0:00

This week on the

0:02

Salesforce-Admins podcast, we're joined

0:04

by This week on the

0:06

Salesforce Admins of the we're joined

0:08

by John Wall, cohost of the

0:11

Over Coffee Over Coffee That's right, That's

0:13

right, we're starting 2025 off on foot,

0:15

right foot, because John shares

0:17

with us the into the ever -evolving

0:19

landscape of AI and marketing,

0:22

including how tools like Generative AI

0:24

are reshaping workflows, strategies, even and

0:26

even content creation. I bet admins,

0:28

you know about this. we Now,

0:30

before we jump into the

0:33

fascinating discussion that we have with

0:35

John, I want you to be sure

0:37

to jump over over and press that

0:39

subscribe or follow button, depending on

0:41

what kind of app you're using.

0:43

It's probably on your favorite platform.

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favorite And then And way you don't

0:47

miss a single episode because new

0:49

ones come out every Thursday Thursday

0:51

I would hate for you to

0:53

miss something like this discussion that

0:55

I'm going to have with host

0:57

of the of the marketing over marketing over coffee

0:59

podcast. on the podcast. get John on

1:02

the podcast. So John, welcome

1:04

to the podcast. welcome to

1:06

the podcast. to be on the it's great to

1:08

be on the mic with you again. I know

1:10

I know it's been a while. feel the I feel

1:12

the last time we recorded was in Boston. Boston.

1:14

A 100 years ago. ago. Yeah, downtown Boston.

1:16

remember we were alive on we were alive

1:18

That was like the heart of

1:20

all the action. was We were recording

1:22

the old style Yep. We were had an

1:25

Edison the was putting it on a

1:27

phonograph We had some wax tubes. putting it on a

1:29

phonograph and there with my ear trumpet Sitting

1:31

there with my ear Ear trumpet. I love

1:33

it. I love those people, like the two

1:35

people in the world that don't

1:37

listen to marketing over coffee, over can

1:39

you give us a brief overview of

1:42

what you do do and marketing over

1:44

coffee is? coffee is? Yeah, sure. sure. I've, you

1:46

know, my whole you know, my whole career worked

1:48

in marketing and tech. tech and, God, going

1:50

on 16, 17 years 17 years

1:52

ago, was podcasting was just

1:54

done with steam engine and

1:56

hammers and nails. created We created marketing

1:58

over coffee with my co- Christopher Penn

2:00

and we've had this ongoing dialogue of

2:03

just every week, you know, 25 to

2:05

30 minutes talking about what's going on

2:07

in marketing and tech and, you know,

2:09

just like CRM, the space is so

2:11

insane and changing every week. There's no

2:13

shortage of stuff to talk about. But

2:16

then, and it's also grown up enough

2:18

that I've been fortunate enough to get

2:20

a lot of big marketing brains and

2:22

authors on like Simon Sinek and Debbie

2:24

Millman, Seth Godin, folks like that. So

2:26

yeah, it's really kind of opened up

2:28

the world up the world because You

2:31

know, the family doesn't want to hear

2:33

what I have to say about marketing

2:35

over Thanksgiving, so I have somewhere to

2:37

talk about that. Oh, that could be

2:39

another, you should rename the podcast that

2:41

for the holidays, marking over Thanksgiving. Just

2:43

see if anybody notices. That glazed over

2:46

luck when I'm talking about what I

2:48

do for a living. So I make

2:50

ads, I'm like John Hamm on madmen.

2:52

No, I and I remember the Boston,

2:54

so much of what admins do, I

2:56

remember, is interfaced with marketing. And that's

2:58

why I love having you on, because

3:01

not only as a personal brand, but

3:03

also, you know, as somebody that does

3:05

a lot of. podcast and content creation,

3:07

it just overlaps with what admins do

3:09

and marketing, you know, is such a

3:11

big facet of any organization now. I

3:13

mean, you can't sit down and talk

3:16

sales with how, well, we should have

3:18

the marketing person in here and they

3:20

always want, you know, 5,000 more requirements

3:22

than what you started with, but that's

3:24

why I love having you on. So.

