Best of LinkedIn: MarTech Insights CW 34/ 35

00:00:00: Provided by Thomas Allgaier and Frennus, based on the most relevant posts on LinkedIn about MarTech.

00:00:05: in CW-three-four-three-five, Frennus is a B-to-B market research company working with enterprises to optimize their campaigns with account and executive insights far beyond AI.

00:00:17: Welcome to the deep dive.

00:00:19: Today we're cutting through the noise to bring you the top Martek trends we saw buzzing across LinkedIn.

00:00:25: This is from calendar once.

00:00:27: thirty

00:00:28: four and thirty

00:00:28: five Frank and this deep dive It's specifically for you the B to B marketing professional, you know the one looking to understand what's really happening out

00:00:35: there Yeah, and how you can actually apply these insights

00:00:37: exactly to your own strategy.

00:00:39: So we've basically taken a whole stack of insights from some really sharp minds and practitioners in the industry and we've tried to distill them down into, you know, actual intelligence.

00:00:49: Our mission here is really to help you navigate this landscape, because let's face it, it's incredibly fast changing.

00:00:55: Yeah, really.

00:00:55: We want to give you that clarity and perspective you need, but without the usual information overload.

00:01:01: Okay, let's dive in then.

00:01:02: Let's maybe start with a, well, a pretty pervasive challenge for a lot of B to B marketers.

00:01:07: The pressure to do more with less, right?

00:01:11: And often, while struggling with what people call a bloated MarTech stack, it sounds inefficient, definitely, but what's really going on there?

00:01:18: Oh,

00:01:18: it absolutely is inefficient.

00:01:20: Yeah.

00:01:20: And someone like Ron Valencourt really underscored this point.

00:01:24: He said, digital maturity isn't about how many platforms you collect.

00:01:27: Right.

00:01:28: Not just ticking boxes.

00:01:29: Exactly.

00:01:29: It's about clarity in your stack.

00:01:31: It's about making sure people actually use the tools for a high user adoption and then demonstrating real impact.

00:01:38: Without those things, your stack is just, well, it's just digital noise, not generating results.

00:01:44: And then Bruce Millard, he took it even further.

00:01:46: He coined this term Frankenstacks.

00:01:49: Pretty vivid image, isn't it?

00:01:51: Strategic stacks that just devolve into chaos.

00:01:53: You end up with multiple unintegrated tools all doing the same job.

00:01:57: That sounds messy.

00:01:58: It is.

00:01:59: So he's calling for rationalization.

00:02:01: Basically, a ruthless audit.

00:02:03: Kill the redundancies.

00:02:04: I mean, honestly, you don't need five different ABM tools, right?

00:02:06: Probably

00:02:06: not.

00:02:07: And then double down on what genuinely drives leads and revenue.

00:02:11: Focus.

00:02:12: Frankenstacks.

00:02:13: That image, it really pants a picture of complexity, but also maybe hidden problems.

00:02:19: Like, beyond the obvious subscription costs, one of the less visible costs of all that.

00:02:24: disarray.

00:02:25: Well, the complexity itself just becomes this massive derriere.

00:02:28: John McDonald, he pointed out that, and I quote, a forty seven Martek tool stack is why you're failing.

00:02:34: Wow,

00:02:34: forty seven.

00:02:35: Yeah.

00:02:36: He argues that often more tools actually lead to worse results.

00:02:39: And you know, the twenty twenty five state of your stack survey by Martek.

00:02:42: basically confirm this.

00:02:43: A huge number like sixty five point seven percent of marketers said data integration was their biggest challenge.

00:02:48: Over

00:02:48: two thirds.

00:02:48: That's huge.

00:02:49: It is.

00:02:50: So the core insight here is really to master fewer tools but master them deeply.

00:02:55: Don't just keep accumulating more stuff without a clear purpose.

00:02:58: So it's definitely not a case of set it and forget it then.

00:03:01: It sounds like there's this constant almost invisible effort required just to keep these systems from.

