you know, we've got this map bar. You

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Speaker 1: told us to buy this map bar. We store our

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Speaker 1: photos on, and we do email, and we serve the web,

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Speaker 1: you know, And is that different? No, it's not different.

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Speaker 1: All the computers do that. Yes, the real world when

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Speaker 1: you realized that, Okay, the reason the scientific rules are

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Speaker 1: like that is because consumers they don't terribly see huge that,

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Speaker 1: you know, they do sometimes they know it Ferrari is

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Speaker 1: not half that you don't need to talk to day

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Speaker 1: to know. They see a lot of brands is in

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Speaker 1: the change, and they don't know much about the brands

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Speaker 1: they're not buying. We're so enamored of our brands, right.

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Speaker 1: We spend so much time in the data and thinking

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Speaker 1: about all the nuances, and we think that translates into

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Speaker 1: the real world. People are just like, what's on the shelf?

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Speaker 1: How much is it? What's convenient? Yeah, and we know

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Speaker 1: all about our competitors and things. But you know, if

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Speaker 1: someone banks with well Sargo and you asked them, what's

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Speaker 1: Bank of America? Like there, I don't know Stargo. Yeah,

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Speaker 1: it's so true. In as marketers. Right, I can tell

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Speaker 1: you all the nuances of first brands superentiation, and they

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Speaker 1: go they just see big banks. Yeah, exactly. Your book's

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Speaker 1: been out for a dozen years, for two years. Now,

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Speaker 1: what are you most proud of that you accomplished with

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Speaker 1: our brands grown? I guess that so many people have

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Speaker 1: brought it and read it, that's a good sign. Yes,

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Speaker 1: I mean some of the earliest findings of the Institute

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Speaker 1: and our advisory board members who are all you know

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Speaker 1: cmos of corporations told us to write it because they

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Speaker 1: needed a book to explain to the CFO and the

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Speaker 1: CEO what they were trying to achieve was marketing is

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Speaker 1: they're trying to move marketing to be evidence based, and

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Speaker 1: there was some for the first time of real evidence

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Speaker 1: behind it. So on that goal. I mean, I think

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Speaker 1: it has been useful, but to transform a big corporation

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Speaker 1: takes off lot of work and talk about it any

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Speaker 1: Bruce McCole, who is probably one of the most famous

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Speaker 1: in starting with the gene at Mars, he still says,

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Speaker 1: this gets forward, one step back, you know. Yeah, more

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Speaker 1: a math and magic right after this quick break, welcome

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Speaker 1: back to math and magic. Let's hear more now from

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Speaker 1: the conversation between Gail Troubleman and Byron Sharp. Some of

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Speaker 1: the criticism of your work was that it eliminates creativity

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Speaker 1: or what we Mathew Magic called the magic of marketing.

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Speaker 1: Why do you think people feel that way or why

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Speaker 1: do you think that completely misses the point of the book.

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Speaker 1: I used the example of the architecture of the book,

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Speaker 1: that it is a wonderful creative people, but they slept

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Speaker 1: build buildings that they can hand out. It's an engineer

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Speaker 1: and they going to stay out. Yes, and so the

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Speaker 1: scientific laws, which are the not laws like dur Shart laws,

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Speaker 1: their laws that this is the way the world. Perhaps,

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Speaker 1: so you can make predictions. I think they'll give you

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Speaker 1: wonderful guidance. I remember creative saying to me a blank

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Speaker 1: sheet of paper was a very scary thing. Yeah, so

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Speaker 1: doing research, knowing what your distinctive assets are and then

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Speaker 1: saying that it's not optional. We used to what we

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Speaker 1: now call distinctive assets used to be called creative devices,

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Speaker 1: and they were sort of optional, you know, like, well

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Speaker 1: stop using for a whole decade, stop using the M

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Speaker 1: and MS characters because someone thought, oh, you know what,

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Speaker 1: all these say about chocolate, you know, but then we say, no,

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Speaker 1: we must use those. And I think to creators, that's

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Speaker 1: really useful. It's like, okay, right, so I'm doing an

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Speaker 1: M and NZ it will be m ends characters. Right.

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Speaker 1: Marketers are so invested in their brands and all this

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Speaker 1: detail and all the nuance and personifying our brands that

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Speaker 1: I think sometimes when we get bored. You know, I've

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Speaker 1: seen so many times where people, you know, new new leadership,

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Speaker 1: new management, new team agencies, and people just want to

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Speaker 1: do new things. It's human nature. They get bored with

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Speaker 1: the same things, and and it's not necessarily because they're

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Speaker 1: not working. The duration of a campaign now it's got

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Speaker 1: to be so much shorter than the days of sort

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Speaker 1: of iconic I mean, which are goes to your whole

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Speaker 1: point of mass marketing, right. You know, one of the

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Speaker 1: things we talked a lot about it, I heart because

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Speaker 1: we reached nine out of ten US consumers just on

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Speaker 1: broadcast radio, and then we have our podcasting and our

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Speaker 1: events businesses, which are also bidding. But one of the

