1 00:00:00,719 --> 00:00:04,160 Welcome to episode number 354 of the Mindful Marketing 2 00:00:04,160 --> 00:00:07,859 podcast. And today, we're talking all about the relationship between 3 00:00:07,919 --> 00:00:11,519 sales and marketing because they go together like peanut butter and jelly. And 4 00:00:11,519 --> 00:00:15,365 today, I'm excited to have Victor Adefuye on the podcast to talk 5 00:00:15,365 --> 00:00:18,185 all about it. But first, a word from our sponsor. 6 00:00:18,965 --> 00:00:22,805 Riverside is the all in one podcast recording and editing tool that 7 00:00:22,805 --> 00:00:26,630 I use for this right here show. I use it to edit not only 8 00:00:26,630 --> 00:00:30,390 the audio and the video. It is like chef's kiss, magical, making the 9 00:00:30,390 --> 00:00:34,010 entire process so so easy. Plus, 10 00:00:34,230 --> 00:00:38,070 I love their magic AI clips. Their 11 00:00:38,070 --> 00:00:41,495 little AI robot in the background pulls out the most 12 00:00:41,495 --> 00:00:45,335 impactful moments of the episodes without me having to comb through and do it 13 00:00:45,335 --> 00:00:48,855 myself, resizes them for social media. So those vertical 14 00:00:48,855 --> 00:00:52,615 videos you see on TikTok and reels, those all come from magic 15 00:00:52,615 --> 00:00:56,390 AI inside of Riverside. It's literally one click. It spits out 16 00:00:56,390 --> 00:01:00,230 10 clips. I pick the best one and away I go saves me so much 17 00:01:00,230 --> 00:01:03,989 time. If you wanna get on the Riverside train, check it out today, the 18 00:01:03,989 --> 00:01:07,590 links in the show notes, and make sure to use my code DREA, d r 19 00:01:07,590 --> 00:01:11,130 e a, at checkout to get 15% off your membership. 20 00:01:12,235 --> 00:01:15,935 Victor, welcome to the show. Thank you, Andrea. 21 00:01:16,075 --> 00:01:19,595 Nice to see you. I should say welcome back because you are a 22 00:01:19,595 --> 00:01:23,435 returning guest, and I'm excited for the conversation today because you've 23 00:01:23,435 --> 00:01:26,750 been doing some really interesting things with AI 24 00:01:26,810 --> 00:01:30,109 specifically. But before we get into all of that, 25 00:01:30,570 --> 00:01:34,409 tell the listeners, what is the relationship between marketing and 26 00:01:34,409 --> 00:01:37,770 sales? Well, in my experience, it's a 27 00:01:37,770 --> 00:01:41,235 contentious one. You know? You would 28 00:01:41,235 --> 00:01:44,755 think that there would be greater alignment between these two 29 00:01:44,755 --> 00:01:48,134 areas of business that are so dependent on each other. 30 00:01:48,354 --> 00:01:52,195 Right? Sales needs marketing to get them the 31 00:01:52,195 --> 00:01:56,009 leads, to figure out the right strategy, messaging, give 32 00:01:56,009 --> 00:01:59,689 them the assets they need to be successful. Marketing needs sales to 33 00:01:59,689 --> 00:02:03,070 close the leads that they drive. But 34 00:02:03,450 --> 00:02:07,049 all too often, there's a lot of finger pointing and 35 00:02:07,049 --> 00:02:10,509 blaming and misalignment between the two teams. And, 36 00:02:10,805 --> 00:02:14,405 yeah, I mean, I think I think it's, it's always, a 37 00:02:14,405 --> 00:02:18,245 sign of, a a challenge for an organization when there's a lot 38 00:02:18,245 --> 00:02:22,005 of contention between these two sides, and, unfortunately, I see 39 00:02:22,005 --> 00:02:25,460 it all the time. So, yeah, definitely one of, 40 00:02:25,780 --> 00:02:29,460 of friction, if you if you will. Yeah. In my 41 00:02:29,460 --> 00:02:32,900 experience so I used to work for Marriott Hotels, and I was on the marketing 42 00:02:32,900 --> 00:02:36,420 team. Marketing team feels, like, very, like, nerdy. We're in our 43 00:02:36,420 --> 00:02:39,885 offices. Sales team is always, like, suits, five star 44 00:02:39,945 --> 00:02:43,545 restaurants. Like, it always feels like a totally different vibe 45 00:02:43,545 --> 00:02:46,905 too just from the people who work at the different departments too. Has that been 46 00:02:46,905 --> 00:02:50,745 your experience as well? Yes. Definitely. I mean, you know, 47 00:02:50,745 --> 00:02:54,285 there are different types of salespeople. There are different types of marketers, but 48 00:02:54,580 --> 00:02:58,120 I don't think it's a coincidence that marketing as a discipline 49 00:02:58,260 --> 00:03:01,940 is taught at business schools while sales is less 50 00:03:01,940 --> 00:03:05,480 taught. Right? It's that's changing. But historically 51 00:03:05,620 --> 00:03:09,319 speaking, marketing has been a foundational topic 52 00:03:09,380 --> 00:03:13,155 for business. And so what that tells me is that marketing is 53 00:03:13,155 --> 00:03:16,694 thought of as an intellectual enterprise, right, where it's like 54 00:03:16,995 --> 00:03:20,674 strategy and what's the right message and what's the who's the 55 00:03:20,674 --> 00:03:24,135 ICP and all of that, and how do you articulate value, 56 00:03:25,170 --> 00:03:28,930 while sales is seen as execution. Right? Like, go out, meet the 57 00:03:28,930 --> 00:03:32,769 people, shake their hands, you know, articulate that value 58 00:03:32,769 --> 00:03:36,550 and try to get them closed. And so I think, naturally, it attracts 59 00:03:36,610 --> 00:03:40,215 different types of personalities, those that are 60 00:03:40,215 --> 00:03:43,655 analytical versus those that are more of, like, you know, just go out and 61 00:03:43,655 --> 00:03:47,415 do. And, yeah, I think that is also a a root of 62 00:03:47,415 --> 00:03:50,935 the conflict is that, you know, the marketers, I think, 63 00:03:50,935 --> 00:03:54,660 sometimes, you know, as as a sales guy 64 00:03:54,660 --> 00:03:58,280 myself, I could critique both sides, but I think oftentimes 65 00:03:58,420 --> 00:04:01,940 salespeople feel that marketers are are more kind of, 66 00:04:02,180 --> 00:04:06,020 like ivory tower kind of, like, theoretical when they 67 00:04:06,020 --> 00:04:06,510 just need, like, practical how to guides for, 68 00:04:11,915 --> 00:04:14,875 Yeah. A %. And I find that a lot of the people that I work 69 00:04:14,875 --> 00:04:18,475 with, especially the smaller businesses or maybe, like, the 70 00:04:18,475 --> 00:04:21,995 ownership of one businesses, you know, there's just one person wearing all of the 71 00:04:21,995 --> 00:04:25,800 hats, tend to lean more one way or the other. But they kind of 72 00:04:25,800 --> 00:04:29,640 go hand in hand. Like, you you need the marketing message to be able to, 73 00:04:29,640 --> 00:04:33,240 you know, really execute on the sales call, and you need the 74 00:04:33,240 --> 00:04:36,895 sales calls to then fuel the marketing. And one of the 75 00:04:36,895 --> 00:04:40,335 interesting things that you and I were talking about was these sales calls. 