Executive RoundtableAI Marketing-Led Growth (AI-MLG)

1
00:00:12.200 –> 00:00:23.100
Julia Nimchinski : Welcome back to the AI Led Growth Summit. Over the next 3 days we’ll explore AI’s impact on product led partner led marketing sales and community led growth

2
00:00:23.340 –> 00:00:25.520
Julia Nimchinski: and many more Gtn trends

3
00:00:25.710 –> 00:00:33.730
Julia Nimchinski: with over 50 Cxos and thousands of AI technologies. Demos. This is where B. 2 B’s future takes shape.

4
00:00:34.260 –> 00:00:36.640
Julia Nimchinski: How are you doing all our panelists?

5
00:00:37.380 –> 00:00:37.930
Jonathan Milne: Good.

6
00:00:37.930 –> 00:00:38.970
Robin Daniels: Very good.

7
00:00:38.970 –> 00:00:39.410
Amanda Kahlow: Great.

8
00:00:40.670 –> 00:00:41.680
Julia Nimchinski: Excited at all.

9
00:00:44.195 –> 00:00:45.440
Amanda Kahlow: Let’s do it this.

10
00:00:46.240 –> 00:01:06.380
Julia Nimchinski: Amazing. Everyone who’s watching. Please follow along the conversation in our Hsc slack events, channel and just check out on the upper right corner. You see a lot of innovative demos, innovative sponsors. Check them out. Don’t forget it and kick things off.

11
00:01:06.650 –> 00:01:11.570
Julia Nimchinski: We have Jonathan Milne with the AI marketing led growth panel.

12
00:01:12.040 –> 00:01:21.819
Julia Nimchinski : Jonathan is a Vp. Of marketing services and demand spring where where he helps companies integrate AI surprise into their marketing strategies.

13
00:01:22.100 –> 00:01:24.130
Julia Nimchinski: Jonathan. Welcome to the show.

14
00:01:24.130 –> 00:01:32.179
Jonathan Milne: Thank you, Julia. Thanks so much for having me. I’m super excited to be here today, and yes, I am real, and not an AI avatar, or am I? We’ll soon find out.

15
00:01:33.890 –> 00:01:36.410
Robin Daniels: With that background we never know. Right?

16
00:01:36.410 –> 00:01:38.480
Amanda Kahlow: Never know this. Yeah, exactly.

17
00:01:38.480 –> 00:01:42.314
Amanda Kahlow: I am not real. This is the Amanda avatar.

18
00:01:42.990 –> 00:01:43.490
Amanda Kahlow: That’s right.

19
00:01:45.690 –> 00:01:57.569
Julia Nimchinski: One question, one question for me, and just passing the microphone to you. Jonathan, what’s 1 AI trend that will define marketing for 2025.

20
00:01:58.185 –> 00:02:26.699
Jonathan Milne: That’s gonna be my last question for the group today. But I think 2025. We’re gonna see a very interesting trend around the edge. AI around browser based AI. So the idea of using compute use or the idea that AI can take control of a computer and enable us to do a whole bunch of things that we’re not able to do before. I think, is going to be a pretty interesting trend. And we’re gonna see a lot more about it. And the the limited barrier this year is going to be the cost. So once they get the cost down, you’re gonna see this go up and up in use.

21
00:02:28.260 –> 00:02:34.719
Julia Nimchinski: Interesting. Didn’t think about it this way. You got a floor. And yeah, let’s kick things off.

22
00:02:35.380 –> 00:02:57.469
Jonathan Milne: Awesome. Well, I thought I’d introduce our panelists so a little bit about myself and demandspring, we are leading b 2 b marketing, consulting firm that works with visionary marketing and revenue leaders to help drive AI led growth strategies and enable them to optimize their marketing automation platforms, including Marketo, Hubspot and salesforce. So I’m sure if you’re a marketing person here on this call, you probably use one of those platforms and need some help.

23
00:02:57.770 –> 00:03:08.189
Jonathan Milne: But let’s jump into our panelists in no particular order. Let’s start off with our 1st panelist, Amanda Calo, CEO, and founder of one mind and former founder, and CEO of 6 sense.

24
00:03:08.280 –> 00:03:31.689
Jonathan Milne: Amanda’s leadership is fueled by a mission to create technology that drives growth and innovation while elevating the human experience. She is redefining the future of B. 2 B. And go to market strategies by replacing sales teams with AI superhumans, intelligent, human-like AI, that engage prospects, qualify pitch, demo, and close deals with unparalleled accuracy, efficiency and buyer delight.

25
00:03:32.040 –> 00:03:51.519
Jonathan Milne: Next, please help me welcome Nalin, Sathamel, co-founder and CEO of Storyline Nalin leads Story Lane, an agentic demo automation platform that helps marketing and sales teams deliver powerful personalized demos at scale with a strong background. In both tech and business he focuses on driving innovation solutions for better customer engagement and measurable growth.

26
00:03:52.500 –> 00:04:09.469
Jonathan Milne: We also have Robin Daniels, chief business officer at Sensei. Robin brings extensive leadership experience from Silicon Valley, having guided high growth tech companies through key transformations. At Sensei he focuses on strategic partnerships, go to market execution and creating a culture where innovation thrives

27
00:04:09.810 –> 00:04:12.669
Jonathan Milne: and did Mark join us as well, do I see? Mark?

28
00:04:12.890 –> 00:04:41.489
Jonathan Milne: Yeah, all right. Finally, we have Mark Stause, a former big company, Cmo and agency leader, who is among the 1st in b 2 b to prove that marketing multiplier is part of the go to market. Strategy. Strategy today serves as CEO of proof analytics, a causal AI platform that helps companies across industries, analyze their data and drive tangible results. Now, the only reason why we do these Demos is sometimes you wonder why do we have these people here to speak and based on these backgrounds, I think you can appreciate. We have our pretty cool panel today.

29
00:04:41.700 –> 00:04:46.619
Jonathan Milne: So one of my favorite questions to ask people that I’ve never met before is how and when?

30
00:04:47.000 –> 00:04:57.789
Jonathan Milne: They kind of had their 1st Aha! Moment with AI. And when did you realize this technology is not like previous technology generations, you know. When did you kind of have that breakthrough of that? AI is something you need to lean into?

31
00:04:58.310 –> 00:04:59.810
Jonathan Milne: I’ll just open up to the panel.

32
00:05:02.180 –> 00:05:02.639
Amanda Kahlow: I can go.

33
00:05:03.320 –> 00:05:03.775
Jonathan Milne: Awesome.

34
00:05:04.230 –> 00:05:19.809
Amanda Kahlow: Yeah, I love that. It wasn’t on your prep list of questions. But let’s do it. Keep us on our toes, Jonathan. I love it, I mean, obviously, the 1st thing I think of is, you know, I took some time off. I had 4 years from when I was at 6th sense to coming into one mind.

35
00:05:20.020 –> 00:05:24.410
Amanda Kahlow: and the 1st time I ever experienced the product that I then took over

36
00:05:24.520 –> 00:05:50.479
Amanda Kahlow: was my Aha moment, and brought me off the bench. I literally said I was retired. I was done. I was a stay at home, mom, but if you’re a stay at home parent of any kind, you know. That is the single hardest job on the planet. Going back to work was a lot easier. But the moment that I realized I could have full conversations with an AI, and it could transpose like the limitations of what humans could do today.

37
00:05:50.830 –> 00:06:16.759
Amanda Kahlow: I mean for me, I it was the beginning. It was just an avatar. It barely looked like a human. It had massive delays like it was. It was a mess, as a product, you know, over a year plus ago. But that was the moment I was like, Oh, my gosh, this is gonna change everything if we can, you know, fix these like small pieces of human, the inefficiencies. It was game changing for sales and marketing, so it brought me off the bench to say I had to come back to work and put my suit back on.

38
00:06:21.932 –> 00:06:45.400
Robin Daniels: I can go next. My moment probably came when I was working at Linkedin. This is a few years back. I was working on the keynote in 2017 for a big conference and big theme of that keynote was around AI, and how we’re going to use AI in our products, and it was more of a visionary keynote than what was actually reality today. But the main theme was. We framed it as kind of a thousand to 10 to one, meaning that

39
00:06:45.600 –> 00:06:49.770
Robin Daniels: because, of course, it’s a hiring platform in many ways is what Linkedin is. And so

40
00:06:50.110 –> 00:07:18.039
Robin Daniels: most recruiters are overwhelmed with the amount of applicants that come into any given scenario, and we kept saying, Well, AI should be so good that it should basically be able to get from, let’s say, a thousand candidates based on their skills and backgrounds and expertise, and all this kind of stuff down to like the 10 best candidates. And then that’s where the human comes in. And so you have basically, instead of a recruiter, or, you know, talent managers sifting through thousands of resumes and talking to a bunch of people that are really not suitable for the role.

41
00:07:18.110 –> 00:07:41.529
Robin Daniels: AI should be able to do the majority of that work. So you can spend time on the quality that really matters. And and to me it’s like feels like, now we’re finally here like to that point. But it took us a while to get there. But to me that was like that was really a moment of that. This is this will become a super powerful humans if we can make this a reality. It feels like here in 25. We’re more or less there. But it took us a while to get there, but that was. That was my moment.