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Speaker 1: things that you know, why we quote you so often

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Speaker 1: and are huge believers, is you dispelled that false assumption

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Speaker 1: about mass marketing just not being competitive anymore in an

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Speaker 1: error of targeting as marketing still critical. Talk to us

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Speaker 1: a little bit about that. Well, I remember which UNI

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Speaker 1: legal ones said. You know, the great thing in the

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Speaker 1: past was that Marcas came up with these targets that

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Speaker 1: excluded most of the bias. I don't want to talk

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Speaker 1: about the bias. But unfortunately, when I handed the money

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Speaker 1: out of the media agency that was impossible to deliver,

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Speaker 1: the brand was saved. And you know, we've got to

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Speaker 1: stick to your grown anyway. But you know that we

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Speaker 1: now have the technology that the bus could actually deliver

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Speaker 1: on those highly restrictive targets, and that would be a

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Speaker 1: fantastic way to drink the brands. Funny, I do a

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Speaker 1: podcast like a clubhouse to podcast conversation with marketers called

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Speaker 1: maybe You're Not the Target. Yeah, I think that's a

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Speaker 1: human bias comes in in so many ways. We have

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Speaker 1: so much data at our fingertips now as marketers versus problem.

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Speaker 1: When you wrote this book, it was much harder to get,

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Speaker 1: you know, research and data. Now we have so much

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Speaker 1: data at our fingertips, and yet I think we're making

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Speaker 1: less informed decisions very often. The send was why I

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Speaker 1: now it's find as anybody who wait for big brands people,

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Speaker 1: we can like some category grows. Of course we like

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Speaker 1: category grows. You know, category, How do categories grow? I'll

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Speaker 1: give you a clue. It's like brand. It's okay, people

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Speaker 1: who are not buying the category buying the category? Right,

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Speaker 1: would you like to talk to people who currently do

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Speaker 1: not buy the category? Oh yeah, I suppose we would. Right,

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Speaker 1: So not only have to reach all category buyers, including

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Speaker 1: the lightest you know, but you actually people who are

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Speaker 1: not in the category at the moment. That how you

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Speaker 1: will grow? Well, you can chase our big drink your brain. No,

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Speaker 1: it's amazing. We see this all the time that I've heard,

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Speaker 1: you know, Mark Pritchard at PNG just a terrific example

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Speaker 1: of years back when P and had sort of moved

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Speaker 1: dramatically away from a lot of mass reach media. They

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Speaker 1: moved almost entirely out of broadcast radio. They were making

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Speaker 1: some decisions to cut budgets. So instead of just like

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Speaker 1: a lot of marketers cut across the board, marks started

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Speaker 1: digging in and to that principle was like, we need growth,

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Speaker 1: we need mass reach. Let's start trying some master each

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Speaker 1: media again and affordable media because we're in a moment

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Speaker 1: of making cuts, and he started reinvesting with a lot

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Speaker 1: of their big Master reach brands back into broadcast radio

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Speaker 1: and into out of both of which they had they

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Speaker 1: had pulled way back from, and they saw this just

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Speaker 1: amazing growth. The premise again, if you're talking to night

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Speaker 1: out of ten Americans about your laundry to churchy, you're

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Speaker 1: probably going to find some new consumers who pop into

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Speaker 1: the storm by it complementary emails saying how it really

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Speaker 1: turned the hats and you put them back up to

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Speaker 1: the christ to yes, you know a few years ago

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Speaker 1: and I think now they're in like the top probably

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Speaker 1: four or five broadcast radio spenders all up, and they've had,

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Speaker 1: you know, just a phenomenal track record of growth. You know,

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Speaker 1: tons of their brands now are very loyal, very dependent

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Speaker 1: on broadcast radio, which we love. Obviously, they're great clients

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Speaker 1: of ours. People going dark right, doing visted campaign and

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Speaker 1: then going silent. You know that suddenly the consumers have

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Speaker 1: stopped buying or some people they need to risk right, yes,

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Speaker 1: or they'll just remember for these long periods of time. Yeah,

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Speaker 1: I don't know if you have any data on this.

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Speaker 1: I've seen some research about how long it takes when

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Speaker 1: you go to our how long it takes to kind

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Speaker 1: of buy back that recall, you know, that mind share

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Speaker 1: with consumers someone else has coming and taken. Part of

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Speaker 1: the problem is reducing the efficiency to spend by clustering.

