Best of LinkedIn: Social Selling CW 15/ 16

00:00:00: Brought to you by Thomas Allgeier and Frenus, this edition highlights key LinkedIn posts on social selling in weeks fifteen and sixteen.

00:00:07: Frenbus 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.

00:00:20: All right, welcome back to the deep dive everyone.

00:00:22: Yeah We've got a really fascinating one for you today.

00:00:24: So imagine your logging into your analytics dashboard Right?

00:00:28: It's morning.

00:00:28: You check your metrics and you see Your follower count has just shot up like thirty percent over The last few months

00:00:34: which feels great.

00:00:35: You should be thrilled, but then you look at your actual pipeline and it is completely dead.

00:00:40: The phone isn't ringing Your organic reaches dropped off a cliff And you're just sitting there wondering what happened?

00:00:46: Yeah that exact paradox Is hitting B to b marketers so hard right now.

00:00:51: in twenty-twenty six It's

00:00:53: uh...it's gotta Be incredibly frustrating.

00:00:55: Oh absolutely!

00:00:56: Its maddening for anyone trying To build an audience but the data proves it's not just in your head.

00:01:02: So Richard Vanderblum recently published this massive analysis of, I think was one point three million LinkedIn posts?

00:01:11: Wow!

00:01:11: One point three millions.

00:01:12: Yeah an absolute mountain of data and the numbers are staggering on average follower counts across the board grew by thirty-one percent But overall impressions actually fell dramatically.

00:01:22: Okay, let's unpack that right out of the gate because I mean mathematically.

00:01:26: how does it make any sense?

00:01:27: If my audience is thirty percent larger How on earth are fewer people seeing my content?

00:01:33: Because its not a glitch It's deliberate architectural decision by platform.

00:01:38: You know LinkedIn rolled-out that new AI model.

00:01:40: three sixty brew Right

00:01:41: algorithm.

00:01:41: reset

00:01:42: Exactly and understand.

00:01:45: you really have to understand how this playing field has fundamentally changed.

00:01:49: The algorithm it just no longer cares about the raw size of your

00:01:52: network.".

00:01:52: So, It's like okay...the platform used to operate as a giant high school popularity contest right?

00:01:58: Whoever yelled the loudest or had most connections automatically got that microphone!

00:02:02: That is exactly what was the old spray and pre-method.

00:02:05: Right but if its not share volume anymore What does this three sixty brew AI actually looking for?

00:02:12: It's looking for profound context.

00:02:15: So according to some really great insights from Nichols Goats and Leonardo Bellini, Three Sixty Brew evaluates what is called semantic meaning.

00:02:22: it creates this highly specific fingerprint of your profile and content.

00:02:27: Semantic meaning?

00:02:28: Meaning its not just doing a simple keyword search anymore?

00:02:31: No!

00:02:31: Not at all.

00:02:32: Think about like a highly perceptive research librarian.

00:02:34: The old algorithm was a librarian who just glanced at the title of your book.

00:02:38: If you're titled said BDB marketing, boom!

00:02:40: It recommended you to marketers.

00:02:42: Simple enough Right but three sixty brew acts like a librarian Who reads the entire book checks Your bibliography and looks it exactly who You are citing?

00:02:51: It understands that terms Like say renewable energy solar engineering and grid integration Are mathematically clustered together even if the exact keywords don't match.

00:03:00: Oh,

00:03:00: I see!

00:03:00: So it's reading the whole web of your expertise not just scanning your headline for buzzwords?

00:03:05: Yes exactly and Bjorn Barthol actually likens this shift to Google's concept of topical authority in SEO.

00:03:13: If you go incredibly deep on one hyper-specific niche The algorithm learns.

00:03:19: as the definitive expert in that space.

00:03:21: It rewards that coherence over keyword stuffing,

00:03:24: which means your profile you're headline Your daily posts.

00:03:27: they all need to tell The exact same cohesive story precisely.

00:03:31: but wait if we connect this To the Daily grind the old advice from like every LinkedIn guru was always post Every single day be relentless feed the algorithm yeah.

00:03:40: and If You do That today?

00:03:41: You are actively destroying your own reach

00:03:43: seriously Actively Destroying it

00:03:45: literally Constance.

