0:00

Good Company is a production of I Heart Radio.

0:03

We'll throw down the glove and have an academic

0:05

data science debate with literally absolutely

0:07

anybody who wants to try to pigeonhole

0:10

search into a niche.

0:18

Hi, I'm Michael Casson. Welcome

0:20

to Good Company, where I'll explore how marketing,

0:23

media, entertainment, and tech are intersecting,

0:26

transforming our lives and the way we do business

0:28

at a breakneck speed. I'll be joined

0:30

by some of the greatest business minds at strongest

0:33

leaders who will share how they build companies from

0:35

the ground up or transform them from the inside

0:37

out. My bed is you'll pick up a lesson

0:40

or two along the way. It's all good.

0:49

I'm excited today to welcome

0:51

to guests to the Good Company

0:54

Podcast. First of all, the

0:56

E d O Founder and as well

0:58

the president and CEO Number

1:01

one, the E d O Founder is Edward

1:03

Norton. And Edward, you don't need much introduction.

1:06

Certainly most of us I

1:08

know have enjoyed you know you as

1:10

talent both in front of the camera

1:12

and behind the camera. And I

1:15

hearken back to the Oscars

1:17

a k A. Sunday Night at the Fights when

1:19

one of the Academy Award winners, talked about

1:22

his daughter referring to him as a nominee.

1:24

Now he gets to say a winner. You've won a couple

1:27

of awards, You've had many nominations,

1:29

but you have certainly been awarded

1:32

and honored in this industry. And

1:34

I will say I've had the pleasure of enjoying

1:36

you on the screen, but I've also had the pleasure

1:39

of listening to you speak to a group

1:41

of advertisers a couple of years ago,

1:43

when I walked away saying he's

1:45

not just a pretty face. He knows a thing

1:47

or two about a thing or two. And so it's

1:50

a pleasure to welcome you, and as well, it's

1:52

a pleasure to welcome Kevin Krim, who's

1:54

the president and CEO of v DO. And

1:57

we've had the pleasure of working together Kevin in

1:59

different and iterations and most recently

2:01

with the d O. So I want to welcome you

2:04

both the good company. I'm excited to

2:06

be able to share with our listeners

2:08

some amazing insights and some understanding

2:11

about what motivated you

2:13

both to really get into

2:15

the trench here on the not

2:18

as a sexy side of the business, but actually

2:20

if one you know, looks at it through the lens

2:22

you do and I do maybe the sexiest

2:25

part of the industry, which is measurement.

2:27

You know. So I would ask you, both,

2:29

Edward and Kevin, what was it

2:31

that motivated you to make a move and get into

2:34

the measurement business. It's fun

2:36

to get into the weeds with

2:38

with someone who's not a CUB reporter

2:40

and asking us what measurement

2:42

means. We

2:46

were talking about. I always wanted to be Jimmy Elson,

2:48

but I'm happy not to be. No.

2:51

I it's for Kevin and I. It's

2:53

a it's a sweet relief to

2:55

talk to a veteran and to an audience

2:58

group that's also probably you know,

3:00

pretty advanced in their

3:03

level of convergency with all this stuff.

3:05

You know, It's funny I worked in I

3:07

worked in low income housing, tax credit syndication

3:10

finance when I first got out of school, if you can, you

3:13

know, like a lot of people, I think the actors traditional

3:15

like my job before I first got a gig was his

3:17

waiter and you know whatever I

3:20

worked in kind of this esoteric corner of I

3:23

got. I had a lot of friends who were in finance, and I got

3:25

really interested in financial technologies

3:28

and investing in that kind of

3:30

stuff, and always kept that up,

3:32

even as my my moonlighting in

3:34

the theater kind of took on a life of its own

3:36

and became a career. I

3:39

would say it became a career along

3:42

the on the way I had

3:44

a I had. I had a friend named Daniel

3:47

Nadler who's the co founder of Video

3:49

with Me. Daniel also

3:51

was a creative person, a published poet. He

3:54

also, on the side had a

3:56

kind of an intellectual and finance career.

3:58

He he had a PhD from Harvard

4:00

and quantitative data science and had

4:03

pioneered data

4:05

science technologies at the FED to help

4:07

them analyze economic

4:10

patterns. And I was really lucky I talking

4:13

to Daniel. He had this incredible idea about

4:15

applying putting edge

4:17

machine learning and artificial

4:19

intelligence to financial market data.