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Speaker 1: You know, you're pressing, clustering all your money and stid

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Speaker 1: of one month and then nothing the next month. You

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Speaker 1: just spread it out out of the two months. Golden

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Speaker 1: rule is buying media spread it out. Yeah, I think

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Speaker 1: that's probably gotten a little better in the you know,

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Speaker 1: the digital era. There's a little more always on probably spending,

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Speaker 1: but there's still this heavy reliance we see from so

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Speaker 1: many customers. And you talk about our OI not being

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Speaker 1: the best driver or measure of growth. So many customers

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Speaker 1: you see buying these very precious targets. I call it

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Speaker 1: the gritty strivers, you know. And so I'm gonna pay

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Speaker 1: a premium on a premium on a premium to reach

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Speaker 1: the this this epicenter of my target. And and I've

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Speaker 1: added so much cost to my media because I'm targeting

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Speaker 1: and targeting and targeting, and again I've shrunk my POE

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Speaker 1: consumers dramatically by doing it. Why are you paying that

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Speaker 1: huge premium because I don't want wastage? Right? Some of

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Speaker 1: that listage is the future customers. Yeah, exactly, exactly. Tell

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Speaker 1: us a little bit about how you think about late

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Speaker 1: buyers versus heavy buyers have to have friends. What we

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Speaker 1: did five year analysis by the continuous panel analysis and

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Speaker 1: ships a typical consumer good about eight percent of your

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Speaker 1: buio only buy you once a year or thessault than

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Speaker 1: once a big two years, with three years of fouritious

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Speaker 1: or five. And people go, okay, well, but then they

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Speaker 1: can't make out much of my sales, right because they're

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Speaker 1: so light. You know, well, i'mbout forty so am I? Right?

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Speaker 1: Your brand tracking only talks to people who have bought

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Speaker 1: the category of the last two months, and you're actually

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Speaker 1: buying these precise targets to only try to reach really

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Speaker 1: you're just talking to your friends basically. Yeah, And it

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Speaker 1: so feels like that sometimes I read these briefs. In

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Speaker 1: the States, there's a lot of media decision makers and

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Speaker 1: people writing the briefs and making a lot of these

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Speaker 1: decisions are very centralized in New York and Brooklyn. Increasingly,

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Speaker 1: Bob always says, how many of you in this room

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Speaker 1: own a tesla. How many you've been in a tesla?

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Speaker 1: You know, it's a It's less than one percent of

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Speaker 1: cars on the road in America. So that's what we're

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Speaker 1: always talking about it. I heart because we have this

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Speaker 1: mass reach and much lower CPMs, So we've got two

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Speaker 1: things going for radio there. What do you see as

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Speaker 1: the challenges about mass reach? Well, fragmentation obviously, but we've

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Speaker 1: got clever people that's got computers and then we do

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Speaker 1: get that reach. I mean, once upon a time these

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Speaker 1: I grew up in a country and in New Zealand,

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Speaker 1: we only had one of the TV stations. So yeah,

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Speaker 1: you put an ad on, you pretty much reach the country. Yeah,

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Speaker 1: and I caught some great brands and built doing that.

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Speaker 1: And then you know, later it got more complicated. And

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Speaker 1: so I used to tell offic I told and saying,

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Speaker 1: you know, you guys used to say, you know, this

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Speaker 1: is all of this new media and it's difficult at

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Speaker 1: leit about it. You know, whereas we new TV, you know,

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Speaker 1: really you didn't know TV. It was just easy. It

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Speaker 1: was just there's three choices. Most of Americans watching so

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Speaker 1: often people you know, they'll hear the data. Americans lower costs,

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Speaker 1: like we have all these cases of other brands and

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Speaker 1: chrome like g by using the mass media and people

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Speaker 1: very they'll be very skeptical, but they'll they'll do a

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Speaker 1: little test and then they'll just go Wow. It's sort

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Speaker 1: of like buying TV back in the day in New Zealand.

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Speaker 1: You know, you're just reaching a lot more people. You're

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Speaker 1: gonna start seeing sales grow. So I would like to

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Speaker 1: see market has drink a lot more research and learning

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Speaker 1: a lot more about things like radio, TV, outdoor. It's

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Speaker 1: like always there's also we must know a lot. Really,

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Speaker 1: what do you know about it? Yeah? You know, I

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Speaker 1: love saying so in the front Time TV show, how

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Speaker 1: many people who watched this week will be back watching

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Speaker 1: next week? People, I don't know. We've known this for

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Speaker 1: fifty years. We can predict this. But you know, I've

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Speaker 1: played the universities because most universities don't teach media at all. Yeah,

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Speaker 1: it's so interesting because, yeah, on the media side, I

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Speaker 1: think people get so caught up in the r o

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Speaker 1: I metrics and these sort of momentary KPIs. You know,

427
00:24:42,320 --> 00:24:44,520
Speaker 1: there's a lot of people touching a campaign, a lot

428
00:24:44,600 --> 00:24:46,680
Speaker 1: of hands on keyboards going I'm just going to drive

429
00:24:46,800 --> 00:24:49,760
Speaker 1: that number or that number or that number, and they're

430
00:24:49,800 --> 00:24:54,000
Speaker 1: all in isolation of they're not actually growth of sales. Yeah,

431
00:24:54,119 --> 00:24:58,959
Speaker 1: they're not thinking about mental and physical availability. Those are

432
00:24:59,000 --> 00:25:03,800
Speaker 1: the two big things undependent value of your company. Yes, yes,

433
00:25:04,560 --> 00:25:06,960
Speaker 1: what about message? You know you talked a lot about

434
00:25:07,040 --> 00:25:11,160
Speaker 1: not getting too specific on who you're targeting, so you're

435
00:25:11,200 --> 00:25:14,400
Speaker 1: going after the biggest pool of potential customers. But when

436
00:25:14,440 --> 00:25:18,920
Speaker 1: it comes to messaging, you do believe in specific messaging.