3:26

Let's dive in. It's, I feel like

3:28

we woke up from the pandemic and

3:31

AI just was everywhere now. I'd love

3:33

to know on what the world of

3:35

AI looks like for marketers now. Yeah,

3:37

it's, I mean, you totally nailed that

3:39

and that the world has changed yet

3:41

again. We were kind of finally, things

3:43

were finally stabilizing a little bit, you

3:46

know, platforms that mature as far as

3:48

email and text messaging and advertising and

3:50

things are fairly. solid and now AI

3:52

has shown up to destroy everything. It's

3:54

been a little weird though because our

3:56

world didn't change as much. We've been

3:59

working a lot with machine learning to

4:01

do data analysis for years. So my

4:03

co-host on the show and partner at

4:05

Trust Insights, Christopher Penn, had long been

4:07

using machine learning to measure PR and

4:09

advertising results. you know, doing statistical models

4:11

to prove like, okay, what's actually working

4:14

in your, your branding and your advertising,

4:16

these things that you can't easily measure

4:18

with clicks. And so that has been

4:20

an area where we were able to

4:22

kind of provide some value and insight

4:24

that nobody else could get. But then

4:26

really, I don't know, about a year

4:29

and a half ago when generative AI,

4:31

you know, became the hottest thing going

4:33

on all fronts for marketing. the amount

4:35

of interest in that has just exploded.

4:37

So yeah, we have a bunch of

4:39

fronts that we're applying the technology, and

4:41

it's just amazing to see the range

4:44

of how marketers adapt. You know, there's

4:46

still plenty of marketers that don't want

4:48

to look at it and have their

4:50

head in the sand, and all the

4:52

way up to, you know, we have

4:54

clients that are like, hey, we want

4:56

to reimagine our entire business because we

4:59

think it's going to be something completely

5:01

different, you know, in the next five

5:03

years. Yeah, we spent a lot of

5:05

time thinking about where this stuff is

5:07

going to go and it's amazing how

5:09

it and literally we have Christopher works

5:11

full-time on monitoring the space and seeing

5:14

what's new and what's coming next Because

5:16

it's it's just insane when you look

5:18

at the fact that we've had like

5:20

six major models You know this year

5:22

there's never been a time in tech

5:24

history where you have six major products

5:27

show up at once so kind of

5:29

yeah, everything is changing and it's a

5:31

just a challenge to keep track of

5:33

what's happening this week Yeah, I remember

5:35

not that long ago, thinking how long

5:37

in the tooth we've been working in

5:39

tech, when I heard some statistic of,

5:42

you know, today we'll create more content

5:44

than was ever previously created in human

5:46

history. So, you know, now with AI,

5:48

are we exponentially creating more? Are we

5:50

creating better content? Is that the conversation?

5:52

Like, I always dig into like, what's

5:54

that next layer down? Like, are we

5:57

really caring about creating better content with

5:59

AI? Or are we just creating more

6:01

content with AI? Right. Well, of course,

6:03

you know, marketers ruin everything, right? Like

6:05

this is nothing new. Yeah, there's a

6:07

whole army of people that are taking

6:09

the stuff that was pretty crappy and

6:12

now we have an exponential amount of

6:14

pretty crappy stuff out there. So yeah,

6:16

and it's going to be really weird

6:18

to see how all this goes because

6:20

it's the classic antivirus defense too. It's,

6:22

you know, as soon as people are

6:24

creating exponentially more junk, all of the

6:27

search engines or AI powered search engines

6:29

are adding defenses to that, you know.

6:31

pull all that stuff back out so

6:33

it's just this never-ending battle and yeah

6:35

the level of content I don't know

6:37

it's so much so that you know

6:39

we're gonna burn more electricity like in

6:42

the next year than the power of

6:44

the sun I mean it's just insane

6:46

how this is all changing but we'll

6:48

have better copy for our website you'll

6:50

have a better landing page it's it's

6:52

gonna it's gonna convert for you but

6:54

then we do see you know as

6:57

with everything right there's people that are

6:59

using the the technology to automate the

7:01

foolishness of the past. You know, we

7:03

have like electronic yellow pages being created.