00:03:47: adults shared some metrics showing that daily posting is now causing feed fatigue.

00:03:52: The algorithm simply does not want to spam users with the same creator every twenty-four hours.

00:03:57: So what's the play then?

00:03:59: The new data shows, the absolute sweet spot is publishing just two or three high quality posts per week and you supplemented by leaving three to four highly thoughtful comments on other people's post daily.

00:04:12: That makes total sense, actually.

00:04:14: It's forcing the platform to act like a real networking event instead of just broadcasting tower?

00:04:19: Like you wouldn't walk into conference and deliver seven keynotes in a row!

00:04:22: I know... People would run away from ya

00:04:24: Right You'd deliver one great talk And then spend rest day in hallway grabbing coffee Actually listening other people

00:04:30: Exactly Speaking old advice that needs die.

00:04:34: Lisa J and Abdulhamid Niyadi pointed out that cheap engagement bait is actively punished now.

00:04:41: You know those posts are like, comment.

00:04:42: yes below it I'll DM you my PDF.

00:04:44: Oh!

00:04:44: I hate this so much.

00:04:45: Everyone hates them And Now the AI Hates Them too.

00:04:49: A one word comment just doesn't signal semantic value.

00:04:52: The new super metric-like...the algorithm values above almost anything else.

00:04:57: right now Is the save.

00:04:59: Oh i love that distinction because I mean, a like is just a polite nod in the hallway.

00:05:03: It takes a fraction of second.

00:05:05: Right it's

00:05:05: cheap

00:05:05: But save means real psychological shift has happened The reader basically saying this information so valuable i need to keep for my actual job tomorrow.

00:05:15: Exactly So take away from you listening really clear.

00:05:18: Stop posting every day Just hit some arbitrary quota.

00:05:21: Focus on specific niche and optimize your content so that its dense enough And valuable enough be saved.

00:05:28: that reality forces us into a very uncomfortable corner.

00:05:31: If broad viral reach is no longer the goal, and you're only posting twice a week to hyper-specific audience how do BDB professionals actually generate pipeline?

00:05:41: Yeah!

00:05:41: That's the million dollar question.

00:05:43: We have to shift from treating this platform as a megaphone And start treating it as A structured go-to market system.

00:05:51: The foundational concept of that system comes form some really interesting data shared by Muhammad Ilaidrissi.

00:05:58: He talks about this reality of the invisible buyer.

00:06:02: According to his research, seventy-three percent Seventy-three

00:06:12: percent is a massive number.

00:06:14: If that phase of the journey is truly invisible, how can we possibly know it's even happening?

00:06:19: I mean our marketers just inventing this statistic to feel better about low engagement rates like oh they're definitely reading my posts are just invisible.

00:06:29: It's a fair challenge for sure but the data comes from How modern companies are fundamentally changing their attribution models.

00:06:36: They're finally moving away from software that just tracks the last link you clicked and they are moving towards self-reported attribution.

00:06:42: Like asking them directly?

00:06:43: Right,

00:06:44: when buyers do book a demo companies ask hey how did you hear about us?

00:06:48: The overwhelming response isn't.

00:06:50: oh I googled this morning.

00:06:52: It's been reading your head of engineering linked in posts for six months.

00:06:56: yeah That they silently read their saving content and evaluating expertise on what we call dark social long before ever fill out form.

00:07:05: So by the time they hit your website, The decision is already mostly made.

00:07:08: If you aren't building a system to capture them during that silent evaluation phase You've essentially already lost the deal.

00:07:15: and Charlie heritage breaks down the architecture of this modern system beautifully.

00:07:19: It's five part model And it's completely sequential.

00:07:22: walk us through.

00:07:23: okay?

00:07:23: first Your profile as your landing page.

00:07:26: second?

00:07:27: Your content Is your positioning engine.

00:07:29: third the signals like who views your profile or saves your posts.

00:07:33: That's your league qualification.

00:07:35: Fourth, your engagement in their comments is your conversion trigger.

00:07:39: And finally you email or YouTube presence serves as the ultimate trust layer.

00:07:43: Okay I love a good framework but let's talk about the sharp end of this spear here.

