September 25, 2025 • 17 mins
This week's show is entitled, "AI-Native Demand Generation Best Practices" and my guest is Alex Roy, Founder & CEO at SalesboxAI.
Tune in to learn:
- Discover how AI Native Demand Gen helps orchestrate personalized, efficient marketing at scale.
- Understand the role of real-time intent signals in identifying and engaging the right leads.
- Learn about overcoming common barriers to AI adoption in sales and marketing teams.
Listen Now | Watch the video HERE
Matt interviews the best and brightest minds in sales and Marketing. If you would like to be a guest on Sales Pipeline Radio send an email to acceleration@heinzmarketing.com.
Sales Pipeline Radio was recently listed as one of 30 Best Sales Management Podcasts and Top 60 Sales Podcasts
You can subscribe right at Sales Pipeline Radio and/or listen to full recordings of past shows everywhere you listen to podcasts! You can even ask Siri, Alexa and Google or search on Audible!
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Matt Heinz (00:17):
All right, well happy Thursday everybody.
Welcome to another episodeof Sales Pipeline Radio.
I'm your host, Matt Heinz.
Excited to have you all here inthe middle of your workday, in
the middle of your work week.
We are somehow, Alex, into late Septembernow as we record this, which is nuts.
But here we are soexcited to have you here.
If you're joining us live onSales Pipeline Radio today,
(00:37):
we're excited to have you here.
If you wanna be part of the show, make acomment, ask a question, make a rebuttal.
Any of those are fairgame, we will see those.
We can respond to those.
We can bring your comment orquestion up on air, onto the screen.
So we'll make you part of the show.
And thank you for doing so.
If you're watching or listening on demand.
Thank you so much for being part ofthe Sales Pipeline Radio community.
(00:59):
Every episode is available, past, present,and future at Sales Pipeline Radio dot
com, and very excited to have with ustoday, the founder and CEO of SalesboxAI.
Alex Roy, Alex, thanks verymuch for joining us today.
Alex Roy (01:12):
Hello.
Nice to be here.
Excited to be here, Matt.
Matt Heinz (01:15):
All right.
So, when we talked earlier and youbrought up this idea of AI native
demand generation, I don't think I'dheard anyone describe that before.
We've seen and worked with a lot ofcompanies that are heavily incorporating
AI into various go to market motions.
But I'm curious, maybe let's just startwith just an introduction yourself and
like, what is AI Native Demand Gen.
Alex Roy (01:37):
Sure.
Yeah.
it's about, you know, AI has been aroundfor several years and, when we talk about
AI native Demand gen, it's about havingan AI agent that is ingesting signals,
realtime signals and making decisions.
And, making sure that it isorchestrating other agents to make
(01:59):
sure that, the right person getsthe right message at the right time.
And, yeah, so it's, it's integrated.
You know, you don't have differentsilos of, systems in place.
So the data is available as wellas the signals go to an AI agent
that takes those decisions.
Matt Heinz (02:17):
So how, I mean for those that are thinking about incorporating
this, like how is this different thanjust sort of traditional demand gen?
Is this new or is this an evolution?
How should people think about it?
Alex Roy (02:27):
Sure.
Yeah.
So, I would say in the, in thepast, you know, the, the fundamentals
still remain the same, right?
But what's different is that,probably, you know, and end of
the day we have to stay human.
We have to stay, you know, make surewe each account and each person and
each contact has the right experience.
But unfortunately, wecouldn't do that at scale.
(02:49):
We had to make sure that, you know, wehad to kind of divide it into personas
and, you know, probably just look at afew, you know, maybe a handful of them and
have one set of message for each of those.
But with an AI agent, what you areable to do now is that give each
account and each contact the rightattention that, that they truly deserve.
(03:10):
So it can be orchestrated atscale and helps you, make sure
that you know, you are earningthe trust of that buying group.
Matt Heinz (03:19):
You know, is the complexity of go-to market motions and complexity
of buying journeys continue to grow.
