Demo • Dana Consulting — The AI Transformation Blueprint for B2B Sales

1932
05:42:26.160 –> 05:42:29.390
Julia Nimchinski: Welcome, Victor Adafuya.

1933
05:42:29.560 –> 05:42:32.630
Julia Nimchinski: Who is the founder and CEO of Data Consulting.

1934
05:42:33.150 –> 05:42:39.939
Julia Nimchinski: The AI Transformation Blueprint for B2B Sales. Super excited to host you here. How have you been?

1935
05:42:40.480 –> 05:42:43.570
Victor Adefuye: I’ve been really well, how are you? Oh, I gotta turn on my camera, that’ll help.

1936
05:42:43.570 –> 05:42:44.320
Julia Nimchinski: Yeah.

1937
05:42:44.320 –> 05:42:45.210
Victor Adefuye: Yes.

1938
05:42:46.390 –> 05:42:48.980
Victor Adefuye: I’m well, how are you? I’m excited to be…

1939
05:42:49.460 –> 05:42:51.949
Julia Nimchinski: Yeah, long time no see.

1940
05:42:51.950 –> 05:42:54.300
Victor Adefuye: Yes, yes, yes,

1941
05:42:54.510 –> 05:43:12.980
Victor Adefuye: I’m excited for this topic. It’s been a great day, lots of, incredible insights, and, hopefully what I, share today kind of brings everything together and talks about how we can, actually realize sort of the full potential of, investments in AI.

1942
05:43:14.110 –> 05:43:15.969
Julia Nimchinski: Excited for this. Let’s… let’s do it.

1943
05:43:15.970 –> 05:43:20.400
Victor Adefuye: Yes, absolutely. Okay, so let’s dive in. I…

1944
05:43:20.530 –> 05:43:22.929
Victor Adefuye: I have some slides that I wanna…

1945
05:43:23.110 –> 05:43:25.610
Victor Adefuye: Share with you guys, and then…

1946
05:43:26.540 –> 05:43:31.809
Victor Adefuye: A few resources, so let me make sure my slides are set up here. Here we go.

1947
05:43:34.760 –> 05:43:37.140
Victor Adefuye: Alright, so mine is a little bit…

1948
05:43:37.450 –> 05:43:55.140
Victor Adefuye: it’s… it’s a demo. I will be demoing, different tools, but I think the most important thing is to make sure that, we are aligned in terms of, how do we actually, produce

1949
05:43:55.140 –> 05:43:57.869
Victor Adefuye: The impacts that,

1950
05:43:57.870 –> 05:44:22.809
Victor Adefuye: that there’s so much potential for with AI, and so that’s what I wanted to talk about today, is not just, you know, there’s a tool here that does this, or I’ve heard, you know, AI can be helpful in this way or that way. It’s, my… this presentation is more about how do we make sure that we are choosing the right tools, that we are focusing on the right problems, which ultimately

1951
05:44:22.810 –> 05:44:29.119
Victor Adefuye: drives, the true ROI. So, I’m gonna dive right in.

1952
05:44:29.880 –> 05:44:32.030
Victor Adefuye: Okay, so,

1953
05:44:32.030 –> 05:44:56.190
Victor Adefuye: I’m sure that everyone that’s been attending for today have heard all of the wonderful things that are happening in the world of AI, but at the same time, while a lot of companies are investing in AI, there’s a lot of data suggesting that only a few of them actually are seeing results. I don’t know, for those of you who

1954
05:44:56.190 –> 05:45:10.200
Victor Adefuye: may be less nerdy about these topics than I am, there’s been a huge debate over the last few weeks that was triggered by a study from MIT that found that 95% of AI pilots fail.

1955
05:45:10.200 –> 05:45:33.539
Victor Adefuye: Right? And so, that obviously is a big headline. You know, the media jumped on top of that, created a lot of, debate about this question of, is AI… does it… can it live up to its potential? I think unequivocally, yes. But we need to approach, AI in a very different way than most firms are approaching it.

1956
05:45:33.540 –> 05:45:57.509
Victor Adefuye: What I’m seeing, having been in this space for, you know, 10, 15 years as an advisor for B2B and go-to-market organizations, I’ve seen a lot of digital transformation initiatives get started that didn’t actually live up to their fullest potential, and my concern is that we are about to make very much

1957
05:45:57.510 –> 05:46:21.649
Victor Adefuye: the same mistakes that we’ve made in digital transformation, but the stakes here are so much higher. So, today, my plan is to share with you guys a blueprint for how to actually choose the right AI tools directed towards the right problems in your go-to-market process. So, for what it’s worth, my focus is on B2B, go-to-market and sales.

