0:01

Welcome to the Sales Enablement Society

0:03

Stories from the Trenches , where enablement

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practitioners share their real-world experiences

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. Get the scoop on what's happening inside

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Sales Enablement teams across the global

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SES member community . Each

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segment of Stories from the Trenches share the

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good , the bad and the ugly

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practices of corporate sales . Enablement

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initiatives learned what worked , what

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didn't work and how obstacles were

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eliminated by corporate teams and leadership

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. Head back , grab a cold one and join host

0:31

Paul Butterfield for casual conversations

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about the wide and varied profession

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of sales enablement , where there is never a fits

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all solution .

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Hello and welcome to another episode

0:41

of the Sales Enablement Society Podcast Stories

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from the Trenches the only

0:45

bias for us podcast

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format that we're aware of where

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we're bringing together enablement leaders

0:52

from across the globe hearing about

0:54

the new and innovative things they're doing , the

0:57

successes that they're seeing and sometimes

0:59

even , just as importantly , where

1:01

they've fallen and failed and how they backed

1:04

up and did even better the second time

1:06

around . We learned from all of it . I

1:09

am excited to introduce you

1:11

to this week's guest . I'm going to start

1:13

off by Nickname that a lot of you may know him by

1:15

. He goes by Coach K . The

1:19

name his mom gave him is Jonathan

1:21

Carford . Welcome , jonathan .

1:23

Thanks , Paul . It's so good to be here . I've been looking forward to this

1:25

.

1:26

Thanks for a little while , For a while . So

1:28

the cool thing for everybody that may not have

1:31

seen your announcement is you recently

1:33

started a new role , so maybe share a little bit about

1:35

that .

1:36

Yeah , I just actually started last week , but I'm

1:38

the head of revenue enablement for a startup

1:40

called Symmetric . It's a reconciliation

1:43

SaaS company out of Columbia actually , but they're

1:45

going international Really and they needed

1:47

some scaling help , which is why I'm there to help

1:49

them go to the next level .

1:51

Wow . So you have the opportunity to help lead

1:53

their go-to-market motions into North America

1:55

.

1:56

Yep North .

1:56

America and Europe . It'll be fun . That will

1:59

be fun . Well , congratulations , thank you . Want

2:02

to have a little fun before we get

2:04

into the serious stuff we're going to talk about , and

2:06

so we're going to do our signature Jimmy

2:08

Kimmel challenge . Yeah , so

2:10

Kimmel passes away . Through your connections , you're

2:13

offered his show . You can

2:15

have anybody you want as your first guest

2:17

. Who do you choose , and

2:19

why did you bring them on ?

2:22

Well , after listening to the show many times , hearing

2:24

everyone's stuff , I thought a lot about it , about famous

2:26

people , but honestly , for me

2:28

it would be my mom . She passed away

2:30

two and a half years ago from cancer

2:32

and she's one of the people who

2:34

inspires me to be the best I can be , and so I'd

2:37

love just to . She would hate to be in front

2:39

of an audience , but it'd be a lot of fun

2:41

to pick her brain and just see what inspires

2:43

her and give her some kudos

2:45

to for inspiring me .

2:46

Wow , that's great . Almost

2:49

positive that that is the first time a

2:51

parent has come up in that context , so

2:53

thank you for that . You're welcome . All

2:56

right , AI unless

2:58

you've been living under a rock , you've

3:00

probably already been hearing a lot about it and

3:02

hopefully maybe even using it a little bit . But

3:06

what you wanted to time and talk about with us

3:08

today are some very specific use

3:10

cases and some of your experience with

3:12

that . So let's jump right in

3:14

Again . Unless people have been under a rock

3:17

, they must know what AI is . But

3:19

I think it's still helpful to start with a definition

3:22

of AI and enablement

3:24

, so let's kick off with that .