00:07:47: step four The Conversion Trigger because we're talking B toB sales isn't sliding into someone.

00:07:53: direct messages just the twenty-twenty six version.

00:07:56: cold calling?

00:07:56: i don't know anyone who actually enjoys getting a cold DM.

00:07:59: Well nobody enjoys bad cold DM But the data tells a pretty undeniable story about effectiveness.

00:08:07: Lindsey Rios shared numbers showing that LinkedIn DMs currently have a ten point three percent average response rate.

00:08:13: Okay, compare that to cold email which is sitting at like five point one percent average right now.

00:08:19: You are literally doubling your chances of getting her reply but The secret sauce Is entirely in how you craft that message?

00:08:26: Right because if you just send them any pitch they're gonna delete it immediately.

00:08:29: exactly Conor Paulson proved this mathematically, he analyzed outreach data and found that problem-focused messages convert at twenty to thirty percent.

00:08:38: That's

00:08:38: huge!

00:08:39: It is.

00:08:40: Conversely solution focused or demo focus message where you just immediately pitch your product they convert in a gizmo five eight percent.

00:08:46: Let us explore why it happens though because psychologically if I jump into the inbox and immediately start talking about my solutions Your brain instantly recognizes me as salesperson.

00:08:56: Yeah The alarm bells go off

00:08:57: Exactly, your sales guard goes up.

00:08:59: You become defensive but if I ask a highly specific question about the problem that you're dealing with... ...I trigger empathy or at least validation!

00:09:06: I'm making it about YOUR pain not my quota.

00:09:09: But doing this level of personalized problem-focused outreach manually?

00:09:13: That takes hours which brings us to a highly tactical example from Dennis Asha.

00:09:19: He shared a ten minute workflow and is essentially cheat code for this exact problem.

00:09:23: Oh i love a cheat code let's hear it.

00:09:25: So step one He uses a tool called Prospeo to find highly specific targets.

00:09:31: And we aren't looking for broad titles like VP's of sales, We're looking for you know SaaS founders using Salesforce who have public pricing on their website Incredibly granular super-specific.

00:09:41: right.

00:09:42: then step two he exports that list and loads it into what tool called extrovert?

00:09:46: Extrovert fetches all the recent LinkedIn posts and helps them organically track.

00:09:51: It allows him to leave two or three really thoughtful comments on their posts before he ever sends a connection request.

00:09:57: Okay, wait a second.

00:09:58: if we are using scraping tools and software to track people aren't We just building a faster machine?

00:10:04: To spam People I mean how does this not just turn into automated bot behavior?

00:10:09: That's the trap A lot of people fall Into.

00:10:11: but extrovert isn't writing Or leaving The Comments for Him It's just fetching the data.

00:10:16: so he doesn't have to spend three hours a day endlessly scrolling through feeds Just to find his targets.

00:10:22: Oh, okay.

00:10:22: So it's organization.

00:10:24: yeah

00:10:24: its workflow optimization not outsourcing is brain.

00:10:27: He still has to read their posts and leave a deeply relevant human comment And because they've seen his name in there notifications multiple times providing value They almost always accept the connection request?

00:10:38: He has warmed up the lead entirely through context before the DM is ever sent.

00:10:42: Ah, I see!

00:10:43: It's a brilliant way to manufacture serendipity

00:10:46: but that

00:10:46: brings us into pretty massive hurdle.

00:10:48: now we have this highly structured system in place.

00:10:51: We had specific targets and workflow.

00:10:53: What do you actually say?

00:10:55: Because we are living completely saturated by AI Everyone has access to exact same language models

00:11:00: And THAT is creating an absolute epidemic of generic content.

00:11:06: Shoaib Ahmed points out that AI is just filling the platform with noise.

00:11:11: It creates posts in what he calls a story vacuum A

00:11:15: Story Vacuum?

00:11:16: I really love that phrasing because if you think about how a large language model actually works under-the-hood it Just predicts, The next most mathematically probable word operates entirely on averages Which means by definition it makes You sound perfectly average.

00:11:30: yeah literally strips Out the element of surprise which Is the core Of What Makes a story Actually interesting to a human being.

00:11:36: It creates a sea of sameness, you know just corporate jargon over explaining perfectly formatted bullet points that sound like a robot wrote them.