437
00:25:19,520 --> 00:25:22,000
Speaker 1: How do you advise people if you're talking to everyone,

438
00:25:22,119 --> 00:25:26,040
Speaker 1: how do you find a message that works. Well, that's

439
00:25:26,040 --> 00:25:30,680
Speaker 1: why we have advertising agencies because it was certainly, you know,

440
00:25:30,920 --> 00:25:33,600
Speaker 1: just all that persons interesting cats, right, Well, we put

441
00:25:33,640 --> 00:25:36,200
Speaker 1: again that the dollars and put a dollar. It was

442
00:25:36,320 --> 00:25:40,080
Speaker 1: that easy. We wouldn't need every agencies. No, we need

443
00:25:40,160 --> 00:25:43,080
Speaker 1: avertyping agencies because we go, okay, well you need to

444
00:25:43,160 --> 00:25:48,679
Speaker 1: communicate to millions of human being and they're all very different.

445
00:25:49,520 --> 00:25:52,159
Speaker 1: They do have a comment that they're human. M h.

446
00:25:52,920 --> 00:25:56,879
Speaker 1: You to work with Matt, Okay, we need will resonate

447
00:25:57,320 --> 00:25:59,880
Speaker 1: because it's very hard to act and do customization. People

448
00:25:59,880 --> 00:26:02,320
Speaker 1: are realize that. But all the research of the tests,

449
00:26:02,359 --> 00:26:05,520
Speaker 1: the academic tests we try personalization, the results of miserable.

450
00:26:06,119 --> 00:26:09,920
Speaker 1: So it's much better to place at bit on great

451
00:26:09,960 --> 00:26:13,120
Speaker 1: creativity that resonates with lots of people, with a little

452
00:26:13,119 --> 00:26:15,840
Speaker 1: bit of sophisticated mass marketing. I mean, obviously if someone

453
00:26:15,920 --> 00:26:18,520
Speaker 1: speaks Spanish by than English, then you talk to him.

454
00:26:18,560 --> 00:26:23,440
Speaker 1: It's been but what we wanted, mass scale without creativity

455
00:26:24,920 --> 00:26:27,359
Speaker 1: appreciate actually did that. We we set what do you

456
00:26:27,400 --> 00:26:30,720
Speaker 1: call it the crap track. Yes, I was there in

457
00:26:30,840 --> 00:26:35,760
Speaker 1: that room for that spanship brilliant. We're wasting all our

458
00:26:35,840 --> 00:26:38,919
Speaker 1: money creating all this different content and so we had

459
00:26:39,320 --> 00:26:42,640
Speaker 1: little money left that actually by media actually make sure

460
00:26:42,680 --> 00:26:47,160
Speaker 1: anyone heard it or so. Yeah, that's true, It's very true.

461
00:26:47,720 --> 00:26:49,680
Speaker 1: What do you think about in this world where everyone's

462
00:26:49,720 --> 00:26:52,880
Speaker 1: talking about privacy, you know, a world where we've become

463
00:26:52,960 --> 00:26:56,320
Speaker 1: so dependent on targeting and now with the Kingbridge Analytica

464
00:26:56,440 --> 00:26:59,520
Speaker 1: and all of the maybe abuse of targeting that's happened,

465
00:26:59,800 --> 00:27:02,280
Speaker 1: it's people are going to be pivoting back to mass marketing.

466
00:27:02,880 --> 00:27:08,920
Speaker 1: But also because they're targeting never worked. You know some

467
00:27:09,040 --> 00:27:12,160
Speaker 1: reports Nico human is very good work in this area,

468
00:27:12,240 --> 00:27:14,920
Speaker 1: you know, buying on programmatic platforms and showing that you know,

469
00:27:15,320 --> 00:27:17,520
Speaker 1: you could do a targe of saying men, and you

470
00:27:17,600 --> 00:27:19,760
Speaker 1: reached men about half the time, and half it's only

471
00:27:19,800 --> 00:27:22,119
Speaker 1: reached women. You know. I mean, we absolutely thought we

472
00:27:22,160 --> 00:27:24,240
Speaker 1: could do this and we couldn't. But most of the

473
00:27:24,280 --> 00:27:28,480
Speaker 1: time we don't need to target geographic right, Geographic is

474
00:27:28,720 --> 00:27:33,400
Speaker 1: hugely important because I do not have physical availability. It's

475
00:27:33,400 --> 00:27:35,680
Speaker 1: a very pat and so I would want to be

476
00:27:35,760 --> 00:27:38,480
Speaker 1: able to buy media on geographic basis. Yes, that's a

477
00:27:38,560 --> 00:27:42,560
Speaker 1: really important tipling thing. Where people live really matters to

