Best of LinkedIn: Account-based Marketing CW 12/ 13

00:00:00: Provided by Thomas Allgaier and Frenus, based on the most relevant posts on LinkedIn about account-based marketing in CW.

00:00:06: twelve and thirteen.

00:00:08: Frenuse is a B to B market research company working with enterprises to optimize their campaigns With Research Grade Account Profiling And Insights.

00:00:16: You can find more info In The Description.

00:00:18: Absolutely

00:00:19: So, welcome to today's Deep Dive.

00:00:21: We are really thrilled to have you with us today.

00:00:25: Our mission for this one is cut through all the noise and deliver the absolute top account based marketing trends that we've seen sweeping across LinkedIn over calendar weeks.

00:00:35: twelve-and-thirteen Yeah!

00:00:36: Basically aggregated most vital insights from BtoB Marketing Professionals And we're going to synthesize them right here.

00:00:42: so don't go scrolling for hours

00:00:44: Exactly.

00:00:45: But

00:00:45: before

00:00:46: I get into modern mechanics of how these ABM campaigns actually work today, I feel like we need to establish a baseline.

00:00:51: Like if we look back just a few years what did the standard approach to ABM actually looked like?

00:00:57: I mean honestly when you think of The Old Approach...the best mental model is it's like a medieval canon.

00:01:03: Oh!

00:01:03: A Canon right.

00:01:04: Yeah You Just Think Of Blunt Force.

00:01:06: You pack the barrel with as much gunpowder is possible, which in this case it's just massive marketing budgets and completely generic messaging.

00:01:14: you aim In the general direction of your target market And you fire

00:01:18: right?

00:01:18: The goal was to make the loudest noise possible

00:01:20: exactly.

00:01:21: Just hope the shrapnel hits a decision-maker somewhere.

00:01:24: Yeah Which Is wild To think about now.

00:01:27: but honestly for A long time that brute force method Was the default setting For btob companies.

00:01:32: It was treated as this massive, incredibly expensive broadcast mechanism.

00:01:37: Which was completely unsustainable.

00:01:39: and based on the aggregated posts from last two weeks The overarching context here is that the cannon has just entirely broken.

00:01:47: Account-based marketing is undergoing this fundamental structural shift right now.

00:01:52: Yeah it's not a side project anymore.

00:01:54: No!

00:01:54: Not at all...it no longer a localized marketing campaign run by some siloed team We are seeing evolve into predictable revenue engineering bottle.

00:02:03: The days of treating your target accounts to a spray-and-pray approach are officially over.

00:02:08: So let's actually unpack the mechanics of that shift, because first major conversation dominating the feeds over the last two weeks is complete rejection of pipeline volume.

00:02:18: Yes, finally Right it moving away from volume in favor of pipeline quality velocity and just hard math Because for years the ultimate brag from a marketing leader was walking into a board meeting and pointing to this massive bloated pipeline.

00:02:33: Oh, yeah Just looking at the sheer dollar amount

00:02:35: exactly.

00:02:36: But high pipeline volume is actually a dangerous vanity metric if you look under-the-hood and realize None of those deals are actively moving through the stages.

00:02:45: Yeah,

00:02:46: a bloated pipe line essentially functions like a smoke screen for deal drag.

00:02:51: Debjit Sen made a brilliant point about this specific dynamic.

00:02:54: Oh,

00:02:54: what did he say?

00:02:55: He argued that in account-based go to market motions so you know the overall strategy of how a company Prices and sells to a target audience.

00:03:03: success isn't about opportunity counts right?

00:03:06: it Isn't about multi touch attribution reports That look pretty on a dashboard.

00:03:11: It is fundamentally About How consistently your strategic accounts are progressing through The buying journey.

00:03:18: Okay, so if I'm understanding this right the pipeline itself isn't the asset.

00:03:22: The velocity is exactly it's like.

00:03:25: Think of a like an air traffic control tower.

00:03:27: If you have five hundred airplanes circling the airport indefinitely.

00:03:31: that Isn't a successful operation?

00:03:33: No

00:03:33: That's a nightmare

00:03:34: Right!That Is A crisis waiting to happen.

00:03:36: a successful Operation is having fifty planes approach and land smoothly one after the other.

00:03:41: that's a great way To put It.

00:03:42: Thanks.

