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Index/RevOps/AI for Revenue Leaders: The AI Hat Podcast
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Stop Losing $30K a Month Per Rep: The AI Sales Enablement Playbook with Vernon Ross

AI for Revenue Leaders: The AI Hat Podcast · 2026-06-14 · 38 min

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Key moments - from our scoring

Substance score

47 / 100

Five dimensions, 20 points each

Insight Density10 / 20
Originality8 / 20
Guest Caliber11 / 20
Specificity & Evidence10 / 20
Conversational Craft8 / 20

Vernon Ross, a senior account executive who closed enterprise deals at Supporting Cast and now runs Vernon Ross Consulting, walks through his framework for AI-driven sales enablement. Rather than deploying AI tools broadly, he starts by identifying the single most painful, time-consuming task your top reps complain about - usually research, email personalization, or training new hires - and builds workflows that remove friction rather than add it. The episode covers his concrete example of automating targeted outreach sequences using AI to build prospect lists and personalize emails within HubSpot, eliminating hours of manual list-building. He also discusses how he used WonderCraft AI and NotebookLM to create AI-hosted podcasts as training content for Fortune 500 companies and medical device firms, allowing new hires to self-onboard on basics via interactive audio content rather than consuming 20-30 hours of top performer time. The math is stark: if a $2M-quota rep spends 30 hours per month on administrative tasks, that represents $300K in lost revenue. Ross shows how to measure ROI by connecting content consumption to sales outcomes using landing pages and CRM data, and emphasizes that successful AI adoption requires reducing steps, not adding them - the difference between pilots that die and those that drive measurable adoption.

Key takeaways

  • →Top sales reps spending 20-30 hours monthly on onboarding and admin tasks costs your org approximately $30,000 per rep in lost monthly revenue, or $300K annually per $2M-quota rep.
  • →Successful AI pilots remove friction and reduce process steps; failed ones add extra work - AI should automate the research, list-building, and personalization that reps currently do manually, not create new approval workflows.
  • →Use AI to identify economic buyers and research targets within MEDPIC deals by analyzing past wins and finding similar prospect patterns, then let humans handle relationship-building and champion development.
  • →NotebookLM and WonderCraft can transform static training materials (PDFs, case studies, white papers) into interactive AI-hosted podcasts and flashcard modules that let new hires self-onboard on fundamentals in 2-3 days instead of consuming 20-30 hours of top performer time.
  • →Connect podcast or AI training consumption to sales outcomes by routing trial signups or CRM interactions through custom landing pages, allowing you to measure listener engagement directly against pipeline and quota impact.

Guests

Vernon Ross

Topics in this episode

HubSpotAI voice cloningNotebookLMprivate podcastsWonderCraft AISupporting CastMEDPIC methodologyHypecastSales enablement automationProspect list building and personalization

Questions this episode answers

How much revenue is a sales organization losing when top reps spend time onboarding new hires?

If a top rep earning $2M annually spends 20-30 hours per month training new hires, that represents approximately $30,000 in lost revenue per month, or $300K per year, due to diverted selling time.

What's the difference between AI enablement pilots that fail and ones that drive adoption?

Successful pilots remove friction and reduce process steps - like using AI to automatically build prospect lists and personalize emails before the rep reviews and sends - while failed pilots add extra work and approval steps that reps resist.

How can you use AI to identify economic buyers in complex sales deals?

Use AI to analyze past winning deals and find patterns in similar prospect profiles and company structures, then research those prospects; this helps you target the right stakeholders faster than manual MEDPIC qualification alone.

What is NotebookLM and how does it help with sales training and onboarding?

NotebookLM is an AI tool that takes your existing PDFs, case studies, and training materials and generates interactive deep-dive podcasts, flashcards, and slide decks, allowing new hires to self-onboard on fundamentals without consuming your top rep's time.

How do you measure the ROI of AI-powered podcast training or enablement content?

Create custom landing pages linked from training content that capture trial signups or CRM updates, then track consumption (listenership, geographic data, time spent) against pipeline activity and trial conversions to prove P&L impact.

What our scoring noted

Our reviewer’s read on each dimension, with quotes from the episode.

Insight Density

10 / 20

There are genuine tactical ideas - voice-cloning your own voice to replace NotebookLM hosts, the "7 minutes Saturday" talk-track podcast, correlating podcast map data to trial signups - but they're spread thin across 38 minutes heavily padded with the host's own monologues, a jingle intro, a self-promotional mid-roll ad, a network outro, and mutual agreement loops. Insight-per-minute is mediocre.

If you have a rep that's doing about 2 million annually and they're spending 30 hours a month. So if they're spending 10 hours a week or a little more, a little less, that's about 300k in lost revenue.
they would go over what their top reps were talking about...the talk tracks that they were using, uh, the routes that they were taking, the things that they were doing to sell in the field. They would then take that and put that into a podcast.

