Best of LinkedIn: Go-to-Market CW 44/ 45

00:00:00: This episode is provided by Thomas Allgaier and Frennis, based on the most relevant LinkedIn posts about go-to-market in calendar weeks, forty-four and forty-five.

00:00:08: Frennis is a B to B market research company helping enterprises gain the customer, competitive, and positioning insights needed to drive GTM success.

00:00:16: Welcome back to the deep dive, our mission today.

00:00:19: cut through all the noise and really zero in on the essential signals driving B to B go-to-market strategy right now.

00:00:26: We've sifted through two weeks of pretty intense discussion on LinkedIn.

00:00:30: Yeah, intense is the word.

00:00:32: And the themes, they're actually really clear that this isn't about small tweaks anymore.

00:00:36: No, definitely not.

00:00:37: We're talking about foundational stuff, systems architecture, this whole new role emerging, GTM engineering.

00:00:43: and a really critical shift away from just doing more.

00:00:46: Exactly.

00:00:47: It's about demanding better execution.

00:00:49: If you boil down all the comments from founders, operators, advisors, the core message is that sustainable growth is not just about adding headcount or the shiniest new tool anymore.

00:00:58: So what is it about then?

00:00:59: It's about structure.

00:01:00: There's this huge focus now on internal clarity, on structured execution.

00:01:06: getting your own house in order first, making the revenue engine predictable, coherent before you try and floor it.

00:01:12: Okay, let's unpack that.

00:01:14: Starting with that foundational piece, what some are calling revenue architecture, or maybe more accurately, the lack of it sometimes.

00:01:22: Right.

00:01:23: Andrew B had this great analogy, didn't he, about startups being like a band slightly out of sync.

00:01:28: Yeah,

00:01:28: exactly.

00:01:29: He said something like sixty-three percent of startups.

00:01:31: It's the same company, but you've got three different teams basically singing three different GTM songs to the customer.

00:01:37: And that creates chaos.

00:01:39: It hits trust, engagement.

00:01:40: Oh, for sure.

00:01:41: And definitely investor confidence.

00:01:42: Uh-huh.

00:01:43: And that kind of incoherence is why Anthony Cadre argued GTM needs to be treated like a... a system of intelligence, not just random campaigns fired off.

00:01:54: A

00:01:54: system, like a continuous feedback loop, integrating sales, marketing, product insights.

00:01:59: Exactly.

00:01:59: So the whole organization can learn and adapt faster than the market changes.

00:02:03: Which leaves right into this idea of upgrading the strategy itself, moving beyond just static ICPs, ideal customer profiles.

00:02:12: Yeah, Jamie Walsh had a strong point on this.

00:02:14: Obsessing over demographics alone.

00:02:17: It's kind of inefficient because it doesn't tell you why someone buys.

00:02:20: Right.

00:02:20: It's the why that matters.

00:02:22: The focus has to shift, he argued, to understanding the buying dynamics.

00:02:26: Like, what forces internal or external push that buyer towards making a change?

00:02:32: What's the trigger moment for urgency?

00:02:34: And crucially, what language are they using before they even start searching for a solution like yours?

00:02:38: Exactly.

00:02:39: And if you want to track those dynamics effectively, your operational foundation, well, it needs to be rock

00:02:44: solid.

00:02:45: Ah, the CRM conversation.

00:02:46: You knew it was coming.

00:02:47: Diana Marcela Gonzalez was pretty blunt.

00:02:49: She said we need to stop trading the CRM like some dusty old logging tool.

00:02:54: Yeah, like a data graveyard.

00:02:56: Right.

00:02:56: It needs to be seen as a strategic product.

00:02:58: Yeah.

00:02:58: Like the actual GTM operating system.

00:03:01: It's vital for predictable growth, but only if the data model is actually tracking the entire buyer journey complexity and all.

00:03:07: If you fail there.

00:03:08: You end up in what Chrissy Saunders call the GTM ops house of horrors.

00:03:13: Just silo data, sink errors.

00:03:17: Basically, making it effective execution impossible.

00:03:21: That's the nightmare scenario for sure.

00:03:23: And Dao Wester pointed out that scaling often just scales those silos, doesn't it?

00:03:27: It does, which is why fixing it isn't just about tech.

00:03:30: He argued the real fix is a shared language.

00:03:33: His

00:03:33: shared language, like the Spice D model he mentioned.

00:03:36: Situation, pain, impact.

00:03:38: Critical event, decision.

