Best of LinkedIn: AI in B2B Marketing CW 35/ 36

00:00:00: This deep dive is provided by Thomas Allgaier and Frennus based on the most relevant LinkedIn posts about AI and BP marketing in calendar weeks, thirty five and thirty six.

00:00:09: And Frennus, just so you know, is a B to B market research company.

00:00:13: They help enterprise marketing teams sharpen strategies and outreach using things like customer segmentation, ideal customer profiles, deep dives, customer needs analysis and buying center insights.

00:00:24: All right.

00:00:24: So today we're taking a deep dive into something that's absolutely buzzing in.

00:00:29: Well, all our professional feeds.

00:00:32: The top AI and B to B marketing trends.

00:00:34: We're looking at what really lit up LinkedIn over the past couple of weeks, calendar weeks, thirty-five and thirty-six specifically.

00:00:40: Exactly.

00:00:41: Our mission today really is to cut through all that noise, give you a shortcut to being well informed.

00:00:46: We want to explore the concrete shifts and actionable insights coming directly from practitioners and thought leaders on the front lines.

00:00:52: Yeah, so you get to hear what's truly shaping the AI landscape for B to B marketers right now.

00:00:57: That's

00:00:57: the plan.

00:00:58: All right, no time to waste.

00:00:59: And let's jump right into the first big shift, the one that was really lighting up our feeds, these surprising new rules around AI search and something experts are calling generative engine optimization.

00:01:10: or GEO?

00:01:12: Yeah, it's definitely moved far beyond just theory.

00:01:14: It's really into execution now.

00:01:16: And what's fascinating here is how fundamentally different AI rankings are from classic SEO.

00:01:23: How so?

00:01:23: Well,

00:01:24: Brittany Muller, for instance, really emphasized that AI doesn't work like traditional search engines.

00:01:28: It doesn't really rank in the same way.

00:01:30: OK.

00:01:31: So the key takeaway for marketers here is that brand authority, not keyword density, is your new SEO superpower.

00:01:38: It's much more about being the definitive trusted source rather than just optimizing for an algorithm.

00:01:44: That

00:01:44: truly redefines how we think about search entirely, doesn't it?

00:01:48: But, okay, beyond just adapting to this new reality, what new frontiers are opening up?

00:01:51: Are there proactive things marketers can do?

00:01:54: Oh, definitely.

00:01:55: Neil Patel highlighted the emerging upside of perplexity.

00:01:58: He kind of sees its trajectory as an early marketing opportunity for those saddy enough to shape their presence in these new AI native search experiences.

00:02:07: Interesting.

00:02:08: Yeah, imagine getting ready to buy customers from, what, a fourteen billion dollar AI search engine that hardly anyone is optimizing for yet?

00:02:15: That's a huge green field.

00:02:16: That is a massive, untapped potential.

00:02:19: So, okay, if we're moving towards AI native search and brand authority is king, what are the practical levers BDB marketers can actually pull right now?

00:02:28: to build that trust and visibility.

00:02:30: Well, several experts pointed to some concrete actions.

00:02:32: Tom Winter and Ollie Hammons, for example, both stressed brand consistency across all platforms.

00:02:38: They advised showing up on places like Reddit.

00:02:41: Apparently, large language models actually love Reddit and investing in meaningful PR.

00:02:46: We're talking Wikipedia-level credibility, not just random guest blogs.

00:02:50: It's all about trust building through diverse, highly credible content sources.

00:02:54: Okay.

00:02:55: Reddit, interesting.

00:02:56: Now here's where it gets really interesting, maybe a bit.

00:02:59: a nerving.

00:03:00: Liza Adams shared some pretty eye-opening insights on how AI is already shaping brand perceptions and influencing buying decisions just through basic everyday Google searches.

00:03:11: Could you walk us through some of her examples?

00:03:13: What do they really reveal?

00:03:14: Absolutely.

00:03:15: So Liza showed how AI overviews in Google search are directly assigning brand attributes.

00:03:20: Like Asana gets tagged as four small businesses.

00:03:23: Monday.com is seen as visual and easy to use and ClickUp becomes the all-in-one solution.

00:03:29: but then other major players like Smartsheet, huge market share, loads of revenue, they can be completely invisible in these AI overviews.

00:03:38: It's a really clear illustration of how AI is directly talking about your brand.