00:03:43: I just think if your sales and marketing teams feel incredibly busy but you're most important target accounts are circling endlessly in those early discovery stages, the system is failing.

00:03:53: Yeah

00:03:53: that's a perfect analogy!

00:03:55: And getting these planes to land requires a flawless ideal customer profile or ICP.

00:04:00: Right the ICP?

00:04:01: For the list of your ICPs it's an exact blueprint for the company which gets the most value from your product.

00:04:08: But Ramon K Singh showed pretty hard truth about this on LinkedIn.

00:04:11: Oh yeah, I saw that post.

00:04:12: Yeah he pointed out... Wow!

00:04:28: Which means targeting them with heavy resources just because they look right on paper is a massive waste of capital.

00:04:34: Exactly!

00:04:35: You are essentially sending like high-end executive gifts and highly polished expensive ads to a brick wall?

00:04:42: Yep, your activity metrics will go through the roof but the actual revenue pipeline remains entirely stagnant.

00:04:47: right Sing makes it really clear that the accounts worth running full resource heavy enterprise strategy against have to possess two things simultaneously they need that strict ICP fit And They must be exhibiting an active buying signal.

00:05:01: Like what kind of signal

00:05:03: It could be a recent executive change, and new round of funding or maybe a major strategic shift in their public filings.

00:05:09: Okay but the problem I see constantly though is how companies built that baseline blueprint in the first place like How do you actually fix a broken ICP?

00:05:18: That's the million dollar question

00:05:20: because most organizations seem to fall into one-of two traps.

00:05:23: Either they cast the net so wide that their ICP is basically anyone with a pulse and budget.

00:05:28: Right, everyone's our customer track?

00:05:30: Exactly!

00:05:31: Or... They create an ICP SO incredibly narrow & specific That their sales team can't even find those people in the database.

00:05:39: But Hailey Martin shared A highly practical framework for solving this exact

00:05:44: issue.

00:05:44: Oh i love her framework.

00:05:45: it's so ruthlessly pragmatic

00:05:47: It really is.

00:05:47: She suggests focusing on three distinct layers to refine your targeting.

00:05:52: The first layer focuses entirely on reachability.

00:05:54: Meaning who can you actually get in touch with?

00:05:56: Exactly, Who Can You Actually

00:05:58: Reach?!

00:05:59: If your theoretical ICP is based on highly specific data points that you cannot filter or target within the current tech stack... That ICP completely useless to front line teams!

00:06:09: Yeah.

00:06:09: so if a perfect customer uses a very specific legacy software but there's literally no database on earth that legally provides you information then you just have to abandon it.

00:06:21: Precisely, you have to be realistic.

00:06:23: Then layer two shifts to velocity.

00:06:26: Right

00:06:26: who buys the fastest?

00:06:27: Yeah and this is counterintuitive for a lot of enterprise teams because your best ICP often hides in your fastest sales cycles not your biggest most glamorous logos.

00:06:37: Oh absolutely

00:06:38: If a mid-market tier closes in three months while The Enterprise Tier takes eighteen months And requires massive discounts.

00:06:45: Your math might dictate focusing on the Mid Market.

00:06:48: Make the Math work For You.

00:06:50: And finally, layer three looks at the company stage.

00:06:52: An early-stage startup trying to establish product market fit requires a drastically different messaging approach than mature publicly traded enterprise focused on risk mitigation.

00:07:03: Yeah that changes entire dynamic.

00:07:05: Once you have that math locked down and stripped away vanity metrics to focus velocity in pragmatic ICP You hit next major operational hurdle Which is... Well!

00:07:14: The exact company you want target.

00:07:17: But an enterprise isn't a single entity.

00:07:20: It's a complex web of human beings.

00:07:22: Oh, right.

00:07:23: So figuring out exactly who inside that account you need to engage with and when is where the strategy shifts from The company level down to the Human Level.

00:07:32: Broad account targeting is rapidly becoming obsolete.

00:07:36: Yeah, it really is.

00:07:37: It's being replaced by precise surgical engagement with specific members of a buying group and Shimon Benayoun shared an interview with Nick Mason that captured this transition perfectly.

00:07:48: Oh

00:07:48: the signalverse concept.

00:07:50: yes The signal verse.

00:07:51: I want to linger on this because the mechanics of the signal verse are critical for you the listener to understand.