Originality

8 / 20

The pre-NotebookLM WonderCraft workflow and the idea of voice-cloning yourself to replace generic AI podcast hosts for internal training are genuinely interesting early-mover observations, but the bulk of the advice - find the pain point, remove friction, use AI to research prospects - is standard sales-enablement orthodoxy repackaged.

The smartest thing to do would be clone your voice. Get a really good clone of your voice...replace the deep dive podcast from NotebookLM with your own voice and push that out internally.
this was pre NotebookLM just creating deep dives into case studies and informational things. I put together a thing for town halls for folks to do town halls, stuff like that.

Guest Caliber

11 / 20

Vernon is a genuine practitioner - founding AE who closed enterprise deals using MEDPIC, built real AI workflows at Supporting Cast and with Bayer, and has named Fortune 500 clients - but he is an individual contributor and consultant rather than a senior revenue leader, and the episode occasionally drifts into self-promotion mode.

I was the founding um, you know, sales account exec working with marketing was pretty much non existent.
there's a company out of Germany called Hypecast that I also work with is to look at past deals to predict the likelihood of success

Specificity & Evidence

10 / 20

The episode names concrete tools (WonderCraft, NotebookLM, HubSpot, ZoomInfo, Apollo, Whisper Flow, Supporting Cast) and real companies (Bayer, P&G, AT&T, GE), and offers rough-but-stated numbers ($30K/month, $300K/year for a $2M rep); however, the flagship medical device case study is anonymised, calculations are asserted rather than evidenced, and the 335% engagement figure from the intro is never substantiated in the conversation itself.

there was a medical device company. They have like all of these case studies and white papers from these doctors and they're using that for selling to other doctors and other hospital systems.
you can use something, I think there's a tool called Whisper Flow that does some of that, uh, where reps can talk through what they need to put into the CRM.

Conversational Craft

8 / 20

The host demonstrates some preparation - correctly defining MEDPIC for the audience, asking about ROI measurement - but repeatedly interrupts to deliver his own mini-monologues, validates almost every answer rather than probing, and asks leading questions that let Vernon off the hook rather than stress-testing his claims or numbers.

Another way to put it, at least you can tell me if I'm wrong, is to think first about the behavior that you're trying to change through the podcast
No, but that's great. That's, that's exactly right. We need to look at the processes first

Conversation analysis

Computed from the transcript - who did the talking, and the words that came up most.

Share of words spoken

  • Speaker A58%
  • Speaker B42%

Most-used words

podcast46sales28folks23reps18revenue16vernon16hours14data14show13trying13help13notebooklm13spending12listening12marketing12podcasts12

Episode notes

If your top reps are stuck training new hires instead of closing deals, this AI sales enablement playbook will help. Enterprise seller Vernon Ross joins Mike Allton to show how to scale your best performers' knowledge without stealing their selling time, and why that "teaching jail" is quietly costing you around $30K a month per rep. Vernon has carried quota, closed enterprise deals, and built the AI training tools that make other sellers faster. Inside, he shares the one diagnostic question that finds your highest-ROI automation, why AI pilots die the moment they add friction instead of removing it, and how he uses NotebookLM, private podcasts, and voice cloning to cut top-rep onboarding from 30 hours down to 10. He and Mike also get tactical on where AI belongs inside a MEDDPICC deal, how to tie content consumption to real revenue, and the one automation any team can build this quarter without a six-figure budget. Vernon Ross drove 75 to 85% increases in new client acquisition at a 32% conversion rate, closed deals with Procter & Gamble, GE, and AT&T, and has generated over $500,000 in enterprise SaaS sales.

Full transcript

38 min

Transcribed and scored by The B2B Podcast Index.

Speaker A: What is it that your top reps are doing or like what are the top things that they're doing that they absolutely hate on a week that they spend like 10 plus hours a week on doing? What's that one thing that they all complain about? That's usually the first question that I ask. I'm like, okay, that's where we can apply looking at is AI the solution for what it is that you're doing? I try to find like the most painful thing that they're dealing with that's taking their top reps because that's who's going to be the measurement of where they get the most impact is if we can save those top reps that 10 plus hours, you're going to make a huge impact. Like one of the numbers I did. If you have a rep that's doing about 2 million annually and they're spending 30 hours a month. So if they're spending 10 hours a week or a little more, a little less, that's about 300k in lost revenue. If you can free up that time, you're going to see an automatic increase in the bottom line. Mike's got the hat. The AI kind unlocking uh, power in business. You'll find. Cut through the hype, explore the tech. Every week, new ideas to CH. All10 leads us on a digital quest. AI secrets he'll always invest. Tune in tight, don't miss a beat. Knowledge groove. Keep you on your feet. Listen up to the AI flow business growth. Here we go. Cutting edge insights. That's the plan with the AI Hat you'll understand.

