Best of LinkedIn: Social Selling CW 29/ 30

00:00:00: Provided by Thomas Allgeier and Frennus, based on the most relevant LinkedIn posts about social selling in calendar weeks.

00:00:05: twenty-nine and thirty.

00:00:07: Frenness supports clients with identifying target attendees for events crafting outreach that cuts through the noise And driving qualified registrations Through strategic linkedin engagement.

00:00:17: you can find more info In the description

00:00:19: right.

00:00:19: so We're really jumping right into the deep end today.

00:00:22: Yeah, exactly and you know over the last two years You've probably noticed your posts are getting like a fraction of the views that used

00:00:28: to absolutely everyone's feeling

00:00:30: it Right.

00:00:30: And if you are a strategic B-to-B marketing professional managing a social selling strategy?

00:00:36: You were not imagining it.

00:00:37: I mean data from Jay Klaus.

00:00:40: analyzing over a million posts, it actually reveals that active creator reach has dropped by roughly sixty percent.

00:00:46: Sixty

00:00:47: percent?

00:00:47: I mean...that is just massive!

00:00:48: It's

00:00:49: huge but the algorithm isn't broken.

00:00:51: its uh-it has just evolved into something entirely different.

00:00:55: so today we are breaking down the underlying mechanics of that shift.

00:00:59: yeah We're gonna deconstruct The absolute top social selling trends across the platform right now and Just to set expectations for you We are skipping the basic fluff.

00:01:12: No fluff.

00:01:13: today

00:01:13: exactly we're diving straight into the operational realities of you know how this platform evaluates content, How do you activate your internal teams.

00:01:22: and really?

00:01:23: You actually track this activity down to closed one revenue

00:01:27: because that's sixty percent drop in reach.

00:01:29: it fundamentally changes the math for B to B pipeline generation.

00:01:33: It really does.

00:01:34: We used to rely on a certain volume of top-of-funnel awareness, just make numbers work.

00:01:38: and if that volume is cut by more than half well we have understand machine controls board I mean platform clearly isn't counting hashtags or chronological timestamps anymore.

00:01:48: Oh far from.

00:01:49: The foundational architecture has been completely overhauled.

00:01:52: Right!

00:01:52: The old rules-based algorithm, it's been replaced by a hundred and fifty billion parameter AI model.

00:01:57: Wow!

00:01:57: A hundred and fifteen billion?

00:01:59: Yeah.

00:01:59: And Greg Dristis and Krista Mullian highlighted that this new system is often referred to internally as three sixty brew.

00:02:05: Three

00:02:06: Sixty Brew Sounds like coffee blend

00:02:09: But actually sits in the same architectural family As large language models Like chat GPT.

00:02:14: It doesn't look at post as you know Checklist of keywords.

00:02:18: It evaluates semantic context.

00:02:21: So it's actually reading it?

00:02:22: Exactly, and essentially reads your profile Your entire posting history And you're comment behavior and it weaves together this like cohesive biography of your professional expertise

00:02:34: Which changes the entire paradigm.

00:02:36: I mean We've been taught for a decade to cast the widest net possible.

00:02:39: Oh

00:02:39: yeah spray-and-pray.

00:02:41: right.

00:02:42: But if the platform is writing a biography about my specific expertise, it means its actively filtering out anything that doesn't fit.

00:02:54: And if you drop external links directly into the body of your post, You're losing like fifty to seventy percent.

00:03:15: Of your reach

00:03:16: man.

00:03:17: Which means?

00:03:18: The platform is punishing anything that tries to pull the user away or you know Anything that feels lazily distributed

00:03:24: exactly.

00:03:24: keep them on the platform

00:03:25: and I assume That extends to how we write the hooks too.

00:03:27: Like if you start a post with templated AI language phrases like stop X Start Y Or here's what nobody tells you about B-to-B sales.

00:03:36: This system flags that structural predictability.

00:03:39: right.

00:03:39: yes

00:03:40: It sees it as generic and suppresses.

00:03:43: The AI is incredibly adept at recognizing other AI-generated patterns, but there's a flip side to this.

00:03:49: Okay good give us the Good News!

00:03:50: The algorithm heavily rewards deep topic consistency.

00:03:54: Cindy Dodd noted that niche even so called boring industries like highly specialized aerospace engineering or defense logistics.

00:04:01: they're seeing up to seventy eight percent higher distribution.

00:04:03: Seventy Eight Percent Just for being niche.

00:04:06: Yeah,

00:04:06: because there was less noise and fewer people claiming that specific expertise.

