1 00:00:00,160 --> 00:00:03,939 Hello. And welcome to another episode of the data driven podcast, 2 00:00:04,080 --> 00:00:07,600 where we peel back the layers of the tech world, 1 byte at a 3 00:00:07,600 --> 00:00:10,965 time. Today, we're diving into the heart of 4 00:00:10,965 --> 00:00:14,725 innovation, customer success, and the art of doing big things in 5 00:00:14,725 --> 00:00:18,210 the tech realm. Our guest is none other than Luke 6 00:00:18,210 --> 00:00:22,050 Dias, the visionary founder of d b t ventures and a maestro of 7 00:00:22,050 --> 00:00:25,895 turning startups into success stories. Luc has a 8 00:00:25,895 --> 00:00:29,654 Midas touch, transforming companies from their humble beginnings to 9 00:00:29,654 --> 00:00:33,254 powerhouses with over $100,000,000 in annual recurring 10 00:00:33,254 --> 00:00:36,630 revenue. LUKE is a veritable oracle of the tech 11 00:00:36,630 --> 00:00:39,990 age. So, if you're as excited as a 12 00:00:39,990 --> 00:00:43,350 processor executing a new algorithm to learn how to scale your 13 00:00:43,350 --> 00:00:47,145 business, predict the future with data, or simply want to hear from one 14 00:00:47,145 --> 00:00:50,365 of the leading minds in the industry, you're in the right place. 15 00:00:51,280 --> 00:00:54,820 Let's boot up this conversation and see where the data takes us. 16 00:00:55,680 --> 00:00:59,005 Without further ado, let's welcome Luke Diaz to the 17 00:01:00,585 --> 00:01:04,345 show. Hello, and welcome back to Data Driven. The 18 00:01:04,345 --> 00:01:07,770 podcast we explore the emergent fields of data science, artificial 19 00:01:07,770 --> 00:01:10,990 intelligence, and data engineering. 20 00:01:11,210 --> 00:01:14,775 And as luck would have it, our my world's 21 00:01:14,935 --> 00:01:18,455 favorite my most favoritest data data engineer in the world has 22 00:01:18,455 --> 00:01:21,975 rejoined this call. Today has been kind of an odd day. It's 23 00:01:21,975 --> 00:01:25,350 February 13th where we're recording this. And while it's not a 24 00:01:25,350 --> 00:01:28,970 Friday, it has that Friday 13th 25 00:01:29,110 --> 00:01:32,905 kind of vibe. Right, Andy? Yes, sir. So, yes, 26 00:01:32,905 --> 00:01:36,585 sir. Sorry about that. No. No worries. No worries. We had some kind of 27 00:01:36,585 --> 00:01:40,025 brown out, but I am So and I'm excited 28 00:01:40,910 --> 00:01:44,430 Yes. Because of our guest. Me too. So we 29 00:01:44,430 --> 00:01:48,110 had a, all sorts of things happen 30 00:01:48,110 --> 00:01:51,435 today, but I wanna get the show done before something else happens today. 31 00:01:52,295 --> 00:01:55,915 With us today, we have Luke Diaz, founder of DBT, 32 00:01:56,855 --> 00:02:00,590 Do Big Things Ventures, which has an amazing portfolio of angel 33 00:02:00,590 --> 00:02:04,110 and venture, capital investments, and 34 00:02:04,110 --> 00:02:07,170 advisory of tech, software, and other innovation, 35 00:02:07,604 --> 00:02:11,125 focused companies. He himself is an expert in customer 36 00:02:11,125 --> 00:02:14,265 success, tech support, software and SaaS trends. 37 00:02:15,330 --> 00:02:19,170 And, he has helped 3 startups grow from single digit millions 38 00:02:19,170 --> 00:02:22,550 to 100, 1,000,000 plus ARR. 39 00:02:23,355 --> 00:02:26,795 And, he releases regular research 40 00:02:26,795 --> 00:02:30,095 through thousands of subscribers, exploring focused 41 00:02:30,395 --> 00:02:34,030 topics such as customer success, how to improve your business 42 00:02:34,030 --> 00:02:37,709 writing, and building a churn prediction model with machine learning, 43 00:02:37,950 --> 00:02:40,770 as well as how VCs or venture capitalists 44 00:02:42,055 --> 00:02:45,655 establish track records of success. So thank you for joining us, 45 00:02:45,655 --> 00:02:49,175 Luke. I know that you had some kind of, sore throat, then you got better, 46 00:02:49,175 --> 00:02:52,950 and then Yeah. I I'm feeling 47 00:02:52,950 --> 00:02:56,390 a lot better. Frank, Andy, big fan of the show, honored to be here. I 48 00:02:56,390 --> 00:02:59,895 really appreciate you having me on the show. Thank you. We're we're very glad to 49 00:02:59,895 --> 00:03:02,635 have you, and we're able to get through this. So, 50 00:03:03,735 --> 00:03:07,470 the first question is, what is a Venture Capitalist? 51 00:03:07,530 --> 00:03:10,650 Right? So, you know, there's a lot of people. We work in technology. That term 52 00:03:10,650 --> 00:03:14,330 is thrown around a lot. I have a college buddy of mine who calls himself 53 00:03:14,330 --> 00:03:15,310 a Venture Capitalist, 54 00:03:18,125 --> 00:03:21,665 but he does real estate. So clearly, it's more than just tech, although, 55 00:03:23,565 --> 00:03:27,230 tech is clearly kind of, when people say the word, that that's 56 00:03:27,230 --> 00:03:30,210 the context. But tell me, what exactly is a venture capitalist? 57 00:03:31,550 --> 00:03:35,095 Yeah. That's it's a great question. I'd say the definition has shifted over the years. 58 00:03:35,175 --> 00:03:38,855 I I I just, I think we owe a debt of gratitude to 59 00:03:38,855 --> 00:03:42,695 Sebastian Malaby, who wrote recently published, The 60 00:03:42,695 --> 00:03:45,700 Power Law, which I think is basically the canonical, 61 00:03:47,040 --> 00:03:50,260 book that has the best all encompassing research 62 00:03:50,400 --> 00:03:53,995 on the space. So, if any of your listeners 63 00:03:54,055 --> 00:03:57,655 want to go deeper, it's definitely been the most 64 00:03:57,655 --> 00:04:01,390 recommended book to me this year, The Power Law by Sebastian 65 00:04:01,390 --> 00:04:04,910 Mallody. But I think at the simplest level, it's a person 66 00:04:04,910 --> 00:04:08,750 who's, giving money to start ups. You know? You you invest in 67 00:04:08,750 --> 00:04:12,424 small companies and you hope they get big. And this trend started in the 68 00:04:12,424 --> 00:04:15,965 sixties, and it really took a lot of different shapes and formats over the years, 69 00:04:16,745 --> 00:04:20,589 with governments playing a different role and partnership structures 70 00:04:20,730 --> 00:04:24,490 changing the face, activist versus passive. So there's been a lot 71 00:04:24,490 --> 00:04:28,065 of dynamics, but the same the trend the the baseline has remained the 72 00:04:28,065 --> 00:04:31,825 same. Giving giving money investing money into small 73 00:04:31,825 --> 00:04:35,510 companies hoping they get big. So that's that's what I do, 74 00:04:35,510 --> 00:04:39,130 that's that's one of the spaces I I love to learn and and play in. 75 00:04:39,750 --> 00:04:43,455 Very cool. Clearly, it's not just software, like, 76 00:04:43,455 --> 00:04:46,975 it could be anything, but so so thank you for that definition, because when he 77 00:04:46,975 --> 00:04:50,735 when he suddenly declared himself one day a venture capitalist, I was 78 00:04:50,735 --> 00:04:54,160 like, dude, dude, you're in real estate. And he's 79 00:04:54,160 --> 00:04:57,940 like, you know, it's more than just .com. This is during a .com 80 00:04:58,695 --> 00:05:02,235 kind of thing. Like, it's more than .com. So so, 81 00:05:03,175 --> 00:05:06,395 yeah. What exactly to you what is customer success? Right? Because, 82 00:05:07,190 --> 00:05:10,790 you know, I worked at Microsoft. I work now at Red Hat, and and 83 00:05:10,790 --> 00:05:14,285 there's this whole thing about customer success. And I've 84 00:05:14,285 --> 00:05:18,044 noticed that is also a term that I wouldn't say it gets 85 00:05:18,044 --> 00:05:21,565 overused, but I think different companies have different terms. Like, what when 86 00:05:21,565 --> 00:05:25,380 you what does customer success mean to you? Like, what how would you define 87 00:05:25,380 --> 00:05:29,220 it? That's a great question. I've I've been 88 00:05:29,220 --> 00:05:32,715 reflecting on that a lot because the space has changed so 89 00:05:32,715 --> 00:05:36,555 much over the last 10, 15 years. If I had 90 00:05:36,555 --> 00:05:40,075 to pick 1 word to kind of encapsulate the entire 91 00:05:40,075 --> 00:05:43,630 function and why companies are willing to spend 10, 92 00:05:43,630 --> 00:05:47,250 20% of their revenue on the function is is value. 93 00:05:47,550 --> 00:05:51,235 They are the owners of value 94 00:05:51,775 --> 00:05:55,475 being achieved and communicated to the customer. 95 00:05:56,335 --> 00:06:00,030 The value is like the and and there's art and science to that. 96 00:06:00,030 --> 00:06:03,870 Right? So they are the they are the team that is responsible for get 97 00:06:03,949 --> 00:06:07,745 often getting teams, new customers implemented, making sure they 98 00:06:07,745 --> 00:06:11,425 use it, overcome overcoming structural political 99 00:06:11,425 --> 00:06:13,605 things to, like, get this software 100 00:06:14,790 --> 00:06:18,470 integrated into a company that's never used usually, in most 101 00:06:18,470 --> 00:06:22,250 cases, never used your software before. So, I think of value 102 00:06:22,310 --> 00:06:25,615 as the north star, the guiding light of the function. 