7:05

But at the other end, there's people

7:07

who are using these tools and, you

7:10

know, totally brand new and novel ways

7:12

to get some insight that they've never

7:14

had before or automate things that used

7:16

to be just insanely difficult to automate

7:18

and, yeah, go to new places and

7:20

create advantage. So there are ways to

7:22

win and there's, there's going to be

7:25

a ton of things that we never

7:27

even expected that will change everything for

7:29

us. I mean the biggest thing a

7:31

few before AI the the wave of

7:33

AI hit the biggest thing we were

7:35

dealing with was data lakes and you

7:37

know these massive. data volumes

7:40

and I think

7:42

even marketers were dealing

7:44

with that with that too

7:46

you have know you

7:48

people going to their

7:50

website and they're

7:52

unauthenticated you know and

7:55

we're assigning a

7:57

profile to them a profile

7:59

to them know how

8:01

do we dig through

8:03

when you've got

8:05

millions of impressions on

8:07

a page what

8:10

was that journey of

8:12

that person how

8:14

did they actually get

8:16

to the pair

8:18

of shoes that they

8:20

bought the pair of shoes that they

8:23

bought now with AI Are we getting smarter

8:25

at doing that? Is that is is of

8:27

the of the the the that we're digging

8:29

into? into Yeah, Yeah, absolutely. so yeah,

8:31

when you look back, you back and

8:33

look at the landscape, the landscape, you know,

8:35

we consider that one of

8:37

only six different options

8:39

to use AI you places. get

8:41

you places. And two

8:43

of them, extraction and just what that's

8:46

just what you're talking about. It's like

8:48

to finally be able to have all

8:50

of these different data sources all

8:52

over the place, load them up into

8:54

a system and have it do

8:56

the heavy lifting of, okay, find the

8:58

commonalities between these things. things. And just, you

9:00

know, we had been promising this for

9:02

decades, this idea that, you know, know,

9:04

when people in marketing talk about personas,

9:06

that's just because like four people in a

9:08

conference room like came up with. a conference room

9:11

like and an idea of who these people should

9:13

be, know, they're like, of yeah, know,

9:15

be. You know, they're like, know, know,

9:17

George Shopper and, you know, George, George Weekend

9:19

or whatever. whatever. But now you

9:21

can get actual summarizations based on the

9:23

data itself. And you know know that, we do

9:25

see that, we do see that look like %

9:28

of the buyers look like this and

9:30

they have these things in common. And

9:32

it's all based on statistics, none of

9:34

it's based on gut. So yeah, those kinds of

9:36

insights are kinds of insights are really

9:38

interesting. We've actually been pushing another

9:40

level. level. you know you can go ahead

9:42

and create these profiles of who these

9:45

people are, but then but then those profiles

9:47

to train the large language models. models so now

9:49

that you can actually treat that as

9:51

a customer on demand, that you can

9:53

and ask questions. So ask questions you know instead

9:55

of everybody with every purchase of

9:57

35 cents to ask for feedback

9:59

on. on what's going on, you just go

10:01

to the large language model and say,

10:04

hey, here's the, you know, next four

10:06

marketing campaigns. Tell us what you think

10:08

about those and does this resonate with

10:10

you? And, you know, you can get

10:12

similar insight, but not cause as much

10:15

trouble and not have to wait. You

10:17

mentioned six, I think you gave us

10:19

one or two, what were the other

10:21

four? Yeah, so obviously, generative AI, you've

10:23

got generation, we just talked about extraction

10:26

and summerization. The other three, rewriting, rewriting,

10:28

rewriting, rewriting, rewriting. which is just something

10:30

that can easily raise your productivity, right?