3:26

It's kind of funny because AI to me , is like the sexy

3:28

thing that everyone calls , but it really comes down to

3:30

predictive analytics , natural

3:32

language processing and some

3:35

sort of machine learning of some kind . So a

3:37

lot of times people are calling predictive analytics

3:39

AI just because it's the sexy thing to call it , but

3:41

they're not exactly the same . No

3:43

, I think it's good to understand the differences between

3:46

those , because then you can really release the power

3:48

in each platform if you understand what it actually

3:50

is , not just AI , because a lot of people

3:53

get confused with being like this alter

3:55

thing out there that , things for

3:57

itself , is going to take over the world , which is not what it

3:59

really is .

4:00

It's like years ago . I led a sales team and into

4:02

it and it wasn't the financial products , it was online

4:04

database product they acquired from MIT and

4:08

they called it . They always talked about it being in the cloud

4:10

. It wasn't . It

4:12

was also the server farm out of the North West

4:15

. The cloud sounded so much cooler in 2009

4:18

, 2010 . Yeah right .

4:19

Cool thing to say now yeah it was All right .

4:22

So , just for those that might be wondering

4:25

, what are the one or two key differences

4:27

between predictive analytics and true

4:29

AI ?

4:30

Yeah , so an actual AI

4:32

is like its own entity that can think and solve

4:34

problems by itself without much guidance

4:37

. Predicted analytics is like

4:39

, basically , take it's looking at patterns and saying , based

4:41

on the stuff that I see , what is the most likely

4:43

thing to happen next . So like , if you

4:45

chit , if you put in a chat like please tell

4:47

me the top 10 things or top 10 books that

4:49

would be about business and pop up 10 things , it's

4:52

just doing that based on it

4:54

, what's gone on the past . And then , with

4:56

natural language processing , that's where , like , you have

4:58

your Siri , your

5:00

any stuff that recognizes your voice , recognizes

5:03

patterns of speech in most languages and

5:06

can thereby give answers , because it recognizes

5:08

in code our voices and language

5:11

, puts into computer code and pops

5:13

it back out whatever response it is . So

5:15

okay .

5:15

All right . So where are you seeing

5:17

the intersection between AI

5:20

and your work and enablement

5:22

?

5:22

Yeah , it's a good question . I've used lots of

5:24

tools like there's things from just making my life

5:26

easier and not so messy to make

5:30

it a lot faster to get stuff done . So , for example

5:32

, I had , through the job interview process

5:34

, I had to put together a one pager and

5:37

went to mid journey to do a couple

5:39

of images to make the branding look like the brand

5:41

I was looking for . Went to Canada to use

5:44

their AI , mimicked a download on whether

5:46

PDFs canva duplicated their branding

5:48

. Pop that to a thing .

5:50

I don't care if we could do that . That's awesome . It's

5:52

pretty cool .

5:54

And then you I put my picture in mid journey

5:56

so it looks branded for the product they're going for , and

5:58

then create this

6:01

interactive PDF out of it , which was freaking

6:03

cool . And then the guys were like , how'd you do this ? This

6:05

is amazing . Like well , it's a you know , $10 month

6:07

canva tool . It's pretty easy

6:10

.

6:10

So that's , it was 1000 hours , but you're working time

6:13

, but you should pay me for this consultant .

6:16

So there's that . And then there's little things like there's

6:19

tools of all kinds from your

6:22

voiceovers you can duplicate your voice and do lots

6:24

of voiceovers to you know , leverage

6:26

your time , and then things like

6:28

I think I posted one in the works

6:30

that we have about there's

6:32

a couple of AI tools that integrate with Slack that

6:34

can , like , summarize chats

6:37

going on so in case you miss anything , it can review it

6:39

for you , which is super nice . So

6:41

there's tons of stuff out there . This kind of

6:43

depends on what pain you're feeling , what you want to solve

6:45

for .

6:46

Tell everybody about there's an AI

6:48

for thatcom . I hadn't heard of that until

6:50

you brought it up either . Oh , really .