00:03:07: I don't know, spiraling out of control.

00:03:09: You've hit on something Matthew Naderberger talked about.

00:03:12: He's this great analogy of entropy in martech.

00:03:15: Entropy.

00:03:16: Yeah, like in physics.

00:03:17: He suggests these stacks naturally drift towards decay and collapse.

00:03:22: Unless you're constantly feeding them.

00:03:24: energy

00:03:24: energy

00:03:25: like governance meetings integration workarounds Rewriting documentation, you know all this stuff that doesn't exactly make it onto a glossy ROI.

00:03:32: slide

00:03:33: right the unglamorous work,

00:03:34: but it's absolutely critical to stop that drift into chaos.

00:03:38: Okay, so if that drift towards entropy is kind of the default state How do companies even begin to reverse that?

00:03:45: How do you build order and maybe a resilience into their mark tech?

00:03:49: It feels like a massive task.

00:03:50: Well,

00:03:50: that's where strategic roles really come into play.

00:03:53: Timo Kovala suggested hiring a marketing architect.

00:03:55: A marketing architect.

00:03:57: Interesting.

00:03:58: Not IT, though.

00:03:59: No, that's the key.

00:04:00: This person is imbooked within marketing or M.O.P.S.

00:04:03: marketing operations, right?

00:04:05: They act as this crucial bridge between the technical side and the functional side.

00:04:09: Got it.

00:04:10: So they enforce conventions they optimize the stacks and they can significantly reduce waste.

00:04:16: and think about this Gartner found that Martek stack utilization is only around thirty three percent

00:04:23: only a third

00:04:24: Wow.

00:04:24: Exactly.

00:04:25: So there's an enormous opportunity there for improvement.

00:04:28: And Grace Campbell also stressed, you know, CMOs need to balance chasing the shiny new AI toy with maximizing returns on their existing Mar-Tech investments.

00:04:37: Get more from what you've already got.

00:04:39: That makes a lot of sense.

00:04:40: Get the house in order first.

00:04:41: Precisely.

00:04:42: And building on that, actually, many of our sources highlighted a really crucial point.

00:04:46: Mar-Tech doesn't fail us.

00:04:48: We fail technology.

00:04:49: Explain that.

00:04:50: Well, Wipowasu tea, for instance, share that most martech failure she sees actually stem from breakdowns in the human element.

00:04:57: Like what?

00:04:58: Like, lack of proper training, processes that don't line up, overlooking change management, which is huge and weak user adoption strategies.

00:05:07: Often the tools themselves are fine, technically, but if the people using them aren't set up for success, it's just.

00:05:13: Not gonna work.

00:05:13: That resonates so much.

00:05:15: It makes me think of Tim Armstrong's thirty-two percent problem.

00:05:19: Oh, yes.

00:05:19: Where like a third of the time is just wasted navigating what he called executional barriers.

00:05:25: He also pointed out, and this is worrying, that seventy-four percent of executives admit their strategies just aren't translated into concrete actions.

00:05:32: There's this huge canyon between strategy and execution.

00:05:35: That's a massive canyon.

00:05:36: Yeah.

00:05:36: And technology alone can't bridge it.

00:05:38: But Tim Armstrong did offer some really practical fixes for that.

00:05:41: Okay, like what?

00:05:42: First, align before you automate.

00:05:45: Get marketing, sales, IT, even finance, all aligned to what success looks like before you buy any tech.

00:05:50: Makes sense.

00:05:51: Second, think workflow, not features.

00:05:54: Map out what you actually need to do step by step, not just what some fancy tool can do.

00:05:59: Focus

00:05:59: on the process.

00:06:00: Right.

00:06:01: and finally build feedback loops.

00:06:03: So execution can genuinely inform strategy and vice versa.

00:06:07: It shouldn't just be strategy dictating downwards.

00:06:09: That's

00:06:09: incredibly practical advice.

00:06:11: So thinking about that bridge.

00:06:14: Where does the marketing operations team fit in?