10:32

If you're somebody who's having to, you

10:34

know, okay, I wrote this white paper

10:36

for the construction industry, I want to

10:39

write about the same kind of stuff

10:41

for the food service industry. Rewriting is

10:43

very easy and instant for generative AI

10:45

to do. Classification is another use case.

10:47

We see this a lot where, you

10:50

know, people that have multiple products, they

10:52

don't know how they fit in together,

10:54

or even if you just have large

10:56

amounts of data. A good example is

10:58

for a call center, you know, you've

11:01

got 30,000 calls a month to have

11:03

AI transcribe those and go through and

11:05

find, you know, the 20 features that

11:07

you should fix to make 10% of

11:09

your calls go away. That kind of

11:12

stuff is a huge benefit, huge lift.

11:14

And then out of six, yeah, the

11:16

last is just question answering, you know,

11:18

you know, you know, you can. really

11:20

get better insight into topics than search

11:22

engine results by asking AI to not

11:25

only give you the answer, but explain

11:27

how it got there and educate you

11:29

on, you know, what do you need

11:31

to know to kind of understand the

11:33

space a little bit more. And I

11:36

think we're seeing, I mean, from the

11:38

sales force side, we're showing a lot

11:40

of use cases and we have a

11:42

lot of customers that are standing up

11:44

agents on public facing sites. Are you

11:47

seeing that more and more as a

11:49

trend for... marketers to work with. I

11:51

think one of the things as I

11:53

say this, one of the stereotypes that

11:55

most marketing falls into is how do

11:58

we drive more sales. But I think

12:00

a lot of marketers are also how

12:02

do we divert service cases as well

12:04

and drive sales through service? Are you

12:06

seeing agents on public facing websites as

12:09

something marketers are paying attention to for

12:11

that? Yeah, I mean everybody wants that

12:13

right and unfortunately, you know, we've all

12:15

seen this cycle this happens where you

12:17

know, there's the board meeting and the

12:19

board is like saying hey, we got

12:22

to get onto this and so now

12:24

somebody's like, okay, I need to get

12:26

me one of these shiny object things

12:28

and you know unfortunately it's mostly disasterville

12:30

right we were seeing these things of

12:33

people hooking up you know a chat

12:35

bot or whatever and it's starting to

12:37

just spout off lies and crazy answers

12:39

and it just becomes a train wreck

12:41

so yeah that is one thing that's

12:44

going to be huge over the next

12:46

couple years the idea of okay yeah

12:48

you've got you know these bots or

12:50

these agents but you know which ones

12:52

are enterprise ready like there's a huge

12:55

difference between something that's been vetted and

12:57

tested If for most of our clients

12:59

we're saying, no, you need to have

13:01

a human in the loop, you, like

13:03

a great, the use case that you

13:06

just talked about would be, yeah, have

13:08

the AI generate, you know, the top

13:10

2,000 answers for problems that it sees,

13:12

but then that goes through the product

13:14

manager for verification to prove that it's

13:16

all real. You can't go live with

13:19

that, but yeah, there's definitely going to

13:21

be a lot of, unfortunately, going to

13:23

see a lot of scary news as

13:25

people, you know, Well, that's kind of

13:27

like we saw the, you know, we're

13:30

not ready for the self-driving cars. We've

13:32

seen that in San Francisco, but they

13:34

still have somebody in the passenger seat

13:36

or in the driver's seat just in

13:38

case. You know, the human in the

13:41

loop. Right. And that's always, even, you

13:43

look back in history and it's like,

13:45

yeah, escalators and elevators, like, you know,

13:47

there used to be people that's out

13:49

with their job just to make sure

13:52

that nothing went wrong. Right, exactly. And

13:54

yeah, you know, there are, well, yeah,

13:56

it's just, so much of that is

13:58

the media and the... the the way

14:00

information gets presented to us as news.

14:02

know, it's like, as news, you these three automated

14:04

cars got in some kind of weird accident.

