Shelia (00:06)
So this is prompt this, right? The podcast for those business leaders who are just like totally fed up with all the AI hype and they really want the real deal, you know? Clint and Greg, they just cut through all that noise. It's really impressive. They bring you like actual analysis and these playbooks on how to use AI to launch new ideas, scale your business and honestly just stop getting left behind.
It's really something. So now let's meet your host.
Greg (00:41)
everyone, welcome to the podcast. I'm Greg. My co-host, Clint and I started this podcast to explore how business leaders are using AI in the real world. We found that our friends and colleagues aren't just talking about AI, they're actually building with it. So we decided to bring them in one by one to share their stories. And that's prompt this.
Clint (01:02)
And I'm Clint. Let's see, a little bit about me. I founded a successful software company years ago where we delivered AI-powered CRM tools. But more recently, I wanted to get deeper into today's AI tech revolution and start asking my friends what they're doing with AI. So now I'm podcaster interviewing smart business leaders to unpack how they have started using AI in their companies.
Greg (01:27)
Again, I'm Greg, and after years of running high performing sales teams that led with AI, I too am now a podcast co-host. I focus on helping sales and marketing leaders accelerate the use of today's AI to deliver record breaking results. Hey Clint, I don't know if you noticed, but I changed the voice on the intro and again on the way out. I like this one. What'd you think?
Clint (01:52)
Yeah, yeah, I definitely noticed very different voice, not only different accent, the Australian accent, which I thought was really cool, the whole like intonation and timber and the pacing was very different. Did you configure it to sound like that or did it just come out that
Greg (02:10)
Well, this was just drop down menus, co-pilot, but put some new options in there and it was really easy and it was fun. But guess what?
Clint (02:17)
You used Microsoft Copilot this time, not 11 Labs, huh? Yeah.
Greg (02:21)
I change it up on you. And guess what? Next week, you're getting a new voice.
Clint (02:26)
That's really cool that that's built right into Copilot. I'm a big chat GPT user, so I'm definitely starting to get some Copilot envy here. This week's episode is a bit different than what we had in the past. This time we had a sales leader come in and talk about how he was using AI on the sales floor.
Greg (02:46)
Now for most of the people we've talked to already, this guest is far ahead of ⁓ most sales organizations in using this within the operation of sales. And I found it fascinating.
Clint (03:01)
Yeah, listening to how all the different AI tools from chat GPT to a bunch of other ones built right into the day to day processes. It's funny how he described how he originally thought they were behind the curve. And in reality, I think they're set in the curve on ⁓ the sales floor.
Greg (03:18)
Let's jump into the episode.
Clint (03:28)
All right, we've got Mark Bautista with us today. He's our guest and he's gonna share the AI playbook you've all been wanting to know about. He's not just a sales leader, he's the kind of operator who builds the systems that keep teams delivering year after year. Now, what I like about Mark is he plays both sides of the board, strategic enough to see that long game, but practical enough to execute in the real world right now. And he does it, you know, without.
chewing through his people. Instead, he builds a culture where talent sticks and performance climbs and the team actually wants to be part of the mission. This is the kind of sales leader that we all want to work for. If you're serious about scaling with AI and still having a team that's engaged, this is the conversation that you're going to appreciate.
Greg (04:19)
Yeah, Mark definitely brings a unique perspective and that he's been deploying AI on the sales floor for over five years now. He's been through the gauntlet and knows what works and where the traps are hidden. So be sure to stay with us all the way to the end ⁓ so we can get through this week's AI challenge. So Mark, welcome to the podcast.
Mark (04:39)
Thank you guys. I know in the beginning you said you have smart leaders on. I don't know if I'm quite there in that category, but I like to tell Greg. I the conversation will prove it out. see. What do I always say, Greg? I'm just a guy. Yeah.
Clint (04:48)
D-guy, get stuffed out.
Greg (04:57)
Sure.
Clint (04:59)
So I gotta ask Mark, ⁓ you worked for Greg at one point, didn't you?
