#H2H 11: Why Marketing KPIs Are Not Enough w/ Mark Stouse

WEBVTT 1 00:00:05.719 --> 00:00:09.509 There's a ton of noise out there. So how do you get decision makers 2 00:00:09.630 --> 00:00:14.589 to pay attention to your brand? Start a podcast and invite your ideal clients 3 00:00:14.910 --> 00:00:24.140 to be guests on your show. Learn more at sweetphish MEDIACOM. You're listening 4 00:00:24.219 --> 00:00:28.940 to be tob grows, a daily podcast for B TOB leaders. We've interviewed 5 00:00:28.940 --> 00:00:32.179 names you've probably heard before, like Gary Vanner, truck and Simon Senek, 6 00:00:32.500 --> 00:00:36.570 but you've probably never heard from the majority of our guests. That's because the 7 00:00:36.689 --> 00:00:41.289 bulk of our interviews aren't with professional speakers and authors. Most of our guests 8 00:00:41.329 --> 00:00:45.689 are in the trenches leading sales and marketing teams. They're implementing strategy, they're 9 00:00:45.729 --> 00:00:50.240 experimenting with tactics. They're building the fastest growing BTB companies in the world. 10 00:00:50.880 --> 00:00:53.799 My name is James Carberry. I'm the founder of sweet fish media, a 11 00:00:53.920 --> 00:00:57.479 podcast agency for BB brands, and I'm also one of the CO hosts of 12 00:00:57.600 --> 00:01:00.719 this show. When we're not interviewing sales and marketing leaders, you'll hear stories 13 00:01:00.759 --> 00:01:04.310 from behind the scenes of our own business. Will share the ups and downs 14 00:01:04.349 --> 00:01:08.709 of our journey as we attempt to take over the world. Just getting well, 15 00:01:10.390 --> 00:01:19.140 maybe let's get into the show. Welcome to the BTB grows show, 16 00:01:19.340 --> 00:01:23.540 the human to human segment. I am Carlos so Dalgo, chief strategy officer 17 00:01:23.700 --> 00:01:29.140 for demand JEN, author of driving demand in the American dream, and I 18 00:01:29.219 --> 00:01:33.129 am also the host of the human to human segment, Hashtag H to h, 19 00:01:33.250 --> 00:01:38.209 for the be to be gross show. And today I have a longtime 20 00:01:38.370 --> 00:01:42.969 colleague, longtime friend. He and I go back to our days at BMC 21 00:01:42.810 --> 00:01:48.280 and mark, I think there's always a six degrees of separation from BMC software, 22 00:01:48.280 --> 00:01:52.560 as we've discussed early. Yeah, but I'm going to ask you to 23 00:01:52.760 --> 00:01:57.959 introduce yourself. So, Mark Stews Code, are founder of proof analytics, 24 00:01:57.079 --> 00:02:02.549 CEO and just killing it from a start up perspective. So mark, introduce 25 00:02:02.629 --> 00:02:07.109 yourself to our audience. Well, first of all, it's just great to 26 00:02:07.150 --> 00:02:12.629 see you again and really happy to be on this having this conversation with you. 27 00:02:13.389 --> 00:02:17.500 You know I mean. I'm a communicator turn marketer, turned business leader, 28 00:02:17.699 --> 00:02:23.819 turned CEO of a software start up. Right my life is a metamorphosis 29 00:02:24.259 --> 00:02:30.889 and then some. And essentially what proof is is we have automated marketing, 30 00:02:30.009 --> 00:02:37.169 mixed modeling, we've automated regression analytics, putting the power that has existed for 31 00:02:38.490 --> 00:02:45.560 thirty years in the fortune five hundred, but very expensively and kind of incrementally, 32 00:02:46.000 --> 00:02:50.800 and we have a harnessed it to the power of automation and now we're 33 00:02:51.280 --> 00:02:54.879 we're off for the races in a really big way. I mean marketing mixed 34 00:02:54.919 --> 00:03:00.949 modeling has been the goal standard for Understanding Marketing Rli for a long time. 35 00:03:00.270 --> 00:03:07.509 I mean it is the application of advanced regression analytics to the marketing business equation. 36 00:03:08.310 --> 00:03:12.629 It is one of those things, though, that the cost of it, 37 00:03:13.460 --> 00:03:20.860 the difficulty in scaling it and the slowness of delivery of the analytics has 38 00:03:20.900 --> 00:03:24.340 kind of kept it a rarefied discipline in the fortune five hundred for a long 39 00:03:24.379 --> 00:03:28.689 time. So you see a lot in retail, you see a lot in 40 00:03:28.810 --> 00:03:32.250 B Toc. You have not really seen it a lot in BTB until just 41 00:03:32.530 --> 00:03:38.009 recently. Part of that is the availability of data has exploded in B Tob, 42 00:03:38.490 --> 00:03:42.840 but also they're just people are starting to realize that multi touch, attribution 43 00:03:43.439 --> 00:03:46.840 and a lot of the other things, while they have a purpose and and 44 00:03:46.240 --> 00:03:53.879 they deliver value, aren't you can't use them to decide how much money you're 45 00:03:53.879 --> 00:03:59.349 going to spend and where. Yeah, and that's a really interesting viewpoint. 46 00:03:59.710 --> 00:04:02.629 Not why, it's one that I agree with, quite frankly, and I've 47 00:04:02.669 --> 00:04:06.469 talked about a lot with some of the clients that I've had over the years. 