4:22

And he had a really articulate and passionate kind

4:24

of view of how he thought

4:26

it could. It could democratize the

4:29

analytics that get siloed

4:31

by hedge funds and things like that, and

4:35

and so he set off on this kind of quixotic

4:38

thing to build a company called Ken Show. And I

4:40

was lucky to be one of his early investors

4:42

and ultimately one of his biggest

4:45

investors, alongside others

4:47

like Goldman Sachs and General Catalyst

4:50

and and ultimately all the six biggest

4:52

banks and the CIA in q Tel

4:54

invested in the company too. And what

4:56

Daniel built with ken Show was

4:58

was truly astonishing. It the company was ultimately

5:00

bought by S and P, and he

5:03

really showed he's one of I

5:05

would say he's a global innovator in

5:08

looking at the way that you

5:10

know, massive parallel processing and machine learning

5:12

and stuff can be applied to open

5:14

source data, not not just proprietary

5:16

data, but to open source data like search

5:19

and other things like that to build incredibly

5:22

powerful predictive models around

5:24

financial market outcomes and

5:27

things like that. I'll give you an example because

5:29

it relates to our world. He they showed

5:31

that, for instance, very

5:33

granular at least specific search query

5:36

around Netflix subscription sign

5:38

ups in European markets could

5:40

end up being more predictive of what

5:42

Netflix's economic performance was going to

5:45

be over the next couple quarters. Then

5:47

most of the other analysis that was out there,

5:50

and this was all through the really pioneering

5:52

way that his company ingested and

5:54

analyzed minute to minute search

5:57

data around specific topics. It

5:59

ended up being a very hailed company in

6:01

the and intelligence community

6:03

world. And I was lucky enough to sort of be along

6:05

for the ride or be adjacent to Daniel's

6:08

efforts on that. Along

6:10

the way, I said to him, you know, you say, what

6:13

was the song or what was the moment? You

6:15

know I was. I was in some good movies like Birdman

6:18

and and Grant

6:20

Budapest Hotel and other things like that, where

6:23

I saw firsthand, you know, that the

6:25

noble and in some ways successful efforts

6:28

of the studio to market these

6:30

films, oscar campaigns,

6:32

all of that. Except I was also privy

6:34

to the fact that Wes Anderson and all the

6:36

rest of us, and all of us who are in Birdman, we're

6:39

inside compensation formulas that were

6:41

basically going to be very

6:43

difficult for us to climb out from under

6:45

the marketing spend inefficiency. But because

6:48

talent compensation these days is

6:51

more and more tied to net profit formulas

6:54

as opposed to gross which it used

6:56

to be before DVDs got atomized,

6:58

and and so it

7:01

sounds funny, but I was very specifically

7:03

aware of how compensation

7:07

of creators, filmmakers, actors

7:10

was getting hammered by marketing and efficiency

7:12

because the more the more a

7:14

studio spends, that

7:17

that's an even bigger hole that you have to recoup

7:19

and climb out from under before that that

7:21

p and A ends up changing your life

7:23

for sure, exactly exactly,

7:26

And and everybody thinks an oscar campaign

7:28

sounds great if a studio is spending

7:30

on it, But what you don't realize is they're literally spending

7:33

your money. They are,

7:35

they are spending Every dollar

7:37

they spend is a dollar

7:39

you have to climb out from under to ever get

7:41

into Wes Anderson seeing upside

7:44

on on one of his best and moment, I want

7:47

to interrupt for a second. I want to interrupt

7:49

for one second, Edward, because I want to tell you a

7:51

story and it involves Clean Eastwood, and

7:54

it's a really interesting story because

7:56

your focus. You know

7:59

that you're not the first. But I will tell you why I

8:01

mentioned Clint east Would in this conversation.

8:03

Back in the day when I ran a large media

8:05

agency, our largest client was the Walt

8:07

Disney Company, and we were exclusive to

8:09

the Walt Disney Company with one exception.

8:13

We could buy for Clint Eastwood for mal

8:15

Paso Productions because the

8:17

founder of the company that I ended up running called

8:19

Western International Media. Dennis

8:21

Holt, who was the founder, had been very good friends with

8:23

Clint back in the day. They were

8:26

in r OTC together, and you know

8:28

they were they were contemporaries. And

8:31

the most efficient marketing campaigns

8:33

of any movies that I ever experienced were

8:36

mal Paso productions, anything that Clint

8:38

produced. And why because

8:40

Clint would actually show up at the planning

8:43

meetings with the media agency and

8:45

he paid attention, and because

8:47

he showed up Back in the day, Bob

8:49

Daly and Terry Semmel would show up to those

8:51

meetings because they knew Clint was showing up. And

8:54

the fact that Clint East would paid enough

8:56

attention to the detail of the actual

8:59

media plan change the

9:01

efficacy back to your word of

9:03

the media then, because keep paid attention.

9:05

It's so funny that I'm hearing you

9:07

say it but through a different lens, But I

9:09

actually saw it in practice thirty

9:12

years ago. It's really interesting. I

9:14

just I had to interrupt to say that, no,

9:16

not at all. It's it's it's always been sort of

9:18

the I mean, look, there's a reason that people

9:21

wanted gross participation, right because

9:23

it's sort of atomized. You

9:25

were getting it off the top line on

9:28

the marketing right, and and and in and

9:30

in our streaming world where the value of the

9:32

home video was taken from

9:35

the main profit center in the

9:37

content media business model to being zero

9:40

effectively, right, and

9:43

you you you know, gross

9:45

went away for the large majority of

9:47

people in the industry,

9:50

and and so so

9:52

inefficiency of marketing actually

9:55

affects talent. But the other thing

9:57

is, and of course now I'm just talking about the

10:00

media. I'm talking about the content,

10:02

you know, studio television, vertical.

10:04

But still, you

10:07

know, a studio's appetite

10:09

for the type of material it makes is

10:12

a function of its sense of the risk, right

10:14

of the cost, and and part

10:16

of the reason video

10:19

producers and finance here's shy away

10:21

from the most challenging materials. They

10:23

struggle to see how they're going to get their

10:25

return. And that's only rational, right, So,

10:28

so inefficiency

10:30

of marketing spend, if if if two

10:32

thirds of your spend is is inefficient,

10:36

it just means that you it's

10:38

harder for you to see a path to how you're going to do

10:40

well on something challenging, right, And so so

10:43

it's not just what do creators get paid.

10:45

It's what content even gets made

10:48

suffers, suffers from

10:51

a sense of the top line cost

10:53

versus the return, and and

10:56

so so the better

10:59

better studios. Yeah, exactly. You

11:01

know, I was gonna say, think of genre, and

11:03

think of Westerns, and all of a sudden

11:05

you have a Yellowstone, and all of a sudden, Westerns

11:08

are now chic again, and everybody wants to

11:10

be one of the Dutton's, you

11:12

know in yellow Stone. So but

11:16

the bottom, the bottom line is um

11:18

for me. I mean, just to bring it round

11:20

to the to where we actually are. I

11:23

said to Daniel at one point, while Ken

11:25

Show was rising in the financial market

11:27

worlds, is this kind of star um

11:29

in in bringing machine

11:32

learning and AI to those

11:35

markets, not in a siloed way, for like through

11:37

quant hedge funds and stuff who keep their black

11:39

box? Right he was, he was democratizing it.

11:42

I said to him, should we start a media

11:44

division of Ken Show? Because you're

11:47

out here crushing the baseline

11:50

data science capabilities in very

11:52

sophisticated markets like the intelligence

11:54

community and and finance. You're

11:56

you're demonstrating data science

11:58

alpha even in those worlds. And I said,

12:00

without without throwing shade on people. This

12:03

is an industry that's still pricing it's

12:06

all. It's advertising around a

12:08

seventy five year old data

12:11

metric called a Nielsen rating

12:13

that is so obsolete and so absurdly

12:16

blunt and uninsightful.