478
00:27:42,640 --> 00:27:45,879
Speaker 1: their lives. Ducan lots re search shows that you know,

479
00:27:45,960 --> 00:27:49,440
Speaker 1: where people live affects what they do online. And then

480
00:27:49,640 --> 00:27:52,640
Speaker 1: some categories have end debased, you know, like I'm selling

481
00:27:52,680 --> 00:27:54,760
Speaker 1: women's clothing, so I want to the women or some

482
00:27:55,000 --> 00:27:59,480
Speaker 1: have some age. But after that it all gets quite trivial. Really,

483
00:28:00,000 --> 00:28:02,720
Speaker 1: we don't need anything much more than that. You think

484
00:28:02,760 --> 00:28:05,760
Speaker 1: consumers are easier dis way than we think. We don't

485
00:28:05,800 --> 00:28:09,720
Speaker 1: need to get seven hundred data points. I've seen literally

486
00:28:09,800 --> 00:28:12,639
Speaker 1: target lists from you know, digital campaigns where there's you know,

487
00:28:12,960 --> 00:28:18,440
Speaker 1: fifty sixty different criteria people are buying one impression that

488
00:28:18,560 --> 00:28:21,840
Speaker 1: is a mistaken belief. It's in shoudive belief that if

489
00:28:21,880 --> 00:28:26,000
Speaker 1: we get more datas My bit of predictions the forecasting

490
00:28:26,080 --> 00:28:28,520
Speaker 1: side of just just shape their heads and go Now

491
00:28:28,640 --> 00:28:31,920
Speaker 1: you wan't now you want a preid simple models out

492
00:28:31,960 --> 00:28:36,120
Speaker 1: before the most complex. Uh. How do you feel about

493
00:28:36,320 --> 00:28:41,600
Speaker 1: loyalty programs? Same problem, talking to too few people too often.

494
00:28:42,080 --> 00:28:44,640
Speaker 1: It might be a multi programs. Yeah, we now know

495
00:28:44,800 --> 00:28:47,600
Speaker 1: why they don't do a lot. You can detect the

496
00:28:47,880 --> 00:28:51,080
Speaker 1: dot lifting nualty. But it's rather disappointing. And the reason

497
00:28:51,120 --> 00:28:54,080
Speaker 1: it disappointing isn't because why do you join that department's

498
00:28:54,560 --> 00:28:59,320
Speaker 1: stools dualty program? Because I shot there regularly, right, And

499
00:28:59,400 --> 00:29:01,400
Speaker 1: if you don't, you don't even hear about the little

500
00:29:02,400 --> 00:29:07,000
Speaker 1: very true, that's the recruits are getting glass. And then

501
00:29:07,040 --> 00:29:10,880
Speaker 1: there's also the incentive effect if you don't buy, then

502
00:29:10,960 --> 00:29:13,040
Speaker 1: you go on up to get many points. So they're

503
00:29:13,120 --> 00:29:19,240
Speaker 1: very extensive or lower reach. And the low quality media

504
00:29:19,560 --> 00:29:22,280
Speaker 1: it's like Facebook friends. You know, I'm going to build

505
00:29:22,360 --> 00:29:25,240
Speaker 1: up a big thing of people who liked on Facebook.

506
00:29:25,520 --> 00:29:27,640
Speaker 1: That is low quality media because you're just talking to

507
00:29:27,720 --> 00:29:30,480
Speaker 1: the same people. I don't know that. It's so funny,

508
00:29:30,520 --> 00:29:33,520
Speaker 1: it's so true. I'm not a big loyalty club person,

509
00:29:33,640 --> 00:29:36,200
Speaker 1: but you have a certain retail story shop at all

510
00:29:36,240 --> 00:29:39,400
Speaker 1: the time so I accruit points. It's usually the first

511
00:29:39,440 --> 00:29:41,800
Speaker 1: story I go to, and I shopped there quite often,

512
00:29:41,840 --> 00:29:44,560
Speaker 1: and every time when they go, oh, you get fifty

513
00:29:44,600 --> 00:29:47,440
Speaker 1: dollars off this, and I'm like, amazing, but I was

514
00:29:47,520 --> 00:29:51,960
Speaker 1: going to buy this anyway. And country like, you've got

515
00:29:52,000 --> 00:29:54,120
Speaker 1: a lot of people living in the rule though you know,

516
00:29:54,560 --> 00:29:57,120
Speaker 1: there's only one guest station. I'm going to buck them anyway,

517
00:29:59,360 --> 00:30:02,720
Speaker 1: the one into down. That's so true. Yeah, no, it's interesting.

518
00:30:02,760 --> 00:30:05,480
Speaker 1: We've been talking a lot lately about rural America, you know,

519
00:30:05,600 --> 00:30:09,640
Speaker 1: smaller towns where you know, obviously because we have reached Americans,

520
00:30:09,760 --> 00:30:13,600
Speaker 1: we're reaching rural, suburban, urban, all of the flavors of

521
00:30:13,800 --> 00:30:16,680
Speaker 1: this nation. And I think so many marketers, you know,

522
00:30:16,720 --> 00:30:19,480
Speaker 1: you see campaign after campaign after campaign we want to

523
00:30:19,480 --> 00:30:22,880
Speaker 1: buy the top twenty markets, top twenty markets again, most expensive,

524
00:30:23,000 --> 00:30:25,480
Speaker 1: top twenty markets. You know, there's so many consumers out there.