00:07:56: look Everyone in the B-to-B industry has access to the exact same third party intent data.

00:08:02: Right, everyone's buying the same list?

00:08:03: Exactly!

00:08:04: Your competitors are buying the generic lists from the same datavendors that you're.

00:08:08: They all know certain accounts are broadly surging an interest.

00:08:11: so if every one has a map where is your competitive edge?

00:08:15: The Edge lives.

00:08:16: how combine shared data with proprietary ecosystem.

00:08:20: Explain it more.

00:08:21: Sure… Third Party Data is just collection of digital breadcrumbs scattered across internet.

00:08:27: The Signalverse is about taking those shared signals and interpreting them alongside your own first-party data.

00:08:34: Ah, like the specific ways that individuals are interacting with a unique website?

00:08:38: Exactly!

00:08:39: Your websites, emails or webinars... It's building an ABM architecture learns and compounds its intelligence over time, rather than just reacting to generic alerts.

00:08:50: And Trinity Nguyen offered a highly concrete example of what this looks like on the front lines.

00:08:56: She pointed out the stark difference between account-level data and contact level data.

00:09:01: This is such a crucial distinction.

00:09:03: It

00:09:03: really is if your system generates an alert that says Acme Corporation is researching your topic.

00:09:10: That is incredibly weak, it's almost useless data.

00:09:12: Yeah

00:09:13: let's walk through the reality of an SDR or sales development rep receiving that alert.

00:09:17: they get a notification about Acme corporation.

00:09:20: then They have to toggle between five different software tools

00:09:23: scouring LinkedIn right

00:09:24: Scouring linked in To guess who out of acmes?

00:09:29: Five thousand employees might be the one doing the research?

00:09:31: yeah And they usually gets wrong.

00:09:37: Absolutely no idea what they are talking about.

00:09:40: But when you shift to the contact level, The entire workflow transforms.

00:09:44: The alert doesn't just name the company right?

00:09:46: It says Sarah Chen VP of Revenue Operations at Acme Corp researched your specific pricing page three times in last seven days.

00:09:54: That is wild!

00:09:55: The SDR wakes up with investigative research already completed

00:09:59: Exactly and for context Revenue Operations is the team that manages the technology and processes for sales in marketing.

00:10:06: So knowing that the VP of that specific department has actively engaged, it's just absolute gold!

00:10:12: The context is baked right into.

00:10:15: I

00:10:28: mean, i get that reaction

00:10:29: because if a sales rep calls the prospect five seconds after they download a white paper it usually creates immediate friction and distrust.

00:10:37: Yeah That Friction is incredibly real but It happens when teams misinterpret what intent data Is actually for.

00:10:45: Eloise Todd addressed this exact behavioral flaw on LinkedIn.

00:10:48: she wrote This fantastic line bro

00:10:50: was it?

00:10:51: She said raising A hand doesn't Mean.

00:10:54: They want to hold yours.

00:10:55: oh

00:10:55: wow That is good right.

00:10:58: far too many ABM teams see a single intense signal and immediately trigger A highly aggressive twelve-step sales sequence.

00:11:05: They treat curiosity as a request for a high pressure sales pitch,

00:11:09: which is the worst thing you can do

00:11:10: exactly.

00:11:11: Todd argues forcefully that intent data exists for prioritization, not necessarily for immediate activation.

00:11:17: You use the data to know where your sales team should focus their research?

00:11:22: Not as an excuse to kick down the prospect store!

00:11:24: Yes

00:11:25: you are looking for subtle signs at an account is warming up and That allows marketing to quietly surround The buying committee with relevant content before sales ever makes a direct introduction.

00:11:35: And I'll be expanded on this idea of subtle observation beautifully.

00:11:39: She advises teams to look way beyond basic form fill.

00:11:43: Oh, absolutely the forms are too late.

00:11:45: Yeah someone filling out a contact us forum on your website is Your primary signal.

00:11:49: you Are completely blinds.

00:11:51: The entire journey that happened before they decided To raise their hand.

00:11:54: by the time They fill at That Forum they have likely already made Their decision

00:11:58: yeah?

00:11:58: They just want the pricing.

00:11:59: At that point ollie B suggests observing person level Website behavior

00:12:03: like.

00:12:03: what specifically Like?

00:12:05: are they leaning into the highly technical product documentation which signals deep evaluation, or are they just browsing the home page?

