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Transcript

• 02:29:04.010 –> 02:29:09.780
  Julia Nimchinski: Welcome, Warren Zenna, the founder of 0 Collective.
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  Warren Zenna: Sure. Sure. Thank you so much, Julia, for having me, and sorry about jumping the gun before. I wasn’t sure about the protocol here. In any event, it’s good to see everybody and we did have some prep conversations. So well, we’re gonna forego some introductions and just jump right into it.
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  Warren Zenna: yeah. The title of this particular panel is important, because, as you know, some may know, some may not know. I probably speak to
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  Warren Zenna: I don’t know. Got hundreds of cros over the last years who
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  Warren Zenna: and I’m constantly hearing the challenges we’re having related to this particular topic.
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  Warren Zenna: And I think, if we may kind of frame the discussion here, the best way to look at it 1st is is that Cros are
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  Warren Zenna: moving from being sales leaders to systems, builders and systems leaders.
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  Warren Zenna: And that’s an increase in their competencies that they need to develop. And
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  Warren Zenna: so 1 1 hand, they’re looking to expand their competencies. But then, with the advent of AI, they’re also having to learn how to shrink their competencies. And that’s a very confusing thing for chief revenue officers right now, this sort of weird sandwich they’re in between a ball to expand, how much they’re doing and also how to shrink it by use of being more productive. And AI is sort of looking at a solution to that.
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  Warren Zenna: So I think the purpose of this dialogue is to ask these great experts on this panel a little bit more about what our Cro supposed to do, you know? Like, if I’m a chief revenue officer today, I’m thinking about the advent of these new technologies and this whole new world. What does it mean for me? And you know, 6 months from now the world is going to be somewhat different. What choices do I have to make today? That’ll either keep me at pace with what’s going on or the mistake. I’ll get into being in the wrong place 6 months from now. And where do I start?
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  Warren Zenna: So I think the 1st thing that we maybe we can just jump into is 1st of all, is is,
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  Warren Zenna: You know, the idea of what does an agent mean for a Systems chief revenue officer? What would that mean? And what were some ways that you know, we should be looking at the world of someone who’s operating a large revenue operation. And the conversation that we we started earlier today in our prep call was really compelling. And this idea of all the different let’s say.
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  Warren Zenna: factors that are pushing down on chief revenue officer to make decisions. So I if you don’t mind, I’m gonna start with with Matt, because, you know, we kind of. Kick this off a little bit earlier. If you don’t mind, Matt, I get your kind of high, level thoughts on, like where you think the role. The chief revenue officer is playing out now, and what you think that this sort of means for them, some things they could start thinking about today to think about what
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  Warren Zenna: what they could do to prepare for this new new planet. They’re living on.
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  Matt Darrow: Yeah, thanks, Warren. And and Hey, guys and Julia, glad to be back Matt Darrell, co-founder, and CEO of Vivin.
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  Matt Darrow: Over here, you know we live this, too, Warren. I think that’s why maybe our story is kind of interesting. You know I had a prior head of sales that this was probably 2 years ago that 1st was struggling to do the expansion remit because I wanted to roll things like customer success sales engineering, all under one umbrella to have a true revenue owner and a revenue function. We have that leader now, but that was like sort of click. Stop one
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  Matt Darrow: of going from old World 0 that just focused on sales to somebody that had more of a broader revenue remit. And now I would say, the thing that
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  Matt Darrow: we’re focused on so much is, how does our Cro not only become hands-on and comfortable with a lot of these new technologies, but they’ve got the right partner in crime from the revenue operations standpoint that’s going to bring the right things to their table. So you asked the question like, Well, what is an agent? And I remember Julia, like a couple months ago. We kind of famously talked about that, too, like everybody, had a different answer. My perspective is pretty simple, which is, it’s a domain expert that can do unprompted.
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  Matt Darrow: and that changes everything from these new guard Cros, where I don’t need a Cro to go and build applications from scratch, but they need to deploy these so they could take work off their team’s plates, and I’m sure the other crew has some good anecdotal stories, too.
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  Warren Zenna: Yeah. So I’d love to hear some other members of the panel weigh in on this topic. I’d like that definition. By the way unprompted. I I didn’t think about that. That’s actually a very good distinction to me. I don’t know, James, you know you and I had a little conversation earlier, you know, I’d love to get just some of your high, level thoughts on this.
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  James Roth: Yeah, I mean, listen. I think a couple of Matt’s points that I really like the the partner in crime, if you will. I think the the concept of a Cro. The role itself has to change. Fundamentally, I think there are going to be skill sets and competencies that folks have.
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  James Roth: We talk internally a lot about the operational rigor you talk about the sales leadership, the locker room, all of these different things. It’s very difficult to find someone that has all of them. And so I think, augmenting some of those with the right team and the right people, and obviously depending on the size of the company or the resources that the company has. You’re not going to be able to have, you know, 4 to 5 different folks from chief strategy officer to chief growth officer, or all the above. But I think you know.
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  James Roth: one of the unique positions that we’re in, you know, sitting in go to market is, I think, from a strategy standpoint.
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  James Roth: it’s basically finding waste anywhere within. Go to market. And so, you know, I think.
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  James Roth: becoming more frontline focused across Cx across Cs across sales. Sdr, and basically finding out, where do you waste the most time building decks formulating a point of view? Where are these areas that across all of these functions are causing people the most friction
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  James Roth: that really makes them hate their job, and I think doing that on a regular basis. And then what of those can we solve with an agent, with some form of AI? And you know again, the ideal goal for us is, then what can we then package from a go to market standpoint, put into a product, and ultimately help sellers and marketers across the board? And so again, I think just to double down. It is
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  James Roth: at this moment in this, like, what’s noise versus what’s real across prioritization and sort of offloading busy work. Or, you know, helping sales folks that might not just have an innate point of view and understanding what’s happening in a vertical like, how can you equip them with almost this massive brain that they may or may not have no offense to some of them. But they might have skill sets or expertise in other areas
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  James Roth: that you know, they’re unbelievably charismatic. They’re great at building rapport, but they’re horrible at some of the organizational stuff. I think it’s this democratization of how can you make all of them pretty good. And what can you then cut out of their day from a waste perspective that allows them to go lean into that superpower. So I’m not going to try to restate Matt’s definition. It was really good. I wrote it down.
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  Warren Zenna: I did, too.
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  Warren Zenna: You’re great. Yeah, thank you. James. Ashley, I know you had some really good thoughts on this earlier today. What what are your thoughts on this.
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  Ashley Wilson: I think what James just said. I’m actually one of the co-founders of momentumio. And and one of the things, James, you just made me think about is that I think that the Cro
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  Ashley Wilson: role requires a new level of curiosity. And then I think we talked earlier about how, for non-technical folks.
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  Ashley Wilson: AI can feel very intimidating. And and we’ve gone from Chat Gbt, introducing AI in a way that feels like okay, this is relatable. But I think when you’re going into the vendor process, and you’re thinking about how to apply it to your workflows, and you’re hearing the word agents all day long, it feels very much like, Okay, I somebody’s gonna figure this out for me, but it’s not gonna be me. And so when they do figure it out, please let me know. And I think that that can kind of turn off some people
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  Ashley Wilson: and kind of stop the curiosity process to say either. Okay, I I know that I need to go fix this, or I need to go identify these problems. That’s why, like James, what you said is, if you’re if you’re not technical, or you find it to be intimidating.
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  Ashley Wilson: applying it to the things you want to answer, which is just like, Where is my team wasting time.
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  Ashley Wilson: The second answer will be like, Go solve for that, and that’s where you could lean on your Rev. Ops teams or your growth teams, or, if you have, you know, a data team to go solve for it. But I think that the the biggest blocker sometimes is just our own personal
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  Ashley Wilson: discomfort with new tech, especially something that everyone’s talking about. And you don’t really know how it’s gonna apply. And I think that us, too, is selling kind of AI tooling and being vendors. That’s a big part of what I think we need to bring to the sales process is just like demystify. Lower the bar and make it seem achievable in a short amount of time to actually see real gains.
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  Warren Zenna: I want Matt. You mentioned your head. Yep.
