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Marketing in Progress is a spinoff of Work in Progress that digs into what’s moving the needle in B2B. We feature marketing leaders, sales leaders, and agency owners sharing real stories, smart ideas, and no-filter perspectives—so you walk away with practical guidance to help you do your job better.
Tal Peretz (00:00):
You need to start building this culture of being what we call AI native. Start small and maybe do a couple of specific solution and even builds like your own agents on specific platforms that you care about specifically.
Gayle Kalvert (00:12):
Welcome to Marketing in Progress. I'm Gayle Kalvert. This show is for B2B marketing leaders who are under real pressure to deliver results without a clear roadmap. Each episode is built to give you practical insight you can use right away. We focus on what actually matters, how success is measured, and the decisions and trade-offs necessary for success. If you're trying to cut through the noise, do better work and build credibility inside your organization, you're in the right place. Let's get into it. Hey everyone. Welcome back to Marketing in Progress. I'm your host, Gayle Kalvert. Today I'm joined by Tal Peretz, co-founder and CEO of Onfire AI. With a background in advanced data and intelligence systems, Tal has built Onfire around a simple but powerful idea. Better data, not just more AI, is the key to effective go- to-market. He's leading a shift toward what he calls vertical AI, using deep contextual data to help companies find and engage the right buyers at exactly the right time.
(01:18):
His contrarian approach, building the data layer before the AI, has already helped customers drive over $50 million in closed deals. In this episode, we get into how to cut through the AI hype and actually apply it to drive pipeline, how to use better data and real buying signals to sharpen your go- to-market strategy. Tal, thank you for being here.
Tal Peretz (01:41):
Thank you so much, Gayle. Nice meeting you.
Gayle Kalvert (01:43):
No, it's so great to see you and to hear and learn more about what Onfire's doing because I can tell you for sure every single day when we talk to our clients in marketing, it's what do we do about this AI? And specifically, AI has made it too easy for every company to do outreach and to quote unquote personalize it. And that is making it harder to cut through. And why I'm super excited about you being here today is that you're targeting, you really help companies target technical buyers, which is super important and not something that we talk a lot about on this podcast. So let's just dive in Tall.
Tal Peretz (02:24):
In this era of AI, everyone globally had their ChatGPT moment and how to use AI and Strait started to do some personalization at scale and adding some AI, let's say, flavor to their outbound motion and marketing activities. And I think it's counterintuitive because right now it's basically made the work or the activities much harder and raised the noise bar a little bit higher than it was in the past. And this is what led us to build on Fire. And we started the company around the main audience for us, which are technical buyers, as you mentioned. Those CSOs, CTOs, CIOs, probably the toughest buyer out there. The ones that always prefer to build versus buy, and they have resistance to salespeople. But at the same time, they have probably the biggest public footprint. And when I say that they have, it's not just those C-level executive, it's also their entire team members.
(03:33):
From their nature being, they're inside those, what we call communities like Reddit, Discord, X, aka, Twitter, and basically talking with their peers about their problems and day to day. And it turns out that if you're looking into the data, it's going to be gold for marketeers and salespeople. And this is what we're trying to build here in on fire.
Gayle Kalvert (03:55):
Talk a little bit about the technical buyer. Like you said, they're notorious for being really hard to reach and even harder to convince. As you said, don't really love being sold to so much, right? Even though we know that selling is actually problem solving. Tell us what you're seeing that marketing teams are maybe getting wrong when it comes to targeting these technical buyers.
Tal Peretz (04:19):
Yeah, 100%. I think it all started when you start with the first point when you try to do the outreach or the outbound activities without any context. You don't have a clear reason to why you're reaching out, why you're reaching out to this specific prospect. It might be, and as we all know, those titles are misleading because it can be like the head of security, but maybe your specific budget line is under the IT director, for example. So it's really tricky. And we see a lot of companies today basically going without any context to those buyers and then lose their basically normal chance to bring in those buyers to the play because we're lacking off the timing aspect and the actual, you mentioned problem solving. So the actual problem that those prospects really have right now. And I think it all started with this option to use the context, which maybe in the past it used to be kind of like an optional.
(05:23):
So right now is a must have in this AI era because it become much harder to basically starting these activities and doing this marketing and album campaigns.
Gayle Kalvert (05:34):
Are you a marketing leader in B2B tech? Do you want to hear what your peers are actually doing? What's working, what they're ditching, and how they're navigating the pressure we're all under? Well, you're in luck. We just launched the Marketing in Progress community. It's a space for sharing ideas, learning from your peers and having fun along the way. Visit creocollective.io/marketinginprogress to learn more and join us. You say it's important to have context in the outreach. And so I think immediately, while we are putting context in, right? And I'm putting myself as the marketing lead, who's targeting CISOs and you're like, "Well, okay, I know what their pains are and we're putting together messaging about how we can solve their pain, but it's still not cutting through." Can you help us understand what you mean by building the data layer first? What is context when it's successful?