76 00:04:40,335 --> 00:04:43,955 So tell us what you're doing with sales calls and how that 77 00:04:44,255 --> 00:04:47,794 benefits marketing. Yeah. So, I mean, 78 00:04:48,014 --> 00:04:51,860 ever since the chat GPT moment of a 79 00:04:51,860 --> 00:04:55,540 few years ago when everyone was like, wow. These large language 80 00:04:55,540 --> 00:04:59,380 models are really working, and they're powerful. You 81 00:04:59,380 --> 00:05:03,015 know, I've been really excited about them because to 82 00:05:03,015 --> 00:05:06,695 me, you know, I I've been describing large 83 00:05:06,695 --> 00:05:10,535 language models as calculators for words. Right? For the 84 00:05:10,535 --> 00:05:14,235 first time, we're able to analyze words 85 00:05:14,375 --> 00:05:17,300 and meaning at scale. And so, 86 00:05:18,080 --> 00:05:21,600 you know, something that used to take, a long 87 00:05:21,600 --> 00:05:25,360 time, I e, you know, even if somebody recorded 88 00:05:25,360 --> 00:05:28,815 a phone call and you wanna listen to that call, you have to put 89 00:05:28,815 --> 00:05:32,574 aside almost as much time as the call itself to review it. 90 00:05:32,574 --> 00:05:35,854 Right? You can speed it up a little bit, but you can't speed it up 91 00:05:35,854 --> 00:05:39,215 too much, right, because you're gonna miss some of the details. Right? And 92 00:05:39,215 --> 00:05:42,035 so it's never actually been realistic 93 00:05:42,850 --> 00:05:46,690 to, analyze, you know, the large 94 00:05:46,690 --> 00:05:50,370 volume of text. But now with AI, it is. Right? And so 95 00:05:50,370 --> 00:05:53,970 one of the first things that I started using AI 96 00:05:53,970 --> 00:05:57,695 for was to analyze sales calls and, you know, 97 00:05:57,695 --> 00:06:01,215 initially started with individual calls, right, to 98 00:06:01,215 --> 00:06:04,735 help reinforce coaching and the methodology. So for 99 00:06:04,735 --> 00:06:08,250 example, if, if a company uses there's a common 100 00:06:08,550 --> 00:06:12,230 methodology called MEDDPIC for enterprise sales. It starts you 101 00:06:12,230 --> 00:06:15,910 know, stands for a lot of different things, but metrics, economic buyer, 102 00:06:15,910 --> 00:06:19,750 decision process, etcetera. And so, what if 103 00:06:19,750 --> 00:06:23,405 you want to, you know, reinforce that methodology, 104 00:06:24,425 --> 00:06:28,125 I can teach an AI chatbot what 105 00:06:28,585 --> 00:06:31,965 metrics mean, economic buyer means, decision process, 106 00:06:32,025 --> 00:06:35,870 etcetera, and then feed it dozens, hundreds of 107 00:06:35,870 --> 00:06:39,710 pages of calls and be like, what patterns are you seeing here? 108 00:06:39,710 --> 00:06:43,550 Right? And so for the individual rep, it's, you know, for this 109 00:06:43,550 --> 00:06:47,169 deal, how well qualified is this deal? Did you get the economic 110 00:06:47,229 --> 00:06:50,965 buyer? Did you talk to them about metrics? But then also 111 00:06:51,425 --> 00:06:55,185 on an aggregate across the entire team, you know, over the 112 00:06:55,185 --> 00:06:58,705 course of a quarter, over the course of you know, you could slice and dice 113 00:06:58,705 --> 00:07:02,545 them. All the win the deals that you won versus the deals that 114 00:07:02,545 --> 00:07:06,120 you lost or the the, certain, segments of your 115 00:07:06,120 --> 00:07:09,720 market and compare them to each other. Now we can analyze those 116 00:07:09,720 --> 00:07:13,479 transcripts and pull insights from them in a way that we couldn't before, and 117 00:07:13,479 --> 00:07:17,259 that just opens up a world of possibilities in both sales and marketing. 118 00:07:17,800 --> 00:07:21,395 Yeah. That like, I'm so obsessed with this idea because I just 119 00:07:21,395 --> 00:07:25,075 naturally record all of my sales calls anyways, and I use them a 120 00:07:25,075 --> 00:07:28,755 lot for my own kind of information just as you said. Going through it 121 00:07:28,755 --> 00:07:32,550 manually, I'll listen to it or I'll pull the transcripts, and I'll be like, oh, 122 00:07:32,629 --> 00:07:36,150 you know, here's something someone said that's a problem. So now I'm gonna put that 123 00:07:36,150 --> 00:07:39,190 on my sales page, or I'm gonna put it in a sales email. But the 124 00:07:39,190 --> 00:07:42,789 fact that you're taking this and then putting it into AI and going, 125 00:07:42,789 --> 00:07:46,495 okay, collectively out of, let's say, these 10 sales calls, 126 00:07:46,495 --> 00:07:49,474 what are the trends? I feel like this is one of the strongest 127 00:07:50,254 --> 00:07:53,794 uses that you can use with all of this information that we already have. 128 00:07:54,095 --> 00:07:57,820 Are you like, what tools are you using for this? I wanna be nosy. How 129 00:07:57,820 --> 00:08:01,280 how are you doing this? Yeah. I mean, look. I think 130 00:08:01,660 --> 00:08:05,120 so the first thing I always recommend to people 131 00:08:05,260 --> 00:08:08,940 is, as much as possible, use what are 132 00:08:08,940 --> 00:08:12,725 called the frontier models. Right? Like, the the ones that are the 133 00:08:12,725 --> 00:08:16,565 cutting edge. Right? And so that's ChatGPT and their 134 00:08:16,565 --> 00:08:20,405 various models. Claw is another one that I use a 135 00:08:20,405 --> 00:08:23,785 lot, and they have a great model or, series of models. 136 00:08:24,005 --> 00:08:27,650 Gemini from Google. You know, if you stay in those categories, 137 00:08:27,870 --> 00:08:31,330 you're you're gonna get the best of modern AI. 138 00:08:32,270 --> 00:08:35,890 And then specifically, though, which tool 139 00:08:36,270 --> 00:08:40,054 depends on the amount of text that you wanna analyze. So, you 140 00:08:40,054 --> 00:08:43,815 know, if I'm doing just one call or just a handful 141 00:08:43,815 --> 00:08:47,175 of calls, then, you know, any of them will do chat 142 00:08:47,175 --> 00:08:51,014 GPT, Gemini, or or Claude. But if you wanna do, 143 00:08:51,014 --> 00:08:54,555 like, large volumes, like hundreds of pages of calls, 144 00:08:55,170 --> 00:08:58,390 I lean more towards Gemini, and that's because Gemini 145 00:08:58,690 --> 00:09:02,530 has a a large context window. So think 146 00:09:02,530 --> 00:09:06,210 of the context window as, like, the bot short term 147 00:09:06,210 --> 00:09:09,990 memory. You know, there's like it's trained on the history of the Internet, 148 00:09:10,145 --> 00:09:13,445 but then you wanted to keep certain ideas in its mind, 149 00:09:13,825 --> 00:09:17,585 and those include the transcripts or whatever else you wanna use as 150 00:09:17,585 --> 00:09:21,345 part of the analysis. And so you need a context window 151 00:09:21,345 --> 00:09:24,385 that's large enough to handle that volume of calls. And, 152 00:09:24,785 --> 00:09:28,620 Gemini has, depending on which one you use, between a million 153 00:09:29,080 --> 00:09:32,760 tokens to 2,000,000 tokens of a context window, which is, I 154 00:09:32,760 --> 00:09:36,440 think, a few thousand pages of words. And 155 00:09:36,440 --> 00:09:40,120 there's a specific tool that is built off of Gemini that's 