1958
05:46:21.650 –> 05:46:25.029
Victor Adefuye: And so that’s… that’s what this presentation’s all about.

1959
05:46:26.100 –> 05:46:31.600
Victor Adefuye: Alright, and so here’s kind of, like, the headline. It’s a,

1960
05:46:31.620 –> 05:46:53.369
Victor Adefuye: a statement that I learned at my old firm, Winning by Design, where I was an MD there for a few years, but I think it is applicable not only to sales calls, but also this challenge of AI transformation and adoption. And that phrase is, prescription before diagnosis is malpractice.

1961
05:46:53.370 –> 05:47:06.090
Victor Adefuye: Right? And so, what does that mean? Well, it’s, think about it in the doctor context, right? If you go into a medical office, and you, walk in with a headache.

1962
05:47:06.690 –> 05:47:31.630
Victor Adefuye: and the doctor barely asks you any questions, barely runs any tests, and then recommends that you have brain surgery the next day. Most of us would be opposed to that. We would think that there wasn’t enough information here to have reached the conclusion. And so I think a lot of what we’re seeing right now is a lot of prescribing solutions without a true diagnostic of the problem that we’re trying to solve.

1963
05:47:31.630 –> 05:47:56.350
Victor Adefuye: solve, and the value of trying to solve it. And so, that’s what I want to share with you today, is how do we embark on this AI transformation journey, but by focusing not just on the tools and the fancy AI that’s available, but really understanding what are the challenges that you should prioritize.

1964
05:47:56.350 –> 05:47:57.960
Victor Adefuye: Prioritize and focus on.

1965
05:47:59.340 –> 05:48:09.149
Victor Adefuye: So, just really, really quickly, let’s, I want to talk a little bit about why, what doesn’t work, right? And so…

1966
05:48:09.390 –> 05:48:23.329
Victor Adefuye: you know, as someone, again, who’s been in this AI… well, not AI, but in sales enablement, transformation, go-to-market strategy for a decade and a half, I’ve seen a lot of,

1967
05:48:23.330 –> 05:48:46.559
Victor Adefuye: companies, fall, fail in their efforts to transform their organizations. Whether it’s bringing on a new technology, or it’s, you know, rolling out a new methodology, or anything, right? A new way that we want to write proposals, a new, tool that we want to use. There is, there are…

1968
05:48:46.560 –> 05:49:09.230
Victor Adefuye: the key issue that always needs to be solved is change management and behavior, right? And so, for a lot of organizations, they kind of skirt over the change management piece, right? There’s a hope that the tool itself will solve the problem, right? There are a lot of people out there who, you know, have

1969
05:49:09.230 –> 05:49:31.750
Victor Adefuye: you know, Gong, and they use Gong, and they use other revenue intelligence or call intelligence, solutions, but everything that I’ve heard from my working with clients is that, most of those calls don’t get listened to, right? And so, just having the, the tool is not enough to get the fullest,

1970
05:49:31.750 –> 05:49:54.679
Victor Adefuye: the most out of it, because the tool actually has to be used, and the behavior of, you know, reviewing calls, analyzing them, coaching towards them is… hasn’t been changed, and unless you get that behavior change from the managers and the reps, then, you know, having a tool like Gong is not really going to get you very far.

1971
05:49:54.680 –> 05:50:19.160
Victor Adefuye: Very often, we also try to solve these problems by just diving into training. You know, hey, let’s roll out training to the team, let’s make, you know, thinking that the training alone is going to move the needle, but, you know, there’s the forgetting curve, there’s a hundred reasons why training without reinforcement doesn’t really get you very, very far, right? And so then we think about, alright, how do we

1972
05:50:19.160 –> 05:50:41.779
Victor Adefuye: reinforce this. One big way is through the managers, but managers or sales managers, are among the most overwhelmed people within an organization. They have so many things on their plate. They’re getting it from, you know, the executive team, they have the reps that they need to answer to, and then they have all of the pressures from external parties.

1973
05:50:41.780 –> 05:51:00.519
Victor Adefuye: And so, it becomes very, very difficult to get them to be reinforcers, right? And a lot of them maybe don’t have the skills, they don’t have the background to be able to do, you know, focus on behavior change among their teams.

1974
05:51:00.520 –> 05:51:16.429
Victor Adefuye: And then, of course, we have enablement, you know, one-pagers, guides, things like that, persona cards, and unless those things aren’t… are tailored to the organization, unless they’re being used.