Mark (05:03)
a long point multiple times I followed him to a a to promised land is what I
Clint (05:06)
multiple times
I
working for the infamous Greg Rosen.
Mark (05:13)
⁓ man, you will know when he's stressed. He does not wear stress well. But I loved working for Greg and I'd follow daddy company and go to he's probably the best like leader I've worked for just because he gets it. ⁓ You you see a lot of people get into leadership and they kind of forget about like, what's it like to be a rep? And again, rep, Greg was a rep.
Clint (05:22)
There's a candidate inside, okay.
Mark (05:44)
So he knows kind of some of the mentalities and how you have to just smooth things over and run things on the floor. But yeah, when we would get into some of these high, very high pressure moments, man, I got some funny stories on how Greg was in his office and Greg was in a fish bowl too. He had a big glass office. Sometimes you'd walk by and I could just tell him like, yep, not today. I'm going to keep going.
Greg (06:07)
You
Clint (06:08)
There you go.
Mark (06:09)
I'll give him five.
Greg (06:11)
I ever do that again, I'm getting curtains for the glass. You know, I didn't think about that.
Mark (06:15)
They make now glassy press a button. It blacks out. You don't even need curtains, man. That could be you. Jeez. Yeah. But thanks for having me on. I mean, this is an exciting conversation and it's kind of what you guys alluded to, whether I knew it or not. We were really early in the AI game before this boom that's happened probably in the last two years in corporate and especially in sales. So yeah, I've seen a lot. We've done a lot. We failed a lot. It will be a good conversation to kind of have.
As we, ⁓ so, probably, so my old company with Greg has my leader at that time. That's probably, I mean, you're going back maybe even six years. It's probably more than five years. Cause there was before it was really known as like AI tools. Cause that's, that's kind of like what the bucket everyone says now is like, what are you guys using for AI? What are AI tools? We, we were implementing different tools that would help us understand things.
Clint (06:47)
Have you been using AI?
Mark (07:11)
that we usually would have an analyst do. just like number crunching, forecast crunching, things of that nature, what customers are called, different stuff like that was being implemented, but we would never call it AI. ⁓ When you hear AI now, typically it's tied to chat GPT, but it was a much different time when we first started to get into
Clint (07:32)
software package we're using for that number crunching.
Mark (07:35)
So
for ⁓ Greg, what did we use for the forecasting? used a VSO. It was originally a VSO when we were using it. And so what that was doing is it was tied into our Salesforce instance. And the cool part was, from I guess like the old school way to do some forecasting is, you're talking to your reps in the one-on-ones, going through their pipeline, analyzing their deals, making them move things in the right stage. ⁓ What we did with the VSO is it actually...
It actually calculates everything based off historicals, because you dump everything ahead of time. And it's kind of like most things in AI. You have to give it some precedence on understanding what it's looking at. So it outputs you an accurate, I guess you could say, view on whatever you're trying to analyze. And so what Aviso did for us was it helped us do forecasting predictions. And what we learned was, I mean, we learned two things. Greg and I were
pretty good at forecasting is what we learned because we were very, we were very on target with what some of the, I guess the estimates that a visa was going to pump out from a quarterly basis.
Clint (08:38)
Wasn't telling you something you didn't already know then, huh?
Mark (08:41)
⁓ Yes and no, but what it did open up was where are the gaps? Like where can we find more, right? Stall deals, deals that are just ⁓ stagnant to the point where we need some interjection. Do we need to do something different? ⁓ Which reps are gaming the system a little bit? Because what we learned is, know, when you're running a big sales org, because under Greg, we had a really big team and, you know, it's almost impossible to see what's going on underneath someone's full pipeline.
And even if we had managers, it's just our manager ratio is like 10 to one. I mean, that's kind of where we like to stay, but there are times where we're leaked up to 12 to one and you can imagine it's almost impossible to see the full picture. And, you know, we had a top rep that was very good at, I hate to say he's gaming the system, but he knew where to place deals. So it's kind of out of sight, out of mind, a tool like a V. So it's like, what about all these?