Speaker B: Greetings program. Welcome to the AI uh Hat podcast. The resource for revenue teams who are ready to stop being the bottleneck in their own business. Every week we architect some simple AI operational systems that eliminate admin drag and can reclaim your time that are freeing you up and your team to focus on the high value work that truly scales your revenue. I'm your host, Mike Alton. Subscribe and let's build your digital team together. But here's the reality most revenue leaders won't admit. Your best sales reps are spending more time teaching new hires than closing deals. Every onboarding session is an hour stolen from your pipeline. Every repeated product demo to a struggling rep is revenue left on the table. And the brutal truth. Traditional sales enablement doesn't scale. You can't clone your top performers. So you're stuck in this endless cycle of manual knowledge transfer while your Competitors are building AI powered learning engines that run 24 7. This isn't a theoretical problem. It's a quota killer. And today's guest didn't just identify this bottleneck. He built the solution that Fortune 500 companies are using right now to fix it. Vernon Ross is a senior account executive who drove 75 to 85% increases in new client acquisition with a 32% lead conversion rate at supporting cast closing enterprise deals with Procter Gamble, GE&AT&T, including the company's largest deal to date. But here's what makes Vernon different. While managing a multimillion dollar pipeline using Medpic methodology, he was simultaneously building AI driven podcasting solutions that increased client engagement by 3,35%. He didn't wait for the perfect AI tool to arrive. He architected the workflow himself, integrating platforms like WonderCraft AI to create AI hosted training content that scales expert knowledge without burning out quota carriers. As president of Vernon Ross consulting and enterprise podcaster, he's generated over $500,000 in enterprise SaaS sales while advertising and advising Fortune,000 companies on, uh, podcast driven learning initiatives and AI enhanced employee engagement. Vernon is that rare practitioner who's carried quota closed enterprise deals and built the AI infrastructure that makes other sales teams faster. Hey, Vernon, welcome to the show.

Speaker A: Hey, man, what an introduction. I'm like, who is that guy? That's awesome.

Speaker B: Like I tell folks all the time, you did all the hard work to accomplish everything I talked about. Claude wrote that script. I just delivered it. Kudos to you, man. Thanks for coming on the show.

Speaker A: Hey, thanks for having me, man. I'm excited to have this conversation.

Speaker B: That's right, that's right. And it's great because you and I have known each other now for almost 10 years, I think getting close to a decade, uh, and it's the first time we've had been able to have this kind of conversation. Uh, and I'm particularly excited to really showcase your past expertise for the folks listening. You've closed, like I said, enterprise deals worth millions while building simultaneously AI solutions for your clients. Kind of walk us through how you identified sales enablement as a workflow that maybe needed AI automation or maybe even needed it first.

Speaker A: Yeah, you know what's funny about that is, you know, typically with sales enablement, you know, uh, you go through your steps and you're trying to identify, you know, who the economic buyers are and your marketing qualified leads and sales qualified leads. And oftentimes those two things are kind of separate. Sales isn't talking to marketing, marketing isn't talking to sales, and nobody's really looking at the data to figure out exactly what you need to work on. It was just a gap that I noticed and because the company I was working at at the time was supporting cast, was small and I was the founding um, you know, sales account exec working with marketing was pretty much non existent. They had two sides to their business, a public side where they deal with subscription based stuff and I was working with you know, all of the private stuff. And so just through some simple AI stuff, just ChatGPT was able to kind of take the sales enablement playbook that we were current, that we were following and modify that some so that marketing and sales me or actually talking to each other to figure out what we should be talking about, how we should change our decks, uh, how we should, we should be looking at potential clients, current clients and doing some land and expand opportunities and really maximizing those leads that were coming in.

Speaker B: I can completely relate. I've been in Agorapulse for almost as long as I've known you and it wasn't until last year that we actually moved to combine sales and marketing into one revenue team. They were very much siloed. And I've always been a silo within marketing so I'm a silo within a silo guy. But it's, it's great to finally have that, that cohesive team and that communication that goes back and forth. You know, instead of just you know, a one off from a sales rep says hey, I talked to this guy, he needs this um, you know, or marketing asking sales, what do you need? What can we do for you? There's that more constant communication. But I also know a lot of revenue leaders, they're drowning in AI pilots in these tools. They're trying things that nobody uses. Which isn't necessarily a new story. Right. I mean so many organizations have installed CRMs and plugins and that sort of thing, but it's a little bit different I think in some ways. So what do you think the fundamental difference is between an AI experiment that dies and one that drives measurable adoption? Like some of the increases that you saw.