00:06:16: Are they the ones really meant to be spanning that strategy to execution gap?

00:06:21: Absolutely.

00:06:22: Mike Rizzo strongly reinforces this.

00:06:24: He says, marketing ops pros are the architects of your go-to-market system.

00:06:28: They are not just a campaign support function.

00:06:30: Architects.

00:06:31: I like that.

00:06:32: Yeah.

00:06:32: Their job is to build the foundational infrastructure.

00:06:35: They translate business strategy into scalable systems, into data flows, into processes.

00:06:39: They make sure all the tools talk to each other effectively.

00:06:41: If you're just treating them like ticket takers, while you're missing out on huge strategic value.

00:06:47: Okay, let's shift gears a bit now to specific tools.

00:06:50: Marketing automation platforms, MAPs, seems like choosing the right one and then making it work is kind of a perennial challenge.

00:06:56: It really is.

00:06:57: And what's fascinating here is an analogy from Nikki Leach, she calls it the MAP match.

00:07:02: MAP match, like dating.

00:07:04: Exactly like dating.

00:07:05: She explains selecting an MAP is about finding the right fit.

00:07:09: Does it align with your team's personality?

00:07:11: It's strengths.

00:07:13: And crucially, what are the deal breakers?

00:07:15: It's not just taking off features on a checklist.

00:07:18: You're building a long-term relationship here.

00:07:20: I like that perspective.

00:07:21: It suggests there's a certain timelessness to foundational practices, right?

00:07:25: Regardless of the specific platform.

00:07:27: Are there enduring best practices for working with powerful platforms, maybe like Marketo, that kind of hold true across the board?

00:07:34: Definitely.

00:07:35: Vanessa Budeck shared her five things.

00:07:37: I wish more teams knew about Marketo, but they apply pretty broadly.

00:07:41: Okay, what are they?

00:07:42: Number one, data quality is critical.

00:07:45: Bad data in down tray just magnifies any mess downstream.

00:07:50: Number two, don't underestimate clear naming conventions.

00:07:53: Your future self will thank you.

00:07:55: Oh, I can relate to that one.

00:07:56: Right.

00:07:56: Number three, sales has to trust lead scoring, which means collaboration is key.

00:08:01: Four, structured folders make everything more efficient.

00:08:04: And finally, number five, master the basics before you start chasing shiny new features.

00:08:08: It's all about solid foundations.

00:08:10: Marketo, as you mentioned, it's been a staple for a long time.

00:08:13: In this landscape where everything changes so fast, what makes certain platforms like that endure, despite all the new tools popping

00:08:20: up?

00:08:21: Well, Arm and Wecamp and Colby Dix offer this humorous homage to Marketo.

00:08:27: They called it the cockroach of marketing automation.

00:08:30: That

00:08:30: cockroach?

00:08:30: Okay, that's memorable.

00:08:31: Resilient, I guess.

00:08:32: Incredibly

00:08:33: resilient.

00:08:34: They noted that for really dedicated marketers, its complexity is a feature, not a bug.

00:08:40: It's a platform built for handling intricate real-world customer journeys, and it's just proven its ability to withstand new tools and shifts in the industry.

00:08:48: That's quite an endorsement of its power, but with platforms that are so robust and customizable, What are the potential pitfalls?

00:08:57: How do you make sure all that power doesn't, you know, become a liability?

00:09:00: That's a really important question, managing that power.

00:09:03: Aerial Sasso caution that testing and monitoring any custom builds you do with these automation platforms is absolutely essential.

00:09:09: Custom builds can be risky.

00:09:11: She called them fragile.

00:09:12: Think about it, a single API change somewhere else or a tiny logic mistake in your build, it can lead to serious issues.

00:09:20: Leads not syncing to the CRM, missed data, broken customer journeys.

00:09:24: If you don't have a robust monitoring plan in place, you're basically flying blind.

00:09:29: Ouch.

00:09:30: Okay.

00:09:31: So.

