Best of LinkedIn: Social Selling CW 39/ 40

00:00:00: provided by Thomas Algeier and Freeness, based on the most relevant LinkedIn posts about social selling in calendar weeks thirty-nine and forty.

00:00:07: Freenes supports clients with identifying target attendees for events crafting outreach that cuts through noise driving qualified registrations thru strategic LinkedIn engagement.

00:00:17: you can find more info.

00:00:19: So today we are analyzing the top social selling trends across LinkedIn.

00:00:23: right now, because you know that platform has just completely evolved.

00:00:26: Yeah well worked even six months ago.

00:00:28: is it's actually actively hurting you to day exactly?

00:00:32: so our mission for this deep dive is to give you The B-to-B marketing professional a really tactical briefing.

00:00:38: We want to extract actionable intelligence on how the platform has fundamentally shifted

00:00:44: Right, because we are moving way past those minor manual algorithm tweaks.

00:00:48: We all used to track

00:00:49: totally were in an era dominated by AI search.

00:00:52: now So we need to look at how top practitioners are adapting their content the profiles there teams To generate actual pipeline Not just vanity metrics.

00:01:02: Yeah, and the first thing we really need to internalize here is that The underlying architecture of the platform it's been replaced entirely.

00:01:09: It's

00:01:09: a completely different game though?

00:01:10: I mean you can't win if You don't realize the rules have changed.

00:01:13: We've officially transitioned away from the social graph

00:01:16: right

00:01:16: so it's no longer Just about who are connected too.

00:01:20: its About an LLM large language model literally evaluating every single syllable u type.

00:01:26: That wild I mean, let's pull the curtain back on the mechanics of that for a second.

00:01:30: The era of easy chronological reach is just dead.

00:01:34: Oh

00:01:35: completely dead?

00:01:35: The feed is entirely driven by AI.

00:01:38: now and there was this brutal reality check happening with organic reach.

00:01:42: we are talking about a forty seven percent drop year over Year.

00:01:45: yeah Melissa Rosenthal actually dug into why this is happening And it really comes down to the fact that the feed was essentially rebuilt around these language models.

00:01:53: So what does that actually look like in practice?

00:01:55: Well, the AI reads or post independently decides what the core topic is and then it handpicks a highly specific audience.

00:02:03: It thinks will care about.

00:02:05: Oh wow So it's not just broadcasting into your network anymore?

00:02:09: No Not at all which you know inherently concentrates reach among Just a few top creators And it really pushes brands toward relying on paid and owned audiences.

00:02:18: right and Gabe pipette found some crazy details in how this machine things.

00:02:23: They're actually two distinct LLMs running the feed right now operating in tandem.

00:02:28: Wait, two of them?

00:02:29: Yeah and the crucial takeaway from his analysis is that native posts so posts that do not contain external links.

00:02:36: they are about thirty-eight percent more impressions.

00:02:39: Thirty eight percent!

00:02:40: That's a massive penalty for trying to take people off the platform.

00:02:43: Exactly The machine has heavily incentivized to trap users' attention.

00:02:48: If it senses a link taking someone into your company blog Chokes the distribution immediately.

00:02:53: Right, it's all about session retention.

00:02:56: But um

00:02:57: It's not just policing links is it?

00:02:59: It's policing the actual substance of the writing too.

00:03:01: Yeah

00:03:02: The new AI slop penalty right.

00:03:04: Cindy Dodd looked into this and the nuance here Is really key.

00:03:08: LinkedIn isn't automatically punishing content Just because it detects an ai tool helped write it.

00:03:14: okay so what makes it slop?

00:03:16: They define slop as that empty, highly polished content.

00:03:19: That just lacks any actual human experience.

00:03:22: You know no unique perspective No contrarian insight Just fluff...

00:03:27: That makes sense.

00:03:27: It sounds like LinkedIn went from being you this loud chaotic networking event where the loudest voice wins to a strict bouncer checking IDs for actual value.

00:03:37: That is perfect analogy.

00:03:39: But I mean let me push back A bit As BDB marketer Answering to a CMO who wants to see graph lines going up and to the right.

00:03:47: Should we just accept getting fewer views?

00:03:50: Honestly, counter-intuitively yes!

00:03:53: And Christian Krause has the data to prove why FEWER VIEWS is actually the goal now.

00:03:57: Wait...really?

00:03:59: FEWERS VIEWS IS THE GOAL.

00:04:00: Yeah

00:04:01: he calls this new reality interest based distribution.

00:04:05: He documented his own analytics & impressions dropped by a staggering ninety percent.

00:04:11: Ninety?!