00:03:40: Yeah, he called it the blueprint.

00:03:42: And the reason SpiceD seems to be gaining traction is it forces that alignment.

00:03:46: It's not just letters, it's a common way to diagnose customer problems.

00:03:50: So everyone from discovery to renewal is speaking the same language about customer impact.

00:03:55: That's the goal.

00:03:56: It forces structure into the whole process.

00:03:58: Okay, so if the internal architecture is often the problem, the sources seem to suggest we need a new kind of role, a new kind of builder to fix

00:04:04: it.

00:04:04: Which transitions us perfectly into the next really hot trend, GTM engineering, GCME.

00:04:09: Yeah, seeing that everywhere.

00:04:10: Brandon Redlinger confirmed it's like one of the highest demand rolls out there right now.

00:04:14: Uh-huh.

00:04:15: And Vege Vasek defined it nicely as the system that keeps the whole GTM motion fast, clean, and trackable.

00:04:22: sort of sitting right in between sales, marketing, and ops.

00:04:26: The connective tissue.

00:04:27: Oriole Sarah made a great distinction too, didn't he?

00:04:29: He did.

00:04:29: He sees GTM engineering as the experimental arm of RevOps.

00:04:34: Experimental arm.

00:04:35: I like that framing.

00:04:36: So they're the ones building and testing the new maybe complex stuff like advanced lead scoring or routing rules.

00:04:42: Exactly.

00:04:42: And then traditional RevOps takes those proven systems and scales them.

00:04:46: governs them for reliability.

00:04:48: Makes sense.

00:04:49: Ajay Jol even suggested this role could finally help bridge that classic marketing versus sales divide by unifying the whole growth system.

00:04:57: Yeah,

00:04:57: a unifier role.

00:04:58: But what's fascinating is how quickly the debate started about its long-term future.

00:05:02: Right.

00:05:03: Like, is this role here to stay?

00:05:04: Oh,

00:05:04: yeah.

00:05:05: What's the debate?

00:05:06: Well, Ashmore noted that, yes, companies are willing to pay top dollar for these GTM engineers right now, but he also observed that many of the new AI tools, maybe counterintuitively, aren't actually reducing the burden.

00:05:19: Sometimes they're adding new layers of complexity to manage.

00:05:22: Interesting, so the tools meant to simplify are adding work?

00:05:25: Potentially, yeah.

00:05:26: which leads to some really provocative takes.

00:05:29: Richard F. Purcell, throughout this idea that GTM engineers might become obsolete before SDRs.

00:05:35: Well, wait, before

00:05:36: SDRs, how?

00:05:38: His argument is that the complex infrastructure they often manage, you know, stitching together clay, NNN, custom APIs, all that.

00:05:46: Yeah,

00:05:46: the Frankenstack.

00:05:47: Right, that infrastructure is rapidly evaporating.

00:05:50: Why pay someone six figures to babysit that stack?

00:05:53: when, maybe very soon, you could get the same result with a simple API call or just a detailed prompt.

00:05:58: Okay, that's a bold claim.

00:06:00: Replacing a hundred and fifty dollar K-rolls with prompt engineering.

00:06:02: It's definitely provocative, but it connects to this idea.

00:06:05: as I had site I. Lee brought up.

00:06:07: He called it the nineteen fifties cake mix problem.

00:06:10: The cake mix problem.

00:06:11: How does that relate?

00:06:12: It's the idea that the original cake mixes were too easy.

00:06:15: People felt like they weren't really cooking.

00:06:17: So the company's changed it so you had to add your own egg.

00:06:20: Okay.

00:06:21: making it feel like more effort was involved.

00:06:23: Exactly.

00:06:24: And the GTM equivalent might be engineers building these super elaborate, maybe forty seven step workflows, adding the egg partly to optimize for the feeling of necessary effort rather than just finding the simplest, most direct path to the outcome.

00:06:40: Optimizing for the feeling of complexity, not the result itself.

00:06:43: I get it.

00:06:44: That complexity is what could get automated away.

00:06:47: That's the thinking.

00:06:48: But, you know, for now.

00:06:49: For now, the demand is undeniable.

00:06:52: Noemi Jacqman observed they're incredibly sought after, and Varun Anand just announced Clay's new talent marketplace specifically for these

00:06:59: roles.

00:07:00: Yeah, the market is definitely hot right now.

00:07:01: Okay, let's pivot them.

00:07:02: Theme three, AI and GTM.

00:07:05: Because you can't talk GTM without talking AI.