00:04:10: So the system confidently distributes their content to a highly targeted audience.

00:04:14: That makes a lot of sense And The metrics this system uses to measure success.

00:04:18: those have shifted away from vanity engagement

00:04:20: really late.

00:04:21: yeah

00:04:21: Heather Adkins pointed out that saves and well time are the new supermetrics.

00:04:26: so a superficial comment like great insights Barely registers anymore

00:04:30: not at all.

00:04:31: the machine wants to see that a user stopped their scroll Spent two minutes reading a complex breakdown and physically bookmarked it for later reference,

00:04:39: right?

00:04:40: And when you combine that deep topic consistency with high dwell time the distribution model just flips in your favor.

00:04:47: Kristi K. Jones and Tony restel Observe this massive spike-in out of network.

00:04:52: reach

00:04:52: Out of Network meaning people who don't follow you

00:04:54: exactly.

00:04:55: In some cases up to ninety five percent of a post visibility is going to non followers.

00:05:00: Wow The platform is essentially matchmaking.

00:05:03: It takes your verified expertise and pushes it directly into the feeds of strangers who have demonstrated a behavioral need for that exact subject matter.

00:05:11: So it's like LinkedIn stopped being a slot machine where you just pull a hashtag lever hoping for a jackpot of random views, and instead became this highly observant librarian.

00:05:21: This librarian reads the last fifty chapters in your professional autobiography analyzes your actual depth of knowledge then walks across library to hand your book to a stranger who asked a hyper specific question.

00:05:35: I love that That is a brilliant way to conceptualize it.

00:05:38: The librarian knows exactly what the stranger needs, does all their business problem and he knows exactly whether your historical footprint qualifies you to answer it which brings up a critical operational bottleneck for marketing teams.

00:05:50: I mean how do you consistently produce content?

00:05:53: For that AI Librarian without falling into the trap of mass producing What the industry's calling AI slop?

00:05:59: Oh, the AI slop.

00:06:01: Because if machine is judging your unique value you cannot just outsource original thinking to a basic prompt.

00:06:07: No!

00:06:08: You really can't.

00:06:08: The data from Leah Bliss paints very stark picture of this.

00:06:12: Fully Ai written posts are experiencing a thirty-to forty percent drop in reach accompanied by massive reduction and actual human engagement.

00:06:20: People

00:06:20: can smell it a mile away.

00:06:21: They really can.

00:06:23: But here's the nuance Ai assisted post where technology used for ideation or outlining But a human voice drives the actual writing.

00:06:33: They are actually seeing a thirty two percent boost in engagement

00:06:37: and that nuance right there Reveals how the platform actually operates.

00:06:41: Tim S Dodd clarified this dynamic perfectly.

00:06:44: What did he say?

00:06:45: well?

00:06:45: The platform is not strictly penalizing the use of AI tools.

00:06:49: I mean they are actively integrating AI into their own user interface,

00:06:53: right?

00:06:53: They have our own AI

00:06:54: tools now exactly What they're penalizing is the homogenized generic output that AI typically produces when it's left unguided, and they are making that judgment based strictly on reader reaction.

00:07:04: Ah

00:07:04: so its behavior driven?

00:07:06: Yes if the audience recognizes the robotic cadence and just scrolls past it The algorithm kills the reach.

00:07:11: And

00:07:11: in a B-to-B context Katie Reithal makes the argument That trust requires a visible identifiable human.

00:07:18: Absolutely

00:07:18: You might be able to use faceless AI content, like a ten dollar consumer gadget at scale.

00:07:23: But no enterprise software buyer is signing a six figure contract based on a listicle generated by an avatar.

00:07:29: The stakes are simply too high.

00:07:31: B-to-B purchases carry real career risk for the buyer.

00:07:35: but there isn't even deeper systemic issue here from marketing professionals.

00:07:40: Anna Lerner Nezbek warned about this psychological shift she calls cognitive surrender.

00:07:46: Oh,

00:07:46: I want to spend a minute on this because it feels incredibly relevant how marketing teams are operating right now.

00:07:52: It really is!

00:07:53: Cognitive surrender...it basically happens when we stop using our slow careful reasoning and just hand the analytical heavy lifting over an AI.

00:08:03: Yeah And degrades capacity for genuine thought leadership.

00:08:07: When marketers rely on an LLM to summarize a complex industry white paper instead of reading it and wrestling with the data themselves, they lose their ability to form original contrasting opinions.

