Inside Marketing with MarketSurge

Welcome to Inside Marketing
With Market Surge.

Your front row seat to the
boldest ideas and smartest

strategies in the marketing game.

Your host is Reed Hansen, chief
Growth Officer at Market Surge.

Reed: Welcome to Inside
Marketing with Market Surge.

Today I'm excited to welcome a guest who
brings enterprise technology experience

and practical insights into the world
of business growth and innovation.

Clay Sharman is the founder of cradio.ai

and AI powered platform designed to help
businesses transform customer data and

traffic data into actionable insights.

And, personalized marketing strategies.

With over 25 years of experience as
a communication strategist, marketing

executive, and solutions architect for
large scale technology implementation,

clay brings a rare blend of technical
depth and narrative clarity.

Cradio AI reflects his passion for
bridging innovation and communication,

offering scalable solutions that empower
businesses to engage smarter, automate

faster, and connect more meaningfully.

Clay's background spans both public
and private sectors, including

leadership roles in, in government,
pr, and enterprise tech, making him

a visionary at the crossroads of
AI and human-centered marketing.

Clay, welcome to the show.

Clay Sharman: re, that
was an outstanding intro.

I'll need you to send that to me.

So thanks so much.

Great to be here.

Reed: I.

Well, well, my pleasure.

You know, it's, it's always fun to have,
uh, people that are on the ground with,

uh, emerging technologies like AI and,
and, uh, but in addition to that, you

have some very rubber meets the road
application here with, uh, with Cradio.

And, um, I think your background
is a solutions architect really,

has helped you with that.

I think so many of these platforms
have, uh, lofty ideals or.

Nebulous goals, but, but, um,
I love what you're doing here.

Could you tell us maybe a little
bit about what inspired you to

start Cradio AI and how did your
background help, uh, direct you here?

Clay Sharman: Sure.

Yeah.

So as you mentioned, um, spent a lot
of years working with the federal

government and um, you know, a good
portion of that time was in the,

kind of looking to the future of
the forefront of machine learning.

At least AI probably was, more of a
concept and not really an application

at the time, but I was doing a lot of
work for the Department of Defense, uh,

the Navy and the Air Force primarily.

Working on solutions around supply chain
logistics and making sure that ordering

and supplies were being delivered on
a timely fashion around the world.

So, you know, automation was
a, a key component of that.

And then about five years ago, I got
into enterprise intelligence and, and

was able to work with a company that
did some work supporting the three

letter agencies and national security.

And, uh, we were looking at things like
bad actors inside threat detection.

the idea being.

You know, let's take an alias down
to an identity and then watch and

track and see how their behavior was.

And then again, at that point we were
trying to predict potential bad actors.

It just so happens that commercially,
the architecture for an alias to an

identity is not all that different than
an anonymous visitor down to an identity.

And so an immediate.

Kind of idea that popped in my head
about commercial application for this

to help brands do better in how they're
relating to that anonymous audience.

That makes up the majority, the
vast majority of their web browsing,

you know, kind of SEO efforts.

So in my mind, you're spending a lot
of money and your SEO may be effective,

but if you're not able to converse
with these people, get back to them

and build a relationship with them.

There's lost opportunity there, and
we wanted to see if Cradio could

help kind of bridge that gap and
bring those two audiences closer.

Reed: And that's great.

You, um, can you tell us a little bit
more about Cradio and, and how it works

and, and you know, what it delivers?

I, I, I think it's a really
interesting product that you have.

I.

Clay Sharman: Yeah.

Um, wanted to approach it not
just from a single threaded,

um, kind of standpoint, so, um.

a critical component that I think, you
know, we took, took on first, which is

the ability to identify an anonymous
visitor as they come onto a website.

That's key.

And there are competitors out there,
uh, that do it alongside of us.

And so that was, you know,
to kind of table stakes.

We had to be able to do
that in order to play.

Um, where things get interesting is
our ability to not just identify these

visitors as they come in, but able
to assess their behavioral kind of.

Patterns as they move around the site.

So not unlike the way Google Analytics
will look give you feedback on your

overall audience, we can do the same
thing at scale, but we do it at the

individual level so everybody gets scored.

And then, um, really the main thrust
of what we're trying to do is to

the point where we can find out.

audience size, who is the most
likely to move forward in a buyer

funnel, and who's the least likely?

