The future of AI-powered sales with Vercel COO, Jeanne DeWitt

Summary

Lenny’s Podcast: Product | Career | Growth

Episode: The Future of AI-Powered Sales with Vercel COO, Jeanne DeWitt
Date: November 30, 2025
Host: Lenny Rachitsky
Guest: Jeanne DeWitt Grosser, COO at Vercel

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Episode Overview

This episode dives deep into the rapidly shifting world of AI-powered sales and go-to-market (GTM) strategy with Jeanne DeWitt Grosser, COO at Vercel and former Chief Product Officer at Stripe. Jeanne shares her experiences building world-class GTM teams, the emergence and impact of AI and the new "GTM engineer" role, actionable sales tactics, insights into segmentation, pricing, and what it takes to build sales organizations that partner effectively with engineering and product teams.

Jeanne offers concrete frameworks, stories from Stripe and Vercel, and a future-facing look at how AI is transforming every stage of the customer journey—from lead qualification to deal closing. This episode is an expert's guide for anyone building, leading, or evolving a modern sales organization.

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Key Discussion Points & Insights

1. The Evolving Definition of Go-to-Market

Timestamps: [05:50]–[08:44]

• Traditional vs. Modern View:
  GTM used to be just marketing and sales at the “tip of the spear.” Jeanne defines it more holistically: “Any function that touches the customer or makes a dollar—marketing, sales, technical sales roles (SEs, platform architects), customer success, support, partnerships.”
• Integration Across Functions:
  "Those functions often have this Venn diagram strategy... what you're going to want to see more in this particular moment is that that become a really integrated life cycle."
• Role Specialization to Collapse:
  The 17+ hyper-specialized GTM roles will “start to collapse”—necessitating a return to orchestrating the full customer lifecycle as a cohesive journey.

2. The Emergence of the Go-to-Market Engineer

Timestamps: [11:23]–[22:32]

• Definition and Context:
  GTM Engineers blend sales process expertise, data, engineering, and now AI:
  “My GTM engineer is helping me build an agent... encode that using Vercel workflows in code that's both deterministic and less so.” ([13:33])
• From Manual to AI-Driven Outbound:
  Jeanne’s early Stripe story: building a “company universe” database to Mad Libs outbound emails, which failed without AI, but “now... works” with AI/agents at Vercel ([14:21])
• Impact:
  Automating lead qualification—inbound SDR’s work—allowed Vercel to reduce from 10 SDRs to 1 with AI agent and keep conversion rates flat while reducing time & touches ([20:37])
• SDR/AE Explained:
  Simple breakdown: “SDR is pipeline generation... Account executives are closers.” ([24:01])
• Reallocation of Human Talent:
  With AI handling rote tasks, salespeople spend “70% of their time interacting with humans,” moving up the value chain ([18:18], [20:31])
• On Whether AI Will Replace SDRs:
  “No one graduated from college to become an SDR... what we’re doing is shifting folks into something that uses more of their full capacity” ([22:32])

3. Tools and Internal AI Agents

Timestamps: [34:33]–[43:10]

• Agent-Driven Sales Intelligence:
  Vercel uses agents to analyze Gong transcripts, Slack, and emails for deal/loss insights (“Lost Bot,” “Deal Bot”), surfacing issues like missing economic buyers or objection handling ([34:33])
• Cultural & Cost Impact:
  “That deal bot... was like two days. He had it 40 hours later.”
  “Lead agent which runs full stack on Vercel will cost us about $1,000 to run for the entire year. I got that [SDR] down from ten people to one... 90+% reduction in total cost.” ([42:31])
• Build vs. Buy:
  “It’s not that hard to build these agents and they aren’t that expensive... the alpha is essentially in building your own stuff” ([43:10])
• Platform Recommendations:
  Most GTM engineers were sales engineers with coding ability: “We’re just building from the ground up here... Vercel platform is making it that easy to use our framework...” ([44:51])

4. Treating Go-to-Market as a Product

Timestamps: [46:37]–[52:30]

• Mindset Shift:
  “The experience that you have of being sold to will increasingly actually differentiate a company and drive buying decisions if products are only different at the margin.” ([46:56])
• Designing Experiences:
  Stripe’s whiteboarding as first call; customer walks away with architecture diagram and insight.
  “You need to go through from the first time you become aware the company exists to that five-year, heavily retained... customer, a set of experiences.” ([46:56])
• Add Value at Every Touchpoint:
  “Adding value at any touch point, regardless of whether or not that customer bought... Those you lose, return years later.” ([50:43])

5. Tactical Go-to-Market Advice

Timestamps: [52:38]–[57:55]

• Unique Insights Win:
  Use data to benchmark prospects vs. peers and reveal “suboptimal” choices.
• “Listen More, Talk Less” ([55:43]):
  “Excellent salespeople typically talk well under half the time in a conversation.”
• Shift from Pain to Competitive Advantage:
  “Rather than focusing on the pain... focus on how you will be better than your competitors... show the alpha you can achieve if you use [your product].” ([57:55])
• Risk Aversion Drives Buying:
  “80% of customers buy to avoid pain or reduce risk as opposed to increase upside.” ([58:27])

6. Segmentation Masterclass

Timestamps: [60:44]–[69:31]

• Frameworks:
  Move beyond “SMB / Mid-market / Enterprise”—add axes like growth potential, business model, traffic (for Vercel), and workload type.
• How to Start:
  “I sat down with our head of data science, said ‘what drives revenue? What attributes tell you this is a $100K vs. $1M customer?’” ([65:31])
• Keep It Simple:
  “Three attributes is something you can reason about.” ([68:19])
• Segmentation Is Org-Wide, Not Just Sales:
  “A lot of times folks think segmentation is a go to market thing. I really think it's a company thing.” ([68:19])

7. Building Sales Orgs That Engineers Love

Timestamps: [69:31]–[74:00]

• Sales Org Disguised as Product:
  “If you are an account executive in my org... it should take [engineers] ten minutes to figure out you aren’t a product manager.” ([69:59])
• Sales as R&D:
  “The best go to market orgs are equal parts revenue-driving and R&D... translating all that feedback into the roadmap.” ([69:59])
• Partnering, Not Just Requesting:
  “Company strategy is product strategy meets go to market strategy... constantly trying to figure out, how do I make more money more efficiently?” ([73:00])

8. Product-Led Growth (PLG) & Pricing

Timestamps: [74:00]–[79:24]

• PLG Still Relevant, But...
  “It does typically have a ceiling... People are generally not going to give a million dollars via a self-serve flow.”
  “Where companies hit walls is when they don’t add the sales portion of it soon enough.” ([74:27])
• Strategic Pricing:
  “Think about pricing like a product... sometimes you’re grossly undercharging... or defaulting to freemium without a strategy.” ([76:52])

9. Sales Comp & Hiring**

Timestamps: [79:41]–[82:22]

• Hot Take:
  “Sales comp... makes your organization less flexible because you basically have to decide 12 months in advance... what you value.” ([79:41])
• Hiring Philosophy:
  Blend traditional sales talent with consulting/banking backgrounds for analytical depth and consultative skills ([79:41])

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Notable Quotes & Memorable Moments

• On Customer Buying Motives:
  "80% of customers buy to avoid pain or reduce risk as opposed to increase upside."
  — Jeanne, [58:27]

• On Go-to-Market Experience:
  "The experience that you have of being sold to will increasingly actually differentiate a company and drive buying decisions if products are only different at the margin."
  — Jeanne, [46:56]

• On AI & SDR Efficiency:
  “We had 10 SDRs doing this inbound workflow and now we just have one that is effectively QAing the agent. The other nine we deployed on outbound.”
  — Jeanne, [20:31]

• On AI Lead Agent Cost:
  “That lead agent... will cost us about $1,000 to run for the entire year. I got that down from ten [SDRs] to one.”
  — Jeanne, [42:31]

• On Building Human-Like Sales Orgs:
  "If you are an account executive in my org, and I put you in front of 10 engineers at our company, it should take them 10 minutes to figure out you aren't a product manager."
  — Jeanne, [69:59]

• On the Role of AI in Internal Productivity:
  “You may find that it’s meaningfully easier than you think, and you get returns pretty quickly.”
  — Jeanne, [43:10]

• On Personal Philosophy (Lightning Round):
  “When the going gets tough, the tough get going... there's always a way.”
  — Jeanne, [82:54]

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Recommended Episode Timestamps

| Segment & Topic | Timestamp | |-------------------------------------------|------------------| | Go-to-Market Defined | [05:50]–[08:44] | | GTM Engineer & AI in Sales | [11:23]–[22:32] | | Tools & Agents — Internal AI Use Cases | [34:33]–[43:10] | | Go-to-Market as a Product | [46:37]–[52:30] | | Tactical Sales Advice | [52:38]–[57:55] | | Segmentation Frameworks | [60:44]–[69:31] | | Building Engineering-Friendly Sales Orgs | [69:31]–[74:00] | | PLG Realities & Pricing Strategy | [74:00]–[79:24] | | Sales Comp & Hiring Philosophy | [79:41]–[82:22] | | Lightning Round — Life Philosophy | [82:45] onward |

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Final Reflections

Jeanne DeWitt Grosser’s frameworks and stories offer a blueprint for building not just a modern sales team, but an integrated, AI-empowered GTM engine that partners with product, leverages data and AI, and delivers highly differentiated customer experiences. Listeners will leave with both actionable tactics and inspiration to reimagine how they think about go-to-market—from first outbound email to a decade-long customer journey.

