Neil Tewari: Marketing Can't Be the Company's AI Bottleneck

Speaker A: I'm Sarah Fatz and I lead community and awareness of Progress. This is 10 Minute MarTech.

Speaker B: Right now there seems to be this slight inversion towards like spending a lot on tokens and stay away from variable based pricing and marketing. I do think that there's going to be a change in the adoption curve there. We saw the engineering, we saw it in sales. I think that there's going to be a big change in the mindset of uh, CMOs and VPs of marketing. I actually think that token spend will outpace advertising and marketing spend over the next five years.

Speaker A: That's Neel Teowari, co founder and CEO at Conversion. Let's get started. So Neil, every day you and your team are actually helping modern organizations move from manually managing campaigns to building modern intelligent systems. So you really have this front row seat to the transformation that's happening in the Martech space. When you look across those journeys, what separates those who are succeeding from those who are struggling and what is surprising them along the way?

Speaker B: Yeah, uh, it is really cool to have that front row seat like you're mentioning where we can actually see what are the fastest growing teams in marketing doing. What are some teams that are maybe lagging behind doing? How is that affecting these companies? And I think it's really interesting when you're like a AI marketing automation company, I think some folks assume that you're just like mass producing like LinkedIn swap or something like that on behalf of businesses, et cetera. I think that the, the teams that are doing things really well understand that the hardest part in marketing specifically is giving agents access to context, is giving agents access to the ability to know actually what's going on, to actually produce the correct things. It's not just sitting down and just like ripping emails and subject lines based on like what it knows about things. They have the plumbing and infrastructure set up correctly and it's. We can take an example is like Sarah. If we're trying to. Let's just use email. Email. You know, um, it'd be really easy for me to just throw a prompt and claude and have it email you for example.

Speaker A: Right.

Speaker B: It's much more complex for me to set up a system that knows all the signals about Sarah, that knows everything, that hey, uh, someone from our team actually spoke with Sarah. That GONG is passing through and actually influencing the decision. The GONG transcript is, is influencing the decision. Um, everything we know about Sarah, the company, the company size, the company prerogatives, all feed in to actually kind of get that first draft, that first version out we noticed that some of the teams that are doing this really well have invested a lot in getting the plumbing and the infrastructure correct. And they still, even with that, have a human QA things, but they're still outputting 5, 10x faster. And some of the slower teams are actually those that are frustrated with, hey, Claude, just didn't one shot this correctly for us. Um, and, and that's what we're seeing some of the best teams doing.

Speaker A: Yeah, yeah, that's great. And are there things that people are, when they come to you and start working with you, they have either preconceived notions that are incorrect or something that surprises them along the way as they're, they're modernizing their, their campaign management systems.

Speaker B: I think they're surprised with the capability set that's possible to achieve both in helping them speed things up and in actually like how much better, um, you can market to folks if you get that infrastructure correct. I think, uh, the correct folks are coming in saying, hey, I can probably do this and I could probably help out with email. Um, and we're seeing some phenomenal. Teams are actually having every single AD that's surfaced to every single person has an agentic component. It doesn't mean that it's necessarily making the creative. It's actually choosing among a large template of folks to actually go in and do things, or it's actually even creating landing pages. And maybe there's still a human in the loop that are QA things. But the entire process, end to end, full funnel, can be touched by agents. And like I said, it's not always creating every single creative, every single bit of asset. But I think people are really surprised with how far along agents have come. I think they are surprised because when they type in something to be done in cloud, it doesn't do it all per into perfection. But with that combine that with the context required, I think people are really surprised with the end results that are possible. We try and use our own product, uh, a lot to be able to show those results to folks. And I think once people are involved, uh, I think they get really excited by it.

Speaker A: Yeah, yeah, that's great. We've been doing these roadshow events, the progress Martech next roadshow. And one of the things Scott Brinker talks about all the time is contact. He said, you know, if there's one word for uh, 2026, it's context. Whether it's context engineering or some of the other things that you said. If somebody is listening to this, who's saying, okay, yeah, Makes sense. Infrastructure, plumbing, all sounds good. Where do I start? What would you tell them?