You know, that we're also seeing,of course, board members and
investors saying, do more with less,
be more efficient.
And yet the motions
we're trying to execute often are really
struggling with speed to market and
efficiency.
Right?
Can you talk about
how AI can really directly address that?
(03:39):
Not in a future state, but right now?
Alex Roy (03:42):
Sure.
Yeah.
So, bandwidth is usuallythe biggest constraint that,
that we have as marketers.
And, you know, an AI agent helps, youknow, gives you that scale wherein
you are able to be more efficient.
'cause now you have the agent takeon some of the laborious tasks.
Be it, you know, from signals, youknow, you have thousands of signals.
(04:04):
But, you know, just distilling downthat into, you know, the right ones you
know the, the noise out of the signals,that's where the agent helps you.
So it makes your overall moreefficient, in terms of that.
Matt Heinz (04:17):
And what does that mean in terms of like realtime intent signals?
I think, you know, I think we'vehad signals around for a while.
How does AI, how is AI different?
How is it different in terms ofspeed, in terms of context, in
terms of, you know, everything.
Alex Roy (04:33):
Yeah.
So, when it comes to intent signals,the key is time, because it's
ephemeral, you know, it doesn't,you have to act on it quickly.
And, a good
example of an intent signal issomebody showing up on your website,
and there's thousands of visitors each month that a company has.
And, these signalsneeds to be, inferenced.
And, you know, you have to identify whichaccount it is, which person it is, and
(04:57):
then have personalized conversations.
So an AI agent helps you facilitate that.
Matt Heinz (05:03):
So walk me through an example of that.
Right.
So like, let's say I'm an, let'ssay I'm an inside sales rep. I'm A
BDR, You know, is this followingup on leads I already have?
Is it identifying newleads I should engage with?
Is it a little bit of both?
Alex Roy (05:15):
Yeah, it's a great question, right?
So typically what you have in anorganization is, you know, there's
a sales focus set of accounts that,you know, sales is looking at.
There is a wider set of accounts thatmarketing is looking at, and then there
are these white space accounts, right?
So, what the agent is doing is, youknow, it's listening for signals and
first party signals is very important.
And as you know, and off the website,it listens for that and, it tries to
(05:40):
find, you know, does that match your ICP?
Is that part of a sales focus account,or is that a marketing focus account and
then it hands it over to another agentthat is going to have that communication.
So for example, if it were a salesfocus account, you know, it's
going to be having a play whichis on behalf of the sales rep.
And, the goal is to, youknow, to get to a meeting.
(06:03):
And whereas if it's a marketingfocus, it's a wider account, you know,
it, it goes into a nurture stream.
So it's not just a single agent, butstarts from a signal, but then you know
the next best action is handed off toanother agent, depending on, you know,
how relevant it is within that ICP.
Matt Heinz (06:21):
Talking today on Sales Pipeline Radio with Alex Roy, he's
the CEO and founder of SalesboxAI.
It's one thing to talk aboutwhat the technology can do.
It's another thing, Alex and youknow, directly to, to get people
to actually do this at scale.
From your work, what do you seeas some of the biggest barriers to
getting sales and marketing teamsto not just experiment with AI?
(06:42):
This isn't thinking about this not justas a tool, but as infrastructure, as
part of a consistent, complex playbook.
What are some of the barrierskeeping people from doing that?
Alex Roy (06:52):
I mean, you know, there's, there's the number one,
I would say, resistance to change.
There is a bit of an unknown.
You know, so it's abouttaking that first step.
You know, it's about, we always recommendto our customers to list down the tasks,
you know, that's part of, you know,your Go to Market that you do today,
and then, you know, the first step isto make sure, identify the task from
(07:15):
that list, which could be automated,that could be, you know, where you
could have assistance of an AI agent.
And, what the agent really is doing ishelping you to get to more detail than
you could possibly have done earlier.
So, probably, you know, it's not likeit's taking off just, it's doing more work
(07:35):
than what you were able to do earlier.