1975
05:51:16.430 –> 05:51:40.919
Victor Adefuye: You know, and they’re not going to be able to drive results, right? And so, all of these traditional approaches, the reason why they fail is that they are too focused on… they’re not focused enough on the behavior change piece. They’re not focused enough on the change management piece, and the realization that, that for you to really move the needle, you need to get the

1976
05:51:40.920 –> 05:52:02.380
Victor Adefuye: reps to behave in ways that they’re doing, and the managers, the whole team, to be acting in ways that are different than they’re doing today. And so, the first step is understanding what is going on today, what is the status quo, so that we can be very, with evidence, so that we can be specifically targeting those challenges.

1977
05:52:03.300 –> 05:52:26.390
Victor Adefuye: So, what I want to recommend for you today is a five-step diagnostic framework, right, that I believe is the best path towards making AI transformations stick, right? It starts with diagnosing and understanding the root cause of the issues that you’re experiencing within your funnel.

1978
05:52:26.390 –> 05:52:31.590
Victor Adefuye: Right? Before you buy any tools, before you, you know.

1979
05:52:31.590 –> 05:52:44.869
Victor Adefuye: invest in any AI demos, I would strongly… this is the critical first step that a lot of people miss, right? And, what I’m going to show you today is how AI can actually help you with this critical first step so that you can accelerate it.

1980
05:52:44.870 –> 05:53:09.780
Victor Adefuye: Right? And then, once you’ve determined what are the key issues to focus on, then it becomes, alright, how do we design an AI tool that will actually solve the problem that is specifically directed at the issues, the real issues that the organization is facing? Then we roll it out to the team, right? And then building into their workflows, then we do the

1981
05:53:09.780 –> 05:53:16.969
Victor Adefuye: And then we make sure that there is, ongoing reinforcement so that that behavior change actually sticks.

1982
05:53:18.910 –> 05:53:34.569
Victor Adefuye: So I want to give you a real case study of an old client of mine where we took this approach and what the outputs were, and then I’m going to show you guys a demo of exactly how you go about doing this sort of analysis.

1983
05:53:34.570 –> 05:53:58.599
Victor Adefuye: So, I had a client, they were a fast-growing company, they, you know, in a few short years, went from 4 salespeople all the way up to 24, but, there were some persistent challenges that they just kept on running into, right? They… there were a huge performance gap, right? Some of their best reps were

1984
05:53:58.600 –> 05:54:01.809
Victor Adefuye: Performing head and shoulders above everybody else.

1985
05:54:01.810 –> 05:54:23.569
Victor Adefuye: Right? They were generating a large volume of leads, but only a small percentage of them were actually converting. And then, this was among the biggest issues, they had a huge no-show rate. So, a lot of their leads were coming from Facebook, and so, you know, I think Facebook

1986
05:54:23.580 –> 05:54:40.180
Victor Adefuye: no knock to Facebook, but a lot of times, those, often, I’ve seen them be kind of, like, lower commitment type of leads, right? And so, when, even though folks were signing up for discovery calls with their BDRs and their AEs.

1987
05:54:40.180 –> 05:54:55.509
Victor Adefuye: half of them weren’t showing, and so they were spending all this money on Facebook, driving leads, right, that would go as far as filling out the form, giving them the information that they need, but when they… when it came down to it, they weren’t showing up.

1988
05:54:55.510 –> 05:55:20.059
Victor Adefuye: Right? And so there were a myriad of these issues throughout the organization. It really had an impact on their ability to scale. The CEO, he was… he’s an engineer, and he said… he described the situation to me as he wants to build a factory. He wants to have… the same way that he can go out and hire a engineer off the street, and if they have the right background.

1989
05:55:20.060 –> 05:55:44.239
Victor Adefuye: background, they can come into his organization and be able to build the complex software and hardware that they were building. He wants to be able to reliably bring in sales reps, you know, plug them into his system, and then efficiently get them onboarding and doing the right things. But he couldn’t do that with confidence because, you know, one example he gave was that

1990
05:55:44.240 –> 05:56:03.460
Victor Adefuye: sometimes he would have to put a rep on a performance improvement plan, and then when he put them on the performance improvement plan, all of a sudden they start, producing a lot more, right? And so… so those, issues made him less confident in his ability to scale, and, and really,

1991
05:56:03.560 –> 05:56:09.200
Victor Adefuye: Kind of these issues were blocking, the… the… them from achieving their fullest potential.

1992
05:56:10.180 –> 05:56:10.920
Victor Adefuye: Nope.