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End of Summary

Transcript

[A]

I've been getting so many asks for go to market help with AI.

[B]

It's just intensified because you have 10 players pursuing the same market opportunity and so your ability to actually bring the product to market to differentiate yourself from the competition has become more strategically important than it was previously.

[A]

I had Jen Abel on the podcast recently. One of her tips is you don't want to be focusing on here's the pain and problem we're solving and instead focus on here's how you will be better than your competitors.

[B]

80% of customers buy to avoid pain or reduce risk as opposed to increase upside, which is a good thing for startup founders to understand. We all love to talk about the art of the possible, everything we're going to enable in the future. But that's often really a sale that's going to resonate with another founder, everybody else, particularly enterprises. You're avoiding the risk of not making your revenue target next quarter.

[A]

I've heard a lot about how you think about go to market as a product.

[B]

We buy a lot of things because of how we feel about them. The experience that you have of being sold to will increasingly actually differentiate a company company and drive buying decisions. If products are only different at the margin and so then you really want to create a customer buying journey that feels like very unique experiences.

[A]

Something I've heard from so many people you've worked with is that your superpower is building a sales org that doesn't feel like a sales org to engineers.

[B]

The litmus test I have always given my sales team is if you are an account executive in my org and I put you in front of 10 engineers at our company, it should take them 10 minutes to figure out you aren't a product manager.

[A]

Today my guest is Jean Grosser. Jean was Chief Product Officer at Stripe, where she built their very early sales team from the ground up. She's currently COO at Vercel where she oversees marketing, sales, customer success, revenue ops and field engineering. Gene has built world class go to market teams at multiple Unicorns and has advised dozens of companies on doing the same. In our conversation we go deep on what a world class go to market team looks like, including what the heck is go to market? The rise of the go to market engineer and how this role is already enabling her team to operate 10 times faster. A bunch of very specific tactics to level up your go to market skills. A primer on segmentation, how to think about your go to market process like a product. Her favorite go to market tools, her hot takes on PLG and Sales Comp and Sales Hiring and so much more. If you are looking to get smart on the latest and greatest in go to market thinking, this episode is for you. A huge thank you to Claire Hughes Johnson, Kate Jensen and James Diet for suggesting topics for this conversation and Kelly Schaefer for the connection. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It helps tremendously. And if you become an annual subscriber of my newsletter, you get an entire year free of a ton of incredible products including Devin lovable, replied, bolt, N8N, linear, superhuman, descript, Whisper Flow, Gamma, Perplexity, Warp, Granola, magic patterns, Raycast, JPRD, Mob in Hand, Stripe Atlas. Head on over to Lenny'sNewLetter.com and click product Pass. With that I bring you Gene Grocer. After a short word from our sponsors, this episode is brought to you by Datadog, now home to epo, the leading experimentation and feature flagging platform. Product managers at the world's best companies use Datadog, the same platform their engineers rely on every day to connect product insights to product issues like bugs, UX Friction, and business impact. It starts with product analytics where PMs can watch replays, review funnels, dive into retention and explore their growth metrics. Where other tools stop, Datadog goes even further. It helps you actually diagnose the impact of funnel drop offs and bugs and UX Friction once you know where to focus. Experiments prove what works I saw this firsthand when I was at Airbnb, where our experimentation platform was critical for analyzing what worked and where things went wrong. And the same team that built experimentation at Airbnb built epo. Datadog then lets you go beyond the numbers with Session Replay. Watch exactly how users interact with heatmaps and scroll maps to truly understand their behavior. And all of this is powered by feature flags that are tied to real time data so that you can roll out safely, target precisely and learn continuously. Datadog is more than engineering metrics. It's where great product teams learn faster, fix smarter and ship with confidence. Request a [e-mail] Lenny that's datadoghq.com Lenny this episode is brought to you by Lovable. Not only are they the fastest growing company in history, I use it regularly and I could not recommend it more highly. If you've ever had an idea for an app but didn't know where to start, Lovable is for you. Lovable lets you build working apps and websites by simply chatting with AI. Then you can customize it, add automations and deploy it to live domain. It's perfect for marketers spinning up tools, product managers prototyping new ideas, and founders launching their next business. Unlike no code tools, Lovable isn't about static pages. It builds full apps with real functionality. And it's fast. What used to take weeks, months or years you can now do over a weekend. So if you've been sitting on an idea, now is the time to bring it to life. Get started for free at lovable.dev that's lovable.dev. gene, thank you so much for being here and welcome to the podcast.

[B]

Thanks for having me. Lenny.

[A]

What I want to get out of this conversation by the end of it is to basically have this conversation be the thing that we send people when they're like I want to get better, go to market. I'm trying to figure out what to do and go to market. We send them this versus having to hire someone for a lot of money and usually they can't find amazing people because they're all snatched up.

[B]

Yes.

[A]

So let me start with just the basics. When people hear the term go to market, what does that mean? What does that encompass?

[B]

I think there are two answers to this. Often what people think of is sort of the tip of the spear of what drives revenue, which is marketing and sales. For me, I think of it as any function that is going to touch a customer or make a dollar. And actually my remit at Vercel is that. So that includes marketing, sales. All of your technical sales roles like sales engineers or post sales platform architects is what we call them at Vercel. It's customer success, it's support, it's partnerships. And the reason I say that is my experience throughout my career has been that those functions often have this Venn diagram strategy where marketing is pursuing one thing. It overlaps with what sales is pursuing, but not perfectly, which also overlaps with what support is pursuing, but not perfectly. Examples of this would be slightly different, slightly differing segmentation frameworks, etc. And so one of the things I think you're going to want to see more in this particular moment is that that become a really integrated life cycle in particular because I think we're going to see a lot of the functions of go to market get redefined. So we've gone through a period of like hyper specialization and go to market. You know, depending on how you count them. There are, you know, I think somebody quoted like 17 different roles within go to market these days and I hypothesize that a lot of those are going to start to collapse. And so if you think of go to market more holistically, I think you can kind of go back to what are the jobs to be done from making a customer prospect aware of of your product all the way through to, you know, high ltv, five years on the platform, fully wall to wall. And you're going to want to map that out and orchestrate it the way you would think about that within your own product.

[A]

Awesome. We're going to go through that whole cycle of go to market. But so is it safe to say just for most companies that that are especially starting out when they say go to market, that mostly is sales and then there's marketing as a, maybe a smaller fraction of that. And then as you become more advanced and grow, customer success plays into a tech sales, things like that.

[B]

Yeah, that's probably where most start, you know, is getting sales or frankly just because a lot of companies also start plg, you might actually start with marketing and then you're layering in sales when it's time to do the sales assisted and ultimately sales led portions. So I think it can, depending on your product and your initial target market, it can either mean marketing or sales or a combination of those two.

[A]

Awesome. So essentially it's like the term go to market tells you what we're talking about. It's how do you take your product to market, get people aware of it, using it, sticking with it.

[B]

Yep, absolutely.

[A]

What has most changed in the world of go to market over the last few years? You've done this for a long time at Google, at Stripe, you built the first sales team, now you're doing that. Vercel. What's changed most in the skill and art of go to market?

[B]

There are a number of things. So when consumption based business models started, I think you saw go to market shift into being meaningfully more consultative. Because often that first land was the very beginning of the journey and represented a very small percent of what you were ultimately going to do with that customer. And so you had to go from being transactional to a lot more relationship based. You had to more deeply understand what that customer was trying to do so you could align that ultimately to your product. I think that has played out that much more with an AI because right now everyone knows they need to change, but they don't necessarily know exactly what they need to change to, whether that's their customer facing product or their internal productivity and workflows. And so I think you're seeing a Lot more of go to market orgs leaning into the art of the possible best practices, helping you actually think things through as if they were a consultant. And so one of the things you see more of right now is forward deployed engineering, which on some level is kind of a rebrand of professional services, but kind of not. And a big part of that is, hey, how do I actually get into your environment, ride alongside you, better understand what you're trying to do, and then help you actually bring the technology to life and learn a lot along the way. Often you're not only making that customer successful, but you're then taking all of that back to your product and engineering organization to figure out, okay, what was generalizable that we ought to build into our offering versus what is something that ultimately is going to be more of a professional service in the fullness of time. So I think that has been a biggie, is actually just like really getting embedded with your customer. And then, unsurprisingly, I think bringing AI to bear on the sales process is another big one. And so you've seen the rise in probably the like 18 to 24 months of the go to market engineer, which, you know, different, different folks define slightly differently. But it, it's kind of bringing one, technical prowess to bear on go to market in general so you can have a lot better tooling, data use, et cetera. And then two, increasingly bringing AI to bear as well to rearchitect your workflows and also make it so that it's easier to have a personalized experience with customers, but do so at scale.