12:19

You know, it's like you're you're talking about something

12:21

that was developed when we had three major networks

12:23

and every demographic of audience was

12:25

constrained into those three And so if

12:28

you said how many eyeballs did I get

12:30

in X demographic? That was

12:32

about the best proxy you could come

12:34

up with for did I reach my target audience?

12:36

Right? But we're in a world where of

12:39

Facebook and digital advertising, where

12:41

the expectation of

12:44

you know, how many people maybe saw something?

12:47

Yeah, and so what right? Right? And I

12:49

mean, we're we're in the point now where where

12:51

you should be able to know much, much,

12:53

much more about the value you got

12:56

back from every dollar you applied. And

12:59

and yet, amazingly, in

13:01

the television landscape, not just linear

13:03

but streaming, the convergent TV landscape,

13:06

we were still even seven years

13:08

ago, we were still floating along with

13:11

everybody, you know, assuming

13:13

that you know, it's it's still sort

13:15

of the best we've got, even

13:17

though everyone on the

13:20

network side, like Kevin when he was at CNBC.

13:23

We're basically breaking faith with this

13:25

idea that their their inventories should

13:27

be priced off of Nielsen ratings. Right, And and

13:29

so I said to Daniel, Listen,

13:32

the big lie is

13:34

that everything is shifting to digital. It's

13:36

not. There's still probably six

13:40

of all major our

13:42

you know, sector verticals advertised on television.

13:45

The large preponderance of advertising dollars

13:47

still goes to television because they know it's a

13:49

powerful medium.

13:52

But the data science has not

13:54

matured on that side of the line because

13:57

it's hard, and because Nielsen Nielsen

13:59

does not only doesn't get to hire people

14:02

like Daniel, it doesn't even get to meet them, right

14:04

like top data science does not go to

14:06

media historically. It doesn't certainly

14:08

doesn't go to legacy companies like Kantar

14:11

and and Nielsen. It

14:13

goes to quant hedge funds, into the to the intelligence

14:15

community, into Google. Right absolutely.

14:18

And look, so that's why

14:20

you didn't have You didn't have intellectual

14:23

acted, you didn't have technological improvement

14:26

in the legacy media data companies.

14:28

But you didn't have to. We didn't have to because

14:31

the world accepted a currency. The bottom

14:33

line is. I've sort of said, Kevin and I have laughed.

14:35

I said, like, it's like if you needed

14:37

brain surgery and the place to see an era

14:39

that was like a stone axe, and you you would

14:42

take it, you know. But but today,

14:44

if if if someone came at you with

14:46

nineteen century tools, you'd say, like, get

14:49

me the fucking gamma knife. You know what I mean? I want

14:52

I want the best, and and that

14:54

that is that is the level

14:56

of technological data science and say

14:58

that these legacy companies are well and

15:00

and Edward, I'm going to throw something out, so

15:03

you know, Traditionally we talked about

15:05

the brand marketer and the performance

15:08

marketer, and those were separate

15:10

and distinct groups inside

15:12

of an organization, inside of an agency.

15:15

I had my brand marketers and I had my performance

15:17

marketers. It really was brought to my attention by

15:19

American Express when we worked with them

15:21

on reimagining their organization and

15:24

bringing the two together. And I give credit to Elizabeth

15:27

Rutledge, the chief marketing officer of American

15:29

Express, for saying to me, Michael, I

15:31

need media links. Helped to bring these two disciplines

15:33

together before we go into the market

15:36

and choose a new agency and

15:38

I had an epiphany. And I always say the light

15:40

bulb went off, and I get corrected. Some people say,

15:43

no, the light bulb goes on. For me, the light

15:45

bulb goes off because I think of it as flashing.

15:47

But when the light bulb went off, I

15:49

said, well, so what you're saying is brand marketing

15:52

and performance marketing are coming together. And

15:54

I always like to find a turn of a phrase, and I

15:56

said, I'm going to call it brandformance marketing.

15:59

And it was the idea of bringing the

16:01

data and the discipline that

16:03

WANT applied to what was traditionally

16:06

performance marketing together

16:09

with that which was the more esoter

16:11

a kind of amorphous brand

16:14

advertising. Because brand advertising, as

16:16

I e. The I want to build the brand

16:18

performance advertising or marketing

16:20

is I want somebody to take an action and

16:22

think of it. With American Express using

16:24

them as the primary example. You

16:27

know you have the don't leave home without it.

16:30

That was the brand marketing membership

16:32

has its rewards, but the

16:34

performance marketing was it's great that you have

16:36

that American Express card in your pocket, but

16:38

are you using it? Because they only make money

16:40

when you use the card. So the

16:43

call to action, the data

16:45

that you use to do that is the data

16:47

that you should be using to do brand marketing.

16:50

Ergo brandformance marketing.

16:52

So that was my little turn of a phrase.

16:54

But it's a good segue.

16:57

Um. It's a good segue because as

17:00

I was having this conversation with Daniel back in

17:02

the day, I said to and listen, I'm

17:04

looking at what you guys are doing on

17:06

on predictive analytics and

17:08

r OI analytics for the financial markets.

17:10

And I said, you know, the

17:13

ultimate, the holy grail. I

17:16

pointed out to him. Look, you have legacy

17:18

data companies like Nielsen, kantor

17:20

com Score that maybe at one point

17:23

represented over billion of market

17:25

cap, and and they're just cratering

17:27

right there there. They've they've gone in half.

17:29

So you have a big open space, and you have

17:32

you have a captive client base

17:34

that really wants a better option. They know

17:37

they need a better option, right, I said, So the

17:39

opportunity is real. I got

17:41

a mutual ally of Daniels in mind. Jim

17:43

Bryer, the legendary excel. You

17:47

see, Jim not only one

17:49

of the one of the great technology

17:51

investors, but also on the board of

17:54

Fox and on Marvel and an early investor

17:56

in Legendary So of all the people. Daniel

17:58

and I knew he had become an invest during Ken Show

18:00

as well. He really straddled

18:03

these worlds and and Jim and

18:05

I convinced Daniel, not only that the that

18:07

the market opportunity was one of those things

18:09

that I al would say, like, you know,

18:11

something's some somethings go very

18:13

slow and then very fast. And it felt

18:16

to me like the post Nielsen moment was being

18:18

talked about, but that at a certain point it was

18:20

going to go very fast and the people

18:22

with the new currency

18:25

positioned with it, who have done the hard

18:28

work to get it ready, will will benefit

18:30

from that and will benefit the market.

