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Who you’ll learn from

The CMO of Samsara joins GTMnow to walk through exactly how she ran an AI transformation inside a public company, from a 2.5 week boot camp to 113 agents in production, all while keeping headcount flat and pushing pipeline and revenue up.

Meagen Eisenberg has led teams through platform shifts before (PLG, social, Covid) at MongoDB, DocuSign, Neiman, and now Samsara, and she argues AI is categorically different: not a new channel, but a production shift that changes how the work itself gets done. She gets tactical on the change-management sequence (learn by doing before you cap anything), how agents live in Slack for every function, the ABM pages that went from 2-3 weeks to under 30 minutes, the KPIs she tracks, how she interviews for AI fluency, and her message to anxious operators: this is a chance to leapfrog, not a threat.

What you’ll learn:

  • Why AI is a production shift, not just a new channel, and what that changes about running a team
  • The change-management order that works: let people learn and play before you put cost caps on
  • Inside the 2.5-week AI boot camp (vibe-coded LMS, hands-on agent build, present-back) that trained half the org
  • Why she democratized agent-building into every function instead of centralizing an AI team
  • How 113 agents run in Slack across events, sales, ADR support, and creative
  • The rebrand that hit the market in 3.5 weeks instead of six months
  • ABM landing pages from 2-3 weeks to under 30 minutes, and content from weekly to 10 a day
  • How she keeps headcount flat: backfill differently, raise the bar on output
  • How she interviews for AI fluency, and why you can’t earn a top calibration score without building agents
  • Her advice to anxious operators: build agents to leapfrog leadership, don’t wait

Episode highlights

01:10 – Welcome, and leading teams through PLG, social, Covid, and now AI

01:47 – The common thread across MongoDB, DocuSign, Neiman, and Samsara

03:39 – Why AI is a production shift, not just a new channel

04:55 – Running an AI transformation as a public company

06:41 – How Samsara rolled out tools: adoption first, cost caps later

08:32 – Building AI literacy: learn by doing

09:52 – Inside the 2.5-week AI boot camp

11:43 – Why a boot camp, and how it evolved from power hours

15:24 – Sponsor: Nooks

16:27 – How to measure AI literacy over time

17:49 – 113 agents: how they’re operationalized and maintained

19:54 – Flat headcount, and rethinking build-vs-hire

21:16 – The interview questions she uses to test AI fluency

22:27 – Her message to anxious operators: leapfrog, don’t fear

26:53 – Why the agents live in Slack (plus Gumloop and more)

27:43 – The human-to-agent ratio, and where it’s heading

29:20 – What actually lets someone 10x: the ABM page app

31:51 – The rebrand that went from a year to 3.5 weeks

32:25 – Favorite creative use cases

33:57 – Advice to other CMOs: jump in, don’t wait

35:15 – What “technical” means for marketers now

37:22 – The AI KPIs she actually tracks

38:30 – The future of marketing: agents that act overnight

40:34 – Rapid fire: raising the bar, and onboarding AI like a new hire

42:01 – The best advice she ever got

43:28 – Where to find Meagen

Key takeaways

1. AI is a production shift, not just a new channel.
Meagen has led teams through PLG, social, and Covid, and she draws a sharp line between them. Social changed how you reach people. PLG changed the buyer. Covid changed the venue. AI changes how the work itself gets done. You can’t adapt to that by spinning up a team to learn a new channel, you have to rethink how the whole org operates. Her throughline across all 4 shifts is an engineering mindset, which tracks with an MIS background and a first job as an IT engineer: curiosity, comfort with technology, and change management, balanced against the creative half of marketing.

2. Let people learn by doing before you cap anything.
Samsara’s first 6 months were pure adoption. No brakes, hackathons, rewards for the people using it, hiring for people who embraced it. Cost caps didn’t come in until about a year in, and teams driving outsized results still don’t have one. Meagen is candid about the economics (“half my AI dollars are probably wasted, I just don’t know which half”) and treats the waste as the price of finding out what works. It only holds up with top-down buy-in: CEO Sanjit Biswas gives everyone tool access, uses the tools himself, and has bought 23 AI-native products.

3. Democratize agent-building instead of centralizing an AI team.
The common model is a central team of experts that builds agents on request. Meagen went the other way and taught the org to build their own. The boot camp runs 2.5 weeks: about a week and a half of self-paced courses on a vibe-coded LMS, then a week of hands-on sessions taught by marketers on her own team, ending with everyone building an agent and presenting it back. Her reasoning is that the expertise for what an agent should actually do sits inside each function, so the only way to scale is to teach everyone. More than half of her 260-person org can now build agents, 113 are in production with roughly 40 more in the works, and they all live in Slack across events, sales, ADR lead-flow support, and creative.

4. Flat headcount, higher output, and AI fluency is now a hiring and promotion bar.
Meagen kept headcount flat this year. The question shifted from “do we hire?” to “do we backfill with a different role?” The numbers behind that: ABM landing pages went from two to three weeks with an agency to under 30 minutes, using an app that researches the account, pulls from Salesforce and past pages, applies brand guidelines, and builds the page in the CMS. Content went from weekly to about 10 a day. A full rebrand hit the market in 3.5 weeks instead of six months. She interviews hard for AI fluency (how you use it at work and outside of it, what you’ve built, what came of it), and nobody at Samsara earns a top calibration score without actively building agents. The trade is explicit: if you invest the learning time, you deliver more, faster, or both.

5. The anxiety is backwards. AI is a chance to leapfrog.
For operators worried AI will take their jobs, Meagen’s answer is blunt: in marketing, there won’t be jobs for people who haven’t learned it. Get your hands dirty and use agents to have outsized impact without building a big team. She’ll happily promote someone doing the work of 10 people. Democratized data and tools also make it easier to cross into adjacent roles, a growth marketer picking up product marketing for example, and you can ask the AI how to do the job you haven’t done before. Her picture of the future marketing org borrows from predictive vehicle maintenance: instead of checking dashboards, calling a meeting, reviewing historical data, and waiting on budget approval, the agents already have all of that and deploy overnight, waking you up to “noticed commercial pipeline in Mexico was low, here’s what I shifted and deployed, and I’ve notified sales.”