Speaker B: Yeah, of course, of course I have a strong bias to setting uh, that foundation right with conversion. And this is a big part of what we do as a product is how can we enable things to get deep and actually understand the context at a robust scale. I think that this is a very interesting time where uh, I think CMOs and VPs of marketing, uh, it's almost a requirement now to be very in the weeds of how your actual tech stack operates end to end. I think for a long time it wasn't actually a big part of the job. I think everybody just chose Salesforce, everybody chose Marketo, everyone chose 6Sense and they all kind of got to work and there was members of the team that go down and use those tools to the fullest extent and there wasn't like that m much else to be kind of thought about when it came to actually executing. Now it's like when I say plumbing and I say infrastructure, it means actually really robustly understanding. Okay, like why do we not have this context inside our market and says, oh, it's on a Salesforce custom object and that's related to these objects this way. That's not stuff I believe that CMOs or EBIs are marketing and very fairly were using their time on before, but now actually can be the difference between marketing well and marketing poorly compared to your competitors. I think there's two things really. It's like you really got into the weeds of that uh, infrastructure and the plumbing to understand where are the faults, where are the gaps. And then second is, I think there also now needs to be a questioning of some of these legacy tooling is like should we even be using these things that have been the standard for so long?

Speaker A: I had been talking for a while about data not being clean, but I think you actually have gotten even more uh, precise. It's not necessarily even that data is not clean. It's that you have to have a high level understanding or maybe a deep understanding of what you're working with to begin with.

Speaker B: That's right, that's right, exactly. And I think if we can agree that this is, can transform the end result for a marketing company, you could make the argument this is now becoming one of the most crucial things to deeply understand as a marketing leader.

Speaker A: If you're in a legacy organization, an organization that's been around for a long time and has legacy systems that, you know, whether they would admit it publicly or not, might be Band Aid together on the Back end. When it comes to the Martech stack, what advice do you give them to think about how to modernize in a way that doesn't break the business?

Speaker B: It's a great question. Let's look at the other departments of a company. Right? Let's look at. I studied engineering. It was the first thing that was dramatically disrupted. Right. It's like, oh my God, is it like now 10 times? It is 10 to 100 times easier to engineer things that we previously had to do. And there was that aha moment and there was a sharp adoption curve from CTOs. And I think there was also like a little bit of pushback on folks that were a little bit slower to adopt. I think that we wanted to be, you see, engineers were eager to be, you know, jumping in and see how could this revamp the entire stack. And now we actually measure like how many tokens are we consuming as an engineering team as a metric of success, which is a little silly. It's like, basically, how much are we spending? Why are we not spending more? And I think that we started to see this curve in certain parts of like sales and rev ups or as well. It's where we see clay really coming in and, and uh, whether it's clay or any other enriching tools, like how can we get as much data and as much context on each person we're reaching out to, et cetera. There hasn't been the same level of scrutiny and adoption in marketing. And I think it's because the legacy systems are so ingrained, the data is so complex that of course, like, there's a little bit like of a higher, higher bar to hit before you can actually go ahead and rethink some of the structuring this old tooling. But I think that the next one, two, three years, the marketing leaders that are considered really ahead of their time will be the folks that said, how can we actually go ahead and safely start thinking about how we can break down this legacy solution? We don't want marketing to become the bottleneck of a whole company as everyone else starts to adopt A.I.

Speaker A: really? Well, yeah. You know, we've talked for years about composability and having composable systems, and that's really the way to go. So you can always have a modern approach to your Martech stack. But I think it's even more critical now. We're talking internally about AI your way. Every customer that we talk to is on a different journey. Right. And so making sure that the products that you're delivering are composable enough that they can use AI in the way that they want and they can replace a legacy system easily. It's just an interesting time. And I think that the composability aspect of Martech systems right now, I think if people built that way and they're not in these walled gardens, are probably going to have an easier time transforming. But I would love your thoughts on that.