6:52

Oh yeah , If you have not gone there

6:54

, it's free to subscribe to it . They just kind

6:56

of like an aggregator of all things AI and

6:59

you can go in there and search for literally

7:01

anything and figure out and find

7:03

stuff . So if you want to like an image

7:06

generator that's free versus mid-journey you can

7:08

go in and find that . There's like

7:10

coaching platforms , just all sorts of things

7:12

in there . So if you haven't gone there , go

7:14

in there , start measuring out and searching things . Most things

7:16

that I find are either from the newsletter , from

7:19

them , or because I went in and I

7:21

researched out some options . So

7:23

pretty cool stuff .

7:25

We published this podcast on Buzzsprout

7:28

that's our platform that feeds Apple

7:30

and Google and everything from there and

7:32

just a few months ago they introduced new AI

7:34

, which I find has reduced

7:36

my workflow significantly . Now , when

7:38

I upload this transcript in

7:41

the next couple of weeks , it will read

7:43

it , it will suggest titles , it

7:46

will write a summary of the episode

7:49

, and

7:52

I usually end up tweaking that stuff , but

7:54

the fact that they're just boom putting it

7:56

out there and all I have to do is just

7:58

make it in my voice , it's pretty cool

8:00

. So even just little things like that , that

8:02

weren't a big deal to do , but it's

8:04

a lot better with somebody else , or AI is

8:06

helping you go through and do it .

8:08

It's kind of like when you and I met before you

8:10

had that note , I had my own note taken .

8:14

There's lots of them out there . Yeah , Fireflies is

8:16

amazing .

8:16

There's a lot of good stuff out there for free

8:18

. That does all the summary for you on your calls

8:20

Like why are you not using that ? Yeah

8:22

?

8:22

no , that's a really nice , a really good

8:24

point . Yeah , All right , so let's

8:27

talk about then . When you talked about

8:29

, you talked about Canva , mid journey . You

8:31

went through all of that . Have you have

8:34

you discovered or identified

8:36

any potential downsides ? Because so far

8:38

, you know everything . We're talking about

8:40

sounds like you know

8:42

everything's good , but everything's

8:44

awesome , Right , what's the flip side ? Or is there a

8:46

flip side ?

8:47

Yeah , I think a

8:49

lot of times . Well , there's

8:51

several . I'm going to give you a few . One is because

8:54

content is so easily made . That means the

8:56

market's going to be flushed with content

8:59

. That's not always the best , it's mediocre

9:01

sometimes . I love chat

9:04

GBT for several reasons , but

9:07

you can tell when someone posts on LinkedIn a chat GBT

9:09

post .

9:10

Oh my gosh , oh , yes , yeah , yeah , yeah

9:13

, yeah .

9:13

And not that that's bad . I mean , sometimes it's good to see that , but

9:15

it's just . I think it can adhere to laziness

9:18

and , like you said , I'd rather have what it

9:20

produces for me than tweak it to my own style

9:22

or words . But

9:24

it can make it . You can make easy . Maybe

9:27

sort of it can

9:29

make you become lazy if you left

9:31

. The other side of it is a lot of people

9:33

who are concerned about data privacy with AI

9:35

because a lot of the integrations and some of the content you

9:37

put in . Where does that go when you put in a

9:39

prompt about some financial modeling , who

9:42

knows ? And then

9:44

the other one was some of them like mid-journey

9:46

is its own language and you have

9:48

to . There's a learning curve around how

9:50

to prompt mid-journey because it's not like a chat . Gbt

9:52

is going to do what you want . You have to kind of work

9:54

it a little bit Less intuitive . Yeah

9:57

, it's awesome , it's a good tool , but

9:59

to get the exact thing you want you have to kind of finesse

10:01

a little bit . So there's a little education on it .

10:04

Yeah , I know that

10:07

LinkedIn's algo favors

10:09

longer posts . I

10:11

personally don't get that , because I look at LinkedIn

10:14

on my phone more often than not and if

10:16

I have to scroll I'm

10:19

rarely engaged enough to do that , but

10:21

it is what it is and I

10:23

think the chat GBT the

10:26

times when you read something that's just so clearly

10:29

written by some AI

10:31

. It reminds me

10:33

of when that newbie BDR

10:35

rep reads

10:38

right , they read the script as

10:40

opposed to internalizing it and talking

10:42

to somebody . Yeah , there's

10:45

something about chat GBT style . It likes to be really

10:47

fancy or formal or I

10:50

don't know what it is Anyway .