And so our system is interesting because
it works from two attack points, right?

We're trying to exclude the low prospects
and move the higher prospects so that

brands immediately get a return on
their investment with their ad spend.

talking more to the right people and
rather than just sort of shotgunning this,

this hopeful blast to a larger audience
and then seeing what kind of comes to it.

And then, you know, we, we in introduced
the notion of AI and continuous

learning because our intent is, I.

To get better on top of that.

So, you know, volume is important.

Yes.

But it's really, we do wanna find
those needles in the haystack so that

you're only talking to those targets.

And that is very different than most of
the, the platforms on the market now.

This idea of, um, exclusion
as well as inclusion.

'cause we're really trying to work the
formula from both sides of the equation.

Reed: Well, and that's, that's a
great way to, uh, use technology to

illustrate, uh, you know, marketing
principle that I, I share with many

of my clients is the, the market.

Marketing funnel where you're
qualifying, uh, candidates and, and

making decisions about who you spend
your time with or who you spend

your ads dollars or salespeople's
time with because, um, it, it's.

You know, you can, you can buy all the
contact information in the world you want.

You can, uh, you know, do
so many things in volume.

But it, it all takes time.

It all takes resources.

And, um, I mean, would you rather have
five people that are looking to buy

your product or 5,000 people that you
know, who know that you have no idea.

So, um, now an interesting, now
I just wanna ask you a question.

I have an interesting situation with my.

Own website.

Um, so market surge.io

is is our website, but we found,
unfortunately that there is a stock

trading database called, uh, market Surge
that is owned by Investors Business Daily,

and a significant amount of our traffic.

I suspect is people typing in
the wrong URL or you know, being

redirected in search incorrectly.

Do you think Cradio is, has um, the
ability to help us sort that potentially?

Is that

Clay Sharman: Yeah.

Uh, I mean, so the way we would probably
approach that problem and, uh, it's not,

I mean, there, there exists@cradio.com

as well, so interestingly, right.

Reed: Oh, right.

Yeah.

Interesting.

Yeah.

Clay Sharman: uh, we, we own the URL, but
there is another company called Cradio.

So, um, we have that same issue,
same question, but yeah, I think

the way I would approach it
with you is, um, we would simply

watch the behavioral patterns.

'cause typically, you know, if, so
if market surge for the investment

side of things and the market side,
duration would probably be shorter.

Um, the number of pages that they
scroll through and that sort of thing.

And so we would probably just make some.

Inference guesses early and
then test those theories.

You know, you might do a nurture
campaign or a newsletter invite on

that to see if we're missing somebody,
but see things like what the referring

URL was that brought them to the site.

So if they were coming from another
site that was an investor, you know,

related thing or market, you know,
kinda stock market related thing,

we would see that and we would then
make that inference that, uh, this is

probably, the wrong type of candidate.

So yeah, it would be a.

Probably a fairly simple filtering
effect for us to, um, sort that group

as a different group and probably,
you know, teach the models pretty

quickly to ignore them or deliver them
to you if you wanted to talk to them.

Because again, when they go to your
website, it is data that you can use.

Um, and then they're probably within
any audience size, there's probably

somebody within that audience that
is actually interested in both.

And so, you know, the question would be.

To your point about resources and time,
do you wanna spend too much time with them

or we rather just get you to those five?

And so that would be our goal,
is to do the same thing, but we

have the tools to, to assess that.

Reed: Yeah, that's perfect.

That, um, that, that would
be a big benefit to us.

We, uh.

Um, we get like unusual spikes in traffic
to like our terms and conditions and,

and some of our compliance, uh, pages
that are, uh, uh, you know, I'm sure

financial advisors very interested in
that, but not so much a, a marketer.

But, um, anyway, that,
that's very helpful.

Um, do now tell us how the AI
functions in this, in with the scoring.

So it sounds like, does it, it, um.

'cause I imagine this has
to be an iterative approach.

There has to be some sort of feedback
back into your system to tell them

that these were good leads, these
were, um, less, less valuable.

Clay Sharman: I would look at it
as, in this instance it's likely

more of a retargeting strategy.

And so everybody comes in and gets
scored, ranked, stacked in the funnel.

And I like your use of the term funnel.