Speaker B: I think it's a really great take. I think that data should be freely passing among systems as, like, a requirement for whatever it is that we use now, if we have data like that cannot get out of a system. Uh, let's just take like, Marketa's APIs are quite limited in how much data can come out of it. Uh, and whether that's because it's like old infrastructure or whether that's because Marketa wants to keep data silent in its own data just to kind of like increase its own moat for businesses. Either way, it's prohibitive. Um, and so it's like, if we want to be able to have access to data that lives in Marketo, in our cloud, mcp, in, uh, any other system that's determining which emails or ads or landing page we get, that's not possible to do. And so I think there's this very high technical bar for marketing products because they process such a high level of data to be as composable as possible. Data should be as free as possible among these systems in order to actually be able to achieve what we should be achieving as a marketing team, which is having free context, infinite context, to be able to market at a high level.

Speaker A: If you're talking to somebody in the Martech stack, right, who maybe is more leaning towards the marketing side and not necessarily as technical, what advice would you give them when it comes to thinking about token consumption and protecting that, that investment and budget?

Speaker B: You, you drew such a good analogy to like, the, the cloud economy as well. It's like, Pete, there was like kind of a learning curve to figure out how to do that correctly. Um, and I'm sure that even like cloud, uh, providers were like, took some time to like, really figure out exactly how their pricing should look as well. And I think I want to draw a similar analogy, which is eventually those businesses were able to get to a place where as you scaled, the bill scaled, but you felt confident it was scaling with you, you were using more resources, it was providing more value as you did. So, hey, now I can, instead of 100,000 users on my platform, I can hold 500,000. Um, and yes, the bill went up 5x represented but also so did the rest of the core functionality of my company. And right now there seems to be this slight adversion towards like spending a lot on tokens and stay away from variable based pricing and marketing. I do think that there's going to be a change in the adoption curve there. We saw the engineering, we saw it in sales. With engineering it's very clear and obvious. You can write X lines of code or it can accomplish like why projects. We just haven't gotten there with marketing yet. Um, primarily like the big focus of today's conversation is that infrastructure isn't there just yet. But once we can feel like, oh, we're actually marketing better, once you feel like we're getting to that place, I think that there's going to be a big change in the mindset of CMOs and VPs of marketing. I actually think that token spend will outpace advertising and marketing spend over the next five years.

Speaker A: Interesting. That's a good hot take. And I haven't even asked you for a hot take, but I like that one. Along those lines, um, curious what you think, um, if you had a crystal ball five years from now or even a year from now because everything's changing so quickly, what do you think a true AI forward or agentic marketing team looks like from a team structure perspective?

Speaker B: Yeah. With how things are shaping, I feel like uh, you're right. We try and only think one to two years ahead, um, um, instead of a half decade ahead as well. Um, and ah, I think like I, I kind of starred the ball here where like I do think that there's going to be um, as much scrutiny around how are we thinking about ad spend, how are we thinking about brand image? The way that we have teams fully focused on that. I do believe that half of the team is going to be thinking about how do we think about token spend, how do we think about training our agents all in the right context. We're starting to see a little bit, we're starting to see a lot more incorporation of complex signals and things like that. That is context and that is context that helps humans and that will therefore be context that helps agents as well. I think that's going to be the next big component. We're seeing this with AEO and geo. We're seeing like a bigger focus on not our tokens, other companies token spend to figure out like where, you know, where do we fit in the mix. And so I um, think there's going to be as much scrutiny on that component I think there's going to be an increased bar. Everyone in a marketing organization be required to get more technical, be expected to be tinkering around with more tooling and be thinking about how can something either make the, the team faster or the team actually market at a higher and higher level, um, and make faster decisions. Um, I actually am not one of those folks that believes that teams will dramatically shrink or a bunch of folks will let go. Uh, I don't think we've seen that in other orgs and if anything, I think we've seen a lot more folks trying to hire a lot more. Um, but I do believe that people's jobs will change a lot and it'll be focusing more on technicals, focusing more on context.

Speaker A: That's awesome. Well, Neil, I feel like I could talk to you for a lot longer, but I need to stay true to our 10 minute martech promise. So thank you so much for your time today. I truly appreciate it.

Speaker B: Thank you. Sarah, thanks so much for having me on.