525
00:30:25,720 --> 00:30:28,440
Speaker 1: You've never exposed your message too, if you just went

526
00:30:28,520 --> 00:30:31,440
Speaker 1: a little bit broader. I've done some diagnostics and brands

527
00:30:31,600 --> 00:30:35,040
Speaker 1: launches that have failed. One of the reasons it's the

528
00:30:35,040 --> 00:30:38,320
Speaker 1: people in the country you never reached, never even got

529
00:30:38,400 --> 00:30:43,719
Speaker 1: your message once. Wow. And usually it's the sales can

530
00:30:43,760 --> 00:30:45,479
Speaker 1: has done a great job, and you know they've got

531
00:30:45,520 --> 00:30:48,240
Speaker 1: it into Walmart or something. It's there, it's ready to

532
00:30:48,320 --> 00:30:55,280
Speaker 1: be bought. Sword on ship because you only top twenty markets. Well,

533
00:30:55,360 --> 00:30:58,680
Speaker 1: that's interesting to memory structures that you talked a lot about.

534
00:30:58,760 --> 00:31:02,479
Speaker 1: Can you explain the theory about memory structures. Consumers are

535
00:31:02,680 --> 00:31:06,520
Speaker 1: fairly naturally loyal. They don't really care that much about brands.

536
00:31:06,720 --> 00:31:10,200
Speaker 1: They keep going about to the same restaurants, the same stores,

537
00:31:10,880 --> 00:31:14,520
Speaker 1: the same brands on shelf. And this is what is brandiquity.

538
00:31:14,720 --> 00:31:18,840
Speaker 1: You have mental and physical availability, but you need to

539
00:31:18,880 --> 00:31:21,760
Speaker 1: have this to overlap. And you know a lot of

540
00:31:21,800 --> 00:31:24,040
Speaker 1: times it isn't overlapping, and that a lot of people

541
00:31:24,040 --> 00:31:26,120
Speaker 1: who are coming into the store just do not see

542
00:31:26,160 --> 00:31:29,920
Speaker 1: you because there's pins of thousands of items in the

543
00:31:30,000 --> 00:31:33,120
Speaker 1: store and they zoom in on the few that they

544
00:31:33,240 --> 00:31:35,360
Speaker 1: know and then they get out of the store. You

545
00:31:35,480 --> 00:31:39,320
Speaker 1: get a terrible return on the physical availability, whether that's

546
00:31:39,320 --> 00:31:41,479
Speaker 1: on a website or in a physical store, you get

547
00:31:41,520 --> 00:31:44,720
Speaker 1: a terrible return on because you went in their heads. Likewise,

548
00:31:44,720 --> 00:31:47,680
Speaker 1: there's no point being in people's heads. They don't know

549
00:31:48,000 --> 00:31:52,400
Speaker 1: where do I get this thing from? Nic As the

550
00:31:52,440 --> 00:31:55,600
Speaker 1: scot Line, the world's biggest search engine is between people's ears.

551
00:31:56,360 --> 00:31:58,680
Speaker 1: I spent so much time trying to figure out how

552
00:31:58,720 --> 00:32:02,160
Speaker 1: to do audio creative well. And we always say that

553
00:32:02,320 --> 00:32:06,440
Speaker 1: the world's best production machine is between your ears. So

554
00:32:07,200 --> 00:32:11,120
Speaker 1: you know, by saying Grand Canyon with jello, you're picturing

555
00:32:11,200 --> 00:32:14,000
Speaker 1: what color jello. It's amazing how we can fill in

556
00:32:14,080 --> 00:32:18,280
Speaker 1: the pictures and be even you know, targeted with audio creative. Right.

557
00:32:18,440 --> 00:32:20,840
Speaker 1: You know, I could say did you have lunch today?

558
00:32:21,640 --> 00:32:26,120
Speaker 1: Was it good? Do you even remember it? Yeah? Right,

559
00:32:26,120 --> 00:32:28,280
Speaker 1: And all of a sudden, I have you thinking about

560
00:32:28,320 --> 00:32:31,000
Speaker 1: your lunch. Whereas you know, back like in Microsoft, I

561
00:32:31,040 --> 00:32:35,000
Speaker 1: would have to make four spots for year for Xbox

562
00:32:35,240 --> 00:32:38,480
Speaker 1: for thirty one countries. And that living room didn't look

563
00:32:38,520 --> 00:32:40,760
Speaker 1: like anyone's living room because I was trying to bash

564
00:32:40,840 --> 00:32:44,040
Speaker 1: up you know, Southeast Asia and Europe, and no one

565
00:32:44,160 --> 00:32:46,320
Speaker 1: had that living room. But if I said picture yourself

566
00:32:46,400 --> 00:32:48,880
Speaker 1: in your living room, I'm relevant right there with everyone.

