Best of LinkedIn: Go-to-Market CW 38/ 39

00:00:00: This episode is provided by Thomas Allgaier and Frannis based on the most relevant LinkedIn posts about go-to-market in calendar weeks thirty eight and thirty nine.

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

00:00:17: Welcome everyone.

00:00:18: So if you're working in B to B go-to-market right now well you definitely feel the ground shifting don't you.

00:00:25: Oh, absolutely.

00:00:25: The whole landscape, it's not just evolving.

00:00:28: It feels like a fundamental kind of structural change.

00:00:31: We're seeing leaders admitting, you know, the playbooks that got them here, they're just not cutting it anymore.

00:00:36: Yeah,

00:00:36: the speed is just, oh, wow.

00:00:39: So our mission today is to try and cut through that noise, find the key go-to-market trends popping up on LinkedIn these past couple of weeks.

00:00:45: We're really zeroing in on this powerful mix of AI, data integrity, and frankly, a much needed return to pipeline discipline.

00:00:53: Okay, let's unpack this.

00:00:55: Starting with theme one, ushering in the age of the AI native GTM operator.

00:00:59: Yeah, this theme really hit home, I think.

00:01:01: You saw this at like existential tension bubbling up.

00:01:05: Daniel DeSousa put it bluntly.

00:01:07: His experience, it will not be relevant in the new AI era.

00:01:11: Wow.

00:01:13: That's a bold statement.

00:01:15: It really is.

00:01:16: Basically saying, my veteran knowledge might have an expiry date.

00:01:19: And then Henry Shuck over at Zoom Info, he called this whole thing GTM's iPhone moment.

00:01:24: Okay, iPhone moment.

00:01:25: Is he just saying our current tools are toast?

00:01:29: Or is it deeper, like the whole structure of GTM, the skills needed?

00:01:33: Right.

00:01:33: Is that all about to change?

00:01:34: The sources definitely point towards skills.

00:01:37: Sam Jacobs, for example, he laid out five trades for the future GTM operator.

00:01:40: Okay.

00:01:41: You got to be AI native, sure, but also P&L fluent, tech forward, a resilient learner.

00:01:46: And this one's key at cross functional.

00:01:48: These aren't nice to haves anymore.

00:01:49: They're basically table stakes.

00:01:50: No, the P&L fluency and the cross functional skills really jump out because AI can't.

00:01:55: Replace those right.

00:01:56: it just makes the tools work better if you have those skills.

00:01:58: It's.

00:01:59: Steve Richard made a great point about being cross-functional.

00:02:02: It's not just demanding stuff for marketing.

00:02:05: It's understanding the trade-offs marketing has to make to get you what you need.

00:02:08: That's real partnership.

00:02:09: totally

00:02:10: agree.

00:02:10: and that P&L fluency is so vital.

00:02:13: It's about connecting your GTM actions directly to margin to ROI.

00:02:17: not just.

00:02:18: you know counting meetings booked right.

00:02:19: James Ross shared this really interesting personal hack he uses.

00:02:24: he takes company board slides, those dense financial reports, feeds them into a secure AI platform and basically tells it, explain this to me like I'm a dumb sales guy.

00:02:34: It's a smart way to really master the language of the business.

00:02:37: You get the business acumen without needing the finance degree.

00:02:40: That's a fantastic use of AI mastering fundamental skills.

00:02:44: But as we know, AI is only as good as its inputs, right?

00:02:48: Yeah.

00:02:48: Which takes us straight to theme two, data quality, the new GTM foundation.

00:02:53: Exactly.

00:02:53: Kunstan didn't mince words here.

00:02:55: AI doesn't fix broken systems.

00:02:56: It just makes the flaws bigger, louder.

00:02:59: And Steve Richard echoed that.

00:03:00: If your top of funnel is already a mess, throwing AI at it, well, you just fail faster and probably spend more doing it.

00:03:07: So job one has to be focusing on input quality.

00:03:10: Precisely.

00:03:11: Alex Schultz pointed this out.

00:03:13: Messy, vague inputs.

00:03:15: They create exponentially messier outputs.

00:03:18: If your GTM team skims on really nailing the ICP articulation, who are we really trying to reach?

00:03:23: What problems do they actually have?

00:03:25: Then you're basically sabotaging your AI investment before it even starts.

00:03:28: The AI needs clean context.