'cause what we would try to do is at
the top fill, the lower likely, you

know, they're all warm because they
went to your site, they're all brand

aware 'cause they went to your site.

But then we would then move them further
in in terms of what we think likely to be.

The people who click the likely
the people who cart or sign up.

Um.

So, yeah, it's really on the return trip.

Exactly.

That we, we use that.

So iterative is the right process.

We see them when they come back in
and we look at the things like was

the tactic that brought 'em back in?

What was the channel?

So was it a social media
display ad, was it an email ad?

Was it both?

Um, but those would all play
into the updating of that score.

And so our AI just uses a
series of variables that are

weighted in terms of value.

And then, you know, we update that score.

So it's sort of got a little bit
of a mountain mountaintop kind of,

uh, line that you watch as it goes.

But audiences will move in and
out depending on how they retarget

effectively or ineffectively.

And then the goal would be.

At that point, identifying what channels
are, you know, behaving better, what

channels are behaving worse, and then
if there are tactics inside the channel.

So all of that stuff plays in.

So things that could do as an analyst, it
just would be incredibly time consuming

to make those leaps at a speed with
which you're trying to keep talking to

these people within a cadence that's
likely to catch them in a buying mood.

So why AI works so well on the back end.

And then on the front end we use
AI as an interaction for the user.

So we have a copilot that, uh, I,
I think I got a chance to show you,

um, it will serve as your specialist.

And so you can talk to it in natural
language the way you would with

any current AI tool that we know,
chat, GBT or Perplexity or Claude.

And, uh,

sort of bound to the service of that.

know, user, that user community.

And so we, we tried to, and I think we're
successful in using AI on the backend

to do all the intelligence in terms of
scoring, moving and identifying, and

then of course, the natural capability
to just talk to your AI specialist as,

as if you're talking to a team member.

And that was our goal, was to create a
platform that could work this anonymous

audience in a way that was meaningful.

But you, the user or
the marketer felt like.

Hermes is over here.

What's Hermes doing for us?

And it's just a team member interaction.

So that's how we, that that is the goal.

And then of course, we're very
up to date and pushing as many

boundaries as we can with what's
possible with AI on that front end.

Reed: That's awesome.

Um, tell, tell me a little bit
about like what are, what would be

ideal, um, users of your software?

Like, um, you know, I, I, I
would assume that a higher volume

of traffic would, would, um.

Help a lot.

But are there particular industries or,
or use cases where they're, um, I mean

maybe the use of ads is kind of a, could
be a, a good way to filter, I don't know.

Is it, what, what do you, what

Clay Sharman: Yeah,

Reed: do you say?

Clay Sharman: you know,
I think there's two.

There's two fundamental user.

of populations within that question.

The one is

Reed: Mm-hmm.

Clay Sharman: We get a lot of web traffic
and we realize we're not optimizing

that web traffic as a means for revenue
generation the way we'd like to be doing.

So customer facing, product service
oriented, high volume a hundred

percent, um, regardless of the
value of the customer at that point.

And then you have the, the
more, um, kind of niche.

facing things, maybe the financial
services, uh, investor, wealth

management, even the automotive
industry, where the value of a single

customer could be so high that it
justifies even with low traffic volume.

Say you only get 2000 web visitors
a month, but if you were to

understand and be able to connect
with one of them and turn them

into a client or a customer return.

Would probably in those low volumes
would, would give you a massive

multiplier on the cost of the tool.

And so the value there would be if
we could just get one, you know, for

the year that would pay for the tool.

But if, if, imagine if
we could get one a month.

And so at that point it's a very,
becomes very surgical in that sense.

But the higher volume ones.

that's fun because the models learn faster
when you're talking about high volume.

But what's nice is one customer,
user or the other, the tool takes

advantage of the aggregated knowledge
that it's learning about audiences

across all the industries, and it can

Reed: Okay.

Clay Sharman: very
specific, you know, niches.

Reed: Okay.

That's, that's fantastic.

And, you know, every, every website's
gonna have a different, I mean, even

within an A given industry E, so
you've got the aggregate knowledge

across all the, all the users.

But then, um, it's learning specific
based on the individual website,

which is, which is fantastic.

What, tell me maybe some examples.

I'd love to hear some examples of.