00:09:31: It feels like we're seeing this broader conversation emerge now about how the fundamental role of these platforms, MAP, CRM, is actually transforming.

00:09:41: what's driving that evolution.

00:09:42: Indeed.

00:09:43: Cenk Karakeya put it quite starkly.

00:09:45: He said, legacy marketing automation.

00:09:47: you know, based on static segments, manual campaigns, it's just outdated now.

00:09:52: Okay,

00:09:52: so what's replacing it?

00:09:53: He contrasts it with what he calls agentic AI.

00:09:56: AI that makes autonomous decisions.

00:09:58: It predicts the right customer, the right product, the right moment, and then it executes proactively at a true one-to-one scale.

00:10:03: That's modern marketing, according to him.

00:10:05: Wow.

00:10:05: And Omri Yilmaz also pointed out that CRMs themselves are evolving.

00:10:09: They're becoming AI-driven revenue intelligence platforms, much more central to the stack, kind of absorbing functions, like marketing automation and analytics.

00:10:17: So that sounds like a pretty fundamental architectural shift.

00:10:21: How is that impacting the traditional CRM setups?

00:10:23: Does it expose any vulnerabilities?

00:10:25: Monica Kemmel-Russ had a sharp insight here.

00:10:28: She said traditional CRMs were never built for failure.

00:10:31: not like modern cloud solutions are.

00:10:34: Meaning they weren't designed for the kind of resilience and scalability we expect now.

00:10:39: She highlighted how combining something like AWS with HubSpot using the AWS marketplace offers that resilience, that scalability and makes AI integration much more seamless.

00:10:50: You move from these big monolithic stacks to more flexible, loosely coupled services.

00:10:54: It's about building a more robust, adaptable foundation for the future.

00:10:58: OK, so beyond AI driving this, what other forces are maybe challenging that traditional MAP model and pushing this evolution forward?

00:11:06: My couch outlined four major emerging threat CCs for MAPs.

00:11:10: First, the rise of low-cost open source AI and easy cloud solutions, ThinkModic, or just using AWS services directly, make traditional MAP licenses look pretty expensive.

00:11:19: Right, competition from below.

00:11:20: Exactly.

00:11:21: Second, sales enablement tools like Apollo, Salesloft, they're increasingly replacing workflows that MAPs use to handle.

00:11:29: Interesting, sales tech eating marketing tech's lunch.

00:11:32: Kind of.

00:11:33: Third, ad platforms like Stackadapt, they're building MAP-like features into their own systems, trying to bridge that gap between ad tech and martech.

00:11:41: Hmm, keeping users in their ecosystem.

00:11:43: Right.

00:11:44: And maybe the biggest sort of existential threat he mentioned is AI fundamentally changing the buyer journey itself.

00:11:50: moving towards zero-click answers from search or AI assistance, that could seriously reduce the need for traditional lead nurturing as we know it.

00:11:59: That is a big thought.

00:12:00: Okay, let's focus on AI then.

00:12:02: It feels like we are finally seeing a shift maybe from pure hype to more practical, actionable applications in marketing.

00:12:09: It's not just a futuristic concept anymore, is it?

00:12:11: No,

00:12:12: I think that's right.

00:12:12: Why?

00:12:12: Aaron Goldin's presentation on turning your MarTech stack into a scalable growth engine really emphasized maximizing AI for actual efficiency gains.

00:12:21: We're talking about leveraging AI for personalization, for automations, for data analysis, things that drive measurable growth.

00:12:29: It's about getting concrete value.

00:12:32: not just looking at flashy demos.

00:12:33: And it's unlocking some genuinely exciting new capabilities too, isn't it?

00:12:37: Like hyper-personalized voice experiences.

00:12:39: That feels like a potential game changer.

00:12:41: Oh yeah.

00:12:42: Devish Singh made a really compelling case.

00:12:44: He said AI voice cloning is about to reshape marketing and ad tech.

00:12:48: Reshape

00:12:49: how?

00:12:49: He envisions hyper-personalized voice ads, imagine.