Meagen Eisenberg

Sophie Buonassisi (Host)

GTMnow

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GTM 207 Full Episode Transcript

00:00 – 00:25

Megan Eisenberg: AI is a production shift. It really changes the way work gets done at a fundamental level. What is it like to go through this big, big transformation in such a high stakes environment? As a public company, obviously our numbers are much larger. We have to be more disciplined, so we’re very focused on outcome and predictability. Megan Eisenberg, Chief marketing officer at Samsara what are the actual AI KPIs, if you will, that you are tracking to measure your AI?

00:25 – 00:44

Megan Eisenberg: If you are? Yeah, I mean, we certainly get reports on who’s logged in and using the different tools. So we we can see who’s actually using them. And we look at it every quarter. You know, we had ChatGPT out of the gate. Then we got Gemini. We have Claude co work. We’ve bought 23 AI native tools. I asked Claude to coworker act like you’re the CMO.

00:44 – 01:10

Megan Eisenberg: Samsara. It’s hooks into access of Salesforce. All these different tools and data sets that we have. And you mentioned so you’ve got 260 people in your marketing organization, 113 agents.

01:10 – 01:37

Sophie Buonassisi: Megan, welcome to GT now. Thank you. Thank you for having me. It is an honor to have you here and now. You are very well known as a marketing leader for driving pipeline, driving revenue across MongoDB, DocuSign, Neiman, and now samsara. You really led these teams through great inflection points. So things like pealed social media at Covid even and now AI.

01:37 – 02:10

Megan Eisenberg: What is the kind of common thread to being an early adopter and really kind of bridging that curve? And how are you doing that today with AI at some Sora? Yeah. So good question. They’re all very different businesses, different buyers, and they all went through different technology shifts. I would say, although AI being probably one of the largest we’ve seen, and I think a common thread for success and really, you know, navigating the different organizations is adaptability and having an engineering mindset.

02:10 – 02:36

Megan Eisenberg: And what I think about days my undergrad was Mis and computer science, and I was always very tech forward. So I started out as a IT engineer but shifted into marketing. And I think that comfort with technology and understanding the buyer and understanding how teams work and how much originally the systems gave us a lot of just innovation and ability to be more productive, to learn insights from our data.

02:36 – 02:53

Megan Eisenberg: And they still do obviously, that today. And I think when I look at those teams, the engineering mindset to learn, right, you’ve got to be curious. You need to learn the new technology. You need to have change. Management is a big part of it as well. In order to adopt these technologies, you want to be innovative and on.

02:53 – 03:13

Megan Eisenberg: You know, you could sit around and wait and see what people do with it, but there’s a huge competitive advantage if you learn and embrace it first and adopt it. So I would, you know, say across all those teams that sort of focus on engineering, learning, playing with the tools, change management. And then I think there’s an art and science with marketing.

03:13 – 03:39

Megan Eisenberg: It is that balance. You can’t just be all engineer building technology. There’s a creativity that goes with it. As CMOs, we’re responsible for building our brands, but also scaling and hitting revenue. And I you know, that’s the reach and revenue and that’s that balance of art and science being able to tell the story. And so understanding how to work with your teams to use the technology, but also bring the stories to market and then build pipeline and deliver revenue.

03:39 – 03:40

Megan Eisenberg: Brilliant, brilliant.

03:40 – 03:58

Sophie Buonassisi: And when you were going through this transformative process, when I kind of first hit, like, what are some of your learnings now in hindsight from going through this particular platform shift? Obviously, you’ve done it before with mobile and social media and all the things, but like you said, was kind of one of the the biggest of all of them.

03:58 – 04:05

Sophie Buonassisi: You’ve been some of your kind of learnings in hindsight. If you were to give advice to somebody else looking to successfully make these changes like you have.

04:05 – 04:22

Megan Eisenberg: Yeah. So, I mean, I think if you look at social, we really changed the way we reached people. It was new channels. If you looked at plug, it changed who the buyer was. If you look at Covid it changed the venue. So AI is a production shift. It really changes the way work gets done. At a fundamental level.

04:23 – 04:35

Megan Eisenberg: It’s categorically very different to adapt to. It’s not just let’s create a team and learn a new channel. It’s actually reinventing completely how you build out and operate as an organization.

04:35 – 04:54

Sophie Buonassisi: That I mean completely makes sense. And it’s an interesting position. I feel like to do it now you tell me at some sort because samsara is a public company trading on the New York Stock Exchange. Like you have high stakes. You have you know, you have this environment that is so unique, like what is it like to go through this big, big transformation in such a high stakes environment?

04:54 – 05:16

Megan Eisenberg: Yeah, I think I mean, as a public company, obviously our numbers are much larger. We have to be more disciplined. We’re very focused on outcome and predictability. But I think that we also have a lot of resources. Right. And we have a strong leader. Our CEO Sanja is very forward on AI. He’s been he, you know, gives everyone at the company access to all the tools.

05:16 – 05:37

Megan Eisenberg: So we’ve you know, we had ChatGPT out of the gate. Then we got Gemini. We have Claude co work, we’ve bought 23 AI native tools. He’s very much leads by example. He uses AI all the time. And he he wants us as leaders to be using it, encourage it. We want to hire people who are embracing it. And we want to transform the way we run our organizations.

05:37 – 06:14

Megan Eisenberg: And it’s not just marketing. He’s looking at this across all functions in the company. And so I think I feel like it’s a huge advantage because we have access to the tools. We have a leader who is very forward on it. And then I have a very technical team. I’ve always hired technical talent on the team, and that just allows you to play and experiment and be very comfortable with it and not having to rely on maybe a central org to help, to be able to really do it within your function and experiment with team members that get what marketing’s function is about and what we’re focused on, I think accelerates it as well.

06:14 – 06:38

Sophie Buonassisi: Super fascinating. I mean that’s amazing to that. You’ve got someone leading by example and empowering everyone with AI that comes with a cost to especially for a larger organization. And we hear often that’s a huge preventative factor for large a lot of large orgs too, because once they switch that Libra on, like the costs go up. How has that balance been with AI and just absorbing all of perhaps the cost differences?