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  Matt Darrow: Yeah, I wanted to jump into because you both talked about that concept of waste 100% like, because there’s so much low hanging fruit to take off of people’s plates, and that’s what AI is really great at. But I would say it to be really smart as a Cro to say, Well, what type of waste are you trying to automate? Because you don’t want to go and just lock yourself into the old world? I’ll give you 2 like simple examples.
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  Matt Darrow: What’s 1 thing that sales reps hate to do all the time? Enter data into their Crm system. So you might be inclined to say, Well, great! If I have an agent that’s puts data into my Crm system.
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  Matt Darrow: I’m taking that off their plate that’s missing the forest for the trees that, like in the AI future data in a structured system doesn’t matter anymore. Like those things become irrelevant, like when your systems have context, across conversations, calls emails, slack messages, web. Everything that a human has like this antiquated mode of like filling fields out is is a No. OP. In the future. I’ll give you a second example, too, which would be like.
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  Warren Zenna: Life.
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  Matt Darrow: Building a sales presentation today, y’all are probably using high spot seismic, some enablement tool that has the second call deck that has the proposal deck that then the rep goes to takes it. Tailors it, but but like that notion of enablement systems like housing all the information that’s also sort of a no up for the future, too, because an agent can do the to your point, James, the brain work, and then you can feed it into these new applications
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  Matt Darrow: that will spin up a deck in your branding on the fly exactly when you need. So yes, to eliminating waste. But don’t eliminating the waste that you sort of.
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  Matt Darrow: We’re accustomed to doing things for the last 10 years.
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  Ashley Wilson: Don’t you think you gotta like, crawl, crawl, walk, run! I I agree with you. And from like a vision standpoint I think the world is going there. But like tomorrow, you still need to fill data into salesforce. And so I I think that like, there’s some of that of like you gotta think about the future, build for the future in your own org. But also.
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  Ashley Wilson: what’s the next 3 months gonna look like? What’s the next year? And I don’t think I bring this in our own experience. We’ve heard a lot in the last year of like, can you push the snowflake? We want to do stuff in a data lake. But then when you actually dig, and you’re like, Okay, where do you want it to go? And they’re like, Okay, we’re not quite there yet, but that’s what we want to build for this year. So I think that there everyone knows where the the trends are maybe going, especially if you’re kind of living in this world.
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  Ashley Wilson: But I do think that like change still takes a while. And if you think about a huge company, the reliance on salesforce. It’s like we’re gonna we’re still a ways away from not needing data in salesforce.
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  Warren Zenna: It’s great stuff, Rasheed. You have a hand up.
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  Rachit Kataria: Yeah, I’ll jump in here. How’s it going, guys? Ratchet co-founder? CEO centralize? Maybe an interesting take here, I like to say is, our tagline is where the r in your Crm, if it actually worked, which my resume here. Only enough, Matt. We’re both, you know, salesforce ventures port codes. So I’m saying this because I’ve told them directly, guys, you’re literally a database. It’s an incredible database. You can’t live without it.
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  Rachit Kataria: But it is a database of names and contacts and accounts, and it has to be updated to your point. Ashley, like that context needs to be there, but it sucks that. It’s so manual. But the way we’ve heard from a lot of Cros, this model of okay, I have all these systems of record. Now, I have my call recordings, my Crm, my conversational data and my slack and my emails, even my Linkedin relationships, is its own Crm.
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  Rachit Kataria: Oh.
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  Rachit Kataria: what do I do about it now, like, what is the next phase of turning the systems of record into system of action? I think that starts becoming the kind of what we’re working towards. But I agree with you in the sense that
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  Rachit Kataria: no one is going to adopt a tool or a platform, or a way of thinking that does not ensure your systems of records are hygienic. And up to the data standards that you need to power the actions that you’re trying to work off of. So I think it’s almost a non-negotiable in my mind that those come along for the ride, and then you live on top of all of them to make a difference, and then actually move the needle on finding the deals that you’re working through. So I like to throw in a tidbit on
• 978
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  Rachit Kataria: like the R. Is missing, and and I think.
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  Warren Zenna: They get it.
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  Rachit Kataria: It’s lazy data.
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  Warren Zenna: Thank you, Manisha. You have a question point.
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  Manisha Raisinghani: Yeah, hey, this is Maneeka. I’m the founder of Sift Hub. So just to, you know, James. Point of how can every a work like a best. A. Because, as James said, right, even though we don’t want to call it Cloud. But there, most of the most of the sellers they don’t want to do the hard work. They don’t want to do personalization because it actually needs a lot of research. It needs a lot of hard work to build personalized decks.
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  Manisha Raisinghani: But now AI can do that for you. Right? I think. What Cros can focus on now is how to
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  Manisha Raisinghani: you know, have all your A’s perform like the top 10% of your A’s, because that’s 1 of the forecasting problems where 10% A’s will bring 80% of the business and then rest. You know, 20% of the business is bought by 80% of the A’s so that can be changed now, and actually to your point of crawl, walk, run!
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  Manisha Raisinghani: I think that’s the biggest dilemma Cros are facing today. From all the conversations I have been having, because the things are moving so fast. They are actually, you know, once they are starting to crawl
• 986
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  Manisha Raisinghani: the A with the AI advancements, they have this realization. Oh, my God! Doesn’t look like you know the crawling is going to work here. I need to now run behind so and so.
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  Manisha Raisinghani: So if you. I’m sure you know, while you you guys have been talking to Cros earlier, they were kind of relying on these AI councils which they were building in the company to onboard all AI tools. A lot of these companies tried this for 2 months, and then they actually scrapped that method. They just told their leaders Board and Ceos. They told their leaders, individual department leaders
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  Manisha Raisinghani: that it is your responsibility to bring on AI agents to bring AI tools and improve efficiency of your team
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  Manisha Raisinghani: because it’s today for Cros. It’s not just about, you know, improving productivity and helping with bottom line. AI is actually helping with top line as well. And wherever you know top line conversations come into picture
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  Manisha Raisinghani: it. It has to be the responsibility of those department heads.
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  Warren Zenna: Hey, Josh? Let me share your thoughts on this.
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  Josh Solomon: I think the I think the groups covered it off pretty well. I mean to me. I I tend to. I tend to fall in the camp of like the Crawl Rock Run is the best approach here.
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  Josh Solomon: and I think you know, James articulated it pretty well. There are tons of areas of waste across our go to market playbooks, whether they’re pre sales or post sales that we can automate today.
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  Josh Solomon: And we can remove where our reps focus their time. And I think what that truly means, and where I think the biggest area of opportunity might live today. For for Cros is well, what’s the new definition of a good hire in my business. What is the supporting cast in the business look like today that I put into my pre-sales motion that I put into my post sales motion. What’s the ratio that I actually stretch for from a test to Se. Or to Sdr.
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  Josh Solomon: And I think some of these things in the business can be fundamentally challenged as you start to think about your capacity model. If you can really remove the waste from the sales cycle or from the from the deployment processes.
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  Warren Zenna: Yeah, so go ahead. James.
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  James Roth: Yeah, I mean, I think 1 1 piece on the Crawl walk run, and it’s certainly top of mind. We’ve got our board meeting next week, and this is a hot topic of conversation. You know, you got a lot of firms that are building their own quote unquote. You got people that want to buy prepackaged AI solutions from all of the regular folks. And so we’ve created like a go to market maturity matrix.
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  James Roth: And we’ve got across again, a lot of customers, 7, 8 figure customers that are
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  James Roth: in different stages of the journey, you know. And so if they’re in a full build, they’ve got a team of engineers. They’ve got an unbelievable data, lake Snowflake, and they’ve got very smart people, you know, in for us. And again, cro zoom info! By the way, I don’t think I introduced myself, but in those situations they’re just buying huge amounts of data to build out a large data model kind of what Rachit was saying around, you know, getting all of the different siloed data right? They’ve got these huge
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  James Roth: instances. They call them things like crystal ball or Artemis, or these really cool names of basically centralizing data and then running go to market at scale on their own. And then you’ve got on the left side folks that are just buying it. And I don’t think it’s not necessarily vertical specific. It’s not size specific. You have small companies that are far ahead on the go to market maturity index. And you have very large companies
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  James Roth: that you would imagine are incredibly tech forward that aren’t. And so I think, as a Cro coming in to a new organization, and I believe at least I feel Cro and I think Cmo are the 2 most replaced roles in sports. And so if you’re a new cro coming into an organization.