00:03:42: It's effectively determining your positioning right there in that critical decision framework for buyers.

00:03:47: Wow.

00:03:48: So AI isn't just delivering information, it's actively framing our brands for us.

00:03:52: That raises a really important question.

00:03:54: How do we even begin to measure this new kind of visibility?

00:03:58: This AI driven visibility.

00:03:59: That's precisely what Tiziana Chimbali tackled.

00:04:03: He introduced a compelling new metric, share of model, or some

00:04:07: share of

00:04:07: model.

00:04:08: Yeah, it measures a brand's visibility right within the data sets of large language models.

00:04:13: So it's essentially trying to predict future market share in an AI first world.

00:04:17: It's a crucial shift really from just tracking share of search to understanding your brand's footprint in the actual data that trains the AI.

00:04:26: share of model some powerful concept that sounds a bit abstract though for you know.

00:04:32: day-to-day marketing.

00:04:33: yeah on the theory what's the most immediate practical steps someone could take today to even start influencing their share of model?

00:04:41: Or is it more of a long game?

00:04:42: It's definitely

00:04:42: both, but the immediate practical step really goes back to what Tom Winter and Ollie Hammond suggested.

00:04:47: It's about ensuring your foundational brand content.

00:04:49: You know, your core story, your value proposition, your differentiators is consistently incredibly represented across as many high authority diverse sources as possible.

00:04:58: Right, get it everywhere credible.

00:05:00: Exactly.

00:05:00: This creates those trusted source signals that the LLMs pick up on.

00:05:04: It's basically about becoming a data point of undeniable authority in those training sets.

00:05:08: That makes perfect sense.

00:05:09: Okay, so if brand authority is the new currency for AI search, how do we actually build and deploy that authority effectively?

00:05:17: I guess that brings us to the operational reality of today's marketing, the rise of AI agents in these smart workflows.

00:05:24: What exactly are we talking about when we say AI agents?

00:05:27: So moving on, yeah, let's dive into AI agents and workflows.

00:05:30: You can think of AI agents as specialized autonomous AI programs.

00:05:34: They're designed to perform specific tasks, often chaining together multiple actions to achieve some marketing goal, ideally without constant human intervention.

00:05:42: Okay.

00:05:43: Yung Rosgosh and Laura Steffen both position these marketing agents as like catalysts for totally new business models and processes.

00:05:50: Though they were clear they come with definite operational challenges.

00:05:54: Autonomous AI programs doing tasks sounds incredibly efficient but yeah I can see the complexity too.

00:06:01: Can you give us some real-world examples?

00:06:03: make a bit more concrete what are these agents actually doing?

00:06:06: Sure.

00:06:06: Peter Wong, for instance, outlined a pretty lean AI native stack, mainly for B to B founders.

00:06:12: He uses Claude and its subagents for the actual content creation.

00:06:16: Then Canva for design, Typefuly for distribution.

00:06:19: Adio for capture and enrichment, and something called Relay.app for automated conversion.

00:06:25: And Valeria Pilkovich also highlighted how these out-of-the-box integrations, you know, through tools like Zapier and Make, can really operationalize AI across workflows.

00:06:35: They let different tools talk to each other to create proposals, repurpose content, or enrich CRM, stuff like that.

00:06:41: That's a fantastic illustration of how these tools can be sort of orchestrated.

00:06:45: But for anyone looking to actually implement these, what are the crucial tips?

00:06:49: How do you ensure these agents actually deliver reliable quality results?

00:06:53: You can't just set them and forget them.

00:06:55: Oh, absolutely not.

00:06:56: You're spot on.

00:06:57: Lore Steffen really stressed that agents aren't built in a day.

00:07:00: They need continuous training, testing, quality control, and a crucially explicit human oversight.

00:07:07: Right.

00:07:07: Oversight is key.

00:07:08: And a really important tip for reliability came from Justin Norris.

00:07:12: Break down complex AI tasks into smaller units.

00:07:17: So instead of asking an LLM to do way too much at once, Decompose it like first extract quotes then analyze each one individually.

00:07:25: He found this dramatically improves consistency and quality.

00:07:28: Oh, okay.

00:07:29: And Laura Marquez also championed what she called progressive prompting basically start broad and then gradually refine your questions to the AI to get more relevant and actionable responses.

00:07:38: That's a brilliant point about breaking down tasks.