42
00:07:41.830 –> 00:07:52.209
Jonathan Milne: Love it, Robin. I had a I had a friend where we’re doing resumes for them. And one of the things we asked AI is who does not fit the profile, but might make a very interesting candidate right? That outlier

43
00:07:52.770 –> 00:07:57.249
Jonathan Milne: and turned out the outlier was who they hired right. It was, very interesting.

44
00:07:58.130 –> 00:07:59.390
Robin Daniels: Interesting, now.

45
00:08:00.060 –> 00:08:00.889
Jonathan Milne: But you know.

46
00:08:01.070 –> 00:08:24.530
Nalin Senthamil: Yep, I can go. So I’ve been a technologist for a long time, probably been involved. Built my own AI systems. So I think my 1st Aha, I would say, is like back when I was in Amazon, building an AI system in 2,01110 time period, I think. We used to build out like an recognition. You can scan your camera with your phone, identify something and puts a buy button. You can go buy it

47
00:08:24.530 –> 00:08:36.259
Nalin Senthamil: right? It was trained with Ml. AI. This was before Gen. AI. So we knew this is powerful, and people building like with Nvidias and everything. How we can make it powerful. That was the time with Cuda was there.

48
00:08:36.289 –> 00:08:45.729
Nalin Senthamil: I think it moved from one modality like images or text, and it became multi modal right where you can combine voice and text. And that happened like few years back.

49
00:08:45.790 –> 00:09:14.410
Nalin Senthamil: I think that was the moment when I felt like when you can start making like multimodal predictions through this. It’s super powerful. What that means is you can do voice learning. What you can do is like you can do avatar talking right? And then it became more like realistic around it. Where you can. As a human, you can start interacting with it more and more moving from a text. So for me, that was the moment I think it started way back. But then it solidified. Really, when it became multimodal, pretty much in our applications.

50
00:09:16.260 –> 00:09:20.110
Jonathan Milne: Alright, and I don’t see Mark’s face. Am I missing? There he is.

51
00:09:20.110 –> 00:09:25.769
Mark Stouse, Proof Analytics: Sorry about that, guys. I I was having some technical problems getting in. But I was able to hear

52
00:09:26.505 –> 00:09:28.710
Mark Stouse, Proof Analytics: right? So

53
00:09:28.710 –> 00:09:39.149
Mark Stouse, Proof Analytics: I’ll say this, this is what Robin was talking about. What you guys were talking about is is actually closely mirrored by the rise of AI powered buyer bots in the enterprise

54
00:09:39.690 –> 00:09:40.670
Mark Stouse, Proof Analytics: right?

55
00:09:41.040 –> 00:09:57.959
Mark Stouse, Proof Analytics: That is essentially doing a scan and deciding on whether or not you’re a good vendor or a bad vendor, and whether you provide good information, truthful information, all that kind of stuff, right? And if you are, then you’ll be elevated up, and and if you aren’t.

56
00:09:58.530 –> 00:10:05.129
Mark Stouse, Proof Analytics: you know you won’t even know that there was an opportunity. Right? So I mean it. It’s very similar.

57
00:10:05.900 –> 00:10:19.480
Jonathan Milne: Well, let’s double down on that comment. Then Mark, you know, there’s a lot of discussion and technology. We’re seeing around the whole buyer process. And and you know, we wondering now, you know, is human led sales

58
00:10:19.670 –> 00:10:30.260
Jonathan Milne: obsolete? Do we still need them? Is it going to be just AI helping it? Or do we need to balance this? So now, why don’t we start with you on on your thoughts around that kind of shift?

59
00:10:30.790 –> 00:10:38.660
Nalin Senthamil: Sure this is my favorite topics and kind of premise of why storyline started itself in some ways. Right? So

60
00:10:38.930 –> 00:10:56.370
Nalin Senthamil: short answer is, I don’t think humans will become obsolete. People buy from people, but I think what is going to change is the line that we are drawing today has shifted. What that means is like if you, if you look at it earlier, right? So people will start like talking to sales very early on. This is like a ticket back.

61
00:10:56.370 –> 00:11:13.500
Nalin Senthamil: That line is shifting a lot today. I mean, there’s a study from Gartner which talks about like 70% of the people don’t want to talk to sales. We don’t wake up saying that, hey? I’m excited talking to sales. 10 people. I’m going to make a phone call to them. Right? So I believe that’s more like 95% today, right in the last 2 years, it’s probably, and it’s going to get more and more.

62
00:11:13.610 –> 00:11:33.700
Nalin Senthamil: So in the entire process, what will happen is you know, people would want to identify as a buyer. Right? I want to pick the top 2 people. I want to have a meaningful conversation. That’s what is going to happen more and more. And then, when I say meaningful conversation, it’s about like a product specialist. That role would be understanding deeper about your product so that I can make a purchase decision.

63
00:11:33.780 –> 00:11:52.830
Nalin Senthamil: So more towards later in the cycle is when they will start talking to sales teams, and you’re not going to swipe 50,000 if you’re going to buy a $50,000 product. It’s not something that you would buy without talking to someone. Still right, you would still talk to someone later in the stages. But you would still understand, you know, in terms of what your product is offering

64
00:11:53.090 –> 00:12:19.709
Nalin Senthamil: right now, there’s a lot of noise with any market. You say there is so much software out there so as a buyer, it’s you’re inundated with too much information. So in my opinion, that’s where basically, AI is going to help them. So the buyer is able to navigate this very easily and make those kind of decisions. Good example, I would say, if you are looking for a software today, you can ask Openai today. Hey, here is my 8 vendors. Give me a full detailed report. It will give you automatically.

65
00:12:19.710 –> 00:12:36.070
Nalin Senthamil: Now you can pick the top 3 from there, and without even talking, have yourself or an agent, go and talk to the other agent on the website itself, and get to know, like, who’s my top vendor I want to talk to. So that’s going to happen, and then you will finally start having a conversation with the salesperson there.

66
00:12:36.070 –> 00:12:54.709
Nalin Senthamil: So the whole paradigm of like outbound Sdr. Is already changing right? Like there is a lot of Asgr tools out there. In my opinion, inbound Sdr. Will also become like challenged a lot more. People will talk to avatars. People will understand what your product is doing very quickly. And it’s already happening. That’s a trend that I see that’s going to happen a lot in 2025.

67
00:12:55.080 –> 00:13:03.289
Nalin Senthamil: And then once you process that, then that’s when basically they’ll start to have kind of your sales engineers, product specialists where you start getting to understand the product itself.

68
00:13:03.580 –> 00:13:06.709
Nalin Senthamil: That wedge is going to keep coming down. Quite a lot, I would say.

69
00:13:07.600 –> 00:13:25.269
Robin Daniels: And you also have, I think I agree with that. I think. B, 2 B behavior, oftentimes mirrors consumer behavior. But a few lags behind a few years in my experience, 5, 10 years behind. And so if you think about your personal life, how often do you really speak on the phone to people anymore. Really, right? You speak to people on the phone

70
00:13:25.480 –> 00:13:53.390
Robin Daniels: if they’re really close, right? Like people who are in your inner circle. But other than that. You text right back and forth. And I feel like the b 2 b experience and buying is going to be very similar. We’re gonna text, probably, and probably with bots more than ever right? Because they can get hold us down. But then the final like the final mile, maybe that’s when you pick up the phone and speak to somebody. But the idea of actually early in the phase speaking to an AI bot on the phone, which I think I keep getting inundated with people. Want to sell me an AI. Sdr. Platform like I don’t want to speak to an AI.

71
00:13:53.390 –> 00:14:13.939
Robin Daniels: I mean it just like it just sounds awful to me, but maybe on text, right, or chat, or something that could work like to get to hold it down for the final stages. I think you do want that human involved, at least in the mid to upper mid market, maybe not in the Smb space as much because the ticket size are small, but I suspect that it will get to that point very much as it’s gone in our, in our personal lives, where

72
00:14:14.350 –> 00:14:20.009
Robin Daniels: we we just text more than we actually speak anymore. I don’t know I could be wrong. That’s my feeling

73
00:14:20.550 –> 00:14:21.030
Robin Daniels: going.

74
00:14:21.030 –> 00:14:44.580
Amanda Kahlow: I. I have a little bit of a a spicy. Take on what you just said. But like do they wanna talk so? I agree like the outbound phone, like, let’s look at it from the bow tie perspective of winning by designs, Bowtie, right? There’s like the top of the funnel all the way through. Go to market doesn’t just end at the sale. It goes all the way through to customer success and upsell and renewal right? I think the top of the funnel the outbound

75
00:14:44.920 –> 00:15:03.150
Amanda Kahlow: is kind of a race to the bottom in a lot of ways like you said, like nobody wants to pick up that cold call to have that conversation over the phone. And you know, while it’s hyper personalized, there is a lot of regulation and things that are happening that people try to identify. I think it’s a tough world. So I I feel for those vendors that are in that world.

76
00:15:04.250 –> 00:15:10.579
Amanda Kahlow: But when your buyer is coming in and leaning in and said, Okay, I’m thinking about this now, and I’m considering this.