14:06

got we're not getting the story of, you

14:09

know, all the ridiculous stuff humans did

14:11

over the past month in cars. Like that's

14:13

just not news did over the past month in

14:15

cars, You mentioned not news or

14:17

the beginning sort of

14:19

the mentioned at the beginning, sort

14:21

of the great, the spectrum of marketers

14:23

with their head in the

14:25

sand we the way to we

14:27

wanna revolutionize our business. our business.

14:30

Where do most marketing's fall terms

14:32

of thinking with AI, AI, thinking

14:34

about AI? where should that be? Yeah,

14:37

should that be? question because

14:39

it's that's a great question because

14:41

it's really, a retooling lot of ways this

14:43

is a retooling for of have to go back

14:45

of have to go back and look

14:47

at all your processes. and and figure

14:49

out which ones apply. because you've talked about

14:51

this in the past, the the fact

14:53

that. that It's not not about

14:55

AI showing up and it's just the

14:58

the marketing department is gonna get wiped

15:00

out. What's gonna happen is over time,

15:02

there's gonna be three or four marketers

15:04

that have added AI to a bunch

15:06

of their workflows, bunch of that they've hated

15:08

doing and so they figured out how

15:10

to automate them. And so And those people

15:12

are gonna be exponentially more productive than

15:14

the folks that are avoiding AI and

15:16

trying to stay away from it. are avoiding AI

15:18

and trying to stay of where people should be.

15:20

The big thing is, should be. You You

15:22

have to be curious, know, it's just like

15:24

with every other major tech tech change, go start playing

15:27

around with something and see what you can

15:29

make it do and what kind of results

15:31

you can get out of it you can get out

15:33

of it. this stage stage of you're going to find

15:35

these really crazy things. You're like, oh man,

15:37

I never thought that I could use that

15:39

to, you know, come up with an intelligent

15:41

email address predictor. email Every sales and marketing

15:44

person has this where they're like, oh, I

15:46

have to get in touch with this person.

15:48

They haven't put their email on the social

15:50

networks that I normally follow. follow. And so, you know, you

15:52

know, getting some suggestions. that do that kind

15:54

of stuff. And the one is, yeah, so much of so

15:56

much of marketing is combing through spreadsheets and

15:58

trying to know, prove results manage. copy and things

16:00

like that. Like all so much of

16:03

that stuff can be automated and give

16:05

you hours back in your day. So

16:07

yeah it's a matter of having you

16:09

know be bold play around and kind

16:12

of see what you can break. Yeah

16:14

I think back to and I've tried

16:16

to look this up but I've heard

16:18

the story of in the late 1800s

16:21

I forget who it was I want

16:23

to say Thomas Jefferson but it's probably

16:25

not right writing a letter to the

16:28

US Patent Office saying you can shut

16:30

down. because everything that's been invented has

16:32

been invented and and and correlating that

16:34

to you know we can't let cars

16:37

happen in the world because they'll put

16:39

wagon wheel manufacturers out of business and

16:41

in the labor force of wagon wheel

16:43

manufacturers it will be devastating to the

16:46

economy that all these all these wagon

16:48

wheel manufacturers will go out of business

16:50

and you know I think back to

16:52

Well, they just didn't understand if you're

16:55

a wagon wheel manufacturer, you're just really

16:57

good at making things with wood. And

16:59

if cars come around, then make things

17:01

with wood for the car as opposed

17:04

to making wagon wheels. And I feel

17:06

like we're in that age now where

17:08

people are, if AI comes out, he's

17:10

going to take my job. Like, AI

17:13

can generate an image, there's no more

17:15

graphic designers. Like, no. Have you seen

17:17

AI's images? Like graphic designers are going

17:19

to be around for a while, but

17:22

there will be a point where I

17:24

feel we're riding on the elevator where

17:26

it'll be pretty good, but the really

17:28

good stuff will be the boutique stuff,

17:31

you know, and you think about it

17:33

now, probably what, 90% of the furniture

17:35

in your home, probably was made by

17:37

robot. I mean, it's slapped together really

17:40

good. But the craftsmen, the people that

17:42

know how to make that stuff, they're

17:44

still in high demand. There's just a

17:46

smaller, you know, labor force of them.