06:38 – 06:41

Sophie Buonassisi: But just as you empower and take this like very empowering approach.

06:41 – 06:58

Megan Eisenberg: I mean, I think we’ve been very smart about it at samsara. I mean, we gave access to the tools we, you know, understood. You know, we’ve been monitoring the cost. We are learning. I think the first step in change management is get the team to learn it right. Don’t don’t put the brakes on. Let the team play. Teach them how to build agents.

06:58 – 07:15

Megan Eisenberg: Give them. Ideally, create hackathons. Hire people that want to be involved in it. Reward those who use it. And that was sort of the first six months really of our change management adoption is just embrace it, learn it, because you don’t even know what you can do with it until you start writing prompts and you start seeing what it can do.

07:15 – 07:38

Megan Eisenberg: And of course, every day the pace at which is going is so fast that, you know, we have grok today, we have fable. You know, these are like real people level capabilities. They it really can do some quite impressive things. And so you I don’t think you want to stop people from learning and playing with that. And yes, we’ve now come over a year into embracing it.

07:38 – 08:01

Megan Eisenberg: And we we have caps on what people can use. But if there’s a team that is having amazing outcomes and is bringing something new. We’ll there’s no cap for that, right? If it’s transforming the business, if it’s driving more revenue, that’s what we encourage. I did hear a funny quote about, you know, the old adage of, you know, half my ad dollars aren’t working. I just don’t know which half. Well, sort of like half my AI dollars are probably going to waste, but I don’t know which half. But I know it’s really important that we that the half that is working is out there and transforming how we, you know, operate as a marketing org. The impact that we have, how we’re driving the business.

08:19 – 08:32

Sophie Buonassisi: Yeah, definitely. And I’m sure that half that isn’t working, perhaps there’s some kind of feeder energy towards the half. That is because like you said, you don’t know what you don’t know. And yes just enabling that literacy is really important at that stage.

08:32 – 08:53

Megan Eisenberg: Yeah. And literacy is really you learn by doing. I think one of the, you know, early I said I had Mi’s computer science undergrad, I went to Cal Poly and their model was really learn by doing. And I think this is that times ten, right. Your team needs to be working with it, using it. It’s a skill they’re going to need in the future.

08:53 – 09:08

Megan Eisenberg: There’s no I don’t think there’s any future where that’s not part of it. And as you know, as we’re interviewing, as we’re talking with candidates, you want to know that they’re curious, that they’re learning that what tools are they using and that they can talk to it. And we spent a lot of time educating our teams on it.

09:08 – 09:25

Megan Eisenberg: We’ve coded an app. So we have a two and a half week boot camp. And you you come out learning how to build an agent, which is even easier now with things like Cloud Coworker, but, you know, giving them that comfort level. And I can see now that we’ve trained more than half the marketing org to build agents.

09:25 – 09:52

Megan Eisenberg: They’ve gone through the boot camp and we have more going through it. All the ideas are starting to unlock and how they’re they’re accelerating their roles, they’re forming their workflows, and we see it in results. More importantly, we see it in our pipeline. We see it in our revenue across, you know, sales segments, products, etc.. So I definitely am you know, I see the benefits of having adopted this pretty deeply in our org in the last year.

09:52 – 09:58

Sophie Buonassisi: That is incredible. I got to ask about this boot camp. You had the AI boot camp. What is it entail exactly?

09:58 – 10:14

Megan Eisenberg: Yeah. So like I mentioned and I’ve gone through it myself. We have a bunch of coursework that you take. So the first week and a half is online courses that we vibe coded the LMS with the recordings. And there’s a lot of reading, a lot of playing with the tools, a lot of downloading and setting up the tools so you’re ready for the environment.

10:14 – 10:34

Megan Eisenberg: And then the second week you’re in class a couple hours a day, and there’s an instructor that are all marketers on my team that are walking through, showing them how to use the tools, and then they’re given an assignment where they need to build an agent and present back. And then I sit in with some of my other directors and listen to the different things that they’ve built.

10:34 – 10:52

Megan Eisenberg: So the first class, we had 23 new agents. We actually have 113 agents. We’ve built as an organization within marketing and 40 more in the works. And I think the trick is you could create a team that just does it. You could have a team of experts and you just train them. And then marketing generates ideas and they go build it.

10:52 – 11:09

Megan Eisenberg: But I don’t think you scale that way. And I don’t think you transform an entire organization because that skill set and their functions lives within their expertise. And so if you train all of them to do their own and build their own agents, you get to a place where we are, where we’ve transformed much more of the organization.

11:10 – 11:27

Sophie Buonassisi: Oh, yeah, I mean, that’s super empowering, too, because those are the people that are going to now have their creativity unlocked and be able to go on and build for the long term rather than centralizing in one group, which is interesting because that’s a very common model actually to centralize it. So I love your democratization process and empowerment across the organization.

11:27 – 11:43

Megan Eisenberg: Yeah, I think people they know this is important skill for their future and they want to learn. I think most most people want to pick this up, want to be able to build with it. It’s all I mean, it’s everywhere. You can’t escape it. So I think if you want to learn it and transform your role to that’s what we’re looking for.

11:43 – 11:52

Sophie Buonassisi: And how did you decide a boot camp was the right environment? Because there’s so many different ways to teach people AI, and we’re still kind of learning what works like, how did you land on this?

11:52 – 12:06

Megan Eisenberg: Yeah, I think I mean, it was probably two quarters into the journey and we first started out lead by example, right? I was playing with the tools. I was building stuff. I would put it into the marketing slack channel. Hey, look what I built. Here’s the prompt I use. You guys should try it. It’s a lot of fun.

12:07 – 12:23

Megan Eisenberg: We had AI power hours, and those started out being where we present technology and learning and people would watch. But then it was like, well, if you’re not doing it, if you’re not learned by doing, you don’t really learn it. And so power hours turned into hands on. You brought your laptop, they showed you, then you did it yourself.