Matt Heinz (07:38):
Yeah, and I think, is there a phased work program you recommend people?
I think if you're thinking aboutdoing AI native demand gen, I mean
oftentimes if we're doing a test witha client or sort of recommending it's
not just launch everything right away,do it in a particular market, do it
a particular industry, pick a segmentof the sales team to start it with
kind of Is there a phased approach?
You recommend people think about that?
Alex Roy (07:59):
Absolutely.
Absolutely.
Yes.
Yep.
Yep.
So we recommend, you know,it starts with signals.
So, you know, we recommend a subset,a specific product page on your
website where you add a tag sothat the agent is listening for the
intent on that specific set of pages.
It's probably, you know,perhaps product centric.
And, you know, so you have, you know,you look to have the agent identify who
(08:24):
is on the website, which company is there,and then orchestrate plays based on that.
So.
Yes.
A phased approach is the alwaysthe recommended way to proceed.
Matt Heinz (08:35):
I've seen some reports already, of, you know, like Forrester
for instance is saying that theymight be seeing some budget cuts in
2026, which I think might be justsort of exhausting to people that have
been through what they feel like hasbeen two, three years of doing this.
I feel like we're getting to this pointwhere this is not just optional, right?
That adopting these programs is kindof mandatory if you want to survive.
(08:58):
And I think, you know, can you talk aboutnot just the program implications you
mentioned earlier just the culture changeis required internally to make this move.
What are you seeing from CMOs andCROs that are operationalizing
this quickly, but also managingthe human element behind it?
Alex Roy (09:17):
Yeah.
So, you know, budgets is a challengeas like, you're, like, you rightly
pointed out, and it, it's forcingteams to be more efficient.
It's about unifying theMarTech stack that you have.
It's about, you know, making sure that,you know, there is, you know, you are.
You are, you know, there's, there'sless inefficient systems in, you
know, within that MarTech stack.
(09:38):
So yeah, so we work with them in aphased approach, like I mentioned
earlier, and it starts with, youknow, a specific use case.
And usually that's about, you know,the inbound leads that you know that's
coming in onto your website and,you know, how can an agent help you?
There is where we start.
Matt Heinz (09:56):
So I think about this, I mean, we've been talking sort of
almost with the assumption that thisis a sort of a direct sales engagement,
but it strikes me that this can impactpartner and channel sales as well.
Have you seen those use cases?
Alex Roy (10:06):
Yeah.
So, one of the challenges which, whichcompanies have is that the partner has,
you know, the, the product knowledgethat the partner has is limited.
They have multiple productsthey're looking at also.
So, you know, an agent that isknowledgeable makes the partner more
knowledgeable indirectly as well.
So the use cases where, you know, wegive an agent to the partner that,
(10:28):
that's grounded to reality by, by theproduct collateral, which is available.
So the partner readily is ableto access that information
and, be more, knowledgeable whenpresenting that to customers.
Matt Heinz (10:44):
Can you help with a little expectation setting
for programs like this?
You know, whether you're takinga phased approach or implementing
a technology like this.
Like what, how much time does that take?
How many people does ittake to implement it?
How much time does it take to implement?
And then what should people'sexpectations be about how and
when it starts to deliver results?
Alex Roy (11:03):
Yeah, I mean, you know, in terms of rollouts, typically we see like two
weeks to four weeks, somewhere in betweenthat in terms of timelines and, part of
it also has to do with, you know, there'ssome back and forth with, with the
marketing team and the IT team as well.
But yeah, but generally we see abouttwo weeks to two to four weeks.
Matt Heinz (11:21):
And then what... I love asking the question about doing a
sort of a pre postmortem, right?
Like if we were, say, if someoneimplemented sort of these programs
today, if we're talking about threemonths from now and they have not
been as successful as people want.
If you do the postmortem, then whatare the things you hear most often?
Like, what are the things thatmost often keep a program like
(11:42):
this from being successful?