156 00:09:40,120 --> 00:09:43,925 actually free, and I love using for this use case called 157 00:09:43,925 --> 00:09:47,765 notebook l m. And so just Google notebook l m. 158 00:09:47,765 --> 00:09:51,225 One of the great things about notebook l m is that it allows you to, 159 00:09:51,285 --> 00:09:54,745 I think, upload a few hundred sources, and each one 160 00:09:55,100 --> 00:09:58,860 can be 50 pages or more long. And so 161 00:09:58,860 --> 00:10:02,460 you can really do a lot of, you know, put a lot of, 162 00:10:02,940 --> 00:10:06,620 you know, transcripts in there. And then the great thing about notebook l 163 00:10:06,620 --> 00:10:10,295 m also is that it provides you with citations. So if you're gonna 164 00:10:10,295 --> 00:10:13,815 make big strategic decisions about, oh, these are the pain 165 00:10:13,815 --> 00:10:17,575 points that are coming up in this call, and so therefore, I'm going 166 00:10:17,575 --> 00:10:21,175 to create marketing assets around that. You wanna make sure that, 167 00:10:21,895 --> 00:10:25,690 that, you know, you're basing it off of validated information. And so, 168 00:10:26,310 --> 00:10:30,070 yeah, I think, having those citations in NotebookLM is really 169 00:10:30,070 --> 00:10:33,670 helpful. Okay. I'm glad you mentioned that because one of my next questions was 170 00:10:33,670 --> 00:10:37,024 about this, like, hallucinating that AI does 171 00:10:37,024 --> 00:10:40,545 sometimes where you're like, oh, this sounds like it could be real, but then you 172 00:10:40,545 --> 00:10:43,585 try to go and find the information and it's it just made it up because 173 00:10:43,585 --> 00:10:46,225 it's a people pleaser. And I was trying to just, here, I think this is 174 00:10:46,225 --> 00:10:49,980 what you want. So I love that I literally put notebook l m in another 175 00:10:49,980 --> 00:10:53,660 tab because I'm like, I'm gonna look at this later because, I do 176 00:10:53,660 --> 00:10:57,279 think one of the challenges that we we face as this emerging 177 00:10:57,420 --> 00:11:00,895 technology is being developed is that sometimes, 178 00:11:00,895 --> 00:11:03,955 especially if we're feeding it hundreds of thousands of pages, 179 00:11:04,655 --> 00:11:08,415 we can't verify what it's spitting back out at us. So I like that 180 00:11:08,415 --> 00:11:11,775 you that you did that. Are there any other kind of 181 00:11:11,775 --> 00:11:15,600 downsides to using this strategy, using AI to kind of 182 00:11:15,600 --> 00:11:19,220 filter through and find voice of customer research, 183 00:11:19,760 --> 00:11:22,740 using, largely language models? Downsides? 184 00:11:24,800 --> 00:11:28,295 I think it's hard to think of what the downsides 185 00:11:28,515 --> 00:11:32,115 would be. So, you know, hallucinations, yes, for sure. Right? 186 00:11:32,595 --> 00:11:36,195 But they're getting better and better at this, and I would argue 187 00:11:36,195 --> 00:11:39,875 that you'd never wanna fully substitute your judgment to the 188 00:11:39,875 --> 00:11:43,699 tools. Like, they're, you know, I like to think about them as, like, an 189 00:11:43,699 --> 00:11:47,459 over eager but very inexperienced intern. Right? 190 00:11:47,459 --> 00:11:51,220 Very smart, but, you know, you need to check their work. You 191 00:11:51,220 --> 00:11:54,899 wouldn't take an intern's paper and just hand it to a client. Right? You would 192 00:11:54,899 --> 00:11:58,495 review it. You would give them feedback, right, and iterate on it 193 00:11:58,495 --> 00:12:02,335 until it gets to a good place. And I think it's the same obligation with 194 00:12:02,335 --> 00:12:05,855 AI to double check the work before it goes out, especially if you're gonna make 195 00:12:05,855 --> 00:12:09,455 big strategic decisions based off of it. But 196 00:12:09,455 --> 00:12:11,615 besides hallucinations, you know 197 00:12:13,190 --> 00:12:17,029 yeah, I mean, I I don't know. What is the downside of having more insight 198 00:12:17,029 --> 00:12:20,250 into your customers? Right? What is the downside of understanding 199 00:12:20,950 --> 00:12:24,730 directly from their mouths how they describe your pain points, what objections 200 00:12:24,870 --> 00:12:28,665 they have, what competitors they're seeing, what their buying criteria 201 00:12:28,725 --> 00:12:32,105 is. To me, like, this is less about 202 00:12:32,485 --> 00:12:35,845 something new that is risky and more 203 00:12:35,845 --> 00:12:39,685 about, democratizing something that 204 00:12:39,685 --> 00:12:43,260 already exists in the world, but now can be done at 205 00:12:43,260 --> 00:12:47,020 scale and a lot more cheaply. You know, I'm I I'm thinking of a 206 00:12:47,020 --> 00:12:50,620 client of mine, who was one of the first people that I 207 00:12:50,620 --> 00:12:54,334 did this voice of the customer analysis with. They, 208 00:12:54,555 --> 00:12:57,995 prior to working with me, had engaged the consulting firm that they 209 00:12:57,995 --> 00:13:01,115 paid a few hundred thousand dollars. I wanna say, like, 210 00:13:01,115 --> 00:13:04,814 $300,000 to do a market study for them. And so 211 00:13:04,954 --> 00:13:08,310 they, like, went out there, did a bunch of interviews, you know, 212 00:13:08,550 --> 00:13:11,930 panels, this and that, and they came up with this very 213 00:13:11,990 --> 00:13:15,830 elaborate presentation that my client then shared with me. And 214 00:13:15,830 --> 00:13:19,610 so when I did the voice of the customer research, I was like, 215 00:13:20,230 --> 00:13:23,945 I I just uploaded the, the report from this consulting 216 00:13:23,945 --> 00:13:27,625 firm and was like, what's accurate? What's inaccurate? What did they get 217 00:13:27,625 --> 00:13:30,825 right? What didn't they get right? And there was a good amount of things that 218 00:13:30,825 --> 00:13:34,570 they didn't get right. And I don't think that this is a 219 00:13:34,570 --> 00:13:37,950 bad firm in any way. I think markets 220 00:13:38,010 --> 00:13:41,690 change. Right? And there's a difference between, hey. Let me go and hire 221 00:13:41,690 --> 00:13:45,290 somebody to do a focus group to go back in hindsight and 222 00:13:45,290 --> 00:13:49,005 explain what matters to them, their buying criteria, things like that, 223 00:13:49,165 --> 00:13:52,225 versus directly out of the mouths of this of the 224 00:13:52,605 --> 00:13:56,365 prospects themselves on the sales calls. You know you know, 225 00:13:56,365 --> 00:14:00,205 I I think the the real value here is, you know, 226 00:14:00,205 --> 00:14:03,565 regular marketer, you know, and even in a small 227 00:14:03,565 --> 00:14:07,400 company using a tool like NotebookLM, if they're recording 228 00:14:07,400 --> 00:14:11,240 their calls, can get do a win loss analysis, voice of the 229 00:14:11,240 --> 00:14:15,080 customer analysis on a dime, get the value of that 230 00:14:15,080 --> 00:14:18,835 without having to pay tens of thousands, if not hundreds of thousands 231 