1993
05:56:11.390 –> 05:56:13.070
Victor Adefuye: And so,

1994
05:56:13.200 –> 05:56:32.409
Victor Adefuye: We did a diagnostic with them, and I’ll show you a little bit more about what I mean by that. And, among other things, we analyzed their sales data, and then we also analyzed, their calls. So, we took hundreds of calls throughout, that were conducted by their teams.

1995
05:56:32.410 –> 05:56:43.400
Victor Adefuye: Analyze them, try to create objective ways to determine, the strengths and the weaknesses of, that were evident in those calls.

1996
05:56:43.400 –> 05:57:06.000
Victor Adefuye: Right? And they used the SPICE methodology, those of you who are familiar with SPICED, situation, pain, impact, critical event, and decision, and so we try to quantify what was SPICED, what were the patterns among SPICED, from their top performers, and then also looking at their closed-won deals and their closed-loss deals.

1997
05:57:06.000 –> 05:57:24.069
Victor Adefuye: And there was… a lot of the patterns were… were immediately evident, right? One of them was, and I think the biggest one was this first one, impact quantification. What we found was that they… the sales reps that were the most successful were the reps who were,

1998
05:57:24.070 –> 05:57:47.180
Victor Adefuye: doing a true ROI analysis with their customers. So what does that look like? Well, this organization, they sold a, they sell these LED signs that are on the side of the road, right? And, you know, every organization, every restaurant that has a sign in front of their building will be evolving to LED

1999
05:57:47.180 –> 05:58:12.109
Victor Adefuye: Over the next few years, because it makes no sense to, you know, have people climb up those poles and change the letters. Whenever you have a new lunch special, it’s better to just, you know, have it be digital on a screen, right? And so… but it was a big investment, right? And the restaurant owners, etc, they were a little nervous about, okay, I’m gonna shell out, you know, 100 grand, 50 grand, whatever it may be, and is this thing gonna pay

2000
05:58:12.110 –> 05:58:18.120
Victor Adefuye: for itself or not. And some of the weaker reps, and in the deals that stalled or lost.

2001
05:58:18.120 –> 05:58:32.209
Victor Adefuye: the, it was kind of a lot of hand-waving. Yeah, oh, you know, our clients tell us all the time that it pays for itself, don’t worry about it, it’s gonna pay for itself. But they’re best reps, and often in the deals that actually closed.

2002
05:58:32.210 –> 05:58:56.860
Victor Adefuye: they were doing what they, what they call a traffic analysis, right? And so what… they would put the address of the restaurant into this tool that they had, and that tool could estimate how many cars were driving in front of the restaurant every single day. And then it was a conversation with the owner about, alright, you know, if we could put your delicious lunch special in a huge sign, and people could see it from

2003
05:58:56.860 –> 05:59:10.789
Victor Adefuye: you know, half a mile away down the road, you know, what do you think would be the impact? Do you think you’d get one more person coming in every day? All right, all right, how much does the average person spend when they come into your restaurant? All right, 50…

2004
05:59:10.790 –> 05:59:24.360
Victor Adefuye: $50 a ticket, all right, you know, this thing will pay for itself in a month or two, right? It was the real, detailed analysis using the client’s numbers that move the needle. And so,

2005
05:59:24.410 –> 05:59:48.249
Victor Adefuye: And so that was a key insight, because what it meant was we should prioritize any sort of intervention, whether it’s AI, whether it’s training or enablement, but directed towards these specific problems that were evident through the analysis that we did. And so, we know, objectively, that the failure to do these things

2006
05:59:48.250 –> 06:00:10.439
Victor Adefuye: were leading to worse results, right? And so, now, knowing what the answer is, we can, in this case, we did, you know, a refresher of the training on ROI for the team. We built out some ROI calculators for the team, right? You know, built that into their onboarding program.

2007
06:00:10.440 –> 06:00:16.609
Victor Adefuye: Right? And so… and then we’re… we’re also looking at AI… different AI tools that’ll help,

2008
06:00:16.610 –> 06:00:40.529
Victor Adefuye: and identify when that traffic analysis wasn’t being done, so that the rep, could be flagged, and it could motivate them to do it, right? With the idea that if we adopt these solutions, we’re gonna see, you know, a positive impact, and that’s exactly what we did. Their win rates went up, by 20% within 3 months of implementing some of these changes.

2009
06:00:41.040 –> 06:00:44.629
Victor Adefuye: Right? And so, that wasn’t the only…

Carilu Dietrich:

2010
06:00:44.630 –> 06:01:09.020
Victor Adefuye: kind of, observation that we had, right? So, they were, like, all organizations, very much interested in AI. And so, they, too, were curious about what other AI tools can we invest in, or which AI tools should we invest in, that’ll really move the needle. And so, again, we looked at what are the different

2011
06:01:09.020 –> 06:01:24.579
Victor Adefuye: challenges that were evident within the organization, right? And then thought about, okay, what then is the AI tool that will be able to help address that problem? So, again, like I said at the beginning.