That people that are leaning in and sayinglike, I need to adopt this, should be
aware of and prepare for now, so thatthey increase their chances of success.
Alex Roy (11:50):
Sure.
Yeah.
So for example, let's say, you know, theKPI is where we wanted to generate more
intent leads and content leads, right?
So intent leads is visitorsthat you convert into leads.
Web visitors.
So you have to commit, you know, sendingthe right audience to those pages as well.
So let's say you, it's likesetting up a mousetrap, but then
you know, you're not driving, youknow, the right folks there, right?
(12:15):
So, yeah, so it's about, you know, makingsure that you also have a marketing
program to drive the right audienceto those pages, and then the agent is
able to, engage with them, identifythem, and then engage with them.
So that's, you know, that's number one.
The other is another metric you look atis, so we have an integrated asset hub.
(12:35):
You know, you have an asset hubwhere the agent is knowledgeable
about the assets, so it's able to,so another KPI we typically look
at is, you know, how many marketingqualified leads were you organically
able to generate, and, you know, howmany conversations were created.
So those broadly I would say, youknow, are the three key metrics, that
(12:58):
would come out of this as an outcome.
Matt Heinz (13:04):
I am curious to hear from your perspective, this is a little
take a different approach, just thespeed of innovation happening in an AI
forward company right now versus sort oftraditional growth and development cycles.
I mean, from the outside it seems likethings are moving incredibly fast, and I
can only imagine that growing a companyin this space is controlled chaos.
(13:26):
What's it like on the inside, sort ofriding this enormous tidal wave right now?
Alex Roy (13:32):
Yeah, it's a great question.
I mean, over the last 10 years, youknow, we've you know, gone through
multiple eras of evolution, I wouldsay started back in the days with, you
know, you have classification models,you know, it's neural network based,
and now you have the LLM based model.
So it's about evolving like you mentioned,and, being engineered to evolve.
(13:53):
Right?
So, which is very important.
So one of the examples is, we look atspecific use cases and which is the right
model for that, is that, should that beusing a fine tuned model that we have
versus, you know, for this specific task,you know, there's another model to use.
So it's about plugging in the right modelsfor the right use case, I would say.
(14:14):
And yeah.
Matt Heinz (14:15):
And I think, you know, I'm thinking about integration
of these programs as well.
Like the volume of tools that marketingoperations folks at RevTech, you know,
people are managing is significant.
I'm hoping that you are gonna help usbuild and you envision a day when we may
have separate tools, but AI actually helpsthem operate and integrate and communicate
with each other a little more seamlessly.
(14:36):
And I'm hoping that that actuallysolves what many people have as a
data management problem as well.
Which inhibits AI from oftentimesdoing what it needs to do.
How do you envision thefuture of the tools, the data,
the integrations happening?
Alex Roy (14:51):
Yeah, it's a great question.
You know, like you rightly mentionedfor AI, you know, you need to make sure
the data is accurate, that, you know,it works on the right data, right?
And in terms of tools, also there areprotocols like MCP, which vendors are
using to enable, the existing agentwith additional skills you could say.
(15:12):
So give it additional context.
So, it's about, you know, you wouldsee each of the, product in the
MarTech stack has this connectorback to this agent and, you know,
enables the agent to, to be more, moreproductive across different systems.
And, at the same time, IT needs tobe able to set certain ground rules,
access controls, et cetera, also.
(15:32):
So it's almost an additional, personwithin the organization that's,
utilizing these, permissionsand making good things happen.
Matt Heinz (15:43):
I think maybe more than any technology we've seen before, AI
has democratized software development.
Right?
I mean, the vibe coding is real.
You can talk to a machine andit will build something for you.
I think that is changing howmany people think about managing
their own technical expertise.
As business leaders, what advice wouldyou give someone sort of new, you
(16:07):
know, sort of recent college grad,who's trying to figure out what skills
they need to have, who in the past,unless they were a developer, didn't
worry about needing to build code.