00:12:53: and having a unified brand tone across all your chatbots and virtual agents, it makes voice programmable, scalable, and importantly, emotionally rich.

00:13:03: It adds this whole new dimension to brand communication that could be incredibly impactful.

00:13:07: Okay, but this raises the practical question again, integration.

00:13:10: How are companies actually supposed to connect all these different AI tools and make them work together smoothly?

00:13:15: Are we just building another Frankenstack, but with AI this time?

00:13:18: That's the danger, right?

00:13:20: But MabSeer shared his experience testing something called the Model Context Protocol, or MCP.

00:13:26: It's basically a way to get different AI tools talking to each other seamlessly.

00:13:30: And did it work?

00:13:31: Yeah, he successfully linked Claw the AI model with his Asana, his HubSpot, and even Canva.

00:13:36: He got clearer project tasks out of it, more actionable insights from the CRM data, and even automatic proposal creation.

00:13:43: Wow,

00:13:44: okay.

00:13:44: And on a related note, Matthew Garapy pointed out that DXP's digital experience platforms, they have to adapt to this egentic AI.

00:13:53: And David Sanfilippo argued that even though AI can churn out content like crazy, the CMS, the content management system, has actually never been more important for governance, for structure.

00:14:03: The infrastructure around the AI is absolutely key to making it useful, not just chaotic.

00:14:08: That sounds incredibly powerful, getting different tools to collaborate on complex workflows like that.

00:14:13: But, you know, given how fast AI is evolving, what about reliability?

00:14:16: Is what's possible in theory actually reliable day to day in practice?

00:14:20: That is a crucial caution.

00:14:22: Scott Brinker highlighted this.

00:14:24: He noted a significant gap between what's theoretically possible with the lie right now and what's actually reliable in practice.

00:14:31: Okay.

00:14:32: He referenced Salesforce research's MCP universe benchmark, which basically confirmed this gap exists today.

00:14:38: However, he also stressed that these gaps can close quite suddenly.

00:14:43: So we need to watch this space closely.

00:14:44: Absolutely.

00:14:45: Keep watching, keep planning for it.

00:14:47: So here's where it gets really interesting for me.

00:14:49: How is AI moving beyond just doing individual tasks to actually orchestrating entire marketing functions, becoming almost like an operating system for marketing?

00:14:58: Exactly.

00:14:59: Jonathan Seel gave this really deep dive into Optimizely's Opal.

00:15:03: He described it as an AI orchestration layer.

00:15:06: And it goes way beyond just generating content.

00:15:09: Opal is basically a contextual AI interface that's embedded right into their core modules.

00:15:14: It can parse natural language requests, you just tell it what you want, it pulls in brand context, and then it takes direct action within the platform.

00:15:21: He sees it evolving into a true intelligent marketing operating system.

00:15:25: That

00:15:25: sounds transformative.

00:15:27: It does.

00:15:28: And similarly, Sumit Goenka highlighted Salesforce's Einstein One platform.

00:15:33: He described that as an integrated AI platform built for enterprise data.

00:15:37: The focus there is on trusted, reusable data, models, and actions.

00:15:42: It's all powered by their unified metadata framework and hyperforce.

00:15:46: that's Salesforce's secure infrastructure aiming for responsible scalability.

00:15:51: Okay, let's pivot slightly.

00:15:52: Let's talk about the critical foundation for all of this.

00:15:55: Data.

00:15:56: Data.

00:15:56: Attribution.

00:15:57: Customer Insights.

00:15:59: It still feels like this is a massive hurdle for so many B to B teams.

00:16:02: It's kind of astonishing, actually.

00:16:03: Dave Katz shared this stat he called shocking.

00:16:06: There's something like, forty to fifty percent of companies don't use an attribution system.

00:16:10: Half.

00:16:10: Really?

00:16:11: Yeah.

00:16:12: His advice was blunt.

00:16:13: Prioritize getting attribution working.

00:16:15: Unify your data across channels.

00:16:16: Then worry about customer analysis and targeting.