77
00:15:11.450 –> 00:15:25.559
Amanda Kahlow: Who gets up in the morning and ever says, Oh, my God! I can’t wait for that. Sales pitch with the sales rep, said no one ever they wanna talk to a salesperson. So my favorite thing, when people ask me, don’t we need to have the human in the loop because people want to buy from people. And you know.

78
00:15:26.280 –> 00:15:48.510
Amanda Kahlow: I’m like, people want to have relationships with people. I want to have connection and community with other go to market leaders, other executives, other founders that you know I want community with. But those aren’t the people that I’m trying to buy Crm from tomorrow or buy the next tool from tomorrow. I’m not trying to build a relationship with that salesperson. So our thesis is that allow shift the control

79
00:15:48.510 –> 00:16:11.240
Amanda Kahlow: from the seller’s pocket to the buyers to give them information, and in the context and relevance that they want when they want it in any channel. And it’s not just a text, or it’s not just text. It has to be like a full demo. It has to be able to show the slides, show the information and be empathetic, like, I think the world we’re moving towards is not just like.

80
00:16:11.240 –> 00:16:21.709
Amanda Kahlow: what’s your answer to this? What’s the agent? But listen to my needs as, like Jocko, winning by design, would say, uncover the pain, uncover the impact, and then give me the best, and when you do that in the moment.

81
00:16:21.710 –> 00:16:41.549
Amanda Kahlow: give me the best case, study that matches to my pain and my solution. And the problem is human sellers. While they have every intention to do those things and go through all these training courses they suck, they suck at. They are no offense to human sellers. But we have capacity limitations as humans to be able to turn that around instantly and pull that slide in or pull that case study in.

82
00:16:41.550 –> 00:17:02.400
Amanda Kahlow: But the beauty of AI is, it doesn’t have capacity limitations. In fact, when you’re a horizontal solution that sells everything to everyone. You can pull in that right piece of information at the right time and move the conversation forward. And oh, by the way you train the AI to ask the hard question, do you have budget? Are you? Are you the champion? Who do? I need all those things that the sellers are afraid to do right. So

83
00:17:02.420 –> 00:17:11.519
Amanda Kahlow: I think, you know, it’s a better experience for the buyer. So that goes to the sale and then think about. You have new products that you want to share, and you have new features.

84
00:17:11.520 –> 00:17:37.860
Amanda Kahlow: Do you want to get a Csm on the line every single time. It’s they’re acting like a robot. Right? They’re just repeating what the new feature is. What if the superhuman could step in and say, Hey, can I share how this works with what you’re doing today. See how you’re using the product today. It has infinite capacity, knows with a product usage, knows what you can upsell and again have these relevant conversations. So for me, the end goal is to create a better buyer experience and a better customer experience

85
00:17:37.930 –> 00:17:42.909
Amanda Kahlow: by giving them control in every channel. Show up in zoom, show up on the web, show up in the product

86
00:17:43.360 –> 00:17:50.108
Amanda Kahlow: that is gonna be when we win. And I think that’s the that’s what we’re solving for, and it gets me so excited, clearly.

87
00:17:50.390 –> 00:17:54.269
Mark Stouse, Proof Analytics: I think that I think that the the part of that, though that

88
00:17:55.080 –> 00:17:59.760
Mark Stouse, Proof Analytics: that a lot of marketers are not yet wrapping their head around

89
00:17:59.980 –> 00:18:17.330
Mark Stouse, Proof Analytics: is that AI is a super technology, and that’s a historical term about certain technologies that behave in certain ways. And in this case it’s talking about the fact that it’s used defensively as well as offensively.

90
00:18:17.990 –> 00:18:30.869
Mark Stouse, Proof Analytics: So you’re seeing AI powered filters now in in enterprise, it email servers that essentially will completely intercept all email from marketing automation.

91
00:18:30.970 –> 00:18:31.900
Mark Stouse, Proof Analytics: Right?

92
00:18:33.070 –> 00:18:44.070
Mark Stouse, Proof Analytics: the shift in power in the relationship towards the buyer with the buyer asking the questions. Right? The fact that

93
00:18:44.320 –> 00:18:52.240
Mark Stouse, Proof Analytics: personalization is being done and will be done right by the buyer, not by the seller.

94
00:18:52.770 –> 00:18:53.650
Mark Stouse, Proof Analytics: Right?

95
00:18:54.599 –> 00:19:10.850
Mark Stouse, Proof Analytics: Is really significant. The bot, the power of the buyer bots that I’m personally invested in right is stunning to me. I’m mainly an investor in those, just because I want to see what’s going on right?

96
00:19:12.060 –> 00:19:19.210
Mark Stouse, Proof Analytics: the there is no funnel, and there ever, actually never really was a funnel.

97
00:19:19.490 –> 00:19:27.360
Mark Stouse, Proof Analytics: And that’s being encoded. That reality is now being enforced by the buyers.

98
00:19:28.770 –> 00:19:39.910
Mark Stouse , Proof Analytics: The level of disintermediation of traditional channels. I think that in less than 2 years we’re gonna see marketing at b 2 b marketing as we know it today

99
00:19:40.640 –> 00:19:45.370
Mark Stouse, Proof Analytics: it’s going to be nothing but brand and reputation.

100
00:19:46.540 –> 00:19:50.150
Mark Stouse, Proof Analytics: Cx, okay, let’s call it Cx.

101
00:19:50.400 –> 00:20:00.170
Mark Stouse, Proof Analytics: And the provisioning of really awesome, highly trustworthy information via an Llm. Attached to a URL.

102
00:20:01.350 –> 00:20:05.470
Mark Stouse, Proof Analytics: So that means web, your website.

103
00:20:05.750 –> 00:20:13.829
Mark Stouse, Proof Analytics: What’s the point of creativity on the website? If it’s mainly being accessed by bots, right?

104
00:20:14.280 –> 00:20:19.800
Mark Stouse, Proof Analytics: You also have to really understand that the primary buy risk

105
00:20:20.420 –> 00:20:30.550
Mark Stouse, Proof Analytics: for b 2 b is risk, and that the customer sees the but the vendor

106
00:20:30.830 –> 00:20:33.790
Mark Stouse, Proof Analytics: as the risk that’s being remediated.

107
00:20:34.120 –> 00:20:56.699
Mark Stouse, Proof Analytics: So that is now really being encoded into the process. And so I think it’s just going to be 52 card pickup. I I think that that what? The parts of marketing that will be around in b 2 b. Within 2 years, 3 at the outside right is going to be a very small fraction of what we see today.

108
00:20:58.700 –> 00:20:59.509
Jonathan Milne: So that’s a super.

109
00:20:59.510 –> 00:21:00.000
Amanda Kahlow: I mean I.

110
00:21:00.110 –> 00:21:13.330
Jonathan Milne: Let’s let’s double down a little bit more on that, because there’s there’s a transition period that needs to happen. There’s also gonna have to be like you said, you still have to create content. Right? You still have to feed an Lm, you’re still gonna have to create

111
00:21:13.510 –> 00:21:15.749
Jonathan Milne: awareness. You’re still gonna have to have

112
00:21:16.270 –> 00:21:32.530
Jonathan Milne: the ability to showcase your brand versus other brands to help feed those elements. Right? So there’s a lot of things that we still do that the benefit? It won’t be as visible right? But the need is going to be there to get in there. So how do we think the funnel. And the whole kind of

113
00:21:33.190 –> 00:21:41.790
Jonathan Milne: techniques we do today are going to evolve right? And you’re still have to do some to maintain them while create new ones. Right?

114
00:21:42.890 –> 00:22:07.520
Amanda Kahlow: But it can be AI driven content. Right? So a lot of it can be created to be hyper personalized, based on the experience the buyer is having. I think that’s a world we’re not seeing yet. Today. I don’t think we’ve seen a lot of tools that will create like decks on the fly, and like Demos on the fly, you know, like you can do them, but they’re there. They’re working. But it’s you know, that’s where the future is going. It’s right. And then, like you said, it’s the agent to agent.

115
00:22:07.520 –> 00:22:27.670
Amanda Kahlow: and as well like mark what you’re saying. It’s like the buyer agent talking to the seller agent and then bringing that down. But then there is a time where there is a human who makes a decision, and I think there still will be a human in the loop to make the decision. But they want to have control and get the answers the way they want to get them. And there’s still, like the multimodal pieces of content that I think

116
00:22:28.180 –> 00:22:38.179
Amanda Kahlow: we today we aren’t seeing it’s text based what you’re talking about, of bringing all that information to get today. We haven’t seen it in the full multimodal approach, and I think that’s the future.

117
00:22:38.690 –> 00:22:42.480
Mark Stouse, Proof Analytics: No, I I think there’s a lot of that, although I don’t think

118
00:22:42.660 –> 00:22:47.380
Mark Stouse, Proof Analytics: that the timeframe is nearly as elastic.

119
00:22:48.130 –> 00:22:52.129
Mark Stouse, Proof Analytics: As some people think it is, I think it’s gonna happen a lot faster

120
00:22:53.083 –> 00:22:55.429
Mark Stouse, Proof Analytics: than a lot of people are prepared for.