10:51

So you can prompt different ways that you can

10:53

make it like . I saw one post when someone said something

10:55

like make this more bro , and

10:58

then I said make it Uber bro

11:00

. So like it kept going more . Like I

11:03

gotta try that one next time .

11:06

That's actually pretty funny . Yeah , huh

11:08

, all right , I gotta try that . That's a new thing to

11:10

do , new thing to do , all right . So

11:13

it sounds like you're saying that the downside is

11:15

really if you're not being thoughtful

11:17

with it , if you're not using this as a springboard

11:19

and just expecting it to essentially

11:22

do your work , the creative

11:24

side of your work and that's

11:26

a really good point about financials , I

11:29

guess how do you fact check

11:31

that ? Right , it's a dome

11:33

tool in the sense that it

11:36

synthesizes from whatever it finds on the web

11:38

. So if it finds

11:40

bad numbers on the web , it doesn't know that

11:42

, it doesn't have a way to validate that . I'll bet that changes

11:45

. I'll let it evolve to

11:47

do that , but I'm sure it will . Points

11:49

well taken . So speaking of evolve

11:51

, yeah , based on your

11:53

experience with the AI I know you've done some research

11:55

into this topic what

11:57

is the future hold for

12:00

enablement teams using AI

12:04

?

12:04

I thought about this a lot actually , and actually put a post

12:07

up on LinkedIn about this a few weeks ago because I

12:09

was thinking about where it could go . But

12:11

it made me think of one of the Iron

12:13

Man's I don't remember which one it was , or one of the Marvel

12:15

movies with Iron man , and he has that virtual

12:18

thing Number two .

12:18

I hope I hated that one .

12:20

It wasn't that one . It might have been Civil

12:22

War , but anyways , he had this

12:24

interactive thing where he watches his younger version of

12:26

himself talk to his parents .

12:28

Right , right , yeah , I do .

12:29

And so I was thinking about something like that going . How cool

12:31

would it be if we had an AI that could go

12:33

out and research a persona and like

12:36

literally the person , the VP of whatever

12:38

at some company , look at all the articles

12:40

, look at their job history , look at their company and

12:42

then create this AI

12:44

persona of this person that a salesperson

12:46

could then pitch to on practice

12:48

and get ready for a big

12:50

presentation , right , and then actually

12:52

get feedback from both AI

12:54

and people on real

12:56

time stuff , because right now it's not to that level . You

12:59

need a little more of a experienced

13:01

sales director or someone who knows what they're doing to kind of give that

13:03

feedback . But how cool would it be to have Stuff

13:06

from the actual company

13:08

in person be the content that they produce

13:10

that you have to be ready for . You know , I think I'd be a blast

13:13

.

13:13

What about concerns and objections ? Is it smart

13:15

enough to do that , or is that where your sales leader has

13:18

to filter ?

13:19

I would sit . Well , I think it could go that way

13:21

if it had , like , a lot of people . I

13:24

don't think know that with like chat , you Bt

13:26

or a lot of them , you have to kind of train it . So

13:28

I think if you loaded it with a bunch of FAQs

13:30

, it could probably replicate it if you knew kind of

13:32

like the theory behind it . I

13:35

look at it more like it'd be cool if you could

13:37

go into a gong or chorus , identify

13:39

all the questions are being asked , get all the answers

13:41

, have some way to fact check those

13:43

answers and then create a thing out of it . So

13:46

if you asked to the question on a chat or voice

13:48

, it could replicate that answer real

13:50

time . It'd be really cool if we could do that

13:52

.