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  James Roth: the ability to basically figure out if the organization has been in crawl, or if they’re in walk, or if they’re in run and understanding where they’re at in that journey and not trying to bite off too much too fast, and basically getting the foundation right?
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  James Roth: And I think in so many of these things to the Crm.
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  James Roth: I think we all know, and we’ve all been around it, and very similar. Not a salesforce venture, but a huge partner, you know. Big number one app in the app store. 20,000 connected customers like they’re friends, but I think that promise of it being a go to market repository when 90% of what’s inputted into it is just Rep. And there’s this brilliant marketing thing like your data is your data. And so it’s the reps fault. And I think every Cro for the last decade has said, it’s rep hygiene.
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  James Roth: And so you go walk the floor and tell reps to inputs. There’s meme pages dedicated to just vps of sales telling people to Update salesforce. And so I think it’s very clear that there’s a problem at the foundational level. And most of the really cool tech is sitting on top of that.
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  James Roth: And so a lot of people don’t want to go attack the fundamental data problem, which is, you have data sitting in Snowflake. You have data sitting in databricks. You have data sitting in. Crm, you have structured data, unstructured data across a million different tools. And we’ve gotten to this place where, if I say, I want to go, run a competitive takeout campaign. I’ve got to engage revops. I’ve got to engage CIO. They’ve got to pull data from Crm. They’ve got to pull data from conversations, and it takes 2 months
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  James Roth: where it used to be as simple as just like, I want to go after everybody that’s got this particular technology.
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  James Roth: And so I think, getting that foundation right first, st and then, being very curious, I think it was Ashley that brought up the curiosity. I think, as Cros, you kind of get out of taking a lot of Demos because you’re very busy. There’s a lot of things, and everybody’s trying to sell something to you, and I think, getting more thoughtful in terms of leaning into these areas in both networks like this to say, what are the cool things that you’re doing? We’re trying to solve this on a health score risk model. Show me the next things that are going to downsell, based on all of this structure and unstructured data.
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  James Roth: talking to those folks leaning into it, but getting the foundation right at the particular point
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  James Roth: that you or your company are in or have been in. I think that’s really the key for a Cro to be able to identify. I’ve got to fix this first, st or else you end up with where a lot of people have ended up through the good times, which is, I’ve got 65 tools that all had the promise of amazing things, and none of them are working well together. None of them are really being used, and none of them are really driving the outcomes that we thought they were going to. Now I’ve got to go get rid of half of it, and I’m not.
• 1011
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  James Roth: We’re not really quite sure what to get rid of.
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  Warren Zenna: You know, James, I appreciate that so much, because this is exactly what I’m talking to with my clients daily, and this is the issue which you just said is that Cros are being asked to solve problems that are very short term problems.
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  Warren Zenna: But they can’t solve longer term problems because the infrastructure of their systems are not updated enough for them to do so, and they don’t have the time
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  02:49:27.680 –> 02:49:47.179
  Warren Zenna: to be able to work enough on the strategies that take, as you know more, what you described takes time to do right takes resources of time. Sometimes the machine has to be shut off for a little while for that stuff to be fixed, and I can’t fix my Crm while I’m using it. At the same time. It’s a very difficult thing to do, at least do it in in the right way. So the notion of hearing a lot about this, which is fascinating
• 1015
  02:49:47.530 –> 02:49:56.269
  Warren Zenna: is the larger companies that have more complex problems, right? Those those comp, those problems you you describe they compound when you’re a bigger company, they’re much more complicated to fix.
• 1016
  02:49:56.310 –> 02:50:07.360
  Warren Zenna: So it’s the earlier stage companies that have the advantage with this stuff today, because they have less to deal with in terms of the problem, they could fix it easier and quicker. I mean the question I posed this panel is, do you then think that
• 1017
  02:50:07.360 –> 02:50:35.359
  Warren Zenna: the smaller Smbs necessarily, but growth, stage or startup companies are really in a position to be faster movers with some of this stuff than larger companies that have much bigger problems to solve. And if you’re a provider of AI services. You go after smaller companies that are more nimble and that can use things and adopt things with more alacrity. Or do you go for the big guys and try and get a bigger bite of the pie. And where where’s the market going to move? I think with this particular technology, it’s going to be a bit different. I’m hearing that a lot. I’d be really fast to hear your thoughts on that.
• 1018
  02:50:35.910 –> 02:50:36.850
  Warren Zenna: Anybody.
• 1019
  02:50:38.480 –> 02:51:00.359
  Ashley Wilson: I think some of the things that we’ve seen is that we’ve kind of had to change our pitch and our packaging depending. If it’s more upmarket enterprise versus mid market or Smb. And I think James pointed it out to, or somebody, maybe Matt. But, like the difference of build versus buy at the Enterprise level, where you do have the resources to gather the teams to get the data.
• 1020
  02:51:00.360 –> 02:51:19.730
  Ashley Wilson: put it in the data like, get the insights versus the small company doesn’t have those resources, nor do they want to spend their time doing that. So I think for us at momentum as we sell it. We’ve had to kind of think about. You have to figure out how you’re going to plug your system into that initiative. That’s ultimately going to be building a lot of agents in house.
• 1021
  02:51:19.960 –> 02:51:39.179
  Ashley Wilson: And in our case, like our value prop is, you know, taking unstructured conversational data and making it structured and clean. So we’ve become a a piece of the much larger puzzle versus trying to come in and say by momentum for XY, and Z. Like you could do that, and some customers do. But on the smaller side you come in a lot more with out of the box
• 1022
  02:51:39.410 –> 02:51:49.720
  Ashley Wilson: agents, out of the box workflows things that just you don’t have the resources to go stand all that up, and you need to have time to value much quicker. So I I think that that’s
• 1023
  02:51:50.020 –> 02:52:01.819
  Ashley Wilson: been a really kind of fun and interesting go to market and positioning challenge for us, and also to listen to as we have these different conversations. How do we adapt like you ultimately can’t. As a.
• 1024
  02:52:01.930 –> 02:52:19.019
  Ashley Wilson: you know, smaller company, you really can’t build a ton of new products to service all these different markets at our stage, but I think it does become a bit of a packaging and positioning to say like we can fit in here, or we can sell you the whole thing, and we can go after both audiences that way.
• 1025
  02:52:19.950 –> 02:52:21.580
  Warren Zenna: Thank you. Rashid.
• 1026
  02:52:22.850 –> 02:52:28.590
  Rachit Kataria: Yeah, I can chime in here. I’ll actually share an anecdote from a head of revops I talked to like a few weeks ago at a
• 1027
  02:52:28.981 –> 02:52:37.940
  Rachit Kataria: deck of corn, you know, late stage private company. I wouldn’t say they’re Smb. They’re not Ipo, but you know they’re like right about there, and it’s interesting. He was telling me that
• 1028
  02:52:38.360 –> 02:52:47.329
  Rachit Kataria: he’s getting pitched tools all day long. Right, like Rev. Ops is now almost the gatekeeper. Out of necessity. They’ve been burned in the past so many times with tools that promise and don’t do anything. And now
• 1029
  02:52:47.650 –> 02:53:00.279
  Rachit Kataria: to to the point here, Cros have to have that strategic partner to really vet like what? What is actually going to do, what we need. And the biggest concern he had was that a lot of tools promise these new workflows, these new ways of thinking
• 1030
  02:53:00.330 –> 02:53:19.590
  Rachit Kataria: that are all not actually core to the workflows he needs to solve today at the baseline, that foundation we were talking about. I think, James, you might mention, like the core foundation to solve, for if that’s not rock solid, all of these new ways to think actually ends up being almost like a scary thing. It’s like, I don’t want to go there if I don’t feel like I’m in a good spot at the foundation.
• 1031
  02:53:19.590 –> 02:53:34.010
  Rachit Kataria: And and so a lot of what he got excited about was when tools come in and say, Hey, I already have these core workflows. I want to think about, you know, account planning and relationship, mapping and research and doing things that are more efficient for my existing team. That’s taking so long the the waste to your point, James.
• 1032
  02:53:34.120 –> 02:53:52.270
  Rachit Kataria: Then he feels like that’s a great place to begin, and can start expanding his mind to everything else that’s possible from from that 1st solve. So maybe actually, your crawl walk runs like the walk phase. If anything like getting that point, the latter point I’ll just call out, too, is, I’m now reflecting it kind of jog my memory. This year I talked to a few weeks ago, said.