2012
06:01:24.580 –> 06:01:44.040
Victor Adefuye: you know, we didn’t start with the AI tool. We started with the root cause, the problems that were evident in their sales funnel, in their sales metrics, in their sales calls, and then being able to understand and quantify what is the financial impact of this, right? If we were able to get you, you know.

2013
06:01:44.160 –> 06:02:09.119
Victor Adefuye: 10% more closed ones, right? Increase your win rate from, you know, 20% to 22% with your closed one through this intervention. What is the bottom line impact of that, right? And so, that is, that was the way that we were able to say confidently that an investment in these various AI tools will actually move the needle in this way.

2014
06:02:09.120 –> 06:02:26.720
Victor Adefuye: and then you’ll be able to get a positive ROI. You know, frankly, whenever I hear from folks that, you know, they’re having difficulty quantifying the ROI of their investments in AI, especially in the go-to-market arena, B2B sales.

2015
06:02:26.720 –> 06:02:51.120
Victor Adefuye: You know, I’m always like, you’re doing it wrong, right? Because at the end of the day, there are only a few, like, levers that we can pull in sales, right? It’s either you’re shortening the sales cycle, you’re improving conversion rates, you’re improving your contract value, right? Or you’re improving the speed that deals are going through the funnel, right? And so, if you cannot

2016
06:02:51.310 –> 06:03:01.809
Victor Adefuye: point to, you know, one of those metrics, you know, volume, speed, conversion, then you’re not likely

2017
06:03:01.810 –> 06:03:26.150
Victor Adefuye: then what you’re doing is not working, right? And so there has to be a way for us to connect not only the challenges that we’re seeing, but also the tools that we are deciding to invest in to actual quantifiable, measurable impacts, and we need to know that going into them. Not after we bought the tool, but going into that purchase decision, so that we’re making the right

2018
06:03:26.150 –> 06:03:31.099
Victor Adefuye: This, choice that will actually, move the needle.

2019
06:03:32.830 –> 06:03:38.969
Victor Adefuye: So, what does that look like? Well, I wanna… there are a few…

2020
06:03:38.970 –> 06:03:52.980
Victor Adefuye: things that you always want to start with to be able to get this AI diagnostic, and to do it the right way. So one of them is, call analysis. So doing… being able to look at calls at scale.

2021
06:03:52.980 –> 06:04:07.770
Victor Adefuye: identify patterns across those calls to try to understand, like I just showed you, what are the, differences between the closed loss of closed won, different industries, top performing reps versus everybody else.

2022
06:04:07.770 –> 06:04:22.349
Victor Adefuye: Right? You also want to, and I’m going to show you an example of that shortly, you also want to do, sales process mapping. So, being able to map out, alright, end-to-end, what… where do deals get stuck.

2023
06:04:22.350 –> 06:04:45.919
Victor Adefuye: You know, what are the first, second, third meetings that we have? What are some of the issues that come up there? You look at your sales data, your pipeline data, and you can see, you know, we have a huge drop-off on stage four, you know, a lot of deals end up, you know, going dark after the demo, whatever the issues are. You need to be able to map out that process, and then try to find the bottleneck with

2024
06:04:45.920 –> 06:04:47.810
Victor Adefuye: within that process.

2025
06:04:47.880 –> 06:05:12.420
Victor Adefuye: The next step that you want to look for is, benchmarking. And so, looking at your performance metrics, your, you know, lead to MQLs, your MQLs to SALs, whatever, you know, funnel metrics that you use, that are relevant to your sale, being able to identify what those are, being, you know, if you’re in SaaS, it’s a lot easier to benchmark.

2026
06:05:12.420 –> 06:05:22.209
Victor Adefuye: Right? Because we have these, you know, VCs and other organizations that are out there tracking these metrics, and so…

2027
06:05:22.210 –> 06:05:45.820
Victor Adefuye: you know, wherever you can, find… get your hands on some comparable benchmark data, and that’s also another area that AI can help, leveraging deep research tools to try to find, benchmarks that are appropriate for you to compare your performance to, right? It’s the combination of the call analysis, right, which actually,

2028
06:05:45.820 –> 06:05:48.430
Victor Adefuye: Reflect the team skills and behaviors.

2029
06:05:48.430 –> 06:06:07.539
Victor Adefuye: Right? Then, the process mapping to understand the bottlenecks, and then the benchmarking. It’s a combination of these things that give you a clear view of what are the biggest issues to address in this sales motion, and what’s the potential return by doing so.