What advice do you give to thatup and coming business leader now?
I was building to my theme there, andI think I lost Alex, did we lose Alex
(16:28):
right before my last question to him?
Oh no, we did lose Alex.
Well, anyway, thank you Alex, forjoining us today on Sales Pipeline Radio.
Really appreciate everyone joiningand listening to us as well.
Have a great week.
We'll see you next week on anotherepisode of Sales Pipeline Radio.
Until that'll be well, take care.
All right, well happy Thursday everybody.
Welcome to another episodeof Sales Pipeline Radio.
I'm your host, Matt Heinz.
Excited to have you all here inthe middle of your workday, in
the middle of your work week.
We are somehow, Alex, into late Septembernow as we record this, which is nuts.
But here we are soexcited to have you here.
If you're joining us live onSales Pipeline Radio today,
(00:37):
we're excited to have you here.
If you wanna be part of the show, make acomment, ask a question, make a rebuttal.
Any of those are fairgame, we will see those.
We can respond to those.
We can bring your comment orquestion up on air, onto the screen.
So we'll make you part of the show.
And thank you for doing so.
If you're watching or listening on demand.
Thank you so much for being part ofthe Sales Pipeline Radio community.
(00:59):
Every episode is available, past, present,and future at Sales Pipeline Radio dot
com, and very excited to have with ustoday, the founder and CEO of SalesboxAI.
Alex Roy, Alex, thanks verymuch for joining us today.
Alex Roy (01:12):
Hello.
Nice to be here.
Excited to be here, Matt.
Matt Heinz (01:15):
All right.
So, when we talked earlier and youbrought up this idea of AI native
demand generation, I don't think I'dheard anyone describe that before.
We've seen and worked with a lot ofcompanies that are heavily incorporating
AI into various go to market motions.
But I'm curious, maybe let's just startwith just an introduction yourself and
like, what is AI Native Demand Gen.
Alex Roy (01:37):
Sure.
Yeah.
it's about, you know, AI has been aroundfor several years and, when we talk about
AI native Demand gen, it's about havingan AI agent that is ingesting signals,
realtime signals and making decisions.
And, making sure that it isorchestrating other agents to make
(01:59):
sure that, the right person getsthe right message at the right time.
And, yeah, so it's, it's integrated.
You know, you don't have differentsilos of, systems in place.
So the data is available as wellas the signals go to an AI agent
that takes those decisions.
Matt Heinz (02:17):
So how, I mean for those that are thinking about incorporating
this, like how is this different thanjust sort of traditional demand gen?
Is this new or is this an evolution?
How should people think about it?
Alex Roy (02:27):
Sure.
Yeah.
So, I would say in the, in thepast, you know, the, the fundamentals
still remain the same, right?
But what's different is that,probably, you know, and end of
the day we have to stay human.
We have to stay, you know, make surewe each account and each person and
each contact has the right experience.
But unfortunately, wecouldn't do that at scale.
(02:49):
We had to make sure that, you know, wehad to kind of divide it into personas
and, you know, probably just look at afew, you know, maybe a handful of them and
have one set of message for each of those.
But with an AI agent, what you areable to do now is that give each
account and each contact the rightattention that, that they truly deserve.
(03:10):
So it can be orchestrated atscale and helps you, make sure
that you know, you are earningthe trust of that buying group.
Matt Heinz (03:19):
You know, is the complexity of go-to market motions and complexity
of buying journeys continue to grow.
You know, that we're also seeing,of course, board members and
investors saying, do more with less,
be more efficient.
And yet the motions
we're trying to execute often are really
struggling with speed to market and
efficiency.
Right?
Can you talk about
how AI can really directly address that?
(03:39):
Not in a future state, but right now?
Alex Roy (03:42):
Sure.
Yeah.
So, bandwidth is usuallythe biggest constraint that,
that we have as marketers.
And, you know, an AI agent helps, youknow, gives you that scale wherein
you are able to be more efficient.