567
00:32:50,320 --> 00:32:53,800
Speaker 1: The impultance of having audio distinctive assets, even if you

568
00:32:53,880 --> 00:32:56,800
Speaker 1: are using video, the fact is you've got to expect

569
00:32:56,880 --> 00:33:01,040
Speaker 1: fleeting exposures. People will not be at tension to all that,

570
00:33:01,240 --> 00:33:02,920
Speaker 1: and there's something you can do about that. And you

571
00:33:02,960 --> 00:33:05,880
Speaker 1: shouldn't worry. You should just be cognisive of all that.

572
00:33:06,000 --> 00:33:08,720
Speaker 1: So I need this tv AD to work in audio

573
00:33:08,800 --> 00:33:12,200
Speaker 1: as well as as individual Yeah, I know, particularly people

574
00:33:12,320 --> 00:33:15,080
Speaker 1: multitasks too. I think a lot of brands have gotten

575
00:33:15,120 --> 00:33:18,440
Speaker 1: more sophisticated in understanding how important audio is because it's

576
00:33:18,480 --> 00:33:20,200
Speaker 1: tastes in your head and then like you said, there

577
00:33:20,200 --> 00:33:22,160
Speaker 1: it is on the shelf. Oh yeah, I don't even

578
00:33:22,240 --> 00:33:23,560
Speaker 1: know why I am picking that up, but it's in

579
00:33:23,600 --> 00:33:28,000
Speaker 1: my head. To stop paying more attention to jingles again, Yes,

580
00:33:28,360 --> 00:33:30,600
Speaker 1: you know we Yeah, we used to do some jingle hacks,

581
00:33:30,600 --> 00:33:33,360
Speaker 1: would get musicians in with marketers and actually work on

582
00:33:33,840 --> 00:33:37,080
Speaker 1: collaborating real time, and some amazing campaigns came out of that.

583
00:33:37,160 --> 00:33:39,880
Speaker 1: Because a lot of household you know brands, we know

584
00:33:40,000 --> 00:33:43,240
Speaker 1: what they are, We just need to remember to buy them.

585
00:33:43,440 --> 00:33:47,040
Speaker 1: Remember they're available. I cannot end a Math and Magic

586
00:33:47,120 --> 00:33:50,080
Speaker 1: interview if I didn't ask you to shout out your

587
00:33:50,280 --> 00:33:55,040
Speaker 1: favorite mathematician. Who's your favorite numbers person? That would be

588
00:33:55,120 --> 00:33:59,040
Speaker 1: Gerald Goodhart, who which with us as a cheer about

589
00:33:59,040 --> 00:34:02,680
Speaker 1: advisable Frank Emeritus Professor Honor Doctorate from the University of

590
00:34:02,720 --> 00:34:05,880
Speaker 1: Southstralia and colleague with Andrew and why do I say

591
00:34:05,920 --> 00:34:11,000
Speaker 1: Gerald because Gerald described himself as a reformed statistician than

592
00:34:11,960 --> 00:34:15,480
Speaker 1: he would always right, what's the simplest way of showing

593
00:34:15,600 --> 00:34:19,319
Speaker 1: this very key, not what where did the data come from?

594
00:34:19,440 --> 00:34:22,800
Speaker 1: I really understanding the data stable before subjecting it to

595
00:34:22,880 --> 00:34:26,120
Speaker 1: any sort of complex he could cut through the bullshit

596
00:34:26,320 --> 00:34:29,759
Speaker 1: very well. There's a danger when people learn statistics like

597
00:34:29,920 --> 00:34:32,840
Speaker 1: Gerald did, they just get enamored by their it's like

598
00:34:32,960 --> 00:34:38,560
Speaker 1: their machinery and yeah, the slice, and they totally lose

599
00:34:38,920 --> 00:34:41,200
Speaker 1: picture of the real world. So, you know, with someone

600
00:34:41,239 --> 00:34:47,040
Speaker 1: who needs statistics the Cambridge but became a silist rather

601
00:34:47,120 --> 00:34:50,719
Speaker 1: than someone who played being a statistician, that's what we

602
00:34:50,800 --> 00:34:54,440
Speaker 1: need more of. Definitely being true to the science of marketing.

603
00:34:55,480 --> 00:34:57,520
Speaker 1: How about the other side of the table, who's your

604
00:34:57,600 --> 00:35:01,000
Speaker 1: favorite creative? Who's your favorite MAGICI ship on the other

605
00:35:01,080 --> 00:35:04,839
Speaker 1: side of the mouth and magic coin. George Felix, who

606
00:35:05,120 --> 00:35:07,759
Speaker 1: was at Proper and Campbell gets responsible for the old

607
00:35:07,800 --> 00:35:13,520
Speaker 1: Spice revival fantastic magic and totally fitted in with you know,

608
00:35:13,960 --> 00:35:17,560
Speaker 1: the scientific laws that was really word and did it

609
00:35:17,640 --> 00:35:19,680
Speaker 1: when he went to Knowing a Chicken. He was part

610
00:35:19,719 --> 00:35:24,279
Speaker 1: of the team that finally brought back the Colonel l back.