00:11:44: show.

00:11:44: a solution is simple but profound.

00:11:47: right?

00:11:48: how You actually speak?

00:11:49: Right use slang Use humor use vibrant words drop the corporate jarg and completely yeah.

00:11:55: And Tony Ristell adds critical context to this from A recent Hootsuite analysis.

00:11:59: they found That over polished content Actually hurt your performance.

00:12:02: now imperfections on The other hand build trust.

00:12:05: Okay, let me stop you there though.

00:12:06: Are we supposed to like intentionally make typos in our posts to trick people into thinking were authentic?

00:12:11: Like oops I misspelled synergistic.

00:12:13: so you know i'm real because that feels incredibly manipulative.

00:12:17: No no it's not about faking mechanical mistakes but this does raise an important question About what authenticity actually means right now.

00:12:25: It's about lived experience.

00:12:28: Laura Acosta emphasizes What she calls proof first content

00:12:31: Proof First.

00:12:33: What does that look like?

00:12:34: Her formula

00:12:34: is eighty percent tactical, step-by-step frameworks featuring actual messy screenshots from her daily work and then twenty percent personal stories about the failures in realities of achieving those results.

00:12:47: The imperfection isn't the raw reality of the word?

00:12:51: not in you know.

00:12:51: spelling errors show people the real engine room.

00:12:54: Show.

00:12:54: don't just tell okay so we are writing human content.

00:12:57: We're sharing real messy screen shots.

00:12:59: but what happens when you pour your heart into a post.

00:13:01: You hit publish and crickets.

00:13:03: Biana Kulvitz had a fantastic breakdown of why so many technically good posts get absolutely zero comments.

00:13:10: Yeah, she argues it comes down to a couple major psychological mistakes creators make at the very end.

00:13:20: Your post is so comprehensive, so perfectly argued that there's literally nothing left for anyone else to add.

00:13:26: The reader reads it thinks yep agreed and just keeps scrolling.

00:13:29: you have to intentionally leave a gap For the conversation to happen

00:13:33: exactly.

00:13:34: And her second point Is even more critical.

00:13:36: people ask questions That feel like A university exam.

00:13:38: What are the macroeconomic implications of the Q-III SAAS downturn on global supply chains?

00:13:44: Exactly.

00:13:45: No one is going to answer that in a public forum.

00:13:47: if they have to sit there and think about their answers for more than three seconds, They won't comment.

00:13:52: Keep the closing questions simple And more importantly ask your question.

00:13:56: That makes the commenter look good!

00:13:58: That's The Secret right There.

00:14:00: People comment on LinkedIn For two reasons Right To support A Friend Or Showcase Their Own Expertise.

00:14:06: It is just human nature.

00:14:08: If your question allows someone to drop a comment that makes them look smart to their own network, they will comment every single

00:14:14: time.".

00:14:15: Right!

00:14:15: Let them share or win... let them be the hero of your comments section.

00:14:18: Exactly!!

00:14:19: Okay so we've looked deeply at The Individual Seller.

00:14:22: We know how the AI clusters topics, we have the GPM system and we know how to write human content.

00:14:28: But what happens when you try to scale this across an entire B-to-B company?

00:14:32: Because if you look at the macro data The biggest untapped resource a company has isn't their ad budget It's there own team.

00:14:40: Oh employee advocacy.

00:14:41: This is where it gets really interesting because of math is undeniable.

00:14:45: DaVinci Jane shared metric.

00:14:47: that should fundamentally change how executives view marketing.

00:14:51: A team's combined LinkedIn network is almost always vastly larger than the official company pages following.

00:14:57: Oh, without a doubt.

00:14:58: and The reach algorithmically is completely different to factly

00:15:01: different.

00:15:01: accompany page gets maybe two-to five percent organic reach on a good day?

00:15:06: The Algorithm actively suppresses it because linkedin wants companies to buy ads.

00:15:11: It's essentially just a digital brochure

00:15:13: while the employees are out there actively networking as real human beings.

00:15:18: Sholem Kemkar notes that employees are the absolute most authentic PR a brand will ever have.

00:15:25: Audiences trust people far more than polished corporate campaigns,

00:15:29: but companies completely ruin this.

