Best of LinkedIn: Go-to-Market CW 40/ 41

00:00:00: This episode is provided by Thomas Allgaier and Frennis, based on the most relevant LinkedIn posts about GoToMarket in calendar weeks forty and forty-one.

00:00:09: Frenas is a BDB market research company helping enterprises gain the customer, competitive, and positioning insights needed to drive GTM success.

00:00:18: Yeah, and looking at those sources, something pretty fundamental seems to be happening, doesn't it?

00:00:22: Definitely.

00:00:22: A real shift.

00:00:23: It feels like a decisive shift in BDB go-to-market.

00:00:26: It's less about those one-off marketing tactics or relying on that heroic salesperson anymore.

00:00:33: Right.

00:00:33: It's moving towards building these robust, I'd say, engineered data-driven systems.

00:00:39: And here's the kicker.

00:00:40: AI isn't just some add-on feature now.

00:00:42: It's becoming like an operating layer, but that demands real strategic thinking underneath it all.

00:00:48: Okay, let's unpack that then.

00:00:49: Let's jump right in.

00:00:50: Today, we're doing a deep dive into the top, go-to-market trends we saw popping up on LinkedIn these past two weeks.

00:00:55: We'll focus on those tactical shifts, sure, but also the strategic rigor that, well, seems essential now if you want real, sustainable B to B growth.

00:01:03: Yeah.

00:01:04: So the first big theme that really jumped out is this idea of foundational rigor.

00:01:09: It seems leaders are really hammering this home.

00:01:12: Focus on the fundamentals before you chase the shiny new tactics or AI tools.

00:01:17: Yeah, get the bait six right first.

00:01:18: Exactly.

00:01:19: Because rushing that groundwork, it just leads to costly mistakes later and actually stops you from accelerating properly.

00:01:26: Alexander Esner really laid this out clearly.

00:01:28: He listed what was it, seven foundations that sauce founders often skip over.

00:01:33: Things like, you know, really nailing down your ideal customer profile, the ICP, getting your positioning and messaging crystal clear.

00:01:40: Absolutely critical.

00:01:41: Figure out the right channels, pricing models, the sales motion itself, even mapping the buyer journey properly.

00:01:48: His point was skipping.

00:01:49: these is exactly why companies stall out before hitting that one million ARR mark.

00:01:54: That's such a critical frame because it treats GTM less like creative magic and more like, well, engineering.

00:02:00: Manuel Hartman drove this home too.

00:02:02: He basically said effective GTM is actually boring and repetitive.

00:02:05: Huh.

00:02:05: Yeah.

00:02:06: Not what you might expect.

00:02:07: Right.

00:02:07: But it's about clarity, consistency, continuity.

00:02:11: If your process feels like constant chaos or requires heroics all the time.

00:02:16: You're probably doing it wrong.

00:02:17: The goal is building a scalable revenue factory.

00:02:20: And that shift from gut feeling to actual intelligence, it's huge.

00:02:25: Apsha Haslani observed that the whole sales function has really evolved into GTM.

00:02:30: It's

00:02:30: broader now.

00:02:31: Much broader.

00:02:31: It's a complete process, sales, marketing ops.

00:02:35: all working together, fueled by data, using automated systems, moving away from intuition towards intelligence.

00:02:41: Which naturally brings us to this hot role, the GTM engineer.

00:02:45: Othmane Khudry had a great warning about misconceptions here.

00:02:48: Oh

00:02:48: yeah, what's the common mistake?

00:02:49: Thinking it's just, and I quote, a mid-SDR with clay access, like just someone technical fiddling with tools.

00:02:55: Ah,

00:02:56: okay.

00:02:57: But it's more than that.

00:02:57: Way

00:02:58: more.

00:02:58: The real role is strategic.

00:03:00: It's about defining clear hypotheses, constantly analyzing what's working and what's not in the funnel, and then building the robust, scalable systems to actually orchestrate and execute the strategy across all the tools.

00:03:12: They're turning that founder intuition into repeatable workflows.