48 00:04:06.669 --> 00:04:11.060 So when you were talking about that data, we were talking a little 49 00:04:11.099 --> 00:04:15.579 bit before we came on air about the relationship. It's more than just the 50 00:04:15.620 --> 00:04:18.860 data, it's the relationship that the data has to the business. We were 51 00:04:18.899 --> 00:04:21.980 talking about the dollars, but you too, you hit on something that's near 52 00:04:23.060 --> 00:04:27.050 and dear to every CMOS heart and every marketers heart, is the allocation of 53 00:04:27.170 --> 00:04:31.050 budget. And you and I both have been in meetings before where there's a 54 00:04:31.129 --> 00:04:35.529 lot of emotion that can go around in a budget meeting. So how are 55 00:04:35.569 --> 00:04:41.720 you right now seeing that data that companies are using, fortune five hundred, 56 00:04:41.920 --> 00:04:45.240 mid market otherwise, and saying, Hey, we're going to actually use this 57 00:04:45.399 --> 00:04:47.839 to shape our behavior as a company? Where we spend, what we spend 58 00:04:47.879 --> 00:04:51.639 on, how we spend it? How are they stewarding the budget, which 59 00:04:51.639 --> 00:04:56.189 is something that marketing people don't talk a whole lot. So give me some 60 00:04:56.350 --> 00:04:59.990 flavor on that that you're you're seeing in your clients and some of the best 61 00:05:00.029 --> 00:05:02.110 practices that you've been able to encounter. Well, I think that. I 62 00:05:02.269 --> 00:05:08.779 think that the issue is that the data is really important, without doubt, 63 00:05:09.060 --> 00:05:15.180 right. The analytics without data is like a gun with no bullets, right, 64 00:05:15.259 --> 00:05:17.420 I mean it's just not going to do much for it. However, 65 00:05:17.459 --> 00:05:25.850 data is by itself a static measurement. That's it says this happened at this 66 00:05:26.209 --> 00:05:30.529 time, full stop. Right. Can You? Can you repeat that again, 67 00:05:30.529 --> 00:05:33.490 because I think that's so important. When I read Oh, it's all 68 00:05:33.490 --> 00:05:38.800 about the data, say that statement again because I want everybody to hear that. 69 00:05:39.519 --> 00:05:43.079 Sure. So the bottom line is is that it's really important, but 70 00:05:44.160 --> 00:05:47.959 it's a static measurement of something that happened at a certain time and a certain 71 00:05:48.000 --> 00:05:53.110 place and it doesn't tell you anything about why it happened, how it happened, 72 00:05:53.709 --> 00:05:58.069 what else might have impinged upon it or made it happen. It just 73 00:05:58.189 --> 00:06:01.670 says this happened, and that's important, but is in no way the end 74 00:06:01.709 --> 00:06:06.180 game, right, and so this is why we can talk about KPI's and 75 00:06:06.420 --> 00:06:12.899 it's relevant, but it is in no way the final solution to the problem. 76 00:06:13.540 --> 00:06:16.899 The final solution is all about the fact that really what we're talking about 77 00:06:16.939 --> 00:06:24.250 here is not static. It's dynamic and relational. It is. How did 78 00:06:24.370 --> 00:06:28.970 this thing impact this thing over here? And you know, a big part 79 00:06:29.009 --> 00:06:31.370 of this, particularly in B tob but also in B Toc, is the 80 00:06:31.449 --> 00:06:36.399 issue of time lag, the fact that when you make a marketing investment, 81 00:06:36.439 --> 00:06:41.519 you put something out into the market place, it does not have, for 82 00:06:41.680 --> 00:06:46.189 the most part, an immediate impact. It is there is a delayed effect. 83 00:06:46.470 --> 00:06:49.829 And then, so let's say that that you do something and there's a 84 00:06:49.910 --> 00:06:57.589 delayed effect on the beliefs in the mentality of your audience, and then so 85 00:06:57.750 --> 00:07:00.910 that took that took a while to happen, and then it's going to take 86 00:07:00.699 --> 00:07:09.660 more time for them to translate those changing beliefs, those changing understandings, into 87 00:07:09.899 --> 00:07:15.060 action in terms of buying your product. So at Honeywell Aerospace, where I 88 00:07:15.100 --> 00:07:19.889 was CMO, the time lags were months for the most part, because we 89 00:07:20.009 --> 00:07:25.050 were talking about a very long business cycle to begin with and we were talking 90 00:07:25.129 --> 00:07:32.720 about audiences that change their views very slowly and carefully. This was a function 91 00:07:32.839 --> 00:07:39.600 of risk and risk mitigation, which is kind of a dramatically underdiscussed topic and 92 00:07:39.720 --> 00:07:43.800 be to be as a rule, but it is what it's the reason why 93 00:07:44.470 --> 00:07:47.670 sale cycles and be tob are what they are, right. I mean more 94 00:07:47.709 --> 00:07:53.389 than fifty percent of it is risk mitigation and due diligence on what the vendor 95 00:07:53.509 --> 00:07:57.269 is saying. The vendor is actually, after a certain point in time, 96 00:07:57.670 --> 00:08:01.180 the source of the risk. Yes, so, so it's so fight, 97 00:08:01.300 --> 00:08:05.660 you know, coming back full circle. You have to you have all this 98 00:08:05.779 --> 00:08:11.459 data that represents this universe that's swirling around, right, and you have to 99 00:08:11.540 --> 00:08:16.089 be able to associate that data and say, okay, this is the outcome 100 00:08:16.250 --> 00:08:20.129 that we were striving for. These are the ten things that we were doing, 101 00:08:20.730 --> 00:08:24.449 hopefully to have an impact on this end game. WHAT'S THE STACK RANK? 102 00:08:24.889 --> 00:08:28.480 Right, the most powerful, second most powerful, third most powerful, 103 00:08:28.959 --> 00:08:33.879 net of time lag. So really, this is actually, I mean, 104 00:08:33.960 --> 00:08:39.600 a great analogy here for everybody is if you have a K and you manage 105 00:08:39.639 --> 00:08:43.269 it and you're called upon by your employer from time to time to re balance 106 00:08:43.470 --> 00:08:48.029 your for one ky, it's the same idea, right, you are rebouncing 107 00:08:48.110 --> 00:08:52.710 your marketing spin based upon what is actually happening out there in the marketplace. 