• 1033
  02:53:52.370 –> 02:53:56.909
  Rachit Kataria: there’s all the fancy fun stuff about celebrating and being in a good spun and closing the quarter.
• 1034
  02:53:57.060 –> 02:54:18.200
  Rachit Kataria: But the one really boring thing every cro wants is governance. It’s just the basic understanding that everyone on their team has a standard they’re holding themselves to. And the entire team is operating against that standard for those workflows that robops is helping them solve. For if you don’t have that joint communication of here’s what I know needs to be true, and revops, please help me find and solve that baseline
• 1035
  02:54:18.300 –> 02:54:31.080
  Rachit Kataria: everything to them frankly feels like scary noise, because it is just a lot of things that you can go and explore. But I’m noticing trend if you can really get those baselines down again. Very core workflows. I think all everyone here tries to solve for
• 1036
  02:54:31.160 –> 02:54:58.299
  Rachit Kataria: multi-threading relationship mapping account research, planning signals, all of the ways that you otherwise would spend 10 HA day trying to do. That’s where the meat of the value is, and then that’s your in, especially an enterprise to say, Okay, great. You’re feeling good. We’re rock solid. We’re powering your your core engine. Let’s go think about everything else that agents flying around unsupervised can go do for you from there. So just 2 anecdotes I kind of realized marrying in my head after this conversation.
• 1037
  02:54:58.850 –> 02:54:59.530
  Warren Zenna: Thank you.
• 1038
  02:54:59.680 –> 02:55:00.620
  Warren Zenna: I was hoping to.
• 1039
  02:55:00.620 –> 02:55:30.320
  Matt Darrow: Answer the question directly to that. I do think that the smaller players have an advantage here, and I’ll mention something that Josh, I think you’ll feel passionate to chime in on is one of the things that the big players, I think, have going against them is that they have so many sort of large vendor agreements already in place, and as every Saas company on the sun has bolted AI onto their service, they’re in a mode where they need to evaluate what they already have 1st
• 1040
  02:55:30.340 –> 02:55:54.365
  Matt Darrow: to fail, 1st with what they have before they move to a more sort of AI native way to go and approach and solve that problem. I know that you know you asked the question about selling to early stage versus Enterprise, or we do both at Vivin, and like James, we run into a lot in the large enterprise you have people that are like, we’ll just build everything we got a day like we got this, we’re going to go whip up all this stuff custom. It’s almost like when Cloud came out. They’re like, Yeah, we’ll just go build everything in the cloud and
• 1041
  02:55:54.590 –> 02:56:22.800
  Matt Darrow: What they’re trying to do 1st is experiment with not only their own tooling, but then the things that they’re really really large vendor providers already are giving them, and it takes them 6 months to figure out. Oh, crap! The stuff that’s bolted on doesn’t work. Now I need to go through another evaluation cycle to say, How do I take those use cases off the plate? And I think when you’re an earlier stage company or cro like you don’t need to be as encumbered with a lot of the top down. I gotta do this before I do that, and you just have more freedom to move faster.

• 02:56:24.520 –> 02:56:44.659
  Warren Zenna: So I wanna shift gears a bit because we’re we’re talking here about Agentic AI, right? Which is, I think, beyond which we’re at right today, which is I I completely agree. We’re really in sort of like a low hanging fruit opportunity to reduce waste. And I see a lot of companies and my clients doing that sort of thing trying to close gaps, which I think you know we we’ve spoken to pretty clearly.
• 1043
  02:56:44.840 –> 02:56:51.760
  Warren Zenna: but the future is, and I’ve seen this right. I’ve had some people come into my world recently who have shown me examples, live Demos, of
• 1044
  02:56:51.840 –> 02:57:16.209
  Warren Zenna: ways in which one person can create an entire go to market campaign. That includes everything from research to targeting to email campaigns that are really, frankly, mind blowingly good, like, not just a good email. But we’re talking about like incredibly precise, that one person can do. And this was very much done. If I would say in an agentic way, much to to match definition. It was like he asked questions, and it was produced without much prompting.
• 1045
  02:57:16.930 –> 02:57:33.430
  Warren Zenna: But I do see this as a reality. I mean it’s out there. There’s a future where this could happen, maybe closer than we might think. I don’t know how how much is going to become ubiquitous, but what’s the transitional sort of advice or guidance that all of you would give to a Cro who’s looking to move from, let’s say, maintenance mode
• 1046
  02:57:33.500 –> 02:57:55.929
  Warren Zenna: to really, truly adopting agentic mode where they’re kind of like having machines sort of do things for them on a regular basis. And you know, I mean, it may be early to us to be able to make some sort of an advisory thing, but you’re all an advantage where you’re seeing a lot of things, and maybe a lot of people aren’t. What might a transition to that phase look like today, so that maybe this year of listening could get a little bit more sense of
• 1047
  02:57:56.040 –> 02:58:10.189
  Warren Zenna: what should they be looking for, or what’s that transition timeframe, or what might the tools that they should be thinking about, or what might ways that they should be structuring their organization today. Keep preparing for these sort of things. I’m open to anybody.
• 1048
  02:58:11.020 –> 02:58:12.140
  Warren Zenna: Go ahead, James.
• 1049
  02:58:12.800 –> 02:58:15.589
  James Roth: I think Manisha had hers up first.st So.
• 1050
  02:58:15.590 –> 02:58:17.750
  Warren Zenna: Oh, I apologize. Go ahead, sure. Go ahead!
• 1051
  02:58:18.340 –> 02:58:27.529
  Manisha Raisinghani: So. I think it’s the way we are when we are talking to Cros. The way we are suggesting them and their teams are comfortable is
• 1052
  02:58:28.280 –> 02:58:32.899
  Manisha Raisinghani: being AI being an assistant today. And once
• 1053
  02:58:33.460 –> 02:58:45.139
  Manisha Raisinghani: teammates have trust that AI can actually do some of the things. Let’s say, you know, give answers to questions, or fill their rfps, or create personalized decks for them.
• 1054
  02:58:45.290 –> 02:58:56.639
  Manisha Raisinghani: then going into the agentic mode and then going into autonomous mode, so the transition is from being an assistant to agentic to autonomous.
• 1055
  02:58:56.730 –> 02:59:18.579
  Manisha Raisinghani: Today, I think the biggest problem which, you know, we as users of AI feel is, how do I trust it, you know, if it is going to send an email on behalf of me to my customer, I’m absolutely not going to do that. I’m not going to keep an auto reply on to my customers, or even to you know. Let’s say my team or board members.
• 1056
  02:59:18.800 –> 02:59:38.010
  Manisha Raisinghani: I want to see the draft first.st I want to read through it, and then only if I’m comfortable I’m going to send that hit button hit the send button right? So once you need to build that trust on AI that it can actually do what it’s supposed to do. Because the expectations today all of us
• 1057
  02:59:38.030 –> 02:59:53.560
  Manisha Raisinghani: have from AI is here like literally here, 3 years back, it was 0. And now it’s here. But AI is still here, right. I mean, this is still very, very high, but the problem is the expectations we have that it can literally do anything and everything.
• 1058
  02:59:53.830 –> 03:00:11.769
  Manisha Raisinghani: I’m sure we are going to get there, but it needs a fine tuning of the flows, fine tuning of the information which is available in the organization to make it go there. And I think Cros, which have already tried and burned their hands with agent force.
• 1059
  03:00:11.780 –> 03:00:34.910
  Manisha Raisinghani: assume, thinking that it is going to do everything for you. They are in a different zone in their journeys right? Because the journeys of every company is different. Some would have tried agent force assuming, oh, it’s going to solve all my problems. Some companies have gone with building internally, and then in 3 months realize? Okay, we have built a bot. But then, now, what you know.
• 1060
  03:00:34.910 –> 03:00:45.789
  Manisha Raisinghani: a bot can probably improve 30 40% of the productivity versus, if I buy a point solution to solve a particular problem, it is actually going to help me with 70 80%
• 1061
  03:00:45.790 –> 03:01:14.120
  Manisha Raisinghani: productivity. And that’s where what we have done is land and expand motion works really well here for both the buyer and the seller, because your buyer is not committing a big contract to a seller and seller is also, you know, proving the value. One use case at a time and building that trust with the users, so that you can move from being an assistant to agent to autonomous.