00:03:15: I liked Alex Pulvgenic's definition too.

00:03:17: He said, GTM engineers figure out why deals are won or lost.

00:03:20: They dig into CRM data, call transcripts, market feedback, looking for patterns.

00:03:25: Right.

00:03:26: don't just automate stuff for the sake of it.

00:03:27: They automate what's proven to work and shows real ROI.

00:03:31: It's definitely not just babysitting Zapier flows.

00:03:34: And the data backs this up as a serious specialized role.

00:03:38: Henley Wing-Chu's analysis.

00:03:40: It showed GTM engineering is basically RevOps, but with a distinct technical twist.

00:03:45: Meaning?

00:03:45: Meaning you actually need a code.

00:03:47: SQL and Python are apparently highly desired skills, and the pay reflects that engineering skill set.

00:03:53: But the focus is different from traditional RevOps.

00:03:55: Now so.

00:03:56: GTM engineers seem uniquely focused on optimizing the outbound and prospecting side of things, the data plumbing for that.

00:04:03: Whereas, you know, traditional RevOps might focus more internally on things like sales forecast accuracy.

00:04:08: Got it.

00:04:08: So, GTM needs this engineered system built on solid foundations and clean data.

00:04:14: That flows perfectly into our next theme, AI and acceleration.

00:04:17: Yeah, the AI impact.

00:04:18: Jeremy Grandian put it really well, I thought.

00:04:20: He said AI isn't changing the fundamental GTM

00:04:24: rules.

00:04:24: No, the core principles remain.

00:04:26: Exactly.

00:04:27: but it's accelerating them like crazy.

00:04:30: So if you find something that works today, you've got to realize it's likely a temporary advantage, what he calls GTM Alpha.

00:04:36: Because someone else will copy it tomorrow.

00:04:38: Probably using AI to do it even faster.

00:04:41: So you're in this constant race for the next edge.

00:04:44: And that

00:04:44: speed is forcing the high growth teams to get really strategic with AI.

00:04:49: I've in Falco observed some key motions they're using.

00:04:52: Like what?

00:04:53: What are they actually doing?

00:04:54: Well,

00:04:54: four main things.

00:04:55: First, using AI for search, essentially bypassing Google by giving direct answers to high intent questions instantly.

00:05:01: Second, automating personalized video generation, but at scale.

00:05:05: Third, creating these little AI driven mini products specifically for qualification.

00:05:10: And fourth, using AI power at ABM for much sharper signal detection and really segmented targeting.

00:05:16: That sounds incredibly powerful.

00:05:19: dream almost.

00:05:19: But if it's so great, why are so many companies struggling?

00:05:23: Sangram Varjo offered a pretty sobering reality check.

00:05:26: Uh-oh.

00:05:27: What's the catch?

00:05:28: He stated that something like ninety-five percent of AI projects either stall or fail completely.

00:05:34: Ninety-five percent.

00:05:35: Wow.

00:05:35: Yeah.

00:05:36: And here's the crucial part.

00:05:38: It's usually not because the tech is bad.

00:05:40: The real problems are things like leadership alignment, poor adoption within the teams, and basic integration gaps.

00:05:47: So if your underlying strategy is flawed...

00:05:50: The AI just helps you fail faster, basically.

00:05:52: It magnifies the existing problems.

00:05:54: Which brings up this risk of, let's call it fragile automation.

00:05:58: Yulia Alenakova had a really sharp warning about certain consultants.

00:06:02: What kind of warning?

00:06:02: She cautioned against those promising, you know, TenX leads using these super complex... Brittle workflows involving multiple tools tacked together.

00:06:11: She had a great nickname for it.

00:06:12: Clay plus spray plus pray.

00:06:14: Uh-huh.

00:06:15: I like that.

00:06:15: Clay plus spray plus pray.

00:06:17: Exactly.

00:06:18: The problem is these setups are often too complicated for the internal team to maintain.

00:06:22: So when the consultant leaves...

00:06:24: The whole thing falls apart.

00:06:25: Right.

00:06:26: Huge budget waste, fragmented data.