00:07:08: Absolutely not.

00:07:08: And Coco Sexton made the point crystal clear.

00:07:11: AI isn't coming.

00:07:12: It's already here.

00:07:13: Right.

00:07:13: He cited stats like two-thirds of GTM teams using it daily, and eighty-five percent reporting productivity boosts.

00:07:20: Yeah, so simple adoption.

00:07:21: We're way past that hype cycle.

00:07:23: But just adopting it isn't the whole story, is it?

00:07:25: There were warnings.

00:07:26: Big warnings.

00:07:28: Piyush D. Pamar observed that AI itself won't decide the GTM winners.

00:07:33: Yeah.

00:07:33: Clarity will.

00:07:34: Clarity again.

00:07:35: It keeps

00:07:36: coming back to that.

00:07:36: It does.

00:07:37: And Ryan Van Schur really hammered this home.

00:07:39: Yeah.

00:07:40: You absolutely need those proper data foundations and standardized definitions we talked about earlier before you try to scale AI.

00:07:48: Otherwise, you just risk automating chaos, but faster.

00:07:51: You need what Rachel Lawler called GTM mastery, the structure before you can achieve GTM intelligence.

00:07:57: Okay, so how do companies practically move from just having that mastery to achieving predictive intelligence?

00:08:04: Well, Coco Sexton talked about moving from phase one.

00:08:07: which was mostly basic stuff like content generation, efficiency gains.

00:08:11: Yeah,

00:08:11: the easy ones.

00:08:12: To phase two.

00:08:13: And phase two is where AI starts driving direct, measurable improvements in actual pipeline and conversion rates.

00:08:20: That's the GTM intelligence Rachel Lawler mentioned, where systems can actually start making predictive adjustments based on real-time data.

00:08:26: Getting smarter on their own.

00:08:27: Kind of, yeah.

00:08:29: And Amon Bouzid shared a really cool tactical approach for this.

00:08:33: Model stacking.

00:08:34: Model stacking, like using different AI models together.

00:08:37: Exactly.

00:08:37: Mixing specialized models for specific tasks, like using Gemini Pro, maybe for high-speed data intake, Claude Sonnet for the more complex logic and lead scoring, and then maybe OpenAI-O-three for the actual execution, like personalized outreach.

00:08:51: Playing to each model's strengths within the workflow.

00:08:53: Smart.

00:08:54: And Maja Voji's data showed where the investment is flowing.

00:08:57: It's targeted.

00:08:58: Fifty-one percent of companies planning to boost spending on AI search AEO, and forty-five percent doubling down on intent-based outbound.

00:09:06: So funding the areas where AI meets immediate buyer intent makes sense.

00:09:11: Okay, let's move to theme four.

00:09:12: Outbound and pipeline quality.

00:09:14: Because this is where all that architecture and AI work either pays off.

00:09:17: Or falls flat on its face.

00:09:18: Pretty much.

00:09:19: Bill Rose found success by finding the A&D.

00:09:22: Not just AI automation, but AI automation and human oversight.

00:09:25: Not just signal-based campaigns, but signal-based A&D profile-based campaigns.

00:09:29: That balanced approach.

00:09:31: Did it work?

00:09:32: Apparently so.

00:09:33: He reported twenty-four percent of MRR coming from cold outbound, but with a forty-five percent lower customer acquisition cost.

00:09:39: Wow.

00:09:40: Lower SCAC and significant MRR from cold.

00:09:43: That's impressive.

00:09:44: It highlights the importance of quality, which is absolutely non-negotiable now.

00:09:48: The full cast EBSA, twenty-twenty-five GTM benchmarks shared by Matt Hardy had a jaw-dropping stat.

00:09:54: Oh, yeah.

00:09:55: What was it?

00:09:56: Only twenty-three percent of the average pipeline is actually high-fit ICP, twenty-three percent.

00:10:01: Ouch.

00:10:01: That low.

00:10:02: What about the rest?

00:10:03: Well, here's the kicker.

00:10:04: Yeah.

00:10:04: Low fit deals would still make up around thirty percent of the pipeline.

00:10:08: They showed an eighty seven percent lower sales efficiency.

00:10:10: Eighty

00:10:11: seven percent lower efficiency.

00:10:12: Just stop right there.

00:10:13: That number alone should dominate GTM strategy.

00:10:16: It

00:10:16: really should.

00:10:17: It proves chasing volume, especially low fit volume, isn't just ineffective.

00:10:21: It's an active cost drag.