00:14:18,835 --> 00:14:22,355 for a consultant to come and do that. You know, it's that's 232 00:14:22,355 --> 00:14:26,035 probably prohibitive for most small companies, but now you can do it 233 00:14:26,035 --> 00:14:29,795 with, you know, notebookLM for free or for some of 234 00:14:29,795 --> 00:14:33,550 these tools, like, $20 a month. You know? Yeah. I mean, I can't even 235 00:14:33,550 --> 00:14:37,090 imagine how long that report took to put together. Like 236 00:14:37,310 --> 00:14:41,070 like, it months, if not a year, to, like, build 237 00:14:41,070 --> 00:14:44,830 out that report and, like, even just the shortened timeline too to be able to 238 00:14:44,830 --> 00:14:48,565 get this information. One of the things you said was interesting was, 239 00:14:49,425 --> 00:14:53,025 how you prompted AI to give you the 240 00:14:53,025 --> 00:14:56,785 results that you want. And I think this is also a skill that 241 00:14:56,785 --> 00:15:00,540 we have to learn as marketers, as salespeople, is, like, we the the 242 00:15:00,540 --> 00:15:03,680 language models are learning us, but we're also learning them. 243 00:15:04,220 --> 00:15:07,980 And so you you said something specific, which was, tell me what they got 244 00:15:07,980 --> 00:15:11,820 wrong, but tell me where they also missed the mark. What are some of 245 00:15:11,820 --> 00:15:15,555 the what are some of the prompts that you use to make sure that 246 00:15:15,775 --> 00:15:19,135 AI language models are giving you the results that you 247 00:15:19,135 --> 00:15:22,355 need? Yeah. I mean, I find that 248 00:15:22,975 --> 00:15:26,495 the more constraints you give these models, the better results you 249 00:15:26,495 --> 00:15:30,290 actually get. So they're getting a lot better at following 250 00:15:30,290 --> 00:15:33,510 instructions. And so 251 00:15:34,050 --> 00:15:37,810 being prescriptive and saying, a, this 252 00:15:37,810 --> 00:15:40,390 is your objective. That's always required. 253 00:15:41,475 --> 00:15:45,155 If it's important to specify the steps in 254 00:15:45,155 --> 00:15:48,675 its reasoning, that is also really 255 00:15:48,675 --> 00:15:52,295 helpful. Giving it the right 256 00:15:52,355 --> 00:15:55,840 context. Right? Meaning, like, here's 257 00:15:55,980 --> 00:15:59,120 my buyer persona document. Here is, 258 00:16:00,220 --> 00:16:03,920 a PDF of my website that describes my products and services. 259 00:16:03,980 --> 00:16:07,660 Here's a one pager. Right? Here's something that describes our 260 00:16:07,660 --> 00:16:11,475 sales process. Whatever it is, that helps it give you better 261 00:16:11,475 --> 00:16:14,995 responses. And then you and so in the prompt telling it, 262 00:16:14,995 --> 00:16:18,675 like, you know, draw on this document for that reason. Draw 263 00:16:18,675 --> 00:16:22,295 on that document for another reason. That level of specificity 264 00:16:22,595 --> 00:16:26,400 helps. And then finally, I I think it's really useful to tell it 265 00:16:26,400 --> 00:16:30,160 the format that you want the output in. You know, I I like to 266 00:16:30,160 --> 00:16:33,540 think of it as, like, something that's writing me a report. 267 00:16:33,920 --> 00:16:37,700 Right? And so if it's for a sales call, right, to specify, 268 00:16:38,365 --> 00:16:41,805 you know, in the start with a 200 word summary of the 269 00:16:41,805 --> 00:16:45,245 call. Then, you know, give me an assessment of the 270 00:16:45,245 --> 00:16:48,545 prospect sentiment at the end of the call and throughout. 271 00:16:48,765 --> 00:16:52,470 Then identify the red flags. Then give me some 272 00:16:52,470 --> 00:16:56,070 coaching on how to improve, this call. 273 00:16:56,070 --> 00:16:59,690 Right? You know, and what questions that I missed that I didn't ask. 274 00:16:59,750 --> 00:17:03,350 And so being very thoughtful about what is the 275 00:17:03,350 --> 00:17:07,075 content of the output is really important. Yeah. And, 276 00:17:07,075 --> 00:17:10,775 you know, there's a lot of stuff out there about prompting and best practices. 277 00:17:10,915 --> 00:17:14,455 I do think that guidance works. And, 278 00:17:15,075 --> 00:17:18,435 yeah, again, the more constraints you put, the 279 00:17:18,435 --> 00:17:22,069 better you are. You know, sometimes when I some of 280 00:17:22,069 --> 00:17:25,750 these prompts, I'm using, like, you know, two, three 281 00:17:25,750 --> 00:17:29,110 page long prompts, right, because it's very 282 00:17:29,110 --> 00:17:32,825 detailed, and that I found gets the best 283 00:17:32,825 --> 00:17:36,585 out of it. Yeah. I find that when I'm talking to 284 00:17:36,585 --> 00:17:40,185 people about AI, especially people who are not 285 00:17:40,185 --> 00:17:44,025 convinced that it's helpful, usually after pulling back the layers, it's like 286 00:17:44,025 --> 00:17:47,490 they asked it two questions and they were like, oh, this is terrible. And I'm 287 00:17:47,490 --> 00:17:50,610 like, woah, woah, woah. Like, we need to get more specific here and I love 288 00:17:50,610 --> 00:17:54,450 that you've done, like, two to three page Yes. Prompts to get 289 00:17:54,450 --> 00:17:58,130 what you need. Okay. So that's that's using the the sales call 290 00:17:58,130 --> 00:18:01,855 itself, creating voice of customer marketing. One of the other things that we've 291 00:18:01,855 --> 00:18:05,615 talked about as well is, like, what to do before the sales call. So 292 00:18:05,615 --> 00:18:08,815 using some of your marketing to help before the sales call. Talk to us about 293 00:18:08,815 --> 00:18:12,655 that. Yeah. To me, this is this is another game changer in the 294 00:18:12,655 --> 00:18:16,430 relationship between marketing and sales. You know, in my career, 295 00:18:16,730 --> 00:18:20,490 one of the most common, contentious points between 296 00:18:20,490 --> 00:18:24,090 marketing and sales is marketing believing that sales is not 297 00:18:24,090 --> 00:18:27,610 using all of the marketing materials that they've created. Right? You 298 00:18:27,610 --> 00:18:31,345 know? You've created case studies. You've created, you know, 299 00:18:31,345 --> 00:18:34,884 certain customer stories or one pagers 300 00:18:35,184 --> 00:18:38,644 or messaging guides. Right? And 301 00:18:39,024 --> 00:18:42,480 too often, that stuff gets in a shelf 302 00:18:42,480 --> 00:18:46,240 somewhere. You know? Nobody is using it. And so 303 00:18:46,240 --> 00:18:50,000 to address that issue, one of the things, like, bots that 304 00:18:50,000 --> 00:18:53,760 I built for my clients are, bots that help them, 305 00:18:54,160 --> 00:18:57,995 sales rep prepare for calls. And so imagine a 306 00:18:57,995 --> 00:19:01,434 sales rep is about to get on a call with a particular prospect. They can 307 00:19:01,434 --> 00:19:05,115 go to LinkedIn, download that person's LinkedIn profile, maybe 308 00:19:05,115 --> 00:19:08,875 use a tool like Perplexity to do some quick research on, you 309 00:19:08,875 --> 00:19:12,720 know, that businesses and, their priority. And 310 00:19:12,720 --> 00:19:16,400 then, you know, upload those into a bot 311 00:19:16,400 --> 00:19:20,020 that I built that helps them identify what's the most relevant 312 00:19:20,320 --> 00:19:24,080 points, to hit on with the person you're about to speak to. 313 00:19:24,080 --> 00:19:27,915 It gives them questions to ask, discovery questions to get them to 314 00:19:27,915 --> 00:19:31,515 open up. And then importantly, it also recommends to 315 00:19:31,515 --> 00:19:35,355 them assets and resources that may be 316 00:19:35,355 --> 00:19:39,195 available that is most relevant to that persona. And 317 00:19:39,195 --> 00:19:42,899 so simple use case, if I'm about to get on the 318 00:19:42,899 --> 00:19:46,659 phone with the CFO, it's, you know, it's a late of late stages of a 319 00:19:46,659 --> 00:19:50,340 sales process where, you know, I know that the CFO just 320 00:19:50,340 --> 00:19:54,179 cares about the bottom line impact. Right? Not how's it gonna help, you 321 00:19:54,179 --> 00:19:57,885 know, Peggy Sue would be 5% better at her job. They care about how does 322 00:19:57,885 --> 00:20:01,485 that impact revenues, etcetera. And so 323 00:20:01,485 --> 00:20:05,025 the talk track, the value statement has to be a little bit different. 324 00:20:05,165 --> 00:20:08,625 And so what if you had a case study of 325 00:20:09,100 --> 00:20:12,940 that was focused on a a CFO as a hero, right, that was 326 00:20:12,940 --> 00:20:16,700 able to articulate the value that that CFO got? Or if 327 00:20:16,700 --> 00:20:20,220 it's some sort of messaging guide that marketing has come up that says, these are 328 00:20:20,220 --> 00:20:23,715 the notes to hit when you're talking to a CFO, I can then, 329 00:20:24,254 --> 00:20:27,855 you know, serve that to the salesperson at the right 330 00:20:27,855 --> 00:20:31,534 time right when they need it. They don't need to go searching through 331 00:20:31,534 --> 00:20:35,375 their materials to go and find this stuff, which they don't do anyway. 332 00:20:35,375 --> 00:20:38,450 Right? And so, you know, being able to give it to them at the right 333 00:20:38,450 --> 00:20:41,570 time makes it much more likely that they're gonna use it, which makes it much 334 00:20:41,570 --> 00:20:45,269 more likely that they'll get the benefit of all that hard work that the marketers 335 00:20:45,409 --> 00:20:49,090 have put in to identify that right messaging. So, yeah, that's 336 00:20:49,090 --> 00:20:52,625 another powerful use case that I that's driving a lot of, 337 00:20:52,945 --> 00:20:56,705 you know, value with clients. Yeah. This, again, feels like 338 00:20:56,705 --> 00:21:00,065 just, like, paying attention at scale because I do find that 339 00:21:00,465 --> 00:21:04,140 so anytime I'm on a call and someone notices something I like, 340 00:21:04,400 --> 00:21:08,046 a social media post that I posted recently or email I shared recently, I'm 341 00:21:08,046 --> 00:21:11,693 always like, oh, okay. They're paying attention. And so I can imagine someone coming 342 00:21:11,693 --> 00:21:15,079 into a call, trying to pitch me on whatever, and they just know 343 00:21:15,339 --> 00:21:18,945 they're, like, hitting all the right notes. They know all the details. And if I 344 00:21:18,945 --> 00:21:21,904 found out that they were using AI to do this, I would be even more 345 00:21:21,904 --> 00:21:25,745 impressed. Mhmm. Because I feel like there's this, it 346 00:21:25,825 --> 00:21:29,345 like you said, it's the calculator effect. I feel like there's this 347 00:21:29,345 --> 00:21:32,645 almost, like, glamorization of, 348 00:21:33,350 --> 00:21:37,190 like, not doing this. Or I feel like some people are like, oh, we 349 00:21:37,190 --> 00:21:40,710 want it to be natural and instinct and, like, this person just cares that 350 00:21:40,710 --> 00:21:44,470 deeply. And I also feel like there's a 351 00:21:44,470 --> 00:21:47,910 power in using the tools that we have available to us to, like, make 352 00:21:47,910 --> 00:21:51,385 the the best impression. I don't know. What do you think about that dichotomy of, 353 00:21:51,385 --> 00:21:55,005 like, is this cheating? No. It's definitely not cheating. 354 00:21:55,145 --> 00:21:58,765 First of all, I remember the for that particular 355 00:21:59,065 --> 00:22:02,870 tool that I built, the first time I did it, 356 00:22:02,870 --> 00:22:06,010 it was, to help, BDRs, 357 00:22:06,390 --> 00:22:10,070 SDRs who are making cold calls to figure out what's the right 358 00:22:10,070 --> 00:22:13,429 message before they reach out to the person. Right? And 359 00:22:13,429 --> 00:22:16,804 so these were folks who just graduated from 360 00:22:16,804 --> 00:22:20,345 college. Right? They were ramping up in their new job. 361 00:22:20,804 --> 00:22:24,585 And in that particular case, they had a pretty complex product to sell, 362 00:22:24,885 --> 00:22:28,585 and they were selling it to, like, electrical engineers. Right? And so 363 00:22:28,669 --> 00:22:32,270 it was the kind of thing where if you aren't at their 364 00:22:32,270 --> 00:22:36,029 level, if you don't hit the right notes with these engineers, and, like, they're 365 00:22:36,029 --> 00:22:39,490 just gonna hang up on you. And so this one of the value 366 00:22:39,710 --> 00:22:43,065 of that tool was to accelerate their ramp time. Right? 367 00:22:43,065 --> 00:22:46,905 Just read the script that the bot gives you, and over time, 368 00:22:46,905 --> 00:22:50,745 you'll be able to connect the dot between this persona and their pain 369 00:22:50,745 --> 00:22:54,585 points and the right value articulation. But until then, this tool 370 00:22:54,585 --> 00:22:58,400 is gonna get you pretty far. So I don't 371 00:22:58,400 --> 00:23:02,080 think that's cheating. I think that's, like, you know, helping to 372 00:23:02,080 --> 00:23:05,840 accelerate productivity and get them, you know, as productive 373 00:23:05,840 --> 00:23:09,360 as possible. And, you know, there is this I have encountered this 374 00:23:09,360 --> 00:23:13,154 idea of, like that some people have of, if they use AI, 375 00:23:13,154 --> 00:23:16,695 they're not gonna learn the right skills or 376 00:23:17,075 --> 00:23:20,835 it's almost feels like people who had, like, a rough childhood or 377 00:23:20,835 --> 00:23:24,515 something, they're like, oh, like, everybody has to suffer because I 378 00:23:24,515 --> 00:23:28,170 suffered. Yeah. But, no, we're not this isn't a game. This is 379 00:23:28,170 --> 00:23:31,870 about revenue and productivity and helping 380 00:23:31,930 --> 00:23:35,770 salespeople, be as effective as possible. And so if 381 00:23:35,770 --> 00:23:39,210 you're not using these tools, your competitors are gonna be using these 382 00:23:39,210 --> 00:23:42,745 tools. And I feel, you know, we're still in the early 383 00:23:42,745 --> 00:23:46,525 stages of this stuff getting out there, but I in