103 00:06:26,235 --> 00:06:29,535 But that said, it's taken a lot of different shapes and sizes, 104 00:06:29,914 --> 00:06:33,700 and and roles and responsibilities have shifted. But the 105 00:06:33,700 --> 00:06:37,540 the thing a lot of your listeners probably remember is, like, when software as 106 00:06:37,540 --> 00:06:41,355 a subscription became a thing, we needed a function or 107 00:06:41,355 --> 00:06:45,115 a team. The problem was, like, you don't just buy the software once on prem 108 00:06:45,115 --> 00:06:48,840 and forget about it and hope, you know, hope it renews. Like, these these teams 109 00:06:48,840 --> 00:06:52,440 have to use the software to get value, and they have to 110 00:06:52,440 --> 00:06:56,235 rebuy in the subscription model, which precipitated a need for 111 00:06:56,235 --> 00:06:59,835 this ongoing account management, but also 112 00:06:59,835 --> 00:07:03,195 usage and adoption component. So I think that was, like, 113 00:07:03,195 --> 00:07:06,370 the the change in the landscape that really precipitated 114 00:07:07,070 --> 00:07:10,830 the need for customer success. And, we could talk 115 00:07:10,830 --> 00:07:14,465 more about how to you know, what that means on a more detailed level, but 116 00:07:14,465 --> 00:07:18,064 that's how I think about it. Yeah. My my first exposure to the 117 00:07:18,064 --> 00:07:21,849 term was when they 118 00:07:22,550 --> 00:07:26,229 had this role. This is maybe, like, 8 years ago at Microsoft. They had cloud 119 00:07:26,229 --> 00:07:29,775 solution architects, but then then one day, they said, no. No. No. 120 00:07:29,775 --> 00:07:33,615 You're customer success architects now. And 121 00:07:33,615 --> 00:07:36,995 a lot of us looked at each other, like, so we're gonna do anything different? 122 00:07:37,590 --> 00:07:40,090 And they were, like, no. No. No. The jobs are the same. 123 00:07:40,950 --> 00:07:44,550 Okay. Why the change? And they're, like, well, because we're a cloud company 124 00:07:44,550 --> 00:07:46,225 now. Okay. 125 00:07:48,285 --> 00:07:51,725 Like, couches my exposure to the term. Like, I get it. Right? I 126 00:07:51,725 --> 00:07:55,245 understand the reasoning for it, but it was just kinda how I was introduced to 127 00:07:55,245 --> 00:07:59,060 it, inter introduced to it would would fit in very well 128 00:07:59,060 --> 00:08:02,199 with the theme of the day of just extreme weirdness. 129 00:08:03,139 --> 00:08:06,865 But, yeah. So so, 130 00:08:06,865 --> 00:08:09,745 like, what what are your thoughts? Like, how do you measure customer success? Right? You 131 00:08:09,745 --> 00:08:13,440 know, the the way we were measured, was kind of, you know, 132 00:08:13,440 --> 00:08:17,040 did they adopt the platform? Are they spending? Are there other 133 00:08:17,040 --> 00:08:20,794 metrics, like, customer satisfaction? Like, what? It seems like it's more than 134 00:08:20,794 --> 00:08:24,595 a one dimensional type of thing. And that 135 00:08:24,755 --> 00:08:27,655 you you raise a great point, Frank, because it is multifaceted. 136 00:08:28,650 --> 00:08:32,429 I think the role of a leader is is really clarity. 137 00:08:32,650 --> 00:08:36,410 And so where customer success leaders, I think, really need to step up is 138 00:08:36,410 --> 00:08:40,034 make sure that that scoreboard is super clear. Because if you're telling the 139 00:08:40,034 --> 00:08:43,875 team 10 things are important, guess what? None of them are 140 00:08:43,875 --> 00:08:47,235 that important, because we have this finite resource of 141 00:08:47,235 --> 00:08:50,710 time. And so the way I think about it is I love 142 00:08:50,710 --> 00:08:54,230 setting goals, performance, and comp based on lagging 143 00:08:54,230 --> 00:08:58,025 indicators and then managing to the leading indicators 144 00:08:58,025 --> 00:09:01,705 that are most correlated to that outcome. So, like, for teams I've 145 00:09:01,705 --> 00:09:04,959 managed in the past, the vast majority of their bonus 146 00:09:05,420 --> 00:09:08,720 was driven by gross, gross retention. 147 00:09:09,500 --> 00:09:12,894 Keep the dollars that we know. We've seen some pretty high customer 148 00:09:12,894 --> 00:09:16,595 acquisition costs over the last 10 years. You are companies 149 00:09:16,735 --> 00:09:20,334 are spending a ton of money, 50, 100, 250 k to 150 00:09:20,334 --> 00:09:24,050 acquire a customer. You have to keep that customer for 151 00:09:24,050 --> 00:09:27,510 years to make the unit economics make sense. And so 152 00:09:28,370 --> 00:09:32,005 if you have a leaky bucket, man, and you've seen a lot of companies 153 00:09:32,005 --> 00:09:35,525 over the last few years get turned upside down because unit 154 00:09:35,525 --> 00:09:37,945 economics weren't scalable, weren't sustainable. 155 00:09:39,220 --> 00:09:42,980 So gross retention, dollars up for renewal is 156 00:09:42,980 --> 00:09:46,785 the denominator and, like, how much of those dollars renewed? That is, in 157 00:09:46,785 --> 00:09:50,465 my view, the clearest way to measure the 158 00:09:50,465 --> 00:09:54,005 outcome of a high performance customer success team. 159 00:09:54,225 --> 00:09:57,920 There's a lot of ways and strategies you could take to get 160 00:09:57,920 --> 00:10:01,600 to that outcome. That's where I think management and leading indicators come 161 00:10:01,600 --> 00:10:05,040 in. You talk about, are the customers happy? Are they using the 162 00:10:05,040 --> 00:10:08,485 product? But customers vote with their dollars. 163 00:10:09,105 --> 00:10:12,885 And so I want to make it super clear to any team I lead or 164 00:10:13,170 --> 00:10:16,930 founders that I back, that retention is the name of the game. 165 00:10:16,930 --> 00:10:20,290 Because if you don't get that right, you you you just have this 166 00:10:20,290 --> 00:10:23,235 treadmill. You have this high cap, shitty, 167 00:10:23,855 --> 00:10:26,915 poor unit economics, sorry, you could bleep that out, 168 00:10:29,055 --> 00:10:32,670 yeah, you don't have a good business, so I try and anchor 169 00:10:32,670 --> 00:10:36,430 on gross revenue retention, as 170 00:10:36,430 --> 00:10:39,925 the the scoreboard. So a lot of our 171 00:10:40,165 --> 00:10:43,605 I say not a lot. All of our interviews are super 172 00:10:43,605 --> 00:10:47,140 cool, but not all of them are applicable to me in my 173 00:10:47,140 --> 00:10:50,740 small boutique business. So when you see me take out Andy's 174 00:10:50,740 --> 00:10:53,640 memory and a writing device, 175 00:10:54,464 --> 00:10:58,165 that that's applicable. So this is helping this one. That's your EMM, 176 00:10:58,545 --> 00:11:02,225 external memory module. That's me. So I am taking notes, 177 00:11:02,225 --> 00:11:05,940 Luke. Those are 2 good things. 1st, the book, the recommendation of the book, 178 00:11:05,940 --> 00:11:09,300 but I love the math. And, if you give me a numerator and 179 00:11:09,300 --> 00:11:11,800 denominator and it resonates, I'm writing that down. 180 00:11:12,695 --> 00:11:16,295 Yeah. World class retention is 181 00:11:16,295 --> 00:11:18,475 typically, 95%. 182 00:11:19,790 --> 00:11:23,630 Nice. So if you got a $1,000,000 business over the course 183 00:11:23,630 --> 00:11:27,170 of that year, you're looking at 184 00:11:27,785 --> 00:11:31,545 churn, the inverse of 50 k. That's a 185 00:11:31,545 --> 00:11:35,065 lot of revenue to retain. Right? So you're gonna renew 186 00:11:35,065 --> 00:11:38,620 950 $1,000 of that 1,000,000, you're 187 00:11:38,620 --> 00:11:42,379 invest in class. And there's there's a 2nd tier that's kinda like 90 to 188 00:11:42,379 --> 00:11:46,204 95, but if you get that right, man and then you you 189 00:11:46,204 --> 00:11:49,805 start layering on products, the whole revenue curve just 190 00:11:49,805 --> 00:11:53,485 goes stratospheric. It gets really really exciting when you have a 191 00:11:53,485 --> 00:11:57,270 strong foundation and a and a non leaky bucket. 192 00:11:57,970 --> 00:12:01,750 I like that. I like the leaky bucket analogy. Yeah. Yeah. 193 00:12:02,370 --> 00:12:05,565 Jinx. I'll take a monster energy drink, 194 00:12:06,205 --> 00:12:09,885 but, no. I'll change with my LaCroix. There you go. There 195 00:12:09,885 --> 00:12:13,630 you go. They closed school here, so, like, 196 00:12:13,630 --> 00:12:15,730 to deal with all the kids, I need the extra caffeine. 