Speaker A: Yeah, the ones that die are the ones that cause friction when they add steps when, when they add more things that uh, the reps have to do when you're you know, creating all of these things that they have to do it, uh, that, that friction kills it. So if you can remove friction by doing the stuff with the, with AI, that's going to help. So you need to be shortening processes and shortening steps. So when things happen, maybe you get an automatic list of responses so, for instance, you know, you're developing an email sequence in HubSpot, and often what you'll do is you'll get that boilerplate sequence or you'll copy a sequence that was working, something like that. And then the rep has to go in and modify for each client they have to go out, they have to build, you know, a profile for each potential prospect that they're looking at. If they're doing some targeted stuff and not just spray and pray, hopefully they're doing targeted outreach. So when they're doing the targeted outreach, they're spending sometimes hours putting together this target list and then trying to modify the email sequence to go out and maybe find a fact here or there. With building the right workflow, you can literally give AI the list of people or the description of the companies of the list of people that you want to contact, get something back, use one of the contact tools like a zoom info or an Apollo, build a quality list, put that list into your tool, the workflow goes through, creates all of the stuff that you need, and then the human in the loop process reviews all of that stuff. And then you can send out those targeted, uh, outreach sequences and HubSpot and know that you actually have something that's unique for every person that you're trying to qualify or that you're trying to reach out to. Just leveraging AI like that. And it's one email thing. It'll, it'll take you some time to build it. But if you can say, hey, rep, all you have to do is put in these qualifications, put in these criteria, and we're going to give you a sequence and a list and then all you have to do, check it out, make sure that everything is right, send it out and follow up. That's a lot different than go, uh, research, go do this, go do that, go do this. And you're spending, you know, 20, 30 hours doing, not selling. So that's, that's kind of, hopefully that answers that question. I went a little bit far into detail with that one.

Speaker B: No, but that's great. That's, that's exactly right. We need to look at the processes first, not just buy a new tool and, uh, you know, some shelfware that nobody's going to use. We need to look at what the reps are doing today. Like you have a lot of reps who, maybe they're not updating the CRM after a call with a prospect because there's too many clicks, too many steps, and they've already had to go on to the next Call and the next column. The next call.

Speaker A: Yeah.

Speaker B: Well, let's look at, you know, putting in some kind of an AI automation where they can just drop the transcript into a folder or a chat window and allow AI to help them, perhaps within seconds, fill in the CRM, um, create the action items, create the next steps and so on. That's the kind of solutions we're, we're talking about in the show all the time, Vernon. So I appreciate you actually going into the weeds and showing off that example. Now when you integrated WonderCraft, ah, AI created some AI hosted content and that was for Fortune 500 companies. What was like the specific enablement bottleneck that you were solving that maybe traditional training platforms, LMS platforms couldn't fix?

Speaker A: You know, taking information that they already had. So there was some newsletter stuff, stuff like that, and creating basically an automated podcast. The first company we did it for was actually, there was a, um, I can't actually mention the name, but there was a medical device company. They have like all of these case studies and white papers from these doctors and they're using that for selling to other doctors and other hospital systems. But they didn't have a good way to get that information to them. And sending out the mailings and trying to print them and do all the things that they were doing and sending these huge PDFs wasn't working. But creating a summary with AI and then using Wundercraft to actually create those podcasts, they were able to then invite doctors in to just listen to a private podcast and get the information that they needed to basically pre sell them and educate them beforehand. And that improved their outreach workflow. Uh, with the Fortune 500 companies, more of it was just automating information that they already had that they wanted to create or giving them an idea of. This is how the podcast could sound if you're doing this information. So even if you don't use the AI created podcast, here is basically a preview of it. You can listen to it, kind of get your, your legs under you because you've never done a podcast before of how this can sound and how this can be, and then they can go and produce it on their own.

Speaker B: So when you're talking about a podcast, you're not talking about something that's just pushed to Spotify or Apple podcasts at the private link type of a situation where only those within the company or that they allow can listen to it.

Speaker A: Yeah, um, not to make it a Supporting Cast commercial, but the cool thing about Supporting Cast is they enable folks to have private Podcasts and have them through Spotify or Apple Podcast so they could listen to them on the go. But it still remained private, so it was used more as an internal training tool than an external promotional tool.

Speaker B: And I think the key there for folks listening to understand is you're using podcast audio content as a medium because as you said, folks can listen to it on their phone, they can subscribe to a feed, they can get a notification when there's new content, they can listen to it while they're multitasking, or they can sit in wrapped intention in front of their computer if that's what they want to do. But all of that's up to them. So that, that makes a lot of sense to me. So this was kind of like a Notebook LM solution, but pre Notebook lm if I'm not mistaken.