• 1062
  03:01:15.460 –> 03:01:16.969
  Warren Zenna: Thank you. Go ahead, James.
• 1063
  03:01:17.130 –> 03:01:42.689
  James Roth: I think it’s really well said, just on a on one very tactical item. I think you know, Cros in general need to be just maniacal on a B testing, I think. Given the amount of noise that’s out there, you know, very different stages. Clearly, if it’s a small kind of startup scale up, and you can either not hire 25 people or build out Warren, the campaign you were talking about very low risk in in trying that.
• 1064
  03:01:42.690 –> 03:01:58.219
  James Roth: But I think with more mature companies, the Ab. Testing, I think, Julie, I sat in on a session earlier today. There was the chat. Talk about an AI. Sdr. It’s a big article that hit the press that we may or may not have been in on the other side, but
• 1065
  03:01:58.410 –> 03:02:20.949
  James Roth: we piloted it out, and I think what you find with some of these things. When we had our live Sdrs and we had the Virtual or the AI. Sdr. You know there are regulations. If you’ve ever tried one. We started building one to be honest and due to regulations and compliance. You have to. 1st thing you say is, this is James Ross Zoom. Info’s AI Sdr. Press 2 to opt out.
• 1066
  03:02:21.580 –> 03:02:29.070
  James Roth: and so the opt out rates, and once they’ve opted out they are opted out. And so it’s very difficult to go retarget them.
• 1067
  03:02:29.110 –> 03:02:54.110
  James Roth: And 99% of people were opting out with the 2 button. Because I think most folks on this don’t answer their cell phones often, and if you do, it’s usually like Oh, crap! Why’d I answer this? But you’re not going to be mean to the person who’s calling because we all started in sales. You’ve got respect for it. If it’s an AI. Sdr. And I can just press 2 to end the call. I’m pressing 2, 100 out of 100 times. So we were a B testing that. And so before we said, Hey, do we really need 550 Sdrs
• 1068
  03:02:54.330 –> 03:03:00.800
  James Roth: like this is amazing Aisdr, we can take 550 Sdrs. And you know, rehash that capacity elsewhere.
• 1069
  03:03:00.810 –> 03:03:27.109
  James Roth: But I think, testing those things out in terms of like, what is noise? What’s real? Manisha? You brought up one of the elephants in the room on this I think a lot of folks have big agreements with that firm. We do. And you know we’ve piloted agent force. There are certain things it does really. Well, there are certain things that we probably wouldn’t put it into place yet, you know, and so, I think, having sat in the room with all of the biggest names that have built out the biggest, splashiest, you know AI agents.
• 1070
  03:03:27.180 –> 03:03:42.780
  James Roth: you know, I think, understanding what’s real understanding where you’re at, and frankly understanding the conversion rates, understanding the good fit show rate, like those particular metrics in an A B test that you’re not going to completely rejigger your go to market machine because of some promise or because of some demo.
• 1071
  03:03:42.920 –> 03:04:10.009
  James Roth: I think that’s probably one of the most important things A Cro has to do is just say, okay, this is a gradual plan. And in the Smb space touching on that earlier, we are moving constantly sales capacity out of Smb, we started in. Micro. And now we’re moving further up the stack to be fully autonomous, plg, grow, renew, acquire all the above, do that in the platform, do that with an agent helping you alongside.
• 1072
  03:04:10.440 –> 03:04:35.299
  James Roth: But that thing has been board meeting after board meeting after board meeting, articulating the risk articulating like this is what it’s going to do to smb. You know, this is what it’s going to do to the asp like understanding those things, because it’s really easy to say. Sure, we’ll get out of the Smb. You know the renewal rates half of what it is an enterprise, and it’s a tough business, and post Ppp loans and post 2021 like we don’t really want to be there. You can’t. You can’t just do that.
• 1073
  03:04:35.430 –> 03:04:51.610
  James Roth: you know. And so I think, testing a B testing understanding what metrics you’re looking for. To say this is something we want to gradually get to. This is something we want to quickly get to. Or this new thing is actually delivering on the promise that it said it was going to. So we’re going to go all in. I think it’s a super important thing.
• 1074
  03:04:52.730 –> 03:04:53.300
  Warren Zenna: Great.
• 1075
  03:04:53.980 –> 03:04:55.860
  Warren Zenna: Hey, Matt? Yeah, what’s up?
• 1076
  03:04:56.450 –> 03:05:18.280
  Matt Darrow: I was going to add to the James Ab. Testing. Yes, and I think that there’s something you can do based on the level of consequence of the test, too, so I’ll give a story and shout out to another, salesforce venture. CEO Craig, overqualified of the Aisdr Piper mostly for inbound, but one of the things that they were discussing a recent summit was.
• 1077
  03:05:18.280 –> 03:05:23.620
  Matt Darrow: well, hey? A really interesting place to start was the off hours. So
• 1078
  03:05:23.620 –> 03:05:48.559
  Matt Darrow: when your Sdrs go home with the time zone. Right? There’s this sort of like low consequence time period that you could run this A B test where you’re not doing anything anyway. So so now to James’s point, yes, you want to be a B testing these different things. And then I think how aggressive you are on what you test is going to be. Well, what level of consequences it’s going to have like. Do you want AI autonomous robot to show up with your top 50 customer accounts?
• 1079
  03:05:48.560 –> 03:06:12.469
  Matt Darrow: Probably not. But there’s certain things that are happening either. Internal workflows, internal assets. If you’re engaging directly with live customers like what batch of customers are those. Would you be servicing them in any regard? I think you can look at that, and then come up with a really good plan, and I’ll end with some of the other guys. Have the hands up, Manisha. I liked your point, too, on how they get started. What we found with other cros is that there’s so many options.
• 1080
  03:06:12.510 –> 03:06:33.859
  Matt Darrow: But nobody wants to keep writing 20 to 50 K Poc. Checks to every single vendor because a lot of times. They’re they’re underwhelmed and not really. They just don’t have the budget to do that. So they need to have a different way to get started with tooling, because experimentation, ab testing and the consequence profile is really really important, and they got to do that. And the vendors have to make them easy for that. Do that, too, if you’re going to take them to the New World.
• 1081
  03:06:34.450 –> 03:06:35.040
  Warren Zenna: Hmm.
• 1082
  03:06:35.690 –> 03:06:36.280
  Manisha Raisinghani: Yeah, for sure.
• 1083
  03:06:36.280 –> 03:06:37.560
  Manisha Raisinghani: I think it’s important.
• 1084
  03:06:37.560 –> 03:06:38.180
  Warren Zenna: Correct. Go ahead.
• 1085
  03:06:38.180 –> 03:07:00.450
  Manisha Raisinghani: For AI native companies. I think to your point, Matt. I think it’s really important that AI integrates natively in the workflows, and it’s not again a new window, a chat kind of a window, where they are going and talking to an agent. So I think what becomes important to make it easy for Ab. Testing is AI integrating natively in the workflows.
• 1086
  03:07:03.420 –> 03:07:06.359
  Warren Zenna: Thank you, Rasheed. You had a question, a thought.
• 1087
  03:07:06.360 –> 03:07:11.629
  Rachit Kataria: Yeah. Just add on to James that you you got my mind racing on the comment on consequence.
• 1088
  03:07:12.220 –> 03:07:13.750
  Rachit Kataria: I’m sure
• 1089
  03:07:14.170 –> 03:07:20.729
  Rachit Kataria: you intentionally said you’re starting with Smb, right, there’s like a certain you know. What consequence and trade off are you.
• 1090
  03:07:20.730 –> 03:07:23.229
  Warren Zenna: They make. They make good guinea pigs. I suppose you know.
• 1091
  03:07:23.230 –> 03:07:41.620
  Rachit Kataria: For better or worse. I mean, you know, we all love our Smb customers. But I think the the interesting piece here is like, for example, you know, we sell enterprise, we automate relationship mapping and operationalize multi-threading for our customers. That’s the core value prop, and that’s a very enterprise motion. All of our customers sell up market. And to your question, Warren, it’s like.
• 1092
  03:07:42.060 –> 03:07:45.179
  Rachit Kataria: Can you go, agentic, and fully trust something to go
• 1093
  03:07:45.370 –> 03:07:50.130
  Rachit Kataria: on the fly? And if so, which segment of your customers are you okay with that?