121
00:22:55.970 –> 00:23:05.279
Mark Stouse, Proof Analytics: You know the the bot that I saw re most recently totally stealth. Well, you’ll never know that it was sniffing your site right?

122
00:23:06.810 –> 00:23:14.330
Mark Stouse, Proof Analytics: It can evaluate everything you’ve ever said about your product or company, whatever against known facts.

123
00:23:15.910 –> 00:23:30.970
Mark Stouse, Proof Analytics: make a judgment on the reliability of your representations, elevate you to the next phase. Right? And ultimately we’ll make a a recommendation to a buyer team

124
00:23:31.850 –> 00:23:38.430
Mark Stouse, Proof Analytics: that knows that the AI knows more than they do about the whole thing. And so

125
00:23:38.540 –> 00:23:47.469
Mark Stouse, Proof Analytics: if you just think about normal human behavior de-risking their own situation. Right? They’re gonna typically go with the recommendation from AI.

126
00:23:47.760 –> 00:23:53.169
Mark Stouse, Proof Analytics: And one of the things that we’ve already seen is

127
00:23:54.189 –> 00:23:59.240
Mark Stouse, Proof Analytics: we make it generally pretty high into the consideration and final.

128
00:23:59.430 –> 00:24:03.079
Mark Stouse, Proof Analytics: the finalist kind of stage in our company.

129
00:24:04.660 –> 00:24:11.049
Mark Stouse, Proof Analytics: But increasingly, the AI is saying, this is what we’re willing to pay you for this.

130
00:24:12.040 –> 00:24:15.090
Mark Stouse, Proof Analytics: Do you want the job or not?

131
00:24:16.140 –> 00:24:22.890
Mark Stouse, Proof Analytics: Right? And if you say, Well, I really feel like, you know, we need to negotiate Nope, not negotiating

132
00:24:23.330 –> 00:24:29.839
Mark Stouse, Proof Analytics: this. Is it right? And if you don’t say yes, we’ll go to the next guy right.

133
00:24:30.300 –> 00:24:31.040
Amanda Kahlow: And it’s a

134
00:24:31.040 –> 00:24:45.149
Amanda Kahlow: you have the best product. You don’t. You haven’t done a good enough job selling the bot, or whoever is doing the selling. If I always if if my sales people come back and say where they’re gonna do this or walk, I’m like we gotta go back in and sell like we haven’t. They don’t understand what we do.

135
00:24:45.570 –> 00:24:55.500
Mark Stouse, Proof Analytics: Yeah, I understand that. But I don’t think that. What’s I don’t think what’s being covered in that statement is the extent of the disintermediation

136
00:24:55.880 –> 00:25:00.429
Mark Stouse, Proof Analytics: from real people that will happen in the buying motion.

137
00:25:02.440 –> 00:25:16.099
Mark Stouse, Proof Analytics: It’s just, I mean, look, the last of company after company after company in research has said the least productive time that our employees spend is in buying things

138
00:25:17.120 –> 00:25:26.819
Mark Stouse, Proof Analytics: so they don’t want their their employees being marketed to, and they don’t want their employees, you know, spending more than X time in buying.

139
00:25:27.710 –> 00:25:36.090
Mark Stouse, Proof Analytics: So they’re gonna do everything possible to mitigate that entire part of it. And they’re gonna use bots to do it.

140
00:25:36.690 –> 00:26:05.789
Robin Daniels: I wonder if that’s true of also the level of complexity of the software? Because, for example, last year, as the marketing team in my organization. We went and switch from Microsoft dynamics as our marketing platform to Hubspot. So many people involved so many conversations, understanding our environment. What our goals are like both people on their side, but certainly on our side, lots of people involved, even including sales and finance, and so on. I don’t see a world yet where AI is gonna replace that completely. But to Amanda’s pointing.

141
00:26:05.840 –> 00:26:10.540
Robin Daniels: helping us get the right information at the right time that’s tailored for us. I think AI is

142
00:26:10.990 –> 00:26:12.879
Robin Daniels: very fast going that direction.

143
00:26:13.360 –> 00:26:39.550
Robin Daniels: But then, the other hand, we bought Asana for project management and tracking, that’s something where it’s like a low cost purchase easy to implement, easy to set up. We don’t need to actually ever talk to a human being to do that. It’s like something you could just have. You can automate, put in a credit card, and so on. So to me that there’s a big difference that I hate. I hate the depends answer, because it feels like it’s noncommittal. But it’s true. I think we’re. It depends on the spectrum of where we are in that that whole b 2 b cycle, like

144
00:26:39.690 –> 00:26:49.950
Robin Daniels: complex versus simple. And maybe we’ll get to the complex at some point. But I feel like we’re a couple of years away from that, at least, if not if not more. And I think also just the way humans are built.

145
00:26:50.120 –> 00:27:05.309
Robin Daniels: You want that relationship. You want to look people in the eye and know you can trust, and they’re going to be there for you if shit goes down in some ways. Right? That’s part of it. When you put your your organization on the line as a Cmo. Or something like, who can I? Who am I gonna talk to?

146
00:27:05.310 –> 00:27:08.399
Mark Stouse, Proof Analytics: Asked quite a few people. That question.

147
00:27:09.107 –> 00:27:13.750
Mark Stouse, Proof Analytics: and the most common answer that I hear back is some form of

148
00:27:14.630 –> 00:27:20.120
Mark Stouse, Proof Analytics: I have lost track of how many people I have looked in the eyeball who have lied to me.

149
00:27:21.040 –> 00:27:22.179
Robin Daniels: Fair enough.

150
00:27:22.180 –> 00:27:23.180
Amanda Kahlow: Yeah, I mean, I love it.

151
00:27:23.180 –> 00:27:24.020
Robin Daniels: That’s a sad statement.

152
00:27:24.020 –> 00:27:49.190
Amanda Kahlow: If my superhumans hallucinate, because the my response back is so simple, do your salespeople hallucinate like, and do they do it nefariously, because they know they’re hallucinating, right? So the AI is doing its best to answer. And if you don’t have, and so not 99.9% of the time, like she’s on guardrail. She’s not. The AI is not going to hallucinate, especially if you build this correctly, like there are ways to do this today. We don’t have to worry about that anymore.

153
00:27:49.200 –> 00:28:14.050
Amanda Kahlow: But people still worry about it. And I’m like your reps are out there doing that every day. They’re doing the best or like. I’m not trying to throw anyone under the bus, but they’re trying to get the deal done. They’ve got a job to do, and they don’t have all the information, and they know if they go back and ask for information and then come back to the conversation. They’ve lost the deal, because time kills all deals right? So if they don’t give an answer, that’s just good enough to get it over the line and get to the next stage.

154
00:28:14.330 –> 00:28:35.390
Amanda Kahlow: They’re losing right, because we only week will go by. 2 weeks will go by, and then these cycles expand like the other thing we’re seeing with with our superhumans, which is like kind of a residual effect which I’m just. It kind of eye opening for me is that we’re building them. Our 1st use cases inbound. They’re on the website. They’re answering questions. They’re giving the pitch they’re giving the demo qualifying.

155
00:28:35.620 –> 00:28:43.260
Amanda Kahlow: But what they’re helping is in the sales cycle. They’re helping the salespeople. So like when I was selling to one of the biggest Crm companies which we closed recently.

156
00:28:43.764 –> 00:28:52.940
Amanda Kahlow: which is really super exciting every time the Cmo. And the Svps of marketing said, They’re doing this. And then I had to get on the phone with, like 10 other people like 10 times right.

157
00:28:52.940 –> 00:29:17.929
Amanda Kahlow: But in that process they would go talk to the superhuman before they got on the phone with me and ask their questions like, Oh, how do you integrate with our technology? What are the how many calls? Do you have? Do you connect to the opportunity or this right? All these technical questions and all these legal questions and compliance and sock 2 da. Da. The superhuman would answer the questions and then shorten the sales cycle. So every salesperson wants that right they want. They don’t want to get back on the line and have to answer those nuances

158
00:29:17.930 –> 00:29:27.480
Amanda Kahlow: questions to get to the finish line. So it really helps shorten sales cycles from like these archaic 6, 9 months. That’s not good for the buyer or the seller to go out that long.

159
00:29:28.460 –> 00:29:43.790
Nalin Senthamil: Think of them as more like a twin of your salesperson right? Who is actually answering them as part of your buying committee? Because you’re not in that place where the decision is being made. So they don’t have to send an email and wait for the follow up. But you have a twin that you sent with them.

160
00:29:43.790 –> 00:30:03.379
Nalin Senthamil: they can reach out and talk to them, and I think it becomes even more powerful, is not just answering questions, but actually demonstrating the product to you. Right it. The whole sales cycle comes down even further, because not everybody is in the decision making process at that point. So when they are in that sitting in a conference room making the decision, and you have a twin that’s representing you as well there. Right?