Tal Peretz (06:35):
The way we see context is not just about, so you can understand, let's say the generic pain points, is the ability to know each data point that you can dream of. So imagine that, for example, you're going into a specific company, you can understand which project they're having right now. What are the problems that they're having? Because as we all know, cybersecurity, this is a pretty wide space. Yeah. It can be from cloud security to endpoint to identity. First of all, understanding what is top of mind right now. Second of it is what are the competitive landscape look like? Maybe they're looking into specific solutions, what they have in place today, what are like renewable cycle looks like. And left but not least, who are the actual buying committee that are going to be involved on it? Who are the true champion, the influencer, and the buyers specifically for my own product and initiative?
(07:31):
And this is what the true context really means. And sometimes we see companies and it's not just like, just to be clear, it's not like startups that started right now doing marketing activities or outbound. We are talking with for the biggest enterprise in the space. They all lean in into what works five years ago and now they understand the game shifted completely. And if you don't have this context and you don't have this visibility and you don't understand what is actually happening, you're going to lose the deal to the one that actually understand what's happening inside the scene. So the importance of context become crucial in today's era.
Gayle Kalvert (08:14):
So what does this look like in practice? I'm picturing four paragraph or four page emails, right? What does this look like in real life?
Tal Peretz (08:24):
So I think going into the on fire experience the day of the rap and also going into what is like AI native solution. So imagine that you're looking into the account and you can ask any questions that you have in mind in what we call like free language and you can ask like, okay, what are the top activities that happen in the account right now? And then on fire basically going into the public web for all of those places and whatever they find, for example, post on Reddit that get posted and then understanding what is happening or specific thread on Slack, for example. And then taking this information and provide it to the rep with the full evidence. So you have trust in the data, you understand how you need to act on it, and you have the flexibility to how you can query it and use it because it's integrated inside your existing workflows to your CRM and of course marketing and sales engagement platform.
(09:26):
And you have the confidence that the data is actively hackerate because maybe this is a good point to double down on is one of the biggest challenges that we saw when we started the company is people use a lot of tools that help them find great data, but they had a lack of understanding how they can trust it and on which data point is actually been built on. And we took a different approach and built what we call like a data first approach, where the rep can see the true data points that's coming from the public web and gain confidence. So this is like how we see the day-to-day and what is being a true data first AI solution today actually works.
Gayle Kalvert (10:13):
Do you suggest then that the sales reps or anybody using that data is crafting their own messaging? I mean, how does this scale, like you said, if we're talking about a company, these huge companies, the first question that comes to mind for me is, well, how do we scale this?
Tal Peretz (10:29):
I think that's a great question and it's evolve in how the organization is maturing with AI and what is the quality bar that they're basically raising right now. And I can tell you few examples. There is companies that use it as what we call completely autonomous. They train the model to be talking just like their top account executive or top marketeers, building the messaging and then push it on autopilot from a data point into an engagement, sorry. And then the second part is those companies that kind of like starting building their AI native motion and they have more what we call like human in the loop kind of mechanism. So you see the data, you make sure that you understand that you maybe see the draft, you tweak it a little bit, and then you send it out. What we usually do with those companies, we are trying together build this like AI native nature and understand what good looks like and what are the quality bar and how we can reach it.
(11:35):
The same way we treat our like reps and we do some onboarding and training. In the AI era, we need to do the same for those AI agents. And this is like how we see it.
Gayle Kalvert (11:46):
You have to train the machine just like we train
Tal Peretz (11:49):
People.
Gayle Kalvert (11:50):
It's true. Yes. Well, if I flip this, your perspective a little bit and talk about as a CEO, when you do your own marketing for your company, are you doing this as well for yourself?
Tal Peretz (12:05):
That's a great question. So I think like today as a CEO, I think this is probably the best time to start a company or build a company, in my opinion. And just to give to the audience a little bit of information, today we have a pretty small team in Onfire that doing the marketing and the admin activities and now generating I think the same amount of pipeline as if there was a team of like 5X on the same amount of headcount. And the only reason it's possible is because we build this data first approach and then we ingest it inside of that the AI agents that help us understand what to do next and which account to go after right now and basically give us the ability to take each one of our reps and make it like 10X of their output that they're giving on a daily basis.
(12:52):
You're
Gayle Kalvert (12:52):
Not going to tell us how. Inquiring minds want to know talk. Yeah. So I'm also thinking here, if obviously Onfire is a solution for this, if an organization is maybe not ready for that, are there ways to do this on a smaller scale? So if you're an early stage B2B company, right, you don't have the brand credibility, if you don't have a big budget, how would they get started?