00:16:18: Don't jump to the shiny new tools if you haven't got that foundation sorted.

00:16:22: And Darrell Alfonso, reflecting on insights from Nadia Davis, reinforced that, look, attribution doesn't have to be perfect, but good enough data still guides better decisions, especially for complex B to B purchases where multi-touch attribution really matters.

00:16:37: The key is just start somewhere.

00:16:39: Good enough data.

00:16:41: I like that practical approach, but how do you actually achieve that good enough state and avoid common pitfalls, like maybe over-investing in complex solutions too early, say something like a CDP?

00:16:51: Well, Nils van Meerjansi, specifically cautioned against investing in a CDP, a customer data platform, if your data maturity isn't there yet.

00:16:59: Why is that?

00:17:00: He noted that the idea of the CDP being the absolute center of everything has actually dropped off a bit.

00:17:06: And many CDPs just don't meet expectations if the foundational data they're supposed to unify isn't solid to begin with.

00:17:11: The

00:17:11: garbage in garbage out, basically.

00:17:13: Pretty much.

00:17:14: And Carla Severin advised data-rich industries, like hospitality, to first just mine and organize existing guest data to figure out what customers want.

00:17:23: She argues that Carla Severin offers a higher ROI for CRM marketing than simply blasting out more emails.

00:17:29: It's about leveraging what you already have, effectively.

00:17:32: It seems like fragmented data on all these different tools.

00:17:35: It doesn't just impact internal efficiency, right?

00:17:37: It must severely impact the actual customer experience, too.

00:17:40: What's the real cost

00:17:41: there?

00:17:42: Linda Fenares highlighted this perfectly.

00:17:44: She stated that nearly sixty-three percent of marketers struggled to consistently deliver personalized experiences.

00:17:50: Wow.

00:17:50: She attributes this to a kind of perfect storm.

00:17:53: Fragmented privacy laws, platform overload, constantly shifting buyer expectations, and intense pressure for ROI.

00:18:00: All of this can lead to what she called message drift and ultimately it erodes customer trust and losing trust.

00:18:07: That's a really high cost.

00:18:08: Yeah, absolutely.

00:18:09: So this really hammers home that recurring theme we keep hearing strategy over technology, putting the customer right at the absolute center of everything.

00:18:16: It's exactly right.

00:18:17: Sundress argued that too many B to B companies build their marketing around the technology rather than building it around their customers.

00:18:25: And that actively hurts their results.

00:18:27: So

00:18:27: what's the alternative?

00:18:28: He advocates starting with deep customer research.

00:18:32: Really understand them.

00:18:33: Build your strategy from those real insights.

00:18:35: Then prove that strategy works with low tech execution first.

00:18:40: Define your KPIs after you know what actually works and only then bring in technology to scale the methods you've already proven.

00:18:47: It's a completely different mindset, you see, prioritizing understanding over just buying tools.

00:18:52: That's a powerful framework.

00:18:54: But thinking about understanding customers with all the new capabilities, how can we leverage some of these emerging technologies to get deeper, maybe more nuanced customer understanding?

00:19:04: beyond just traditional surveys and things.

00:19:06: Well, Marie Marino shared some really interesting insights on using generative AI specifically for analyzing customer conversations.

00:19:13: How does that work?

00:19:14: You can use Gen AI to detect trends, reveal purchase intent, and craft hyper relevant B to B campaigns, all based on what customers are actually saying.

00:19:23: Yeah.

00:19:23: This goes way beyond surveys because you're analyzing huge volumes of unstructured conversational data think, email, chat logs, social media comments in real time.

00:19:34: It leads to much smarter segmentation and messaging because it's based on actual voice of the customer at scale.

00:19:39: Truly

00:19:40: listening at scale.

00:19:41: Okay.

00:19:42: So once we have all this intelligence and hopefully a more customer-centric strategy, how do we translate that into effective conversion?

00:19:50: and to go to market strategies that actually drive revenue.