'cause now you have the agent takeon some of the laborious tasks.
Be it, you know, from signals, youknow, you have thousands of signals.
(04:04):
But, you know, just distilling downthat into, you know, the right ones you
know the, the noise out of the signals,that's where the agent helps you.
So it makes your overall moreefficient, in terms of that.
Matt Heinz (04:17):
And what does that mean in terms of like realtime intent signals?
I think, you know, I think we'vehad signals around for a while.
How does AI, how is AI different?
How is it different in terms ofspeed, in terms of context, in
terms of, you know, everything.
Alex Roy (04:33):
Yeah.
So, when it comes to intent signals,the key is time, because it's
ephemeral, you know, it doesn't,you have to act on it quickly.
And, a good
example of an intent signal issomebody showing up on your website,
and there's thousands of visitors each month that a company has.
And, these signalsneeds to be, inferenced.
And, you know, you have to identify whichaccount it is, which person it is, and
(04:57):
then have personalized conversations.
So an AI agent helps you facilitate that.
Matt Heinz (05:03):
So walk me through an example of that.
Right.
So like, let's say I'm an, let'ssay I'm an inside sales rep. I'm A
BDR, You know, is this followingup on leads I already have?
Is it identifying newleads I should engage with?
Is it a little bit of both?
Alex Roy (05:15):
Yeah, it's a great question, right?
So typically what you have in anorganization is, you know, there's
a sales focus set of accounts that,you know, sales is looking at.
There is a wider set of accounts thatmarketing is looking at, and then there
are these white space accounts, right?
So, what the agent is doing is, youknow, it's listening for signals and
first party signals is very important.
And as you know, and off the website,it listens for that and, it tries to
(05:40):
find, you know, does that match your ICP?
Is that part of a sales focus account,or is that a marketing focus account and
then it hands it over to another agentthat is going to have that communication.
So for example, if it were a salesfocus account, you know, it's
going to be having a play whichis on behalf of the sales rep.
And, the goal is to, youknow, to get to a meeting.
(06:03):
And whereas if it's a marketingfocus, it's a wider account, you know,
it, it goes into a nurture stream.
So it's not just a single agent, butstarts from a signal, but then you know
the next best action is handed off toanother agent, depending on, you know,
how relevant it is within that ICP.
Matt Heinz (06:21):
Talking today on Sales Pipeline Radio with Alex Roy, he's
the CEO and founder of SalesboxAI.
It's one thing to talk aboutwhat the technology can do.
It's another thing, Alex and youknow, directly to, to get people
to actually do this at scale.
From your work, what do you seeas some of the biggest barriers to
getting sales and marketing teamsto not just experiment with AI?
(06:42):
This isn't thinking about this not justas a tool, but as infrastructure, as
part of a consistent, complex playbook.
What are some of the barrierskeeping people from doing that?
Alex Roy (06:52):
I mean, you know, there's, there's the number one,
I would say, resistance to change.
There is a bit of an unknown.
You know, so it's abouttaking that first step.
You know, it's about, we always recommendto our customers to list down the tasks,
you know, that's part of, you know,your Go to Market that you do today,
and then, you know, the first step isto make sure, identify the task from
(07:15):
that list, which could be automated,that could be, you know, where you
could have assistance of an AI agent.
And, what the agent really is doing ishelping you to get to more detail than
you could possibly have done earlier.
So, probably, you know, it's not likeit's taking off just, it's doing more work
(07:35):
than what you were able to do earlier.
Matt Heinz (07:38):
Yeah, and I think, is there a phased work program you recommend people?
I think if you're thinking aboutdoing AI native demand gen, I mean
oftentimes if we're doing a test witha client or sort of recommending it's
not just launch everything right away,do it in a particular market, do it
a particular industry, pick a segmentof the sales team to start it with
kind of Is there a phased approach?
You recommend people think about that?
Alex Roy (07:59):
Absolutely.
Absolutely.