Speaker A: Yeah, actually it was weeks before NotebookLM launched. And then when NotebookLM came out, we're like, oh my, look at this. We can actually like just put this in here, get a deep dive and then use that as a script. Because what most people are doing, they're like, oh, and you'll hear all these NotebookLM podcasts everywhere now. And it's the same two host what WonderCraft end up ended up doing. They were like, oh, we can pull that into Notebook LM and then you can just change the speaker to whoever you want. So the smartest thing to do would be clone your voice. Get a really good clone of your voice. Use their. I think they have some system where you can put intonation in and the right way of speaking and all that other stuff. They didn't have it at the time, they have it now. But you could pull all that in, clone your voice, and then replace the deep dive podcast from NotebookLM with your own voice and push that out internally. And so it's not like, who in the heck are these hosts that are talking about our stuff? Oh, this is our normal host. Give it an update. It wasn't perfect, but it was definitely a way to do it once Notebook LLM came out. But yeah, this was pre notebooklm just creating deep dives into case studies and informational things. I put together a thing for town halls for folks to do town halls, stuff like that. Pull all of that in, automate it, and free up the executives to not have to sit down for 30 to 45 minute podcast that they didn't want to do.

Speaker B: Yeah, this is such to me a beautiful use of artificial intelligence. And for folks listening, maybe you haven't experienced an AI created podcast like NotebookLM M. In fact, I did a whole episode just about NotebookLM sounds great. You're creating a repository for AI by giving it the PDFs, the white papers, the case studies and that sort of thing. This is creating what's called a rag retrieval augmented generation system where the AI knows how to speak the language and has general knowledge, but any facts and information are restricted to that content. So it's not hallucinating, it's not making up anything, but it's also at the same time summarizing and if you give it the right context, it's focused on your target audience. If it's physicians, it's great. It's talking to them from their perspective. What do they need to know about X, Y and Z, these products? They might not need to know really, really highly technical specifications, but they may need to know applications and the results of past studies and you know, trials and that sort of thing. So brilliant use of AI. Uh, but let's bring it back to something I mentioned at the outset because I want to help folks get to this point. We talked about you being using medpeg to navigate complex like multi stakeholder deals for folks. Maybe the marketers in the audience are listening. You know, that's metrics, economic buyer decision criteria, decision process, paper process, identify, pain, champion and competition. It's a whole framework for basically how a salesperson, an AE or even an SDR should approach a sales conversation. These are the things that they want to ask about right in the conversation. So what parts, Vernon, of that entire methodology do you think can be AI enhanced versus which parts do you think still absolutely require human judgment and relationship capital?

Speaker A: Yeah. You know what's interesting about Medpic, you can, you can use that methodology to identify a lot of how you approach a deal. So you know, some folks will be familiar with the Challenger sale or the Challenger customer really goes into that type of. It's not really Medpic, but it goes into the methodology of it a little bit. One of the biggest things that I use it for, particularly at supporting Cast and I'm also working, I used to work with them, but uh, there's a company out of Germany called Hypecast that I also work with is to look at past deals to predict the likelihood of success if you re engage those deals or looking at past deals and using AI to find other deals that are similar to it so that you know exactly who it is that you need to talk to. Because one of the problems with MEDPIC is identifying those economic buyers and it's not the Same in all companies. And finding those, those people specifically and then targeting those people can be a bit of a challenge. So you can use AI to help you get to who your potential folks are and exactly what it is that you want to communicate with them. Because all the time it's not exactly clear with each prospect of what do you want to communicate to that economic buyer or how do you best align with the issues and the pain points that they're actually having so that they can become your internal champion.

Speaker B: Got it, Got it. So we can use AI to help identify buyers. We could certainly use AI to, um, help research them. And that, and that usage, I think, of AI is going to help train new hires, new AES, new BDRs and so on, uh, because it's speeding that entire process. But I think still we have a bit of an issue with what I call teaching jail, where you've got some of our best performers. We want to duplicate their success. Right. So we're asking them to spend time, valuable sales time, onboarding new hires.

Speaker A: How do you.

Speaker B: Let me ask you this. How much revenue do you think the average sales org is losing because some of their top performers are stuck onboarding these guys instead of working pipeline?

Speaker A: Yeah. I mean, if you spend 20 to 30 hours doing that, I did some numbers and you're. It's about 30k. It's about 30k, uh, of revenue that you're losing in lost opportunities per month, not per year. You're missing about 30k of possible revenue per month by having your top agents, your top reps train and onboard new folks. When most of that stuff can be done with AI, it can be done with podcast, it can be done with podcasts using AI. Uh, for instance, you mentioned NotebookLM. There is a feature in NotebookLM where you can create flashcards that walk people through individual things that they need to learn. Or you could put all of that knowledge into a database that's in NotebookLM and then your new folks can do some of their onboarding with NotebookLM. They could listen to a deep dive. You could put together a slide deck in NotebookLM, all with the knowledge that you create as resources for those new folks to onboard. And so maybe they spend their first two days going through NotebookLM so that they have a basis to work from. And then instead of 20 to 30 hours of your top reps spending that time, maybe they're only spending five to 10 hours of actual time working with them. And then it's on things that are like, really valid that they need to talk about. Not the basics of, um, who do you need to talk to? What do you need to do? You know, all of the basic things that you do when you're onboarding someone. You can put all of that stuff into an AI workflow. You could do it with podcasts, which is how I was previously doing. It was just with podcasts. I've created a lot of onboarding podcasts that take folks through all the basic stuff that they need to do so that they don't have to spend those revolutions talking to and pulling in their top folks.