197 00:12:17,710 --> 00:12:21,545 Fair enough. But, so I mean, I would imagine so so this 198 00:12:21,545 --> 00:12:25,305 seems like, you know, this seem you've grown 3 199 00:12:25,305 --> 00:12:28,445 startups from single digit rev 1,000,000 revenues to a 100,000,000 200 00:12:30,150 --> 00:12:31,290 plus annual recurring, 201 00:12:35,029 --> 00:12:38,070 clearly, this has to be a factor in that. Right? Like, you you have to 202 00:12:38,070 --> 00:12:41,645 get this customer retention right, right, if you wanna scale. Is that 203 00:12:41,645 --> 00:12:45,325 a is that a fair assessment? It 204 00:12:45,325 --> 00:12:48,820 is. And it's a leading it's it's one of the criteria that 205 00:12:48,820 --> 00:12:52,340 most, series a, series b 206 00:12:52,340 --> 00:12:56,155 venture capitalists are looking for because they don't wanna 207 00:12:56,535 --> 00:12:59,995 they don't wanna invest in a lot of them got burned in these 208 00:13:00,535 --> 00:13:04,250 maybe they're high growth, but you got this leaky bucket where customers are just 209 00:13:04,490 --> 00:13:08,090 flooding out the back door. And that's not good because those 210 00:13:08,090 --> 00:13:11,690 customers talk to other people. It's like, oh, yeah. We churned that 211 00:13:11,770 --> 00:13:15,485 we we terminated that product. So it it really 212 00:13:15,485 --> 00:13:19,005 doesn't work unless you get those those numbers right, 213 00:13:19,005 --> 00:13:22,385 retention in the in the 90 90 to 95 214 00:13:22,525 --> 00:13:25,990 plus percentiles. Yeah. And it's become kind of 215 00:13:26,450 --> 00:13:30,130 a core metric for anyone that's looking at unit economics and 216 00:13:30,130 --> 00:13:32,790 the ability of this business to do something big. 217 00:13:34,565 --> 00:13:38,165 Yeah. So I would say, yeah, huge plus 1 on that as an anchoring 218 00:13:38,165 --> 00:13:41,970 metric. But then the more fun part of the job, in my like, it's really 219 00:13:41,970 --> 00:13:44,290 easy to run numbers at the end of the quarter or the end of the 220 00:13:44,290 --> 00:13:48,130 year. That's easy. But the the more interesting challenge is how do you 221 00:13:48,130 --> 00:13:51,824 get there? Right. How do you how are you structuring your onboarding 222 00:13:51,824 --> 00:13:55,584 process? How do you know if like, what is it how are you 223 00:13:55,584 --> 00:13:59,390 defining a successful onboarding? A lot of these startups 224 00:13:59,390 --> 00:14:03,230 I talked to, they they don't know. They're still figuring that out. How do 225 00:14:03,230 --> 00:14:06,855 you communicate value? You know, you start up, you build a a 226 00:14:06,855 --> 00:14:10,695 software or any business to solve a problem, give a strong 227 00:14:10,695 --> 00:14:14,135 hypothesis, but then you need to validate, like, okay, here's how we think about the 228 00:14:14,135 --> 00:14:17,940 return on investment. And by the way, most enterprises are looking 229 00:14:17,940 --> 00:14:21,620 for a, a software investment that has an ROI of 5 to 230 00:14:21,620 --> 00:14:25,335 7 x. So if you close this 100 k deal, they're looking for 231 00:14:25,335 --> 00:14:28,935 500 to 700 k of value to 232 00:14:28,935 --> 00:14:32,615 even rationalize renewing with you. So how do you that's a big 233 00:14:32,615 --> 00:14:36,120 number. Like, you're invested like, we better be able to show some business impact, 234 00:14:37,140 --> 00:14:40,360 and that that gets into the the products, capabilities, 235 00:14:41,265 --> 00:14:44,705 the impact on the business, the user workflows, and, ultimately, the p and 236 00:14:44,705 --> 00:14:48,065 l for how you're helping them either drive revenue or save 237 00:14:48,065 --> 00:14:51,710 costs. Right? It's this is all simple stuff. It's really easy to get abstract 238 00:14:51,710 --> 00:14:55,470 and hand wavy in software, but, like, it all goes back to the numbers. 239 00:14:55,470 --> 00:14:59,170 Right? So that I try and stay grounded in that way. 240 00:14:59,855 --> 00:15:03,615 Right. And as the cost of customer acquisition goes up, this becomes 241 00:15:03,615 --> 00:15:07,370 even more important. Right? We're not talking about, you know, 242 00:15:07,370 --> 00:15:11,050 somebody who's gonna drive by the the local convenience store and pick 243 00:15:11,050 --> 00:15:14,270 up, you know, a cup of coffee and a donut. Right? I mean, this is, 244 00:15:14,965 --> 00:15:18,085 you know, I'm sure they have numbers too, but the math is completely different in 245 00:15:18,085 --> 00:15:21,765 terms of what the incentives are. Right. Mhmm. Mhmm. Makes sense. 246 00:15:21,765 --> 00:15:25,500 Interesting. So what what what are the 247 00:15:25,500 --> 00:15:28,700 things that that because I'm sure in our audience, we have a lot of people 248 00:15:28,700 --> 00:15:32,545 who are either entrepreneurs, they run kind of boutique shops and shops themselves, and 249 00:15:32,545 --> 00:15:36,384 maybe they're thinking about, you know, I was gonna call you out by name, Andy. 250 00:15:36,545 --> 00:15:39,105 But but I I know I know for a fact we have a lot of 251 00:15:39,105 --> 00:15:42,529 people who are independent contractors here, and some of them I think are pondering the 252 00:15:42,529 --> 00:15:46,370 idea of, you know, hey, I'm selling my time for money. It'd be nice 253 00:15:46,370 --> 00:15:50,095 if I can make a platform where I can take some of that 254 00:15:50,095 --> 00:15:53,615 and kind of scale, like and I so I think this is an 255 00:15:53,615 --> 00:15:57,135 interesting opportunity to figure out, like, well, you know, how do you 256 00:15:57,750 --> 00:16:01,370 once you hit the single digit millions, obviously, you know, 257 00:16:02,230 --> 00:16:05,925 what's really the secret? Like, how do you that's a 100 x scale. That's 2 258 00:16:05,925 --> 00:16:09,524 orders of magnitude. Like, how do you if you had to pick the 259 00:16:09,524 --> 00:16:11,865 top 3 important things, what would they be? 260 00:16:13,699 --> 00:16:17,139 And I just wanna make sure I understand the question. You're talking along that path 261 00:16:17,139 --> 00:16:20,899 from it's called $1,000,000, which is a milestone in and of itself. Right. 262 00:16:20,899 --> 00:16:24,595 Like, getting to that 100 100, 1,000,000 revenue, what 263 00:16:24,595 --> 00:16:28,275 are, like, the from the customer success perspective? Right. The difference 264 00:16:28,275 --> 00:16:31,430 between generally. But the difference between comfortably buying a, 265 00:16:31,910 --> 00:16:35,290 Mercedes or 2 to buying a Bugatti. 266 00:16:35,350 --> 00:16:39,029 Right? Right? Like so it's like, what what 267 00:16:39,270 --> 00:16:43,014 how you get there. Right? I'm just I'm, like, 268 00:16:43,014 --> 00:16:45,755 curious. Like, what are the top 3 important things? Like, if you were 269 00:16:46,935 --> 00:16:50,770 advising somebody, like, what what really matters? Because there's a lot of 270 00:16:50,770 --> 00:16:54,310 noise in business, and I think the people that are successful 271 00:16:54,450 --> 00:16:56,710 can filter out the signal from the noise. 272 00:16:59,155 --> 00:17:02,135 What are your what are the kind of the 3 main levers to kind of 273 00:17:03,475 --> 00:17:05,095 filter out signal from noise? 274 00:17:07,150 --> 00:17:10,990 Let me let me ruminate on that, because as you 275 00:17:10,990 --> 00:17:14,804 mentioned, I've seen that ride three times and have been fortunate 276 00:17:14,804 --> 00:17:18,585 enough to play a small part in that in that outcome, in that growth. 277 00:17:19,284 --> 00:17:22,790 I'm trying to now, kind of, parse for common denominators 278 00:17:23,410 --> 00:17:27,250 that enabled that, I 279 00:17:27,250 --> 00:17:30,470 think customer success as one of the fastest growing 280 00:17:30,775 --> 00:17:34,475 functions in Silicon Valley in in the space. 281 00:17:35,175 --> 00:17:37,755 I think we do take a little too much credit sometimes 282 00:17:38,650 --> 00:17:42,170 because, at the end of the day, the product is 283 00:17:43,130 --> 00:17:46,645 that is what's being bought, and the and the product 284 00:17:47,025 --> 00:17:50,865 has to be there. So I would I would start with the 285 00:17:50,865 --> 00:17:54,520 inherent capabilities of the product itself, put 286 00:17:54,520 --> 00:17:58,360 away all the the post sales customer, kinda like my world that I 287 00:17:58,360 --> 00:18:01,660 operate in. If the product is not solving 288 00:18:02,375 --> 00:18:03,595 a valuable problem, 289 00:18:06,615 --> 00:18:10,190 and people aren't willing to pay for it, and it's not a 290 00:18:10,190 --> 00:18:13,950 lot better 7 x, you know, there's different data on how much 291 00:18:13,950 --> 00:18:17,465 better it needs to be than the next alternative, kind of like Ubers 292 00:18:17,465 --> 00:18:21,305 versus taxis, then you're not really 293 00:18:21,305 --> 00:18:25,050 in the arena to even get to 100,000,000. It you 294 00:18:25,050 --> 00:18:28,670 might just be building another high CAC inefficient 295 00:18:28,810 --> 00:18:32,170 leaky bucket, you know. Like, you might be able to ram 296 00:18:32,170 --> 00:18:35,995 software into these companies, but the the product's 297 00:18:36,054 --> 00:18:39,275 value and the strength is is what creates that enduring 298 00:18:39,815 --> 00:18:43,309 competitive advantage. So I I would look for 299 00:18:43,770 --> 00:18:47,070 the the nature of the product, the user mechanics, 300 00:18:48,730 --> 00:18:52,445 how frequently it's used, is it is it a 301 00:18:52,445 --> 00:18:56,125 product that you can habituate the users, as they 302 00:18:56,125 --> 00:18:59,085 adopt this new thing? Is it something you use once a month or is it 303 00:18:59,085 --> 00:19:02,610 something you need to use every day? So, like, the 304 00:19:02,610 --> 00:19:05,910 usage frequency and the perceived value 305 00:19:05,970 --> 00:19:09,330 are key indicators of, like, that product 306 00:19:09,330 --> 00:19:12,785 strength. The 307 00:19:12,785 --> 00:19:16,305 second is a willingness to invest in customer success. A lot of 308 00:19:16,305 --> 00:19:20,070 founders think the product can and should 309 00:19:20,370 --> 00:19:23,110 kind of just you know, if you build it, they will come. 310 00:19:25,684 --> 00:19:28,965 But the but the reality is is you start growing and you start getting some 311 00:19:28,965 --> 00:19:32,325 traction, 1,000,000, 2,000,000, 5,000,000. Now you're starting 312 00:19:32,325 --> 00:19:36,029 to think about moving upmarket where it's not selling 313 00:19:36,029 --> 00:19:39,710 a small smaller ticket item to an SMB or a company that's pretty 314 00:19:39,710 --> 00:19:43,390 nimble and can adopt your software, but you're talking to a collection of 315 00:19:43,390 --> 00:19:47,235 humans that now need to now need to adopt something new. 316 00:19:47,235 --> 00:19:50,775 So now you're talking about change management, process mapping. 