the not too distant future, 384 00:23:46,745 --> 00:23:50,265 I see a world where customers are gonna expect you to 385 00:23:50,265 --> 00:23:53,885 have deep knowledge of them, to come into meetings 386 00:23:53,945 --> 00:23:57,680 with a unique point of view based on what you know about them because 387 00:23:57,680 --> 00:24:01,440 it's gonna be table stakes to be able to do that level of research. And 388 00:24:01,440 --> 00:24:04,880 so if you're gonna be like, you know, I'm gonna do this the whole way 389 00:24:04,880 --> 00:24:08,240 and your competitor who they're also talking to is much more 390 00:24:08,240 --> 00:24:11,655 thoughtful, is much more, targeted in their 391 00:24:11,655 --> 00:24:15,495 messaging, in their approach, much more aligned with the needs of the 392 00:24:15,495 --> 00:24:18,475 customer, you're just gonna lose. Right? And so, 393 00:24:19,174 --> 00:24:22,475 yeah, it's to me, we're very closely 394 00:24:22,535 --> 00:24:25,820 approaching a world where it will be a competitive 395 00:24:26,120 --> 00:24:29,179 disadvantage to not use these tools 396 00:24:29,559 --> 00:24:33,400 because your competitors are gonna use it, and they're gonna deliver a better 397 00:24:33,400 --> 00:24:37,160 customer experience. Yeah. Yeah. I I think it's gonna be 398 00:24:37,160 --> 00:24:40,905 interesting to see what shapes the next five to ten years because I think we're 399 00:24:40,905 --> 00:24:44,745 at we're at an inflection point with this. And it's it's here. Like, AI is 400 00:24:44,745 --> 00:24:48,424 here to stay. It's not going anywhere. It's how we all use it as the 401 00:24:48,424 --> 00:24:52,184 tools that we, can to our benefits and and actually 402 00:24:52,184 --> 00:24:55,620 help us grow our business with by leaps and bounds. It really does remind me 403 00:24:55,620 --> 00:24:59,380 of when social media first started too, and people were like, oh, I don't 404 00:24:59,380 --> 00:25:03,220 need this. It's, you know, it's just the kids played around online. Yes. And now 405 00:25:03,220 --> 00:25:06,820 as a business, you can't imagine not having some sort of 406 00:25:06,820 --> 00:25:10,054 marketing present digital marketing footprint. Right? And so, 407 00:25:10,434 --> 00:25:14,034 yeah, the future is here. The future is here. Okay. So we've talked about 408 00:25:14,034 --> 00:25:17,875 using AI, like, using the actual sales calls. We've talked about preparing for 409 00:25:17,875 --> 00:25:21,635 the sales calls. What about after the sales calls? I 410 00:25:21,635 --> 00:25:25,410 know you have a strategy around using AI to build, like, landing 411 00:25:25,410 --> 00:25:28,770 pages and marketing content things like that. Tell us about Yeah. 412 00:25:28,770 --> 00:25:32,450 So AI has a lot of different uses and 413 00:25:32,450 --> 00:25:36,210 means a lot of different things at different contexts. You know, there 414 00:25:36,210 --> 00:25:40,045 are presentation tools. Like, I use one 415 00:25:40,045 --> 00:25:43,265 called gamma that can create 416 00:25:43,885 --> 00:25:46,305 landing pages in an instant. 417 00:25:47,965 --> 00:25:51,725 And they're now these AI coding tools that actually could create much 418 00:25:51,725 --> 00:25:55,330 more sophisticated landing pages in an instant 419 00:25:55,790 --> 00:25:59,490 well designed. And then content creation 420 00:26:00,270 --> 00:26:04,030 is so much easier now, right, to be able to go and 421 00:26:04,030 --> 00:26:07,475 do some research on a company and then, you know, 422 00:26:07,615 --> 00:26:10,435 have, like, a piece of content that you've written before 423 00:26:10,975 --> 00:26:14,355 and upload both to AI and be like, can you rewrite 424 00:26:14,495 --> 00:26:17,795 this in a version that's gonna be most appealing to this particular 425 00:26:18,470 --> 00:26:21,530 customer with this particular research. 426 00:26:22,470 --> 00:26:26,010 The combination of the research, the ability to create unique 427 00:26:26,070 --> 00:26:29,590 content or landing pages on demand, again, tells me 428 00:26:29,590 --> 00:26:33,075 that marketers, salespeople can 429 00:26:33,075 --> 00:26:36,835 build those assets into their, for example, account based lead 430 00:26:36,835 --> 00:26:40,375 generation. Right? If you're going after some targeted enterprise 431 00:26:40,434 --> 00:26:43,955 accounts, you're trying to close six figures, seven figure deals with 432 00:26:43,955 --> 00:26:47,800 them, they're gonna expect you to really understand their business, and 433 00:26:47,800 --> 00:26:51,400 you're gonna have to develop relationships with lots of different 434 00:26:51,400 --> 00:26:55,160 stakeholders. And so if we can create a landing page, 435 00:26:55,160 --> 00:26:58,520 for example, for lead generation that is tailored to 436 00:26:58,520 --> 00:27:02,360 that, particular customer, why JPMorgan Chase 437 00:27:02,360 --> 00:27:06,115 can save $7,000,000 by adopting this new way 438 00:27:06,115 --> 00:27:09,495 of doing things. Right? You know? And it'll be a personalized 439 00:27:09,634 --> 00:27:13,315 one. If you wanna write a a white paper that's just for 440 00:27:13,315 --> 00:27:16,995 them that takes into account their research. Right? Things 441 00:27:16,995 --> 00:27:20,720 that used to take weeks and a team of dedicated 442 00:27:21,340 --> 00:27:24,940 writers and designers, these are things that can be 443 00:27:24,940 --> 00:27:28,380 done instantaneously with AI. And 444 00:27:28,380 --> 00:27:31,760 so, yeah, that's another really powerful use case is 445 00:27:32,365 --> 00:27:35,904 creating that personalized content at scale, that personalized 446 00:27:36,125 --> 00:27:39,804 buying experience at scale, and really 447 00:27:39,804 --> 00:27:43,245 making the customer feel like, you know, you 448 00:27:43,245 --> 00:27:46,225 are crafting something that's unique for them, 449 00:27:47,070 --> 00:27:50,590 whether that's at the top of the funnel or during the sales 450 00:27:50,590 --> 00:27:54,429 process. You know, for example, I one of the uses of 451 00:27:54,429 --> 00:27:57,870 AI, that I with with clients is is 452 00:27:57,870 --> 00:28:01,605 ROI analysis, like coming up with customized tools to 453 00:28:01,605 --> 00:28:05,285 do an ROI analysis that, you know, basically, the 454 00:28:05,285 --> 00:28:08,805 rep just has to ask a few questions, upload it, their 455 00:28:08,805 --> 00:28:12,345 transcript, and then it'll do put together, like, this customized 456 00:28:12,405 --> 00:28:16,029 report that looks beautiful. Right? That used to be a very expensive 457 00:28:16,029 --> 00:28:19,389 thing for businesses to build on their own, you know, with 458 00:28:19,389 --> 00:28:22,909 software, especially. But now with AI, with a lot of this AI 459 00:28:22,909 --> 00:28:26,529 software development tools, you can build those customized ROI 460 00:28:27,070 --> 00:28:30,555 calculators, etcetera, on a dime. And so, again, 461 00:28:31,095 --> 