12:23 – 12:45

Megan Eisenberg: You could ask questions. And so as that evolved, we realized, okay, there’s a need for more than just AI power hours, just sharing of knowledge. We need some sort of boot camp. It didn’t really exist. Like I would say, it used to be, you would go to a one week class and pick up. You would learn how to do Excel or Lotus Notes or I don’t know, you know, some sort of skill, but that didn’t exist.

12:45 – 13:03

Megan Eisenberg: And so we thought, let’s just build it. We we feel sophisticated enough in playing with it and building it. The first quarter we were really into it. We got really into Geo. And of course, because here’s a whole new channel that customers are getting information. How do you understand the content? How do you see where you’re ranking and stay on top of it?

13:03 – 13:29

Megan Eisenberg: We looked at different tools that were out there and we decided to build our own. So we built our own, I guess, profound equivalent that looked at ChatGPT, it looked at Gemini, looked at perplexity, and really started to analyze how we were ranked content, where we were showing up well, where we weren’t. And then that kicked off a whole content build strategy, a whole set of learnings around FAQs and how you rank the different LMS.

13:29 – 13:55

Megan Eisenberg: And so that gave us a huge lift. Like we saw a lot of return in learning geo, building out the tools and that. And you know, we had to create an MSC P server for that. Our back end, we use Databricks for our data platform and really started to be able to connect all the different tools. We had all these SaaS tools that were really hosting siloed information that we wanted to to pull into one place.

13:55 – 14:13

Megan Eisenberg: And so the ability we unlock that now, that’s much easier to do. Even Databricks has genius, where it makes it pretty easy to to go and use natural language to query on your data and get information right away. So we started doing that. We played with tools like One Mind. So it’s, you know, its own agent in itself.

14:13 – 14:35

Megan Eisenberg: And it’s it sits on our website. It answers questions. Of course we had to train. We call our Sam. And she’s been she’s very knowledgeable. People spend on average two minutes and seven seconds with her. You can either chat with her or you can talk. Chat is 59% of the conversations and 41% is talking. I actually think more and more we’ll talk.

14:35 – 14:58

Megan Eisenberg: We’re used to texting, talking to text. We’re just getting a lot more used to that, talking to our LMS and everything else. But it’s been great to see the interaction with our customers. And she’s selling right. She’s already returned a lot to us as as someone on our team that’s moving deals along at various parts of the funnel, people that are just starting to learn, and others that want to learn about our new products that we put out there.

14:58 – 15:06

Sophie Buonassisi: Oh that’s incredible. And it really does take it to the next interactive level, like the name play, to feel very fitting for samsara.

15:06 – 15:09

Megan Eisenberg: Yes. We even created for World Cup a custom background.

15:09 – 15:10

Sophie Buonassisi: Amazing.

15:10 – 15:20

Megan Eisenberg: So we have some fun. I was in London for two weeks during it, so I will say I was rooting for that for Great Britain. Yes, England I should say yes.

15:21 – 15:36

Sophie Buonassisi: Yeah, yeah, that was a tough one for them. Yes. Now you’re empowering people with these boot camps and teaching them AI literacy. How do you actually measure AI literacy after that or ongoing? Like how do you know where teams at and where you need to take them?

15:36 – 15:56

Megan Eisenberg: Yes. So, you’re right, it doesn’t stop with just a boot camp. That’s certainly, I think, the beginning. I’ve seen the unlock as they learn how to build an agent. They’re not as they’re not as timid about it, and they start to think of new ideas. But the technology is changing every day. So, I mean, I always share I’m listening to a bunch of newsletters and reading a bunch of newsletters in the morning.

15:56 – 16:18

Megan Eisenberg: I think rundown AI is great. I think neuron, all of these, AI fire. There’s dozens, right? Yeah. And every day you’re getting the updated news on what’s going on in the AI space. And so I’m always I learned something new. I’ll send that out to someone on the team. Hey, we should look at this to build a video or we should look at this.

16:19 – 16:41

Megan Eisenberg: I here’s an interesting case study with AI. Are we doing this or not? And my team leaders are as well trying to really stay up on it. Our CEO, he sends me stuff all the time like, hey, have you seen this? It’s really cool. He’s built some amazing videos on cryo and some some of these other platforms. And so it is probably the most fun I’ve had in the past year learning new technology.

16:41 – 16:47

Megan Eisenberg: It’s accelerated so many different things. And I think it’s it’s just a lot of fun. Yeah, yeah.

16:47 – 17:04

Sophie Buonassisi: So fun. And I think you mentioned now you have 131 agents in the 113, 113 party. Yes. 113 agents. Like how do you operationalize that? How do you maintain them? What kind of use cases are they for? Where do people find them. Yes.

17:04 – 17:21

Megan Eisenberg: Yeah. So I they start out by function I think as you release your team to learn. So the events team has several agents. Think about our big user conference. There’s an agent that might talk about how you drive demand, what are some ideas and give you new ideas every day. And look at your demand. There’s agents that we’ve built for sales.

17:21 – 17:47

Megan Eisenberg: They always have questions. What’s the agenda? Has my customer or prospect registered? What is there an executive that can talk to this. And so that agent and these agents all live in slack so they can access them. We have it on the Addr side. So we support our address. Leads come in at 30% of our tickets to marketing ops are were really around lead flow SLAs, questions like that.

17:47 – 18:05

Megan Eisenberg: Now they just ask the agent and the agent, you know, does the three hours of research to track down where the lead came from, what the campaign was, what the SLAs were, and all the background creates the doc sends it over to the ADR and their manager if necessary. And that’s taken the work off the Ops team’s plate.

18:05 – 18:25

Megan Eisenberg: So I think that’s a great example. We’ve created a ton of tools for our sales team just to make them very efficient of following up on leads, sending messages, and being able to ask anything. We have a reference agent that will help them get references, and it will ping the right owner of the account. It will then get the approval process.

18:25 – 18:39

Megan Eisenberg: It does a lot of stuff that just took a lot of time, and so the team’s gotten a lot more efficient. We’ve we’ve been able to pull in a lot of our, you know, if something used to take two weeks, we can do it in a week. So our capacity is much higher. We can just do many more things.