00:12:13: Which signals casual curiosity.

00:12:16: Even more powerfully she points toward leveraging conversational intelligence tools

00:12:21: like Gong

00:12:22: exactly like gong.

00:12:23: and for those unfamiliar gong And similar platforms record transcribe an use AI to analyze actual sales

00:12:30: calls.

00:12:30: right but Exactly how you extract value from that is what matters.

00:12:34: Ali B suggests mining Those call transcripts.

00:12:37: What specific objections keep repeating in the early discovery phases across your target accounts?

00:12:42: Oh, that's smart.

00:12:42: Where exactly are the deals?

00:12:44: stalling

00:12:44: Exactly and marketing can take those raw human objections And build highly targeted campaigns That answer those concerns before the prospect even has to ask deeply without ever being aggressive.

00:12:58: Okay, but the mechanical reality of this is incredibly daunting!

00:13:02: It is a lot of work...

00:13:03: Yeah I mean we are talking about mapping complex buying committees tracking individual website behavior analyzing call transcripts and prioritizing outreach across hundreds of target accounts simultaneously.

00:13:16: doing that manually sounds like a recipe for total team burnout.

00:13:19: Oh, one hundred percent.

00:13:20: So how do go-to market teams actually execute this level of granular tracking without just exhausting their staff?

00:13:27: Well coping with that sheer volume of data brings us to the integration of artificial intelligence within the modern tech stack.

00:13:34: The data requirements we're discussing necessitate a fundamentally different approach to daily ops.

00:13:39: the speed at which AI is resolving these bottlenecks Is just staggering.

00:13:43: right now it

00:13:43: really is and Alper Yerder shared an anecdote That perfectly illustrates this acceleration.

00:13:49: Oh, the list building one.

00:13:50: Yes!

00:13:51: So he sat down to perform a standard routine task for an SDR.

00:13:55: He needed to build and enrich A List of European B-to-B SAWS founders

00:14:00: Which is usually in nightmare.

00:14:01: Right In a manual world.

00:14:03: this involves finding venture capital portfolios scraping company data cross referencing those companies against the firm's ICP Manually verifying hundreds email addresses and formatting spreadsheet.

00:14:16: That is easily a three-hour task of pure administrative

00:14:20: friction.

00:14:21: in what, like a fraction of the time?

00:14:23: Eleven

00:14:23: minutes.

00:14:24: Wow!

00:14:24: Yeah he managed to complete that entire workflow in eleven minutes.

00:14:28: He connected Claude The AI model directly to Apollo which is a massive B-to-B contact database

00:14:34: Right...He

00:14:35: used natural language To ask the AI to pull target accounts from specific VC portfolios.

00:14:40: He then had the AI automatically score those new accounts against his rigid ICP parameters right there In the chat interface.

00:14:46: That's

00:14:47: incredible.

00:14:47: And finally, the AI queried Apollo to return fully verified contact cards.

00:14:52: Eleven minutes to accomplish what used to take three hours of grueling manual labor...

00:14:56: ...and you know when you abstract that out into a broader organization it isn't just about making an SDR slightly faster.

00:15:04: It is completely restructuring the role of the account executive The

00:15:09: AEs right?

00:15:09: The senior reps whose primary job was actually close their revenue Exactly

00:15:14: And Miles Cain shared that his operations team is actively building a roadmap of nine distinct AI agents designed specifically to strip non-selling activities away from their AEs.

00:15:26: Nine

00:15:26: agents?

00:15:26: That's intense!

00:15:27: Yeah, the architecture these agents are fascinating.

00:15:30: They're building a signal agent that operates autonomously in the background, scanning target accounts daily for trigger events like fresh executive hires or new product launches.

00:15:40: Oh wow!

00:15:41: They also have meeting prep agents who listen to CRM data and generate comprehensive pre-call briefing real time.

00:15:47: Complete

00:15:47: with contact intelligence and recommended discovery questions I imagine?

00:15:51: Precisely they are even building deal acceleration agent.

00:15:54: What

00:15:54: does this do?

00:15:55: Imagine an AI instantly analyzes the transcript from a discovery call, identifies the core business pain points.

00:16:03: The prospect mentioned and automatically generates a formatted business case document for the buyer champion to take straight to their CFO.

00:16:11: that is wild.