18:32

And we kind of convinced Daniel that there was there

18:34

was a there there, and so

18:37

we the reason we started the d O was

18:40

we believed in this concept of

18:42

sort of that there was a data science talent

18:45

arbitrage available in this

18:47

but we know with all respect

18:49

those people who have those capabilities

18:51

do not get hired into these

18:53

markets. But because Daniel it was

18:55

a very celebrated entrepreneur

18:58

and data scientists with great

19:00

success in building Ken Show in the financial markets,

19:03

he had the ability to go to Harvard

19:05

and M I T and Stanford and and

19:07

really recruit the creme de la creme

19:09

of some of the top you know, machine

19:12

learning and engineering

19:14

talent on the planet and

19:16

bring a cohort of them in. And we brought it

19:18

together. And the key piece, because I want

19:20

to have Kevin is we

19:23

knew we could bring an unprecedented cohort

19:26

of data science caliber to this

19:28

problem set. But obviously you

19:30

have to understand the way

19:32

that this sits within the industry.

19:35

And Kevin, Kevin

19:37

was at Universal, NBC Universal

19:39

UM and and we he

19:42

he was. He identified Ken Show as

19:45

an incredible innovation and actually got it programmed

19:47

onto CNBC as the Ken Show stats

19:49

Box, and and helped

19:52

push Steve Burke and Comcast to

19:54

make a co investment with Goldman

19:56

Sachs and Ken Show. And so, you

19:58

know, Daniel said to me, there's this kayat CNBC

20:01

who really gets it um.

20:03

And as we all got talking, we realized

20:05

that Kevin Kevin was you

20:08

know, a key a key

20:10

advocate for CNBC dropping Nielsen

20:13

Ratings as its pricing metric.

20:15

And when we all started to talk,

20:17

Daniel and I just instantly realized,

20:19

like, you know, he was running another company. I

20:21

have a day job too, and we had we had

20:24

put together this really great team, but we needed

20:26

someone who was capable of

20:29

straddling, you know, understanding the Bicell

20:32

ecosystem in a you know, C suite

20:35

kind of way, but also really

20:37

conversing with technology on a level that

20:39

would do it. And so the best thing that happened

20:42

for us was Kevin agreed to leave NBC

20:45

you and come and run video and and

20:47

and basically, you know the last few

20:49

years has been Kevin leading

20:52

the charge on getting our both

20:55

our network you know, advertising sellers

20:57

and all of our brand clients to come

20:59

to understand why

21:02

what we're doing is of higher value

21:05

than the nice to have signals

21:07

that are out there, let alone these kind

21:09

of obsolete UM metrics

21:12

of Nielsen and and and and all the success

21:14

we've had leading up to this fantastic

21:16

investment round. You know, Edward, I want

21:18

to say one thing before I turned it

21:20

over to Kevin. But you

21:22

know, you talked about the actions.

21:25

I'm going to bring it back to kind of dime store

21:27

philosophy, which

21:29

was something I learned from my grandmother. Of

21:32

all things, um she taught

21:34

me when I was a kid not to read people's

21:36

lips, but watch their feet and

21:38

you know it's it's it's

21:41

what you just said. It's one thing to

21:43

think of the signals, it's one

21:45

thing to think of the likes. It's one thing

21:48

to think. But what did they actually do

21:50

is what really matters, and

21:52

if you're a marketer, knowing

21:55

what actually happened. And look, Kevin

21:57

was famous to me before we got to work together

22:00

their e d O because he cut quite

22:02

a path at CNBC and

22:04

and other parts of the digital ecosystem

22:07

that Kevin worked in. And I can't

22:10

imagine a better choice that

22:12

you guys made for someone to be

22:15

in this leadership role with the d O

22:18

because Kevin understood it and reputationally

22:20

the marketplace knew that as well. It

22:22

was so illuminating when at CNBC

22:25

we would put together we would put together these

22:27

massive we'd

22:29

call them three sixty packages back then, right,

22:32

it would be a combination of traditional linear

22:34

and all the digital kind of assets

22:36

that we had be because these huge thirty

22:38

million dollar sponsorship packages for all

22:41

the endemic advertisers at CNBC,

22:44

right, Charles Swabs or the TD marriage

22:46

rads, fidelities, and

22:49

you do a review with them and say, okay, all

22:51

these things that we did for you, you know, what

22:54

would you like us to do more of going

22:56

forward? And they'd say, you know, there

22:58

was this moment where we did the co branded segments

23:01

where we're teaching we're teaching your viewers

23:03

how to do you know, more advanced trading

23:06

on online,

23:08

and we'd see these massive spikes

23:11

in activity on our platforms and

23:14

we'd say, well, that's great, let's let's talk about that

23:16

data. Let's get into it. Well, we'll try to maximize

23:18

that for you. And they say, well, that's that's

23:20

too precious for us. That's that's our

23:22

data. We can't have. Let you have it.

23:24

But it got got us thinking about the opportunity

23:27

to truly level that playing field

23:29

and say, for both the buyce on this outside,

23:32

here's the data of what's working right

23:34

in our Mantra video is know what works?