13:53

You just sparked an interesting idea for

13:55

me , so what do you think of this ? In

13:58

my experience , product marketing Typically

14:02

owns and ICP

14:04

or personas , however

14:06

enablement is a big stakeholder

14:09

in that and typically revops

14:11

is as well , right . Do you think that

14:13

if a company Doesn't have

14:15

that ICP or persona figured out

14:17

, that that they could get AI

14:19

to you know , put in some , put , like

14:21

you say , faqs or some data about , about

14:24

the problems they solve and use

14:26

cases and things like that and smart enough to start

14:28

generating some ideas for customers ? They should go , not

14:31

not customers by company

14:33

, but , yeah , general customer types .

14:36

Yeah , that's something that Thomas

14:39

actually went through . On the sec thing . He just went the

14:41

same thing . It said , hey , let's find your

14:43

ideal persona job and

14:46

train that train . Gonna quote chat

14:49

. You did say , okay , here's the job description , here's

14:51

a couple of paragraphs about the company . Give

14:53

me the top concerns of this role

14:55

for this product and then brand that

14:57

popped out a bunch of stuff . Wow , okay , that's

15:00

the kind of thing I suggest doing all the time is like really

15:02

getting some if you don't know

15:04

, like Just like

15:06

that example , if you don't know exactly what they do or what the response

15:08

before , go , go grab a job description

15:11

, fill it up and say , okay , here's the product

15:13

I'm trying to pitch . What are some concerns that could have

15:15

? Now , the challenges with

15:18

chat to be tea , specifically , is limited to 2021

15:20

info , but if you go into things like AI

15:23

, ai , prm , if

15:25

it was called , yeah , AI . PRM is a is

15:27

like a Add-on

15:29

you can put to chat GBT and then has access

15:31

to more modern stuff and then

15:33

you can have real-time 2023

15:37

concerns .

15:37

So I saw Thomas speak on this in

15:39

New York City . Yeah , but , gosh

15:41

, that was way back in March , right , so

15:44

sounds like I missed a more recent thing , but but he's

15:46

, yeah , he's , he's doing some amazing thought leadership

15:48

On this topic . I definitely

15:50

agree . One that I've heard about

15:52

but I haven't had the chance to try in

15:54

a live enablement environment is Analyzing

15:57

10ks . I know you know

15:59

in the past , because how many times

16:01

do you hear that from sales leaders ? Oh , they're a public company

16:03

, go read their 10k . But if a salesperson

16:06

didn't go to B school , I

16:08

didn't really always know what to look

16:10

for . And and I know

16:12

of people that are using that very Effect

16:15

teaching their reps how to use that just to analyze

16:17

, upload the 10k and just get an analysis

16:19

of you know the top takeaways and

16:21

you know From certain perspectives

16:24

, that sort of thing . I thought that was pretty cool .

16:26

Yeah , I think there's a ton of stuff out there , but I think

16:28

that there's actually one I'm gonna

16:30

look this up in . I mean , there's that there's an

16:32

AI for that . Right now I'm looking at 10k

16:35

financials . You can find anything .

16:37

I think there might be people I know doing . They're just

16:39

using chat GPT . Oh yeah , you can totally

16:41

do it there may be a specialized tool as well

16:43

, but mean to me that one's a kind of

16:45

a big deal because in the past , for example

16:47

at Vonage , we developed

16:49

what we called mini MBA program

16:51

for sales Mm-hmm and that had a few

16:53

components to it . For example

16:56

, our head of IT . Right

16:58

, we had him do a session with us on

17:00

who gets through to his gatekeeper to him

17:03

, because we sold to IT is one of

17:05

our Presence like who got through to Dara and

17:07

why did he choose to listen to that person versus

17:10

the other ? You know 20 right

17:12

? Yeah , we did a few things like that , but

17:14

one of them was actually how to

17:16

read , how to analyze , and

17:19

you know , and make use of that analysis

17:21

in selling , and I think that's still a useful

17:24

skill . But , man , with the , with

17:26

the acceleration of business and

17:28

everything , just in the time I've been gone from Vonage

17:30

what three , three and a half years

17:32

? Yeah , a while . This is so much

17:34

better , so much better . You

17:37

talked about Iron man earlier . What

17:40

about , like a Jarvis for sales ? That

17:42

would be pretty cool , that would be awesome

17:44

.