611
00:35:24,920 --> 00:35:26,839
Speaker 1: I think there was a time where yeah, turn Chicken

612
00:35:26,960 --> 00:35:30,040
Speaker 1: changed its name at KFC because because the mont pun't

613
00:35:30,080 --> 00:35:33,240
Speaker 1: worried about that weird fried. This is a classic example

614
00:35:33,280 --> 00:35:37,239
Speaker 1: of marketing team just in their own little bubble, right, simnicate.

615
00:35:37,480 --> 00:35:40,439
Speaker 1: Everyone knows it's fried. Everyone knows it's fried chicken. That's

616
00:35:40,600 --> 00:35:43,759
Speaker 1: why they lost on you when you're wiping the grease

617
00:35:43,840 --> 00:35:48,560
Speaker 1: off your hands. That's why it's good. Yeah, might go, oh,

618
00:35:48,719 --> 00:35:51,040
Speaker 1: you know this old white guy from the South, that's

619
00:35:51,080 --> 00:35:53,279
Speaker 1: not really so good to go, Well, don't think about that.

620
00:35:54,000 --> 00:35:57,839
Speaker 1: It's a distinctive asset. It's branded. As I always point out,

621
00:35:58,040 --> 00:36:01,160
Speaker 1: no one stops to think, why does the bigger chant

622
00:36:01,320 --> 00:36:10,040
Speaker 1: a spot of shame? Also, nobody cares bringing the king back.

623
00:36:10,120 --> 00:36:13,400
Speaker 1: That was also genius. Yeah, that's totally in line with

624
00:36:13,520 --> 00:36:16,719
Speaker 1: the signs. And that's wonderful, gradual and right ready to

625
00:36:16,760 --> 00:36:20,120
Speaker 1: do it. So true, it's so true. We need more

626
00:36:20,239 --> 00:36:24,600
Speaker 1: bravery definitely the creative side of the equation. Well, this

627
00:36:24,719 --> 00:36:27,919
Speaker 1: has been amazing. I think marketers out there are ready

628
00:36:28,000 --> 00:36:30,799
Speaker 1: to learn a little math, a little magic, and your

629
00:36:30,800 --> 00:36:33,760
Speaker 1: book Our Brands Grow has just been really the bible

630
00:36:34,000 --> 00:36:37,360
Speaker 1: for so many marketers. Who are succeeding, and it's amazing

631
00:36:37,480 --> 00:36:39,920
Speaker 1: the advice you have from marketers holds up so well,

632
00:36:40,280 --> 00:36:46,040
Speaker 1: so so well today. So here are a few things

633
00:36:46,080 --> 00:36:49,440
Speaker 1: I've picked up from Gail's conversation with Byron. One, A

634
00:36:49,560 --> 00:36:54,200
Speaker 1: data driven approach can fuel creativity, not killing. Byron uses

635
00:36:54,280 --> 00:36:58,000
Speaker 1: the example of architectural design. Math and magic must come

636
00:36:58,040 --> 00:37:02,320
Speaker 1: together to create buildings that are beautifu full and structurally sound.

637
00:37:02,800 --> 00:37:05,680
Speaker 1: Stay rooted in data and facts, and your creative ideas

638
00:37:05,719 --> 00:37:10,439
Speaker 1: can flourish. Two. In an era of targeted advertisements, mass

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Speaker 1: marketing still works. While targeting can be a powerful tool,

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Speaker 1: over targeting can cause missed opportunities. Byron's research still finds

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Speaker 1: that reaching more people brings in more customers. Three numbers

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Speaker 1: don't lie. As marketers, it can be tempting to create

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Speaker 1: the campaigns we want to hear, but the data shows

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Speaker 1: that our preferences might not reflect the mass audience. Byron

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Speaker 1: reminds us that we need to cast aside our biases

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Speaker 1: and stick to the messages that have proven success or

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Speaker 1: Conventional wisdom often hides the truth. When we buy in

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Speaker 1: the group thing without examining the proof, we often miss

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Speaker 1: the right idea I'm Bob Pittman. Thanks for listening. That's

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Speaker 1: it for today's episode. Thanks so much for listening to

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Speaker 1: Math and Magic, a production of Radio. The show is

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Speaker 1: hosted by Bob Pittman. Special thanks to Susan Ward for

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Speaker 1: booking and wrangling our wonderful talent, which is no small feed,

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Speaker 1: Marissa Brown for pulling research, our editors Derek Clements, Mary

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Speaker 1: Dow and Ryan Murdoch, our producer Morgan Levoy, our executive

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Speaker 1: producer Nikki Etor, and of course Gayle Roel, Eric Angel Noel,

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Speaker 1: and everyone who helped bring this show to your ears.

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Speaker 1: Until next time,