18:40 – 18:52

Sophie Buonassisi: I mean, incredible to grow that capacity. And naturally that translates to hiring and curious. Yeah. How has that impacted your thought process around do we build this? Do we hire a headcount?

18:52 – 19:14

Megan Eisenberg: Yes. So I’ve kept headcount flat this year. So it’s less on. Do we hire headcount. It’s more on. Maybe we’ll backfill it with a different role. And and we’re we’re really thinking through how we run the organization moving forward. But we still do quite a lot of hiring. And that there’s there are backfill for roles. There’s areas that we’ve changed out who’s there.

19:14 – 19:38

Megan Eisenberg: And I think hiring is I think it’s very important I meet everyone that joins my team. And I have a, you know, 260 person team. And whether they’re a direct or an I see I care deeply about what they’re going to add to the culture. I care that they understand what we’re doing on the AI side. And I ask a lot of questions on how they’re using AI, how they approach it, what tools have they used?

19:38 – 19:55

Megan Eisenberg: And I’m looking to see do they have a command of the language? Can they get in the details? Can they talk about the different languages and models? Do they have a MCP server. And I want to know have they really transformed their role? It’s one thing, okay, I use it to write. Every day. I ask a question. I use it to write.

19:55 – 20:13

Megan Eisenberg: I think you should. That’s definitely the right answer. But on top of that, have you changed your role? How how do you change the outcomes and you’ve become a much better? Whatever function that is, you’re a much better events manager, growth manager, you’re much better product marketer, whatever the function is, communications. I want to know how it’s transformed that role.

20:13 – 20:21

Sophie Buonassisi: That’s a great way. Do you have any like tactical questions that you asked to really pull that out of people engage if there are staying abreast of AI?

20:21 – 20:40

Megan Eisenberg: Yeah, I mean, I just asked them how how are you using AI at work and how are you? How are you using AI outside of work at what have you? You know. Have you built any agents talked to me about the actual agents? How did you build that? What was the outcome of it? What did you learn? And you can quickly see those who have not really done it at all.

20:40 – 20:56

Megan Eisenberg: And those who have. And it’s not a no if you’ve not done it. But I want to know that you’ve at least some some people are working at companies that won’t let them use it at all. But there’s some all these tools are available outside of work. So and many of them you’re not paying to use them. There are free tiers.

20:56 – 21:02

Megan Eisenberg: So at least show that you are are experimenting with it outside of it.

21:02 – 21:11

Sophie Buonassisi: That’s a great call out. And there’s so many different personal use cases. I’m sure you hear all sorts of things from applicants to around different, different use cases in life overall.

21:11 – 21:12

Megan Eisenberg: Yes.

21:12 – 21:24

Sophie Buonassisi: A lot of go to market operators are most quietly anxious, sometimes not so quietly anxious, but just anxious about AI overall and essentially eating their job. What’s your take on this?

21:24 – 21:43

Megan Eisenberg: So I mean, I think they need to have they need a mind shift. This is the future. Certainly in marketing there will not be jobs in the future if you have not learned this technology, we are training you. We’re giving lots of opportunities to use it. So one, I think they have to have the mind shift. It’s here.

21:43 – 22:01

Megan Eisenberg: There’s no avoiding it. So it’s in your best interest to learn it. To be curious, just get your hands dirty. Start asking it to do things, even if it’s not the output that you use, just ask it. I mean, I, I don’t know, a week or two ago, I asked Claude to work, act like you’re the CMO of samsara.

22:01 – 22:31

Megan Eisenberg: It hooks into access of Salesforce, all these different tools and data sets that we have. And I said, my job is to drive revenue and to build pipeline. What are my top three highest priorities every morning? Assess my email, my calendar, where what our status is. And it’s really impressive when it comes back with and some of the insights, some of it not even part of the that it’s not under my direct control, but it’s certainly something I could impact and should be that I hadn’t thought about that it’s brought in.

22:31 – 22:53

Megan Eisenberg: So do that for your role, right? This is my job. This is my company. Here’s what I’m trying to do. What could I be doing differently? Or what should I focus on today outside of all the other things I’m working on? And so that is, you know, an example. I also think the smart ones will go, this is my opportunity to leapfrog leadership, because I don’t need to hire and build a large team to have impact.

22:53 – 23:11

Megan Eisenberg: I can build agents, I can transform the workflow. Maybe I want to hire 2 or 3 people, but if if someone came to me and said I didn’t, I don’t need to hire 2 or 3 people. I’ve built these agents and they’re doing the work of 2 or 3 people or ten people or whatever that is. I am definitely going to promote them and give them more responsibility.

23:11 – 23:35

Megan Eisenberg: Right. So it’s an opportunity to, I think, have a larger impact within an organization. To your point earlier around democratizing the information and the data, everyone in many ways has access to it, and you can do any role. I could be a growth person who now does product marketing. I can be product marketing who does comp Intel and I can, you know, you can ask it even if you don’t know how to do that role.

23:35 – 23:55

Megan Eisenberg: Hey, how would I do this role and how would I work with you to do this role? And these tools are amazing at even teaching you how to do that. And even as a leader, what should I expect of this team? What should they be doing? Here’s what I’m seeing. And so I, I think, yes, sure, people are nervous about it because it’s new, but the ones who adapt and deal with the change are going to be successful.

23:55 – 24:18

Megan Eisenberg: And so I think you just have to realize life has changed. And this is, yes, a dramatic change, but it’s could be career defining for them. And it gives them the opportunity to really to grow within the organization by embracing it. And I think as leaders, it’s our job to reward that. And we have I mean, we have even when we look at calibrations, we rank one through five.

24:18 – 24:39

Megan Eisenberg: You can’t get a 4 or 5 the highest rankings unless you’re actively working with AI building agents. And so setting that expectation a year ago. So people realize that’s an important part of how we’re we’re measuring and building. And it’s part of the job. I think it’s as people build cool things, putting them in front of all hands, putting them in front of the company, showcasing their work with it.