00:03:30: Makes sense.

00:03:30: It

00:03:31: does.

00:03:31: But the flip side, the good news is that the tools for getting clean custom data are getting surprisingly affordable.

00:03:38: Andreas Wernicke showed this using tools like Clay.

00:03:41: Not

00:03:41: Clay, yeah.

00:03:42: He estimated that getting custom AI data for super precise segmentation like analyzing half a million company websites to figure out exactly what they do costs only about a thousand bucks total.

00:03:52: Wow.

00:03:53: That kind of high accuracy custom Intel, it just blows up the old model of buying expensive generic.

00:04:00: But when you start doing that kind of custom data work at scale, especially with contact info, well, GTMOps suddenly has a much bigger legal hat to wear.

00:04:09: Ah, compliance.

00:04:10: Yep.

00:04:11: Charlie Saunders flagged this as the elephant in the room.

00:04:15: using personally identifiable information, PII, in AI workflows.

00:04:20: Okay, so let's clarify.

00:04:21: Even if a team is just feeding contact data into, say, an LLM for internal stuff, like training or getting ideas for personalization, but they never actually send anything based on it, are they still on the hook for Judy PR or CCPA?

00:04:34: Absolutely.

00:04:35: It's still data processing.

00:04:37: Your ops teams need to be legally literate now.

00:04:39: because they're responsible for how that PII interacts with the AI.

00:04:43: It shifts GTM ops from purely technical to compliance.

00:04:46: critical.

00:04:46: Interesting.

00:04:47: And this whole drive for clean, durable data, it's the bedrock for theme three, the pivot to customer centric, durable growth.

00:04:54: Yeah, the message we saw everywhere was pretty clear.

00:04:56: The old grow it all costs playbook, it's dead.

00:04:59: The MLO stated that pretty clearly.

00:05:02: It really is.

00:05:03: Acquiring new customers is just more expensive now.

00:05:05: Tom Passello highlighted that.

00:05:07: Markets are saturated, buyer expectations are way higher.

00:05:10: Right.

00:05:10: So the focus has to shift from just getting new logos to keeping and growing the customers you already have.

00:05:16: Mm-hmm.

00:05:16: Anthony D'Souzawer pointed out that focusing on expansion, preventing churn, that's the only path to real durability.

00:05:24: Anthony D'Souzawer actually shared some compelling math on this.

00:05:27: He showed how a system pouring say, seventy-five percent of its budget into acquisition might get stuck around a hundred percent NRR net revenue retention.

00:05:37: Standard.

00:05:37: But flip that script.

00:05:38: Put seventy-five percent into existing customers.

00:05:41: He argued you could push NRR up to maybe a hundred and twelve percent.

00:05:44: That's huge cost leverage, turning customer success into your main revenue engine.

00:05:48: And that focus changes who you hire and how you train them, doesn't it?

00:05:51: Yeah.

00:05:52: Brittany Borelli made a strong case against just churning out SDRs in SDR factory.

00:05:56: Right,

00:05:56: those high turnover rolls.

00:05:58: Exactly.

00:05:58: She advocates for proper GTM apprenticeships instead.

00:06:01: Rotations through marketing, through CS, even product.

00:06:05: OK, apprenticeships sound good focusing on that broader business sense.

00:06:08: But how do you sell that internally?

00:06:11: Doesn't it risk making the SDR role look less immediately productive if they're spending time cross-training?

00:06:16: Barelli's argument is you're future-proofing the seller.

00:06:19: It's an investment.

00:06:20: You get a higher value, higher retention person who actually understands the whole customer journey, not just one part of prospecting.

00:06:27: And connecting this back to AI, this is where the metrics get really interesting.

00:06:31: Jared Gibson pointed out, if AI agents start handling complex buyer tasks like solutioning or even building ROI models, then old metrics like meetings booked are just broken, completely irrelevant.

00:06:44: GTM leaders need to track things like cycle compression, actual bottom funnel impact.

00:06:49: David Wilkins and Rahul Wadhwa were clear.

00:06:51: Executives care about revenue contribution, period.

00:06:55: not vanity metrics.

00:06:56: And that massive shift in what we measure forces us to look at the underlying machinery.

00:07:01: Which brings us nicely to theme four.

00:07:03: Systems architecture and the whole GTM engineering debate.

00:07:06: Sangram Vajra argued that lack of alignment is just.