17:49

Yeah, right. And that's the, you know,

17:51

we see this all the time is

17:53

the expert tools versus tools. experts, right?

17:55

The idea that the tool is just

17:58

going to do all the things for

18:00

me. But yeah, now the real neat

18:02

interesting stuff, like you said, you know,

18:04

the master woodworker who's kind of, who

18:07

doesn't have to deal with all of

18:09

the paper instructions and measuring things, you

18:11

know, like they can just work on

18:13

picking the right wood and thinking about

18:16

the design of the furniture itself, rather

18:18

than, you know, the more mundane tasks.

18:20

And yeah, that's where things are going.

18:22

And you've another great point of freeing

18:25

resources up, you know, you know, you

18:27

know, you know, Like the big one

18:29

is stock photo, you know, stock photo

18:31

takes a huge hit if people are

18:34

able to generate and just kind of

18:36

get images that they want. But you

18:38

know, now it's the thing of like,

18:40

okay, all these companies that really had

18:43

a hard time having quality graphics and

18:45

images on their website, like what happens

18:47

if they finally have the ability to

18:49

create a better website and be able

18:52

to kind of do more with less?

18:54

What kind of lift can they see

18:56

from that? Yeah. So I'll ask a

18:58

big question. Does AI make us better?

19:01

Well, it's like any tech tool, right?

19:03

That's the problem. It can make us

19:05

better and it can make us worse.

19:07

You know, it's it's all about whose

19:10

hands is it in and what are

19:12

they trying to do with it and

19:14

where are they trying to go? But

19:16

it is weird in that it, you

19:19

know, again, like tech, it makes everything

19:21

faster and bigger and accelerating and unfortunately

19:23

are kind of, you know, Caveman brains

19:25

are already having enough difficulty handling the

19:28

speed and volume of everything that's going

19:30

on around us in the world So

19:32

yeah, it's gonna get a little bit

19:34

wonky and weird and you know the

19:37

idea of me even trying to predict

19:39

something is kind of silly Yeah, well,

19:41

I think that's the that's the hardest

19:43

part of is is Great Tech appears

19:46

as magic right isn't that the the

19:48

saying and we're getting to the point

19:50

now where we can't tell magic from

19:52

great tech so That's um, that's I

19:55

guess that's always where we're going, but

19:57

we're always trying to out

19:59

-invent ourselves, you know? and

20:02

it's you know ultimately it just comes down to the

20:04

just comes down to what good news is

20:06

like, okay, what are people actually willing to

20:08

pay for? I mean we mean, we can do a

20:10

lot of weird and crazy stuff, but but you

20:12

actually going to find something that fits. And

20:14

that funny. That's something that's kind of evolved

20:16

over the past. that's kind years too, over the

20:18

past 10 always thought about sales as

20:20

always thought people to your thing and

20:22

moving the river to go in

20:24

your direction. to go in your really what

20:26

we're seeing is that seeing you know,

20:28

is more about what is is the

20:30

existing system already there how how do

20:32

we move our business so that

20:34

we can get in front of

20:36

whatever's coming next and where to

20:38

go. to go. And And so that

20:40

idea of being able to strategically

20:43

see what's coming next and already

20:45

be there know, for as they customers as

20:47

they that's the money, that's a

20:49

different approach and kind of changes everything

20:51

for sales and marketing, right? It's not

20:53

about just banging the drum, it's more

20:55

about about... you know ahead and figuring out where

20:57

to be. out where to the

20:59

part that's the think all of

21:01

this all of this touched on touched

21:03

the the the of AI, right?

21:06

right so So we're approaching all

21:08

of this now because almost everything

21:10

has some sort of freemium model. model

21:13

which means we're the product. and and

21:15

it's it's free they need our data.

21:17

They need our prompts. our They need

21:19

to be able to comb the

21:21

internet. They need to be able

21:23

to read our blog posts and

21:25

our white papers. posts But when

21:27

they don't need that but when they then

21:29

what is the economics of AI?