00:07:40: It feels like a fundamental principle for working with any complex system really.

00:07:44: and didn't Alex Vaca and Michelle Lyvin actually map out different categories of these agents.

00:07:48: Mm-hmm showing how spectacular they're getting?

00:07:50: They did, yeah.

00:07:51: They identified everything from research agents like Klagenet to reply agents like Instantly.ai, sales agents like Attention that extract insights from calls, sourcing agents like Exa, LinkedIn agents like Valley, even scraping agents like Appify, and then full-blown AISDRs like Artisan.

00:08:08: So it's clear the tools exist across the entire go-to-market funnel, but like you said, strategic thoughtful implementation is absolutely key.

00:08:16: Okay, so if these agents can automate complex marketing work workflows, it really begs the question about entire human roles, which brings us to sales and SDR automation, always a hot topic.

00:08:28: The big question everyone keeps asking, can AI fully replace human SDRs?

00:08:37: And often, maybe not entirely, Chris Ritzen shared this cautionary tale of a founder who fired five SDRs, hired one AISDR, and then saw a meetings drop, conversion rates tanked, and he ended up hiring the humans back.

00:08:50: Michael Heiberg elaborated on this.

00:08:51: He explained that those first gen AISDRs often failed because of poor data quality, basically, garbage in, garbage out, which just led to inbox chaos and ultimately missed opportunities.

00:09:04: Samir Jehik also critiqued Salesforce's agent force, saying, look, it's pretty ineffective without really strong training and good quality data.

00:09:12: That's a powerful warning against just rushing into full automation without understanding the, you know, the underlying mechanics.

00:09:19: But it's not all doom and gloom for AI and sales, is it?

00:09:22: Are there successful models emerging?

00:09:24: Absolutely not all doom and gloom.

00:09:26: George Vitko and Jonathan Levy highlighted that the real winners aren't choosing between humans and AI.

00:09:31: They're building what they call hybrid sales machines.

00:09:34: Hybrid

00:09:34: machines?

00:09:35: Yeah, and these hybrid teams are actually outperforming the traditional models on both efficiency and outcomes.

00:09:41: For email outreach, for instance, Alija Kralishin pointed to solutions like JSON AI's approval mode.

00:09:46: Okay, what's that?

00:09:47: It's where the AI drafts the emails, but humans provide oversight and ensure compliance before anything gets sent, which is crucial, especially given Mick Gossett's warning about some AISDRs creating fake LinkedIn profiles in bulk just leading to an exponential increase in spam.

00:10:02: Yikes.

00:10:03: Fake profiles.

00:10:04: Yeah.

00:10:05: And Bill Stathopoulos really emphasized that AI is a co-pilot, not the pilot.

00:10:09: He stressed the absolute need for human input in defining the ideal customer profile, really nailing the offer and setting the overall strategy.

00:10:17: That idea of AI as a co-pilot feels like a much more sustainable and frankly ethical path forward.

00:10:23: Yeah.

00:10:24: We also saw Alan Rucktein describe how deploying two distinct AI agents, one specifically for inbound, one for outbound, significantly improved sales KPIs for one of his clients, that shows effective coordination between AI-driven motions can work.

00:10:37: That's tangible success.

00:10:39: It really is.

00:10:39: And if you want to dive into the numbers, Ulyana Machysovska provided this really compelling ROI comparison.

00:10:45: Human SDRs versus SDR agents specifically in the Netherlands.

00:10:48: Okay,

00:10:48: let's hear it.

00:10:49: Get this.

00:10:49: She calculated that an AI SDR agent costing around If thirty nine thousand five hundred annually could process over three thousand contacts and book maybe twenty thirty meetings per month.

00:10:59: Wow.

00:10:59: Compare that to a human SDR at seventy five thousand annually processing maybe nine hundred contacts and booking eight twelve meetings.

00:11:06: So her projection showed an incremental revenue of three hundred sixty thousand per year and an ROI of around nine hundred percent for the AI agent.

00:11:13: Nine hundred percent ROI.

00:11:15: That's that's almost an unbelievable number if implemented effectively.

00:11:18: But.

00:11:19: Hang on, it also raises a really critical question.

00:11:21: What about the human element?

00:11:23: Amidst all this automation, are we risking losing?

00:11:26: that crucial touch, the thing that truly converts just in pursuit of sheer volume.