Clients that are using your tool
that, you know, like what, what

kinds of impacts are they seeing?

I, I, some, some are tangible,
some are probably intangible, but

what, what, um, do you have any
anecdotes that we could digest?

Clay Sharman: Actually
we got a few good ones.

Um,

Reed: Yeah.

Clay Sharman: one of our early
customer surprises, that I like

sharing is, uh, they're, they're
an energy drink manufacturer, uh,

Reed: Oh.

Clay Sharman: ketones, but they,

Reed: Okay.

Clay Sharman: you know, direct product.

Customer facing.

Um, one of the things we do is we collect
the com commer commercial visitor as

well as the consumer, so B2B and B2C.

And so they weren't really
interested in the B2B side of

things, even though we were

Reed: Hmm.

Clay Sharman: a little bit of information.

but when we dug in to see who in that
professional traffic was looking around,

seeing a particular national gym that.

their chief marketing officer was
coming to the site a fair amount,

enough to generate like, Hey, you
should probably reach out and see

what they're, what they're thinking.

If you're not thinking about it, they
might have an idea and, you know.

Anyway, cut the long story short,
they wound up signing a national deal

to put all of their products in the
cafes, in these gyms for everyone

Reed: Wow.

Clay Sharman: country.

And so it wound up being
their biggest partnership.

And, and it was just an outgrowth
of the data that we were collecting.

So, you know, we had warned
them in a very positive way.

You can't answer a
question if you don't know.

What to ask and you can't ask
a question without the data.

And so just by us presenting the
data, it began a conversation.

So that was a great surprise for us

Reed: Yeah.

Clay Sharman: that became a very
good use case for us to talk through.

Don't dismiss an opportunity 'cause
you have a perceived notion of who your

audience is or who you're talking to.

And then the other thing is you know,
understanding the difference between the

ICP, that ideal customer profile and then.

The ideal web surfing profile
typically looks vastly different.

And so it's very important
from a website standpoint.

So you brought it up, it's
important to see what, what are

people digesting from the site?

What's working, what's not working?

So, you know, those are
questions we're not really built

to, to hone in on right now.

But over time, that's
information that we could make.

Kind of predictions on based on traffic,
what pages are being avoided, which pages

are people lingering on, scrolling down.

so there are some secondary things that
you could start to look at and say,

you know, we put this landing page up.

Nobody seems to be going to it.

That's not what our goal is.

But that's a capability that we have in
the data that we collect to say, yeah,

we don't know why, but this is something
we should probably pay attention to.

And if you look at the
demographics, you may discover.

landing page is speaking to the wrong age
group or the wrong gender or whatever.

But you could then answer it.

And then of course, the most obvious ones
are, know, suddenly being able to speak to

this much higher top funnel of marketing
prospects that went to your site.

And so you don't have to
introduce yourselves to them.

So that was a key one, right?

Is this idea of you're, you're
really just reintroducing them and

giving 'em an opportunity to come
back in and learn a little bit more.

different than.

Me reaching out and saying,
hi Reid, my name's Clay.

I'd like to tell you about what I do.

It's different than if I know you'd
come by over the weekend and I just

didn't get a chance to talk to you.

Now it's a completely different
conversation and that's really what

we're real, uh, you know, our customers
are discovering is the ability to

segment and sort how they talk to
smaller audiences within their funnel.

driving up click rates, it's driving up,
you know, all of the things that you'd

like to see from an engagement standpoint.

you know, and then ideally it's
setting everybody up for becoming a

customer faster, building this trust,
so some really cool ways to use it.

And then, you know, over time, what
I'm really excited about is, you

know, when, and we're not there yet,
uh, because, you know, we, we started

onboarding people last year, so we're
only now just getting into that 12

month, um, kind of return trip on
what 12 months looks like and beyond.

But I think the most exciting things are.

When we have kind of garnered
the trust of our customers from

the standpoint of predicting, you
know, what's likely to happen going

forward in the next 12 months.

And that's really gonna be cool because
then at that point we really are the team

member and kind of a specialist in an
area that up till now you sort of had to

write off as a lost marketing opportunity.

Yeah.

That's the cost of doing business.

You know, you drive a lot of people
in, in hopes to get a few out of it

and now we can sort of change that
equation and suddenly you're looking at.