• 1094
  03:07:50.230 –> 03:08:06.799
  Rachit Kataria: And I think in we’re okay with your point on the guinea pigs. And seeing if that’s something that can scale. Because, frankly, the alternative of selling enterprise is a very relationship, human heavy sale. You cannot automate that in some ways you don’t want an Asdr to blast your limited tam and the at bats you have up there
• 1095
  03:08:06.960 –> 03:08:13.470
  Rachit Kataria: ruin even that one chance you have with that Vp of sales sees a terrible email and says, guys like, we’re never buying from this company ever again. And so.
• 1096
  03:08:13.470 –> 03:08:14.120
  Warren Zenna: Okay.
• 1097
  03:08:14.120 –> 03:08:30.100
  Rachit Kataria: I think I’ll add, like this qualifier to your question, which is really interesting of yes, you can go, agentic, but you have to have a very honest conversation of do you trust the workflow you’re trying to replace? And is your end customer, if it’s customer facing. Okay with that, if if there’s margin of error.
• 1098
  03:08:30.647 –> 03:08:35.729
  Rachit Kataria: I’m sure. James. Well, that’s why Smb is the starting point there, too. But just as a perspective
• 1099
  03:08:35.870 –> 03:08:37.420
  Rachit Kataria: customer selling enterprise.
• 1100
  03:08:37.600 –> 03:08:45.560
  Warren Zenna: Yeah, that’s a good point. I I see this is almost like the point at which, when outbound went from email to cell phones.
• 1101
  03:08:45.810 –> 03:09:15.639
  Warren Zenna: You know, there was a lot of reticence around. Am I gonna call people’s mobile devices or not, you know. And there was all this sort of chatter around. Who’s gonna be the 1st person to do that now it’s commonplace, right? I mean, I think that if we see people start running out of the gate all of a sudden. This permission? Oh, he’s doing it! I’m doing it, you know. And all of a sudden your phone’s ringing all the time, and and I do think there’s gonna be some outliers that do it enough, and they’re willing to be the 1st movers right through the door. The 1st in the door, so to speak. But similarly, nobody wants to be the 1st or last person to buy anything. So
• 1102
  03:09:15.750 –> 03:09:35.110
  Warren Zenna: I think there’s gonna be an interesting opportunity to see. And I agree. I think we’re going through the same points here that the smaller businesses are where the experimentation is going to take place, and where more risk is gonna be allowable to to extend out into like, I think, the larger the larger organizations. So I think, like, this is the part where I’d like to talk a bit more about.
• 1103
  03:09:35.730 –> 03:09:47.589
  Warren Zenna: So there’s such a noise out there, right? I mean, I I see amazing platforms being presented in the marketplace. I have a lot of, I imagine the amount of phone calls just like everybody I’m getting from people of New AI platform to do XY or Z.
• 1104
  03:09:47.800 –> 03:09:56.200
  Warren Zenna: And I also see now every single one of the software platforms that I’ve been using for the last 10 years. Now, all of a sudden has that little star next to it, right? That little
• 1105
  03:09:56.430 –> 03:10:15.060
  Warren Zenna: quinkly star that indicates they’ve like peppered some AI into it to make it seem like. It’s magical all of a sudden. I don’t know what that means, you know, it’s like, okay, so it’s a cute little star. But show me what the AI is, I think we we all need to be a bit more educated on the kind of questions we need to ask to find out when you’re usually artificial intelligence in the systems.
• 1106
  03:10:15.290 –> 03:10:19.089
  Warren Zenna: How much of it is, AI included
• 1107
  03:10:19.470 –> 03:10:30.389
  Warren Zenna: to make it seem more palatable for the marketplace today, because everybody else is doing it a bit performatively. And then there’s also, if I were to remove the artificial intelligence from your system, would it
• 1108
  03:10:30.620 –> 03:10:56.769
  Warren Zenna: devalue? It’s it’s its viability to me. And how do we know that? Right? And I do think there is some kicking of the tires we need to do, because I’m seeing a lot of examples of where the AI components of software that I’m using aren’t really that useful. I think they may seem more like they’re trying to tether some pieces of their software together to make it seem like the frog DNA that they use in Jurassic Park to close the gaps on the DNA. They couldn’t find the dinosaurs, you know. I think there’s some of that.
• 1109
  03:10:56.800 –> 03:11:03.230
  Warren Zenna: So I I think, like we sort of like would be helpful to get a sense of like, how do you evaluate as the Cro? Look at the world
• 1110
  03:11:03.270 –> 03:11:11.829
  Warren Zenna: and determine what AI is the right stuff to evaluate? How do they know what to test, in the 1st place, because it’s it’s not an easy diagnostic to me.
• 1111
  03:11:12.860 –> 03:11:13.900
  Warren Zenna: James. Go ahead.
• 1112
  03:11:15.010 –> 03:11:16.879
  James Roth: Ashley. I think you were. You were first.st
• 1113
  03:11:16.880 –> 03:11:18.340
  James Roth: Yeah.
• 1114
  03:11:18.610 –> 03:11:39.190
  Ashley Wilson: Yeah, no, I I was gonna weigh in on this. I think that the it it kind of goes back to the earlier part of the conversation around the analysis of where the maybe the waste is or the used cases. Because I think if you start from that sort of 1st principle. Then you can go. Do evaluations of AI products to go solve that
• 1115
  03:11:39.190 –> 03:11:57.519
  Ashley Wilson: versus general purpose. AI transformation. What does that even mean? Where would you even start from, and I think about things like you know, when AI got embedded into notion, I know that it’s available, but I still go to Chatgpt or Claude to rewrite things, even though it’s in notion it’s just like
• 1116
  03:11:57.560 –> 03:12:27.080
  Ashley Wilson: and cause I just trust in a sense that like, okay, I’m just gonna go to like. I’m gonna pick my model. I know that it’s like for this case. I’m gonna go there, have my Gpts already trained. And then I copy paste a notion that might be a waste of time. But ultimately you’re gonna do the thing that solves for the best. And I think that if we think about how a Cro would want to make evaluations in 2025. If you go to, I want to solve for helping my reps with account planning.
• 1117
  03:12:27.080 –> 03:12:45.199
  Ashley Wilson: or I want to solve for Crm hygiene like, Start there do the vendor search. And I think we have to go into the question of going back to like, how do you intelligently transition to all these agentic? AI. You gotta make some bets like you got to get in with some of these vendors and
• 1118
  03:12:45.640 –> 03:12:53.799
  Ashley Wilson: work alongside them. Because AI is all about the prompting. It’s all about learning about your organization, and so if you always write things off.
• 1119
  03:12:53.800 –> 03:13:16.510
  Ashley Wilson: then you might never adopt things, and and going to our point of like for a walk, run like you might be too late if you say, Oh, none of them worked. None of them worked, none of them worked, and I think all of us have been building in this space for the last couple of years. The rate at which we can improve our product is just dramatic, and the rate at which that product changes because of feedback from our customers.
• 1120
  03:13:16.510 –> 03:13:22.010
  Ashley Wilson: because we’re working closely with our customers means that on the other side, doing the evaluation.
• 1121
  03:13:22.540 –> 03:13:24.680
  Ashley Wilson: you got a comment. Actually, just
• 1122
  03:13:24.990 –> 03:13:28.509
  Ashley Wilson: pick some tools and get them integrated. And I think, too.
• 1123
  03:13:28.680 –> 03:13:40.250
  Ashley Wilson: maybe something that you wrote off a year ago you should come back and revisit, because one year in this world is so dramatic in terms of the change, and you might be so pleasantly surprised at how
• 1124
  03:13:40.610 –> 03:13:52.509
  Ashley Wilson: the combination of the the models. And you know the companies that we’re all building on top of it have improved to where actually can solve your problem now. And that’s only gonna continue as we go on year by year.
• 1125
  03:13:54.550 –> 03:13:55.990
  Warren Zenna: Okay, got some heads up.
• 1126
  03:13:56.150 –> 03:14:01.108
  James Roth: Yeah, so I’ll I’ll preface this. I have a little star on our logo, so I might.
• 1127
  03:14:01.910 –> 03:14:04.129
  Warren Zenna: It’s a it’s a pretty star, too, James. Really nice.