Greg (09:33)
I
remember when we first brought it in, everybody had different feelings about it. know what, you know, some people really fought it. I remember you had a different opinion on it.
Mark (09:45)
I mean, in the sales world, what do all salespeople hate? Change, right? So out the gate, we're all like, they're trying to control us. kind of, I think Greg played that biggest part. They're trying to spy our business type thing, you know?
Greg (09:59)
I had to start something to get you guys involved.
Mark (10:04)
So, so the good news is like, we adopted it pretty fast. I think the hardest part though, it comes down to most things AI, it's adoption. Like if the reps aren't adopting it, that's where you'll struggle. And I think that's, you know, I mean, as we kind of get deeper into the AI world conversation, I could kind of talk about what I've seen with just.
Clint (10:21)
I'll put on my geek hat here for a minute and say that tool, Avizo, and what you're talking about there, that's predictive analytics. Predictive analytics is a component of AI, and that's been around for a while. Like you said, you started using this six years ago. I would say that's pretty real then. Is that real tools, real software, real AI solving real problems?
Mark (10:45)
A hundred
percent. And it's to the point where even at my new company where I'm at, I'm at a little startup called Splashtop. I wouldn't say we're little, but we're like one of the unicorn companies. We're growing fast, we're chasing IPO, but we're using SalesLoft to do some of that same analytics. It's very similar to what Avisa was doing. But so when we started to leverage SalesLoft to do this type of predictive analytics, it was very familiar to me.
And so I kind of helped drive that into the sales reps and the other leaders that are using the tool too, because it was foreign to them, right?
Greg (11:18)
The new version like using a new version compared to, know, we were kind of the one dot auto of of automation back then. Is it better now? Are you finding like it's easier or better or are we still getting kind of the same?
Mark (11:32)
It's I feel like when we had a Viso, it was so far advanced, we just didn't know it. Because the way SalesLoft is running for us, it's almost eerily similar. Same types of trends, the way it presents graphs, ⁓ highlighting what deals to focus on. So I think if anything on the back end, it's probably just doing it way better. I think the predictive aspect of it is more accurate than what we were doing it.
Clint (12:00)
What you're describing is that there's a variety of different software packages out there that do that kind predictive forecasting. Is there any one reason to choose one or the other, or is it just kind of whatever you have?
Mark (12:12)
In my experience, ⁓ my company is very hard up on security and it's how fast can you get a tool approved internally?
Greg (12:20)
You
were hearing that from different people too. Yeah, everybody wants these incredible tools and ⁓ the security guy just won't let them in the door and it's frustrating for lot of the business and sales and marketing people we're talking to.
Mark (12:23)
Yeah!
Well,
the roadblock is always, well, what data is it accessing? And then depending on how strict your company is, like my company, we're very strict on what data gets accessed and touched because in our space, we want to be secure. Splashtop, sell remote access solutions for IT departments. And so you don't want some of this data getting out there. And you're selling to HIPAA compliant hospitals.
schools, it's not just success companies and tech companies. So yeah, that's the hardest part is like, how fast can I get this tool deployed? I mean, we had one tool, it took about seven months cycle just to get everything done from a security, a legal standpoint, where then another tool, is very, I guess you could say it's lightweight in what it touches. I had that thing done in under a month and we're deploying like in under a month.
Yeah, and then it comes down to what documentation do they have? know, you're going to ask them things on like, well, did you guys get this piece of information certified yet? Things like that. That's what will slow down.
Clint (13:40)
That's good advice for a lot of these new AI startups out there. ⁓
Greg (13:44)
question I have for you is, know, a lot of AI seems to do a lot of really cool things in the sales floor and shortcuts a lot. But are you finding that, you when you're looking through all the results and everything, are you finding that it's actually like, you know, helping people achieve better results, like at a multiple, like something that's better than just them getting a little bit better?