2030
06:06:07.640 –> 06:06:09.000
Victor Adefuye: So…

2031
06:06:09.120 –> 06:06:16.029
Victor Adefuye: This is just a little bit more about that end-to-end process, just thinking about what is the data they.

1
00:00:00.380 –> 00:00:17.370
Victor Adefuye: Right? And then, you know, sales call recordings and transcripts, you know, downloading conversion metrics, doing interviews with reps and managers, and then, you know, being able to clarify, you know, what are the… what are sort of the skill gaps across the team.

2
00:00:17.380 –> 00:00:40.970
Victor Adefuye: you know, I always do a cultural assessment because, and you can call it a coaching assessment, because at the end of the day, and we’ll talk more about this shortly, you can roll out the best technology in the world, the best training in the world, the best coaching program in the world. If it’s not reinforced, if there aren’t opportunities within the organization

3
00:00:40.970 –> 00:00:52.019
Victor Adefuye: for ongoing practice and role-playing and, you know, skill development, right? Then none of that stuff is gonna stick. You know, you’re gonna have turnover, you’re gonna have

4
00:00:52.020 –> 00:01:15.999
Victor Adefuye: you know, some teams that are more into it than others, right? And so you’re always going to end up with this disparity. And so, one of the things that is also essential is that there is this kind of view towards good communication, that there are opportunities to reinforce, to practice, that there’s a culture of coaching, there’s a culture of continuous learning.

5
00:01:16.000 –> 00:01:28.279
Victor Adefuye: Otherwise, you know, the… it’s really hard to… to make this work stick. So, I’m not gonna get into too much of this detail right now, because I actually want to show you guys

6
00:01:28.280 –> 00:01:39.810
Victor Adefuye: some of what is possible, from… and how you can leverage AI to actually solve these problems.

7
00:01:40.450 –> 00:01:49.780
Victor Adefuye: So, let me… share my screen with you, and I’m gonna pull up…

8
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Victor Adefuye: a few documents. I want to start with, call analysis, but while I’m pulling this up, any questions on what I’ve shared so far?

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Julia Nimchinski: We have a couple of questions around… That’s great.

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Julia Nimchinski: So here’s one. Where should we start if our sales team is resistant to adopting AI technology?

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Victor Adefuye: I think the answer is what’s in it for them.

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Victor Adefuye: Right? You know, I think… that…

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Victor Adefuye: well, two things, actually. So, one sitting for them is the most important, right? When I build, you know,

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Victor Adefuye: tools that help with better qualification, or analyzing sales calls and providing coaching to reps and to managers about it, right? In addition to

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Victor Adefuye: This thing will help you better qualify, and, you know, you’re less likely to miss gaps, and then, you know, you’re less likely to chase deals that aren’t gonna close.

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Victor Adefuye: things like that. You can even get down into much more nuance about, you know, this thing will help you write your recap emails faster, this thing will help you write your proposals faster, right? I have a client, that we’re doing a project now that, at least with the BDRs, when they have their qualification calls, it analyzes the calls, and among, in addition to saying, hey, is this thing BANT qualified?

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Victor Adefuye: or not, it also pre-populates a lot of their fields that the BDRs used to have to fill out on their own in Salesforce, right? And so, that’s,

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Victor Adefuye: that saved them a ton of time, right? And, you know, they didn’t have to recreate from their notes or their memory what they remember from the call, it just did it for them, right? And so, to me, that is an essential first step, is being able to articulate for them what’s in it for them, show them how it… the value from it, and it’s not just, you know, we’re…

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Victor Adefuye: We’re kind of, looking over your shoulder and all of that.

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Victor Adefuye: Alright, excellent. So, I want to show you guys an example of…

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Victor Adefuye: the cross-deal kind of analysis, piece. So, this is a bot that I use.

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Victor Adefuye: to… help… clients,

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Victor Adefuye: to analyze their sales calls using MedPick, and then identify patterns that would call for more interventions. It takes a little bit, but it’s gotta think… it’s this thinking model, so…

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Victor Adefuye: I wanted to get it set up here.

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Victor Adefuye: All right, so this is a bot, it’s called my MedPick Cross Deal Analyst Bot. Just really quickly, people like to see the back end of it, but, you know, it’s not…

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Victor Adefuye: it’s not that hard, right, in a way, but it takes some planning and some forethought to get it there, right? There’s a complex set of instructions about what it should do, you know, analyzing the calls, transcripts that I provided, and, you know, spitting out a MedPick analysis, and then some recommendations. It’s got a knowledge base that has

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Victor Adefuye: information about Medic and, you know, Medic qualification best practices, what is a champion, things like that. And then, some other, best practice guides that support the analysis. And so that allows me…

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Victor Adefuye: 2… Computer’s a little slow today, here we go.