• 1128
  03:14:04.130 –> 03:14:05.610
  James Roth: You know, I think
• 1129
  03:14:06.210 –> 03:14:32.839
  James Roth: you know, going into the thunderdome that is Linkedin, I do think undefensively the vilification of companies that have added AI to their products. I think you went through a period. If you listen to public company earnings calls where it’s like, how many times can somebody say AI, and so there was like some noise there. But I think again, having a pretty large and robust tech stack. I think there are examples
• 1130
  03:14:32.970 –> 03:14:37.539
  James Roth: where AI can take what is a great core competency and make it better.
• 1131
  03:14:37.640 –> 03:15:06.280
  James Roth: And so I don’t think it’s necessarily vilifying the fact that all of these companies are now saying AI, because they’re trying to get some market lift. I think the market lift is over, especially as a public company. The market lift is definitely over from just saying AI. But I do see, you know, some of these companies that probably everybody has used. There’s a massive opportunity to make them better. And so, like, I use ours as an example, like 48% of our customer base
• 1132
  03:15:06.280 –> 03:15:23.770
  James Roth: for a period of time was still just using us for contact lookups. It’s great to be a known household brand that everybody knows has great contacts. It’s really frustrating on the other end, talking to the likes of you guys or cros say, no. I just bought this company for technographics. I just bought this company for intent, and it’s like, Oh, did ours miss the mark. They’re like we didn’t know you had it.
• 1133
  03:15:23.870 –> 03:15:47.709
  James Roth: And so the ability to take AI and basically serve up more of a proactive use case than it is, I think, for many years, and seeing some of the folks on the earlier panels for many years, we hired these armies of Csms for these products, and you can name any go-to-market tech stack product. And you hire a couple 100 Csms. And please go teach someone how to use this thing to its full capacity.
• 1134
  03:15:47.710 –> 03:16:13.500
  James Roth: and I think one of the things that AI does nicely is it takes like the really meaningful moments, irrespective of what the product is, and it ties them together and serves them up more proactively across different systems. And so I wouldn’t necessarily vilify that. But I think on the what does a Cro do where you’ve got existing incumbent vendors that are throwing AI at you. Then you’ve got like cool mit guy startups coming at you. I think I forget who said it. But
• 1135
  03:16:13.650 –> 03:16:33.160
  James Roth: ultimately it does come down to like what is the biggest problem. And what are we trying to solve and like? Is this nice to have? Or is this something that is ingrained that the people like? And this just makes it better? And I think you know, to Rashid’s Point, across where I see the biggest value in AI is for the 1st time ever
• 1136
  03:16:33.290 –> 03:16:38.540
  James Roth: you have the ability to consume massive amounts of data and get it right.
• 1137
  03:16:38.550 –> 03:16:55.419
  James Roth: And so, you know, on the relationship map side and rasheed, we need to have a conversation after this like that’s been one of the hardest things. When I think about waste, my slack is filled with like, Hey, you know this guy, hey? You’re connected on Linkedin, you know, this guy I’ve got like 20,000 connections. I probably know 1,000 of them.
• 1138
  03:16:55.420 –> 03:17:07.620
  James Roth: And so I’ve got to go through and look. And when you think about data points like Alma mater growing up high school all of the things that might be publicly available, and then say they work together at the same organization for this long. And you know
• 1139
  03:17:07.620 –> 03:17:25.520
  James Roth: you can get pretty tight then not mention all the 1st party data around emails and calendar invites and things like that that used to be this massive undertaking that my poor Ea had to go through thousands of calendar meetings to say I actually met with Warren before, or you go to Linkedin and say, Oh, yeah, I actually worked with this guy for a year, even though I never knew him.
• 1140
  03:17:25.520 –> 03:17:42.159
  James Roth: The amount of data that it takes to get that to a pretty good place was damn near impossible 5 years ago. Now you can consume all that data and make heads or tails of it. Same thing with podcast information. Everybody’s probably done a thousand podcasts on this call, the likes that some sales guy is going to listen to it.
• 1141
  03:17:42.290 –> 03:18:10.799
  James Roth: 45 min. It’s impossible. But now you can summarize all of those things. And so you amalgamate huge amounts of data to take out an underlying nugget of a point of view, or some reason to go after them, like, regardless of if they’re new, cool tech AI, or if their legacy old company that’s gotten into AI as long as the use case is bringing value to something that you are trying desperately to solve in Cro Land it’s a win, regardless of whose company it is my point of view.
• 1142
  03:18:13.490 –> 03:18:15.509
  Warren Zenna: I’ve got some hands up. Who who wants to jump in.
• 1143
  03:18:15.740 –> 03:18:29.690
  Manisha Raisinghani: So I’ll go next, I think. You know 1 1 point I differ. Here is, instead of you know, looking for what is, what waste is there in the company, and then find solutions for that?
• 1144
  03:18:29.870 –> 03:18:42.489
  Manisha Raisinghani: It’s also good to go the other way around, because there are so many things in the company which are, you know, which could be adding to inefficiencies, and you might not even imagine that it can be solved by AI today.
• 1145
  03:18:42.570 –> 03:19:01.519
  Manisha Raisinghani: because not a lot of you know, either Cros or even you know, other sea level people. They know what is possible with AI and what is not possible with AI. So actually, you know, instead of just finding waste and then going to find tools around that waste, it’s also
• 1146
  03:19:01.807 –> 03:19:26.520
  Manisha Raisinghani: good to have an open mind and see what you know what other tools are available in the market, because you might not know that this problem can actually be solved by AI. And when it comes to AI native companies, I think, Warren, you put it in a very good way, is, if you take the AI features out of your product. Does the product still work? I think that’s a huge difference. I’m sure. You know, companies here, like few of us who start
• 1147
  03:19:26.520 –> 03:19:53.599
  Manisha Raisinghani: after chat gpt was launched their product will not work like I’ll be very honest if we take AI out of sift hub, sift. Her platform might not work right, but the products which were born before Chat Gpt was launched. Those products will still work. So that is the difference between, I think. AI native pre chat, Gpt and post chat gpt companies. There are 3 superpowers which I think any AI platform needs
• 1148
  03:19:53.650 –> 03:20:18.339
  Manisha Raisinghani: to perform. The best is, when is knows what you know. So actually, we’re giving an example of notion right now, you’re not using notions. AI, because Chat Gpt has learned a lot from what you know, right? So what you know it continue. It evolves continuously, and it remembers what you have been talking about.
• 1149
  03:20:18.340 –> 03:20:25.180
  Manisha Raisinghani: Now, these 3 components, not just in chat Gpt, but also in b 2 b setup are really important.
• 1150
  03:20:25.350 –> 03:20:49.800
  Manisha Raisinghani: I mean, some data is in salesforce. We spoke about that. Matt was like, you know, why do we need sales, enablement tools, which is true? So the knowledge is spread across so many sources. Now, as a salesperson, I know knowledge which resides in 10 sources. So an AI agent needs to know that knowledge which resides in 10 sources to make my job easier.
• 1151
  03:20:50.470 –> 03:20:57.880
  Manisha Raisinghani: Otherwise it is just taking siloed information and making decisions on basis of only one knowledge source.
• 1152
  03:20:58.000 –> 03:21:15.590
  Manisha Raisinghani: which is, you know, which was something which was done pre AI pre chat gpt era as well. So I think 3 things which Cros should look at, especially for in b 2 b domain is AI agents should know what you know. It learns as it goes, and it never forgets.
• 1153
  03:21:18.080 –> 03:21:20.580
  Warren Zenna: Good. I can see your sheet, and Josh have a heads up.
• 1154
  03:21:20.790 –> 03:21:33.060
  Rachit Kataria: Yeah, I’ll go fast. I know we’re close on time. So I’ll be brief. One, Jake, let’s definitely chat. There’s a reason we started with the relationships. And AI for multi-threading relationship mapping. And it’s this point I want to make. If we zoom out.
• 1155
  03:21:33.680 –> 03:22:02.079
  Rachit Kataria: This is a conversation about cros, not vps of sales. There is a core difference here. It cros, care about all things from sales success marketing both front of the house and the house. A lot of folks just confuse that, for pure revenue is just the net new. But I think to your point, Warren, way back. When you asked why or how you should evaluate tools. It should be tools that actually apply across your revenue org. It should be tools that are not a point solution for just sales. It should be something that everyone across sales success.