Speaker B: Love it. Love it. Folks. We're talking with Vernon Ross about how AI is impacting sales enablement. And I've got a bunch of more questions. In fact, we're going to dig into. How do we even know that this is working? But before I get into that, a quick word about shadow AI. Right now, your best people are drowning. Um, they're buried in data entry, meeting prep, and internal reporting. The admin drag that kills momentum. To keep their heads above water, they're turning to AI tools you haven't approved. They aren't trying to be reckless. They are trying to be efficient. They are trying to hit the goals you set for them. But this shadow AI creates massive blind spots in your data security. You can't afford to ignore it, but you also can't afford to ban it. You need to architect it. I've created the Executive Guide to Shadow AI to help you bridge this gap. It's a blueprint for turning a security risk into a competitive advantage through proper governance. Don't fight the shadow. Sanction it. Download the free guide today at theai hat.com/hyphenai that's the AI hat.com/hyphenai. So, Vernon, let's talk impact. You built AI enhanced analytics dashboards to track podcast performance and ROI. How did you connect content consumption metrics to actual sales outcomes so leadership could actually see some kind of P and L impact?

Speaker A: Yeah, that's, that's interesting. So how I was looking at this question, I'm like, otherwise, did I do that? So I'll give you, I'll give you two answers to that. The first was actually pre AI, and this is how I was doing it. Pre AI. There wasn't a really good way to measure it. I was working with Bayer and they were creating a podcast for a, uh, farming software that they were using. And the reason that they were doing the podcast was to educate consumers on this software, talk about the things around it, what they could do with, you know, seed utilization and all this. All this stuff around farming that I had no idea that existed, the way that we would measure it or the way that I told them to measure it so they could actually justify spending. All the money they were spending on the podcast was to put up a custom landing page and have that custom landing page be the driver for where all of their trial signups were coming from. And then wherever they were getting the most listeners from using map data for podcast consumption, they would then know, okay, we're getting more signups and trials from this area or from this state, because you could kind of drill down state to state, very manual process. But you could look at, hey, where is this coming from? And our trials went up after this episode in Iowa. So we know that folks are listening to the podcast because they're clicking on the link that's on this site, or, you know, depending on the app, they're clicking on the link that's in the app to go here, and they're signing up. And so you could drive, you know, or you could measure signups to listenership. And it was a way to sort of tie that into podcasting. You can. You can do the same thing now with AI, but even easier. You can just automate the process. So if it's internal, it's any of the things that folks are interacting with. So if they're listening to the podcast, you can look at podcast consumption data and then tie that into revenue actions by reps. So if a rep, for instance, at a pharmaceutical company, I did a thing where they did seven minutes Saturday podcast, I helped them create, and in seven minutes, they would go over what their top reps were talking about. And it's. What's working this week is. Is actually what the. The episodes were. And they would talk about the talk tracks that they were using, uh, the routes that they were taking, the things that they were doing to sell in the field. They would then take that and put that into a podcast. And now you can actually measure that stuff with AI about who's doing what, where the performance is coming from, how they're accessing the podcast, whether it's mobile, whether it's on their computer, whether it's on their laptop devices, and really actually tie it back to the revenue they're producing based on if they're doing the things that are working. So hopefully that. That answers that question.

Speaker B: Oh, 100%. Another way to put it, at least you can tell me if I'm wrong, is to think first about the behavior that you're trying to change through the podcast and then determine how would you measure a change in that behavior. And then you craft the podcast in order to impact that change. So for instance, if you wanted your sales reps to talk more about other products in your catalog that they don't typically talk about because they're kind of used to selling the things that they sell and they forget to upsell or cross sell and so on. So you create podcasts that are specifically deep dives designed to educate them on those particular products, and then you measure the increase in those product sales relative to consumption. Does that sound right?