Uh, opportunities differently, that's all.

So, those use cases are exciting and
you know, there it should be endless

because you could be as creative as you
want with the data that you're looking

at, and it can be unique and it can
be very, um, surgical in how you're

using it for you versus how it worked
for, you know, like a service company.

A product company might use
it totally differently, and

that's what's cool about it.

If you have the data,
you can ask the question.

Reed: Yeah.

Well, I love what you're describing.

It, it, um, you know, it's like
driving the user experience, design

process, uh, forward, because I.

You know, uh, I've worked with
user experience designers.

I'm not one myself, but, um, I
understand a lot of their process is

observational and, and observing how
people interact with your, uh, your,

your physical products, your, your
website in a, in a captive environment.

But, but your, uh, but the anonymous
traffic has always been a question mark.

You know, it's, it's, um, you've been
able to get like wide swaths from Google.

Analytics, you know, like age ranges,
gender ish, you know, like measures.

But to get down to individuals and,
um, you know, it, it, it changes a lot.

'cause it, like you said, it, it
might change the kind of customer.

You decide to, to target.

Uh, you, you, it might, it might
change the kinds of products you

promote or, you know, the ad spend.

And it's, I mean, it, you know,
the, the, the principle is, um, is

is the same as it's always been for
designing your, your user experience.

But with this richer information,
you can, you can actually do it.

Yeah.

Clay Sharman: I would say that,
you know, the way I look at it is

I try to invert the model, right?

It's sort of statistically
a 2% success rate.

98% come in and take
no action and leave 2%,

Reed: Mm-hmm.

Clay Sharman: give you what you
want, and hopefully become customers.

build your entire strategy around that 2%.

And we're like, man, what if we could
knock that, you know, open to 3%?

You know, or 4%.

I mean, it's a massive impact
across the bottom line.

And yet from my perspective, just a 2%
bump in data that I can now look across

that we could be examining at AI speed.

And so concept should be there's no
reason we, we can't get there and help

the market understand at a broader level
to do what you just said, which is.

Hey, what products do we
wanna introduce next year?

That because of the way people
are engaging with the site,

maybe there are things we didn't
think about that we should be.

And so that would be my ultimate goal in
the boardroom is, you know, conversations

that go just beyond marketing and
sales, but the overall kind of future.

Outlook of the company, you know, uh,
maybe the way that the web branding

is kind of going forward and all of
those things where that kind of data

can influence each one of those areas
and have a broader business impact.

That would be awesome.

You know, and it's possible.

That's what's cool.

I.

Reed: So let me, uh,
zoom out a little bit.

And now as a business owner, um, and
your own marketing efforts as you're

promoting Cradio, can you tell me.

What channels do you like to,
you know, you found success with

in promoting your own business?

And, you know, maybe, I mean, I'm
sure you've used your, your eating

your own dog food, so to speak,
you know, and using your own tool.

Like what, what have been some
learnings you've had along

the way in promoting Cradio?

Clay Sharman: Yeah, great question.

So, you know, coming out of the gate it
was a lot of, um, sort of our own investor

community referral group that was kind
of passing us around and getting us out

there and then doing things like, uh,
articles about what's happening and trying

to get them into the technology kind of.

Uh, eyesight so that people have eyes
on it and understood what we were doing.

And talking to people like you
who have great questions from

a marketing standpoint about
how could we be doing better.

we started doing, you know, we worked
with, um, direct sales outreach efforts.

Um, we're currently doing a lot of work
on LinkedIn, which is yielding some,

some good, really good results actually
from a, you know, booking which, you

know, from my perspective, it was simply.

we knew we had a problem that's gigantic.

It, it's a trillion dollar
industry that we're trying to

tackle and we wanted to take, you
know, know, the right bite sizes.

But I also wanted to make sure that we
weren't missing, too many opportunities.

So, LinkedIn's a great space.

Uh, we have good metrics around, um.

Um, converting a demo to a customer, we
just weren't getting enough demos, and

so it just became a volume game for us.

So, we use companies that use AI to
identify the best targeting pools.

Areas like financial services
has been good for us.

Um, obviously retail.

Um, you know, one of the challenges
with retail and, and I'm not giving

anything away, is, uh, retail
companies typically, they have a jaded.

a jaded kind of view on the
technology stack and what AI

means in that technology stack.