Mark (14:09)
Funny enough, the timing of this call is actually perfect. So two days ago, at my company, we did a company-wide hackathon. And what it was, it was focused on... So we heavily leverage, uh, Chad GPT and GPTs. And it's even better now because they just launched Chad GPT 5, like last week. And so what we were trying to do is, again, it comes down to adoption. We noticed that there's some gaps in different departments and individuals in all the different departments that are a little bit behind on AI.
and leveraging it to help their job be easier and more, I guess you'd say efficient, right? And so this hackathon was, we took four hours, everybody got into different breakout teams. We did it virtually because we're spread out, but there's a chunk of us in the office. And the goal was, the goal of it was each team, we had some homework ahead of it. So like all things AI and Chad GPT, you got to do some homework upfront so you get the right output, right?
The way AI works is it wants to be your friend and it's trying to guide you. If you don't give it any guidance, it'll just spit out what they think you want you to hear, right? So the homework was everyone needs to pick three things or three topics to build a GPT that will help their job ⁓ be done more efficiently or bridge a gap. And so you gotta imagine there's teams of five where each person had three ideas. So that's 15 ideas. We come together as a group and we pick the top three GPTs.
prompts that we're trying to build that will help other people in the company. So essentially, every group was trying to output three main prompts. And then the whole goal is to document this because we want to build a GPT library internally. so in the sessions, what we did was it was constant refinement. We picked the three that would make the most impact for our company for not just us, but different departments. And I could kind of give some examples of what was coming out of it.
things around the nature of like how do we better automate ⁓ just notes in Salesforce. So as a sales leader, the number one thing that everyone gripes about, it's always a meme, is like update your Salesforce, right? If you don't update your Salesforce.com, we're gonna have problems, right? But again, these are-
Greg (16:21)
time listening because when you say the word sales force, it has an effect. Both came from the competitors.
Clint (16:28)
You guys
Mark (16:34)
I did sell that as well, you know? ⁓ But the reality is that was still the pain, even when it was sugar CRM. It was painful, right? You get hounded on, on where's this deal? so one group's idea was, can we do a way to automate transcripts that were recorded? We use Microsoft Teams internally. Can we do that and we output it into our sales methodology? So internally, we use Spiced. ⁓
for those that don't know that's like situation pain like it's it's like acronyms for different
Clint (17:09)
Like a medic or med pic or something like that, right? Spiced.
Mark (17:12)
Spice
is like, yeah, it's just like an offshoot of it, right? That's what we, that's what we picked. did a training on it years ago and we had just stuck. But what happened was, is that team built prompts and how to extract ⁓ the actual spice content from a recorded discovery call. And then now to drive it into Salesforce in a perfect world, we want it to be automated, but the output now is just a copy and paste. The rep will copy and paste the spice.
they'll dump it in the sales force. you could, think the biggest success of that is what happens is a lot of my reps are on back to back to back calls. And so you could imagine if you're taking notes and you're, trying to get this, the right spice into the system after three calls back to back, you're kind of toast, right? It's going to be hard to go back to your notes.
Greg (18:03)
Yeah, back to call one and get some and be meaningful and thoughtful about what you're you're typing in is, you know, that that's it. That's the age old problem, right? We never liked what we read.
Mark (18:14)
or they're writing it with their hand. Like have you seen Greg's handwriting? Can you imagine Greg going back two hours reading his handwriting?
Clint (18:20)
handwriting.
Greg (18:23)
I was only able to write the word approved by the end.
Mark (18:27)
That's the
most important world in sales leadership.
Clint (18:30)
Let
me walk through this, Let me get my head wrapped around you. So you've got Microsoft Teams, and you're recording the customer conversations. then you ⁓ export out the transcript into a file, upload that into ChatGPT, and say, help me analyze this customer transcript using the Spice method. Am I going through the right steps there?
Mark (18:56)
Yeah, close. So we do all the pre-work. So essentially, ⁓ we have a GPT specific for Spiced, right? So what happens is a rep will go into the
Clint (19:06)
keep
saying you have a GPT could you just clarify exactly what that means you have a
Mark (19:10)
Yeah, so GPTs are like customized. So when you hear chat GPT, that's the platform, right? So GPTs are very focused things where if you feed it, like, I guess you could say pre-work or content or trend, I guess you could say, what do you call it? There's a, hold on, give me a second. materials. Training materials and there's different ⁓ formats. Like it's called a ROCF format or shoot.