[A]

Amazing. Okay, let's follow the thread on this go to market engineer.

[B]

Yep.

[A]

So what was it like before and what is, what are these engineers doing at companies?

[B]

So I think maybe like an interesting story to tell. When I, when I was at Stripe, we went to launch an outbound SDR function. So outbound prospect expecting and Stripe always ran lean. The company at that time had an operating principle which was efficiency is leverage. And so if you looked at the sales organization I was running, most companies out there probably would have had 30 SDRs and I was going to get four. So, you know, there's no way I was going to do the typical sdr, you know, approach and be successful. And so we thought to ourselves, okay, what can we do? We'll be super data driven. And so we went and we started building projects. Rosalind Rosland is the scientist who originally mapped DNA. And what this was, was effectively a company universe. So you can think of this as like a Massive database. Every row was a different company on the planet and every column was an attribute about that company that would help you sell to them in a more targeted fashion. So at Stripe, an example would be like knowing that they're their business model was a marketplace was super helpful because that would mean you wanted to sell Stripe Connect versus Vanilla Payments. And so the goal was basically, hey, can we create a Mad Libs, you know, where I will come up with sort of a predefined email template, but 80% of it will be fill in the blank based on the different attributes of that. That customer. Right. So if they're this industry or this business model, then pull this customer reference, this value prop, you know, send it to this Persona, not that. And we were trying to do this in 2017 and it was very hard and didn't actually totally work. Our ability to like the false positive rate when. And we worked deeply with data science, like just. It just never really got there. And now that we're literally redoing here at Vercel as we speak, and it actually works. And that's because you can bring AI to bear on it. Um, and so what's different is we now I have a data scientist, just like I did back in 2017, but I have a Go to Market engineer, whereas before I just had someone in systems that was helping me configure outreach or sales Loft. And my Go to Market engineer is helping me build an agent. Where we're coming up with, okay, well what's the human workflow that you would have done? And then how do you encode that using Vercel workflows as an example, you know, in actual code that's both deterministic and. And less so. Where an agent's going out and trying to replicate what a human might have done to produce that. Fill in the blank. Mad Libs.

[A]

I love the ambition of that project. What is this, like eight years ago?

[B]

Yes.

[A]

It's such a. I love the big thinking there. We're going to map the entire universe of companies and then here's how we sell to them. And then just. I'm trying to picture doing that without AI. It's like crazy to imagine trying that without AI. And now it's like so much simpler.

[B]

Well, the thing that's amazing about that, just to geek out on this a second. So I was working on that with a bunch of folks at Stripe on my team, obviously, and a gentleman named Ben Salzman who went on to go to Zoom Info and then actually recently just founded a Go to market startup that is basically sort of productizing that concept of a company universe and then layering AI on it on top of it. And ultimately his view is actually AI will get to the point that you won't have to do outbound prospecting because it will just sort of company and product match. So it's fun to sort of see back in 2017, some of the folks doing that now work at OpenAI. They work at Anthropic. They also are doing GTM. Eng, you've got him starting a totally AI native GTM company and then here I am at Vercel trying to do the same.

[A]

Okay, so what's cool is this is an emerging role and emerging skill that I don't think a lot of people have recognized as something that is happening.

[B]

Yep.

[A]

So one example I'm hearing of what this role does is they automate outbound emails essentially and outbound outreach. They figure out, they write workflows and agents that figure out, here's the company to go after, here's how we message them. Does that end up being kind of like an email that's custom designed and written for this prospect?

[B]

That's one version. So it's broader than that really. Basically the full remit of GTMNG will be to go through each of the different functions within, go to market and break down all the different workflows that they do and then turn those into agents where AI is better placed than the human to do that task. So right now we started with actually inbound and are now moving to outbound because that workflow is most legible. And by legible I mean you can basically write it down. It's relatively replicable, mostly deterministic. So it's more likely that AI will do it well. And we actually built the agent and then we keep a human in the loop. But from there we're starting to look at outbound. And with an outbound, we're starting more at the lower end of the market where you tend to, you know, have slightly, slightly less customization because there's a single decision maker at the company. But I think it'll take a while before we're able to really do that in a very large enterprise. There we might use an agent for research, but maybe not all the way to actually send a message. And that's just within the prospecting function. So other places that we're looking at this would be for install based sales. So again, there it's a little bit more deterministic because you've got awesome internal Data on what a customer is and isn't using, what's the next best action, what's the thing they should get most value from? So that's where we're starting to map, hey, what does that ideal workflow look like? But basically you want to get to a state where as long as I've been in sales, they release these annual reports that help us all benchmark ourselves relative to one another. And one of the stats is what percent of time do your sellers actually spend in front of customers? And you know, for the 20 years I've been in sales, it's always been somewhere around 30 to 40%. So the minority of time is actually talking to us other humans. And I think we're getting to a point where with layering in agents, ideally we finally get salespeople to a point where they're actually spending 70% of their time interacting with humans. And we can get the research, the follow up, the things that are a little bit more, you know, rote and don't use the entirety of your human capacity done by an agent and then sort of unleash you to go deeper with your customers.

[A]

I love that this is such a great example of where AI is contributing in a very meaningful high ROI way, taking on all this work that people that you have to hire, say 50 SDRs as you described to do, and now you could do with a lot more. So it's a really cool example of leverage that AI gives you. One thing that I know a lot of people think about when they hear this is, okay, I'm going to get more of these really bad emails trying to pitch me on stuff and just like, this isn't going to work, I can tell this is AI. What have you learned about how to do this where people actually receive emails that actually convert and do?

[B]

Well, our processes all always have human in the loop. And so basically where we'll start is we take a go to market engineer and we have them shadow the highest performing individual in that function. And so you can go and you shadow an SDR and you can see, oh wow, they've got seven tabs open, they're looking up the person on LinkedIn, they're reading about the company doing ChatGPT on this or you know, looking in this database to get these sets of attributes. And so that's how you sort of inform the initial work workflow. And then what we do is we let the agent make a call. So in the specific example with, with inbound, right, you have to determine whether or not you think the lead is likely to be qualified and then you have to determine what to say to it. And so we'll let the agent make those two calls. It ultimately then does some deep research, pulls in a bunch of information from our databases and crafts a response. But we have a human review all of those and actually hit send. Now, for us, we had 10 SDRs doing this inbound workflow and now we just have one that is effectively qaing the agent. The other nine we deployed on outbound. So we got to move them up the value chain. At some point I think we'll get to a place where we feel like, hey, you know, the human reviewer is saying, yes, enough of the time that we feel confident that these will be on brand targeted, et cetera. But right now we're still trying to train the agent and it, you know, it incorporates feedback on what we choose to reject, edit, et cetera.

[A]

And you shared that. It's already having a lot of impact. Like you said you had. You said 10 SDRs and now one can do the job of 10.

[B]

Yes.

[A]

Wow.

[B]

Yeah. And we. So before we did that move, I mean, the other thing that's just incredible about this is the person who built the lead agent was a single GTM engineer. He spent maybe 25, 30% on his time of his time on this. It was six weeks before we felt confident going from 10 to 1. So it wasn't like this was a multi quarter process. It actually moved super quickly. So. And then again now we just sort of keep that agent manager sort of working with the agent to get it to a point where we say, hey, we're ready to roll. And actually throughout the process we also tracked all of the KPIs that you typically would hold an SDR accountable to. So we were looking at our lead to opportunity conversion rate. We're looking at the number of touches it takes, the time to convert. And basically what we were able to do is hold that lead to opportunity conversion rate flat. So the agent is as good as our humans were, but it's actually condensed the number of touches it takes to convert because it's so much quicker at responding relative to leads inevitably sitting in the queue or coming in at nighttime and no one can get to it, that type of deal. So that's sort of when we knew it was ready to pull nine people off and shift them into outbound.

[A]

That's incredible. Okay, that's interesting. So you shift them to outbound. What I love about this is this SDR that is now doing. This is as you said doing the things they enjoy more. They're talking to customers more. They're not doing all this kind of top of funnel rote work.

[B]

Yep.

[A]

I don't want to get into whole like jobs AI discussion, but there's always been this talk about AI SDRs, basically replacing SDRs. It feels like that's one thing where everyone's like, this is 100% going to be AI in the future. What I'm hearing here is it gives one a steer, a lot more leverage and obviously you still need people running the show. Tate thoughts there. Just like, do you think AI will replace all this at some point? And then I don't know, you don't need salespeople.