108 00:08:54.230 --> 00:08:58.179 So it's definitely not the bit, it's not the Bitcoin of marketing, because 109 00:08:58.220 --> 00:09:01.139 I'm hearing so let me ask you, because you said something that is, 110 00:09:01.340 --> 00:09:05.340 I think, is really important because I hear this from marketers all the time, 111 00:09:05.899 --> 00:09:13.370 the pressure from the sea suite to show immediate results, and I oftentimes 112 00:09:13.370 --> 00:09:16.490 I just got on the phone yesterday with a colleague who said I'm just getting 113 00:09:16.730 --> 00:09:22.009 I'm getting hammered and they've been in the role for forty five days. So 114 00:09:22.809 --> 00:09:28.000 how should marketers use the data that they have and again, whether or not 115 00:09:28.080 --> 00:09:33.679 they have a system like prove for anything, to show and prove to and 116 00:09:33.919 --> 00:09:37.669 actually educate? I believe the sea level that marketing is not a wishing well. 117 00:09:37.669 --> 00:09:41.309 We don't drop a coin in wish for something and all the sudden leads 118 00:09:41.350 --> 00:09:46.470 populated and our revenue grows. How are you seeing or how do you advise 119 00:09:46.549 --> 00:09:50.669 your customers a proof to use the data to educate, because it really is 120 00:09:50.909 --> 00:09:54.379 that pressure in a lot of organizations. No, it's a huge pressure. 121 00:09:54.580 --> 00:10:00.059 And so I was I was in a Gbr not too long a ago with 122 00:10:00.179 --> 00:10:03.779 a brand new customers that this customer had ingested some data into proof, but 123 00:10:05.419 --> 00:10:09.850 basically they were totally the beginning of the process right, and I had I 124 00:10:09.970 --> 00:10:13.210 had met with the CMO go ahead of time and I had told him I 125 00:10:13.250 --> 00:10:16.570 said, look, you know, if you go in there and you this 126 00:10:16.730 --> 00:10:20.769 was their q two. If you go in there and you're comparing your Qto 127 00:10:20.440 --> 00:10:24.919 to the sales leaders qt, this is not going to work. Well, 128 00:10:24.480 --> 00:10:28.120 this is just not going to work. I said, I don't know what 129 00:10:28.279 --> 00:10:33.200 the time lag is, but there is a time lag in your business and 130 00:10:33.399 --> 00:10:37.309 that this is just going to be dangerous. So sure enough, you know, 131 00:10:37.389 --> 00:10:39.990 he had his own plan. So he stood up, he delivered his 132 00:10:41.309 --> 00:10:46.269 grand and glorious marketing summary For q two. Sales leaders stood up and delivered 133 00:10:46.309 --> 00:10:50.419 it. You know, pretty much a really tough report out and he ended 134 00:10:50.500 --> 00:10:58.059 up by saying, and once again we see marketings report as evidence of how 135 00:10:58.220 --> 00:11:03.289 disconnected from reality they really are. Wow, right. So I raise my 136 00:11:03.409 --> 00:11:07.730 hand in the in the in the back of the room and I say, 137 00:11:07.809 --> 00:11:11.529 Hey, you know, I'm marks to some with proof analytics. Right, 138 00:11:11.129 --> 00:11:18.039 I think that actually, this is a this is not representing what's actually happening 139 00:11:18.080 --> 00:11:22.200 here. And so we talked about time lag, we talked about the fact 140 00:11:22.200 --> 00:11:30.960 that that marketing impact and sales impact are asynchronous across time and space. And 141 00:11:31.159 --> 00:11:33.870 then, if you it's one thing to kind of know this conceptually, and 142 00:11:33.950 --> 00:11:37.669 I think that a lot of people do know kind of conceptually, but if 143 00:11:37.710 --> 00:11:43.710 you can't say this is the timeline and this is the point in the calendar 144 00:11:43.830 --> 00:11:48.500 where you're going to see the results from this, you're going to have and 145 00:11:48.659 --> 00:11:50.860 so we I actually, I mean you want to talk about high wire act. 146 00:11:50.980 --> 00:11:54.740 I mean it was kind of where I rushed in, where angels here 147 00:11:54.899 --> 00:12:00.860 to bread and finally importulate. But I pulled a proof on their big screen 148 00:12:01.340 --> 00:12:05.610 and I did a real life demo with their data right there, not knowing 149 00:12:07.250 --> 00:12:09.769 what the answer was going to be. Right, right, sure enough. 150 00:12:09.809 --> 00:12:16.679 Right, marketing and sales are separated by about five quarters. So I said, 151 00:12:16.279 --> 00:12:20.200 marketings q two had absolutely nothing to do with your qt. Right. 152 00:12:20.320 --> 00:12:28.480 Nothing. Well, right, your your Qtwo was impacted by the previous what 153 00:12:28.679 --> 00:12:31.389 que, a year and a border. Right, and I said so, 154 00:12:33.029 --> 00:12:35.909 there is no hey, you know what, we're halfway through the quarter. 