Clint (19:29)
right?
Mark (19:38)
Maybe it's ROFC, hold on, chat GP. Let me Google it real quick. So the whole purpose of that is what it does is it builds a framework for this GPT to understand versus just pulling out from like the universe. And that's where you get like hallucination, right? And that's where if you give it a ⁓ upfront framework and you feed it, so for us, we're feeding it splash top specific pieces. It knows when you ask it a question,
what's going to happen is it's going to be tied specifically to what we want the framework to be.
Clint (20:15)
Let
me see if I'm catching this right. So you've got a customized version of ChatGPT with your sales methodology of situation, pain, impact, critical event, decision criteria. That's spiced. And then got all of your product information loaded up in there too. And so it knows all about...
What are the pain points that Splashtop can do, can solve, and it knows the methodology, and then it's gonna very specifically analyze that call transcript against your spiced methodology and your product knowledge. Do I?
Mark (20:51)
that right? is that exactly what's happening and so that's why we because we're trying to eliminate hallucination on just random articles or whatever it
Clint (20:59)
You mean like ChatGBG is making stuff up, right? Like, where did that come from? That doesn't have anything to do with my business, right? You're trying to avoid that. And that's where a custom GPT comes in.
Mark (21:10)
And it catches things like acronyms too. I think that's the key part, right? Because some of these IT guys, and it's not even just Splashtop specific acronyms, it's just industry specific IT stuff. And so it'll catch that and it knows because obviously we've done the homework upfront for that GPT. So for a rep, all they gotta do now is just copy, well, they have the file for the transcript, they dump it into the GPT and it's just say, please output my Spiced. And then it's in the manner.
because we set it up where it's copy and pasteable very easy back into Salesforce. And so the key part is now a rep, they don't really need to keep notes. That's, think, like when you kind of go back to the original thing is like, how do they gain efficiency on it? Now I've, forcing my reps to not take notes. You just have to pay fully attention to the discovery and not miss things.
Clint (21:58)
That's huge.
Greg (21:58)
So we've been trying to solve that for a long time. It excites me that you solved it.
Mark (22:04)
Well, yeah.
Greg (22:08)
You, you solved it in your group, right? You know, so I've got a few questions about that. you know, if I take a look at that, that was like one piece in the, in the sales universe that, that, that is a huge upgrade. So if I think across like, you know, what happens in a sales organization across maybe a week or a quarter, you know, as, know, from, you know, planning, you know, forecasting, you know, you know, all the things that happen.
on a sales floor, I can just imagine, you know, huge upgrades. Like I think, you you were telling me a story before. I'd like you to tell me a little bit about that, like the RFP response, right? That was, you know, before you talk about it, like when those used to come up, the only answer was, well, if you didn't create it, walk away. It's a waste of time. Now let's hear your new one.
Mark (23:02)
leave now.
Yes. So that was one of the, you know, when we were at our old, ⁓ our old company, when RFPs bubbled up, it was someone else helping build that RFP for that prospect. Right. And so to be handed an RFP, was almost like, it was almost like a, it was, it was a loss, right? You're just trying to be a third quote in this scenario.
Clint (23:24)
for proposal, When a prospect says, can you answer these questions and help me figure it out, right?
Mark (23:32)
And they could be as simple as 10 questions or it could be a packet, right? And so the other term is request for information, RFI. And so what happened was before, I mean, historically at most companies, you have to go find resources, a sales engineer, you might have an RFP team if you are a bigger entity where you supply to them, they usually have a 48 hour, if not more turnaround time to give you the output so you could then submit it
for the actual bid. And so what we've leveraged is, you know, with AI, if you've, we've built this AI, we called it the answer hub. is, yeah, yeah, this custom GPT answer hub, we've turned it essentially into a product expert slash sales engineer. So when you ask it questions, it's going to output accurate splash top related answers. And so you could,
Clint (24:11)
Is this of your custom GPTs again?