17:44

I think they're in close , honestly , with some of the

17:46

companies they have , like Clary and other places

17:48

like they're . We're really advancing all the

17:50

things that can be capable of , and I think the next

17:52

step is like a Jarvis type AI , where

17:55

it's like a salesperson and they're Jarvis

17:57

chat , you BT person Talking to

17:59

them , say , okay , let me make this thing and let's talk about this thing , and

18:01

they explode it up and can see some really

18:03

cool diagrams . I think it's gonna be way fun

18:05

to be a part of and , to be fair

18:07

, though , I thought you probably

18:09

saw that Gartner article about how CRO

18:12

is going to be implementing like an AI

18:14

specific revenue generator manager

18:17

who you want to call that title there's

18:19

got to be , with someone focusing on

18:21

that full time . I think that's going to make

18:23

huge strides in the organization , with

18:25

revenues specifically , which would be fun .

18:27

I agree , and not

18:30

to scare anybody , but my thought with

18:32

that is there's some

18:34

entry level rev ops position that are going to disappear

18:36

too , yeah , you know which

18:39

? I think we all have to be a little cautious about

18:41

that to one degree or another . But I mean , that's the

18:43

kind of stuff that you don't need

18:46

nearly as large a team because you're not trying

18:48

to generate all of that . I

18:51

think of . Yeah

18:53

, it'd be interesting to see how that evolves .

18:55

I think you can see in rev ops or enablement

18:57

or maybe both , whatever . But I think there will be

18:59

a position sooner than later that will be an AI

19:01

specific enablement role , whatever

19:04

that title is you know , but

19:06

there will be something .

19:07

That would be interesting when to explore . Well , you know

19:09

you're going to be putting together a team sooner

19:12

than later , so maybe you're the first one to

19:14

try that out AI

19:16

specialist .

19:17

There you go , that's right , you're right .

19:18

An enablement AI specialist . Ai enablement

19:20

specialist . There , you go Very cool , All right

19:22

. So AI

19:25

is pretty cool . I mean

19:27

, we're having a lot of fun talking about it here , but

19:29

what is your advice for

19:32

enablement teams or maybe

19:34

even companies ? You know , because I know you've done

19:36

a broad , broad types of work

19:38

when it comes to

19:40

AI anything

19:42

, any specific advice or first

19:45

steps to get started , anything like that

19:47

would be helpful .

19:49

Well , I think it's really identifying what

19:51

the core need is . I think with any

19:53

tech tool of any kind , it's really easy to get the shiny

19:56

new thing and be like hey , we need to get this thing because it's so awesome

19:58

and everybody else has it yeah . Yeah , it's

20:00

just I don't think that way . I think more

20:02

of like what are we actually trying to solve for it

20:04

? It comes down to enablement , basics . What are we

20:06

trying to change ? Is there

20:08

a behavior , is it a KBI and what is

20:10

it ? And is there a tool that will be best fit

20:13

to do that thing ? Because

20:15

you'll find most of the times that you could probably get

20:17

a core of three or four

20:19

techs and you'll cover 80 to 90%

20:21

of what you need . Right , I agree Versus saying I need

20:24

10 things and have all the stuff , and it just makes it overwhelming

20:26

for you and for the sales team and everyone else involved

20:28

. So I think I say keep it simple with what

20:31

you actually want to change and

20:33

then , secondly , just start

20:35

to research out with some different options . Most

20:37

of them have some sort of free offering

20:39

, like I , I tried your Fireflies note

20:41

ticker . I tried three or four of them . I'm just trying to

20:43

figure out which one I , like you know they all

20:45

have different styles , yeah . Different styles , different

20:47

approaches . And then , lastly

20:50

, I'd say is don't be

20:52

afraid , like don't be afraid of trying

20:54

something new and and figuring out , because

20:56

it's it's well worth it .