155 00:12:37.429 --> 00:12:41.990 We know we need marketings helped pull out this quarter. That's just not happening 156 00:12:41.269 --> 00:12:46.299 in this business. In some businesses you could, because the cycle time is 157 00:12:46.419 --> 00:12:50.139 tight enough, but not in this one, and there's many other make it 158 00:12:50.379 --> 00:12:56.059 right where the die is cast. And so one of the things that this 159 00:12:56.379 --> 00:13:03.289 means in many be to be marketing organizations is that the risk on their sin 160 00:13:03.610 --> 00:13:09.330 is back in loaded, and so that means that they won't know for a 161 00:13:09.450 --> 00:13:15.679 long time really what unless they have analytics, unless they're running regression right, 162 00:13:16.279 --> 00:13:22.559 they won't know whether they're even on track. You have a good outcome right 163 00:13:22.440 --> 00:13:26.429 in five quarters, and so you have to this is where regression become so 164 00:13:26.549 --> 00:13:31.470 critical. You know, it's the it's the early warning system. Right, 165 00:13:31.629 --> 00:13:35.230 it's hey, you know, this is the track we're supposed to be on, 166 00:13:35.909 --> 00:13:39.669 you know, but we're actually down here and it doesn't look like things 167 00:13:39.710 --> 00:13:43.259 are going to get better. So maybe we ought to kill this thing early, 168 00:13:43.779 --> 00:13:48.860 before we have spent every last time in the budget on this, right, 169 00:13:48.860 --> 00:13:52.179 because probably not going to get better. Yep. So this is a 170 00:13:52.620 --> 00:13:56.850 that's a really important statement here. And you're not going to get that same 171 00:13:56.929 --> 00:14:01.970 level insight from the raw data that. That's not my opinion. That's just 172 00:14:03.129 --> 00:14:05.769 a mathematical fact. Now, and I agree with that, and that's, 173 00:14:05.970 --> 00:14:11.559 you know, to me, data without context is just data. So one 174 00:14:11.600 --> 00:14:13.679 of the things I hear, one of the pushbacks I hear from CMOS, 175 00:14:15.039 --> 00:14:18.200 svp's marketing, whoever, whether they agree with you or not, oftentimes you 176 00:14:18.279 --> 00:14:22.879 hear yeah, but we're built to be a data science organization. Or, 177 00:14:24.590 --> 00:14:26.990 you know, there's there's so much data we don't even know how to begin. 178 00:14:28.029 --> 00:14:31.870 or The you know, we look at the numbers and they don't tell 179 00:14:31.909 --> 00:14:35.990 a story. So what kind of skill set really, just at the human 180 00:14:35.029 --> 00:14:37.820 level, are you seeing? To say, it's one thing to show a 181 00:14:37.860 --> 00:14:43.139 dashboard, it's another thing to know the story, about the backstory and then 182 00:14:43.139 --> 00:14:48.940 the future story of what that Dashboard is showing. So what kind of skill 183 00:14:48.019 --> 00:14:52.649 set are you seeing? Whether it's from a marketing organization? I've even said 184 00:14:52.690 --> 00:14:56.490 go, go partner with your bi group. If you can't figure it out, 185 00:14:56.289 --> 00:14:58.809 what do you see in in the market right now that marketing teams are 186 00:14:58.850 --> 00:15:03.649 doing to enhance that skill set? Well, it's without a doubt it is 187 00:15:03.690 --> 00:15:09.679 always a collective solution. So if you know, you can go out and 188 00:15:09.759 --> 00:15:16.240 hire ten PhDs and data science and they will absolutely know how to crunch your 189 00:15:16.279 --> 00:15:20.990 data, but they will have no domain knowledge right on your business or marketing 190 00:15:22.070 --> 00:15:26.750 or anything else. So there's a term and data science that essentially gets to 191 00:15:26.830 --> 00:15:31.149 the heart of this problem and that's packing pacting. It is running all kinds 192 00:15:31.190 --> 00:15:37.019 of correlation and regression analytics without a thesis, without an understanding, without any 193 00:15:37.100 --> 00:15:43.179 domain knowledge, you're just kind of like everything against everything and we're just going 194 00:15:43.179 --> 00:15:46.899 to kind of look at what pops out right. And there is actually a 195 00:15:46.940 --> 00:15:50.490 time and a place to do that, but not on a regular basis. 196 00:15:50.769 --> 00:15:56.929 And so the flip of that relationship. So so the the data scientists need 197 00:15:56.049 --> 00:16:00.649 the marketers in the business people to help guide them, them to help all 198 00:16:00.730 --> 00:16:06.159 the right models to answer the right questions. That's the essence of that. 199 00:16:06.720 --> 00:16:11.639 The marketers and the business people need the analysts to do this work or they 200 00:16:11.720 --> 00:16:17.080 need software to help do this work right, because they don't have a freaking 201 00:16:17.200 --> 00:16:19.750 clue most of the time how to do it right. And even though I 202 00:16:19.870 --> 00:16:22.350 mean this is this is kind of, you know, funny. It's cool, 203 00:16:22.509 --> 00:16:26.950 but it's also funny. So I was just named, much to my 204 00:16:26.149 --> 00:16:33.299 great and enduring surprise, right one of the top ten most influential analytics leaders 205 00:16:33.379 --> 00:16:36.940 in the world for two thousand and twenty that congrats. Yeah, no, 206 00:16:37.299 --> 00:16:41.220 and and it is really cool, but I am not a mathematician. If 207 00:16:41.259 --> 00:16:45.580 you ask me to do this, I would bust right. It's kind of 208 00:16:45.580 --> 00:16:51.370 like when you and I were at BMC I could talk about data center automation. 