161
00:30:03.470 –> 00:30:27.430
Nalin Senthamil: Also. One more thing I would add to that point from the Romans mentioned, is, too many people are involved in the nation. Making the part that we always miss out is the opportunity cost that goes in to purchase something like you buy something for, like, as you said, like 50 k, like a bit product. There is like a 4 to 5 months of buying committee involved in making the decision, and people just forget that there’s so much

162
00:30:27.430 –> 00:30:49.639
Nalin Senthamil: lost to the company at that. 4 months in buying decision, right? From a finance. Persons involved, controllers involved the product decisions involved. Pocs involved. So many people. Look at the number of hours you’re wasting and the cost to that. And somewhere, people just forget that and focus on what they’re buying. And it hurts when they’re buying a smaller, cheaper product, and they’re spending too much time on those things.

163
00:30:49.840 –> 00:30:55.710
Nalin Senthamil: That process will completely flip with these. With the with the avatars and the agents coming in. In my opinion.

164
00:30:57.100 –> 00:30:57.600
Jonathan Milne: So we’ve.

165
00:30:57.600 –> 00:30:58.459
Nalin Senthamil: Started realizing that.

166
00:30:58.460 –> 00:31:23.499
Jonathan Milne: So this is great. We talked a lot about agents and a gentic and stuff. So let’s talk about then, as a Cmo in an organization. How do we need to think about restructuring our team training them? The organization structure, the skills we’re gonna need, right? So you’re already talking about the buyer journeys is disruptive. Mark, you talked about how you know brand and community are gonna be super important. So what does our org structure today look like. And then what do we need to move it to.

167
00:31:26.560 –> 00:31:40.940
Mark Stouse, Proof Analytics: Well, I think that that a lot, surprisingly. And I didn’t originally think this. Okay, so I’m I’ve kind of evolved in this into this position based on the data and the analytics. And what I see.

168
00:31:41.960 –> 00:31:49.739
Mark Stouse, Proof Analytics: I think there’s gonna be whole areas of organizations. So not just picking on marketing right?

169
00:31:52.210 –> 00:31:58.929
Mark Stouse, Proof Analytics: As we know them, as we have known them for a long time, that will

170
00:31:59.620 –> 00:32:07.830
Mark Stouse, Proof Analytics: either cease to exist or will cease to exist in in a in a form in which we

171
00:32:08.180 –> 00:32:16.209
Mark Stouse, Proof Analytics: recognize them. Right? I think. Web, for example, is a great, is an exemplar of this.

172
00:32:19.570 –> 00:32:27.260
Mark Stouse, Proof Analytics: You know the whole, the whole transaction hinges on de-risking the decision.

173
00:32:27.980 –> 00:32:31.100
Mark Stouse, Proof Analytics: So they’re going to the absolute essence

174
00:32:31.560 –> 00:32:40.609
Mark Stouse, Proof Analytics: of what matters, which is quality of information, reliability of information. Cx. And your reputation for really great. Cx.

175
00:32:41.350 –> 00:32:42.540
Mark Stouse, Proof Analytics: I mean, I think.

176
00:32:42.540 –> 00:32:42.970
Amanda Kahlow: Oh, sorry!

177
00:32:42.970 –> 00:32:46.999
Mark Stouse, Proof Analytics: Everything else is kind of a subsidiary idea.

178
00:32:48.850 –> 00:33:00.089
Amanda Kahlow: Yeah, sorry I didn’t mean to interrupt you, Mark. I think there’s we’re moving to a world where, if you don’t do these things like, there’s the opportunity costs. And you’re gonna fall behind.

179
00:33:00.250 –> 00:33:02.160
Amanda Kahlow: Right? So and it’s not.

180
00:33:02.340 –> 00:33:16.410
Amanda Kahlow: you know, we’re solving for growth, right? Who doesn’t have a growth problem or challenge or opportunity. Right? We’re solving for growth. But it’s also efficiency, like we can’t throw money at it anymore. The way we used to. And unfortunately, humans are the most expensive thing on our P and L.

181
00:33:16.877 –> 00:33:31.050
Amanda Kahlow: So we really have to think about in a world. But they just the cash isn’t where it used to be. And we can’t spend $4 to acquire a $1 customer like we’re talking about these long sales cycles and the cost on the buyer side as well.

182
00:33:31.050 –> 00:33:47.400
Amanda Kahlow: I mean, and not to mention the cost like once you get into procurement, I mean, please, somebody out there solve. For let’s have all like the leaders in tech like come up with, like, what are like the minimum requirements like, what are we gonna say on both sides of the procurement cycle, and just

183
00:33:47.470 –> 00:34:13.459
Amanda Kahlow: like cut out the Bs like, what do you ask for when you’re the buyer and the way you ask me to sell her. And let’s just agree. Because why do we go through 6 months into procurement as well? That is, not helping anyone. So I know we don’t talk about that. But man, that’s a waste of money. It’s killing me if somebody needs to solve that. And I know there’s like tools. But like it needs to be all the best leaders coming together and say, like, we agree, this is it. This is like, just like there’s a Yc safe note. Everybody agrees. Oh, that’s the Yc. Safe note. Great like. Nobody even looks at it. Can we do the same thing?

184
00:34:13.460 –> 00:34:27.369
Mark Stouse, Proof Analytics: I think you have to always, though, come back to some key rules of the road, and that is that there is no better way to improve efficiency in anything than to improve its effectiveness.

185
00:34:28.480 –> 00:34:33.310
Amanda Kahlow: Yeah, you have to be better than humans today like these, these thoughts on both sides have to.

186
00:34:33.389 –> 00:34:57.240
Amanda Kahlow: If we are just as good as humans, we would not survive. I would not sell a single deal when I’m responding, and have the accuracy of a human and the recall of a human and the conversation of a human. I need to, the superhumans need to know. Have the best sales methodologies in their brain. Be able to like rat off spice, challenger, you know. Med pick, have all of those things going through their head. Bring in the right information. Recall within 3 seconds.

187
00:34:57.290 –> 00:35:22.600
Amanda Kahlow: If a human like takes 5 seconds to respond. Nobody has a problem with it. But if my superhuman sits there and like, thinks for a second oh, that wasn’t natural enough like, Wait, what? And then you have slow talkers and fast talkers, and so do you want her to interrupt you? We’re giving space to make sure, like. I just, interrupted Mark rudely. You know you don’t want the superhuman to do that right when they’re coming in. So there’s all these Agi problems we’re solving for which are so super exciting.

188
00:35:23.780 –> 00:35:24.359
Amanda Kahlow: higher than it.

189
00:35:25.350 –> 00:35:26.340
Mark Stouse, Proof Analytics: What?

190
00:35:26.340 –> 00:35:29.210
Amanda Kahlow: I thought that was just conversation. Well, I thought.

191
00:35:29.670 –> 00:35:30.520
Robin Daniels: I saw that.

192
00:35:31.360 –> 00:35:33.350
Amanda Kahlow: I thought you had paused. I thought you were done.

193
00:35:33.350 –> 00:35:34.520
Robin Daniels: And you weren’t that.

194
00:35:34.520 –> 00:35:37.630
Amanda Kahlow: And so. But that’s where humans, yeah.

195
00:35:37.630 –> 00:35:41.550
Amanda Kahlow: superhuman can’t do that right like it was a super exciting.

196
00:35:41.550 –> 00:36:11.219
Robin Daniels: You say it’s such. I think it’s great, because that shows that there’s a flow to a conversation. Sometimes. These conversations you have with bots are so weird. It’s like you speak. And then it processes. It’s very weird on the org chart thing. I’m convinced more than ever that any skills, anything to do with hard skills will get disrupted by AI, and it already is obviously. But it’s going to get disrupted super fast in the next 2, 3 years, and those people who are only relying on their hard skills at work are going to see a severe disruption.

197
00:36:11.220 –> 00:36:32.880
Robin Daniels: Anything to do with soft skills are still far from being disrupted. It will get disrupted in different ways, and it, for sure will, but not as much so creativity, communication, teamwork being able to lead. Well, all these kind of things. I think there’s still going to be a strong need for you. But anything to do with synthesizing data, doing reporting analytics. It’s gonna get disrupted. I mean, it’s interesting. So

198
00:36:32.950 –> 00:36:48.279
Robin Daniels: here’s an a real world. AI example. One of the things that’s always been the hardest in my career. So, figuring out, how do you get the right competitive information when you’re in competitive space to your sales team to win more deals right at Salesforce Box and Linkedin. All these companies were like, always

199
00:36:48.280 –> 00:37:18.159
Robin Daniels: honestly, a hassle in the ass, and you can either spend a lot of time researching, or you hire people to do it now with AI. Honestly, you can do it and say, like my team just signed up for Chat Gpt deep research. And we can get rid of our, you know, competitive agency. Now, we don’t have to spend 20 h researching competitive deal like we can do that instantly. That’s a beautiful example of where this becomes a super power for humans to focus on what they’re best at the creative part of product marketing, branding, positioning, messaging all that kind of stuff. So anything with hard skills.

200
00:37:18.220 –> 00:37:21.390
Robin Daniels: it’s gonna get disrupted. It already, actually, is, yeah.

201
00:37:21.390 –> 00:37:25.199
Mark Stouse, Proof Analytics: I agree, Robin, I think that the perhaps the biggest

202
00:37:25.460 –> 00:37:28.750
Mark Stouse, Proof Analytics: impact that AI will have in the short term.