21:31

what Will there quickly become a

21:33

have and have become a have and have-nots

21:35

layer have the can't afford

21:37

the AI. afford the AI because

21:40

there is a cost to it it now? Yeah, that

21:42

is a Yeah, that is a gigantic

21:44

question that I think is just

21:46

underappreciated is the fact that. the fact

21:48

kind of. of... AI AI has taken

21:50

all the oxygen out of the room

21:52

as far as far as VC and we normally

21:54

would kind of see. see you know you

21:56

know, money being sprinkled across

21:59

a whole bunch of. places, but everybody

22:01

is just putting all their chips on

22:03

this and it's yeah, the... Everybody wants

22:05

to have the iPod. They want to

22:08

be the one that invested in the

22:10

Facebook and the one that wins. Right,

22:12

yeah, everybody is going for the topic.

22:14

Like I can't think of a period

22:17

of time where we're getting more powerful

22:19

free stuff than ever before, you know,

22:21

and so yeah, yeah, there's huge questions

22:24

as far as like, okay, when this

22:26

shakes out and suddenly... you know maybe

22:28

there's three winners or one winner or

22:30

whatever like how does that change yeah

22:33

you know unfortunately marketing again has a

22:35

horrible track record for like yeah it's

22:37

great and free at the beginning but

22:40

then once it starts getting tuned for

22:42

ads and traffic yeah it gets expensive

22:44

fast and a lot of people get

22:46

left behind right that i mean that

22:49

was just as you were answering that

22:51

that was something i was thinking of

22:53

is You know, at some point, and

22:56

I suppose we thought about this with

22:58

social networks too, at some point they're

23:00

going to start charging. And we didn't

23:02

think that day would come, and I

23:05

actually thought the model would be very

23:07

different. Now the social networks charged to

23:09

verify you're a human, which I wouldn't

23:12

have expected, you know, we thought everything

23:14

on social would go to a subscription

23:16

price. We're seeing AI be subscription price

23:18

early on, but I don't even know

23:21

if in five years. AILB subscription price

23:23

because there could be a completely different

23:25

cost model to it because of I

23:28

don't know, right? Like could you have

23:30

predicted that Facebook is going to charge

23:32

you to become a verified Facebook user

23:34

as opposed to a monthly subscription, which

23:37

was the traditional magazine model? Yeah, that's,

23:39

you know, a turn that is bizarre.

23:41

And I don't know, but part of

23:44

me too is still hoping one day

23:46

we get to that point where... It's

23:48

more about verified users because when you

23:50

get to back to all these platforms,

23:53

right, the problem is they do violate

23:55

the laws of communication, right? Like anybody

23:57

can go on any platform and just

24:00

say whatever they want and it can

24:02

be unchallenged. Whereas, you know, for all

24:04

of human history prior to that, if

24:06

you were talking some crazy stuff, there

24:09

was instant, you know, ramifications, whether it

24:11

was, you know, somebody throwing a tomato

24:13

at you or, you know, whatever. But

24:16

there were repercussions for this. And so,

24:18

you know, we've seen this as a

24:20

crisis and trust across the board in

24:22

all institutions. And yeah, I kind of

24:25

think at some point, somebody's going to

24:27

get the bright idea that by verifying,

24:29

you know, in anybody's best interest, like

24:32

when that stuff gets filtered, how does

24:34

that make it different? But I didn't

24:36

do, I thought that that would have

24:38

happened a long time ago and it's

24:41

not here yet, so I don't know,

24:43

you know, can't it even happen? Yeah,

24:45

I mean, selfishly, I know I've had

24:48

a friend have a YouTube video of

24:50

his transcribed and turned into three online

24:52

magazine articles, all without his consent, and

24:54

then posted to Facebook. via a bot

24:57

and the bot 100% had an AI

24:59

generated profile image. So I'd be a

25:01

fit, yeah, verified users, that would be,

25:04

you know, it's like, it's like when

25:06

you get pulled over by the police,

25:08

you have to hand them your ID.