209 00:16:51.929 --> 00:16:56.529 I was totally fluent and all that stuff, but if you put me 210 00:16:56.690 --> 00:17:00.289 in a in a data center and said turn it on, I would know 211 00:17:00.330 --> 00:17:03.839 how to turn it off exactly. I wouldn't know how to operate it, 212 00:17:04.240 --> 00:17:08.000 right. I mean all I am as an empty suit at that point, 213 00:17:08.160 --> 00:17:14.279 right. And so, but my skill set is actually in being able to 214 00:17:14.839 --> 00:17:18.829 listen to the data scientists and I know enough about their world to ask the 215 00:17:18.869 --> 00:17:22.309 right questions, to listen to the marketers and listen to the business people and 216 00:17:22.509 --> 00:17:27.430 kind of bring it all together. So I am a professional con Sumer of 217 00:17:27.549 --> 00:17:32.299 analytics. Right, I'm a I'm a kind of a little bit of a 218 00:17:32.339 --> 00:17:37.339 maybe even a connoisseur of analytics from the standpoint that I'm very just you know, 219 00:17:37.460 --> 00:17:41.299 I can differentiate, I can distinguish and I know kind of what is 220 00:17:41.420 --> 00:17:47.130 the best thing to use in a particular situation. So I don't ask anymore. 221 00:17:47.170 --> 00:17:48.410 I used to do it all the time, but anymore I don't ask 222 00:17:48.450 --> 00:17:52.890 a lot of dumb questions, you know. But that's really what makes me 223 00:17:52.930 --> 00:17:57.210 an influential analytics leader. It's not. I mean, I'm in there the 224 00:17:57.289 --> 00:18:03.279 other nine guys they're all phds and data science, they're all mathematicians. So 225 00:18:03.480 --> 00:18:06.680 it it's sort of like one of those things where you just kind of go, 226 00:18:07.279 --> 00:18:11.079 okay, right, I'll think they're yeah, I'll take it all day 227 00:18:11.119 --> 00:18:14.509 long. So from a market or perspective, who is sitting there? They're 228 00:18:14.509 --> 00:18:17.269 saying, yeah, I'm not. I always I kind of make a joke 229 00:18:17.309 --> 00:18:18.910 to where I say, Hey, sucked at mass so I got into marketing 230 00:18:18.990 --> 00:18:25.430 right. But from that perspective, you're in a whether you're an enterprise or 231 00:18:25.549 --> 00:18:29.019 mid market or an SMB, you're still going to have the CEO who's saying 232 00:18:29.740 --> 00:18:33.019 that's kind of how I got into the business I'm in. As my president 233 00:18:33.059 --> 00:18:34.099 said, I gave you a dollar. What are you turning back for it? 234 00:18:34.180 --> 00:18:37.420 If you can't figure it out, your replacement will. Where can they 235 00:18:37.539 --> 00:18:41.450 start to not that they've got to go get their PhD in analytics, but 236 00:18:41.609 --> 00:18:45.529 where can they go to find or what steps would you recommend for them to 237 00:18:45.569 --> 00:18:51.009 say at least get to that connoisseur level, because when I see people going 238 00:18:51.250 --> 00:18:53.609 we do dat a driven marketing, honestly it makes my teeth hurt because I'm 239 00:18:53.650 --> 00:18:57.880 like do you? Yeah, I really. If anything, the so the 240 00:18:57.960 --> 00:19:02.000 main reason why I think you hear so much about data driven is that it's 241 00:19:02.000 --> 00:19:07.319 a littered alliterative right. It's yeah, but if anything, you should be 242 00:19:07.400 --> 00:19:12.430 analytics led, not data driven. I like that and that's really the deal 243 00:19:12.509 --> 00:19:17.910 they're now in terms of the way forward. I think the number one you 244 00:19:18.150 --> 00:19:22.269 have to begin to understand the language of business, which is numbers, it 245 00:19:22.509 --> 00:19:26.700 is finance. It's not necessary for you to become an accountant, right, 246 00:19:27.220 --> 00:19:33.299 but at BMC and at Honeywell, I rotated all my teams wherever they were 247 00:19:33.380 --> 00:19:38.529 in the world, through a local finance for non financial managers class. You 248 00:19:38.650 --> 00:19:44.849 know, most universities, most colleges have that. You know they it's really 249 00:19:44.890 --> 00:19:48.890 important, right to have a basic fluency in it. The other thing we 250 00:19:48.970 --> 00:19:55.000 did was we rotated everybody, particularly at BMC but also at Honeywell, through 251 00:19:55.240 --> 00:20:00.400 sales enablement training, sales training right the week long. You know, Mosh 252 00:20:00.559 --> 00:20:07.750 pit from Hell, you know experience, because it really gave all my guys 253 00:20:07.789 --> 00:20:11.269 a lot of knowledge, a lot of understanding, a lot of empathy and 254 00:20:11.430 --> 00:20:15.910 a lot of great relationships with sales teams. That then became really important. 255 00:20:17.589 --> 00:20:19.309 Now last thing is, and this is actually one of the things that we 256 00:20:19.390 --> 00:20:25.980 discovered, certainly a year to two years ago, with proof, is that 257 00:20:26.420 --> 00:20:30.859 you can't really show up in the marketing analytics space or even other like HR 258 00:20:30.940 --> 00:20:37.930 analytics. You can't really show up as a pure sass offering and be successful. 259 00:20:37.450 --> 00:20:45.970 There's just not enough skill and capacity and capability within these organizations to run 260 00:20:47.049 --> 00:20:51.279 it and people are going to get frustrated and it's just going to kind of 261 00:20:51.400 --> 00:20:56.720 suck. Right. And so, even though we had built this beautiful automated 262 00:20:56.759 --> 00:21:03.309 Sass Platform, we came to conclusion that we had to deliver it most of 263 00:21:03.349 --> 00:21:07.029 the time. We had to deliver it as a man is service, and 264 00:21:07.950 --> 00:21:15.309 people really like that, even if we're very mature already. So they didn't 265 00:21:15.309 --> 00:21:18.339 need help. They were like, you mean, I can have you run 266 00:21:18.420 --> 00:21:22.420 this for me and it's just cost me a little bit extra and that means 267 00:21:22.539 --> 00:21:26.980 my guys can go do other things. They took that in a heartbeat. 