317 00:19:50,835 --> 00:19:54,420 Hey. How does this software fit into your existing workflows? And the 318 00:19:54,420 --> 00:19:58,180 complexity gets higher. A lot of CEOs look at 319 00:19:58,180 --> 00:20:02,020 their head you know, right now is a common annual planning time. A lot of 320 00:20:02,020 --> 00:20:05,715 companies have their fiscal year end in January, and they're like, 321 00:20:06,815 --> 00:20:10,195 man, customer success could cost 20% of our revenue. 322 00:20:10,735 --> 00:20:14,420 And they're like, I don't want to make that investment. I've seen it 323 00:20:14,420 --> 00:20:18,180 a 100 times because it's a it's a big investment to have these 324 00:20:18,180 --> 00:20:21,940 humans try and figure out the complexity of working 325 00:20:21,940 --> 00:20:25,315 with these new larger customers and getting them to 326 00:20:25,315 --> 00:20:28,855 adopt a new habit, a new software, a new workflow. 327 00:20:29,850 --> 00:20:33,610 And so, that would be, like, linchpin number 2 is founder willingness 328 00:20:33,610 --> 00:20:35,309 to invest in the function, 329 00:20:37,645 --> 00:20:41,085 like, best in class success, at 330 00:20:41,085 --> 00:20:44,845 Salesforce, for example, is, like, 9 to 10% of revenue, so they're running 331 00:20:44,845 --> 00:20:48,289 a really efficient machine. They also have a lot of revenue, so the 332 00:20:48,289 --> 00:20:52,049 denominator is pretty big. But their their customer 333 00:20:52,049 --> 00:20:55,590 for life program is typically 9 to 12% of revenue, and that's considered 334 00:20:55,809 --> 00:20:59,635 hyperefficient. But when you're small and you're just trying to go 335 00:20:59,635 --> 00:21:03,315 out there, bag some big deals, and help them out, it's not uncommon to 336 00:21:03,315 --> 00:21:06,830 see customer success cost 20% of revenue. So 337 00:21:07,130 --> 00:21:10,590 on a 5,000,000 ARR business, are you willing to invest $1,000,000 338 00:21:11,929 --> 00:21:15,665 to hire, you know, 8 people and some 339 00:21:15,665 --> 00:21:19,365 managers to, like, take on this challenge? Maybe not. 340 00:21:19,905 --> 00:21:23,429 And then you're, kind of, setting the stage for those customers to not get the 341 00:21:23,429 --> 00:21:27,110 help they receive. So that's, like, kinda linchpin number 2 after 342 00:21:27,110 --> 00:21:30,565 product strength is is the willingness 343 00:21:30,945 --> 00:21:34,785 to even invest. And then, you asked for a third one, I 344 00:21:34,785 --> 00:21:38,360 might need there's so much variability that comes into 345 00:21:38,360 --> 00:21:42,120 play with market dynamics, the macro, the competitive space. So 346 00:21:42,120 --> 00:21:45,020 I'm not sure I have a clear third one that is 347 00:21:45,480 --> 00:21:49,225 abstractable. But those 2, I think, are important right there, 348 00:21:49,225 --> 00:21:52,345 because I think so the second one, I think, kinda well, the first one, if 349 00:21:52,345 --> 00:21:55,885 you don't want the first one, the second one's irrelevant. Right? Like but, like, 350 00:21:56,549 --> 00:22:00,309 the whole willingness to expand up to 20%, I mean, I that's 351 00:22:00,309 --> 00:22:03,669 a tough pill to swallow for a field that most people, if you ask them 352 00:22:03,669 --> 00:22:07,505 what customer success is, they'll probably give you a blank look, 353 00:22:07,505 --> 00:22:11,205 or as they say in LLM world, hallucinate an answer. 354 00:22:11,585 --> 00:22:15,345 Right? Like, because, like, even even I'm, 355 00:22:15,345 --> 00:22:19,090 like, I I only know I only got deep into this because as we were 356 00:22:19,090 --> 00:22:22,850 doing our planning for my day job, we were, like, 357 00:22:22,850 --> 00:22:26,465 you know, customer success, and the guy basic the guy runs it kind of 358 00:22:26,465 --> 00:22:29,505 explained his pitch. And I was, like, oh, well, that makes perfect sense. You know? 359 00:22:29,505 --> 00:22:33,290 But prior to that conversation, I don't know. I would have been, like, 360 00:22:33,770 --> 00:22:37,610 you want 20% you want, you know, like, if you were a $5,000,000 company, 361 00:22:37,610 --> 00:22:41,370 I mean, that's, you know, may maybe not in the Bay area, but that's 362 00:22:41,370 --> 00:22:45,135 still a lot of money. $1,000,000,000 will buy will 363 00:22:45,135 --> 00:22:47,875 buy you a house around here. But, 364 00:22:48,655 --> 00:22:52,000 sorry. I thought that was a not okay. I thought that was a really good 365 00:22:52,000 --> 00:22:55,060 analogy, and bringing the numbers home, 366 00:22:55,600 --> 00:22:59,360 being a person, you know, I'm, you know, being a person in business for 367 00:22:59,360 --> 00:23:02,945 myself, I'll just say it that way. The, and from 368 00:23:02,945 --> 00:23:05,925 that perspective, I'd I'd like to ask, 369 00:23:07,505 --> 00:23:10,245 how do you deal with folks who may be reluctant 370 00:23:11,010 --> 00:23:14,710 to engage with any form of venture capitalist 371 00:23:15,090 --> 00:23:18,470 person simply out of fear of the unknown? 372 00:23:18,530 --> 00:23:22,135 They don't understand it. They, you know, they've 373 00:23:22,355 --> 00:23:25,875 maybe they've heard some horror stories of, you know, things 374 00:23:26,115 --> 00:23:29,900 deals going south and bad outcomes. Or they've seen 375 00:23:29,900 --> 00:23:33,660 Shark Tank, right? And they're like, you know. Well, I mean, you know, and I 376 00:23:33,660 --> 00:23:37,360 mean, the risk aversion, I think everybody has 377 00:23:37,900 --> 00:23:41,405 some bit of that. And certainly, you know, 378 00:23:41,405 --> 00:23:45,245 the 100 X upside. Yeah. I'm all in, 379 00:23:45,245 --> 00:23:49,000 you know, on that piece of it. But I'm wondering what's I don't understand 380 00:23:49,000 --> 00:23:52,680 permit. I'm I'm just gonna confess. I don't understand all of the mechanics of 381 00:23:52,680 --> 00:23:55,980 VC deals. I imagine there are many variations, 382 00:23:57,095 --> 00:24:00,855 and there has to be a certain amount of trust with the actual 383 00:24:00,855 --> 00:24:04,695 firm or the venture venture capitalist. So how would you address you 384 00:24:04,695 --> 00:24:08,000 can you can talk to me. How would you address my fears of the unknown? 385 00:24:10,060 --> 00:24:12,240 It I think it's a very valid point. 386 00:24:13,995 --> 00:24:17,195 When numbers are involved and, like, you're a founder, you're talking about the equity of 387 00:24:17,195 --> 00:24:20,955 your company. You know, someone's coming into 388 00:24:20,955 --> 00:24:24,390 this room and and you're gonna you're gonna lock arms and be 389 00:24:24,390 --> 00:24:28,070 financially entangled. It's it's not dissimilar to a marriage in 390 00:24:28,070 --> 00:24:31,815 some regards because, like, you're going to be working together. You're not sleeping together, 391 00:24:31,815 --> 00:24:35,515 but you're you're working really closely together on the financials and you have 392 00:24:35,815 --> 00:24:39,590 a a very vested shared interest. But you kind of hit the nail 393 00:24:39,590 --> 00:24:43,350 on the head. It is a relationship business. You guys have interviewed 394 00:24:43,350 --> 00:24:46,890 some some great VCs and some in the space. So, 395 00:24:48,095 --> 00:24:51,775 I would encourage your listeners to relisten to some of those episodes, as well, which 396 00:24:51,775 --> 00:24:55,315 I found really valuable. The things that, 397 00:24:55,900 --> 00:24:59,580 I think scare people are the like, you mentioned the horror 398 00:24:59,580 --> 00:25:03,145 stories. So everything's great when the market's up, but 399 00:25:03,145 --> 00:25:06,905 where it's kinda like when when someone passes away or 400 00:25:06,905 --> 00:25:10,345 there's a divorce, that's where stuff hits the fan. 401 00:25:10,345 --> 00:25:13,960 Right? So you start to hear stories of dirty term 402 00:25:13,960 --> 00:25:17,659 sheets, which basically have these 403 00:25:17,960 --> 00:25:21,775 prep stacks or these, like, liquidity preferences, which basically just means, like, 404 00:25:21,775 --> 00:25:25,135 I get my money out before other people, and I actually might get more money 405 00:25:25,135 --> 00:25:28,115 out than other people. They they kind of 406 00:25:28,780 --> 00:25:30,640 they derisk the deal 407 00:25:32,220 --> 00:25:35,820 by exerting leverage to minimize 408 00:25:35,820 --> 00:25:39,665 their downside and and that screws other people. Right? Like, that's 409 00:25:39,665 --> 00:25:43,345 less money for employees, the founders, and 410 00:25:43,345 --> 00:25:47,170 subsequent investors. So dirty term sheets are are 411 00:25:47,170 --> 00:25:50,850 something that are a tactic I've never employed. I'm 412 00:25:50,850 --> 00:25:54,550 usually a little earlier, so there's some standardized agreements that, thankfully, 413 00:25:55,165 --> 00:25:58,845 thanks to Paul Graham and the team at Y Combinator, they've put 414 00:25:58,845 --> 00:26:01,745 out these simple agreements for future equities, 415 00:26:02,590 --> 00:26:06,210 like a basic safe agreement, which I've used dozens of times, 416 00:26:06,590 --> 00:26:10,190 where it's clean, it's founder friendly. There's a ton of 417 00:26:10,190 --> 00:26:14,015 these being populated. Yeah. So I would caution you to 418 00:26:14,015 --> 00:26:17,775 look at, like, the this I would encourage you to look at, like, the 419 00:26:17,775 --> 00:26:21,390 numbers in the sense of, like, dirty term sheets and press stacks, 420 00:26:21,390 --> 00:26:25,150 they're exceedingly rare. Like, I've only seen 421 00:26:25,150 --> 00:26:28,370 them in less than 2 or 3% 422 00:26:29,184 --> 00:26:32,625 of the companies or deals that I've worked, where there is really a 423 00:26:32,625 --> 00:26:36,465 VC trying to to leverage, you know, and have kind of 424 00:26:36,465 --> 00:26:40,240 an angle. My question is that VC would be, 425 00:26:40,240 --> 00:26:43,460 like, why do you want if you believe in us so much, why do you 426 00:26:43,919 --> 00:26:47,534 why are you trying to, like, change the nature of the dynamics? 