23:37

The ability to just see it and and

23:39

Michael, I love that, you know, watch their

23:41

feet not their lips kind of advice

23:45

because we see it in the data all the time

23:48

when you do correlations on share

23:51

of search in a competitive category

23:53

and you name it works in insurance,

23:55

automotive, restaurants,

23:58

UH, pharma, and certainly

24:00

in entertainment like movies and streaming

24:02

originals. If you stack

24:04

up shareff search, so of

24:07

the competitive set, who's getting the most shareff

24:09

search it is not only strongly

24:11

correlated with their market share, but

24:14

it's predictive of it. It's an early

24:17

leading indicator. So if you

24:19

see someone gaining shareff search a

24:21

couple of quarters later, and it depends on the category,

24:23

you'll see them gain market share. It

24:26

is the KPI that every CMO

24:28

should have at the top of their dashboard

24:32

every day, every week. And frankly, it's

24:34

the kind of KPI that will level the playing field in

24:36

the boardroom for them. Right the

24:38

CMO is sitting there at a just at

24:40

a literal disadvantage when

24:43

you've got the head of sales, the head of distribution,

24:45

the CFO, the CEO talking

24:48

about results, and then the

24:50

cmos are walking in with g RPS

24:52

and some brand

24:55

attribute survey of favorability,

24:58

and the board is saying, and then, what, okay,

25:01

you reach of your target

25:03

audience. We got a couple of upticks

25:05

in our in our brand survey.

25:08

Then what and what we

25:10

can help connect is that very

25:13

moment that you're talking about, that brand performance

25:15

moment where it's not

25:17

an ore it's an end because rooted

25:20

in what we're doing is the understanding of

25:22

the twenty one century consumer. They aren't

25:24

always connected, always on consumer,

25:26

They are never more than centimeters

25:28

away from a connected

25:31

device. And if they see something

25:33

in the programming, in the content, or

25:35

in the commercial breaks, they see something

25:38

that moves them, moves their hearts and minds, they

25:41

their fingers do the walking for them.

25:44

And that is that is the thing where you can't fake

25:46

it. You can't lie with their fingertips.

25:49

You know, a lot of surveys all the time. I

25:52

tell you, Kevin that we did a conversation

25:55

several years ago during Advertising Week.

25:57

Media Link always has a wonderful

25:59

spot to tell our stories, and

26:02

we did something years ago on the loss

26:04

of serendipity and marketing. And

26:07

you know, we said, here, we all are searching

26:09

for the right device at the right time to the

26:11

right person in the right context. All

26:14

of those things are valid and important

26:17

drivers, but we can't forget

26:19

there is something in marketing called, you

26:21

know, surprise and delight and

26:23

and so if you think of autom manufacturers,

26:26

and I've told this story so many times, but it

26:28

still resonates. You think

26:30

of auto manufacturers, they always wanted to

26:32

reach Edward Norton or or

26:35

Kevin Krim When they're quote in market

26:37

for a car, what does that mean? It

26:39

means your lease is up, it means you just

26:42

got moved to a new center city, your

26:44

kid just got their license, whatever it may be, You're

26:46

in market. So that's when

26:48

you want to get that person with a car. Ad right.

26:51

Well, the story I like to tell it was a milestone

26:54

birthday for me. Yes it was, no,

26:56

I'm kidding, but this was

26:58

a couple of years ago and my wife

27:00

said, do you want to do you want to watch?

27:03

Do you want a party? I said, no, I don't want

27:05

to party, and I you know I've got enough watch

27:08

it. So I was affirmatively not in the market

27:10

for a watch. Okay. I

27:12

picked up a catalog in

27:15

in my house and it opened

27:18

to a picture of a watch, and I went, WHOA.

27:22

I ended up buying that watch. Okay.

27:25

So the surprise and delight of that

27:27

ad, if you will, changed

27:29

my purchase intent. I went from affirmatively

27:32

not wanting it, in fact affirmatively

27:35

saying no, to actually

27:37

buying it. That was serendipity,

27:39

because if I didn't pick up that picture at

27:42

that moment and look at that magazine, that

27:44

catalog. It was actually a department store catalog.

27:47

So I tell that story all the time because

27:49

we want to be precise. We want to get all

27:52

the science and all the data, but we also

27:54

have to blend it in the right way with

27:57

the artistic part of the business. And it's kind

27:59

of a merger of mad men and math

28:02

men. You know that

28:04

that we're seeing, and yet you want to have both.

28:07

How do you how do you manage that? The most frustrating

28:09

thing that I come across is

28:13

the desire to pigeonhole what

28:15

we do into that that's

28:17

sort of small box of oh, well, you're about

28:19

data, you're about performance, or you

28:22

know, the various ways that people want to put

28:24

us, compartmentalize us away into something

28:27

that they don't need to pay attention to. And

28:29

I and I what I do is whenever I'm talking

28:31

to a head of marketing or

28:33

a head of media or head of investment in

28:35

a big agency, I

28:38

said, let's just play a game. I'm gonna open our

28:40

software up and let's pick pick

28:42

one of your favorite brands, and your your brand if

28:44

it's you, if it's a marketer, or when your clients,

28:47

and let's watch two ads. I'm

28:50

not gonna tell you anything about the data yet, we're

28:52

gonna watch two of these ads, and one, inevitably

28:54

all have chosen ahead of time, is going to be a brand

28:56

at right, the big high

28:58

concept, not trying to sell you

29:00

anything right now, don't leave don't

29:02

leave home without it, right exactly. And then

29:05

and then I'll and then I'll show them a you know,

29:07

a limited time offer spot or a sales event

29:09

spot or something that's down funnel

29:11

retail performance. Right. That's

29:14

that's how inevitably their categories. And

29:17

nine and a half to ten times out

29:19

of ten, it's the good brand spot

29:22

that outscores in terms of driving

29:24

people to take actions like going and

29:26

searching for the brand, going to the

29:28

website, going to a shopping site to look for

29:30

that brand, all those actions. It's

29:33

the brand ad that drives more of that. It's

29:36

significantly more about. The single best ad

29:38

in all of non Luxuria Automotive last

29:40

year was a spot from Toyota

29:43

during the Summer Olympics where they were showing

29:45

a group of young women teammates

29:48

piling into a self driving car, a

29:50

car that is purely a concept. It won't

29:52

be available for probably the next decade, and

29:54

the cars, playing songs with them, singing

29:56

with them, doing karaoke with them.

29:58

It was a fantastic ad. It

30:01

has nothing to sell right now for Toyota,

30:04

nothing in the next decade. And it was

30:06

the highest performing single ad in all of non

30:08

Monchy automotive. And you know

30:10

it's the it's a surprising delight, My daughter said

30:12

next. And he knows that we worked closely with Toyota, so

30:15

she pays attention and she's she

30:17

says, is that from Toyota?