Oh yeah.

I mean we, we saw, I've seen 10 demos
of companies just like you, and then

I always say, I bet you haven't.

when I show them there, there is a
leaning in and there is a, well, I

didn't know you could do all that,
so, Separation in a, in a large

competitive space, like retail is tricky.

There's a lot of noise and, and
it's hard, I can't shout as well

in that space as I could in other
spaces, but retail is a clear target

for us, so we don't wanna miss out.

So, you know, we're doing, it's just,
yeah, LinkedIn, social media, um,

kind of direct dial outreach using AI
technologies to try to find industries

where people, you know, should be
interested and probably are so.

don't think we're doing anything
that's, um, different than every

other company's trying to do, which is
maximize the potency of what we're doing.

But of course, we do use Cradio to
identify our own visitors, and that

works out as well as, or better than
every other thing for the same reason.

Right.

They, I know they've gone to the site,
they typically have some questions.

Um, you know, anytime you can get them
to say, well, I went to your site and

it looks pretty interesting, you know,
you're gonna have at least a demonstration

to show them why it's interesting.

So that's been great.

It's just you know, we're still
trying to build our own SEO volume

at a level that would give us, you
know, man, if, if I could build

the pipeline from my own SEO stuff.

But we're not, we're not
getting that kind of stuff.

We're busy trying to get
our name out so that other.

People hear about us.

So it's a little bit of a, I'd say
marketing is one of the areas where I'm

trying to get smarter, faster now at,
at the same time to take advantage of

what's, what's out there and available.

Reed: Well, and you know, it,
it, everything does feel, it.

It's, it's like a combination of some
marketing approaches are tired and, you

know, but then some, some things are, um,
are very new because, you know, you're.

You've got a new product, a
new concept, you don't really

have much to compare it to.

I mean, there, you know, some at a high
level, but you're, you're within that,

you're, you're delivering so much more.

And so if you take the, you know, the
route of I'm, you know, we're like

Google Analytics or, or meta tags, you
know, and, um, then people look away.

But, you know, if you, um, if you
don't use that context, it's hard

to, hard to explain on a first touch.

So.

Clay Sharman: yeah, actually
that's a great point.

It really is hard to figure out
what that sweet spot is when

you're trying to describe, I.

You know, because the question is
invariably does pop up, well, who are you?

Like?

And if your answer

Reed: Right,

Clay Sharman: we're not really like
anybody quite, then it's kind of like,

uh, I don't know what that means.

You know, is that gonna be useful to me?

And so you

Reed: right.

Clay Sharman: you know, you have to
walk that line and make sure that

there's a familiarity that says,
oh, okay, you're like those guys

only smaller, more nimble, whatever.

And, uh, you know, typically when
we talk about the individual, the

anonymous individual, and what we're,
what we're capable of doing to find.

10 or 50 or a hundred or a thousand more
of that person who's, you know, supremely

interested based on how they interacted.

a very key differentiator across any other
platform that I'm compared against once.

Once we talk about personalizing
the scoring and audience building

based on personalization.

Most people kind of have to bow
out of the race at that point.

I've taken a good lead, so you know, if
I'm running that four by 100, that they

usually don't have that fourth leg runner,
and so typically bringing it in even if

they can keep up with me for three legs.

And so that was intentional.

We wanted to make sure we had a full
completed journey where we could then

take what we learned on the first journey.

And predict what the second
journey return might look like.

And that's also very different, um,
in terms of what's available today.

And, you know, whether I think
that's gonna stay the, the case

or not to be, to be determined.

But right now, that is
the long and short of it.

We, we can do things that
other platforms don't.

Reed: Yeah, well, I, you have a great
product and, and, um, uh, you know, like

as, as somebody that's, you know, trying
to generate more leads for clients,

you know, this is, this is like gold.

This is really, really
valuable info and, um.

You know, I, yeah.

So I'd encourage everybody
to, to reach out.

Um, one last question before we wrap up.

Um, and I'm gonna ask you to put
on your predictor hat and say

Clay Sharman: I am

Reed: Exactly now AI is,
has been changing so much.

We were talking about this
before the call, um, the.

It seems like the rate of acceleration,
um, is, it's hard to understand how

much new, um, how much is new about
ai, uh, you know, every day, every,

every, uh, every update we get.