00:07:10: It's killing GTM effectiveness everywhere.

00:07:12: Yeah, that misalignment hurts.

00:07:14: His solution.

00:07:15: A systems-based approach.

00:07:17: Transformational.

00:07:18: CEO owns GTM.

00:07:21: NRR is the one metric everyone aligns on.

00:07:24: You have to build systems, not just chase goals.

00:07:27: And that systems thinking is exactly what's driving this debate around job titles.

00:07:31: RevOps, GTMOps, GTM Engineering.

00:07:34: Right, what's the difference?

00:07:35: Well, Jonathan Fianna noted that just having this debate shows that discipline is maturing, which is a good sign.

00:07:40: Paul Nicole offered a really useful frame using ExploreExploit.

00:07:44: He sees RevOps as the exploit engine, focused on efficiency, scaling what works, optimizing the known.

00:07:50: GTM Engineering is the Explore engine, running quick experiments using AI for new advantages, figuring out the next playbook.

00:07:57: They're compliments, not rivals.

00:07:58: And the tools are evolving fast to support that explore side.

00:08:01: Colby Morgan highlighted Clay's recent updates.

00:08:04: Sculptor sequencer audiences basically collapsing that duct-taped mess of separate enrichment and sequencing tools into one spot.

00:08:11: That sculptor feature is particularly interesting for the engineering idea.

00:08:14: Harris Otobasic noted that because Sculptor lets non-technical folks build complex data tasks.

00:08:20: using plain English, it could be Klee's checkmate move.

00:08:23: It makes GTM engineering something a business user can do directly, not just a specialized technical role needing APIs.

00:08:29: So this relentless drive for efficiency, for engineering, for AI, it really begs the question, where does the human fit in?

00:08:38: What's our unique value?

00:08:40: And that's our final theme, theme five.

00:08:43: the human differentiator.

00:08:45: Unreasonable hospitality.

00:08:47: Yeah, Bill Hobbett made a critical point here.

00:08:49: In B to B, often true product differentiation is fleeting.

00:08:52: Features get copied so fast.

00:08:54: True.

00:08:54: So if the product isn't the lasting advantage, then experience becomes the real differentiator.

00:08:58: That's

00:08:58: powerful.

00:08:59: And it lines up perfectly with all the buzz around Will Goddard's keynote on unreasonable hospitality.

00:09:04: Jason Moore, Nagin Kamangar, Randy Sue Deckard, they all flagged the key takeaway.

00:09:09: The best experiences have to be to spoke.

00:09:11: Exactly.

00:09:12: Diggin' Kamangar talked about one size fits one.

00:09:15: The goal isn't just efficiency anymore.

00:09:17: It's optimizing for real, personal connection.

00:09:21: And that takes intention, empathy.

00:09:24: Things algorithms don't really do.

00:09:26: And they shared that perfect anecdote, didn't they?

00:09:28: The hot dog moment.

00:09:29: Oh yeah, the hot dog moment.

00:09:31: Yeah.

00:09:31: At Eleven Madison Park, this four-star place.

00:09:34: Gadara overhears some European guests saying they've never had a real New York hot dog.

00:09:37: Right before their fancy main course.

00:09:39: Exactly.

00:09:40: He runs out, gets one from a street vendor, serves it up with ketchup, sauerkraut, the works.

00:09:45: Medine Comangar and Kurt and Roderick pointed out that single, personal, intentional gesture.

00:09:50: It created a story people would tell forever.

00:09:53: That moment of human connection beat any amount of marketing spend because it built real loyalty.

00:09:58: A great story.

00:09:59: So if you enjoyed this deep dive, remember new episodes drop every two weeks.

00:10:03: Also check out our other editions covering account-based marketing, field marketing, channel marketing, martech, social selling, and AI in B to B marketing.

00:10:11: So we heard loud and clear today.

00:10:12: The old playbook's done.

00:10:14: GTM is being rebuilt right now.

00:10:15: Thinking about those five traits for the future GTM operator.

00:10:19: If you had to pick just two critical skills to really master force a year of twenty-twenty-six planning, setting aside AI native for a moment, would you double down on becoming truly P&L fluent or deeply cross-functional?

00:10:32: Finance or collaboration?

00:10:33: It's something to mull over.

00:10:34: Definitely something to think about.

00:10:36: Thank you for listening to this deep dive and remember to subscribe.