24:39 – 25:01

Megan Eisenberg: We did an amazing rebrand recently, and the creative team built a ton of agents that I mean, imagine all the work when you do a rebrand of all the assets you have, your website, all the PowerPoints, all the case studies, and they they created agents that actually go, you know, we go on it’s called branding Agent. And you can give it a document and it’ll rebrand it for you.

25:01 – 25:25

Megan Eisenberg: So I’m in slack, I’m sales. Hey, here’s my PowerPoint deck. I need the rebranded version of it. It will do it. I need the rebranded case study. And it’s, you know, using our custom fonts. It’s using our branding guidelines, our images, all of that. So the team did a ton of work on even icons and building out, you know, you just need a ton of images for paid search, for digital search, all of these things.

25:25 – 25:40

Megan Eisenberg: So to mass produce those used to be hiring a lot of creative production hires. And now you you you can use AI to build them. You know, you need an ad in ten different format sizes and it can just do that instantly. It’s it’s really impressive.

25:40 – 25:51

Sophie Buonassisi: That is very impressive. And it’s so nice that it’s accessible through slot for other functions too. That’s that’s huge. Yes. So regardless of how you’re building, your agents are all in stock. That’s where they live.

25:51 – 26:15

Megan Eisenberg: A lot of them live on slack. Yeah. I mean we built certainly others and we use Gum Loop for a lot of creation of agents and workflows. But yeah, a lot of the way you you have others access, it is through it. But we have stuff built into our slide decks where it’s a widget. We have Chrome browser plugins that sales can use to to use it that have been built out on AI.

26:15 – 26:21

Megan Eisenberg: So there’s definitely many other formats. But for the go to market organization, slack is a big go to. Yes.

26:22 – 26:40

Sophie Buonassisi: For sure. Everybody’s living in their meat where they’re living. And you mentioned so you’ve got 260 people in your marketing organization. Yes, 113 agents. That’s about like a 2.3 ratio actually, of human to agent. What do you anticipate that changing in the future?

26:40 – 27:01

Megan Eisenberg: I mean, I think in two years your orgs are smaller, right? I think you’re 200 people maybe. And you’re 400 agents, right? Yeah, right. There has to be a whole life cycle of the agents. We’re going to sunset. Some of them, some of them weren’t built. You know, they need to be optimized. Maybe some are more costly. You know, we learn a lot around gong video calls voice.

27:01 – 27:36

Megan Eisenberg: All of that is heavy is a lot of tokens. So we optimize that through building a vector database and Databricks. And so that’s a way to access gong versus going direct. So there’s a you know we’re constantly learning what’s the most efficient way models are changing. They’re becoming less expensive. And so picking the model that you’re using the tool that you’re using I was at lunch today with a couple of our engineers in marketing, and they were talking about, oh, I flipped between the models depending on if I run out of tokens, if I have a certain job I want to do.

27:36 – 27:58

Megan Eisenberg: And and they, you know, I think it’s called herder. They use a tool called Herder that allows them to go and bounce through the different, models. And, you know, that will continue to evolve. People find a way to be the most efficient. So I think we will have more agents, but I think we’ll sunset some because imagine you built an agent and you leave a company, you know, who monitors, who manages that.

27:58 – 28:04

Megan Eisenberg: You know all of these things we have we plan governance around and and and compliance and then we’re monitoring the cost.

28:04 – 28:17

Sophie Buonassisi: So needless to say, you have greatly empowered your organization with AI. Like when somebody ten axed, they’ve gone through the boot camp, they’re suddenly super productive. Like what is actually enable them to do that. Previously they could.

28:17 – 28:38

Megan Eisenberg: Not I mean, the basics are like the content team. Maybe they did some, you know, a piece every week or every two weeks, and now they do ten a day, right? Abby M pages is a great one. We created a tool, an app that a true agenda app and that it thinks it builds. So it used to take 2 to 3 weeks.

28:38 – 28:58

Megan Eisenberg: We worked with the agency. We build a landing page around a company. We’d work with the sales rep, and now this actual app goes, you know, we give it the name, it does the research on perplexity. It looks at our other past ABM pages. It looks at the industry, it hooks into Salesforce, pulls information on the account, looks at the sales reps interactions.

28:58 – 29:13

Megan Eisenberg: It looks like at relevant case studies, it pulls our branding guidelines. Then it logs into Contentful, our CMS, and it actually builds and designs the landing page. And it can do that unless it basically is less than 30 minutes because you want to go in and review. You may change a few things, but it does all that and delivers it.

29:13 – 29:37

Megan Eisenberg: So you can do 40. I mean, you could do unlimited, right? I think AI skills us in unlimited ways. We just have to be able to then take the work and take it to market or build agents that take it to market. Maybe. But it does scale to infinity, right, as you think about it. So as each of these teams are unlocking what they can do with it, it’s giving them time back to work on other things to move forward.

29:37 – 30:03

Megan Eisenberg: We’ve certainly I mentioned earlier, we’ve compressed our timelines. So things just don’t take as long as to to deliver. We can just the same amount of people can do so much more. And that was part of the discussion I had with the team. We’re investing in, the time we’re learning and we’re building all these agents. We either need to deliver more or do it in less time or both, and it’s not the same people taking the same amount of time with the same, you know, there’s going to be a trade off there.

30:03 – 30:27

Megan Eisenberg: And it’s interesting. I think as a leader, you have to keep setting a higher bar because your output can be so much more. And we are all in. Every business is in a competitive situation. So our ability to execute very fast is a competitive advantage. And our enabling our teams with all of these skills to build just puts us out in the market in so many different ways and more personalized ways.

30:27 – 30:46

Megan Eisenberg: So we are what we deliver to market is way more effective than what we’re putting out there, because we have time to personalize it, because we can access this information really quickly. We could, you know, a rebrand might take six months. When we landed our our our brand, we took it to market at beyond. And within three and a half weeks, we rebranded and launched at the company.

30:46 – 30:49

Sophie Buonassisi: That’s how long your rebrand just took? Yeah.