00:16:12: so the ultimate goal as an AE who spends absolutely zero time on administrative research or formatting emails

00:16:19: right allowing them To dedicate one hundred percent of our cognitive energy to actual selling.

00:16:23: this paints A picture of a hyper efficient sales utopia But I think it forces a highly uncomfortable question for you, the listener.

00:16:32: Which

00:16:32: is?

00:16:32: What happens to the human marketer in this heavily automated world like if AI pulling lists writing pre-call briefs scoring intent data and drafting follow up emails.

00:16:42: What is the strategic role of human beings on the marketing team?

00:16:46: Yeah,

00:16:46: that's an existential question right there.

00:16:48: And Alex Brachaw and Michelle Bee provided essential clarity to this on LinkedIn.

00:16:52: What do they say?

00:16:53: Alex points out a glaring flaw in current AI outputs.

00:16:56: A lot of AI generated value propositions and cold emails look incredibly polished on surface

00:17:02: Right!

00:17:03: They sound very professional

00:17:04: But when a human expert actually digs into copy it often lacks any real nuanced account specific insight.

00:17:12: AI is an absolute miracle worker when it comes to rapid research, generating options and scaling data processing.

00:17:19: But It has no lived experience.

00:17:21: you still absolutely require human judgment.

00:17:25: Which specific business problem is actually worth solving for the client?

00:17:29: Yeah, and AI cannot understand the political dynamics of a target company's boardroom.

00:17:33: It doesn't know why your company was founded or the philosophical nuances of your market positioning Exactly!

00:17:40: And Michelle B highlighted this exact issue referring to it as The Governance Gap.

00:17:44: The governance gap?

00:17:45: I like that.

00:17:46: yeah...the

00:17:46: underlying technology has literally never been more capable.

00:17:49: You can execute in hours what used to take weeks of coordination, but the board of directors does not care that your marketing team is using exciting new AI tools.

00:17:58: No

00:17:58: they definitely don't!

00:17:59: They care that the revenue pipeline is predictable and growing.

00:18:02: so The technology Is virtually perfect.

00:18:05: But the governance gap meaning That strategic human oversight required To stitch these disparate AI agents into a cohesive Predictable Revenue engine is wider And more dangerous than ever.

00:18:17: The AI needs a human to set the coordinates.

00:18:19: That's exactly it, and you know we've spent this time thoroughly examining that digital architecture right?

00:18:26: Yeah!

00:18:26: The hard math of pipeline velocity...the contact level tracking...AI integrations.

00:18:31: but digital theories eventually have to survive contact with the physical

00:18:35: world And that is where gets messy

00:18:37: Right.

00:18:38: Recently, practitioners gathered at the European ABM Forum in Amsterdam specifically to discuss what happens when you try and operationalize these strategies across disparate regional teams.

00:18:48: And moving from digital theory to operational reality exposes a lot of friction.

00:18:53: It really does.

00:18:54: Ingrid Archer actually delivered a keynote insight that reframes how we should look at the timeline for this deal.

00:19:00: She noted that traditional B-to-B buyer journey is stretching rapidly into two completely opposite directions The

00:19:05: shift left & right concept

00:19:07: Yes.

00:19:08: She argues that modern marketers need to simultaneously shift left and shift right because the old linear funnel model of awareness, consideration in decision is just fundamentally dead.

00:19:21: It's gone.

00:19:22: The reality today is most enterprise buyers have already constructed a mental shortlist of vendors before they even initiate formal trackable research.

00:19:30: Right

00:19:31: Think about buyer journey like building high speed rail line.

00:19:35: Shifting left means your marketing team has to act like the advanced surveyors.

00:19:40: You have to be miles ahead of the train, surveying the landscape and laying the foundational tracks of brand trust and awareness long before the buyer even realizes they need to travel.

00:19:49: Because if you wait until they announce that their looking for a train, your competitors have already built the station.

00:19:54: Exactly!

00:19:54: You have to be on that mental shortlist day one.

00:19:57: And shifting right is recognizing that work doesn't stop once the contract has signed and trains leave this station

00:20:03: Which so many teams forget

00:20:05: They do.

00:20:06: You have to continuously maintain the tracks behind the train, you have to build post-sale advocacy.

00:20:12: Ensure that client actually experiences a deep value your sales team promised and engineer pathways for account

00:20:19: expansion.".