00:11:31: That's precisely the concern that Eric Bauer addressed.

00:11:33: He offered this fascinating counterpoint.

00:11:36: He observed that the sheer volume of automated outreach is, ironically, driving some sellers back to what he called high effort, high conviction tactics.

00:11:46: Like what?

00:11:46: Like hand delivering customized cakes to prospects.

00:11:49: Slight chuckle.

00:11:50: customized cakes, seriously.

00:11:52: Seriously.

00:11:53: He argued that instead of just automating outreach, maybe we should automate the intelligence that tells us when not to automate.

00:11:58: You preserve those high effort plays for maximum impact.

00:12:02: And Dan El-Khanim noted that cold email when done right is still the most cost efficient channel, especially when you enhance it with AI, but it absolutely needs that targeting and human oversight.

00:12:13: Hand delivering cakes.

00:12:15: That's quite a strategic leap from mass email.

00:12:17: It really highlights that emotional pendulum swing, doesn't it, from full automation back to hyper personalization.

00:12:23: It's clear AI is profoundly impacting how we sell, but it's also reshaping our our overarching brand and marketing strategy too, isn't it?

00:12:32: Absolutely.

00:12:33: Anjali Mullins pointed out that go-to-market attention seems to be shifting away from just pushing features and more towards brand building.

00:12:40: She actually calls brand the last differentiator in these AI heavy markets.

00:12:44: The last

00:12:45: differentiator.

00:12:45: Yeah, as AI becomes kind of ubiquitous, a strong, clear brand is what really sets you apart.

00:12:51: So brand becomes the ultimate differentiator in an AI saturated world.

00:12:54: That implies we need some very careful strategic vetting of AI tools, right?

00:12:59: How do we make sure AI doesn't accidentally dilute or compromise that hard-won brand reputation?

00:13:04: Well, Suzanne Mora highlighted a framework for vetting AI in your marketing stack that focuses precisely on that.

00:13:10: First, grand protection.

00:13:13: Second, is it solving real unscalable problems to gain efficiency?

00:13:18: And third, ensuring there's measurable ROI.

00:13:21: It's all about building in safeguards and always having a human in the loop strategy rather than just treating AI like some kind of magic bullet.

00:13:28: That makes perfect sense.

00:13:30: It's not just about what AI can do, but what it should do for your specific brand with those safeguards in place.

00:13:36: Anjali Mullins also reinforced that those brand authority signals consistent messaging, credible PR community presence are being prioritized for that.

00:13:44: AI ranked exposure we talked about earlier.

00:13:46: Exactly.

00:13:47: And everyday search behavior is now cited as shaping brand perception and buying decisions, making your brand narrative just more critical than ever.

00:13:54: Exactly.

00:13:55: And Michael Ocean brought up a really compelling point for sales leaders.

00:13:58: Start treating AI like a headcount, not just another tool.

00:14:01: Like a headcount.

00:14:02: How so?

00:14:03: It means giving the AI its own KPIs, assigning a human owner to sort of coach it, and using it strategically to solve specific inefficiencies like, say, after hours need capture.

00:14:16: It's really about accountability and managing AI as part of your team structure.

00:14:21: Treating AI like a headcount, that's a powerful analogy for true integration.

00:14:25: You know, Caroline Healy shared an incredible story about overcoming team resistance to AI.

00:14:30: She started by actually listening to their fears of irrelevance, mainly.

00:14:35: Then she redefined AI's role, not as a boss, but as an intern.

00:14:39: And crucially, she gave team members control over which tasks they wanted to automate.

00:14:44: What were the results of that human-centric approach?

00:14:46: The results were apparently massive improvements in campaign output, lead quality, and team satisfaction.

00:14:52: It just really demonstrates the power of human-centric integration when you're introducing new tech.

00:14:56: Nikki McKenna and Hannah Kalanachenko both underscored this too, while AI can make our lives easier, that human touch remains crucial.

00:15:03: AI isn't going to set your business strategy.

00:15:06: It won't understand those subtle customer quirks or tell your brand story the way a human can.

00:15:10: It should be there to empower humans, help us move faster, see farther, and lead better.

00:15:15: That story really highlights the importance of internal buy-in and smart implementation.

00:15:21: Beyond internal strategy, though.

00:15:23: We can't ignore the growing emphasis on compliance and ethics.