Mark (24:27)
What we do is we dump in like a simple RFI was 10 questions. It came in last week. My rep had back to back calls. The problem was the customer said is due tomorrow, right? in old days, if you said it's due tomorrow, like we're no bid. You essentially say we're not going to bid today. What we do is I could get that RFI. I dumped it into ⁓ our GPT. It outputs all the questions.
And then all you gotta do is you can just refine it. You obviously have to read through it, because you do wanna always look out for some hallucination on any answer. So that's one of the key things that you always have to use with AI is you gotta trust but verify. You can't just, yeah, it's gonna be. ⁓
Greg (25:12)
but verify.
Clint (25:13)
But you get it done quick, right? you have a ⁓ working response inside of seconds, and you can spend 10 minutes reviewing it. And instead of what might take a day or two or something like that, you've got it ready to go. That's huge.
Mark (25:29)
Yeah, so I got it done and into my rep's hand with a with a cover letter, pretty much giving our response, mimicking what they presented to us. And he had it over in five minutes. Right. So that's the power of like what this stuff does. And I just I don't I don't know if everyone knows that this is possible. Right.
Greg (25:48)
Here's the internal piece that seems to grind sales ⁓ teams to a halt. The QBR.
Mark (25:57)
⁓ Yeah. Man.
Clint (25:58)
Early Business Review.
Greg (26:00)
yeah.
Tell us about now what the experience is like having this.
Mark (26:04)
world
is just it it was almost like you dress
Clint (26:10)
What is the typical format of a QBR? What are you doing in it and what's the pain that you typically have in there?
Mark (26:16)
So when it comes to quarterly business reviews, like historically from my role company with Greg and even here at my new company, you know, you're doing analysis on how did we perform against our goals last quarter? And everyone has a section, marketing, sales, ⁓ product, you name it. Everyone has their own presentation they give. Typically it's to see staff or whoever your sales leader is. It depends on how focused the session is. But in the past, we'd get the notice a month in advance.
And you start prepping a month in advance because it's a matter of chasing data ⁓ and then crunching the numbers on the data and then trying to understand what you're even looking at. It was charts, graphs. ⁓ It was so heavy on, I guess you could say just, just work that it too, it took away from your day job because you're off the floor heads down into this, this actual presentation you have to build.
Clint (26:58)
right
Mark (27:15)
With AI now and the way we do it is we have our rev ops team give one source of truth for the data when it comes down to every stack possible, every key performance indicator or KPI, it will be in this one packet. And then from there, everyone starts to build off of that. And it will, I can't even explain how much time it has saved me. Like when it would take me a week to do a, realistically I did my QBR in a day.
Like I built it from like from zero to done and presented the next day. Like I really didn't even prep at a time. ⁓ you know, it's all through leveraging. And so we, would use some of our chat GPT GPTs. It, knows the data because we dumped it in there because you could add files to the GPTs for it to analyze. And it's asking just simple questions like, ⁓ what's the win rate of my reps outputs it.
Greg (28:13)
That's amazing. That used to be like a nine person job and to get the one stat could take up to two days depending who has to be involved. I mean that was
Clint (28:23)
That guy
at my last company, was the one crunching all the numbers all the time for people because I was the master of the reporting on our CRM. And that was a huge amount of time that should, you just you're saying just goes away. It's just right there.
Greg (28:36)
He was 20
GPT man.
Mark (28:38)
But the thing about it, right? Like someone's asking you a request for the data. You might not get back to them for six hours the next day. So now they're freaked out. Like, I don't have this content. I don't have this data. I got to present in this QBR. Now I'd have it like instantly, right? And then you refine it. So the key part of like using an AI is constantly refining the output that you get. ⁓ You know, I mean, it's simple as, you know, what's the win rates? Okay, now it's
Greg (28:46)
Everybody's gonna dig.
Mark (29:07)
what's our big deal win rate like by rep ⁓ by territory and I'll output it and I'll chop it up and then it comes down to once you once you get the numbers you want to present it's as simple as like please output this in a slide form.