203
00:37:29.410 –> 00:37:33.280
Mark Stouse, Proof Analytics: which probably none of us are actually really prepared for

204
00:37:34.090 –> 00:37:39.250
Mark Stouse, Proof Analytics: is the level of transparency and accountability, that it brings

205
00:37:39.370 –> 00:37:48.860
Mark Stouse, Proof Analytics: the fact that there we have all grown up with a zone of ambiguity in which we are able to bob and weave and do our thing.

206
00:37:49.610 –> 00:37:54.130
Mark Stouse, Proof Analytics: and that that zone, that gray circle, is shrinking.

207
00:37:54.650 –> 00:37:59.949
Mark Stouse, Proof Analytics: and that far more will not only be known, but be knowable.

208
00:38:00.440 –> 00:38:00.780
Robin Daniels: Alright!

209
00:38:00.780 –> 00:38:02.889
Mark Stouse, Proof Analytics: Than it has ever been the case.

210
00:38:03.330 –> 00:38:08.430
Mark Stouse, Proof Analytics: and if you’re a bullshitter it will reveal that, you know very clearly.

211
00:38:09.010 –> 00:38:16.020
Amanda Kahlow: I can’t help but think of politics here. But like, do people actually care? Because clearly, we don’t like, you know, like.

212
00:38:16.640 –> 00:38:22.080
Amanda Kahlow: we’re voting into, yeah, no political but will, because I mean.

213
00:38:22.080 –> 00:38:22.800
Mark Stouse, Proof Analytics: I don’t really.

214
00:38:22.800 –> 00:38:26.359
Amanda Kahlow: Clearly don’t care if people bullshitting like humans aren’t.

215
00:38:27.130 –> 00:38:30.300
Amanda Kahlow: I’m just so I don’t know how that really, that comes.

216
00:38:31.011 –> 00:38:34.569
Jonathan Milne: Love emotions over facts so.

217
00:38:34.570 –> 00:38:39.279
Amanda Kahlow: You know. So like we’ll still be sold on whatever it is. Yeah, like that.

218
00:38:39.280 –> 00:38:45.640
Jonathan Milne: Let me throw a little challenge here, because so far, what I’ve heard, and it’s quite interesting as I as I listen to all of you is that

219
00:38:45.860 –> 00:39:01.500
Jonathan Milne: we’re talking about AI being this augmentation thing to our existing process. Right? But, Mark, you’re just kind of teasing this idea that I think it’s going to change a lot more more quickly. Right? So if you go back to Robin, your example of competitive intelligence.

220
00:39:01.880 –> 00:39:10.340
Jonathan Milne: you took an old system and you put some AI on it right. I don’t think that is gonna last very much longer in the cycles.

221
00:39:10.340 –> 00:39:10.870
Jonathan Milne: right.

222
00:39:10.870 –> 00:39:11.670
Robin Daniels: I agree, agree.

223
00:39:11.670 –> 00:39:23.059
Jonathan Milne: I think we’re gonna leapfrog this, you know. And I’m thinking about like, you guys keep talking about demoing a software I’m like, why do you? Even demo software, I’ll have an environment set for you integrated with your data

224
00:39:23.190 –> 00:39:40.659
Jonathan Milne: as part of the sales cycle. I don’t need to have a proof of concept, it’ll be instantly done right? So we, I think, in marketing, when we start to think about, you know our org structure and our changes, we keep thinking about, you know, taking our existing world and adding some efficiency to it.

225
00:39:40.690 –> 00:40:10.149
Jonathan Milne: And I think the mindset needs to be, what’s the leapfrog that this new stuff will open right? So like deep search. If you haven’t played with it. If you haven’t played with compute use, these are going to rapidly change the needs of, you know. Do I even need Apis right? Or do the agents talk to each other? And there’s talk about them coming up with their own language to share data. Right? So there’s this kind of next phase that I think we need to talk about more. So when you guys think about tools and next kind of phases. What are you thinking of?

226
00:40:10.150 –> 00:40:25.280
Mark Stouse, Proof Analytics: I think the logistics are gonna be the thing right? I mean. And here’s and here’s where the problem is right now, statistically speaking, only about 3 to 4% of corporate data is worth a damn

227
00:40:25.440 –> 00:40:49.769
Mark Stouse, Proof Analytics: right? It’s not usable. In fact, all the cases around fiduciary duty expanded fiduciary duty to officers, right? That are being filed right now, okay, are about data quality issues, data accessibility issues holding companies back from being able to adopt

228
00:40:49.840 –> 00:40:56.499
Mark Stouse, Proof Analytics: full blown enterprise. AI tools losing competitive advantage, things like that. Right?

229
00:40:56.630 –> 00:41:11.669
Mark Stouse, Proof Analytics: So the idea, for example, even though I love it as much as anybody on this call that you will be able to auto, attach your your software to people’s data as part of the sales process

230
00:41:12.360 –> 00:41:15.590
Mark Stouse, Proof Analytics: is right now, a fantasy.

231
00:41:16.240 –> 00:41:18.969
Mark Stouse, Proof Analytics: Right? It’s just not happening.

232
00:41:19.460 –> 00:41:33.760
Mark Stouse, Proof Analytics: And and so that is a that’s a major limitation that any Cdo and that’s who I work with a lot. Right? Any Cdo will tell you that that’s the reality of the situation. Right?

233
00:41:33.950 –> 00:41:44.640
Mark Stouse, Proof Analytics: So so we are like, one of the reasons why Robin loves his his Ci tool. Okay.

234
00:41:44.760 –> 00:41:51.290
Mark Stouse, Proof Analytics: is that he’s not having to feed any data into it right?

235
00:41:51.450 –> 00:42:02.270
Mark Stouse, Proof Analytics: The magic of it is that it conjures all this knowledge out of the ether painlessly, for he and his team right

236
00:42:02.570 –> 00:42:06.699
Mark Stouse, Proof Analytics: as soon as you other forms of AI, though that’s not the case.

237
00:42:07.090 –> 00:42:29.170
Amanda Kahlow: I think that only applies. I think that applies in when you’re talking about Pii and sensitive data, others like we can spin up a superhuman. Just by scanning your website. We can see what you sell all your products, and she can sell better than us rep like I could do that we can do that pretty quickly for folks. So it just depends on what we’re talking about and what level of data that we’re bringing in. But going back to like.

238
00:42:29.170 –> 00:42:31.359
Mark Stouse, Proof Analytics: And also who we’re talking about.

239
00:42:31.360 –> 00:42:32.870
Amanda Kahlow: 100%. Yeah, yeah.

240
00:42:32.870 –> 00:42:33.250
Mark Stouse, Proof Analytics: First.st

241
00:42:33.250 –> 00:42:33.700
Amanda Kahlow: Principal.

242
00:42:34.190 –> 00:42:35.120
Amanda Kahlow: All of this

243
00:42:35.260 –> 00:42:39.495
Amanda Kahlow: is, if we get back to a world of 1st principles like you think about like

244
00:42:40.410 –> 00:43:06.529
Amanda Kahlow: floodgate. Mike Maples talks about the concept of backcasting right looking into the future, and like you think about when we got into an Uber like, whoever said like, Oh, yeah, I’m going to jump in a stranger’s car, I said, F. No like no way am I jumping into a stranger’s car? No way am I letting somebody sleep in my bed. But you know, actually, this summer somebody just offered me a ridiculous amount of money for my house. I’m like, yeah, that pays my mortgage for 2 years, like, sure, for 3 months, like I’ll do it

245
00:43:06.530 –> 00:43:15.819
Amanda Kahlow: right. So we say yes to things, because the efficiency and the convenience and the benefits outweigh like the ick factor. And I think there’s a lot of it right now, like

246
00:43:16.080 –> 00:43:20.340
Amanda Kahlow: all these systems of record in especially in Martech and sales, tech

247
00:43:20.580 –> 00:43:30.119
Amanda Kahlow: are to basically enable humans to go get at one piece of data and to glue it together. And and those all of that agentic workflow is going to replace that. So

248
00:43:30.310 –> 00:43:51.659
Amanda Kahlow: I don’t think we can. Even I can’t wrap my head around like where we’re going to be. We need to house the data, so that, like Mark said, agents to agents can talk to each other. But the humans will want to come in potentially and into the solution. Have a conversation as well, but do it with their kids running on their lap, and not have to put a suit jacket on and like Button up to talk to a salesperson like who wants to do that? Nobody right? So I think

249
00:43:51.850 –> 00:43:53.300
Amanda Kahlow: I think everything is

250
00:43:53.750 –> 00:44:01.139
Amanda Kahlow: like ripe for disruption right now, which is why this is such an exciting time to be a part of what’s happening, especially in sales and marketing.

251
00:44:02.050 –> 00:44:02.640
Jonathan Milne: So let’s have a look.

252
00:44:02.640 –> 00:44:03.500
Nalin Senthamil: Thumbs up.

253
00:44:03.760 –> 00:44:15.589
Jonathan Milne: People always want practical advice. Right? So how about everybody? List off your favorite one or 2 or 3 tools you’re using today? Cause you know. I’m sure you’re all playing with something fun. And what are you using it for?