Tal Peretz (13:18):
First of all, even if you are with a small budget, I think you need to start building this culture of being what you call AI and A and see how we take like small processes of the workflow and start to automate it with AI. I think the main gap that you probably will have at the beginning is that you won't have this rich data context and ecosystem, but you can start small and maybe do a couple of specific solution and even like maybe build your own agents on specific platforms that you care about specifically. So you can do that and then tie it up with other systems and other workflows inside like in- house solutions just to start and be ready for the next phase.
Gayle Kalvert (14:01):
Right. And the next phase happened yesterday. I mean, this is all happening so quickly, right? So for somebody who's a marketing leader at a tech company right now and basically they're like, "I use Cloud, I was using ChatGPT, now I see that Cloud is way better. Maybe I've played around with Gemini and Gronk and all these other things." What are you talking about? When you talk about using AI-
Tal Peretz (14:24):
That's a great question. And this is kind of like an overview of what I seen from the last few weeks, which I think is fascinating. There is three types of organization right now in the marketing crowd. So one is the ones that's still acting AI as like what do you call like a chat assistant. Sometimes I go to ChatGPT or Cloud and asking a question and then getting some answer. The second one basically took a specific, what you call like a workflow, for example, building ads campaign or building an automation to do some prospecting or doing any other activities. It can be with Cloud or any other tool that they have, but it basically take one workflow, they automate it until it works. They work on the prompting, they work on setting up the environment, they connect it to their software proof from your HubSpot or Salesforce, and they do that.
(15:20):
The last and maybe the most advanced one, they're starting building, and you said you're not coding, but I can tell you that I saw, I think in the last week, two VP of RevOps that basically been using CloudCloud or Curacer, hooked up to, in this case on Fire, but there is a lot of other tools to find those data points and context and to build dedicated applications that's doing the day-to-day much better, not just their day-to-day, but for their return reps. We saw one of VP of Republic to build an agent that live inside Slack, their organization Slack, and query on Fire at the backend, but it built by itself. And then I saw it as a CEO of the company and then I saw, "Hey, that's amazing. I think you're in the cutting edge. Maybe if you will think in the future to join a company that build this type of products, you have a position here, you see?" But it all started when you wanted to basically solve a big problem that they had.
(16:29):
And now you have the tools to do that. And I think we will see more and more marketeers and sales reps going into the right side of building those solution because you know best what you need right now on top of the best context and data learner.
Gayle Kalvert (16:46):
Honestly, it's incredible. Like you said, this is what you saw last week, and I'm sure when we watch this in two weeks, there'll be new information. I'm curious, Tal, what you think as far as what do you look for when hiring somebody in sales and marketing? I think what you just said is one thing I can obviously state as somebody who's really enthusiastic and excited about AI and using it to solve problems. What would you say are the traits that you're looking for when you're hiring now?
Tal Peretz (17:19):
As a growth startup, you're always in hiring mode for great talent. So just in the last month we had a new BDR and a new account executive that joined, so I can have a way to look into that. First and foremost for us is still that we want to see those values that resonate with the company DNA. And for us, we are looking for winners, people that used to win in the past and want to win in the future without interrelevance into AI or any solution that they had. So that, number one. Number two, I'm looking into and asking one question which I think show you what is the true creativity of the rep in the other end is, what have you built or done with AI in the past six months? And then in one question, you can see the ones that might be use ChatGPT for maybe asking do it yourself project in their free time in the weekend and the ones that actively been using it in the day-to-day and building stuff and shipping stuff.
(18:26):
And the way I see it is they have this DNA of they want to automate their work so they can do more if you take more deals, building more product line, basically make them 10x better without someone that's asking them to do that. And it's not even need to be collated to work. Maybe they build, I don't know, internal system for their daycare shifts that they have with their family. So I think this is the big question. And last but not least, we're looking for someone that is coachable. We want to see that people that they want to win, they understand technology, but they know how to listen and to improve. So those will be like the top three things that I'm looking for right now.
Gayle Kalvert (19:13):
Well, Tal, thank you so much. We appreciate your time. Where can everybody find you?
Tal Peretz (19:17):
So first of all, thank you for your time. It was amazing to participate. So you can find me on LinkedIn under my profile and also in Onfire.ai on our website, and feel free to contact me. I must say that we are hiring basically across all roles from engineering, finance, sales, marketing, so feel free to attend and thank you for your time. Appreciate it.
Gayle Kalvert (19:39):
Terrific. Thank you. If this episode was helpful, please follow Marketing in Progress and tap like. It helps other marketing leaders find the show. And if you know someone who's navigating similar challenges, feel free to share this episode with them. Thanks for listening. We'll see you next time.