00:19:53: John

00:19:53: Miller directly challenged the MQL obsession, you know, the constant focus on marketing qualified leads.

00:19:58: Yeah, MQL.

00:19:59: The advocates focusing instead on genuine handraisers.

00:20:02: Yeah.

00:20:02: People showing real purchase intent.

00:20:04: He outlined this multi-tiered framework for tracking progress.

00:20:07: Okay, what does that look like?

00:20:08: You start with tracking target account engagement.

00:20:10: Then you look for meaningful moments like an executive attending a key event.

00:20:13: Especially important, he notes, as AI might start disintermediating some traditional digital signal.

00:20:18: Right,

00:20:18: intense signals might change.

00:20:20: Exactly.

00:20:20: Then you track buying group formation and intense signals within that group.

00:20:25: And finally, you focus on those actual handraisers, demo requests, contact sales, that sort of thing.

00:20:30: It's about identifying deeper, more reliable signals than just a simple lead score someone clicked on.

00:20:35: That's a much more holistic view of the buyer's journey, isn't it?

00:20:41: Okay, on a really practical level, what about web conversion tactics?

00:20:44: Any examples of what's actually working on the ground right now?

00:20:48: Michel Lieben shared a specific inbound workflow example that he said generated an extra twenty to forty meetings a month for his team.

00:20:54: Okay, how'd they do

00:20:54: it?

00:20:55: It involved identifying anonymous website visitors first, then qualifying and enriching those leads using tools like instantly.ai or clay.

00:21:04: Then, re-engaging them with targeted ads and outreach may be using something like Lemlist, and finally nurturing them with personalized email sequences through a tool like Customer.io.

00:21:13: a multi-step, multi-tool process.

00:21:16: Exactly.

00:21:17: And Josh Hill also mentioned that even a big platform like Markito can be a product-led growth or PLG powerhouse.

00:21:23: If the back-end data streams are really well architected, then you have clear GTM motions to

00:21:28: find.

00:21:28: It sounds like agility and efficiency are just absolutely key in this environment, especially when you're trying to build out a comprehensive, yet manageable, martech

00:21:37: stack.

00:21:37: Totally.

00:21:38: Robin Winstanley provided a great example with her optimized FinTech marketing tech stack.

00:21:43: She specifically designed it for agility, efficiency, and handling complex buyer journeys in FinTech.

00:21:49: What did it include?

00:21:50: Her stack had HubSpot as the central backbone.

00:21:53: She used Google Trends specifically for spotting regulatory shifts crucial in fintech.

00:21:57: Dojo AI for predictive analytics and days of driven strategies.

00:22:01: And Adobe Express for creating quick but still on-brand creative assets.

00:22:06: It's about a lean, smart approach that really prioritizes being responsive.

00:22:10: That makes sense.

00:22:10: A tailored agile stack.

00:22:12: Okay, great insights.

00:22:14: So, if you found this deep dive valuable, new sessions drop every two weeks.

00:22:18: Also, check out our other editions on account-based marketing, field marketing, channel marketing, AI and B to B marketing, go-to-market, and social selling.

00:22:27: Yeah, and you know, as Anna Moran observed in one of the posts, there seems to be this... overall disappointment with Martek out there, despite all the shiny decks and the fact that usage is increasing.

00:22:39: That's interesting.

00:22:40: A disconnect.

00:22:40: I

00:22:41: think this deep dive really reinforces that the path to success isn't just about accumulating more tools.

00:22:46: It's really about embracing that strategic alignment we talked about, ensuring your data maturity is solid, and really understanding and nurturing the often overlooked human element within your team.

00:22:56: Well said.

00:22:57: Thank you for joining us on this deep dive into the latest Martek insights.

00:23:00: Don't forget to subscribe for future deep dives.

00:23:03: And maybe a final thought to leave you with, given that constant energy needed to fight martech entropy and bridge that persistent strategy execution gap, are you focusing your efforts on building a truly resilient customer-centric system?

00:23:16: Are you perhaps still just collecting shiny tools?