00:06:28: The system needs to be robust and sustainable, not just clever on paper.

00:06:31: An even seemingly simple automation needs that human sanity check.

00:06:36: Andreas Wernicke shared a specific example where AI, just doing basic data enrichment, misclassified a personal email, something like RobertDelgita.team.

00:06:46: It flagged it as a system email just because of the structure of the pattern.

00:06:50: Because it looked like something at company.domain.

00:06:52: Exactly.

00:06:53: It matched the pattern, but completely missed the context.

00:06:56: AI does pattern matching brilliantly, but it doesn't understand.

00:07:00: And if you don't have that human oversight, You risk polluting your CRM data badly, undermining all that rigor we just talked about.

00:07:07: Which leads us perfectly to the operational backbone.

00:07:10: Data quality and RevOps.

00:07:12: Because the success of these engineered systems, the AI acceleration, it all hinges completely on the quality of the data flowing through them.

00:07:20: It's where scale either works beautifully or just breaks everything.

00:07:23: Precisely.

00:07:24: And that data quality issue, it might be the biggest internal risk GTM teams face right now.

00:07:29: Don Simpson called it the uncomfortable truth.

00:07:32: What's the truth?

00:07:33: That many GT imagines are fundamentally broken because they're relying on intent data.

00:07:37: that's maybe, at best, only twenty percent accurate.

00:07:41: Only twenty percent.

00:07:42: Ouch.

00:07:42: Yeah, so think about it.

00:07:44: If your initial signal is wrong eighty percent of the time, it poisons everything downstream, your lad routing, scoring, personalization.

00:07:51: Yeah.

00:07:52: Even your forecasting becomes unreliable.

00:07:54: So Joseph Santos argues, and I think he's spot on, that master data is the real GTM growth engine.

00:08:01: It's not just background plumbing, it's essential infrastructure.

00:08:04: Meaning you need that single source of truth.

00:08:06: Absolutely.

00:08:07: A single trusted unified data set to reconcile everything across your CRM, your marketing automation, your ABM tools.

00:08:14: If you can't trust the inputs, especially for AI models, you definitely can't trust the outputs.

00:08:18: Okay,

00:08:18: but on the rev op side, there's hope too, right?

00:08:20: It's not just about data hygiene.

00:08:22: Pankaj Kumar shared a great example of efficiency games.

00:08:25: Oh,

00:08:25: yeah.

00:08:25: What did they achieve?

00:08:26: They reduced client sales cycle by thirty percent in just ninety days and get this with no extra budget.

00:08:33: Purely through process and alignment, defining agreed upon qualification criteria between sales and marketing, setting up clear SLAs for handoffs and getting everyone rallied around shared revenue goals, basically fixing those classic friction points that add weeks to the cycle.

00:08:50: It's amazing what just getting aligned can do.

00:08:53: And it's crucial to connect that operational rigor up to the C-suite, too.

00:08:57: Dan Sparing had some advice for CMOs talking to their CFO.

00:09:00: How to speak the CFO's language.

00:09:02: Exactly.

00:09:02: He said, focus on customer lifetime value, LTV.

00:09:06: But, and this is the key part, but analyze LTV at the segment level, not just the overall average.

00:09:11: Why the segment level?

00:09:12: Because the aggregate average hides which customer segments might actually be unprofitable or way too expensive to acquire.

00:09:19: Segment level LTV gives the CFO real insight into where to allocate resources effectively and which types of accounts are truly worth chasing hard.

00:09:27: Makes total sense.

00:09:28: Okay, so we've got the system, the data, the financial alignment.

00:09:31: Now let's talk about execution, the actual motions driving revenue, starting with expansion.

00:09:35: Right.

00:09:36: Expansion.

00:09:37: Jamie Walsh made a strong case that it shouldn't be an afterthought.

00:09:40: It needs to be treated as its own explicit, high-priority GTM motion.

00:09:45: Engineered, just like acquisition.

00:09:47: Precisely.

00:09:48: He shared a case study.