30:49 – 31:04

Megan Eisenberg: Yes. So it took us a year with an agency and working through and working with our customers and going out there and and building the new brand. But now that go to market piece, where you do change management in the company was about three and a half weeks now. There was a lot of people working on it, long hours.

31:04 – 31:10

Megan Eisenberg: But we also used a lot of agents. And I think the only reason we could do that is because we had AI and agents to.

31:10 – 31:23

Sophie Buonassisi: Do it. That is an incredible use case. Yes. Do you have any other you mentioned ABM pages. You mentioned the rebrand. Any other favorite use cases that have been super transformative, or that your team has just loved doing with AI now?

31:23 – 31:45

Megan Eisenberg: I mean, everyone loves making videos, so I think creating videos have been fun. We did a World Cup players card where you could make your own personalized player card and then people. I was it was so fun to see everyone’s player card out on LinkedIn. So they’d create their card and then they would post it. And my feed for like a week was at World Cup player cards, which were the individuals.

31:45 – 32:00

Megan Eisenberg: But we did that for our customers. And so our customers really loved having their own player cards. So I think, you know, video and creative is always going to be fun with it. And I’ll just the level at which it can build and fast and so accurate now.

32:00 – 32:00

Sophie Buonassisi: Yeah.

32:00 – 32:01

Megan Eisenberg: Yeah.

32:01 – 32:24

Sophie Buonassisi: That’s super fun. Content is a really fun use for sure. Yeah. And now you mentioned a really interesting point earlier. And it was about how you have to keep pushing the bar to stay abreast with competitors or competitors. And it’s interesting because we used to have this finite time period or finite capability of a human. And so you, you were kind of constrained by that factor.

32:24 – 32:40

Sophie Buonassisi: When working against a competitor, you either hire more headcount to get ahead or you don’t. Yeah. Now it’s almost like this internal lever around that to you can hire more headcount if you train them to be more effective and skills. But you’ve also got this internal barometer like you’ve been pushing it super aggressively. You’ve kept had count flat.

32:40 – 32:42

Sophie Buonassisi: But what you’re doing is amazing.

32:42 – 32:42

Megan Eisenberg: Yes.

32:42 – 32:55

Sophie Buonassisi: So it’s this whole other kind of dimension that you’re dealing with from a leadership side. And I’m curious as you look at this just AI landscape as a CMO, what advice would you give other CMOs in this time?

32:55 – 33:17

Megan Eisenberg: Yeah, I mean, certainly jump in, don’t take six months to build an AI strategy. I think if you don’t have the skills in your team, go higher. Go hire engineers, technical folks that have the capacity to learn the tools or have already been playing with them. So you can unlock that for your team, invest and then training your team, making sure they there.

33:17 – 33:36

Megan Eisenberg: So there are a lot of tools online, all the, you know, clouds and open eyes. They all build classes. Now that you can learn how to build agents and work with it, I think, you know, set the expectations on how you’re going to measure success and and promotion, reward people when they’re using it every week you’re talking about it.

33:36 – 33:55

Megan Eisenberg: You have to lead by example. Of course, you have to be playing with it yourself and showing how you’re using it. You have to be up on the technology. If you don’t have an MCP server, get one set up and built, learn, talk with other CMOs, you know, exchange ideas. But I think you you can’t certainly I mean, nobody wants to sit on the sidelines.

33:55 – 34:10

Megan Eisenberg: I think I’ve been able to move really fast with the team because of our, you know, our ability, our technical talent and then just our leadership saying, yes, go, you go play with it, go learn, you know, train and do it, but also deliver the revenue.

34:10 – 34:26

Sophie Buonassisi: Yes. Always important that the army of the day. And I mean, you have a very technical background yourself. You mentioned you skewed towards hiring technical people. Define technical. Is that engineering background or for marketers and like how can they become if they are not already more technical.

34:26 – 34:45

Megan Eisenberg: Yeah. I mean, so certainly when most marketing teams will run the website, we, we have a website and a web store, but you typically have web developers for that. There’s also a lot of martech out there. So usually you have someone that’s running your martech stack that, you know, making the team a lot more efficient, giving them insight with the technology and all the tools.

34:45 – 35:06

Megan Eisenberg: So find people that have that skill set to add and then invest in the team and getting them to learn and to to build agents, have a hackathon, right? Train them how to do it and then do a hackathon. I think that’s the it’s one thing to watch the videos, but when you actually go to build it, that’s I think, where the real learning is.

35:06 – 35:29

Megan Eisenberg: And so having them learn it and and so I, you know, out of 260, I would say more than half are building agents and they’re not technical backgrounds. They I mean, this you don’t have to have a technical background to use these. You may have to have access to some of the tools. Right. You might need to work with it if you don’t know how to set up a mic server, if you don’t have access to Databricks or whatever your data platform is.

35:30 – 35:57

Megan Eisenberg: If you don’t, you know, if you work with your IT team on MarTech, then then pull them in. But I I’ve always found it to be a huge advantage to have technical resources that want to focus on the marketing problem or the marketing opportunity, because it’s hard to work with shared resources and it if they’re supporting every org, it’d be better to have technical engineers, web developers on your team that care deeply about what what you’re trying to build and build pipeline and use the different tools.

35:57 – 35:59

Megan Eisenberg: I just think you’ll move faster.

36:00 – 36:19

Sophie Buonassisi: That makes sense. That makes sense. Yes. And when you mentioned reward earlier you talked about recognition and a few things to help incentivize people to use AI. Yeah. You also talked about the levers around efficiency or output. What are the actual AI KPIs if you will, that you’re tracking to measure your AI if you are.

36:19 – 36:39

Megan Eisenberg: Yeah, I mean, we certainly get reports on who’s logged in and using the different tools. So we we can see who’s actually using them. And we, we look at it every quarter. And we as executives we can see it across our team. So that’s one I think two is when someone builds something and we see outsized results, then we put that on all hands.

36:39 – 36:59

Megan Eisenberg: We put that on leadership calls. We you know, our marketing slack channel is very active with what people have done, what they’ve built. I’m on the boot camp. So, you know, 23 in the first class, maybe another 20 in the second class. And so seeing the output there and what they’re building is important. We have hackathons and we have winners of the hackathon.