00:20:19: But

00:20:20: for that massive end-to-end rail line to function... The internal teams building it must be flawlessly.

00:20:26: Aligned.

00:20:27: Oh,

00:20:27: yeah.

00:20:27: And Lisa Okira made a vital point in Amsterdam about this convergence of sales and marketing.

00:20:32: She argued forcefully that Marketing must completely abandon the practice of reporting mere activity metrics to the sales

00:20:39: team.

00:20:39: Handing is sales leader or spreadsheet?

00:20:41: That shows high click-through rates Or open rates.

00:20:44: it's just useless.

00:20:45: It really is.

00:20:46: marketing has to translate those digital signals into actionable conversation entry points

00:20:51: and The mechanics of that translation are where most companies fail.

00:20:54: Why do you think that is?

00:20:55: Well, if marketing throws an alert over the fence Right.

00:21:06: If you cannot answer that question, You have a massive operational disconnect.

00:21:10: So marketing has to translate the fact That the prospect read three articles about compliance Into specific suggested email opening About upcoming regulatory changes

00:21:20: Exactly giving them hook.

00:21:22: And once Marketing provides that translated entry point The physical speed of execution becomes final bottleneck.

00:21:29: Edwina Denler shared a staggering operational statistic at the forum.

00:21:33: I remember this one.

00:21:34: Responding to a qualified signal in under five minutes yields

00:21:45: That is insane.

00:21:46: Right, when you compare that under five minute window to the average B-to-B response time which hovers around a lethargic forty seven hours The competitive advantage becomes glaringly obvious.

00:21:57: Yeah if you wait fourty seven hours To respond to a buyer signal they have either already solved their immediate problem lost interest or worst of all They've already engaged deeply with a competitor who answered the phone immediately.

00:22:08: So it proves that all of the sophisticated technology, The SignalVerse, Deep Intent Tracking and Nine Specialized AI Agents are ultimately engineered to optimize timing.

00:22:18: Exactly!

00:22:19: The digital signal tells you exactly when the window of opportunity opens... ...the marketing translation tells human rep what to say... ...and automated AI architecture ensures message is delivered before a five minute window closes.

00:22:32: It really solidifies the reality that account-based marketing is no longer just a tactic deployed by few creative people.

00:22:39: it has to function as the core operating system for modern B-to-B growth.

00:22:44: Absolutely

00:22:44: Well, we have covered immense ground today moving from the chaotic blast of The Medieval Canon To the highly engineered precision Of Modern Revenue Ops.

00:22:54: But before we sign off there's one final lingering concept That challenges everything We Just Discussed.

00:23:00: Oh A curveball.

00:23:01: Yeah,

00:23:02: we have spent this entire deep dive obsessing over efficiency.

00:23:05: We talked about how to track the exact individual showing active intent.

00:23:09: How do you use AI?

00:23:10: To build lists in eleven minutes and how to execute outreach In under five minutes.

00:23:14: that Steve Armenti shared a perspective on LinkedIn That completely inverts This entire methodology.

00:23:19: right

00:23:19: The ninety-five percent problem

00:23:21: exactly?

00:23:22: our mentee pointed out A massive blind spot in this hyper-efficient model, most modern B to D companies are dedicating one hundred percent of their technological infrastructure.

00:23:32: To fighting over the exact same five percent of accounts.

00:23:35: Yeah

00:23:36: they're obsessed with the five percent that are actively in market The ones already researching...the ones throwing off those trackable digital signals

00:23:43: But mathematically that leaves a massive void.

00:23:46: What happens to the other ninety five percent?

00:23:49: Of your target market?

00:23:50: That is the crucial question to leave you today.

00:23:53: What about the ninety-five percent of your ideal perfect Fed accounts that are not showing any digital signals simply because they do Not even know.

00:24:01: They have a problem yet, right?

00:24:02: If you were only building complex radar systems to catch The five percent who we're already flying You are completely ignoring the vast majority Of your future revenues sitting on the runway.

00:24:13: so true.

00:24:13: So the question to mull over as you look at your own strategies this week is This how Are you actively creating demand and Building foundational trust with the accounts that aren't signaling at all, so when they finally do enter a buying cycle you are already

00:24:51: calibrate the machinery, and start engineering your revenue.

00:24:54: We will see you next time!