[B]

I think on prospecting it can replace a fair amount because the average SDR wasn't doing overly sophisticated research in the first place. So where I, I think the last part to go, as I mentioned, will be in deep enterprise prospecting where you know, you can be at multiple layers in an org chart. You've got to pick between business lines, you got to triangulate those. But I do think for the things that are more repetitive, that often don't take that much time to learn and get ramped, AI will be good at that. And in my view, no one graduated from college and was like, yes, I just went to college for four years to become an sdr. It was more, okay, that's where you are forced to start. But I think the average SDR could have gone straight into outbound or straight into an S and P closing role. And so basically what we're just doing is shifting folks into something that uses more of their full capacity right out of the gates rather than sort of the, you know, the forcing function of working your way up the totem pole.

[A]

Awesome. Since a lot of people listening to this aren't. Salespeople don't have a lot of background in sales. We've used this term sdr. There's also the term ae. Can you just help people understand what is an sdr, what do they do? What's an ae and then what's kind of the role above?

[B]

Sure. So SDR is typically in charge of generating pipeline. So they're meant to talk to prospective customers and get them to a point where it is worth investing time to run them through a sales process. So you typically have two types of an sdr. You have an inbound one. So this is where people come to your website, they fill out contact sales. They'll be the first call to make sure that it's Actually worth a more expensive account executive to go and run a sales process. Or you then have outbound. So this is where when you want to grow faster than your inbound demand, they will go out. And at this point you probably have a point of view on where you think you have product market fit. And so they will target that part of the market and try to drum up interest from folks who weren't otherwise raising their hand saying I'd like to talk to you. So that's sales development basically pipeline generation. Account executives are closers. So it's their job to take somebody from okay, hey, I'm interested in learning about your solution. I have a legitimate problem. I potentially could make a decision to I now believe that your product is the best in the market for me and I'm willing to pay for it. And then account executives, depending on the segments that your company sells into, eg, small business, mid market enterprise, et cetera, they may work their way up the food chain from selling to a smaller company like an SMB or a startup. Those tend to be a little bit more of a transactional sale. You often have a single decision maker to then going into a mid market or commercial role where now maybe you have an economic buyer like somebody in finance and a technical buyer like somebody in engineering to getting into enterprise where you know, you now have procurement and you have committees and 10 people have to weigh in and you know, you've got to help them figure out how to de risk the fact that they're probably migrating from something so much more complicated coordination effort to sell.

[A]

That was extremely helpful. So SDR pipeline, generation AE closer. Such a simple way of thinking about it. Okay, this is great. Going back to the GDM engineer. A few questions for people that may want to try this at their company. What scale do you think it makes sense to start hiring for this role? Having someone automate the go to market process.

[B]

What's interesting about this is it will force companies to be more rigorous about their sales process early. So often startups, when they go from founder led sales to say I'm going to have my first salesperson, whether that's an actual, you know, account executive who has prior sales experience or your general athlete, wicked smart, who's going to go figure it out. You know, often founders will just say okay, sales is showing up and talking to people isn't, you know, isn't that what I just did for the last couple years? But actually sales is, is more than that. It's a skill. Just like writing code is a skill or Building a financial model is a skill. It's about discovery. So asking all the right questions that help you identify challenges and pain, willingness to pay, you know, et cetera, and then going through a process to handle those objections and showcase, you know, where you add enough value such that somebody ultimately wants to hand over some money. So often, you know, startups will get particularly ones with strong product market fit to pretty significant scale without really having a replicable process. And you can't really apply go to market engineering unless you actually have a point of view on what best practice should look like. And so I think basically this is going to force folks to have more of a playbook out of the gates. What's working, what's not, can I document it? Do I have content for the different parts of the sales process? And then, you know, once you do that, which, you know, maybe 10 people is a good size and scale for that. Ostensibly, you know, a GTM engineer can come in and turn that into an agent. You could also argue that if you know, you're a founder who wants to bring in a general athlete profile and that person is technically minded, that you could have a hybrid AE GTM engineer who figures out what their best practice is and then tries to turn that into an agent, you know, that's riding alongside them and making them more effective as well. So, you know, I, I don't know that I have a point of view yet on what's the optimal size and scale, but I've forever have given founders the advice that it's, you often want to bring in revenue operations, which is basically the analytical arm of sales, earlier than you think. Because having data, having process is actually what gives you insights as a founder into what is and isn't working. And so I would argue, just like it's a good idea to have that sooner than later, increasingly it'll probably be a good idea to have GTM engine and be looking to bring agents to bear on your process at the outset.

[A]

While we're on this topic, just a quick tangent. The advice for hiring your first salesperson that I usually hear is wait until you're around a million in ARR. When you have a repeatable process, you can teach someone any, anything there is that. Does that seem right? What would you, what would you recommend?

[B]

Yeah, I think that seems about right. I do think as a founder you want to stay deeply connected to customers and get it to a scale and get it to a point where, you know, you use the word, there's some repeatability there. I think that's One of the things that not all founders get right is founders are incredible salespeople, right? They convinced a VC angel investors to fork over a bunch of money. So clearly they're going to inspire people to buy. But if you're getting to a million in ARR and the set of customers you have look nothing like one another, you still have very much like an evangelist sale, very much founder led sale versus if you can say, hey, I now have an ICP here or ideal customer profile, eg, something you can write down. You know, we are good. Our product fits with startups with less than 100 employees who are typically building SaaS applications, right? Something like that. Then you're probably ready to hand over the reins. And then what founders have to remember is to actually hand over the reins. So you know, you got to enable the person who comes in. What is it that you know you're doing effectively? What's your content? What are the discovery questions you're asking? How are you handling objections? So you can transition that knowledge but also don't hand them over entirely. Right? You want to stay connected to the customer because you still have a fair amount of R and D to do to figure out where are you, you know, where is the product next going to resonate? Where are you getting, you know, stock as you scale, et cetera, to close.

[A]

The loop on the go to market engineer. What's the profile of the ideal go to market engineer? Maybe your first.

[B]

What we have found works really well is somebody who does have go to market experience. So at Vercel, our first three go to market engineers were actually sales engineers. So Vercel hires very technical sales engineers. All of them were front end developers before they decided they wanted to get into sales. And so we just said, hey three of you, congrats, you're now founding members of our GTM Eng team. And the thing that works well there is, you know, you do understand aspects of what is good gtm. What does a process look like? It's been really interesting actually. So the gentleman who runs GTM Eng for me, we were going through, you know, this, this lead agent and qaing it and you know, so I'm going and I'm looking at some of the responses that we've ultimately had had lead agent send and realized, oh, I wouldn't have sent that. And that's because I have 20 years of sales experience. And we modeled the lead agent off, you know, our best person, but our best person who has two years of experience, sales experience. So it actually is important to understand the art and the science of sales and how you bring best practice to bear. So either you've done it and so you know, some best practice or you're going to geek out on sales, read a bunch of books, learn a thing or two, you know, and try to incorporate some of those into, into your agent development.

[A]

That is really interesting. So come from the sales side, not from the engineering side. And I imagine this is such a cool opportunity for salespeople to do something completely different and move closer to engineering.

[B]

Yeah, I mean we're having a lot of fun with it. At Vercel in particular, we basically get to be customer zero. So everything that we're building with agents, we're building on Vercel's AI cloud. So you know, these agents are now have multiple steps that they go through. So we're using Vercel's workflow SDK and Workflow offering. We, you know, use the AI gateway to call the different models that we use to do deep research or other enrichment that we do. So for us it's, it's great because we basically sort of bang on everything the engineering team is building and get to go be a discerning customer before we actually get it out the door to real customers.

[A]

What a fun time to be alive. I could tell the fun that you guys are having. Just the way you describe it. Stripe handles the massive scale and complexity of many of the world's fastest growing enterprises, including 78% of the Forbes AI 50 and more than half of the Fortune 100. Enterprises like Atlassian, Figma and Urban Outfitters use Stripe to create fully branded and customized checkout pages with access to more than 125 global payment methods. There's a reason I've had more leaders from Stripe on this podcast than any other company. They know how to build great products that scale and that people love. And Stripe is a lot more than payments. They've also got a category leading billing solution and a highly optimized checkout experience built specifically to increase your checkout conversion. Join the ranks of industry leaders like Salesforce, OpenAI and Pepsi that are using Stripe to grow faster and to grow the world's gdp. Learn how Stripe can help your business business [e-mail] zooming out a little bit in terms of you mentioned tools, some tools that you use. I'm curious just what are kind of the state of the art tools within the go to market stack that you love, that you'd recommend?