Yes.
Yep.
Yep.
So we recommend, you know,it starts with signals.
So, you know, we recommend a subset,a specific product page on your
website where you add a tag sothat the agent is listening for the
intent on that specific set of pages.
It's probably, you know,perhaps product centric.
And, you know, so you have, you know,you look to have the agent identify who
(08:24):
is on the website, which company is there,and then orchestrate plays based on that.
So.
Yes.
A phased approach is the alwaysthe recommended way to proceed.
Matt Heinz (08:35):
I've seen some reports already, of, you know, like Forrester
for instance is saying that theymight be seeing some budget cuts in
2026, which I think might be justsort of exhausting to people that have
been through what they feel like hasbeen two, three years of doing this.
I feel like we're getting to this pointwhere this is not just optional, right?
That adopting these programs is kindof mandatory if you want to survive.
(08:58):
And I think, you know, can you talk aboutnot just the program implications you
mentioned earlier just the culture changeis required internally to make this move.
What are you seeing from CMOs andCROs that are operationalizing
this quickly, but also managingthe human element behind it?
Alex Roy (09:17):
Yeah.
So, you know, budgets is a challengeas like, you're, like, you rightly
pointed out, and it, it's forcingteams to be more efficient.
It's about unifying theMarTech stack that you have.
It's about, you know, making sure that,you know, there is, you know, you are.
You are, you know, there's, there'sless inefficient systems in, you
know, within that MarTech stack.
(09:38):
So yeah, so we work with them in aphased approach, like I mentioned
earlier, and it starts with, youknow, a specific use case.
And usually that's about, you know,the inbound leads that you know that's
coming in onto your website and,you know, how can an agent help you?
There is where we start.
Matt Heinz (09:56):
So I think about this, I mean, we've been talking sort of
almost with the assumption that thisis a sort of a direct sales engagement,
but it strikes me that this can impactpartner and channel sales as well.
Have you seen those use cases?
Alex Roy (10:06):
Yeah.
So, one of the challenges which, whichcompanies have is that the partner has,
you know, the, the product knowledgethat the partner has is limited.
They have multiple productsthey're looking at also.
So, you know, an agent that isknowledgeable makes the partner more
knowledgeable indirectly as well.
So the use cases where, you know, wegive an agent to the partner that,
(10:28):
that's grounded to reality by, by theproduct collateral, which is available.
So the partner readily is ableto access that information
and, be more, knowledgeable whenpresenting that to customers.
Matt Heinz (10:44):
Can you help with a little expectation setting
for programs like this?
You know, whether you're takinga phased approach or implementing
a technology like this.
Like what, how much time does that take?
How many people does ittake to implement it?
How much time does it take to implement?
And then what should people'sexpectations be about how and
when it starts to deliver results?
Alex Roy (11:03):
Yeah, I mean, you know, in terms of rollouts, typically we see like two
weeks to four weeks, somewhere in betweenthat in terms of timelines and, part of
it also has to do with, you know, there'ssome back and forth with, with the
marketing team and the IT team as well.
But yeah, but generally we see abouttwo weeks to two to four weeks.
Matt Heinz (11:21):
And then what... I love asking the question about doing a
sort of a pre postmortem, right?
Like if we were, say, if someoneimplemented sort of these programs
today, if we're talking about threemonths from now and they have not
been as successful as people want.
If you do the postmortem, then whatare the things you hear most often?
Like, what are the things thatmost often keep a program like
(11:42):
this from being successful?
That people that are leaning in and sayinglike, I need to adopt this, should be
aware of and prepare for now, so thatthey increase their chances of success.
Alex Roy (11:50):
Sure.
Yeah.
So for example, let's say, you know, theKPI is where we wanted to generate more
intent leads and content leads, right?
So intent leads is visitorsthat you convert into leads.
Web visitors.
So you have to commit, you know, sendingthe right audience to those pages as well.
So let's say you, it's likesetting up a mousetrap, but then
you know, you're not driving, youknow, the right folks there, right?