30:19

Is that really from Toyota? And

30:21

it had changed her mind about what Toyota could

30:24

be for her. She's thirteen, but

30:27

she will be behind a car in the next decade.

30:29

Absolutely, No, you gotta plant the seed early. I

30:31

mean, you know, I learned this back in the day

30:34

working with Home Depot.

30:37

The highest selling Skew branded

30:39

Skew at Toys r US back in the nineties

30:42

was the Home Depot tool Kit

30:44

for kids. So you know, kids grew up with play

30:46

school or whatever it might have been that, you

30:49

know, the hardware kids whatever, you know,

30:51

the tool kids. That was the word

30:53

I was looking for. And Home Depot branded

30:55

at Home Depot and again

30:57

it was the highest selling branded Skew and so

30:59

I Toys, r US and the old days. And I said,

31:01

well, of course, because you know, I

31:04

was taught a long time ago. You don't want

31:06

to start advertising a Mercedes to somebody

31:08

when they can afford it. You want to start advertising

31:10

it to them when they when they're aspirational,

31:13

so that when they can't afford it, that's the

31:16

that's the standard, that's what they're looking for.

31:18

Home Depot took the same approach. So you're

31:20

absolutely right. You know

31:22

your daughter is not ready to buy a car yet or are you

31:24

ready to buy her one, but you will be shortly,

31:27

trust me, you'll be buying it. And you

31:29

know as a result of that, you're right because the

31:33

nagging of kids, by the way, we did

31:35

a study years ago called the nag factor. You

31:38

know, not in a pejorative way, nagging,

31:40

but you know, what's the value of getting

31:42

the kids to nag on the parents to do something?

31:45

And how do you do that? Yeah?

31:47

Yeah. One of the things I'm proudessed of, Michael

31:50

is that the we've been working

31:52

with Disney both on the as

31:54

the studio, marketing, their originals,

31:57

marketing, Disney Plus and Disney

32:00

all in the ads for across their family

32:02

of networks. The protesting I am is

32:04

that that the creatives at the studio

32:06

at Disney Folks cutting the

32:08

thirty second and fifteen second spots for their films

32:11

all the way up to a who

32:14

runs the whole marketing division, they

32:16

can't wait to see our data about their new

32:18

spots. They are

32:21

clamoring for it first thing

32:23

in the morning, before the first cup of coffee. Because

32:25

it's completely non judgmental. It just

32:28

tells them what's working right. It leaves

32:30

their judgment to figure out what

32:34

should we do from here? Well, I

32:36

can tell you, Kevin, and I will tell our audience

32:38

how right you are. We we lead in

32:42

the global review for the Walt Disney Company

32:44

to determine working with the sod

32:47

and the team, and you know,

32:49

to determine who was going to be the person placing

32:51

billions of dollars of media on behalf

32:53

of the Walt Disney Company globally. And

32:56

I know how important this is because the work

32:58

we did around Disney Plus was

33:00

really again that illustration

33:03

of the brand formants. Because traditionally

33:06

the Walt Disney Company, as all

33:08

the studios were marketing to put

33:10

butts and seats on Friday, Saturday and Sunday

33:13

when Edwards opening a movie. And on

33:15

the one hand, with Disney Plus

33:17

and the streamers, everybody had to reassess

33:19

and it gets to the brand formants. They

33:21

had to reassess that their marketing muscle

33:24

needed to be put against subscriber

33:26

acquisition and avoiding

33:29

churn. And that's a different marketing

33:31

muscle as we talked about earlier.

33:34

So you're spot on relative

33:36

to how that impacts not only what a sod

33:39

and and the marketing site puts on the air,

33:41

but it has massive impact for what Rita

33:43

Pharaoh and Lisa Valentino and the people in

33:45

their group are selling. So it's

33:48

it's both sides of that equation, not

33:51

you know this chime in that there's these

33:53

other like there's

33:56

multiple derivatives of efficiency

33:58

that flow out of a

34:00

data insight capability

34:03

that lets you see in

34:05

market in real time what's

34:08

getting a type of grab that

34:11

you come to have confidence really

34:13

lines up with purchase intent, right and

34:16

and one of them you're kind of you're talking

34:18

around it, but it's worth saying because you you

34:20

were kind of saying this in our

34:22

conversation earlier, Michael, think

34:25

about the amount of money that historically

34:27

any kind of marketer has spent

34:30

in the lab trying

34:32

to score the sentiment

34:35

around something right, not really knowing

34:38

whether lab based analysis

34:40

of sentiment lines

34:42

up with any of the things that actually

34:45

matter in terms of the actions of summer

34:47

take right, But think about the amount of money that's

34:49

wasted. I would argue

34:52

trying to do lab assessment when a

34:54

lot of our clients are starting to realize

34:57

they can literally cancel that

35:00

at lab analysis market testing

35:02

budget because they can do an

35:04

A and a B creative take

35:07

a package of low cost cable inventory

35:10

just to a B test in the

35:12

same target market type

35:15

of thing. They can put one up and put the other up,

35:17

and they can the same dollars

35:19

they would have spent in the lab not actually

35:21

even putting it in the marketplace. They can put

35:24

it in the actual marketplace and

35:26

watch in real time what

35:28

gets the purchase intent

35:31

grab from the actual

35:33

market. So literally your whole

35:36

lab testing budget goes

35:38

direct into into actually

35:41

putting spend out into the world, and you get a

35:43

higher grade analysis of which of your

35:45

creative variations works in

35:48

real time in the market. Are you sure you're

35:50

not a secret media buyer. Yeah,

35:53

but literally

35:56

again again, I know, but again again.

35:58

Think about it. From my into view, every

36:01

dollar spent testing thirty

36:03

second ad spots for a given movie

36:05

is just lost leader for all of us who

36:08

are trying to make money on the back end. Right, If

36:10

you put a thirty second ad number one joker

36:12

and thirty second add number two and you put them

36:14

up against each other, then at least it

36:17

was ads and Warner gets to see

36:19

in real time, Wow, that one really

36:21

takes. It has a little more humor in it. It. Who

36:23

knows why, but it takes. Now we can just lean

36:25

into that one and get more value

36:29

out of the thing. But we didn't waste some money

36:31

on some supposition all you know, God

36:34

forbid. Like my the test

36:36

audience and the commentary of the focus

36:38

group literally should end in

36:40

the world. I mean, it's it's it's the

36:43

single worst experience for a director,

36:45

for a commercial director, for an ad marketer.