254
00:44:17.630 –> 00:44:35.119
Amanda Kahlow: I mean, we’re building a lot of our own, I think, building my, I’m looking to my team to say, replace yourself. And if you replace yourself. I’m trying to find a way. It’s not done yet. So just full transparency out there where I can accelerate all their vesting. If you can fully replace yourself. You get your vesting accelerated and like, but like building.

255
00:44:35.270 –> 00:44:45.720
Amanda Kahlow: I think, building the tools that are helping in your individual job is where people should be looking like really focusing like, how can I replace my task today so that you can level up and do the task that

256
00:44:46.160 –> 00:44:47.760
Amanda Kahlow: that AI can’t do.

257
00:44:49.340 –> 00:45:12.110
Nalin Senthamil: Yeah, I think one of the themes that we had in the in our company today is scaling up like, like, what Amanda said is like, how do you make yourself more efficient? 10 x yourself by using AI tools? Right? We use a lot of them. I mean, like not just marketing, if I can name few like. It’s like, even from an engineering. I think you’ve all heard, probably cursor. Who can write code for you right? Something that is has been profound change in this year a lot.

258
00:45:12.140 –> 00:45:40.244
Nalin Senthamil: So we use that a lot in our tech teams in the marketing stack. We, you know, we use a Sdr on our side, actually, with not fully automated, we use with the human in the loop to have that kind of. You know, empathy in terms of the conversation. We’re going to have that as well. We use copyai for generating content and everything. Of course we use our own sterling tool to build out these Demos for our customers as well. And we use

259
00:45:40.988 –> 00:46:10.189
Nalin Senthamil: support tools, for we use intercom fin AI in fact, we were looking for hiring additional support folks as well, and in fact, we didn’t go ahead because you know, it’s come along a lot in the last one year, if you look at it with a lot of data that we’ve been training with it itself. It’s fantastic, in which how it results in small support tickets as well. So there is tools used in every function. And if you’re not doing that. Actually, you’re like lagging behind, in our opinion, right? So I think we use it across these are some of the tools we use quickly.

260
00:46:10.570 –> 00:46:11.310
Jonathan Milne: Awesome.

261
00:46:12.630 –> 00:46:16.500
Mark Stouse, Proof Analytics: So I would part of a research team that

262
00:46:16.700 –> 00:46:22.499
Mark Stouse, Proof Analytics: did a paper last fall. On the economic impact of Gen. AI.

263
00:46:23.060 –> 00:46:29.800
Mark Stouse, Proof Analytics: And one of the things I mean at some level. This won’t be a surprise, but it was for a lot of people.

264
00:46:30.542 –> 00:46:38.190
Mark Stouse, Proof Analytics: When you, when you apply it to a bell curve of population right in terms of how it’s used.

265
00:46:38.510 –> 00:46:46.350
Mark Stouse, Proof Analytics: Yes, there is. There are efficiency gains of approximately 20%, and that is more or less

266
00:46:46.930 –> 00:46:55.839
Mark Stouse, Proof Analytics: pervasive across that curve where you really started to see major economic impact

267
00:46:55.980 –> 00:47:05.359
Mark Stouse, Proof Analytics: was as a multiplier on effectiveness and innovation and all that kind of stuff in your highest potential employees.

268
00:47:06.000 –> 00:47:11.600
Mark Stouse, Proof Analytics: which was off the charts, the messy middle. You still get a lot, but not as much.

269
00:47:11.720 –> 00:47:16.990
Mark Stouse, Proof Analytics: The people on the far end that you’re probably gonna Riff at some point, right?

270
00:47:17.150 –> 00:47:19.920
Mark Stouse, Proof Analytics: Not much of a multiplier at all there.

271
00:47:20.390 –> 00:47:34.019
Mark Stouse, Proof Analytics: But the big lesson here right on AI in general, all 4 types, right? Not just, Jim, is that the real upside is in how it makes human beings bionic

272
00:47:34.480 –> 00:47:35.680
Mark Stouse, Proof Analytics: effectively.

273
00:47:36.040 –> 00:47:41.030
Robin Daniels: Not in how it replaces large swaths of them.

274
00:47:42.290 –> 00:47:51.710
Mark Stouse, Proof Analytics: And we cannot. We can. In all of this right we cannot lose sight of being humanists with me.

275
00:47:51.710 –> 00:47:56.420
Amanda Kahlow: It’s time to reskill. And like, we’re gonna lose certain jobs. And we have to reskill like the way

276
00:47:56.420 –> 00:48:04.110
Amanda Kahlow: we don’t have. Yeah, like, I think I think I think we’re doing everyone a disservice by saying that jobs aren’t going to be replaced. We’re trying to make people feel good.

277
00:48:04.110 –> 00:48:04.490
Robin Daniels: They will.

278
00:48:04.490 –> 00:48:10.510
Amanda Kahlow: In the sales function and say, Don’t worry. We’re just just gonna elevate you like, hey? Well, to happen.

279
00:48:10.510 –> 00:48:11.660
Mark Stouse, Proof Analytics: Yeah, but I.

280
00:48:11.660 –> 00:48:17.279
Amanda Kahlow: People need to really be thinking about where their world is going. And it’s not. It’s not kind, I feel, to do that. I’m not saying you’re not.

281
00:48:17.280 –> 00:48:18.139
Mark Stouse, Proof Analytics: No, I’m not.

282
00:48:18.140 –> 00:48:40.899
Amanda Kahlow: So this whole like, oh, it’s only going to elevate. It’s gonna make the best better. And I’m like, no like if you are an inbound. Sdr, your job is gone. If you’re a sales engineer, your job is probably gone like in the next year, so we need to all rethink like my neighbor was a data scientist. His job is gone, and now he’s a prompt engineer. I was like, you need to rethink about what you’re doing. This is, you don’t have that job anymore. So yeah, I’ve.

283
00:48:40.900 –> 00:49:05.436
Jonathan Milne: We’ve seen this over and over on time, right? So the example I always like to give to was that, you know, if you think about the banking industry. When we brought Atms we said it was the end of small branches, and this is the end of tellers. Well, there are still tellers today right? Fewer. But there’s still tellers today there are more branches than ever. And if you look at the banking industry, there’s more jobs than ever created right. And so with with this change, the the CEO of

284
00:49:05.810 –> 00:49:23.640
Jonathan Milne: of anthropic talks about how he believes that they’ve already created 15 million new jobs with AI right? And these are all AI enabled, or AI purposeful jobs, right? So I don’t think in any of my careers. And anyone here who’s got gray hairs would ever say that I’ve held the same position for 30 years.

285
00:49:23.640 –> 00:49:38.069
Jonathan Milne: Right? We don’t. And so so I you know this replacement is the wrong is the wrong vocabulary. Right? We are, we are augmenting or moving into higher value or other types of skills. And this AI

286
00:49:38.070 –> 00:49:56.410
Jonathan Milne: whole change is going to create new opportunities that we never thought about right. And you know, Amanda, you said something. I think a lot of people don’t quite understand enough yet. Is that little statement that says my team is building our solutions. I strongly believe there’s going to be a big world where we are building our own tools and not acquiring them.

287
00:49:56.530 –> 00:50:20.110
Jonathan Milne: So this idea that I need to go and find somebody to buy something is going to become a little bit less and less if I have the skill, sets, and knowledge to to use cursor, and other tools that Elean was talking about, that would enable me to build more right? So so I think some things are drastic going to change. Now, I’m going to ask the same question that Julie asked me to the panelists here to wrap things up is that you know what is your one prediction?

288
00:50:20.409 –> 00:50:39.260
Jonathan Milne: In 2025. I don’t think we need to look out too much further, because I think, mark you, already hit it on the head. Things are changing very quickly, right? And I think if we look at this year, we’re going to see more leap and bounds right? And if you’re not playing with the tools and getting accustomed to it, you’re going to be far, far behind. But what do you? What is everyone’s 1 prediction of something big that’s going to happen in 2025.

289
00:50:41.005 –> 00:50:51.160
Robin Daniels: For me, I think it’s a hyper. Personalization is gonna come really real. And here in 25, I mean, it’s it’s been getting close, and I feel like it’s been building the last couple of years. But it’s been kinda honestly hit or miss

290
00:50:51.280 –> 00:51:01.159
Robin Daniels: some of the stuff I’ve seen coming out. Now to start up ecosystem. Advise a few companies who are in this space super impressive where you can reach out at scale. Let’s say you get, you know.

291
00:51:01.200 –> 00:51:24.679
Robin Daniels: a webinar, and you have a thousand people come. And then, being able to reach out at scale to all those in a with a very personalized message about what they care about their industry, their background. I feel like we’re finally getting there. And I think this is gonna make a big game at the top of the funnel. So I think these tools here that can do that and prove that they can do it well. Game changer, game changer for for top of funnel and and getting it, getting getting into it. Yeah.

292
00:51:24.680 –> 00:51:34.319
Jonathan Milne: And I shared the mistake. You very saw today where I already got an email from somebody saying congratulations on your your session. Obviously it hasn’t even happened yet. And

293
00:51:35.050 –> 00:51:35.890
Jonathan Milne: thank you.

294
00:51:36.231 –> 00:51:38.279
Jonathan Milne: Right? So I was like, Okay.