427 00:26:49,275 --> 00:26:53,034 Because because the best VCs just want you to be successful. They're not planning for 428 00:26:53,034 --> 00:26:56,700 the divorce. They're not making you sign a prenup. So, 429 00:26:56,700 --> 00:27:00,399 anyway, that's just, just one thing on the the term sheets 430 00:27:00,700 --> 00:27:04,080 where I think it's it can be perceived as a little bit predatory. 431 00:27:06,284 --> 00:27:09,745 And, yeah, I I don't think most founders need 432 00:27:09,965 --> 00:27:13,680 venture capitalists. I think I encourage like, if you 433 00:27:13,680 --> 00:27:17,280 don't need my money, please don't take it. More money for founders is 434 00:27:17,280 --> 00:27:21,120 better for you. Do don't delete it. It's it's almost, like, glamorized a little 435 00:27:21,120 --> 00:27:24,755 bit. Like, these are just people writing checks that and and they 436 00:27:24,755 --> 00:27:28,435 have an amazing network. So, like, there's really smart people, but, like, they're just 437 00:27:28,435 --> 00:27:32,240 writing checks and joining board meetings. So I would almost knock 438 00:27:32,240 --> 00:27:35,840 them down a peg because the founders are the ones creating value and 439 00:27:35,840 --> 00:27:39,539 changing the world. It's it's not the venture capitalist, so I would almost 440 00:27:40,225 --> 00:27:43,665 I would challenge the premise of that. I don't think most 441 00:27:43,665 --> 00:27:47,205 founders even need it. I'd much rather see them bootstrap. 442 00:27:48,660 --> 00:27:52,280 Well, that's that's an interesting take, you know, as a as a founder. 443 00:27:52,580 --> 00:27:55,995 That's that's an interesting, thought. And I've I've not 444 00:27:56,315 --> 00:27:59,755 seen, you know, and I guess that's not what VCs lead with, you know, when 445 00:27:59,755 --> 00:28:03,434 they're when they approach or angel investors. That's not what they they first lead 446 00:28:03,434 --> 00:28:06,799 with. So it's refreshing, actually to hear 447 00:28:06,799 --> 00:28:10,640 that. But the other side of it, I wouldn't discount, even though I 448 00:28:10,640 --> 00:28:14,485 know less about the process than I 449 00:28:14,485 --> 00:28:18,245 would need to know before, you know, I participate. But even 450 00:28:18,245 --> 00:28:21,780 then, I know the value of a network and I know the value of 451 00:28:21,860 --> 00:28:25,160 advice and having a broad experience 452 00:28:25,540 --> 00:28:28,980 across many different businesses in the field. And being able 453 00:28:28,980 --> 00:28:32,735 especially to look at something dumb that I'm 454 00:28:32,735 --> 00:28:36,015 doing and go, you know, Andy, that's dumb. And, you know, let me tell you 455 00:28:36,015 --> 00:28:39,450 this other horror story about this founder who did exactly what you're doing, and then 456 00:28:39,450 --> 00:28:43,290 they lost everything. And, you know, that's that advice 457 00:28:43,290 --> 00:28:46,965 I think would be valuable as well. I mean, I won't say invaluable, but 458 00:28:47,125 --> 00:28:50,804 it's not nothing. And to have that described as you did 459 00:28:50,804 --> 00:28:54,585 early in terms of a relationship and being arm in arm and and 460 00:28:54,885 --> 00:28:58,640 working for the success of the venture because that 461 00:28:58,640 --> 00:29:01,060 makes perfect sense because then everybody wins. 462 00:29:02,640 --> 00:29:06,355 Mhmm. Well said. And the, I think back to 463 00:29:06,355 --> 00:29:10,195 my days at Optimizely where, Benchmark led our 464 00:29:10,195 --> 00:29:13,794 a round, and Peter Fenton, who's a fairly well known 465 00:29:13,794 --> 00:29:17,560 investor, is on the board at Twitter and Yelp. He joined our board, and he 466 00:29:17,560 --> 00:29:21,240 was very helpful and insightful. And you know what? He he didn't 467 00:29:21,240 --> 00:29:24,934 offer advice, but he asked really good questions. And I had him come speak to 468 00:29:24,934 --> 00:29:28,774 my team at an off-site, and, we're expecting this long, 469 00:29:28,774 --> 00:29:32,540 eloquent talk. He just went up to the the whiteboard, you know, and he 470 00:29:32,540 --> 00:29:35,840 wrote executive visibility equals 471 00:29:36,460 --> 00:29:39,935 budget. And we talked about this concept that if, like, the 472 00:29:39,935 --> 00:29:43,055 executives and your customers, if they don't know who you are, you don't have budget. 473 00:29:43,055 --> 00:29:46,495 And so he has these to your point, Andy, he has these 474 00:29:46,495 --> 00:29:50,309 insights that can lead to really interesting things, and he asks really good 475 00:29:50,309 --> 00:29:53,990 questions. And so the value was less than the money and more about, like, the 476 00:29:53,990 --> 00:29:57,455 insights and the questions. What are the unknown unknowns you're not thinking 477 00:29:57,455 --> 00:30:00,895 about? That's where I think VCs can Yeah. Maybe maybe 478 00:30:00,895 --> 00:30:04,440 impact the trajectory more. Yeah. Well said, I'd love to call out. 479 00:30:04,679 --> 00:30:08,360 Yeah. I I love that because I I say this because it's true. 480 00:30:08,360 --> 00:30:11,820 I I don't know what I don't know. And if I'm a solopreneur, 481 00:30:12,120 --> 00:30:15,925 like I am, it's like I am stuck here unless I have 482 00:30:15,925 --> 00:30:19,205 good friends. And I do. I have Frank and I have a number of really 483 00:30:19,205 --> 00:30:23,000 close friends who are in positions all over in different companies. 484 00:30:23,000 --> 00:30:26,360 1, one good friend who was an early guest on the 485 00:30:26,360 --> 00:30:29,985 show, about almost 2 years ago, got 486 00:30:29,985 --> 00:30:33,605 his MBA from, from the Sloan School at MIT. 487 00:30:34,145 --> 00:30:37,985 And he's gone on to gain experience, and he's reached out, you know, a 488 00:30:37,985 --> 00:30:41,780 number of times. In fact, I mentioned, I think in the green room with Frank 489 00:30:41,780 --> 00:30:45,160 and I met at this, user group meeting in Richmond in late November 490 00:30:45,780 --> 00:30:49,455 2005. I met we met Nick there as well, the 3 of 491 00:30:49,455 --> 00:30:52,995 us. And so, you know, and so Nick's awesome. 492 00:30:53,215 --> 00:30:56,580 And but he has these conversations with me as as 493 00:30:56,580 --> 00:31:00,179 well. And knowing each other that amount of time, 494 00:31:00,179 --> 00:31:04,015 first off, and then, you know, interacting, we partnered 495 00:31:04,075 --> 00:31:06,955 a little bit and and done a little bit of work. Kinda know each other's 496 00:31:06,955 --> 00:31:10,554 personalities. That's been it it's not a 497 00:31:10,554 --> 00:31:14,260 board. But it's what I would imagine 498 00:31:14,320 --> 00:31:17,760 a good board would be like. They're advisors. There's 499 00:31:17,760 --> 00:31:20,980 there's more than just a fiduciary interest, 500 00:31:21,535 --> 00:31:24,915 and this is actually love. You know, we're friends. 501 00:31:26,255 --> 00:31:28,995 So, anyway Love it. For a mutual concern. 502 00:31:29,860 --> 00:31:33,540 Yes. Yeah. Nice. Mutual concern. Did have 503 00:31:33,540 --> 00:31:37,310 you have you heard of a founder named Jeremy Clark? Does that name ring a 504 00:31:37,310 --> 00:31:41,095 bell? I haven't. I've seen the name on LinkedIn, 505 00:31:41,095 --> 00:31:44,795 but I don't I'm thinking about the casino. You have a lot. 506 00:31:46,730 --> 00:31:50,570 I'm sorry. Funny because he's a he really likes driving fast cars. 507 00:31:50,570 --> 00:31:54,385 I don't know. Anyway, Jeremy Clark, I I bring it up because 508 00:31:54,385 --> 00:31:58,005 a lot of your listeners are hustling to build something special and 509 00:31:58,544 --> 00:32:02,230 use data driven insights. This guy started, a company 510 00:32:02,230 --> 00:32:05,690 called Webmerge in 2011. Totally bootstrapped. 511 00:32:06,150 --> 00:32:09,825 I don't think he took any outside capital, maybe some friends and family. 