00:28:34,715 it's what can what do these tools make possible 462 00:28:34,935 --> 00:28:38,315 today that we can insert into our existing 463 00:28:38,535 --> 00:28:42,295 processes or do things that we wish we could have done 464 00:28:42,295 --> 00:28:46,010 in the past, but we're prohibited by time, by effort, by 465 00:28:46,010 --> 00:28:49,770 resources. Now we can do those things on demand at 466 00:28:49,770 --> 00:28:53,310 scale in a much more custom way. And sales, 467 00:28:53,450 --> 00:28:56,670 marketing, we are in a world where our 468 00:28:56,970 --> 00:29:00,615 initiatives should produce revenue. Right? We can 469 00:29:00,615 --> 00:29:04,375 directly connect what we do to revenue. And so if 470 00:29:04,375 --> 00:29:07,815 you have a broken process, if you're unsatisfied with your 471 00:29:07,815 --> 00:29:11,575 conversion rates on this or that, I bet you personalization can help 472 00:29:11,575 --> 00:29:14,820 a little bit more. And so we can measure what's the baseline 473 00:29:15,280 --> 00:29:19,120 of, you know, engagement, qualified opportunities, whatever it it 474 00:29:19,120 --> 00:29:22,720 is, then we insert these tools in, and then we measure, are they 475 00:29:22,720 --> 00:29:26,455 moving the needle? And the ones that tend to move the 476 00:29:26,455 --> 00:29:30,215 needles are the ones that are about how do we personalize this, how 477 00:29:30,215 --> 00:29:33,735 do we engage customers in a new way that makes that 478 00:29:33,735 --> 00:29:37,495 educates them. Those are the types of things that I I see really 479 00:29:37,495 --> 00:29:41,270 moving the needle. So yeah. Yeah. Oh my gosh. I think this is so 480 00:29:41,270 --> 00:29:45,110 fascinating because, for a while, especially in my space, in 481 00:29:45,110 --> 00:29:48,950 the marketing spaces, this idea of scaling was 482 00:29:48,950 --> 00:29:52,390 was it. Right? It's like everyone wants to do more. They wanna do bigger. But 483 00:29:52,390 --> 00:29:55,575 the problem with scaling is you do lose the personalization. 484 00:29:56,355 --> 00:30:00,115 Right? Like, there's some of that that gets lost along the way. But then 485 00:30:00,115 --> 00:30:03,715 when we add back in AI, we can scale and we can have 486 00:30:03,715 --> 00:30:07,475 personalization at mass Yeah. When we kind of combine these tools 487 00:30:07,475 --> 00:30:11,270 together, which I find so fascinating and interesting. And 488 00:30:11,270 --> 00:30:14,870 again, I'm curious to see how this plays out in the future 489 00:30:14,870 --> 00:30:18,710 as as more tools get developed, as things happen. Because I 490 00:30:18,710 --> 00:30:22,315 know it can happen even better. Like, I think about companies like 491 00:30:22,315 --> 00:30:25,915 Amazon, for instance. They have so much information on me because I buy so much 492 00:30:25,915 --> 00:30:29,755 stuff on there. But I feel like they could they could really take AI and 493 00:30:29,755 --> 00:30:33,435 start, like, personalizing that whole experience. Like, they already 494 00:30:33,435 --> 00:30:36,870 have some things like reminders to buy, but I feel like there's so much more 495 00:30:36,870 --> 00:30:40,309 they could do. It'd be like, hey, Andrea. I know you're thinking about this, but 496 00:30:40,309 --> 00:30:43,190 have you thought about this? Or here's another option we know you'll like. Like, I 497 00:30:43,190 --> 00:30:46,789 would give them all my money. Yes. Yes. Yes. I I I don't we don't 498 00:30:46,870 --> 00:30:50,549 I don't wanna, like, open up an all other line of, conversation here, 499 00:30:50,549 --> 00:30:54,394 but, I went recently to a an event with a 500 00:30:54,394 --> 00:30:57,455 company in New York that does, video. 501 00:30:58,394 --> 00:31:01,755 They've they've been big in the video space. They compete with, like, 502 00:31:01,755 --> 00:31:05,480 Loom, etcetera. And so, they 503 00:31:05,480 --> 00:31:08,540 just launched an AI avatar solution 504 00:31:09,160 --> 00:31:12,600 that basically a sales manager, you know, asked their 505 00:31:12,600 --> 00:31:16,280 reps to shoot a ninety second video of themselves, and then it 506 00:31:16,280 --> 00:31:19,720 creates this avatar that the sales manager can put 507 00:31:19,720 --> 00:31:23,485 in, like, any script into the mouth of this avatar and 508 00:31:23,485 --> 00:31:27,005 then send it out on triggered plays. And so in their 509 00:31:27,005 --> 00:31:30,605 presentation, the one of the use cases that they use 510 00:31:30,605 --> 00:31:34,445 was, like, confirming an appointment the morning 511 00:31:34,445 --> 00:31:37,820 of. Right? And so the the manager doesn't need 512 00:31:37,820 --> 00:31:41,420 to tell the sales rep, oh, every single time you have an appointment in the 513 00:31:41,420 --> 00:31:45,100 morning, shoot me, like, a thirty second video where you say, 514 00:31:45,100 --> 00:31:48,240 hi, Andrea. Looking forward to meeting you this afternoon. 515 00:31:49,175 --> 00:31:51,895 We're gonna talk about this in the agenda. Let me know if you have any 516 00:31:51,895 --> 00:31:55,735 questions ahead of time, but I'll see you at 04:30. Right? Something like as 517 00:31:55,735 --> 00:31:59,175 simple as that, it's so hard to do at 518 00:31:59,175 --> 00:32:03,015 scale, so hard to do personalized. Maybe you do a generic one that you send 519 00:32:03,015 --> 00:32:06,770 to everyone, but not one that's personalized. But now it's just, like, 520 00:32:06,909 --> 00:32:10,669 submit, like, you know, you substitute the name. Hi, 521 00:32:10,669 --> 00:32:14,510 blank. Right? I'm looking forward to seeing you at blank, and it looks 522 00:32:14,510 --> 00:32:18,154 like it came right from your, you know, SDR 523 00:32:18,215 --> 00:32:21,894 or your salesperson, and they don't even have to think about it. It's just triggered 524 00:32:21,894 --> 00:32:25,654 on meeting on the calendar with a new lead this 525 00:32:25,654 --> 00:32:29,414 afternoon. This automated video goes out to them. 526 00:32:29,414 --> 00:32:32,900 Like, that to me is just another example of personalization 527 00:32:33,520 --> 00:32:36,900 at scale made possible by these powerful 528 00:32:36,960 --> 00:32:40,740 tools. Yeah. The future is gonna look very different from the past. 529 00:32:41,040 --> 00:32:44,560 Yeah. Okay. I do have a lot of thoughts about the AI video, though, 530 00:32:44,560 --> 00:32:48,235 because I know. I know. I don't know. I that's the one where I'm like, 531 00:32:48,235 --> 00:32:52,075 oh. So, like, I use Riverside to record my podcast. They have this built in 532 00:32:52,075 --> 00:32:55,835 now where you because I've done so many on here, they 533 00:32:55,835 --> 00:32:59,434 have all of me saying all of the things. And I can put make 534 00:32:59,434 --> 00:33:03,169 myself say anything. And it's like 90%. I'm like, oh, that does sound kinda 535 00:33:03,169 --> 00:33:05,970 like me. There's some words that are off. I don't know how I feel