00:10:23: It inflates cap, burns out teams.

00:10:25: It completely validates that push for clarity we talked about earlier.

00:10:27: You need to know who you're targeting and

00:10:29: stick to it.

00:10:30: Absolutely.

00:10:30: And it confirms what Bill Stathopoulos argued.

00:10:33: The decisive variable in outbound success often isn't the tool or the sequence, it's the talent.

00:10:38: The

00:10:38: people.

00:10:38: The people who actually know how to build, wire, and run a GTM system that learns from its execution and feeds those learnings back into the strategy.

00:10:47: That human operational expertise is critical.

00:10:50: And

00:10:50: we saw some cool tactical examples of that execution.

00:10:53: Melissa Gaglione, via Dean Fiacco, mentioned ditching cold calls entirely.

00:10:59: Yeah,

00:10:59: switching to cold video outreach on LinkedIn and finding success.

00:11:02: Interesting.

00:11:03: And Nafal Nugraho shared a neat GTM engineering play using Clay Flows.

00:11:07: Right,

00:11:08: to de-anonymize website traffic and then instantly turn those visitors into qualified, highly personalized outreach sequences.

00:11:15: That's closing the loop fast.

00:11:17: Taking intense signals and acting on them immediately.

00:11:19: Very cool.

00:11:20: Okay, finally, let's quickly touch on theme five.

00:11:22: New frameworks and support systems popping up to make all this more efficient.

00:11:26: Yes, Moonwell's offering serious leverage.

00:11:28: Summit N showed a system where Claude AI apparently build a whole ninety-day GTM plan

00:11:33: positioning funnel design roadmap the works

00:11:36: in under four hours which historically he noted might cost a founder like twenty thousand dollars in consulting fees.

00:11:42: that's a massive potential shift in access to strategic planning.

00:11:46: huge.

00:11:47: And Timothy Goble highlighted another efficiency tool, using a brand intelligence layer, like RISA content.

00:11:54: The idea there is faster GTM content execution, right?

00:11:57: Like two, three X faster.

00:11:59: Yeah.

00:11:59: Yeah.

00:11:59: While crucially protecting brand integrity, it sort of codifies the brand's DNA so teams can move quickly without going off message.

00:12:06: And for diagnosing those internal messes we talked about, Eddie Reynolds launched a GTM ops maturity assessment tool.

00:12:13: Oh yeah.

00:12:13: How does that work?

00:12:14: It uses a big hundred and fifty.

00:12:16: diagnostic to generate a really specific report analyzing your processes inbound outbound pipeline metrics.

00:12:24: Basically a self-serve way to pinpoint architectural weak spots.

00:12:27: Like a health check for your GTM system.

00:12:30: And of course there's still a need for human expertise.

00:12:32: Definitely.

00:12:33: Neil Weitzman championed the continued rise of fractional CROs.

00:12:37: For those scaling startups they bring that senior level GTM discipline, the focus, balance, drive for predictable growth.

00:12:43: But without the immediate hefty cost or of a full-time exec hire.

00:12:47: Exactly.

00:12:48: It provides that senior guidance when it's needed most.

00:12:50: Okay, so wrapping all that up, the focus on architecture, the rise of engineering, the push for quality over volume, smarter AI use.

00:12:57: And keeping that absolutely staggering, eighty-seven percent lower sales efficiency for low-fit deals burned into our minds.

00:13:05: Right, so here's our provocative thought for you, the listener, to mull over.

00:13:10: Given that drag from low-fit deals, what internal processes are you tolerating right now?

00:13:14: Could be messy CRM data, maybe misaligned definitions between sales and marketing.

00:13:19: Could just be accepting poor lead quality.

00:13:22: What things are actively degrading your entire GTM systems performance, no matter how fancy your new AI tools are.

00:13:28: Because the sources really remind us strategy sets the direction, the distance you want to go.

00:13:33: But it's the culture.

00:13:34: What your teams, especially sales, tolerate and accept as normal day-to-day, as Joshua Smith might put it, that ultimately determines your actual speed.

00:13:42: Structure and clarity really do trump tech alone.

00:13:44: That's the big takeaway.

00:13:46: If you enjoyed this deep dive, new episodes drop every two weeks.

00:13:49: Also check out our other editions on account-based marketing, field marketing, channel marketing, mark tech, social selling, and AI in BDB marketing.

00:13:56: Thanks so much for joining us for this essential deep dive into the latest thinking on GTM architecture and engineering.

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