512 00:32:11,424 --> 00:32:14,725 He built it up to 5,000,000 ARR, very 513 00:32:15,264 --> 00:32:18,920 achievable number, and he didn't have a lot of 514 00:32:18,920 --> 00:32:22,680 outside advice from boards, but what he was relentless about was 515 00:32:22,680 --> 00:32:26,475 listening to the customer feedback. Hey. I wanna do this. So his whole 516 00:32:26,475 --> 00:32:30,155 feedback, he didn't have a team of advisers or high paid PCs. He just 517 00:32:30,155 --> 00:32:33,995 listened to the customer. Interesting. Fast forward so when once he got to 518 00:32:33,995 --> 00:32:37,730 $5,000,000 right thereabouts, he sold to 519 00:32:37,730 --> 00:32:41,510 Formstack for $100,000,000. 520 00:32:42,434 --> 00:32:46,195 And he was able to achieve this in, I think, 7 years. 521 00:32:46,195 --> 00:32:49,655 So he's kind of that canonical bootstrapped hustling. 522 00:32:50,195 --> 00:32:53,860 If there was a third thing to ask to add to your first your 523 00:32:53,860 --> 00:32:57,620 earlier question, Frank, it'd be that, like, that customer centricity of, 524 00:32:57,620 --> 00:33:01,220 like, they guide you. Like, you don't need a VC to tell you what to 525 00:33:01,220 --> 00:33:04,894 do. The customer will tell you what you you know, solve this problem, solve this 526 00:33:04,894 --> 00:33:08,575 problem. They got loads of problems. So I'll mention Jeremy Clark and the 527 00:33:08,575 --> 00:33:12,080 Formstack acquisition of WebMerge as one of my 528 00:33:12,080 --> 00:33:15,620 favorite and most powerful examples Yep. Of 529 00:33:15,840 --> 00:33:19,679 customer feedback and just the what an amazing founder can 530 00:33:19,679 --> 00:33:23,525 do. Well, I'll just interject that that's very confirming to me 531 00:33:23,525 --> 00:33:26,885 because that's that's how I roll right now on customer stuff. It's 532 00:33:26,885 --> 00:33:30,649 just they they say what they want. I look at it. I 533 00:33:30,649 --> 00:33:34,409 go, yeah. Yeah. And often when they do that, Luke, 534 00:33:34,409 --> 00:33:38,025 I'll say I'll think of, oh my gosh. Yes. We can do that, and then 535 00:33:38,025 --> 00:33:41,785 we can do this. Mhmm. So it is very much a 536 00:33:41,785 --> 00:33:45,165 virtuous cycle. So Yeah. Yeah. Cool. 537 00:33:45,540 --> 00:33:49,300 Very cool. So while we're on the subject of 538 00:33:49,300 --> 00:33:52,440 kind of being data driven, 539 00:33:53,300 --> 00:33:57,025 and, so talk to me about it, Frank. How does has 540 00:33:57,025 --> 00:34:00,705 machine learning kind of, like, helped in the customer success space in terms 541 00:34:00,705 --> 00:34:04,480 of figuring out churn, retention? Like, has that 542 00:34:04,480 --> 00:34:08,239 has that helped? Is that or is it just kind of a, like, 543 00:34:08,239 --> 00:34:11,614 a, more hype than than help? 544 00:34:13,914 --> 00:34:17,594 I'd say it's more hype at this stage. For 545 00:34:17,594 --> 00:34:20,839 my function, I I've definitely seen some interesting use cases, 546 00:34:22,099 --> 00:34:25,940 but I'd say the hype far outseeds the business value at the 547 00:34:25,940 --> 00:34:29,645 moment. There's 2 use cases that have really helped 548 00:34:29,645 --> 00:34:33,324 me drive performance. 1 is figuring out 549 00:34:33,324 --> 00:34:37,110 churn. So machine learning is really good at 550 00:34:37,110 --> 00:34:38,409 taking lots of attributes, 551 00:34:40,790 --> 00:34:44,565 analyzing them for what's most correlated with churn, but you need a big 552 00:34:44,565 --> 00:34:48,244 enough sample size, so you might be at, you know, how many how many 553 00:34:48,244 --> 00:34:52,005 things can you train the model on is is really valuable in 554 00:34:52,005 --> 00:34:55,679 the instance of machine learning to reduce churn. That's a use 555 00:34:55,679 --> 00:34:58,900 case I do like. We've used, I've used XGBoost, 556 00:34:59,599 --> 00:35:03,015 which is a Kaggle grade model, and, also Random 557 00:35:03,015 --> 00:35:06,695 Forest, which is another way it's just another fancy name 558 00:35:06,695 --> 00:35:09,595 for a type of model that's trying to figure out something. 559 00:35:11,000 --> 00:35:14,760 But, yeah, that helped us reduce churn by highlighting accounts that were at 560 00:35:14,760 --> 00:35:18,059 risk that we had not known were at risk. 561 00:35:18,715 --> 00:35:22,255 So talk about unknown unknowns, machine learning is really good 562 00:35:22,715 --> 00:35:26,155 at raising flags for things that a human might look 563 00:35:26,155 --> 00:35:29,950 over. No. I think this account's fine. Actually, the machine learning 564 00:35:29,950 --> 00:35:33,550 model says you're they're actually very risky. Let's talk about 565 00:35:33,550 --> 00:35:37,115 that. That's where I've seen value case number 1. Value case number 566 00:35:37,115 --> 00:35:40,815 2 is applying large language models embedded in 567 00:35:41,195 --> 00:35:44,950 call recording software, like Gong, Chorus. The notes that you can 568 00:35:44,950 --> 00:35:48,710 get like, you record a call with a customer. The 569 00:35:48,710 --> 00:35:52,425 built in large language models now that summarize the 570 00:35:52,425 --> 00:35:56,045 notes are phenomenal. So you just saved your CSM 571 00:35:56,585 --> 00:36:00,210 an hour post call because the notes are almost turnkey. They 572 00:36:00,210 --> 00:36:03,570 pull out action items, they pull out key topics, they pull 573 00:36:03,570 --> 00:36:07,250 out filler words like, yeah, So, there's even 574 00:36:07,250 --> 00:36:10,865 coaching embedded in the the software. So Gong and 575 00:36:10,865 --> 00:36:14,464 Chorus are the the best tools I've used that machine 576 00:36:14,464 --> 00:36:18,065 learning, like, or in this case, large language models have really had an 577 00:36:18,065 --> 00:36:20,950 impact on type time saving and quality. 578 00:36:23,730 --> 00:36:27,454 No. I'll second that. I use I use Castmagic to do a 579 00:36:27,454 --> 00:36:31,304 lot of the show notes and stuff like that, and it Oh, yeah. The 580 00:36:31,304 --> 00:36:35,153 feed they've added, recording as an option and, for for do meetings, 581 00:36:35,153 --> 00:36:38,530 and it it is science fiction level good at 582 00:36:38,530 --> 00:36:42,309 that. Yeah. And if you have a customer that's 583 00:36:42,369 --> 00:36:46,115 publicly traded and you have, like, a 10 q or one of these public filings 584 00:36:46,115 --> 00:36:49,715 that big companies have to to file, you can upload that to 585 00:36:49,715 --> 00:36:53,517 chat GPT 4. And, actually, they're getting it's 586 00:36:53,640 --> 00:36:57,400 a good a good CSM should know their account. One way to 587 00:36:57,400 --> 00:37:00,940 do that, hey. Upload the s one or sorry, the 10 q, 588 00:37:01,000 --> 00:37:04,695 and I've been impressed with the output of chat 589 00:37:04,695 --> 00:37:08,535 GPT 4 and reading an s one, so you can save, you 590 00:37:08,535 --> 00:37:10,715 know, 98% of the reading time. 591 00:37:12,170 --> 00:37:15,609 So that's another time savings, but I don't know, maybe there is value in having 592 00:37:15,609 --> 00:37:19,095 them read the q the 10 q to to get deeper versus just 593 00:37:19,095 --> 00:37:22,775 getting the topical superficial summary of it. But that's 594 00:37:22,775 --> 00:37:26,215 been that's been interesting. Something I'm watching along with, like, the data 595 00:37:26,215 --> 00:37:29,690 analytics tools built into these models. Very 596 00:37:29,690 --> 00:37:32,590 cool. Yeah. Awesome. 597 00:37:33,850 --> 00:37:37,234 So, Andy pasted the, the the the 598 00:37:37,234 --> 00:37:39,095 preformed questions that we have. 599 00:37:41,154 --> 00:37:44,755 And, so the first question is, how did you 600 00:37:44,755 --> 00:37:48,580 find your way into into the space? 601 00:37:48,580 --> 00:37:52,360 Did you find the space, or did the the the space find you? 602 00:37:54,154 --> 00:37:57,194 In a past life, I was a hedge fund manager, so I've always been I've 603 00:37:57,194 --> 00:38:00,795 always loved numbers. So I'd say I 604 00:38:00,795 --> 00:38:04,590 found a love of numbers When I was, at 605 00:38:04,590 --> 00:38:07,630 Cal Poly in San Luis Obispo and I was studying numbers, I was like, I 606 00:38:07,630 --> 00:38:11,230 really like spreadsheets. So I'd say I'd say I found 607 00:38:11,230 --> 00:38:14,925 numbers, and then in when I transitioned into software, I saw, like, 608 00:38:14,925 --> 00:38:18,684 woah. This is much bigger than spreadsheets. This 609 00:38:18,684 --> 00:38:21,425 is, like, big data at scale. So then I got interested. 610 00:38:23,150 --> 00:38:26,910 Cool. That's my quick story. So we have second question is, 611 00:38:26,910 --> 00:38:29,250 what's your favorite part of your current gig? 612 00:38:31,485 --> 00:38:34,525 I love being on a Zoom call with a founder I'm meeting for the 1st 613 00:38:34,525 --> 00:38:38,065 time and seeing their absolutely unbridled 614 00:38:38,445 --> 00:38:42,220 ambition for they're gonna charge at the world and 615 00:38:42,220 --> 00:38:45,760 they're gonna make a dent in it, and I just 616 00:38:46,140 --> 00:38:49,875 it's something about the human spirit that is, I don't 617 00:38:49,875 --> 00:38:53,555 know, it just gives me the goosebumps to this day, and I get 618 00:38:53,555 --> 00:38:57,395 really excited when I have the honor of, like, meeting a founder that is 619 00:38:57,395 --> 00:39:01,119 hell bent on making the world a little bit better in 620 00:39:01,119 --> 00:39:04,260 their domain, so that gets me pretty that's definitely my favorite thing. 