about 536 00:33:05,970 --> 00:33:09,730 it, though. I feel like there's this trust issue too 537 00:33:09,730 --> 00:33:12,710 with the AI avatar. I feel like we'd have to be very 538 00:33:13,605 --> 00:33:17,365 transparent, and I feel like this is where we're still figuring it out as, like, 539 00:33:17,365 --> 00:33:21,205 the humans behind the machines on how transparent can we be 540 00:33:21,205 --> 00:33:24,965 with this process. Like, hey. This is Andrea's avatar, or this 541 00:33:24,965 --> 00:33:28,640 is this is the the clone. I don't know. I Yeah. 542 00:33:28,640 --> 00:33:31,760 Anyways, that is a that is a whole other question. I I I think it 543 00:33:31,760 --> 00:33:35,380 depends on the use case. Right? So, like, if it's top of the funnel, 544 00:33:36,080 --> 00:33:39,520 you know, prospecting at scale, if it's this kind of meeting 545 00:33:39,520 --> 00:33:42,985 confirmation use case, these are low stakes kind of 546 00:33:42,985 --> 00:33:46,345 things that, you know, even if they're not perfect, 547 00:33:46,345 --> 00:33:49,385 like, you're reaching out to a lot of people, you're gonna have a really low 548 00:33:49,385 --> 00:33:52,985 response rate anyway. So, you know, it's about how do we optimize that 549 00:33:52,985 --> 00:33:56,440 response rate. Yeah. And I I agree with you. Like, there's 550 00:33:56,500 --> 00:34:00,200 definitely more that can be done to make them feel more natural. 551 00:34:00,259 --> 00:34:04,019 Maybe there's, could be more disclosure about 552 00:34:04,019 --> 00:34:07,320 when they're being used. But, again, I come down to the practical 553 00:34:07,460 --> 00:34:10,145 reality. Like, if this thing can, 554 00:34:11,405 --> 00:34:14,785 make it less likely that the meeting cancels, 555 00:34:15,485 --> 00:34:18,844 right, which makes it more likely that you add another 556 00:34:18,844 --> 00:34:22,670 opportunity into your pipeline, right, which then closes 557 00:34:22,670 --> 00:34:26,510 at your typical win rate, then it's really the question is, does this 558 00:34:26,510 --> 00:34:29,409 thing work? Right? Can it Yeah. Actually drive these results? 559 00:34:29,869 --> 00:34:33,710 And if it does, then I think we have to 560 00:34:33,710 --> 00:34:37,255 seriously consider it and overcome some of these resistance. 561 00:34:37,475 --> 00:34:41,075 And also keep in mind, like, these things are only gonna get better 562 00:34:41,075 --> 00:34:44,595 from here on out. Right? Like, they're gonna become more realistic. And 563 00:34:44,595 --> 00:34:48,435 so those those issues about, like, perfection, I think, are 564 00:34:48,435 --> 00:34:52,280 gonna be less and less. Yeah. Well, time will tell. 565 00:34:52,280 --> 00:34:55,659 Okay. So for those people who are listening, they're like, I am so curious 566 00:34:56,040 --> 00:34:59,640 about using AI, especially in sales. I know you 567 00:34:59,640 --> 00:35:03,480 have a blog about this called super intelligent sales. Tell 568 00:35:03,480 --> 00:35:06,795 us all about it. Yeah. You know, I believe 569 00:35:07,815 --> 00:35:11,495 that this AI thing is the most important thing that's ever happened in the go 570 00:35:11,495 --> 00:35:15,275 to market function, marketing, sales, and customer success. 571 00:35:15,735 --> 00:35:19,115 You know, the reality is that all of the good stuff that happens 572 00:35:19,415 --> 00:35:23,180 happens in conversations with customers. And up until now, we 573 00:35:23,180 --> 00:35:26,640 haven't been able to analyze those conversations at scale. 574 00:35:27,020 --> 00:35:30,859 And so once you can, you can do so much with 575 00:35:30,859 --> 00:35:34,400 it, a lot of the things that we've talked about. And so I really see 576 00:35:34,460 --> 00:35:37,655 myself as being on a mission to help marketers, 577 00:35:37,955 --> 00:35:41,635 salespeople, leaders to realize how to take 578 00:35:41,635 --> 00:35:45,395 advantage of these tools and how to adopt them into their sales 579 00:35:45,395 --> 00:35:49,155 process in a way that's effective, right, and not just, like, you know, we're 580 00:35:49,155 --> 00:35:52,619 gonna roll out and go and buy the latest tool. Right? And so so that's 581 00:35:52,619 --> 00:35:56,380 what I write about on my blog. So, I have a blog 582 00:35:56,380 --> 00:35:59,819 called superintelligencesales.ai where I write about 583 00:35:59,819 --> 00:36:02,799 sales. I share use cases. I share implementation 584 00:36:03,260 --> 00:36:07,025 strategies. You know? I wrote a few articles related 585 00:36:07,025 --> 00:36:10,785 to the topics that we share, so I'll I'll put that out there. So folks 586 00:36:10,785 --> 00:36:14,384 can get in touch with me on the block. They can find me on 587 00:36:14,384 --> 00:36:17,984 LinkedIn. I'm Victor Adefuye. That's a d e f 588 00:36:17,984 --> 00:36:21,390 u y e. You know, I have a consulting practice called, 589 00:36:21,710 --> 00:36:23,230 Dana Consulting. So that's 590 00:36:23,230 --> 00:36:26,990 Dana-consulting.com where we help 591 00:36:26,990 --> 00:36:30,590 organizations implement AI into their sales process, you know, with 592 00:36:30,590 --> 00:36:33,950 proper training and coaching. And so, yeah, hit me up on 593 00:36:33,950 --> 00:36:37,385 LinkedIn. Check this out at danaconsulting.com 594 00:36:37,685 --> 00:36:41,445 or on a blog at superintelligencesales.ai. Perfect. 595 00:36:41,445 --> 00:36:44,005 I'm a put all those links in the show notes. You can find them at 596 00:36:44,005 --> 00:36:47,765 onlinedre.com/35four. Victor, thank you so much for being on the 597 00:36:47,765 --> 00:36:51,520 show today. Thank you. This was a fun conversation. Yay. 598 00:36:51,520 --> 00:36:54,800 And thank you, dear listener, for tuning in to another episode of the Mindful Marketing 599 00:36:54,800 --> 00:36:58,560 Podcast. Make sure you leave us a five star rating on Apple Podcasts and 600 00:36:58,560 --> 00:37:02,400 Spotify. Helps keep us in the top 100 marketing podcasts, and that's all 601 00:37:02,400 --> 00:37:06,215 because of your support. And also, if you wanna go even deeper 602 00:37:06,215 --> 00:37:10,055 into the world of marketing and AI, I've got you. Inside of the Mindful 603 00:37:10,055 --> 00:37:13,895 Marketing Lab, one of the biggest benefits of being in the lab is you 604 00:37:13,895 --> 00:37:17,735 get unlimited support. So if you ever have questions about AI, I've 605 00:37:17,735 --> 00:37:21,520 got a whole course on it. But also, if you wanna ask, there's no shame 606 00:37:21,520 --> 00:37:24,319 in asking. I'm here to support you. So come on into the lab. You can 607 00:37:24,319 --> 00:37:28,160 find that on the website as well. Next week, I have Natalie Bullen 608 00:37:28,160 --> 00:37:31,839 coming on the podcast to talk about having a magnetic personal 609 00:37:31,839 --> 00:37:35,474 brand and using social media to grow your revenue. See you 610 00:37:35,474 --> 00:37:38,454 next Tuesday. That's all for today. Bye for now.