00:08:17: They

00:08:17: just get average.

00:08:18: Exactly!

00:08:19: They confidently accept AI's flattened average consensus...they end up wearing the blazer as expert but there is absolutely no substantive battle-tested experience underneath

00:08:29: them.

00:08:30: So for the practitioners staring at a blank screen trying to avoid cognitive surrender, The tactical advice from Zoe Hart's field is just stop over complicating strategy.

00:08:40: Keep it simple!

00:08:41: You do not need twelve intricately mapped content pillars.

00:08:46: you need one operational topic cold and write about with plain unpolished language when talking

00:08:56: and pay meticulous attention to the entry point.

00:08:58: Ryan Yackey observed that it is rarely the algorithm that arbitrarily buries a post,

00:09:06: everything.

00:09:07: The first two sentences carry the entire weight of the content, you have to hook the reader immediately by challenging an industry assumption or highlighting a specific painful operational reality.

00:09:18: and from a capacity standpoint Tiffany Spillnally ran the numbers in found that a cadence of three high quality deeply considered posts a week easily outperforms daily forgettable fluff.

00:09:29: less is more.

00:09:29: this sheer volume approach is totally dead.

00:09:32: but let me push back on.

00:09:35: Are we just penalizing efficiency here?

00:09:37: Like if an AI writes a structurally perfect, highly informative post about supply chain logistics.

00:09:43: Why does the B-to-B buyer actually care if he human wrote

00:09:47: it?".

00:09:48: Well because a structurally perfect post demonstrates formatting skill not implementation experience.

00:09:55: B to b buyers are looking for signals that you understand the messy complicated reality of their specific business environment.

00:10:02: I mean, an AI can list the five steps to optimize a supply chain.

00:10:07: But only human practitioner could tell story about how step three completely falls apart when procurement team uses legacy software.

00:10:14: and then how to navigate that internal political friction.

00:10:17: That's

00:10:17: a great point!

00:10:18: Yeah,

00:10:18: it doesn't have battle scars...humans do And buyers trust battle scars.

00:10:22: The messy middle is where the trust has actually built

00:10:24: Exactly.

00:10:25: By the way if you are finding this breakdown of mechanics helpful make sure hit subscribe on whatever app your using to listen.

00:10:31: We these deep dives every two weeks pulling out actionable signals from noise.

00:10:35: so adjust strategies in real time.

00:10:37: Highly recommend subscribing

00:10:39: Which brings us to massive structural challenge for B-to-B brands.

00:10:43: If authentic human voice and actual battle scars are the only currency that buys reach & trust, well a faceless corporate logo is fundamentally disadvantaged.

00:10:53: A brand page cannot have battle

00:10:55: scars.

00:10:55: No it can't.

00:10:57: It's a profound bottleneck.

00:10:59: Distribution has to be routed through individual people.

00:11:02: People buy from people.

00:11:04: Always.

00:11:05: Dan Rosenthal broke down the arithmetic on this.

00:11:07: The average modern B-to-B buying decision involves roughly thirteen internal stakeholders.

00:11:12: Thirteen?

00:11:13: That's a huge committee!

00:11:14: It is,

00:11:15: and single corporate marketing account cannot possibly speak to the highly specific concerns of CFO, chief information security officer or end user all at once.

00:11:25: but a decentralized team of employees utilizing their combined networks in distinct professional lenses can absolutely cover that entire buying committee.

00:11:33: And the robots shifting distribution model are pretty staggering.

00:11:37: AJ Eckstein detailed a scenario where companies stopped muting their internal experts.

00:11:41: What did they do?

00:11:42: Instead of forcing employees to copy-paste those sanitized corporate press releases, they permitted them post freely about the honest unpolished chaos in their daily jobs.

00:11:51: I

00:11:51: love that!

00:11:52: Six team members publishing just eleven posts generated four hundred seventy two thousand impressions and drove over one thousand job applications.

00:12:02: Just from being honest.

00:12:03: Yeah That proves...that most effective corporate influencers are rarely the polished marketing executives.

00:12:10: PJ Catalano emphasized that the real influence lies with your engineers, customer support staff and product managers.

00:12:20: These are people operating in trenches.

00:12:22: When an engineer explains exactly how a piece of technology circumvents common infrastructure failure The technical buyer on other end trusts them implicitly

00:12:30: And Philip Werner and Keisha Fowler backed this up through their own pilot programs.

00:12:35: They found that the content that drove the highest engagement wasn't coming from the employees with massive existing followings or like media training, really?