36:48

No one should ever talk to a focus group

36:50

ever again, because they lie, their

36:52

egos come into it. It's the worst

36:55

way to assess anything that

36:58

there is. And and you know, we we

37:00

we have a funny thing with the universal guys when they

37:02

were doing fifty

37:05

shades of gray right, Like the market

37:07

was telling them that they were going to do

37:09

like sixty five and our guys were saying, no, you're

37:11

gonna do like a hundred and ten in the opening

37:13

weekend. And this is a direct function of what we're

37:15

talking about. If you survey people

37:18

and RG style and say hey, are

37:20

you going to see fifty shades of gray

37:22

eight subtext are you up for a little light

37:25

bondage this weekend? A lot of

37:27

people in a survey are going to say no. But

37:29

their search what they're searching

37:31

at home, the very gods

37:36

Yeah, sitting in their underwear saying, you know,

37:38

Dakota Johnson imagery combined with fifty

37:40

shades of gray showtimes near Me tonight tell

37:43

the tell a much more

37:45

accurate story about their appetite

37:47

for B DSM than if you survey them,

37:49

right, And that's that's that's

37:51

a really obvious one. But I think, um,

37:54

I mean, you know, it's funny you say that

37:56

about the predictive so years and years

37:58

ago, and and this is really a story worth

38:00

telling. We

38:03

we came up with a strategy when I was running

38:05

a media agency which was

38:08

looking at the theatrical release

38:10

and the home video and the windowing and

38:13

what I what I posited and we proved

38:16

it was that on Friday morning

38:18

of a week opening weekend, by

38:20

whatever time in the morning, you

38:23

should be able to predict the entire

38:25

life cycle value of that product. You

38:27

should know what home video is going to

38:29

do within a plus or minus ten percent, because

38:32

you know what the box office did. There are examples

38:34

of exceptions, but by

38:37

whatever moment you know that opening weekend

38:39

gross, you should be able to calculate

38:42

the entire value of that

38:44

product through its windows. And as a

38:46

result, you should be able to set your marketing budget.

38:49

Because this was around setting the marketing budget.

38:51

And it was a guy named Warren Lieber far pretty

38:53

famous in the day at Warner for

38:56

creating the DVD literally

38:58

and you know, he said, I should be able

39:00

to know the marketing budget of that movie for home

39:03

video the moment it opens in theatrical

39:05

and he was right, because you should be able to predict

39:08

based on what the theatrical opening that opening

39:10

Friday is going to be is going to tell you what the home video

39:13

volume is going to be. And it's

39:15

that data that kind of should be informing

39:17

everything we're doing. The focus group

39:20

could never tell you that the box office on

39:22

Friday, And to

39:24

take another category of it now we're talking

39:26

about for the marketing side. But one of

39:28

the reasons that some of the top top

39:30

network ad sellers have really

39:33

you know, and I don't know Kevin mentioned to

39:36

earlier, it just it happened to line up with this

39:38

big investment round we just took in. But you

39:41

know, Discovery Networks announced that

39:43

video is their preferred core

39:46

measurement analysis metric, which

39:48

is thrilling for us, but in some ways

39:50

unsurprising because we've played

39:53

a central role in

39:55

affirming to Discovery that they've got a

39:57

huge percentage of this shows that

40:00

deliver the bank for the buck in

40:02

the whole industry. And if you're

40:04

a seller, think about the fact

40:06

of the persuasion that you've

40:08

had to do around

40:11

the notional reach of

40:13

what your show provides. Right, it's it's

40:15

such a soft science. Well, these number

40:17

of people watch our show and this' it's kind of

40:19

what Kevin said, Yeah, you you

40:21

you've got to x number of people notionally

40:23

and then what right, if suddenly

40:25

you're able to see a massive

40:27

regression analysis of the way

40:30

that you've driven purchase intent inflection

40:32

on a specific show. Everything you're

40:34

getting out of the weeds of generalities and you're

40:36

able to say, hey, look like

40:39

Kevin said this, this may this may seem like

40:41

an noun sexy show, this home improvement show,

40:43

but look what it moves relative

40:46

to other things for certain types of people.

40:48

What does that open up? And and a particular

40:51

head of all ad fills at one of the major networks

40:53

said to us, my god, like, you know,

40:56

we've stood here and watched financial market

40:58

operators build struct heard products around

41:01

bond yield or credit default swaps or

41:03

whatever, and sat here just thinking, why

41:05

can't we sell optimized pods

41:08

of structured product on our advertising

41:10

because we don't have sophisticated

41:12

analytics that give us a data driven,

41:15

finance grade analysis. We're

41:17

trying to open up for the

41:19

sell side the capacity

41:21

to build unprecedented sophistication

41:24

into the way they package

41:27

their inventory and structured products

41:29

for specific clients. Right, And if you

41:31

think about what's going to bring the yield back

41:33

to television, you know that's

41:36

the kind of thing that that will transform it. Because

41:39

you know, and this may be a controversial thing to say,

41:41

but I would argue that after all

41:43

the romance with the idea that digital

41:45

was more you know, effective, I

41:48

think it's kind of gone the other way. In digital. There's

41:50

been a realization that a lot of what

41:52

Facebook and other people assert is

41:55

kind of being blown apart by really smart firms

41:58

that are showing, well, you know, it didn't get

42:00

off mute, or it never really

42:03

got watched in anything other than picture and picture.

42:05

And the truth is a lot of what goes out in

42:07

digital blows by and is being

42:10

shown to be less effective than

42:12

people thought, Whereas what we're

42:14

doing is showing people

42:17

that television is as or

42:19

more effective than they even

42:21

thought. And it's

42:23

just in some sense, I

42:26

think the television advertisers

42:28

have had one hand tied behind their back because

42:30

they the meaning the

42:33

networks. They haven't been able to show what they

42:35

believe to be true and that it is in

42:37

fact true, which is that they

42:40

deliver the effect, meaning

42:42

that they move people to the

42:44

action that does actually tend to

42:47

line up with conversion. You know what I mean? Yeah,

42:49

No, absolutely, And look here's what

42:51

I would say, Edward and Kevin, this

42:53

is a conversation that you

42:55

probably can tell that I would love to have for

42:58

hours.