[B]

Well, so I'm gonna have an interesting answer to this so I'll give you one. And it's not state of the art per se, although I don't, don't mean that disparagingly. It's just that it's been around for, for a while now and, and a lot of folks use it. But I think GONG has gotten just meaningfully more interesting in the last year. And then second half my question I will get into. I think the calculus on build versus Buy is changing, so. All right, GONG GONG is incredible because you can run agents against it now. So we take all of our GONG transcripts and we dump them into an agent called the Deal bottom. And that deal bot then can do a bunch of things. So the first thing we had it do was lost opportunity review. So we had just finished Q2. We had, you know, a list of our top losses for the quarter sorted by deal size and we ran it against that and it was incredibly interesting. So the biggest loss that quarter according to the account executive was lost on price. And when you ran the agent over every Slack interaction, every email, every GONG call, it said actually you lost because you never really got in touch with the economic buyer. And when you talked to somebody about ROI and total cost of ownership, it was clear from their reaction that they didn't really buy your math. And so really the reason we lost was an inability to demonstrate value, which, you know, upon reflection, I've got work to do to build out how we quantify the value of Vercel, which actually is very easily quantifiable. It's one of the things I love about selling this product, but we gotta codify that for the Go to Market team. So that was incredibly interesting. And now we run it against all of our lost opportunities and actually do a much better job of categorizing why it was we really, really lost and then either feeding that back into the engineering team or back into marketing Sales leaders on, hey, where are we falling short in the sales process? And so that was awesome. But then we're like, well, it's not very fun to lose, so why don't we pull that forward? And so we went from lost bot to deal bot and now the deal bot is running in real time and we basically feed insights into Slack. Vercel is incredibly heavy users of Slack. So we have a channel for every single customer, either opportunity or existing one. And so now we're feeding insights into that Slack channel, which is, you know, hey, you're this far into the sales process and you haven't talked to an economic buyer. You should think about that. Or hey, you just got off that call. An economic buyer didn't sound like it went that, that, that. Well, you know, here's some things to consider and how you might follow up and last thing before I pause the other thing that's really interesting and how we're, we're using this too is, is you know we are in this moment right where like I, I have never seen an iteration velocity like exists now in my career, my 20 plus year career has all been in tech. And so for go to market teams that's really hard. If you are launching something every other day, the ability to be enabled on that is actually quite challenging. And so this bot agent is now also letting us. Where we're starting to go with it is we'll release something, we'll do our best to enable the team, then we'll go run the agent across calls, interactions and we'll diagnose where we did a bad job of objection handling where we're getting stuck and then at the end of the week we can have a huddle and say okay, what are all the places that our agent would suggest we aren't selling effectively? And then almost like an engineering team will now run sprints which is like those are just bugs. They're bugs in your go to market process so you should not have them. And you know, by the next week we're going to add content to our objection handling to guide. We're going to add content to a discovery guide, we're going to figure out something we need to change about our demo, so on and so forth. So that's early, that's a little bit of a preview but, but that's where we're talking about taking things right now within our go to market Org.

[A]

Jean, you're blowing my mind in so many ways. This just sounds so fun and just like you guys are going to win is what I'm feeling when I hear all this incredible. What I love about this is this AI tool, this agent you built sees things that humans were not seeing. The fact that you were surprised of just like this is a completely different conclusion is such a big deal. This is the whole promise of the AI. It's going to do things we aren't even thinking about or capable of.

[B]

It is we had a really interesting one of the things we're doing at Vercelso. You know we have an AI cloud so people use that to put AI native features into their customer facing applications, but they're also using it to build internal applications to improve productivity or outcomes and we are talking to a very large airline and that airline obviously gets tons and tons of support queries. So of course they would want to go apply AI to, hey, how can we have AI answer these so that our cost to support goes down? Sort of the obvious thing. But the more interesting conversation was actually with one of the C level executives who said we also actually transcribe every single one of those support calls. And so what I really want to know is why are they calling and how do I make it so that fewer people call the next week? And so again, this is now with AI, you can rapidly go through all of that content and actually be able to much more quickly than having a human in your CRM, sort of pick some status why it was that folks were calling the airline this week and what, if anything, you can do to make it less the case next week.

[A]

I imagine many people hearing this are like, I need one of these deal bots and loss bots. These are all internal products that you all built.

[B]

Yes.

[A]

Is there anything that you've learned about making them this good? Any tips you can share? Here's how to make a really good bot for sales.

[B]

Yes. So actually that's the second half of my answer that I forgot to forgot, which is sort of like build versus buy calculus. So I think one of our learnings is that it's not that hard to build these agents and they aren't that expensive either. So you know, I mentioned the lead agent that was a six week process with one human a third of his time. That deal bot, the lost bot version was like two days. Like basically we riffed on it, he had it 40 hours later. You know, now we're continuing to refine it for, for the other things I mentioned. And, and what's also interesting about them is they this, you know, for better or for worse for Vercel, but that, that lead agent which runs full stack on Vercel will cost us about $1,000 to run for the entire year. So if you remember I told you we had 10 people in the SDR function. So I'm, I'm paying well over a million dollars for that from a salary perspective. I got that down to one. And then behind that I have a lead agent that costs a thousand bucks. So that's like a, you know, 90 plus percent reduction in total cost there. So. And you know, there are a lot, there's lots of software for agents out there right now. And I think one of the things we're learning is because this whole space is so nascent often your own esoteric context, you know, your content, your workflow is really key to unlocking the power of the agent. And so I think there's real value in experimenting with your own internal agent development. We may ultimately end up on, you know, better integrated agent platforms in the fullness of time, or we may find that the CIO increasingly goes from a procurer of software to a builder of software and you'll have an AI AI internal platform with a thousand agents running across your org. I'm not really sure yet, but I certainly think there's value in trying it yourself because you may find that it's meaningfully easier than you think and you get returns pretty quickly.

[A]

So what I'm hearing here is that you're finding that there are not tools out there to plug and play. The alpha is essentially in building your own stuff.

[B]

I think that's partially true. And I think because you also have all these tools proliferating right now, you get into the perennial problem where you wind up with 20 of them to do, you know, the 20 jobs to be done, basically, rather than an integrated platform that's doing all of them. I'm hearing this a lot, actually, when I'm talking to customers right now, where their biggest issue in deploying AI is actually just getting through procurement. And it's sort of because everyone's got an AI mandate, you kind of have a blank check. I recently heard the term of, instead of ARR, it's err, which is experimental run rate revenue, which is to say, you know, everyone's out there sort of, hey, we're going to give this thing a go for a year and then TBD on whether or not we keep it. But, you know, basically you're having to procure 20 different things because most things are getting off the ground. And so, you know, they're solving something relative narrow. And that'll change in the fullness of time. But I do think there's an opportunity to figure out, hey, where do I likely have a more specific workflow, you know, internally? For that, it might be well worth building your own agent. And then maybe for the things that are a little bit more generalizable, you go get something off the shelf.

[A]

Are there any platforms or tools you want to shout out that allow you to build these agents so quickly? I know they sit on Vercel, so shout out Vercell. But just anything that you point people to. Like, are these sdr, these GTM engineers, they're former salespeople, Are they learning to code? Are they by coding these agents. How does that work?

[B]

Well, the. So our sales engineers all have CS degrees, so they, they were engineers in a sales capacity. So they're writing code. And actually these agents, they're building directly on Vercel. So you get the AI gateway that lets you, you know, call different models. You have a sandbox if you're running untrusted code. You've got workflows that let you build the process. You've got fluid compute, which lets you really efficiently use compute when you only need it. So we're just sort of building it from the ground up here because again, it's not that hard. Now you do need to write code for that. Certainly there are a lot of vibe coding tools out there that also give you more kind of workflow builders that are somewhere between fully wysiwyg, almost like drag and drop and a little bit more. More code forward. So you've got a bunch out there along those lines. But you know, I, I do think we've sort of found like one of, one of the reasons actually the GTM Eng team at Vercel can build these agents so easily is because the Vercel platform is making it that easy to use our framework to find infrastructure and get that agent onto, into production very rapidly.

[A]

What a neat, unfair advantage you all have to do this.

[B]

Yes, it is, it is fun to like. I mean, I do think this company is better than any I've seen at eating its own dog food. And just everyone is constantly, we say Vercel builds Vercel with Vercel. So you're just always looking for ways to hey, how can we use our product to go do what we need to do and as a result either understand then what a customer would want or what's missing from our product that we could go make better.

[A]

Along these lines, something that's already come across a lot in the way that you describe this stuff is I've heard a lot about how you think about go to market as a product. A lot of people listening to this, as I've said, are product builders. So I think this is a really nice way of thinking about go to market. I'm guessing you've already talked about elements of this, but just what's a way to think about go to market as a product?