621 00:39:04,960 --> 00:39:08,375 Cool. So we have 3 complete this 622 00:39:08,375 --> 00:39:12,055 sentence, questions, and when I'm not working I 623 00:39:12,055 --> 00:39:13,035 enjoy blank. 624 00:39:16,020 --> 00:39:19,619 Man, I love flying airplanes, so I'm I love 625 00:39:19,619 --> 00:39:23,460 flying up in the sky, and also training for 626 00:39:23,460 --> 00:39:27,155 triathlons. I do a lot of, like, triathlon stuff, Ironman stuff, 627 00:39:27,155 --> 00:39:30,915 so I'm usually I love flying, and I love swim, 628 00:39:30,915 --> 00:39:34,215 bike, run, and, and obviously spending time with the kiddos 629 00:39:37,289 --> 00:39:41,049 and my wife. Very nice. The second1 is I think the coolest thing 630 00:39:41,049 --> 00:39:43,150 in technology today is blank. 631 00:39:47,215 --> 00:39:50,734 Man, old school answer, I still think screenshots are one of the most 632 00:39:50,734 --> 00:39:53,570 low like, screenshotting is one of the most 633 00:39:54,770 --> 00:39:58,470 simple technologies that is so pervasively used, and I think 634 00:39:58,850 --> 00:40:01,990 it's not talked about enough how amazing just a screenshot 635 00:40:02,395 --> 00:40:06,095 tool is used anyway anyway. But a more concrete answer 636 00:40:06,315 --> 00:40:09,915 is I think stable stable diffusion models are becoming next 637 00:40:09,915 --> 00:40:13,470 level. I I've seen I asked my my 3 year old 638 00:40:13,470 --> 00:40:16,930 daughter, hey, Davie, what are you thinking about? She's like, 639 00:40:17,390 --> 00:40:21,135 a rainbow unicorn. And I type in, show me if you know, create 640 00:40:21,135 --> 00:40:24,494 an image of a rainbow unicorn, and we have this, like, shared album on the 641 00:40:24,494 --> 00:40:28,000 iPhone and on the TV. So she she has all her, like, stable diffusion 642 00:40:28,000 --> 00:40:31,780 images on the TV rotating just a way to get your kids involved. 643 00:40:32,240 --> 00:40:35,615 But, I've been so impressed in, like, video is the next frontier. I mean, 644 00:40:35,615 --> 00:40:39,215 it's insane what visually these models can do 645 00:40:39,215 --> 00:40:42,815 now. That's really exciting. It is very 646 00:40:42,815 --> 00:40:46,260 impressive. My my middle child is 647 00:40:46,260 --> 00:40:49,960 into anime now. And, you know, so we 648 00:40:50,180 --> 00:40:53,845 will take, like, clips of him or him playing with the dogs, or just a 649 00:40:53,845 --> 00:40:57,685 description and say, as an anime. Right. 650 00:40:57,685 --> 00:41:00,585 He could kinda create his little little, like, anime thing. 651 00:41:01,770 --> 00:41:05,290 It's just I might have to try that with my daughter. That sounds Yeah. Yeah. 652 00:41:05,290 --> 00:41:09,130 I I I never got into anime, but, like, thanks 653 00:41:09,130 --> 00:41:12,925 to him, I can kind of I only like the 1 movie Akira from, 654 00:41:12,925 --> 00:41:16,765 like, the eighties nineties. But, like, thanks to him now, I I know about 1 655 00:41:16,765 --> 00:41:20,390 piece, demon slayer, Naruto, and there's something 656 00:41:20,390 --> 00:41:24,150 else he's watching because it's snow day. He's watching it upstairs. I can hear it 657 00:41:24,150 --> 00:41:27,849 in the background. So you got us talking about kids now. So, 658 00:41:28,085 --> 00:41:31,925 you know, stand back. My my baby girl is at, 659 00:41:32,165 --> 00:41:35,845 Virginia Tech now, doing her her 2nd semester 660 00:41:35,845 --> 00:41:39,380 there. And, I'll just I'll encourage you. Thank you. I'm 661 00:41:39,380 --> 00:41:43,220 so so, so proud of her. And my other my other daughters 662 00:41:43,220 --> 00:41:46,755 and my my 2 sons as well. They're all proud of them. They're they're 663 00:41:46,755 --> 00:41:50,195 awesome. The, the advice I always 664 00:41:50,195 --> 00:41:53,494 give dads, especially, of daughters, especially, 665 00:41:53,910 --> 00:41:57,510 is drink this in, man. Drink because like in 2 weeks, she's 666 00:41:57,510 --> 00:42:01,350 gonna be driving. It's gonna feel like that 667 00:42:01,350 --> 00:42:04,785 when you when you get there. It's just it will. 668 00:42:05,164 --> 00:42:08,924 And the other just tidbit I share 669 00:42:08,924 --> 00:42:12,305 with dads is you're it's normal for you to look back 670 00:42:12,730 --> 00:42:16,490 and say I didn't spend enough time. And it's a vicious trap, and 671 00:42:16,490 --> 00:42:20,090 it's not true. Yeah. If you spent all of your time, you would 672 00:42:20,090 --> 00:42:23,875 still look back and wish you would spend more time. Regret, wish 673 00:42:23,875 --> 00:42:27,475 you would have spent more time. Yeah. So, don't fall for that. I appreciate that. 674 00:42:27,475 --> 00:42:31,210 Absolutely. My oldest is going to high school in the fall, and 675 00:42:31,210 --> 00:42:34,970 he's ready. I'm not ready. I know. Right? I'm not ready. I 676 00:42:34,970 --> 00:42:37,964 said that to the end of the day. I'm not ready ready for him to 677 00:42:37,964 --> 00:42:41,724 go to high school either. As I said to him, because they had, like, an 678 00:42:41,724 --> 00:42:44,845 open house or whatever. I'm like, I I I can't believe it's high school already. 679 00:42:44,845 --> 00:42:48,680 I'm like, wow. And I looked at him, like, you're ready. I'm already, 680 00:42:49,780 --> 00:42:52,839 like, it's it's totally on me. A big step. Yeah. 681 00:42:53,460 --> 00:42:55,560 Keep us posted. That's a big deal. 682 00:42:57,625 --> 00:43:01,465 The next complete the sentence is, I look forward to the day when 683 00:43:01,465 --> 00:43:03,325 I can use technology to blank. 684 00:43:06,140 --> 00:43:09,280 The technology is not there yet, but when you can talk to someone in another 685 00:43:09,420 --> 00:43:12,720 language and it real time translates in the AirPods. 686 00:43:13,345 --> 00:43:17,185 Oh, nice. I feel like that's going to connect humanity at something we've 687 00:43:17,185 --> 00:43:20,865 never seen before. That's that's that's one 688 00:43:20,865 --> 00:43:24,410 that I'm personally just as someone who loves to travel and connect, 689 00:43:24,470 --> 00:43:28,310 man, would that be a game changer or what? Yeah. For sure. 690 00:43:28,310 --> 00:43:31,915 And it's almost there, Like, it's it's it's not you're right. It's not there yet, 691 00:43:31,915 --> 00:43:35,755 but, you know, it's the closest. Yeah. We're close. I mean, it's almost like, 692 00:43:36,075 --> 00:43:39,730 you know, I think we've hit another, you know, Star Trek is 693 00:43:39,730 --> 00:43:43,090 often used, cited as example of, like, leading indicators of 694 00:43:43,090 --> 00:43:46,595 technology, and it's just like, you know, the other day I was 695 00:43:46,595 --> 00:43:50,195 using we had a previous guest on the previous show that talked 696 00:43:50,195 --> 00:43:53,635 about how you can interact with ChatGpt through the Android or 697 00:43:53,635 --> 00:43:57,480 Ios app, And, like, just 698 00:43:57,480 --> 00:44:00,440 through voice, and, like, I this is very Star Trek. I could be, like, you 699 00:44:00,440 --> 00:44:02,600 know, give me an image of this or give me an answer to this. It's 700 00:44:02,600 --> 00:44:06,025 not clearly what I was looking for. Can you me? And it's just it. Yeah. 701 00:44:06,025 --> 00:44:09,484 If you watch kind of like the next generation, how they interact with the computer 702 00:44:10,105 --> 00:44:13,705 is very conversational. And I think we're seeing a lot of that evolve 703 00:44:13,705 --> 00:44:17,460 today in ways that not that long 704 00:44:17,460 --> 00:44:20,520 ago were impossible. And when you mentioned screenshots, 705 00:44:21,435 --> 00:44:24,635 the first thing I had to learn when I switched from Android to to Android 706 00:44:24,635 --> 00:44:28,355 from Ios was how to do a screenshot. Because I cannot function 707 00:44:28,555 --> 00:44:30,895 Yeah. Without the ability to do a screenshot. Right? 