268 00:21:26.299 --> 00:21:32.019 Right. So I think that that is right now. And we you know, 269 00:21:32.299 --> 00:21:37.569 you'll remember this at BMC, right it service management huge dirty curve. 270 00:21:37.690 --> 00:21:42.289 Right, this is the same situation and people are strung out all along this 271 00:21:42.609 --> 00:21:48.799 curve. And so, as a former CMO, right, I mean running 272 00:21:48.799 --> 00:21:52.799 this business, the one of the things really important for us is segmentation. 273 00:21:52.839 --> 00:21:56.880 Right. So who we should be really talking to right now, because we 274 00:21:56.920 --> 00:22:00.630 can't afford to talk to everybody. But that said, right, you have 275 00:22:00.750 --> 00:22:06.150 to nurture in some way, shape or form, the entire curve, because 276 00:22:06.190 --> 00:22:10.630 its people come up the curve and they are ready for something like proof, 277 00:22:11.390 --> 00:22:15.819 it becomes really important that they know about you. Right. So last thing, 278 00:22:15.940 --> 00:22:18.619 the last thing I just say about this, real quick of course, 279 00:22:18.460 --> 00:22:25.779 is that it's really important to understand how this all evolved. So people are 280 00:22:25.819 --> 00:22:30.329 doing all kinds of marketing and PR and all this kind of stuff for years 281 00:22:30.970 --> 00:22:34.490 and then, beginning about twenty five years ago, they came under significant pressure 282 00:22:36.089 --> 00:22:41.450 to for the first time, to prove stuff, hmm. And so all 283 00:22:41.529 --> 00:22:45.839 they need to do, given the state of Technology and state to the world, 284 00:22:45.200 --> 00:22:48.640 right, is to begin to measure things. And so they were just 285 00:22:48.880 --> 00:22:52.640 measuring that, which they were doing at the time, right. Yeah, 286 00:22:53.000 --> 00:22:59.789 that is colored the mindset on this whole thing for agents. Right. The 287 00:23:00.029 --> 00:23:06.309 reality is is actually that that's you're starting at the wrong end of the pole, 288 00:23:06.670 --> 00:23:08.950 so to speak, if you start there. The place that you really 289 00:23:08.990 --> 00:23:12.619 have to start is one am I seat? What is my CEO, my 290 00:23:12.740 --> 00:23:15.819 CFO, my business leaders? What do they want to know? What of 291 00:23:15.900 --> 00:23:22.220 their top end questions? Those top ten questions will spawn one or more models. 292 00:23:23.099 --> 00:23:26.690 So these are analytical models. These are sort of think of it is 293 00:23:26.730 --> 00:23:33.809 that your hypothesis of how you think things are adding up, how they're impacting 294 00:23:33.930 --> 00:23:38.890 each other in to achieve something right that they're interested in. Once you have 295 00:23:40.009 --> 00:23:44.720 the model, you have to instrument the model, and that's the data right, 296 00:23:45.200 --> 00:23:48.839 but you're usually not. You're most of the time you're using maybe twenty 297 00:23:48.920 --> 00:23:52.599 percent of the data that you've collected overall. So all, there's a lot 298 00:23:52.680 --> 00:23:57.990 of data that you're collecting through measurement. That is sort of maybe not something 299 00:23:59.069 --> 00:24:02.589 you should be collecting too much longer. I mean it's very expensive to do 300 00:24:02.789 --> 00:24:07.789 that. So move you know, this is a process of reverse engineering. 301 00:24:07.029 --> 00:24:11.859 You starting with what the business wants to know and you just kind of move 302 00:24:11.140 --> 00:24:17.380 through the process of scientific discovery, which is really what undergirds all this, 303 00:24:17.980 --> 00:24:19.859 and you say, okay, now I've got them, I got my question 304 00:24:19.980 --> 00:24:22.740 that I have to answer, I've got the model which theoretically is going to 305 00:24:22.779 --> 00:24:26.569 provide the answer, I've got the data in the model and now I can 306 00:24:26.569 --> 00:24:30.809 hit compute and it's going to give me an answer and then I'm going to 307 00:24:30.930 --> 00:24:34.769 say, Huh, I wonder if I can make this an even better model 308 00:24:36.089 --> 00:24:40.440 by introducing some additional data for it. Kind of perspective. You know, 309 00:24:40.480 --> 00:24:42.599 we're going to create a different model, we're going to explore that. That's 310 00:24:42.720 --> 00:24:47.079 really be the way that this works, right. So it's not a bottoms 311 00:24:47.119 --> 00:24:52.240 up, it's a tops down, not organizationally, but water the tops down 312 00:24:52.599 --> 00:24:56.670 and then once you fill in all these blanks tops down, you hit compute 313 00:24:56.789 --> 00:25:00.150 and it comes right back up to the top. And in the end what 314 00:25:00.269 --> 00:25:03.869 you're really trying to do is you're trying to say, okay, this is 315 00:25:03.150 --> 00:25:07.420 how I'll shook out, this is what's really working, this is what's not 316 00:25:07.579 --> 00:25:10.099 really working. We're going to stop doing that, we're going to do more 317 00:25:10.140 --> 00:25:12.819 of this and we're going to take all that we're going to plug that into 318 00:25:12.819 --> 