[B]

Yeah, I've always. So I had this realization probably a little over a decade ago in my career. So my first job out of college was working on Gmail in 2004. So Gmail launched on April 1st. I joined on June 1st. And as I'm sure you'll remember as well, Gmail was this incredible innovation, massive JavaScript application that didn't really exist at the time and it had this gig of storage. It was a full year before Yahoo Mail caught up and even longer before Hotmail and others did. Right. So that was the level of technical differentiation between, you know, Gmail and the next best. And a decade later I, you know, you had cloud computing enabling folks to do stuff that you never would have been able to do previously. And so I kind of felt like, huh, like software is starting to commoditize a little bit. And so, you know, when, when that happens, when technical differentiation kind of narrows, what are other things that will differentiate you? And you know, sort of thinking outside of tech, like we buy a lot of things because of how we feel about them. And so I started to develop this thesis that actually the experience that you have of being sold to will increasingly actually differentiate a company and drive buying decisions if products are only different at the margin. And so if you believe that, then you really want to create a customer buying journey that feels like very unique experiences. And so we did a lot of this at Stripe and now we're looking to replicate this here. But an example of one of the things I think we did really nicely at Stripe was, you know, a lot of companies, sales, sort of the first call after you're qualified, you know, we've decided you're worth engaging in sales processes, discovery, which is basically, let me ask you a lot of questions to try to under uncover pain, figure out where buying power lies, et cetera. And so that is kind of boring sometimes for a customer. You're basically being quizzed often on the phone. And so what we started to do at Stripe was that first session was a whiteboarding session and we would actually get together and have you draw your architecture for payments and all the other things that were under the hood to enable you to take money and drive customer outcomes. And through that we would learn a ton about, you know, what was in your stack, what we were going to have to compete with displace where value lied. But the customer also learned a lot themselves because in many cases they'd never drawn their architecture diagram. And so they left that meeting with an asset and a sense of like, wow, this is a really collaborative person who's like deeply interested in helping me like, you know, develop a mental model for how to think about this, you know. And then we had other things that we, we would do. So that's sort of how I think about building go to market like a product is basically you need to go through from the first time you become aware that the company exists to again, that sort of five year, heavily retained, wall to wall customer, a set of experiences. And those experiences can feel transactional, flat, boring, or they can feel very human, personalized and unique. And so we try to go map those out and figure out how do you bring the product to bear, make it really human and hopefully that creates a customer for life in the end.

[A]

I love that whiteboarding example. Are there any other examples of what you've done to make it actually work really well in this way?

[B]

Yeah. Another principle, we really developed this at Stripe two and I brought it to Vercel was just the idea of adding value at any touch point, regardless of whether or not that customer bought. Because even if customers don't buy, you often find that if you miss them on that buying cycle, three or four years later when they're in another buying cycle, they do come back. You know, I was at Stripe for nine years and so I saw the number of customers that we lost and then half a decade later, here they are and they bought. So that, that was sort of another one. So, you know, examples of this that we're doing at Vercel is we, you can. There's great data on the Internet that helps people understand the performance of their website and how fast your website is actually impacts SEO. And SEO impacts aeo. And everybody's thinking about AEO right now. And so, you know, one of the things we try to do when we reach out is actually folks insight immediately into how they're performing on an absolute basis, how they're performing relative to peers. So ideally, you know, that piques your interest and you want to learn more from us, but even if it doesn't, you still have insights that you may or may not have been aware of that maybe make you contemplate whether or not you've got the optimal setup.

[A]

Awesome. So what I'm hearing here is when you say think of it like a product, it's basically a product. Person thinks about the experience of their product at every step of the journey. Here's the flow. Step 1, 2, 3, 4, 5. How do we make every step awesome? Keep them going along that journey. And so what you think about is just from the prospect's perspective, how do we make every step of that journey awesome. Continue them down that journey.

[B]

Yeah, yeah. How do you make it be an experience rather than a transaction versus just.

[A]

Like feel like sales coming at you, trying to sell you Stuff.

[B]

Yeah.

[A]

Okay. Staying along this track of being, staying tactical, I want to go even further there. So what are just some go to market tactics that you find really effective these days for people trying to just to be more successful in getting people to pay attention to their stuff, to buy their stuff?

[B]

I mean one I would sort of say dovetails with where I just ended but is what are the unique insights that you can bring to bear about your product or you know, how that that that customer may be in a suboptimal state. So I do think investing in data to tease that out is one thing. I think the other thing, this is straightforward but often not done enough is a lot of good companies invest in docs, good thing to do, but they stop there. And particularly if you're selling into a slightly larger company doing things like, you know, AWS calls it, well architected guides or blueprints. A lot of customers, particularly larger ones, really want to know the best practice for how exactly to implement your product in with their particular setup. A great example of this, this is from Stripe was, you know, Stripe was excellent at marketplaces. Most, you know, Lyft, Instacart, Doordash, they were all on Stripe. And so Stripe definitely knew the best way to set up payments for a marketplace because we'd seen them all. And so when you then would go and sell a marketplace and you know, say oh yeah, we've got docs, go check them out. They didn't like that, right? Because they're like, hey, every marketplace runs on Stripe. I don't want to look at generic docs. I want you to tell me what's the best way to set up payments for a marketplace. And so I think that's another key thing to be doing, particularly as you move past that sort of solo developer, startup, founder as potentially a target audience. And then I don't know this is a tactic per se, but I do think just a good reminder for founders in particular who are still in that maybe founder led sales moment is just the value of really good discovery. I often find founders are so in, you know, so excited about talking about their product or you know, you ask one question and now they've got a hook of like oh, I can fix that for you. But excellent salespeople typically will talk well under half the time in a conversation because they're out asking questions, probing, often helping a customer arrive at conclusions on their own. And so learning how to, you know, do five whys go deep rather than immediately going into problem solving mode. You know, if they ask A question, you respond often if they ask a question, you should ask a question about the question and then respond. Right. So learning to be great at that, I, I think differentiates people.

[A]

So the last tip, I think there's something a lot of I bet everyone could learn is just listen more and talk less.

[B]

Yep.

[A]

On that first piece of advice, this kind of sharing unique insights and how you're suboptimal, is there an example you could share of how you did that? Maybe a story of just how you convince someone you're selling Stripe or Vercel? Like here, something you're missing. Here's how this could help you become much better.

[B]

So with Vercel, the sort of giving an example, but I'll make it more specific so you know, the performance point. You can go and look at core web vitals and so we can actually see the different things within their site that are fast or, you know, load correctly, et cetera. So at that we then. So anyone can go look that up. But what we can do is actually then help with benchmarking relative to peers. So that's been a big one that we've gone out and done. The other one that we've spent some good time on is just around helping customers understand MCP servers and when it would make sense to use one. So I think, you know, those are all the rage, but often people don't know how to contemplate them within their own product. So that was another one that we've gone pretty deep on. And then related to the first one is AEO answer. Engine optimization is actually, you know, somewhat tangential to Vercel. Right. So we drive performance, performance drives SEO. SEO is an input into aeo. But we have spent a ton of time sharing insights on AEO because we ourselves focus deeply on it and think we understand it better than many. And so again, as part of just building a trusted relationship, you know, folks may go from those AMAs or that content into, okay, great, you learned, you taught me a lot. And therefore I want Vercel to help me with performance. But in many cases, they actually now are just like, this is a company that seems insightful. It seems like one I can learn from. And now I'm going to pay a little bit more attention to them. And over the fullness of time, maybe, you know, they see something that triggers them to decide, now's the time. I want to go investigate that aspect of Vercel.

[A]

Awesome. So what I'm hearing here, in many ways, and this resonates, I had Jenna Abel on the podcast recently and it was all about sales skills and how to sell. And one of her tips is you don't want to be focusing on here's the pain and problem we're solving and instead focus on here's how you will be better than your competitors. Here's a big gap and alpha that you can achieve if you use, say, Vercel. So here's like you, you're missing out on speed and you're gonna get screwed in AO and all these things. Here's like how you can architect your entire payments art system to be top tier. Does that resonate?

[B]

Yeah, it. There's I, I was told this stat, it's round numbers. So I, I can't imagine it's entirely accurate. But you know, basically that customers, 80% of customers buy to avoid pain or reduce risk as opposed to the other one out of five to increase upside, which is a good thing again for startup founders to understand. So, you know, we all love to talk about the art of the possible. You know, everything we're going to enable in the future. It's very exciting. Everyone's visionaries, right? But that's often really a sale that's going to resonate with another founder. And for everybody else, you know, particularly enterprises, you're avoiding the risk of not making your revenue target next quarter, the risk of having, you know, being outdone by the competition, the risk of having brand damage, et cetera. And so it's really hard actually for many startups to make that pivot because it, it feels off. Off brand, but it does actually drive more buying behavior. Is setting up a little bit of that concern that either I might not be well positioned or again through good question asking, I know exactly where I'm not well positioned and you can help me de risk that.

[A]

That is such an important stat you shared. This has come up actually before in this podcast that buying people are buying in large part to reduce risk to basically not hurt themselves in their career, not hurt the company. Like that's a bigger factor in the buying decision. Then I have this problem I need to solve and. Okay, thank you. This solving and the way April Dunford came in the podcast and talking about this of just like, like it's such a massive career bet. We are going to bring in product X and it's going to become like stripe, let's say, let's not talk about Vercel, but let's say stripe. We're going to adopt stripe. That's like a huge decision. If it doesn't go well, your career is hurt, your manager is going to be mad at you, it's going to set your company back.

[B]

Yeah.

[A]

So a lot of the buying decision, as you've said, is I just don't want to screw this up.