708 00:44:32,610 --> 00:44:36,290 Yeah. Cool. It's amazing. I'll just I'll just throw this 709 00:44:36,290 --> 00:44:39,565 out because I was, Frank and I were communicating 710 00:44:39,945 --> 00:44:43,085 when he had this leap to conversations 711 00:44:43,464 --> 00:44:47,310 with Chad g p for the app. And he 712 00:44:47,310 --> 00:44:50,830 was I I know when Frank's excited, and he was very excited about it. And 713 00:44:50,830 --> 00:44:54,190 he was like, this is so phenomenal. And I'd heard about the 714 00:44:54,190 --> 00:44:58,035 functionality, but I've just been like, I've been typing at it for, 715 00:44:58,035 --> 00:45:01,315 you know, a year, and it's been typing back to me. And I thought that 716 00:45:01,315 --> 00:45:04,994 was super cool. But hearing the enthusiasm in his voice, I was like, 717 00:45:04,994 --> 00:45:08,680 okay. I gotta get this. I I it it 718 00:45:08,680 --> 00:45:12,119 is it is game changing, and it was from a previous podcast guest who showed 719 00:45:12,119 --> 00:45:15,340 me. And I'm like, he did, like, a live demo. I'm like, no way. 720 00:45:16,425 --> 00:45:19,705 Like and it shouldn't have surprised me in the way that it did because, you 721 00:45:19,705 --> 00:45:23,545 know, voice recognition technology is, you know, not a 100%, but it's 722 00:45:23,545 --> 00:45:27,280 it's good. And then voice synthesis technology is, 723 00:45:27,580 --> 00:45:31,420 you know, better than the recognition. That's for sure. Like, it 724 00:45:31,420 --> 00:45:34,945 shouldn't surprise me combining these 3, but here I 725 00:45:34,945 --> 00:45:38,705 was just the lady with the result. So our 726 00:45:38,705 --> 00:45:42,385 last our next thing is we ask guests to share something different about 727 00:45:42,385 --> 00:45:46,150 themselves, but we always throw out, remember, it's a family 728 00:45:46,150 --> 00:45:49,850 podcast. We're trying to keep our family friendly rating and all of that. 729 00:45:52,635 --> 00:45:55,835 Let's see. You know, I heard a quote. I was reading, 730 00:45:56,555 --> 00:45:59,375 Marcus Aurelius and some of his writings, 731 00:46:00,400 --> 00:46:03,920 and there's a quote that really stuck with me. He said something like, be 732 00:46:03,920 --> 00:46:07,680 tolerant of others and strict with yourself. So one of the 733 00:46:07,680 --> 00:46:11,115 things I'm a little strict with myself on is I track everything 734 00:46:11,895 --> 00:46:15,575 I do on this, like, weird little table. Like, at the end of the day, 735 00:46:15,575 --> 00:46:18,460 I write down, did I work out? Did I stretch? Did I do this? Did 736 00:46:18,460 --> 00:46:22,060 I do that? Did and there's, like, 30 things, so I'm a little Wow. I 737 00:46:22,060 --> 00:46:25,900 kinda micromanage myself just to know, like, do am 738 00:46:25,900 --> 00:46:29,715 I capable of doing the things I say I'm gonna do? 739 00:46:30,895 --> 00:46:34,575 And so I I have a lot of data on my own personal, so that's 740 00:46:34,575 --> 00:46:38,230 a little weird. It's, like, a little neurotic, but also helpful. We're, like, oh, I 741 00:46:38,230 --> 00:46:41,830 committed to that, but I didn't do it. That's interesting. Why? 742 00:46:41,830 --> 00:46:45,430 Did I you know what I mean? So I've been trying to, like, use data 743 00:46:45,430 --> 00:46:49,015 driven insights to, like, reflect on why I do 744 00:46:49,015 --> 00:46:52,474 or don't do something I say I wanna do 745 00:46:52,775 --> 00:46:56,125 in my quarterly goal setting. So You know, that that sounds like 746 00:46:56,454 --> 00:47:00,040 spreadsheets. It it sounds like habit tracking, but 747 00:47:00,040 --> 00:47:03,880 then using the habit tracker, that data. And that's something 748 00:47:03,880 --> 00:47:07,020 that I haven't heard people speak of before. So I'm intrigued 749 00:47:07,625 --> 00:47:11,165 and inspired. I like the idea myself. Like I have 750 00:47:11,625 --> 00:47:15,380 the from for my blog and look at the the content I produce, 751 00:47:15,440 --> 00:47:18,180 I have a spreadsheet and that has kept me very honest. 752 00:47:19,200 --> 00:47:22,885 I need to do that for working out and stuff like that 753 00:47:22,885 --> 00:47:26,565 too. Like, I like that idea. I mean, it's really helpful with the with the 754 00:47:26,565 --> 00:47:30,340 physical stuff. It's really helpful. And, yeah, I'll send you 755 00:47:30,340 --> 00:47:34,100 I'll send you the a visual of you guys and we could compare notes 756 00:47:34,100 --> 00:47:37,000 because I feel like we're all trying to solve a lot of the same 757 00:47:37,825 --> 00:47:41,345 challenges in mine, that is very help that is really helpful in that 758 00:47:41,345 --> 00:47:45,185 regard. Sure. I'll share what I what I use, and, yeah, be neat neat to 759 00:47:45,185 --> 00:47:48,670 swallow this. I I actually have my blog, spreadsheet 760 00:47:48,810 --> 00:47:52,570 off there on that screen there, so reminding me that 761 00:47:52,570 --> 00:47:56,315 I'm behind schedule. So 762 00:47:56,315 --> 00:47:59,835 Audible is a sponsor of the show, and you can go to 763 00:47:59,835 --> 00:48:03,680 thedigitsroombook.com, and you can get a free audiobook on us. Do 764 00:48:03,680 --> 00:48:07,520 you do audiobooks on, either way, can you recommend a good 765 00:48:07,520 --> 00:48:10,960 book that you like? Yeah. Two recent 766 00:48:10,960 --> 00:48:14,585 ones. On the more, like, inspirational and 767 00:48:14,585 --> 00:48:17,965 entertaining, I would recommend The $1,000,000,000,000 Coach about Bill Campbell, 768 00:48:18,665 --> 00:48:22,265 written by 3 Google executives, Eric Schmidt among 769 00:48:22,265 --> 00:48:26,080 them and, Mr. Rosenberg and, the 770 00:48:26,080 --> 00:48:29,815 story of Bill Campbell is one of the most incredible stories of 771 00:48:29,974 --> 00:48:33,815 Silicon Valley, so I would point listeners to that for education and 772 00:48:33,815 --> 00:48:36,795 entertainment and just, like, learning about leadership. 773 00:48:38,020 --> 00:48:40,280 Practical, Hamilton Helmer's 774 00:48:42,740 --> 00:48:46,515 strategy book is off the charts. I forget it I 775 00:48:46,515 --> 00:48:50,355 read the hard copy. I forget if it's on audiobook, but 776 00:48:50,355 --> 00:48:54,079 it's called 7 Powers by Hamilton Helmer. I recommend it 777 00:48:54,079 --> 00:48:57,839 to every CEO I work with or fund or just 778 00:48:57,839 --> 00:49:01,680 meet, and a lot of them have started already have heard 779 00:49:01,680 --> 00:49:05,475 of it, But it's basically how to build a business. Yeah. It's really 780 00:49:05,475 --> 00:49:09,015 good. Excellent. So Yeah. 781 00:49:09,235 --> 00:49:12,720 So, where can people learn more about you and your business? 782 00:49:14,940 --> 00:49:17,820 You know, if they wanna I have some book summaries on my website. So if 783 00:49:17,820 --> 00:49:21,655 they go to dbtventures.com and they go to library, I think I 784 00:49:21,655 --> 00:49:25,095 got, like, a couple 100 books I've read and some nerdy notes I 785 00:49:25,095 --> 00:49:28,855 take because I I don't trust my memory. I read a book and I'm 786 00:49:28,855 --> 00:49:32,059 like, what was that book? So I did I try and distill it down in 787 00:49:32,059 --> 00:49:35,900 the 5 page, you know, short summaries for mostly for CEOs, honestly, 788 00:49:35,900 --> 00:49:39,495 and founders. Because they all tell me they wanna read more, 789 00:49:39,655 --> 00:49:43,095 but they have not much time. So I'm like, here's a summary. 790 00:49:43,095 --> 00:49:46,615 Maybe, you know, maybe it's valuable, maybe it's not. So, yeah, 791 00:49:46,615 --> 00:49:49,970 DBT Ventures is one way and then LinkedIn. Okay. 792 00:49:50,430 --> 00:49:54,190 Yeah. Whatever works. That that's what you spot. Okay. Well, I'll definitely be 793 00:49:54,190 --> 00:49:57,869 connecting with you on LinkedIn. We had a little exchange earlier, and I 794 00:49:57,869 --> 00:50:01,615 was I was so excited because, I love it. I love connecting 795 00:50:01,615 --> 00:50:04,495 with guests, and I was like, now I've got the link to you, and we 796 00:50:04,495 --> 00:50:08,195 can connect through that. Yeah. And me to you. I'm stoked. 797 00:50:08,335 --> 00:50:11,350 Thank you guys so much for having me. Hey. Thanks for coming. I'm glad we 798 00:50:11,350 --> 00:50:15,030 can make it work, with weather and health challenges and all 799 00:50:15,030 --> 00:50:18,845 that. Kids snow days, you know, we persevered, and thank you very 800 00:50:18,845 --> 00:50:22,545 much for your patience, and, we'll let Bailey finish the show. 801 00:50:22,924 --> 00:50:26,630 And just like that, we're at the end of another enlightening episode of the 802 00:50:26,630 --> 00:50:30,390 data driven podcast. A monumental thank you to 803 00:50:30,390 --> 00:50:34,085 our guest, Luke Diaz, for sharing his invaluable insights 804 00:50:34,085 --> 00:50:37,845 and experiences with us. Luke, your journey and 805 00:50:37,845 --> 00:50:41,599 the wisdom you've imparted today are nothing short of inspiring, and 806 00:50:41,599 --> 00:50:45,440 we're all the richer for it. To our listeners, we hope 807 00:50:45,440 --> 00:50:49,220 you've found this episode as fascinating and illuminating as we did. 808 00:50:49,945 --> 00:50:53,625 It's your curiosity and passion for knowledge that drive this show, and 809 00:50:53,625 --> 00:50:57,245 we're endlessly grateful for your company on this journey through the Datascape. 810 00:50:58,310 --> 00:51:01,690 Before we part ways, a small but significant request. 811 00:51:02,630 --> 00:51:06,470 If you enjoyed today's episode, please take a moment to rate and review 812 00:51:06,470 --> 00:51:10,175 us on your preferred podcast platform. Your feedback 813 00:51:10,235 --> 00:51:13,835 not only warms our digital heart but also helps others discover our 814 00:51:13,835 --> 00:51:17,680 podcast and join our growing community. Remember, 815 00:51:17,740 --> 00:51:21,580 whether you're scaling the next unicorn, decoding the mysteries of machine 816 00:51:21,580 --> 00:51:25,260 learning, or simply curious about the tech world, you're always 817 00:51:25,260 --> 00:51:27,655 welcome here, where data meets discernment. 818 00:51:28,755 --> 00:51:32,355 Until next time, keep crunching those numbers and questioning the 819 00:51:32,355 --> 00:51:35,955 status quo. I'm Bailey, signing off. 820 00:51:36,895 --> 00:51:38,995 Stay data driven, my friends.