What do you see as the future, you
know, in, in this year and coming

years of AI and AI for marketing?

Um, do you have any, uh, any thoughts on
what we can anticipate coming up soon?

I.

Clay Sharman: Yeah, actually that's
a timely question for two reasons.

One, it's one that we're keenly interested
in, but two, um, I got the opportunity

to sit and moderate a panel down in, uh,
new Orleans in April for the American

Marketing Association, and it was their
inner collegiate college graduate program.

So there was about

Reed: Oh, cool.

Clay Sharman: Uh, emerging graduates
who are interested in marketing.

And that question came up amongst the
panel and um, you could imagine some of

the answers were optimistic and some were
a little bit, you know, kind of scary.

So the, the one thing that I do think is
likely to happen is there are gonna be

a reduction in, in marketing team sizes.

'cause AI can do things and mimic.

In credibly, and in some, some cases,
you know better because they have a

broader base to kind of research into.

And so copywriting is a tough one.

I, you know, so I wouldn't want to pick
and choose, but I do think marketing teams

are gonna get smaller and more nimble.

Um, I think, you know, um, what's awesome
about it is there's still gonna be the

o the opportunity for creativity, but
it's gonna force marketers to think a

little bit differently and, and then.

Again, how do I sound a little
different in a sea of sameness?

Because AI is gonna allow just about
everybody to level the playing field.

Then it, then it falls to the
human to outthink, which I think

is gonna be an awesome challenge.

Right?

And so that was something I was
very um, up kinda the upside.

That was very exciting.

the downside is also the upside, right?

Our giant AI technology companies that
are pushing the forefront, they're

not really releasing the roadmap.

So you and I can't see the
horizon until it's actually on us.

And so, you know, if I was just guessing,
and I, I think I'll probably be right,

a good portion of this one anyway is.

Um, the term generative ai, it
sort of stormed outta the gate in

like 2022, um, and it became this
great tool that became adopted.

And then suddenly in 2024, you'd
start to hear this term agentic ai.

so, you know, at the simplest
level, you have this.

to generate an answer.

And one of the problems with it was,
of course, you know, it didn't know

enough not to sometimes hallucinate,
which is a term where it made up the

ending of the story or filled in parts.

Um, but it could generate things
at speed and at a competence

that was, you know, eye popping.

And now you move to this ag agentic
world where it doesn't just generate

the answers, it, it actually sets
the table to take the action for you.

And so.

know, I think that's gonna be awesome
because I think workflow automation is

going to change, um, in, in the near
future where workflow automation is gonna

finally have a permission statement at
the end where, you know, companies will

have the option to flip that toggle that
says Yes authorized, and then an AI.

Platform or AI technology is gonna be
able to actually close the circuit itself

on an action that it's basically said,
would you like me to, on an ongoing

basis, continue to do this for you?

And then if you toggle it to, yes,
it's a set it and forget it type of

methodology, which is really different.

And then I think, you know, the next
obvious leap from there will be you, once

we have a trust in the AI's ability to
take that action and deliver results.

Pretty soon it'll, you know, it's gonna
become a real recommendation platform

that's going to be the, the one that
suggests the, the movement at some point.

then that, that I think is where
we're gonna come, you know, kind of

have that next conversation of is
this a good thing or a bad thing?

And I think the answer is gonna be.

Yes.

Right.

It's gonna be both and, and
it'll just to be depend.

So, but I do think we, it's a, it's
an inevitability that the, the AI is

gonna become the recommendation agent
before, you know, before long and

maybe faster than I'm even imagining.

I'm thinking I've got 16 months
maybe AI's laughing at me

saying, I'll see you in six.

You know, so I just, just don't know.

Reed: Well, I mean, I, you know, I think
it's, it's good to go in with eyes open.

Um, you know, I tell all my
clients, um, you know, you

have to be acquainted with ai.

If you don't see the use case
yet, um, you know, that's fine.

You know, as the agents get
stronger, there will definitely

be more and more, uh, use cases
for more and more businesses.

But you don't want to be.

On the, the tail end of it where,
you know, you hadn't ins decided not

to build a website or decided not to
install phones or, you know, any of

this where, um, you just got disrupted
and you had plenty of warning.