[B]

Right, Absolutely.

[A]

Okay. Along the line of tactics, something that I know you're a big fan of and help people think about is segmentation.

[B]

Yes.

[A]

This is something a lot of founders struggle with. They know, okay, I need to figure out my segmentation strategy. And here we're going after. Can you just kind of give us a primer on segmentation, what people should know about why this is important and how they might approach this?

[B]

Yeah. So segmentation is basically how do you carve up the world of companies that exist on the planet to reason about them where they buy differently? So I'll give, I'll give examples from, from Stripe and Vercel to bring this home. So a very, very typical company segmentation is small, medium, large. That's a rational way to do things. Small, you often have a single decision maker, medium, you know, a small team and large, it's complex as a committee, et cetera. So the buying process does change across SMB, mid market enterprise. But if you stop there, you are likely missing. Okay, but what are the things within your offering that also change the way something gets sold? So at Stripe, there were two ways we further cut the business way. One was so think of segmentation as a graph. So X axis was size. So small medium large, Y axis was growth potential. And that was important for stripe because it was a consumption based business. So if you were going to grow at 200% year on year, you were more valuable to stripe than if you were going to grow at 8% year on year. And so we wanted to spend more time, spend more money going after the 200% rowers than the 8%. So that was one that informed your strategy on who you targeted. And then for stripe, the other thing that we cut it was business model. So are you A, B2B? Are you B2C? Are you B2B2B eg a platform or B2B2C eg marketplace. And why is that relevant? Well, if you're B2B, you were going to need business payments, right? Credit card was useful for a PLG function, PLG sale, but you were going to need ach, wires, et cetera. And you probably had a recurring business, so you were going to want stripe billing. You know, if you were B2C, that's consumer, so you're going to want consumer Payments, Apple pay is super important. If you were in the like the platform or the marketplace you were going to buy our Connect product. So it helped us basically then craft a more targeted and replicable sales Vercel sort of similar deal. So small, medium, large buying complexity. We also do the same thing on growth potential because we are similarly a consumption based business. But for us a couple other things on the X axis we layer in promote which is one of the things that is observable is traffic site traffic on the Internet. So Google publishes a crux X score which is basically they have a bunch of data in Chrome and so they know that Lenny's site gets you know, a million X the amount that Gene's site does. And so basically if you're a small company but you have super high traffic that's going to be more complex. Vercel is going to make more money and so we want to promote you. So great example of this would be OpenAI. OpenAI. I forget these days how many employees it has. Let's, let's say it's 3,000. It's probably more than that at this point but so that's going to put it in the mid market at most companies. But they are a top 25 traffic site on the Internet. So for us that's going to push them in our enterprise because we need to go, you know, lean in with a much, you know, more in depth sales process. And then the other thing we layer on is workload type. So if you are an E commerce company that's going to be a very different sale. We're going to have to. You actually use different language. You talk about product listing pages and product description pages and you've got an order management system as the back end. Super different from a crypto company where you know, you might be running soup to nuts on aws. And so again that helps us start to then have a really different buying content for you.

[A]

Okay, this is awesome. So essentially what you do is you break up this universe going back to your original story at Stripe into to help you sort essentially which companies are most likely to buy your product. And what you're coming up with is these attributes that are correlated with they are likely to be great potential customers.

[B]

Yep.

[A]

Do you recommend using this X Y axis as the approach versus something else? There's like a spreadsheet with like five columns. Like I don't know, how do you start?

[B]

There's probably something to be said for the X and Y. Like I do think size is going to play into most Buying decisions. And then these days there is a fair amount of, you know, consumption happening. So there'll be aspects of this that I think are somewhat universal. But I think basically like when I came to Vercel because new product market, product offering, for me it's a new market. I had a lot to learn. But this is one of the first things I did in the first 30 days. And so basically I sat down with the gentleman, abhi, who leads data science here and you know, said okay, what, what drives revenue? So what are, what are the things that you can look at ex ante about a customer to know this person's likely to pay us $100,000 versus a million. Those that's probably going to be part of a segmentation framework. And then similarly, okay, where can we, how, how, what attributes would we look at for. To cluster where we seem to be winning repeatedly? And that was how we ultimately got at okay, crux rank is going to be super important because what you pay Vercel is correlated with your traffic and then workload type was super important as well. So you know, and for, for Vercel, when we did that it was really interesting because you know, we saw, wow, like we have a lot of penetration and E commerce, not, not that surprising actually given that we, you know, drive highly performant sites and E Comm having a super fast performance site really matters. But you know, at the time, if you looked at as an example an enterprise SaaS companies, we didn't have a lot of penetration. Even though you would have thought, okay, front end cloud, very developer oriented, of course software companies would be on us. But in enterprise, most of those companies built that SaaS offering before Vercel existed. And so, you know, migrating 200 or 2 million lines of code, you know, to Vercel, that's a big lift, right? So it helped us really understand where are we winning, where are we not? You know, and now as an example, like in, within SaaS companies and enterprise, we're actually seeing a lot of interest in the AI cloud because those are some of the earlier adopters of hey, let's add AI native functionality to our existing SaaS app app. And so again it helps us figure out what to target where.

[A]

Okay, so essentially you're doing kind of this regression analysis on what's working and then here's the attributes that are most correlated with success. Something I always recommend when founders ask me for. How do I figure out my cp? How do I figure out where to focus? My heuristic is just think of three attributes. That narrow them down. So it's like series A company with that's Angela, that's the marketplace, something like that. I feel like a good just rule of thumb just to start, I think.

[B]

Like beyond three, like, you know, that's getting pretty detailed and reasonably speaking, you're not going to cut like you have five sellers. So you're what, you're going to put one seller in five different segments. So I do think three is something you can reason about. The other thing I'll say on this topic that I think is really important is a lot of times folks think segmentation is a go to market thing. I really think it's a company thing. So when you join Vercel, I actually deliver and every new hire's first week. One of our company values is kyc, know your customer. And I deliver the KYC section and you know, talk through our segmentation framework how our customer base maps into those segments. Because it's really important as you know, those new product managers leave the room that when they're building something, they think to themselves, okay, I'm building a new backend product. Who is this targeted at? Is it targeted at an enterprise or a startup? You know, basically, do I have a point of view on where I'm trying to win and why? And if you're doing that out of the gates, then it's much easier to then go speak the same language with the go to market Org and figure out, okay, how are we going to take that to market in line with the other motions that we we have in play.

[A]

Okay, this is a great segue to. There's a couple other things I want to talk about. One is something I've heard from so many people you've worked with is that you are amazing at building a go to market Org that works really well with product and engineering. So I'll read this quote from your former colleague Kate Jensen. She said that your superpower is building a sales org that doesn't feel like a sales org to engineers. So the question she suggested asks just like, what does it take to do that? What are the ingredients to building a sales org that engineers and product teams really like working with?

[B]

The litmus test I have always given my sales team is if you are an account executive in my org and I put you in front of 10 engineers at our company, it should take them 10 minutes to figure out you aren't a product manager. And what I'm trying to get across is you need to have incredible product depth. And the reason for that is twofold one, it gives you credibility with the product and engineering org. And two, I also believe that the best go to market orgs on the planet are equal parts revenue driving and R and D. And the reason I emphasize the latter is if you think about a product management organization, you know, you may have a UXR team, you know, out doing research. Product managers certainly should be out talking to customers. Well, if I have a 20 person sales team, think of the number of customers that we talk to in a week. And so if we can do an excellent job of translating all of that feedback into signal and then feeding that into the roadmap, you know, we can be actually an extension of the product management org. But that takes being really good at discerning signal from noise, understanding when something is an objection that should be overcome versus you know, a market, an opportunity in the market. So I think, I think those things have helped.

[A]

I just love this as a product manager, maybe former product manager. I don't know what the hell I am these days, please. I just love the idea of the salesperson like you not knowing the difference between a product manager and a salesperson. The most classic challenge is sales orgs ask for all these features.

[B]

Yes.

[A]

And PMs are constantly having to push back and think about does this fit into everything? So it feels like that's a big part of this is to understand that deeply.

[B]

Yeah, you want a sales, you want a sales org that can think like a general manager so you know, that's not just trying to get deals done but is trying to help build a business. And so again, knows when to say no, knows when to objection. Handle versus, knows hey, I've actually heard this on the last three calls and I do think this would be a really big unlock that would make us more competitive, you know, would be something that new that nobody's doing. So you know, I think that takes looking for a profile that both has sales skills but also is going to think with, you know, that product mindset.

[A]

I love that. Okay, so another quote from Claire Hughes Johnson, former podcast guest, amazing sales leader, worked with you at Stripe. She said something along these lines, but a little different. That Jean is probably the best go to market person at connecting with product and engineering, deeply understanding the product and providing the most valuable input to her counterparts of any I've ever seen. It sounds like just another ingredient here is just sales feeling like a real partner to product engineering. Actually not just being like, hey do these things for me, but actually feeling like a partner.