25:10

We need some sort of digital ID

25:13

for that. Yeah, that use case that

25:15

you described as crazy as anything about,

25:17

right? Because that's playing under old SEO

25:20

rule. Somebody's thinking like, oh, I'm going

25:22

to get in three or four more

25:24

different channels and I'm going to take

25:26

that traffic. And the reality is, you

25:29

know, all the search engines now, the

25:31

first five things they're throwing up are

25:33

their own internally generated AI, like organic

25:36

traffic is continues to crater. Yeah, right.

25:38

John, it was great having you on

25:40

the podcast. I'm sorry it took so

25:42

long, but I promise I've not stopped

25:45

drinking coffee since then, nor will I

25:47

ever usually. That sounds great. Yeah, no,

25:49

it's good to be back. We haven't

25:52

had a... to hang at at

25:54

Dream I used to

25:56

do all the

25:58

time, so the time, to

26:01

catch up. to know,

26:03

but there is

26:05

still the still the the Dream

26:08

Force marathon. I I don't even know

26:10

what people are wearing now

26:12

for wearables. You remember, it used

26:14

to be You and - it used right, be

26:16

fit bits? Oh were all Fitbits all everybody

26:18

had that and it was

26:20

the that and it was I think, you

26:22

know, to be fair, I because I

26:25

am to be fair, we I hear that

26:27

and there has been a

26:29

very long look at how do

26:31

we not necessarily keep people in the

26:33

same space but reduce the amount

26:35

of - mile across San Francisco, you know, Francisco, be

26:38

banned. know. a few of it can be that

26:40

There's a few of them at that you

26:42

just look at and be like, going to

26:44

stay at the bottom. bottom. Always a fan. I just a

26:46

fan. I just get the cable car

26:48

pass for the week you know, know care care

26:50

of that. There you go There you go.

26:52

it was great having you on. I promise

26:54

to have you back on sooner sooner, because I'm

26:56

I'm sure we're gonna have more AI to

26:58

talk about AI to talk it's ever evolving so

27:00

quickly Yeah, yeah, yeah, hopefully it'll

27:02

still be us and not just

27:04

avatars of us having to of us it

27:06

for us. it for be fine that'll be

27:08

We'll see. see. Maybe people won't know

27:11

the difference. difference. Then and I can be

27:13

riding a cable car in San

27:15

Francisco. in Right, right, as they're watching

27:17

the video of me with my third

27:19

watching the video of me with my third forget your

27:21

sixth finger. your always gets the fingers

27:23

wrong, too. gets the fingers wrong too. So

27:29

that was a great discussion with

27:31

John. I'm, I'm so glad I

27:33

could have him back on the

27:35

podcast. It's, it's been way too

27:37

long. I've been a I've been listener,

27:39

a second time interviewer. I didn't

27:41

say that. say that. Anyway, if you enjoyed you

27:43

enjoyed John's episode, be sure to

27:45

check out Marketing Over Coffee is definitely on

27:47

my podcast playlist. They do do

27:49

so much to help keep up. If you're in up.

27:51

If you're in tech marketing is definitely something

27:53

you pay attention to. know And you know

27:56

what, if you enjoyed this episode, be sure

27:58

to share it with a friend. a friend. Apple

28:00

you can can those three dots and

28:03

click click to share episode or you could

28:05

head on over to all of

28:07

the resources that we have on

28:09

admin .salesforce .com. That's your one the

28:11

for all of the links, we anything

28:13

that we included, including a transcript

28:16

of this episode. be remissed if course,

28:18

it'd be that I didn't mention that

28:20

you can join the conversation in

28:22

the trailblazer group that is in is in

28:24

the trailblazer community. Don't worry, worry

28:27

in the show notes. show notes So, next

28:29

week, thank you so

28:32

much for your time

28:34

and we'll see you

28:36

in the cloud. so much

28:38

for your time, and we'll see you in

28:40

the cloud.