20:57

On the other side , I think it would be helpful

21:00

for our audience to get a little bit inside

21:02

your head on on how you've gone . You

21:04

know , done that because probably a

21:06

lot of them haven't really gone

21:08

and done that level of evaluating

21:11

and implementation and that sort of thing . So let's start

21:13

with what you said on outcomes

21:15

. Now , hopefully everybody in enablement

21:17

by now , if they haven't been

21:20

already is is is

21:22

defining outcomes or forcing their stakeholders

21:24

to define outcomes with them before they just start

21:26

enabling stuff . But

21:29

do you have a couple examples of specific outcomes

21:31

you've identified that AI

21:33

is going to ? Where AI

21:35

will shine over maybe other things , ways

21:37

that we've been doing it .

21:40

Yeah , so I'm actually in the middle of

21:42

I won't see the name of the company , but I'm actually in the

21:44

middle of implementing a content

21:47

, a CMS , lms combo , which is built

21:49

on AI platform . Okay , and

21:52

the cool thing is is that in the old

21:54

iterations of content management systems , I'd

21:56

have to manually tag everything . My current company

21:59

has three different languages . That speaks yeah

22:01

, I'm tagging . It speaks three

22:03

languages Spanish , english and Portuguese . I don't speak

22:05

Spanish and Portuguese , so for me to have to tag

22:07

in Spanish and Portuguese I'd have to have someone to translate

22:10

for me . What the world they're talking about would

22:12

take forever . So this

22:14

new AI auto tags based

22:17

on the content itself and the title and

22:19

the language , and then we'll pull

22:21

up at the right time or right sequencing

22:23

, either in email or Salesforce , based on the

22:26

persona , the cell stage and

22:28

what they're looking for , which makes my life

22:30

light years better than what it would have been two years ago

22:32

when I was doing this all manually , right .

22:35

Oh my gosh . Yeah , we went through that . We went

22:37

through that in structure because

22:39

we had deployed an enablement platform that let

22:41

us serve up content right stage

22:43

, right time , right persona , all of that right

22:45

in the Salesforce . But the amount

22:48

of meta tagging that had to go in . And

22:50

then I happen to have Spanish

22:52

speakers and Portuguese speakers on my team

22:54

because a bit writing team reported me and

22:57

then we had to bring them in to do everything you just

22:59

said manually

23:01

. I don't even know how many work hours that

23:03

was . That's a pretty cool use case

23:07

. That's a really cool use case .

23:08

Yeah , I mean , and from enablement person of one

23:11

. I'm building it from scratch . I don't have time

23:13

to do all this Like I've got to do it now . So

23:15

anything that can help me get that done quickly

23:17

, I think , is for me just well

23:20

so helpful .

23:21

Plus , you get to look like a badass because you did it with AI , right

23:24

yeah ?

23:24

because how'd you do this ? Well , you know , I study Portuguese

23:26

and that's right .

23:29

And then the other question that your

23:32

last track

23:35

sparked for me was can you

23:37

share some of the criteria

23:39

that you've developed for yourself in

23:42

a value ? So you talked about the importance of evaluating platforms

23:44

, not trying everything on

23:46

earth . Any recommendation for people

23:49

. What should they be looking for ? What do you use

23:51

when you evaluate AI ?

23:53

Well , it really comes down to me , for who's

23:56

going to be using it and it's for me . It's

23:58

more about how often will I use this tool

24:00

. Is this a once a month thing or is this a once

24:02

a day thing ? That's number one , and

24:04

then two for the team . It's more about , specifically

24:08

for revenue teams . It's more

24:10

about do they have to log in somewhere else or

24:12

can this go to where they are and help them ? Because

24:15

if they have to go somewhere else , it's just another shiny

24:17

tool that sells people have to keep track of , or the CSM

24:19

or whoever is using it . So ease

24:21

of use and being able to understand

24:24

what they're going through in their own workday

24:27

is the best use case , and I got to

24:29

see it in action , which , of course , takes a demo or some

24:31

sort of experience . But if

24:34

anyone tries to convince to go into their platform

24:36

and all this other stuff , I guess it's just not

24:39

helpful . And then , like any other tech stack , I want

24:41

to compare it to what else is

24:43

out there , which is again why there's an AI , for that

24:45

is great because you can look at and see you

24:48

know you can even see any other options

24:50

you have out there to see what's going to be the best for

24:52

your situation .