[B]

You know, ultimately company strategy is basically Product strategy meets go to market strategy. Right. And so I spend, I guess as a go to market leader, I'm constantly trying to figure out, you know, how do I make more money more efficiently. And you typically do that by having a winning product in the market that is well commercialized. And so that means that I really lean into thinking about product strategy and thinking about pricing strategy because if those two things are optimal, you're going to win more often and there'll be less friction in it. And so that's sort of where you got to put as a revenue leader like a GM hat on and not just think how do I sell but actually how do I enable the insights I'm getting from talking to customers constantly to have the company strategy be more effective.

[A]

Speaking of product going in a slightly different direction, plg product led growth. It felt like it was very hot for a while where everyone's like you gotta go plg. That's the only way to win. Now it's impossible to do sales. There's no the future's plg. It feels like that's gone away. And in large part obviously still companies grow through PLG and work through plg. What's just kind of your thoughts on PLG and when does it make sense for a company these days to actually think this is how they will grow for a while?

[B]

I think a lot PLG is, makes sense for a lot of companies at the outset unless you are very explicitly building a product for enterprise. So Sierra as an example, right. Like they are very clearly going after Global 2000 or something, something close to that. So PLG is not going to be overly useful to them because they are trying to win eight figure deals from day one. But for a lot of products, folks are targeting a startup audience at the outset and then they're adding more functionality so that they can ultimately continue to scale up market. So I think PLG is still super relevant. It's a, it's a major driver of Rosel's growth. It was a big driver of stripes growth. The thing that folks, folks get wrong is it does typically have a ceiling. So people are generally not going to, you know, go give it, give you a million dollars via a self serve flow. So at some point if you want to sustain growth rates, you're going to have to have your deal sizes get bigger and bigger. And where I think folks get stuck is waiting too long on PLG because it does take a while to build a replicable sales process and a sales process which often you're getting fed by Inbound at the beginning and then you got to add outbound. It takes a while actually to turn outbound into a predictable engine. So I think where you see companies hit walls is just when they don't add the sales portion of it soon enough.

[A]

So essentially every company ends up having to build a sales org. Some start product LED and then at sales, some just start sales and have it from the beginning. Beginning.

[B]

Yeah, I would, I would agree. There are, you know, there are probably some good examples of like large vertical SaaS, platforms that are S and B, but even they wind up with like a, you know, velocity sales team. So. Yeah, I don't, I don't know that I can think of like a hundred billion dollar company that's plt only.

[A]

Yeah, like it just feels like a big, like you're losing, you're leaving money on the table even if you are growing really fast. I know Atlassian was a long time theology company but. But eventually succumbed. I don't know if that's the right way to put it. Okay, you mentioned pricing. I know you have strong opinions on pricing and pricing strategy. What's just like a couple tips you might share with someone thinking about how to price their product.

[B]

Yeah, so I, it's kind of a theme, but I think the first thing is like you got to think about pricing like a product. So it's another one where it actually really matters how you choose to price a product. Do you really understand where customers are going to drive value? Do you really understand where you incur costs and are you doing a smart job of aligning those things? You've got lots of examples of companies grossly underpricing because you're sort of afraid to charge for the value that you actually provide. I think there are a lot of examples where people default to including a freemium strategy without that actually being a strategy. Like a good example at Stripe, we launched Stripe Billings years ago. It had a freemium strategy because that's what you do. And then we sort of looked at it and we're like, you know, actually integrating straight billing takes a little bit of work. So if you do that, you're probably going to stay. And so we killed that, that killed, that killed the free trial to zero downside. So you know, that's, that's another one. At Vercel we've been going through that transition where you know, we're a consumption based business model ultimately. But for at the outset we basically kind of bundled that into what looked like a SaaS like price and you know, as we've added a lot more functionality that, that wasn't working anymore. And so we did an unbundling and right now actually we, we did a pre substantial pricing change in, in August where we have an enterprise at a pro sku and if you looked at the enterprise sku, it's called enterprise for a reason. Enter. It's meant to be sold to an enterprise. And actually about half of the folks on enterprise SKU were startups which suggests that there's stuff in enterprise SKU that a startup really wants. So we kicked a lot of that stuff out of the enterprise SKU and made it so you could buy it self serve online. And what do you know, people are so, you know, so now that's like really driven a lot of growth in our PLG funnel which is awesome for startups because it's super efficient. They can just buy things they want that it's awesome for us because you don't have to have a human intermediate that so you know, getting all of these knobs really tuned is a key to both a great customer experience and optimal revenue outcomes.

[A]

Maybe just one more question before we get to our very exciting lightning rounds. Give you a combo question. I hear you have a hot take on kind of sales comp. How to comp salespeople that's different from other people and also who to hire when you're hiring folks in sales. Can you just talk about your takes there?

[B]

I struggle with sales comp because.

[A]

You.

[B]

Know, it's all about pay for performance which I'm obviously a fan of, but it is, it makes your organization less flexible because you basically have to decide 12 months in advance. These are things I value and particularly in this moment that could be different. As a great example of this, when we wrote the sales plans for this year at Vercel, the AI cloud did not exist. We were selling our front end cloud and we were selling V0 and introduced the AI Cloud halfway through the year. Now we had all sorts of good ways to still incentivize that but you know, I, I think you want to be able to be innovative and pivot and you know, when you have a well designed sales plan or you know, a very structured sales plan that, that can be challenging. So that's, that's a little bit of, of my hot take is just I'm trying to figure out how do you have the upside of, of sales of you know, motivates people. It's a quantitative function which is great, but also the flexibility to change your mind because I think a lot of Companies right now are having a hard time doing annual planning. So, so that's one on profiles. I have always valued what just sort of a diversified portfolio. So I, I strongly believe that sales is a skill. And so you want salespeople with, with actual sales experience in your organization. But I think there's value in pairing them with more non traditional backgrounds in particular consulting or a banking, you know, background. Those folks are really good at, you know, more quantitative and analytical aspects of sales. So getting into that consultative, you know, part which I think we talked about at the, at the outset. And so I find that when you mix these together, the sort of, you know, consultant banker profile realizes, oh, wait a minute, sales is a skill and I didn't really have it. And so they go learn from, you know, your, your account executives with that background and then your AES learn more about. Okay, how do I think about a P and L? How can I talk to a cfo? You know, how do I present a TCO analysis more effectively? And so just creates a much richer learning environment where people are bouncing ideas off each other.

[A]

That is awesome. I love that strategy. Okay, final question. Just is there anything else you wanted to share, anything else you want to leave listeners with before we get to our very exciting lightning round?

[B]

Oh, man, I feel like we've been very thorough.

[A]

I think so too.

[B]

Yeah, I'm going to. You've stumped me on that one.

[A]

Okay. That's the goal. With that gene, we reached our very exciting lightning round. I'm going to make it very quick because I know you got to run one. I'm gonna ask you just two questions.

[B]

Okay.

[A]

One is, I'm gonna skip to your life motto. Do you have a favorite life motto that you often come back to find useful in worker and life?

[B]

I do. I, I actually found that I'm known for saying a handful of things that I didn't necessarily realize it, but when you leave an organization, people tend to, you know, tell you what stuck with them. But there is one that I think I'm, I'm known for saying, growing up, my mom always said to me, when the going gets tough, the tough get going. And I, you know, in sales you're always going to have a quarter when you're not on pace. And so that's one that I feel like I pull on, not infrequently because, you know, there's, in my view, there's another, another version of this my mom also would always says was where there's a will, there's a way. So you know, I think you can always choose to find a path forward, even when that's not super clear.

[A]

I love these. Okay, last question. I read that you were a very competitive diver in college. Early on, I'm just curious if there's something you learned from that experience that you brought with you that helps you be as successful as you've become.

[B]

Well, I mean, first of all, I should say I was. I was generally coming in like third place out of three on my team. So I. I managed. Managed to, to do it in college, but that, that was the extent of that career. Um, so I do think so. Diving is a precision sport, and it is a repetitive sport. And it is also a sport where when you land flat on your back and literally as you are swimming to the side of the pool, like welts are forming on it, you always, 100% of the time will be forced to immediately get back on the diving board and do that exact same dive again. And so I think that has a lot of stuff that's transferable to work and to sales. So, you know, for me, I just have an obsession with excellence and within sales. Sales is about replicability. How do you drive predictable outcomes, you know, how excellent are you at your ability to forecast? And so I think I bring that to bear within sales a lot. And then similarly, like, you get a lot of no's in sales. And so, you know, I. Another phrase that a sales guru said to me once or in a training was, yeses are great, no's are great, maybes will kill you. And so how do you get really comfortable that no is a great thing and that just gave you data and now you can go do something, something with it.

[A]

This is a really inspiring and empowering way to end the conversation. Gene, thank you so much for being here.

[B]

Thanks so much for having me, Lenny. It was a lot of fun.

[A]

Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show@lenny's podcast.com. see you in the next episode.