00:12:43: Yeah it was raw authentic reflections for practitioners simply sharing they're daily operational hurdles.

00:12:49: but I mean let's be honest about the internal friction here.

00:12:53: getting a team of engineers are executives to consistently write content is incredibly difficult.

00:12:58: Usually, marketing just drops a plea into the company-wide Slack channel and it is met with total silence.

00:13:05: Crickets!

00:13:05: Because nobody wants to risk their personal professional brand by acting as mouthpiece for corporate marketing message they didn't even write.

00:13:14: The incentive structure isn't entirely broken.

00:13:16: So Ike Sinkahal proposed radically different incentive structures?

00:13:21: just stop asking for favors and start paying them.

00:13:24: Money talks?

00:13:25: It does!

00:13:26: When they transition from an unpaid corporate scripted advocacy program to actually compensating employees' practitioners, three hundred five-hundred dollars proposed.

00:13:34: in allowing total control over their own voice and angle the program outperformed a legacy model by factor of

00:13:40: four.

00:13:41: That's incredible And it makes sense.

00:13:42: you are essentially taking budget that would have been burned on low converting sponsored ads and reallocating directly into pockets credible sources available.

00:13:51: Alex Lieberman expanded on this dynamic, noting that internal executives are proving to be the most cost effective B-to-B creators

00:14:00: over influencers.

00:14:01: by consistently sharing their strategic level expertise they're driving pipeline generating PR and in some cases facilitating massive funding rounds.

00:14:11: I look at this like we are moving away from a single centralized corporate megaphone standing on the stage, and we're replacing it with a decentralized mess network of fifty highly specialized walkie-talkies.

00:14:24: That's great image.

00:14:25: Each

00:14:26: walkie talkie is tuned to very specific frequency speaking directly a

00:14:32: mesh network that surrounds the entire buying committee.

00:14:35: But having that network operational and capturing top of funnel attention is only the first phase,

00:14:41: right?

00:14:41: Attention doesn't equal revenue.

00:14:43: exactly.

00:14:43: The critical failure point for most marketing teams Is how they transition that attention into close one revenue

00:14:49: because organic impressions do not meet payroll.

00:14:51: So what does the actual conversion architecture look like in this new algorithm?

00:14:56: Well let's ground this on reality check from Devin Reed.

00:15:00: forty percent of B to D deals currently die in no decision.

00:15:05: The buyer doesn't go to a competitor, the initiative just stalls out entirely.

00:15:10: and this happens because the buying committee lacks the collective confidence to sign off on a risky change.

00:15:16: that makes sense.

00:15:17: so the primary function of this decentralized content network is to build that confidence in public months before a sales representative ever schedules a discovery call.

00:15:25: but the sales team cannot and wait for inbound content leads to magically requested demo.

00:15:32: No, they have to work it!

00:15:34: Daniel Disney & Adia Toll stressed that the highest conversion rates occur when you aggressively combine this organic social strategy with targeted cold calling.

00:15:42: It's a one-two punch.

00:15:43: Yeah

00:15:44: The content warms the prospect and establishes credibility And the phone call forces the timeline and closes the deal.

00:15:51: They are interdependent.

00:15:59: Meilan Kong detailed the systemic failure of relying on last-click attribution software.

00:16:04: Oh, Last Click is The Worst!

00:16:06: It's blind to actual BDB.

00:16:08: by your journey... I mean it cannot track a chief operating officer who reads your engineer post during their commute, screen shots and shares in private executive slag channel then directly googles company name three weeks later to request demo.

00:16:26: In that scenario, the CRM assigns one hundred percent of the pipeline credit to organic search.

00:16:31: Exactly

00:16:31: And The Chief Financial Officer looks at marketing dashboard and concludes that social selling program is a complete waste budget.

00:16:38: Precisely To solve this Marketing operations must implement self-replugated attribution

00:16:43: Like asking them directly.

00:16:44: Yeah Adding a mandatory.

00:16:45: How did you hear about us?

00:16:47: Free text field on intake forms.

00:16:49: Furthermore They need track influence pipeline logging every single digital interaction across the entire six-month deal cycle rather than just crowning the final click.

00:16:58: Because of behavioral reality, as Adam Noor highlighted is that the vast majority are lurkers.

00:17:04: Yes!

00:17:05: Silent lurkers?

00:17:06: Up to ninety percent of leads you eventually close will never publish their own content and they'll never publicly comment on yours.

00:17:13: Never.