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Victor Adefuye: Just provide some calls. So these are… Just some random calls.

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Victor Adefuye: from… an old client of mine.

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Victor Adefuye: And so… they… have allowed me…

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Victor Adefuye: Because it’s very old. These are 7 different calls, right? And so, I always, think it’s essential to, have a broad cross-section of calls to analyze. Why isn’t this showing up here?

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Victor Adefuye: Let’s make sure these are all… Showing, sometimes… There’s always one.

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Victor Adefuye: There we go.

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Victor Adefuye: Okay, let me make sure I didn’t… Miss any… Here we go.

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Victor Adefuye: Alright.

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Victor Adefuye: So, analyze… These calls… for patterns… Right? And so…

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Victor Adefuye: What the bot is doing is it’s…

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Victor Adefuye: you know, following my instructions. It is reviewing these four calls.

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Victor Adefuye: And trying to pull the, what it finds around MedPick.

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Victor Adefuye: In each of these calls, and then provide the diagnostic report that, that I’ve asked it to, just for the sake of time. It’s always better, this is a small thing, actually, it’s not that small, it’s pretty important. If you’re going to be doing the type of work that I’m showing you, you always want to use these, the thinking models, right? The reasoning models, because…

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Victor Adefuye: you know, that they’re better at math, they’re better at analysis, right? And so, you know, something like…

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Victor Adefuye: you know, what is this MedPick standard? What is the definition of a champion? And then, is there evidence in the transcript that we have a champion? Those are the kind of, kind of more…

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Victor Adefuye: complex reasoning tasks that you actually want it to think a little bit before it spits out an answer. But let me, for the sake of…

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Victor Adefuye: Speed… Just get it to… Give us an answer as quickly as possible.

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Victor Adefuye: Right? And so it’s following the instructions, right? Across at least these three conversations, the reps are securing exploratory dialogue, they’re uncovering pain, right, and some decision process. However, there are consistent gaps in metrics, economic buyer, quantifying impact.

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Victor Adefuye: Right? Leaving a lot of these deals kind of feeling, like, nice to have, rather than, you know, you know, urgent initiatives, right? And so, across those calls, it’s saying, hey, look, on average, your reps are doing

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Victor Adefuye: pretty well with identifying pain, but they are not doing well at engaging economic buyers. They’re doing okay in other areas, but, you know, I think for those of us who’ve been in sales and go-to-market for a long time, we know the value of

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Victor Adefuye: you know, quantifying impact, right? And so, you can see which challenges are the… are the biggest, right? And then, you know.

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Victor Adefuye: this thing also does provide some insight into what’s going on with these buyers. Are they ready to buy, generally, or are they not? This was a… this is a key insight that I’ve gotten from a lot of calls as well, that sometimes, you know, sales reps have happy ears, and they think that someone is actively in the buying process, but they’re not. And so… and if they would just listen a little bit more, they would hear that

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Victor Adefuye: oh, you know, I’m just starting this process, I haven’t, you know, spoken, I haven’t done a lot of research on it, right? They’re very much early in the process versus someone who’s actively buying, and so,

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Victor Adefuye: Insights into how mature, your buyers are is essential.

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Victor Adefuye: Right? And then identifying what are some of the big risks, and what are the coaching priorities that are necessary to address these risks, right? And so, this then is… gives us one snapshot.

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Victor Adefuye: Right? Of what is happening within this organization, at least in how they’re engaging with customers, and where might there be the greatest leverage to try to find one or more AI tools, or any sort of intervention, training, coaching, whatever it is, to help address, this, any of these issues.

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Victor Adefuye: Another critical step that I think is, really helpful is understanding and analyzing, sales metrics. And so this is a…

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Victor Adefuye: Actually, I’ll show you the full bot. I have a teaser bot that I’m going to share with you guys if you’re interested at the end. But I want to show you this… I want to show you this one. So this one is all about, looking at sales metrics.

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Victor Adefuye: And…

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Victor Adefuye: Being able to identify what are the root causes of some of the issues, comparing them to benchmarks.

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Victor Adefuye: And then… And then, and then, identifying solutions. And so…

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Victor Adefuye: I’ll just show you guys this very, very quickly, the root… the source information, just to show you that it’s, like.