(12:15):
So, yeah, so it's about, you know, makingsure that you also have a marketing
program to drive the right audienceto those pages, and then the agent is
able to, engage with them, identifythem, and then engage with them.
So that's, you know, that's number one.
The other is another metric you look atis, so we have an integrated asset hub.
(12:35):
You know, you have an asset hubwhere the agent is knowledgeable
about the assets, so it's able to,so another KPI we typically look
at is, you know, how many marketingqualified leads were you organically
able to generate, and, you know, howmany conversations were created.
So those broadly I would say, youknow, are the three key metrics, that
(12:58):
would come out of this as an outcome.
Matt Heinz (13:04):
I am curious to hear from your perspective, this is a little
take a different approach, just thespeed of innovation happening in an AI
forward company right now versus sort oftraditional growth and development cycles.
I mean, from the outside it seems likethings are moving incredibly fast, and I
can only imagine that growing a companyin this space is controlled chaos.
(13:26):
What's it like on the inside, sort ofriding this enormous tidal wave right now?
Alex Roy (13:32):
Yeah, it's a great question.
I mean, over the last 10 years, youknow, we've you know, gone through
multiple eras of evolution, I wouldsay started back in the days with, you
know, you have classification models,you know, it's neural network based,
and now you have the LLM based model.
So it's about evolving like you mentioned,and, being engineered to evolve.
(13:53):
Right?
So, which is very important.
So one of the examples is, we look atspecific use cases and which is the right
model for that, is that, should that beusing a fine tuned model that we have
versus, you know, for this specific task,you know, there's another model to use.
So it's about plugging in the right modelsfor the right use case, I would say.
(14:14):
And yeah.
Matt Heinz (14:15):
And I think, you know, I'm thinking about integration
of these programs as well.
Like the volume of tools that marketingoperations folks at RevTech, you know,
people are managing is significant.
I'm hoping that you are gonna help usbuild and you envision a day when we may
have separate tools, but AI actually helpsthem operate and integrate and communicate
with each other a little more seamlessly.
(14:36):
And I'm hoping that that actuallysolves what many people have as a
data management problem as well.
Which inhibits AI from oftentimesdoing what it needs to do.
How do you envision thefuture of the tools, the data,
the integrations happening?
Alex Roy (14:51):
Yeah, it's a great question.
You know, like you rightly mentionedfor AI, you know, you need to make sure
the data is accurate, that, you know,it works on the right data, right?
And in terms of tools, also there areprotocols like MCP, which vendors are
using to enable, the existing agentwith additional skills you could say.
(15:12):
So give it additional context.
So, it's about, you know, you wouldsee each of the, product in the
MarTech stack has this connectorback to this agent and, you know,
enables the agent to, to be more, moreproductive across different systems.
And, at the same time, IT needs tobe able to set certain ground rules,
access controls, et cetera, also.
(15:32):
So it's almost an additional, personwithin the organization that's,
utilizing these, permissionsand making good things happen.
Matt Heinz (15:43):
I think maybe more than any technology we've seen before, AI
has democratized software development.
Right?
I mean, the vibe coding is real.
You can talk to a machine andit will build something for you.
I think that is changing howmany people think about managing
their own technical expertise.
As business leaders, what advice wouldyou give someone sort of new, you
(16:07):
know, sort of recent college grad,who's trying to figure out what skills
they need to have, who in the past,unless they were a developer, didn't
worry about needing to build code.
What advice do you give to thatup and coming business leader now?
I was building to my theme there, andI think I lost Alex, did we lose Alex
(16:28):
right before my last question to him?
Oh no, we did lose Alex.
Well, anyway, thank you Alex, forjoining us today on Sales Pipeline Radio.
Really appreciate everyone joiningand listening to us as well.
Have a great week.
We'll see you next week on anotherepisode of Sales Pipeline Radio.
Until that'll be well, take care.
Popular Podcasts
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.