Greg (29:23)
That's That's so cool.
We used to listen to calls and you could just tell reps weren't prepared to go on these calls or just winging it, you know, you know, it's, you know, suddenly trying to, trying to connect, ⁓ talk about strange things. Do you find when you listen to a call, ⁓ is there like pre customer intelligence in a different level now? Like,
Mark (29:50)
Detectable? Again, we have a customized discovery GPT where you gather a few things. Obviously, you put in who the customer is, you pull the contacts linked in. ⁓ We did the work to extract what we want ⁓ for the sales rep. It'll say things like, because some stuff out there is public, especially in MySpace, where we will know
we'll know what they're using now and what tools for remote access they're coming from.
Clint (30:23)
into
that public data about companies and so you got a handle on who they are before you even talk to them.
Mark (30:29)
Yeah. it's, and it's not even just the company, it's the individual too. Right. So we're arming the rep. So when the conversation is had in the discovery phase, it's, I've seen you've been there at 10 years, but previous year at this company, I was there. Funny enough. Right. Like the rep just has to dump these few pieces into the GPT and it outputs it for them. And it, ⁓ we do it in a format where then they can build the slide deck, right? Cause the discovery call typically you want like a simple slide deck.
and it'll allow them just to copy and paste what the output is. And so one, it looks very professional. Two, it looks like we spent a lot of time researching the company and the individual. And then obviously with the other tools we have in place for the reps not taking notes, they could actually be engaged in a discovery and conversation of it because that's where it's valuable. So many reps are worried about typing or writing that you're missing things is what we noticed.
before we had these types of tools implemented. ⁓ Because it's simple questions. Is this person a decision maker? Like, man, I don't know. I got to go back to the call. Those little things, because they're not active listening, right?
Clint (31:37)
in a lot of software selling situations and a lot of software buying situations and that question of is this person is a decision maker. Sometimes the person thinks they're a decision maker, but they're really not.
Greg (31:50)
We're making some decision, but not the decision.
Mark (31:53)
making a decision.
Clint (31:55)
question for you on all these pieces. within this, you know, up to now, we've kind of been talking about how you use chat GPT on the sales floor, right? And all the cool different ways for those, ⁓ you know, those RFP responses and preparing your QBRs and doing your data analysis and your customer analysis, there's a lot of great stuff in there. But the thing you've said kind of over and over is that it's all about your custom GPT that you set up. Can a company
Do what you're doing without creating a custom GPT.
Mark (32:27)
They can, but your output's going to vary. And is it going to be valuable output? So
Clint (32:33)
going to vary across rep to rep.
Mark (32:35)
Just just the output you don't know what you're gonna get because you have to remember the whole idea around ⁓ AI like chat GPT ish AI like any whatever Whatever LLM you're gonna use it's gonna err on the side of making you the user happy like it's not gonna It's not gonna push hard on what you're asking for if it's the right thing to ask for like if you tell any AI like this is what I'm trying to output it's not gonna question it
Clint (33:01)
give you an output. And that's where the hallucinations come from.
Mark (33:04)
They
don't don't they don't think right it just outputs and I think that's the main thing where you have to do some work
Clint (33:12)
Good insights, good insights. So a lot of what I'm hearing in there is AI is very helpful for answering product knowledge and answering a lot of the kind of the standard questions, as long as you train it well. But it's not ready for you to just turn over like a whole piece of the business to the AI and have it just run all of it. You got to have a human in the loop every step of the way is what I'm
Mark (33:40)
You it, you even see it on LinkedIn. People are saying AI is going to take these jobs, take that job. I think for sales, AI will never take a salesperson's job, not like a hardcore mid-market enterprise salesperson, even SMB to a point, even if it's a little transactional. I I tell my team all the time, AI will not take your job. The sales rep that figures out how to use AI to do their job, they will take your job and you will be out of the job.