Speaker A: Sounds exactly right. And you know, the problem is, is that with all of the, uh, all the podcast platforms out there, you have those stats, but you have to go in, someone has to go in and manually pull a report or look at, okay, where is this coming from? And then try to put it into some tool tableau or something like that and extrapolate that data. That's all automatic. Now. You can automate that with an AI workflow. So instead of spending 30, 45 minutes trying to compile that information, now it's automatic and it's run via, uh, a cron job every week with something like claw code or claw coworker. You can actually say, hey, every week I want you to go out, look at these podcast stats in this platform. We're going to give you access to it and show me what's happening with all of my podcasts. And oh, by the way, look at rep performance in this tool and see if those reps who are listening to the podcast, if you track them via AI or via IP address, which you could do, show me what the performance data is and send me a report weekly. You can do, you can automate that now with AI, whereas before, that's two and a half, three hours worth of work that you'd have to individually do. If you have it just like down pat to a workflow and you're not trying to figure it out every probably month when you're looking at it.

Speaker B: And I guess for those listening who maybe you don't have that automated, if you're not sure where to start, maybe you don't have budget for that kind of stuff. Open up Chrome, open up your podcast or whatever it is that you've got, that's got like reporting analytics on consumption. And then you can open up in a completely different tab your sales rep performance data, whether that's in Salesforce or something like that. And you can ask Gemini in Chrome to look at those two tabs and help you Analyze that data. It's not going to be automated. You'd have to ask it that every time. But if you can dust some insights out of the data with the use of AI, you can take that to your vps sales, right. And say, hey, this is what we've got going on right now. I could use a little extra budget to automate this. So Vernon, when you walk into a revenue leader's office and they say we need AI for sales, what would you say is like the diagnostic process that you run to help identify which workflow or workflows might deliver the fastest time to value the quickest return for that kind of a pilot project?

Speaker A: Yeah. The first thing that I ask is, you know, what is it that your top reps are doing or like what are the top things that they're doing that they absolutely hate on uh, a week that they spend like 10 plus hours a week on doing? What's, what's that one thing that they all complain about? That's usually the first question that I ask. I'm like, okay, that's what we were, we can apply looking at. Is AI the solution for what it is that you're doing? I try to find like the most painful thing that they're dealing with that's taking their top reps because that's who's going to be the measurement of where they get the most impact is. If we can save those top reps that 10 plus hours, you're going to make a huge impact. Like one of the numbers I did. If you have a rep that's doing about 2 million, 2 million annually and they're spending 30 hours a month. So if they're spending 10 hours a week or you know, a little more, a little less, that's, that's about 300k in lost revenue. If you can free up that time, you're going to see an automatic increase in the bottom line.

Speaker B: Oh, I couldn't agree more. Some of the stats that I've seen have uh, suggested it's as much as 70% of a sales rep's time that's being wasted on non revenue driving activity. So that's a big part of what we talk about here. That admin drag is basically the kind of, that I talk about constantly on this show and with the people that I'm working with. I'm going to sales kickoff meetings and uh, all over the country and helping teams understand how they can use AI for mundane things. These aren't sexy things. This is, help me write an email, help me draft a Proposal faster, those kinds of things, but they add up to so much. Now. One of the things that I know you've done, you've worked with all these big name brands. I talked about P&G, GE, AT&T, all these letters. Right. And a lot of these organizations I think are famous for compliance and risk management. Did the idea of shadow AI, this people are using AI, but they're not telling their manager, they're not being sanctioned or trained. Did that come up? And if so, how did you get buy in for that, working with those kinds of materials?

Speaker A: The, you know, the, the, the funny thing about compliance folks, and a lot of times it came from procurement risk mitigation. When you can talk to, you know, a, uh, senior exec and say one of the things that you tell them, I understand that we want to implement this and we want to use something generally like a podcast tool and there's some AI built into it that your, your risk mitigation is, is minimal. Uh, or we have risk mitigation in place and it's SOC2 compliant with an audit trail. They're like, oh, wait, wait, what? We've, we've not heard other AI on, uh, podcast related vendors. And it's like, well yeah, anything that I use, it's going to be, there's going to be some audit trails, I'm going to mitigate risk and there's going to be SOC 2 compliance and there's, there's very few, you know, like podcast hosting companies that do that. So I just, I make sure that I'm working with folks that have their SoC2 compliance, not ones that are actually working on the SoC2 compliance or one of the things that some companies will say because they're hosting the podcast and the Amazon S3 bucket is basically where you store the audio for the podcast. Because Amazon is SoC2 compliant. They say that they're SoC2 compliant and you know, it's more security by obscurity. Which I'm like, oh, uh, that's, that's not actually saying that they're SOC2 compliant, but I work with companies that have that SOC2 compliance in place and their, whatever ISO number it is, that they've gone through all of that and that they're very careful and they have audit trails so that big companies like A P and G or an AT&T can produce content with confidence, particularly for internal stuff, external stuff, goes through a number of compliance checks and everything else to make sure that, oh yeah, we can publish this, there's no data going out that shouldn't go out. So if you're hearing a, uh, podcast that's public, you don't have to worry about, okay, this, this is, this is what should be out there. But if it's a private podcast or an internal podcast where the intended audience is your employees, even if that data were to get out, you want to make sure that there's an audit trail so you can know what happened, how it happened, and is there a way that we could have prevented it? Or at least here's the audit trail of how this thing happened.