• 1156
  03:22:02.080 –> 03:22:02.550
  Warren Zenna: Thank you.
• 1157
  03:22:03.070 –> 03:22:12.790
  Rachit Kataria: Gtm. Gets value out of. And I think the problem is why they’re so burned is there are 60 point solutions out there that do something across the board. But maybe, James, to your point, like
• 1158
  03:22:12.900 –> 03:22:25.969
  Rachit Kataria: they should wake up and realize that there’s actually a lot of tools that can do these things all together, and they just don’t realize it. But if they do, it’s just much more powerful in the same place, because the hardest problem is getting one provider to have all the data to, then do all the magic on top of it.
• 1159
  03:22:26.140 –> 03:22:44.040
  Rachit Kataria: If you don’t have that, yes, you’ll be in point solution. Hell for the rest of your life. But as you start finding, I think, the winners in this market and the zeros that should look for that are ones where you can actually understand that you have all the data. You’re applying this at a scale that not just your Aes, but your Sdrs, your Ams. Your Csms get value out of.
• 1160
  03:22:44.230 –> 03:22:55.939
  Rachit Kataria: And then we’re talking about a tool that’s actually useful across. Go to market. Not just, you know, a rollout for one portion of my team, so I’ll be brief on that. But I want to emphasize like we’re talking about. 0 is not not a specific question.
• 1161
  03:22:55.940 –> 03:22:59.830
  Warren Zenna: Great. I I agree it has to be that has to be, and it should be
• 1162
  03:23:00.050 –> 03:23:04.970
  Warren Zenna: cross functional solutions optimally. Josh, we gotta get a point.
• 1163
  03:23:05.680 –> 03:23:27.369
  Josh Solomon: Yeah, for sure. I think in my mind I find often this conversation sort of centers around, what are the use cases for AI, and I think there’s a natural tendency for that, because a lot of people are under pressure to adopt AI, either they’re looking on Linkedin, and they feel like they’re behind their boards, putting pressure on them, their bosses putting pressure on them. You have to start from a 1st principle. Of what problem am I trying to solve.
• 1164
  03:23:27.400 –> 03:23:53.259
  Josh Solomon: There’s just too much AI for the sake of AI out there today, and I think if you get clear and I totally agree with Richie. If, like, we’re able to look across the customer experience and define what we want to actually solve. For then we can start to actually score out those use cases right? And I think this is where actually made a comment. That’s about, you know, being curious, right? You need to have a little bit of technical understanding here to understand what’s possible today.
• 1165
  03:23:53.260 –> 03:24:17.370
  Josh Solomon: How costly is this actually going to be to do? How risky is it for me to take these on. And I think if you start to build out these use cases and score them across these, vector, these vectors, you can build a pretty clear roadmap. And I I just consider this to be the medium term roadmap. You’re not looking 3 years in the future, and you’re not looking one month in the future right? How do I establish a medium term roadmap? And then you can start to look for tools or sets of tools that will allow you to do. That.
• 1166
  03:24:17.760 –> 03:24:37.969
  Josh Solomon: One thing, I think, is very unique about the world of AI and companies that are building a native platforms is they’re much more broad. They’re more horizontal applications. They’re way more flexible, and they will be able to satisfy more use cases than what you’re used to buying in the past. And so you have this opportunity to get more out of your vendors and satisfy more. Use cases inside of 1. 1 partner.
• 1167
  03:24:40.410 –> 03:24:51.559
  Warren Zenna: Great. This has been great, so I know we’re kind of getting close to the end here. I just wanted to kind of close to a couple of things that we didn’t mention, and it’s an important one. And another thing that Cros should be doing on a regular basis is talking to other Cros
• 1168
  03:24:52.540 –> 03:25:22.160
  Warren Zenna: because Cros are experimenting with this stuff, you know. And they’re already making the mistakes and making learnings. And you know, when I put together the Cro groups that I put together the conversations are amazing around. Tell me what you tried. Tell me what it didn’t work, and to be to be, you know, respectful to the the vendors and stuff. You know. They’re not talking to somebody who’s trying to sell them something. They’re talking to other people who are having the same problems that they are, and they’re using them. And and those are really valid people who, I’m saying, wow, I got the same problem. I did. You use this tool? It worked. And so
• 1169
  03:25:22.160 –> 03:25:32.330
  Warren Zenna: other Cros should be doing whatever they can to talk to other ones and just find out what what they’re doing. Whatnot and learn from each other. So we got like, what? Like 3 min here. So maybe just a
• 1170
  03:25:32.710 –> 03:25:37.940
  Warren Zenna: yes or no, this is probably interesting. Question, are Sdrs gonna become robots or not?
• 1171
  03:25:42.160 –> 03:25:43.000
  Josh Solomon: I’ll say no.
• 1172
  03:25:43.560 –> 03:25:44.560
  Ashley Wilson: I was gonna say no.
• 1173
  03:25:45.130 –> 03:25:46.040
  Warren Zenna: Okay.
• 1174
  03:25:46.310 –> 03:25:50.230
  James Roth: Smaller teams, more efficient teams, but not not extinct.
• 1175
  03:25:50.950 –> 03:25:51.600
  Warren Zenna: Okay.
• 1176
  03:25:52.020 –> 03:25:57.060
  Ashley Wilson: They might have, like 90% of their job done for them, but I think they will still orchestrate.
• 1177
  03:25:57.650 –> 03:26:06.759
  Josh Solomon: I see a world where you pay pay Sdrs way more than you do today. They’re way more valuable. They have a better role inside of the business, and a lot of the grunt work that they’re doing today totally changes.
• 1178
  03:26:08.370 –> 03:26:18.259
  Manisha Raisinghani: I think Sdrs who use AI. Who you know who are, who AI can empower them, and they can bring in more pipeline.
• 1179
  03:26:19.970 –> 03:26:23.580
  Warren Zenna: Okay. So there’ll be like, almost like a Cybert.
• 1180
  03:26:24.500 –> 03:26:36.910
  Ashley Wilson: I think we’re all gonna be like that. I think we’re all gonna be orchestrating our AI to do the work. But you still need, like the human hope. Well, for a while, I mean, maybe eventually that will be replaced. But.
• 1181
  03:26:36.910 –> 03:26:53.309
  Matt Darrow: I don’t buy it, guys. I mean, the whole premise of AI is, it’s labor, disruption. And the more expertise and the more culturally comfortable. We get all of these roles that were invented because of skill specialization. That’s what AI is all about. It’s just gonna go away.
• 1182
  03:26:53.730 –> 03:26:54.510
  Josh Solomon: Alright. I think
• 1183
  03:26:54.510 –> 03:27:01.619
  Josh Solomon: fundamentally there’s a problem with that, though, that that I mean, if every one of us on the call has an AI, Sdr, that’s you know, so great.
• 1184
  03:27:01.810 –> 03:27:20.180
  Josh Solomon: How will anyone land in an inbox right? Like it creates actually a totally reverse problem. Right? So I actually am not so convinced that once everybody has this magical tool that you know, pipeline just busts open, I actually think that it creates a reverse feed inside of what’s it like to manage your inbox? And you know what are the inbox providers? Do.
• 1185
  03:27:20.420 –> 03:27:23.429
  Matt Darrow: We could go longer on it. But I would contend that that’s just the same
• 1186
  03:27:23.430 –> 03:27:27.930
  Matt Darrow: workflow in that future. You’re not going to run that same workflow.
• 1187
  03:27:29.220 –> 03:27:37.429
  Warren Zenna: It’s great. Well, look, thank you. This is awesome as as expected. Thanks everyone for all your contributions. And Julia, thank you so much for putting this together.
• 1188
  03:27:37.710 –> 03:27:40.910
  Julia Nimchinski: Such a pleasure. Thank you so much.
• 1189
  03:27:40.910 –> 03:27:41.230
  Rachit Kataria: Evidence.
• 1190
  03:27:41.230 –> 03:27:43.130
  Julia Nimchinski: And Warren. Thank you.
• 1191
  03:27:43.130 –> 03:27:44.230
  Ashley Wilson: Thank you.
• 1192
  03:27:44.600 –> 03:27:45.060
  Warren Zenna: Thank you.

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