295
00:51:38.280 –> 00:51:40.318
Robin Daniels: Oh, maybe I’m wrong. Maybe I’m wrong.

296
00:51:40.610 –> 00:51:45.450
Jonathan Milne: Going a little too quickly, but you can already see the effects of it. But yeah, absolutely.

297
00:51:45.790 –> 00:51:46.920
Jonathan Milne: How about you? Mark.

298
00:51:47.140 –> 00:51:59.349
Mark Stouse, Proof Analytics: I think that that like if we, this is maybe where a compare contrast with consumer is, it has some clarity to it. Right? I think that consumers who want

299
00:51:59.460 –> 00:52:03.400
Mark Stouse, Proof Analytics: a personalized environment with

300
00:52:03.690 –> 00:52:11.030
Mark Stouse, Proof Analytics: Hermes, or whoever right are, gonna get that in spades. And it’s gonna be truly wonderful.

301
00:52:11.170 –> 00:52:15.730
Mark Stouse, Proof Analytics: Right on the b 2 b side, though all the evidence

302
00:52:15.880 –> 00:52:40.830
Mark Stouse, Proof Analytics: is that this technology, meaning AI is being actively weaponized from a defensive posture like nothing else we have seen recently. Right? And so what that’s saying is, a lot of companies don’t want this stuff anymore. Right? I mean the opening preamble of Gdpr

303
00:52:41.010 –> 00:52:48.289
Mark Stouse, Proof Analytics: sites. B, 2 B marketers as the whole reason why a long, moribund.

304
00:52:48.410 –> 00:52:53.329
Mark Stouse, Proof Analytics: regulatory system was brought back to life. Right?

305
00:52:53.590 –> 00:52:57.599
Mark Stouse, Proof Analytics: I mean, what does that tell you? Right. And so I think that

306
00:52:59.750 –> 00:53:09.790
Mark Stouse, Proof Analytics: you’re gonna see a lot more focus on effectiveness, the more is more thing, gotta know more about the person I’m talking to.

307
00:53:09.930 –> 00:53:13.530
Mark Stouse, Proof Analytics: What if the person you’re talking to doesn’t want to be known

308
00:53:14.040 –> 00:53:29.820
Mark Stouse, Proof Analytics: right? Which is increasingly the case where their employer doesn’t want them to be known, which is even more the case. Right? So I I just I, I think that the what we’re gonna see towards the end of this year in early 2026

309
00:53:30.140 –> 00:53:40.669
Mark Stouse, Proof Analytics: is. It’s gonna be a very, very challenging situation for marketers, because it’s gonna be the end of something. It’s gonna be kind of

310
00:53:41.364 –> 00:53:47.750
Mark Stouse, Proof Analytics: the king is dead. Long live the King! Right! That’s going to be the transition in a nutshell.

311
00:53:49.030 –> 00:54:08.269
Amanda Kahlow: Okay, I can’t help but just comment on not wanting to be known. I do believe that maybe our personal information we don’t want to be known. Sorry, Mark. I always keep me at spicy with you here, but I believe buyers actually want to feel heard, and want an empathetic experience, and want to hear how you’re going to solve my problems. Not just pitch me your solution.

312
00:54:08.270 –> 00:54:29.240
Amanda Kahlow: And so that is going to Robin’s point about hyper personalization. But to the question, I think 2 things are going to happen. One, we’re going to move away from a fear-based mentality to a love-based mentality, to like acceptance, and that this is like, this is the future. And this can actually help me. I think we are in this like fear world. And 2, I think we’re moving into a world of Agi. So we’re moving from, I think agents is going to be yesterday’s news.

313
00:54:29.240 –> 00:54:49.429
Amanda Kahlow: So I think agents is simple task based workflows like Mark Benioff said in his keynote. That is, yesterday. I think we’re moving to a world of Agi, where it truly understands it has empathy has Eq. It has IQ. It knows when to speak, it can carry on a conversation it can be always on available in any channel, and delight the buyers at the end of the day provide a.

314
00:54:49.560 –> 00:55:14.019
Robin Daniels: 10 x better buyer experience than what we’re putting people through today. The world we put people through is archaic. It’s expensive. It costs money on the seller side, like, Oh, my God, the shit we put like how many people at the problem, to sell one piece of software and like what we go to a website, get to dig around and find the solution. And then you talk to an Sdr. Who’s 20 years old and try to qualify you, and then you get to a salesperson, and the salesperson then does can’t answer the technical questions like.

315
00:55:14.340 –> 00:55:30.689
Amanda Kahlow: Tell me that this is the way anybody wants it, and on either side of the equation. So I think we’re we’re definitely moving to. I am so excited to solve for Agi to solve for hard problems the nuanced problems that will make this work. And yeah, I think agents are agents are yesterday. So that’s.

316
00:55:30.690 –> 00:55:32.080
Mark Stouse, Proof Analytics: But my prediction.

317
00:55:32.080 –> 00:55:34.549
Mark Stouse, Proof Analytics: I agree with that. I agree with that. But

318
00:55:34.800 –> 00:55:39.660
Mark Stouse, Proof Analytics: right who’s controlling the personalization is key.

319
00:55:40.030 –> 00:55:40.700
Mark Stouse, Proof Analytics: So.

320
00:55:40.700 –> 00:55:42.510
Amanda Kahlow: Yeah, I think in some this is the fireside.

321
00:55:42.510 –> 00:55:51.929
Mark Stouse, Proof Analytics: Hold on, hold on, we. We have an Llm driven site. Okay, what does that mean? It means that we we see thousands of questions a day.

322
00:55:52.040 –> 00:56:00.940
Mark Stouse, Proof Analytics: And people are asking questions in which they need a con, a context, aware answer, and they get it right.

323
00:56:01.050 –> 00:56:13.069
Mark Stouse, Proof Analytics: And so we are helping them. We are collaborating with them, or, more accurately, the Llm. Is right collaborating with them to give them a personalized answer.

324
00:56:13.270 –> 00:56:15.229
Mark Stouse, Proof Analytics: but they’re calling the tune.

325
00:56:15.470 –> 00:56:16.010
Amanda Kahlow: Yeah.

326
00:56:16.010 –> 00:56:38.969
Amanda Kahlow: I think the control has to be in the buyers. I’m not. I don’t disagree with the control being in the buyer’s pocket, but I think the buyer side agent only really works like I’m not going to go build myself a buyer side agent for everything that I buy. If I’m like a repeat purchase person, or I’ve got a long sales cycle. Maybe I’ll like we’ll invest in that like some of the shorter purchases. Maybe not. You know where you just want to get in, get done like I’m buying a $10,000 like whatever it is.

327
00:56:39.140 –> 00:56:57.059
Amanda Kahlow: It just really depends on the product and the solution we’re selling. But I’m with you like we need to organize our data in a way that the agents and the superhumans and Agi could talk to each other versus it just being like the human to data. Or it’s it’s really data to data. But allow the human to come in when it’s relevant.

328
00:56:57.890 –> 00:57:20.400
Jonathan Milne: All right. We’re going to have to wrap this up. So I’m going to just say, and I’m going to give you the final thought Nalin in one second. But, Julia, thanks for putting on the conference. Thank you, Robin. Mark, Nalin, and Amanda for the conversation. I love it. I love that there’s debate and different opinions, and I’m going to give naling the last final thought to wrap up our AI Led marketing panel and thank you for everyone for listening to us today.

329
00:57:21.410 –> 00:57:46.960
Nalin Senthamil: Thank you. Yeah. And I think I’ll agree to the Agi part. Which you know, Amanda mentioned. I think the way it will happen to me is like we have a team of agents today, right? That everybody’s building to do a certain task. What I do predict and happen in the end of 2025, early, 2026 will be agents building more agents for you, and that’s going to snowball into more of these things. That’s how the Agi will be achieved where you train your agent to build additional agents for you to you know to complete your task itself.

330
00:57:47.000 –> 00:57:55.350
Nalin Senthamil: and to me that is what the AI led motion will be a lot more. And I do see that happening a lot more than this year itself. Yeah.

331
00:57:59.230 –> 00:58:07.469
Julia Nimchinski: Thank you so much, everyone. Thank you so much, Jonathan. What’s the best way for our community to support you? And let’s transition to the next fireside chat.

332
00:58:10.430 –> 00:58:11.460
Julia Nimchinski: Jonathan.

333
00:58:12.380 –> 00:58:14.330
Jonathan Milne: Sorry I didn’t hear that last part.

334
00:58:14.330 –> 00:58:18.590
Julia Nimchinski: Yeah, thank you. And what’s the best way for our community to support you.

335
00:58:19.120 –> 00:58:47.010
Jonathan Milne: Oh, absolutely so. Please reach out to us on demand, spring on Linkedin or Twitter. We would love to hear from you. We love to have these discussions. I think the one thing that everyone should take away from the next 3 days in this conference is, there are no answers. There are only strong opinions today, and the future will tell us what happens. But between now and the future we need to just keep experimenting. Keep trying new things, and don’t be afraid so absolutely. Thank you so much, Julia.

336
00:58:47.710 –> 00:58:48.900
Julia Nimchinski: Our pleasure.