24:55

That makes sense , and I would think that we

24:58

already should be reevaluating their tech

25:00

pieces on a regular basis

25:02

. With AI , we probably need to reevaluate

25:04

those maybe two X the speed , because

25:07

this is evolving so much and there's going to be

25:09

tools online in six months that aren't there

25:11

today . So very good . Well

25:14

, thank you . This is this has been a great

25:16

conversation on that , but

25:18

before I let you go , want to give you a chance

25:20

to you know , drop a truth bomb on

25:22

us all , and if you've

25:26

been given the gift of time travel and

25:28

you can go back and you can coach young

25:30

Jonathan on anything you want , but

25:33

the only restriction is it has to be

25:35

what you , only one thing . So

25:37

what would you choose and tell us

25:39

a little bit about that ?

25:41

Oh gosh , even in the moment

25:43

I've thought about this for weeks now . I still have a hard time

25:45

with this but the

25:48

biggest thing is to trust , trust

25:50

myself . I know it sounds kind of cliche , but

25:52

okay . There's been many times over the years

25:55

I have doubted my career

25:57

path , doubted my skill levels , doubted all

25:59

sorts of things , and if I can have my

26:01

future stuff come to me , I'll be like okay , just trust yourself

26:03

, you're on the right path , it's going to be okay

26:06

. Because a lot of times I think that

26:09

doubt is what has held

26:11

me back professionally , financially

26:14

, all sorts of ways , because they didn't trust my initial

26:16

instinct . So that makes sense . And

26:19

if I could add one thing to that is like always

26:21

, always be progressing not perfect

26:24

, but progress whatever . That is One

26:26

reason why I love being on the edge of things , because I

26:28

love learning , I love not knowing stuff

26:31

and figuring stuff out , and so it's always been like hey

26:33

, you don't know , go figure out , don't be afraid of failing

26:35

. It's a lot of fun .

26:37

That was actually one of our values at GE was

26:39

fail fast . You know

26:41

, if you figured out , move on

26:43

. If that's not the right way , you'll do it Well

26:46

, thanks , Appreciate your time . I'm

26:49

sure you have sparked questions

26:51

with some of the folks listening right now . Is

26:54

LinkedIn the best way to connect with you

26:56

if anyone wants to follow up on this conversation ?

26:59

Yeah , please . Linkedin , and probably connected

27:01

to you , is looking me up as Jonathan Carford

27:03

, a coach K it's

27:05

, I think it's JMK MBA on

27:07

LinkedIn is my handle . I

27:09

respond to all messages as long as you don't

27:11

pitch , slap me . So if you do that , I may

27:13

or may not respond .

27:15

Yeah , and if you respond

27:17

, they probably won't like it they won't , I'll

27:19

be like coaching and make .

27:20

Let me tell you what you should have said yeah , Well

27:22

, and what I do is I ?

27:24

I just unconnect if I've chosen . I

27:26

accepted the connection request . They hit me with that . I just

27:28

I'm busy , I just love

27:30

to give them coaching , but yeah , all

27:32

right . Well , thank you again . Appreciate the time

27:34

, especially your you know weekend to your brand new job

27:36

. So you got a lot going on . And

27:38

thank you to everybody that's invested

27:40

30 minutes of your time with us . Stay

27:43

safe , come back in two weeks . We'll have a

27:45

new guest and new content . Thank you , thank you

27:47

.

27:47

Thanks for joining this episode of stories

27:49

from the trenches . For more sales enablement

27:52

resources , be sure to join the sales enablement

27:54

society at s ? E societyorg

27:56

. That's s e s

27:58

o c I e t y dot

28:00

org .