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Victor Adefuye: you can download this information from your CRM, whatever it is, right, or you can fill out a form like this that breaks down, you know, your pipeline metrics, conversion rates throughout the funnel.

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Victor Adefuye: Right? Breaking down by your teams, different lead sources, to the extent that those are relevant. So, I could take this data intake form.

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Victor Adefuye: Move it back over to… This metrics analysis bot, and then, again, you’re gonna get better answers

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Victor Adefuye: If you do… if you use a reasoning model, but for the sake of time, I just want to show you the types of analysis that it could do. Just drop this data in here.

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Victor Adefuye: And, again, Okay, yep.

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Victor Adefuye: Do all that.

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Victor Adefuye: Yeah, proceed.

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Victor Adefuye: Right? And so…

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Victor Adefuye: Again, we can leverage AI to analyze, objectively, the data, right? In this case, it’s, looking at their metrics, right? Identifying where they’re outperforming.

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Victor Adefuye: Right? Early in the funnel, they’re killing it, right? But as soon as they, get into the mid-funnel, they, there’s some significant issues. So, this is actually the same, organization that I gave you that case study of a second ago, and so you can see their very high no-show rate.

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Victor Adefuye: Right? And then, they are, below benchmarks in their win rates, so it’s able to identify, you gotta stabilize these win rates, you gotta get… address these no-shows.

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Victor Adefuye: Right? And then, you know, here are your strengths, here are the top 3, issues that you should focus on, and this is the funnel analysis.

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Victor Adefuye: Sometimes the chat GPT formatting is off, but you can see what it’s doing is it’s looking at their metrics.

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Victor Adefuye: calculating the conversion rate, looking at industry benchmarks, and it’s pulling on source data that I’ve given it around industry benchmarks, right? And then it’s saying, are you…

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Victor Adefuye: good? Are you weak? Are you strong in these different benchmarks? How does that differ by lead source, right? What… how does that differ by your different teams?

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Victor Adefuye: Right? And then, root cause analysis. What are the reasons why this may be, this metric might be very low or very high? And then recommendations fix it over the next 30, 60, 90 days, right? And so.

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Victor Adefuye: This is another snapshot into the organization. We have calls, right, analysis that tells us, alright, here are the skill gaps that the team has, right, and how to, and where there might be opportunities for improvement. We just, showed you the metrics analysis about, you know, the data that, what does the data show are the biggest challenges.

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Victor Adefuye: in this sales organization, and then

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Victor Adefuye: You know, having that insight then allows you to, identify, alright, where’s the low-hanging fruit?

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Victor Adefuye: Where might there be, you know, opportunities to invest in AI or any sort of other training and enablement that will help move the needle? And so, again, this is what I recommend.

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Victor Adefuye: you know, starting with this sort of analysis, looking at your benchmarks, I mean, looking at your metrics, looking at the call performance across your team, and then making sure that whatever intervention you decide on, whatever agents you decide to build, that they are actually targeted towards the real issues that are evident in the data.

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Victor Adefuye: So, I already showed you the live demo,

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Victor Adefuye: But yeah, so for those of you who are interested, I actually will… I’m happy to share with you, public links to the, GPTs that I built and I just showed you. One of them is…

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Victor Adefuye: The sales call analysis one, and then the other one is the metrics analysis, and so what, I’m gonna put a link into the chat.

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Victor Adefuye: Here, so if any of you are interested, you can go there and, it’ll give you… fill out the form, and it’ll give you…

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Victor Adefuye: It’ll give you, send you a note that has a link to these bots, and you can download your own sales data, you can upload your own sales calls, and start to analyze them at scale, right? Try to aim for at least 15 calls, so you could start to get some statistical significance. But this is the foundation of identifying the right

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Victor Adefuye: solutions, right? And, really anchoring them in the types of things that are gonna move the needle. So, yeah, that’s,

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Victor Adefuye: For the most part, my presentation for today.

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Julia Nimchinski: Amazing. Thank you so much, Victor. Amazing session. We passed along your link to the chat, to the Slack chat. Thanks again for the incredible session, and that wraps up our Day 2 of the Agenda Distribution Summit.

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Julia Nimchinski: Thank you to all of the incredible speakers, panelists, all of you watching, and the demo leaders and sponsors. We’ll be back tomorrow at 8.30 a.m. Pacific.

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Julia Nimchinski: And we have lots of really exciting fireside chats, executive roundtables, VC roundtables. So yeah, and don’t forget, you can book one-on-one sessions, mentorships, advisory sessions on the HSC Marketplace, artskillexchange.com.

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Julia Nimchinski: And see you tomorrow!

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Victor Adefuye: Alright.