That's what I tell them every day. So if you're behind on any of the AI trainings or exercises, you're going to get smoked in the next few quarters because you could just see reps are becoming more efficient. They're closing more deals. The deals are bigger. can, their pipelines are, they're able to touch more deals in cycle. ⁓ I think that's the hard part is people need to understand it's, it's never going to take away a salesperson's job. It'll make you better.
Greg (34:31)
Yeah, one question I have, you know, since it's since you've been surrounded by AI, do you feel like your skill set has come up because AI has been there around you? Hmm.
Mark (34:49)
Made me lazier.
Greg (34:53)
so a better manager. Very good.
Mark (34:55)
Yeah
Clint (34:56)
Yeah, I was gonna say, I'm a developer, I'm a software developer and lazy is my goal.
Mark (35:01)
Yeah, I feel like it's added a lot. It saved me a lot of time on tasks that I would have had to done, crunch through spreadsheets, ⁓ whatever it may be. And I feel like it's helped me out to help manage my people more. And I think that's the cool part, because as a sales leader, the one thing you have a very, very, very small window is with your people, right? You're too busy in meetings crunching data, whatever it may be.
If you have GPTs or AI to do some of this stuff and actually present it for you and handle it, I could spend more time on deals. Because I think that's what I've learned is I could help my reps on deals more, which is that's the one of the most important parts. Right. That's the goal. And I think that's what it's done for me. And I think that's the greatest part. You know, I'm not locked in all week prepping for a QBR. ⁓ I'll find myself because I have some things that are always running that, all right, I don't have to do it.
Clint (35:59)
Well, I got to tell you, man, this sounds like the best time ever to be in sales. These tools are making your life so much easier. And I know you joke around about ⁓ being lazy and that sort of thing. This is a tough job. It's a tough job. You're always moving. You're always hustling. You're always... And to have AI handle all this busy background work, that must be a nice place to be.
Mark (36:04)
Gosh.
but see ya.
Well, I mean, even as a rep, so ⁓ we have a I hired one of my old managers over at this company. He worked for Greg also ⁓ Anthony. We joke all the time with all the AI that we've deployed and reps running deals. We're like, man, if we have this 10 years ago, I'd be retired. I don't know.
Greg (36:43)
Just one generation, one generation changes everything. Well, if I could say one thing, I know Mark jokes around, but ⁓ lazy is never one thing. He's been, he's like having Mark on your team is like having four people. So ⁓ that's pretty awesome.
Mark (36:59)
I get
one pay though, that was always my grave.
Greg (37:03)
You gotta ask. No, I'm just kidding.
Clint (37:13)
So hey guys, as we get ready to wrap up here, we have a segment that we do in each of our podcasts called the AI challenge.
Greg (37:20)
The AI challenge is a takeaway assignment for our audience to begin getting comfortable playing around with different AI tools. So Clint, tell us about this week's episode, AI challenge.
Clint (37:33)
Well today we learned about using custom GPTs within chat GPT and we heard from Mark and his how he and his sales team use custom GPTs that his company created for their own internal use. But I don't know if you know this there are hundreds of free custom GPTs up on chat GPT that you can start using right away. For instance you need help writing cold emails or how about an objection handling coach or a proposal writer like what
Mark described earlier. Well there's a free custom GPT for all that and more. So here it is. I challenge everyone listening to go to chat GPT use one of these custom GPTs and do each of those different tasks I outlined above. It shouldn't take more than 15 minutes.
Greg (38:20)
Now we have a blog article on this at promptthis.ai that describes step-by-step instructions to learn how to use these tools. So you can look in the show notes below for the links to the challenge and the instructions. Once you finish, share your experience in the blog comments. We'll share the best insights on the next show.
No, that was a great session, Mark. We really appreciate you coming on here today.
Clint (38:46)
Outstanding.
was a great session. Appreciate it, Cool.
Shelia (38:51)
Well, thank you so much for joining Clinton Greg today. It really means a lot, you know, you can find all the episodes of prompt this and some wonderful in depth articles at www.promptthis.ai. It's all there just waiting for you. And ⁓ don't forget to click that follow button below. We absolutely look forward to having you back. It's always such a pleasure truly.
Clint (39:15)
you