00:17:14: They are a silent majority watching your mesh network of walkie-talkies until the exact quarter they have budget to deploy.

00:17:21: Which means, The actual selling relies entirely on monitoring intent signals behind the scenes.

00:17:26: Right.

00:17:27: Nancy Denafrio, Aidan Collins and Eduardo Schuch detailed operational frameworks for this.

00:17:33: Your sales development reps need to monitor who is repeatedly viewing the profiles of your executive team.

00:17:40: Okay

00:17:41: Who was engaging with competitors?

00:17:42: technical tear down.

00:17:44: who within your target account list just changed roles or secured a new round of funding.

00:17:49: You're looking for the digital footprint?

00:17:51: Exactly, you score those digital footprints against your ideal customer profile and then shift conversation into direct messages.

00:17:57: But wait let me challenge practicality.

00:18:00: What's concern

00:18:01: If our most valuable buyers are intentionally lurking in shadows and deliberately avoiding public engagement?

00:18:08: how does sales rep transition that to a direct message without coming across as like digital stalker.

00:18:15: It's a very fair question and it is critical distinction to make.

00:18:19: Monitoring intent signals are not stocking, but active listening.

00:18:23: Active listening?

00:18:24: Yeah if potential buyer walks into physical showroom spends fifteen minutes analyzing specific piece of machinery competent sales professional approaches them answer questions.

00:18:34: That was good service!

00:18:36: Digital intent requires the exact same contextual awareness.

00:18:39: You just have to be careful not to reveal the surveillance mechanism, like you don't send a message saying hey I saw you looking at my CEO's profile?

00:18:46: Exactly do NOT DO THAT!

00:18:48: You reach out with contextual relevance...you message them saying i notice your team is expanding its footprint in this specific sector based on the operational challenges we typically see at this stage.

00:18:59: here is a technical resource you might find useful

00:19:02: so it's value-led.

00:19:03: It is about providing utility at the precise moment of need.

00:19:07: But there are massive operational pitfalls here if you get the execution wrong.

00:19:12: Connor Paulson and Manny McEwen audited several failed social selling strategies,

00:19:19: Do not

00:19:22: fully automate your outreach sequences.

00:19:24: The AI algorithm can detect the lack of human variance, and it will aggressively filter your messages right into the hidden other inbox.

00:19:32: Oh yeah you'll never be seen.

00:19:33: Second do not pitch.

00:19:35: slap a prospect in the very first message.

00:19:38: You have to lead with their operational problem Not Your Product Solution.

00:19:42: Nobody wants a pitch on that first interaction.

00:19:44: And finally, stop leaving generic congratulations on job update notifications just to check a box in your CRM.

00:19:51: It is so transparent because it completely blends into the noise.

00:19:54: You look exactly like the fifty other automated bots sending this same congratulatory note.

00:19:59: Exactly The strategic play is to wait three weeks research new mandate.

00:20:03: they were hired execute and check-in with highly specific insight related their role.

00:20:09: It requires intense patience

00:20:12: not a frantic end of quarter sprint.

00:20:14: It really is, and you know before we wrap up there's one final forward-looking strategic shift that we need to address.

00:20:22: What's

00:20:22: that?

00:20:23: Chris Long and Terry Heath brought up massive emerging factor AI.

00:20:28: search engines like ChatGPT and Claude are actively summarizing the web to answer user queries.

00:20:35: When they formulate those answers, They are scanning digital footprints for verified evidence of expertise.

00:20:41: So their reading LinkedIn too?

00:20:42: Yes

00:20:44: The consistency your headline Your newsletters and deeply technical posts.

00:20:48: Their building a permanent digital knowledge graph.

00:20:52: When a buyer asks an AI engine for the best vendor in your specific niche that Engine will cite.

00:20:57: The most consistent authoritative footprints it can find.

00:21:00: so It's not just about the feed anymore.

00:21:02: No, the ultimate question you need to be asking yourself right now isn't Just how?

00:21:05: You reach A human buyer on a chronological Feed.

00:21:07: today it is are you systematically writing To train the ai engines of tomorrow?

00:21:13: That Is something to think About.

00:21:14: If you enjoyed this episode, new episodes drop every two ricks.

00:21:17: Also check out our other editions on Field Marketing, Martech AI and B-to-B.

00:21:22: go to Market, ABM & Channel Marking in Partner Ecosystem.

00:21:25: Thank You for joining us for the deep dive into the underlying mechanics of social selling.

00:21:29: Make sure you hit subscribe And we will see you next time.