Clay Sharman: Yeah, actually that, that

Reed: um,

Clay Sharman: reminded me of one
more thing that I should have

Reed: yeah.

Clay Sharman: the way you said it.

I think it's important that we as the
marketers or the users understand why.

platform gave us the
answer, it gave us you.

You can't take it for granted
that it's the right answer

because it was generated by ai.

So I think, you know, there, it's gonna
be kind of incumbent on us to keep

challenging the why of the question,
but I, I totally agree with you, Reid.

You have to not be afraid of it.

You need to understand what use case
applications are available to you and

you need to sort of dive in and say.

here.

I don't, I like your use
of the term tail end.

I don't wanna be the person
riding in the back who's kind of

Reed: Right.

Clay Sharman: else in front of me.

So I think if you can adopt a mindset
of this should be a great tool, right?

It's it.

It's a tool still no matter
what, it shouldn't be the answer.

it could feed, you know, and inform why
your answers are getting better, right?

As long as I think you challenge it.

So my optimism right there
at the tail end is we

Reed: Yeah.

Clay Sharman: it, but
we should challenge it.

Reed: Yeah, and I, I too lean towards
the optimistic side, but you know,

of course it's, uh, you know, we,
we just have to be aware and, and

consider all the implications.

Well, clay, can you tell us, just in
closing, um, you have a great product.

I, I think you've got some tremendous
expertise in, in this field.

Where can listeners find you if
they'd like more information,

uh, from you or from Cradio?

Uh, what, what's, what are
the best places to find you?

Clay Sharman: so obviously you can go to
our website, which is simply cradio.ai.

Um, you can find us on LinkedIn and
we do a weekly biweekly newsletter.

I'm still working on which one it
is, but we pro produce the newsletter

fairly regularly and there's a lot
of, you know, most of the emphasis

on those net newsletters is.

The use of ai, not just as a, as a,
you know, um, answer, but you know, the

things that you should be leveraging as
a use case and how to talk to people.

So that's a great place.

So LinkedIn, you can
find us again, cradio.ai

there.

Um, we are on Facebook, um, you know,
and so we're trying to find it, but the

website and LinkedIn are the best ways
to reach us, and you can get some great

information off of the LinkedIn page on.

You know, for Cradio.

So, and feel free, you know, I hope
everybody will sign up for that

newsletter 'cause I enjoy writing it.

um, you know, it's, it's a,
it's a great way, it's not

technical, so it's easy to digest.

And so it's been a lot of fun.

But yeah.

I

Reed: Perfect.

Clay Sharman: was great.

I.

Reed: Yeah.

Well, thanks so much, clay.

And uh, you know, I learned a lot
and, you know, I think this will be

really beneficial to, to our audience.

You know, we've got a lot of business
owners, a lot of non-technical

marketers and um, you know, just the.

More information we have and especially
from somebody that's really immersed

in it like you are, is, is, is great.

Clay Sharman: I

Reed: So.

Clay Sharman: the opportunity and for
the non-technical people out there,

you know, uh, it's, it's, um, you know,
think of it in terms of how you'd like

to see the information on your customer.

Improved and then that
sort of softens the idea.

'cause intelligence can help with that.

And that's the good news.

And you know, we really are excited about
what's possible and I do want to end on

this very positive upbeat data privacy
note where, you know, we do only collect

information from the website traffic,
which means it's all first party data.

we don't use third party sources.

And uh, you know, so.

Our whole goal is the ethical use of
data in the service of building a trusted

relationship the brand to the consumer.

'cause at the end of the day, you and I
are consumers, and it would be great if we

trusted the brands that had access to us.

So we weren't always scratching our
head as to how information got out.

were just more impressed with how
it's being used to kind of provide us

with the most relevant material or the
most relevant products and services.

And so that's really our.

goal is to help reduce spam across all
advertising channels and, and, you know,

Reed: Yeah.

Clay Sharman: impactful.

So enough of my

Reed: That's great.

Clay Sharman: there,

Reed: No, no, I think that's important
and, you know, an important piece of

the, the trust puzzle that, that, uh, uh,
everybody, everybody wants to consider.

So thanks again, clay and, uh,
look forward to, to continuing

conversation in the future and,
and, uh, following your progress.

Clay Sharman: so much, Reid.

This was great.

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