00:25:18.460 our planning and budgeting for next time. And that you've got the full loop 319 00:25:18.579 --> 00:25:22.329 right, the full life stuck right. So you said something about tops down 320 00:25:22.410 --> 00:25:26.690 and let me give you my perspective. And then you also likened to the 321 00:25:26.849 --> 00:25:32.289 its, the mental Idsm the IT service management, that we worked on a 322 00:25:32.410 --> 00:25:36.359 BMC when we were both there. Yeah, I would. I would say, 323 00:25:36.400 --> 00:25:38.839 and I'm curious to your thought, that this is we are at a 324 00:25:38.960 --> 00:25:45.200 point, especially in B to be where this is an imperative that marketing groups 325 00:25:45.279 --> 00:25:48.240 get their arms around. And here's why. A stat from Mackenzie that's at 326 00:25:48.240 --> 00:25:55.190 over eighty five percent of CEOS are now looking at marketing as a growth driver 327 00:25:55.789 --> 00:25:59.950 and only twenty three percent are saying you're actually meeting that mark. So if 328 00:26:00.069 --> 00:26:06.099 I am a marketing executive, that is my ocrap moment to say, Oh 329 00:26:06.339 --> 00:26:10.579 so if I'm going to go talk to my CEO, that's a conversation that 330 00:26:10.619 --> 00:26:12.220 I'm going to have. Of I can't walk away going wow, we just 331 00:26:12.460 --> 00:26:17.660 we can't do that. CEO's are already we know they're looking for growth, 332 00:26:17.819 --> 00:26:22.250 we know they're looking for revenue creation from marketing. So our am I being 333 00:26:22.289 --> 00:26:26.170 too much of an alarmist here, or it's truly an imperative for marketing groups 334 00:26:26.210 --> 00:26:30.890 that and executive that actually want to survive and thrive? Absolutely, and I 335 00:26:30.009 --> 00:26:34.839 think that what's happening right now. So this is March, the fifth the 336 00:26:34.960 --> 00:26:41.680 market dropped nine hundred fifty points today, righting the gains from yesterday. High 337 00:26:41.720 --> 00:26:48.230 volatility, great uncertainty, increasing fear. You're going to see, even if 338 00:26:48.269 --> 00:26:53.269 you don't see a true economic correction, you're going to see a correction in 339 00:26:53.589 --> 00:26:57.750 the mindset of business leaders. Yep, and you're going to start tightening it 340 00:26:57.829 --> 00:27:02.339 up, and they're already starting to tighten it up. Yes, and so 341 00:27:02.740 --> 00:27:11.019 if you are be to be and your impact is obscured by time lag to 342 00:27:11.099 --> 00:27:15.890 begin with and by the complexity of the business you I'm just going to be 343 00:27:15.970 --> 00:27:19.730 super clear on this, you cannot measure your way out of that hole. 344 00:27:22.130 --> 00:27:26.730 It is just not happening. You're right, just not. I'm not trying 345 00:27:26.730 --> 00:27:30.279 to be difficult and I'm not I'm not trying to be false alarmists. Right, 346 00:27:30.039 --> 00:27:33.880 it's just talked to the data scientists. They'll say the same thing. 347 00:27:33.279 --> 00:27:38.920 Right. So you're going to have to start using regret, because you're going 348 00:27:38.960 --> 00:27:45.029 to have to understand the relationships between everything that you're doing and everything that business 349 00:27:45.109 --> 00:27:48.029 care is about and everything in between. You're going to have to understand the 350 00:27:48.150 --> 00:27:52.910 time lag so that you can calibrate expectations. You're going to have to deal 351 00:27:52.990 --> 00:27:59.140 with budget cuts that you cannot peanut butter right. That's going to work anymore. 352 00:27:59.500 --> 00:28:06.059 You're going to have to identify what is really secondary and tertiary priority in 353 00:28:06.180 --> 00:28:10.220 your marking Spin and you're going to have to whap that so that you can 354 00:28:10.380 --> 00:28:15.130 really preserve and even strengthen the stuff that's most important. And if you don't 355 00:28:15.130 --> 00:28:18.250 use regression, you will not be able to know what that is for a 356 00:28:18.329 --> 00:28:23.289 fact. I mean that's just again the truth. Yeah, you won't get 357 00:28:23.329 --> 00:28:27.039 pushed back here and it's it is amazing to me when I see CMOS and 358 00:28:27.359 --> 00:28:33.720 executives and marketing actually run from this, and I'm my thing just in all 359 00:28:33.799 --> 00:28:36.720 the data and even in the CEOS that I speak to. You need to 360 00:28:36.759 --> 00:28:38.680 be running towards it. You need to embrace this and yes, it is 361 00:28:38.720 --> 00:28:42.670 a massive sea change. To your point, when you said twenty five years 362 00:28:42.670 --> 00:28:47.190 ago, I had visions of Jeff Honeycomb in my head saying what do you 363 00:28:47.230 --> 00:28:49.430 I've given you this much money. How much did you return back to the 364 00:28:49.549 --> 00:28:52.549 organization? And we did have to say, you know, what we put 365 00:28:52.589 --> 00:28:57.180 in today is not going to produce tomorrow because we have a sales cycle or 366 00:28:57.220 --> 00:29:02.579 a bicycle in that enterprise. That's nine to twelve months. So if we're 367 00:29:02.619 --> 00:29:06.259 not investing now, you can expect that hit to come later down the road. 368 00:29:06.460 --> 00:29:08.339 That's right. So here's the other thing that really plays into this, 369 00:29:08.460 --> 00:29:12.849 and you just touched on it, right. The sales contribution, right, 370 00:29:14.170 --> 00:29:18.569 is linear. Yes, if I hire a certain point in the maturity of 371 00:29:18.609 --> 00:29:22.450 the company, I know that if I hire two more sales guys, I'm 372 00:29:22.490 --> 00:29:26.480 going to get x amount more revenue. Yep, and it's going to happen. 