Speaker B: That is incredibly smart because to your point, we're usually talking to procurement teams or IT teams. They just want to ban this stuff because it seems unsafe. And if you can improve the safety and security, well then you've definitely addressed one of their major issues. Vernon, I just got one more question for you, uh, for the revenue leader who's listening. And they know that their sales enablement, their onboarding process is broken, but they don't know where to start. What do you think is like the first automation that they should build this quarter? Something that it doesn't require a six figure budget or a data science team. Where should they start?

Speaker A: You know, I, I think and I wrestled with, with kind of how to answer this, but one of the most valuable things that I put into place was voice to text CRM field completion. It's really easy to do. You can use something, I think there's a tool called Whisper Flow that does some of that, uh, where reps can talk through what they need to put into the CRM. It speeds up entering stuff. It doesn't cost a ton of money. You can find a number of apps that are text to speech. You can even do it with something as simple as like an otter AI and then just copy and paste. I don't recommend that necessarily, but there are a couple tools out there to just auto populate the fields in your CRM. That's just one quick thing that you can implement that'll save your reps so much time and maybe actually get them to complete the things they need to complete in the CRM on a, on a regular basis. Because that's, that's huge. You'll see it in almost every job description that, you know, you have to be good at, you know, completing and keeping up with CRM data. So yeah, that's, that's probably like the one thing that is a pain point for just about everybody.

Speaker B: I love that recommendation. We've talked about Whisper Flow a couple times on the show, but I'm Feeling like I need to do an entire episode. Uh, because it's very much an undeserved or underrepresented tool for folks who you're not really familiar with. It's an app. It's not a Chrome plugin. It's an app that lives on your computer or your phone or both. And because it's an app in any, any text field that you're in, whether it's a web browser or a different app, you can push a button or whatever you want to do, there's options in terms of activating Whisper Flow, and at that moment, it'll start listening to you wherever you're on it, wherever your cursor is in a text field. But it's not like the live Speak dictation that we see in OpenAI, where as soon as you speak, it's punching the characters in, it listens to you until you stop talking, and it thinks through what you said, which means if you correct yourself, it will fix it. If you share things that sound like a list, it'll put it into a list, nicely formatted. And of course, everything's spelled right and so on. So it's definitely a step up from a lot of the texting, uh, voice texting and dictation things that we've used up until now. So appreciate you calling that Albert, and you've been an absolute treasure trove of information. I know folks are really excited to share this with their ops teams and get some input on their salesman processes, but for those who want to learn more and maybe they want to reach out to you, where should they go?

Speaker A: Well, I mean, the best place to reach me is LinkedIn. It's easy just in slash. Vernon Ross. That's the best place to reach me quickly. Of course, you can find me, uh, Vernon Ross.com or Enterprise podcaster.com and I have a, uh, AI planner that I'm releasing and so you can also find that out on aiplanner.com I've given you enough URLs, but, uh, just reach out to me on LinkedIn. Best place to get me, quickest place to get me is out on LinkedIn.

Speaker B: Don't worry about that. As always, we will have all those links in the show notes below. So thank you, Vernon. We'll also include a link to Vernon's brand new podcast, which will have come out by the time this episode drops. So thanks, Vernon, so much for coming on the show. Thanks all of you for listening. That is, of course, all the time we've got for today. But if you haven't yet talked to your team about how they're really using AI, Shadow AI. It's time Learn what shadow AI is, why you should lean into it, and how to proceed for free at the aihat.com forward/Shadow-AI. Check it out and I'll see you in our next episode. Welcome to the Grid. That's a wrap on another episode of the AI Hat Podcast. I hope you gained some valuable insights and actionable strategies to boost your business with AI. If you enjoyed the show, please subscribe, leave a review and share it with your network. And don't Forget to visit theaihat.com for more resources and to connect with me. Until next time, keep innovating and remember, the future of business is human and it's powered by AI.

Speaker A: Uh, you may know you're listening to this show along the Marketing Podcast Network, but did you know there are other great shows on MPN to help your business? Heather Ek hosts an amazing show called you'd Radiant Spirit. Heather, Tell listeners about the show. What if the colors you're drawn to, the creative urges you ignore, and the quiet, intuitive hits you brush off are actually trying to tell you something? Your Radiant Spirit is the podcast that helps you listen and live with greater clarity and purpose. And where can people subscribe? You can find and subscribe@heather.com your radiant spirit on marketing podcast.net or search for it wherever you get your podcasts. You heard her. Go subscribe. This podcast is heard along the Marketing Podcast Network. For more great marketing Podcasts, visit marketingpodcasts. Net.

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