43:00

This is bread and butter to me. And you know, as

43:02

I said to you and were in the sort of

43:05

green room before we were recording,

43:08

I'm a believer that our industry is

43:10

pivoting on a couple of words,

43:12

and those words are all with the tea.

43:15

As I said, you know, trust, transparency,

43:17

technology, transformation, and talent.

43:20

And I think I actually said it on the broadcast

43:22

as well. You guys are speaking

43:24

truth to power, if

43:27

you will, relative to trust and

43:29

transparency, so that people

43:31

can make those decisions

43:33

more real time. And look, one

43:35

of the dynamics in the industry that makes

43:38

E d oh so much more important than it

43:40

would be anyway is the

43:43

importance of procurement. And you know,

43:45

inside the organizations that

43:47

we're talking about wanting to

43:49

prove the efficacy of the spend because

43:52

at the end of the day, you need to do

43:54

that because when you have the bean counters

43:57

looking at it more critically and

43:59

under standing that you want to make sure.

44:02

You know, the basic premise of the advertising

44:04

industry is to be able to if you're an agency

44:07

or somebody placing media on somebody's

44:09

behalf, you're really not unlike a

44:11

mutual fund anyway, what you're hoping to render

44:14

as a return on investment. What I

44:16

think E. D O is able to demonstrate is

44:18

you don't have to waste any of it anymore. The

44:20

other thing I would say

44:23

is it's almost like within the marketplace

44:25

of the new there's there's a lot of noise,

44:27

there's a lot of assertion going on right I

44:29

think one of the things we've we've

44:31

been increasing willing to say is like we'll

44:33

we'll throw down the glove and have an academic data

44:35

science debate with literally absolutely anybody

44:38

who wants to try to pigeonhole search

44:41

into a niche like we

44:44

think everything else is nice

44:46

to have, and and we'll throw down

44:48

and say that not one thing anybody's pitching

44:50

you, um that that

44:52

is not within that. In

44:55

terms of mid funnel efficacy outcome

44:58

measurement, we don't

45:01

think there's anything that can stack up

45:03

as as a as an authentic

45:06

investment grade metric of what your financial

45:08

outcomes are going to look like an

45:10

efficacy like we've you know, top of

45:12

the funnel stuff, bottom stuff

45:15

maybe, but if you want to know literally whether

45:17

you're getting what you paid for in real time, we

45:19

will say I'm on the stage and

45:22

and have the academic debate about

45:24

why the components of

45:26

our signal are are higher grade

45:28

and actually line up with a much higher

45:30

correlation to purchase

45:32

intent and ultimate financial outcomes.

45:34

And part of the reason, you know, sometimes

45:37

what people says, well, if that's true, then you know

45:39

why is more people doing it? And here's

45:41

the answer is it's fucking

45:44

hard, like really really hard

45:46

to think about what it means to say

45:48

you can sort and scrub from all

45:51

of search that's happening all the time, the

45:53

granular specific around

45:56

each and associated with in

45:58

a time stamped way, with each and repiece

46:00

of advertising. It really is like that scene in the

46:02

Matrix of saying, I can see what's

46:04

going on as the numbers fall past me and

46:07

the bottom line is A woman

46:09

who built the Google Trends product at Google who

46:11

ended up working at Ken Show literally

46:13

said to our team one time, I'm

46:16

not even sure there's I think there's people

46:18

at Google who don't even know that this is possible

46:20

at the scale that you're doing it. We've done it in a white

46:23

paper sense, like in short form,

46:25

highly specific sort of minute by minute

46:27

resolution demonstrations, but

46:29

on an industrial scale, we don't

46:32

think there's anybody who's even

46:34

close to being able to pull off technologically

46:37

what Daniel and and our amazing

46:39

team have kind of pulled off on

46:41

a technological sense. And that's that's

46:44

one of the reasons I think people have a

46:46

hard time wrapping their head around can

46:49

this actually be true? Because it is. It

46:51

is literally like matrix like vision

46:54

of what's taking place in real time, and it's

46:56

it's it's pretty phenomenal. Um, you

46:59

know, and I think here's what I'd say,

47:01

Um, there are times and and

47:03

and it's a great fine point to kind of close

47:06

on. There are times where something

47:08

feels like it's too good to be true, but actually

47:10

it is true. And what it sounds to

47:12

me like and and this is a great

47:15

compliment. Please take it as such. You've

47:18

identified with the d O something

47:20

that might sound like it's too good to be true, but

47:22

it's actually true. Any

47:25

time I can end up a podcast by quoting

47:27

Oscar Wilde, I will, because

47:29

I think you're taking not cynical,

47:32

but you know the great definition Oscar

47:34

Wilde ascribed to a cynic with

47:36

somebody who knows the price of everything and the value

47:39

of nothing. And you

47:41

know what, what you've just articulated

47:44

is there is a relationship between

47:46

the price and the value? Edward

47:48

and Kevin, I I can't thank you enough

47:51

for one of the most robust conversations

47:54

that I've had on Good Company. And I've

47:56

been doing this for you know. You

47:58

were nice to say, I'm not a reporter. I've been

48:00

doing this for a minute or two, and

48:03

this is one of the most enjoyable and

48:06

illustrative conversations of

48:09

an opportunity and a challenge on a marketplace

48:11

issue. So Edward Norton

48:13

and Kevin Krim, thank you so much

48:16

for for for sharing your thoughts.

48:19

Absolutely, I'm

48:26

Michael Casson, thanks for listening to Good

48:29

Company. Good

48:31

Company is a production of I Heart Radio.

48:33

A special thanks to Lena Peterson, chief brand

48:35

Officer and Managing Director of media Link for

48:37

her vision I'm Good Company, and to Jen Seely,

48:40

Vice President Marketing Communications of media

48:42

Link for programming amazing talent and content