373 00:29:26.480 --> 00:29:30.359 I mean there's certainly a there is time lag there. There is not 374 00:29:30.519 --> 00:29:33.200 only time lag in the deal, right, but there's also time lag in 375 00:29:33.759 --> 00:29:38.630 bringing a sales rep from being unproductive to productive. Right, right, but 376 00:29:40.029 --> 00:29:45.269 it's not you know what it can be from a marketing perspective. HMM. 377 00:29:45.670 --> 00:29:52.220 So it's what's actually amazing is how much marketers have gotten absolutely right just by 378 00:29:52.500 --> 00:29:57.380 intuition. Yes, so, for example, one of the things that you 379 00:29:57.539 --> 00:30:03.420 hear a lot and be to be is consistency matters. That is actually really 380 00:30:03.579 --> 00:30:11.210 true, but they don't necessarily know why. The reason why it matters so 381 00:30:11.369 --> 00:30:15.970 much is that the time lags are so significant that if you've got a lot 382 00:30:15.009 --> 00:30:22.160 of oscillation like this, it's just going to whip saw through your extended impact 383 00:30:22.680 --> 00:30:25.799 right and it's just going to be weird. It's just not going to work 384 00:30:26.039 --> 00:30:32.000 right. So you would be better off actually having a lower spin than you 385 00:30:32.039 --> 00:30:37.630 would ideally like. That is pretty much locked in and what you do with 386 00:30:37.789 --> 00:30:41.710 it based on what the analytics are telling you changes. Yeah, no, 387 00:30:41.990 --> 00:30:47.789 agree, agree, a hundred percent. You know, I I could literally 388 00:30:47.829 --> 00:30:49.500 sit and talk about this stuff. My kids always tease me that I geek 389 00:30:49.579 --> 00:30:55.460 out on on the this marketing stuff. Obviously, mark, you're really passionate, 390 00:30:55.779 --> 00:31:00.859 but we are at time. So before we wrap up, where can 391 00:31:00.660 --> 00:31:04.009 listeners find out more about proof analytics? Where can they find you? I 392 00:31:04.130 --> 00:31:07.009 know you do a lot of speaking as well, so just give them some 393 00:31:07.170 --> 00:31:11.809 of that detail. Sure, absolutely so. Proof analytics. Dot Ai is 394 00:31:11.930 --> 00:31:19.519 the website. So proof and then analytics and then dot AI. My twitter 395 00:31:19.920 --> 00:31:27.880 is at marks douice. The proof analytics twitter feed is proof analytics. So 396 00:31:29.119 --> 00:31:30.799 you can find me there. You can certainly find me on Linkedin. On 397 00:31:30.960 --> 00:31:37.150 very active on Linkedin. Sure, a lot of content so and I also 398 00:31:37.230 --> 00:31:40.549 I do get around. In fact, you know, in about a week 399 00:31:40.589 --> 00:31:44.630 or so I'm supposed to be at south by. We're just doing you know, 400 00:31:44.789 --> 00:31:48.460 but I'm we're trying to figure out whether that's actually going to happen now. 401 00:31:48.019 --> 00:31:51.539 Yeah, that's up in the air as of this morning, especially with 402 00:31:51.619 --> 00:31:56.779 IBM and twitter and others pulling out absolutely and, and you know I mean 403 00:31:56.220 --> 00:32:00.099 talking about human to human, right. I mean, there's nothing in my 404 00:32:00.259 --> 00:32:04.970 business that's worth me getting sick or anyone else getting sick. Right, so, 405 00:32:05.289 --> 00:32:08.730 right, so I may hunt for that reason, but we're just trying 406 00:32:08.769 --> 00:32:12.130 to kind of figure it out right now. All right. Well, mark, 407 00:32:12.170 --> 00:32:15.319 thanks so much for sharing your time, sharing your knowledge and experience. 408 00:32:15.880 --> 00:32:19.640 You know, while we did work at BMC, we actually reconnect it of 409 00:32:19.640 --> 00:32:22.400 all places, if you remember, and a United Club Lounge and Chicago. 410 00:32:22.920 --> 00:32:25.119 That's right. We just know we're like, wait a minute, out of 411 00:32:25.200 --> 00:32:30.430 context that I know that guy. So I'm thrilled that that Sarendipity occurred and 412 00:32:31.349 --> 00:32:35.990 just that we're friends and it's been almost twenty years that you've put up with 413 00:32:36.069 --> 00:32:37.990 me. So thank you so much for being a guest. This is going 414 00:32:38.029 --> 00:32:44.539 to be a rap on the BB gross show. Tune in for podcasts like 415 00:32:44.779 --> 00:32:49.740 this and many other thanks to mark and his entire team and go check them 416 00:32:49.779 --> 00:32:57.900 out at proof analytics dot AI. I hate it when podcasts incessantly ask their 417 00:32:57.980 --> 00:33:00.369 listeners for reviews, but I get why they do it, because reviews are 418 00:33:00.490 --> 00:33:05.569 enormously helpful when you're trying to grow podcast audience. So here's what we decided 419 00:33:05.650 --> 00:33:07.369 to do. If you leave a review for me to be growth in apple 420 00:33:07.450 --> 00:33:13.400 podcasts and email me a screenshot of the review to James at Sweet Fish Mediacom, 421 00:33:13.720 --> 00:33:16.039 I'll send you a signed copy of my new book, content based networking, 422 00:33:16.279 --> 00:33:20.359 how to instantly connect with anyone you want to know. We get a 423 00:33:20.400 --> 00:33:22.839 review, you get a free book. We both win.