36:59 – 37:18

Megan Eisenberg: So we celebrate them. We’ve done some bonus like spot bonuses. We’re just really like wow, this was amazing. What you worked on a lot of of stuff around the rebrand. A lot of cool stuff was built there. And so, you know, all the tools that you have for it and making sure rewarding the ones that are leading. Yeah, I.

37:18 – 37:27

Sophie Buonassisi: Love it, I love it now. It’s transform marketing so much. Like, what do you think the future of marketing holds? What does the future look like for marketing? Is it is it discipline?

37:27 – 37:49

Megan Eisenberg: Yeah, I mean I think it’s completely reinvented. I think it’s a whole different organization. It’s not just taking a curating a team that’s focused on a channel or a function. I think you’re reinventing how marketing works. And let me let me give an example of that. If we look at our space in samsara, I think a traditional way to service the vehicle would be the check engine.

37:49 – 38:07

Megan Eisenberg: Light goes on. You notice that or you don’t as the driver. Then eventually you go back. You call it in a work order has to be created. Then you’ve got to drive to the service shop. They’ve got to order the part like it’s a whole multi-step process. With AI and agents. You really can transform it by the agencies.

38:07 – 38:30

Megan Eisenberg: The light go on, or may even predict through maintenance that the light’s about, that it needs maintenance. It automatically creates the work order. It automatically orders the part you’ve got routing on the vehicle. It automatically reroutes the vehicle to the shop it the service person, and it fixes it. And all of a sudden that happens in an environment where you took the human out, you took the guesswork out because all these systems are connected.

38:31 – 38:51

Megan Eisenberg: So now think about that in the marketing and the marketers world, every day we go, we get up, we look at our dashboards, and we go, oh, okay, this segment is looking low on pipeline. Hey team, let’s all get together. Let’s talk about what tactics, what campaigns should we be running to get that segment up. And then they go, okay, let’s look at historical data okay.

38:51 – 39:07

Megan Eisenberg: Paid search really worked well or direct mail worked well or whatever the specific campaigns were. All right let’s go do that okay. We got to go get the budget. Lets you know, think of all the steps and all the people involved to make that decision. You don’t need that with agents. The agents already see the dashboard. They already know the historical.

39:07 – 39:25

Megan Eisenberg: They already know tech decks that are working. They already know your budget and they deploy it and they’re working through the night. Right. And you wake up and said, hey, notice we were low on commercial in Mexico. I’ve deployed these campaigns. I’ve shifted budget over here. You had some excess there. Now we’re operating and I’ve notified the sales team.

39:25 – 39:32

Megan Eisenberg: Right. And you think about that, how it’s going to just really rebuild how we work together.

39:32 – 39:45

Sophie Buonassisi: Incredible. Yeah. Very exciting times ahead. Okay, Megan, I’ve got a couple quick rapid fire questions for you. You ready? Yes. Okay, finish this sentence. The thing that nobody tells you about leadership is.

39:45 – 40:05

Megan Eisenberg: You’re always raising the bar, right? Even if you hit your goals, the goals get higher. And I think your job is to constantly raise the bar. You have to. And it’s think of all the functions in marketing. It’s raising the bar on commerce, it’s raising it on growth, it’s raising on product marketing and Intel. And once you hit that it’s okay.

40:05 – 40:14

Megan Eisenberg: What next. And you’re you’re always you’re you’re responsible as a leader to keep pushing the team, getting the team excited, training the team and delivering.

40:14 – 40:22

Sophie Buonassisi: And now I adoption like we’ve been talking. Yes, yes. Okay, great. And what is the most underrated piece of advice in go to market?

40:22 – 40:45

Megan Eisenberg: I will take it from a marketing standpoint, even sales. I think the most important thing is to one know your product. So understanding the product. But even more important than that is understanding the customer. So you should be in the field. What’s their pain? What are you solving for them. And then understanding your product as a marketer makes you much better to market what the product can do to solve that pain.

40:45 – 40:59

Sophie Buonassisi: I love it, I love it, those are fantastic. Those are my two rapid fire. Now I’ve just got an overall question to finish this off. Sure. For you. What is the best piece of advice? Could be any kind of context that you have gotten and who gave it to you? Yeah.

40:59 – 41:18

Megan Eisenberg: I would say early in my career, I will go all the way back to my parents and babysitting. I remember I was going to a babysitting job and my mom said, whatever you do, be the best babysitter. I was like, what do you mean? She’s like, don’t sit there and eat in front of the TV like, sing songs, play with the kids, teach them like you.

41:18 – 41:36

Megan Eisenberg: Whatever job you take, be the best at it. And I really took that to every job I went to, whether I was a lifeguard, whether I worked at the pharmacy. I got my first job at Applied Materials. It was important that I was the best at my job, so that meant learning. Like, how do I do this job?

41:36 – 41:54

Megan Eisenberg: How do I learn this skill set? I read a lot. I just I wanted to come in and deliver. I wanted to be the person you wanted on the job. And so I think that matters more than ever today. And I look at my team and who I promote and those that like, really care, care about your craft.

41:54 – 42:20

Megan Eisenberg: I think that’s really important. You care about it and you’re you’re learning all the best practices and you’re networking and your you work hard and your your the output, the product you put out there is, is at the highest bar. I think you will be successful. And in the AI world, that means you’re going to learn how to use these tools, and you’re going to learn how to transform your function and the marketing team, and you’re going to end up leaving the marketing team because you have that sort of mindset.

42:20 – 42:25

Sophie Buonassisi: That is fantastic advice. And if anyone wants to fall on with you your journey, where can they find you?

42:25 – 42:32

Megan Eisenberg: Yeah. So I’m on LinkedIn. That’s probably the best place and happy to engage there.

42:32 – 42:35

Sophie Buonassisi: Amazing. Well Megan, thank you so much. This has been phenomenal.

42:35 – 42:36

Megan Eisenberg: Thank you for having me.