00:09:50: A client got thirty-eight percent growth in expansion ARR without building a single new product feature.

00:09:56: Really?

00:09:56: How?

00:09:56: Just

00:09:57: by coordinating plays around mapped triggers.

00:09:59: Things like product usage signals, customer funding rounds, key users changing roles.

00:10:04: They systematically activated expansion efforts at just the right moment.

00:10:08: So engineering the moment, not just the message.

00:10:11: That applies to outbound too, right?

00:10:12: Yeah.

00:10:13: Enzo Carasso had a sharp take on this.

00:10:14: What was his point?

00:10:16: That simply having hyper-precise targeting that GTM alpha we mentioned isn't enough if your actual outreach is generic.

00:10:23: Successful outbound delivers real value before the sale.

00:10:26: Okay, what does that mean in practice?

00:10:28: It means engineering the aha moment into the very first interaction, making the value proposition immediate and tangible, not just a promise for later.

00:10:36: That's why it works, he argues, and why it's hard for competitors to just copy.

00:10:40: And getting that aha moment right requires knowing exactly when to reach out, which means advanced signals.

00:10:48: Shaktival Matheshwan talked about moving beyond outdated signals.

00:10:52: Like what?

00:10:52: What's outdated now?

00:10:53: Things like webinar signups, maybe.

00:10:56: He says modern teams hunt for unique ready-to-buy social triggers.

00:11:01: Interesting.

00:11:01: Give me an example.

00:11:02: Like finding someone from your ICP, asking on a forum, does this specific tool integrate with PlatformX?

00:11:09: or seeing a target account posting a job that requires expertise in a competitor's tool?

00:11:14: Ah, signals of immediate friction or need.

00:11:16: Yeah.

00:11:17: Much stronger than just passive interest.

00:11:18: Exactly.

00:11:19: High intent actions happening right now.

00:11:22: Okay, one final point on execution.

00:11:24: Yeah.

00:11:24: Global GTM.

00:11:26: Thomas Ducerot had a crucial warning about just copying and pasting playbooks.

00:11:30: Especially

00:11:30: into EMEA, right?

00:11:31: Yeah, he specifically mentioned EMEA.

00:11:33: Trying to just replicate a successful US playbook there can waste millions.

00:11:37: Yeah.

00:11:37: Success demands really updating those playbooks for local realities.

00:11:40: But what does that involve?

00:11:42: Things like precise country selection, surgically activating the right local partner ecosystem, like global system integrators, hyperscalers, and ensuring real cultural fluency to avoid friction.

00:11:53: It needs rigor.

00:11:54: So looking back across all these insights from the last couple of weeks, the big message seems crystal clear, doesn't it?

00:12:00: Yeah, I think so.

00:12:01: What's your main takeaway?

00:12:02: That the modern GTM Pro really has to ditch their reliance on pure instinct or one-off tactics.

00:12:08: You have to adopt an engineering mindset.

00:12:10: Prioritize building durable, data-driven systems over chasing temporary wins.

00:12:15: That shift towards GTM is a robust, auditable system.

00:12:19: that feels essential now.

00:12:21: And maybe here's a final thought for you, the listener.

00:12:23: to chew on, inspired by Elon even.

00:12:26: Go on.

00:12:26: If you aren't doing regular, tough GTM audits, really digging into fixed foundational issues, like you're targeting your positioning, your core metrics, then AI isn't going to rescue you.

00:12:36: Quite the opposite, probably.

00:12:37: Exactly.

00:12:37: In fact, it'll likely just amplify the broken processes you already have.

00:12:41: Yeah.

00:12:41: And that failure will probably show up later as a massive play-blind crisis, right when your budget's already locked in elsewhere.

00:12:47: That's a powerful, maybe slightly terrifying thought.

00:12:50: to end on.

00:12:51: If you enjoyed this deep dive, new episodes drop every two weeks.

00:12:55: Also, check out our other editions on account-based marketing, field marketing, channel marketing, MarTech, social selling, and AI in B to B marketing.

00:13:04: Thanks for diving deep with us today.

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