00:15:27: What were some of the key takeaways there for BDB marketers?

00:15:29: Yeah, that came up quite a bit.

00:15:31: Dr.

00:15:31: Phillip Melz and Damia Melle both highlighted things like transparency obligations, IKey rates concerns, and the issue of deep fakes as really central governance topics now.

00:15:41: The advice is clear.

00:15:42: Leaders need to codify policies and controls before scaling AI across customer facing workflows.

00:15:48: It links governance directly to brand protection and trust.

00:15:51: Ultimately, as As Bill Stackopoulos and Scott Jones reinforced, AI isn't here to replace marketers, it's here to amplify the smart ones.

00:15:59: It's about embedding AI where it actually makes a difference, moving beyond the buzzwords to find genuine impact.

00:16:04: Okay, so with all these strategic shifts, the rise of agents, this evolving role of AI, you might be wondering about the tools themselves.

00:16:13: I mean, it feels like there are new AI solutions launching every single day.

00:16:17: How are marketers even navigating this incredibly crowded landscape?

00:16:21: Yeah, it's a lot.

00:16:22: We definitely saw posts with curated tool lists and lean stacks that people claim delivered material time savings, especially for founders and small teams.

00:16:31: Peter Wong and Jason Hunt noted this.

00:16:34: These optimized stacks seem to accelerate delivery and client satisfaction just by streamlining processes.

00:16:39: Right.

00:16:39: So it's really about finding the right mix that works for your specific needs, not just, you know, collecting every shiny new tool that comes along.

00:16:46: And for those who are evaluating, it can feel like comparing apples and oranges with all the different branding GBT.

00:16:51: GEMS projects agents.

00:16:53: Are the major players fundamentally different their core AI capabilities for these custom use cases?

00:16:59: That's

00:16:59: a great question.

00:17:00: Nicole Leffer actually provided a helpful cheat sheet on this.

00:17:03: She clarified that the major suites think chat GPT, Google Gemini, Claude, Microsoft Copilot are broadly comparable for custom AI capability.

00:17:14: Whether they call them GPTs, gems, projects, or agents, the core functionality for creating those custom pre-prompted versions with attached knowledge files is actually quite similar across the board.

00:17:27: So the choice often comes down more to your existing ecosystem preference or maybe specific integration needs.

00:17:32: That's incredibly clarifying, Ashley.

00:17:34: So if the core capabilities are broadly similar, what then becomes the most critical forward-thinking investment for any B to B marketer who wants to truly leverage AI successfully.

00:17:45: Yeah.

00:17:45: Where should the focus really be?

00:17:46: Well,

00:17:46: what's fascinating here, and several people touched on this, Oliver Collie and Durkan Stam referencing Sam Jacobs, they all underscored a really fundamental truth.

00:17:54: AI is only as smart as the data you feed it.

00:17:56: Right.

00:17:57: Garbage in, garbage out.

00:17:58: Yeah.

00:17:58: Exactly.

00:17:59: So the most critical, truly forward-thinking investment isn't just in another AI tool.

00:18:04: It's in creating a single, reliable source of truth for all your marketing data.

00:18:09: That's the bedrock.

00:18:10: That's the indispensable foundation for any truly successful and impactful AI strategy.

00:18:15: Without clean integrated data, even the most sophisticated AI agents are just going to struggle.

00:18:21: Okay, that was a truly insightful deep dive into the latest AI trends, shaking up B to B marketing, all drawn from LinkedIn.

00:18:29: We covered wow everything from that paradigm shift and generative engine optimization and the rise of AI agents to the complex role of sales automation and the crucial enduring importance of brand and human oversight.

00:18:40: a lot to unpack there.

00:18:42: definitely If you enjoyed this deep dive, just a reminder, new deep dives drop every two weeks.

00:18:46: And also check out our other editions covering account based marketing, field marketing, channel marketing, more tech, go to market and social selling.

00:18:54: Thank you so much for joining us.

00:18:55: And yeah, don't forget to subscribe.

00:18:56: That way you won't miss out on our next deep dive into what's really moving the needle in your industry.

00:19:01: So as BDB marketers navigating this incredibly fast moving landscape, the real question is, how would you not just integrate AI?

00:19:09: but truly leverage it to redefine your brand's authority and amplify that human potential.

00:19:14: So think about it as we move forward.