00:15:31: they recognize The reach their employees have and then they force these awful corporate scripts on them.

00:15:37: It's like holding up a cue card in a hostage video.

00:15:39: I am thrilled to announce that our synergized cloud solutions have been recognized by...

00:15:44: It's so painful to read.

00:15:46: Nobody talks like that at a dinner party, why would they talk about it on social media?

00:15:49: And that is exactly the reason these programs crash and burn!

00:15:52: Ivan Dimitrijevic in Alien Jerkic stressed that employee advocacy programs fall apart the moment they lack trust…and start sounding like forced copy-paste marketing.

00:16:02: If content doesn't feel authentic for employees' actual daily voice …It will immediately trigger those sales guards we talked earlier.

00:16:09: So if you are a marketing director listening to this, how do you actually roll out?

00:16:37: Build the framework, the tracking and confidence around them first.

00:16:41: And crucially you have to separate executive thought leadership from everyday employee content.

00:16:46: Right!

00:16:46: What do mean by separate?

00:16:47: Let executives share high level industry opinions in vision But let every day employees share their actual flexible daily experiences.

00:16:56: Pictures of desk Frustrating coding bug.

00:16:58: they finally fixed A great conversation we had with client.

00:17:02: match the voice to the person's actual role.

00:17:04: That makes perfect sense, let them be themselves.

00:17:07: and if we are talking about matching things to the right roll We have to dig into the incredible data from Jody Leon and Bradley Keenan.

00:17:15: They analyzed what was it?

00:17:16: A hundred ten thousand employee LinkedIn posts through DSMN eight Yeah

00:17:20: massive sample size.

00:17:22: And this analysis is brilliant because it exposed a massive expensive blind spot in how companies run these programs.

00:17:28: they found that most employee advocacy programs fail Because managers do not match the content format to the desired business outcome.

00:17:37: Let's unpack the mechanics of that because they found that forty two percent Of all posts being shared by employees are image posts.

00:17:45: people just default To uploading a picture, because it feels easy and safe.

00:17:48: But according to the data images or middle-of-the-pack for almost every single metric It is a huge wasted opportunity

00:17:55: And it comes down to how the algorithm calculates.

00:17:57: dwell time.

00:17:58: If we look at their breakdown, you have to be highly strategic.

00:18:27: If your goal is actual website traffic, maybe you're promoting a webinar or new tool.

00:18:32: You have to use links.

00:18:34: link posts will kill your overall impressions because LinkedIn hates when you take people off their platform but they naturally have the highest click-through rate.

00:18:41: exactly and if Your Goal is engagement like starting conversations in the comments?

00:18:46: You should use gallery or carousel posts.

00:18:49: The lesson here is profound stop asking what does the linkedin algorithm want and start asking, what do we want this specific piece of content to achieve?

00:18:58: Match the format mathematically to the outcome.

00:19:01: It all comes down to intentionality whether it's how you structure your profile for semantic search.

00:19:05: have you researched a specific problem before he sent a DM?

00:19:08: or How You Run A Massive Employee Advocacy Program?

00:19:10: The days of throwing spaghetti at the wall To see what sticks are just gone.

00:19:14: everything has to be deliberate

00:19:15: Which brings us to a final provocative thought For you consider as We wrap up todays deep dives.

00:19:21: Take a hard, honest look at your own LinkedIn activity over the last week.

00:19:26: Are you optimizing your precious time for The Algorithm of Twenty-Twenty?

00:19:30: Are posting every single day chasing empty likes and striving for broad generic audience that will never buy from you or are doing the hard work building focused twenty-twenty six ready system?

00:19:43: A system actively supports how specific buyers make their decisions today because remember the invisible buyer Your network is watching you.

00:19:52: They're evaluating your expertise, and they are making decisions even when they aren't liking your posts.

00:19:57: If you enjoyed this episode new episodes drop every two weeks.

00:20:00: Also check out our other editions on account-based marketing field Marketing channel marketing mark tech.

00:20:05: go to market an AI in BDB marketing.

00:20:07: Thanks so much for joining us on this deep dive.

00:20:09: don't

00:20:09: forget to subscribe And we will see next time.