00:04:12: I mean, in the old days you'd think your business was dying.

00:04:15: Right but his revenue more than doubled during that exact same period.

00:04:19: Okay

00:04:19: a ninety percent drop in visibility But one hundred percent increasing cash.

00:04:24: How?

00:04:25: Because The AI matchmaker is acting as an ultra strict filter.

00:04:29: It stopped showing us posts to random connections and it started putting its content strictly In front of highly qualified leads

00:04:36: People who actually suffer from the specific problem he solves.

00:04:39: Exactly, The volume collapsed but the buying intent just skyrocketed.

00:04:44: It's fascinating.

00:04:46: So we are optimizing for relevance not virality.

00:04:50: But you know the impact of this LLM shift is also bleeding way off the platform itself.

00:04:56: What do you mean?

00:04:57: Think about where buyers go when they don't want to scroll a feed.

00:05:00: They go to AI search tools like chat GPT.

00:05:03: Conor Gillivan analyzed the citation data for those platforms and LinkedIn is now showing up in one out of every nine AI search answers.

00:05:11: One out of nine?

00:05:12: Yeah, it's the second most cited LLM source on the entire internet right behind Reddit.

00:05:17: Wow which means your linkedin posts aren't just social updates anymore.

00:05:22: they are literally training data For global AI search engines

00:05:26: exactly And Faison Amad laid out the tactical implications of this.

00:05:31: because of this shift Posts need to be structured for machines as well humans.

00:05:35: Right, like ruthless formatting.

00:05:37: Yeah

00:05:37: clear bullets short sentences question-based headlines.

00:05:41: You have to feed the AI crawlers cleanly so they can easily parse and cite your insights into a buyer.

00:05:46: So we are literally formatting our thoughts for bots.

00:05:49: that is a wild reality It

00:05:52: really is.

00:05:53: But I mean, if the LLM feed makes every single impression so much harder to earn and so highly targeted you absolutely cannot waste that attention by trying to sell directly in the feed.

00:06:03: Right which brings us through a really critical pivot moving this cell off-the-posts an onto profile.

00:06:10: yet You have to separate those two functions.

00:06:13: The post job is awareness the profiles job is conversion And

00:06:17: Mike Bolton actually ran an AB test on identical posts to prove This right

00:06:20: he did.

00:06:21: On one post, he left a standard call to action as CTA at the bottom.

00:06:25: on the other He removed the CTA completely.

00:06:28: The caption without the cta saw an impression lift of nearly seventy nine times.

00:06:34: Seventy-nine times more reach just by deleting his sentence asking them do something.

00:06:40: Yep

00:06:41: How does the algorithm even know it's a CTA?

00:06:43: Well the LLM reads for commercial intent.

00:06:46: It sees patterns like Lincoln bio DM me or book a demo.

00:06:51: When it flags that intent, it throttles the reach because it views as an ad.

00:06:55: Ah so doesn't see its organic value?

00:06:57: Exactly!

00:06:58: You must let the post get to reach and let profile do selling.

00:07:03: So we're essentially treating LinkedIn Profile like a high converting B-to-B landing page.

00:07:07: Right

00:07:08: Richard Vanderblom has whole framework for this.

00:07:11: Content only builds awareness.

00:07:13: To convert attention into client meetings you need smart signals exactly where buyer lands.

00:07:18: Like what kind of signal?

00:07:19: A pinned featured section a native book of time button and intentionally moving high intent comments straight into the DMs.

00:07:26: Okay, that makes sense.

00:07:28: And Austin Belchak actually laid out some tactics for optimizing that profile real estate That tripled his own profile views.

00:07:35: Oh yeah?

00:07:35: What did he suggest?

00:07:36: He says to use a value proposition headline.

00:07:39: So instead of job title it's I help this audience achieve this result.

00:07:44: And he said you need to maintain a five percent target keyword density in your about-and experience sections.

00:07:50: Five percent.

00:07:51: Okay, so the internal search engine knows exactly what to rank you for?

00:07:55: Exactly

00:07:56: Oh and Carter Whittig shared this fascinating SEO trek.

00:08:00: if You put target keywords in the first one-to-two lines of your post it actually shapes The public LinkedIn URL.

00:08:06: slug

00:08:07: wait So it directly connects Your name To those specific Search Terms on Google.

00:08:10: yes It's like free SEO juice.

00:08:12: that is brilliant.

00:08:14: But you know let me play doubles advocate For a second.

00:08:17: If we all tweet our profiles Like landing pages And we all use the exact same I help X achieve Y formula.

00:08:25: Don't we risk looking like a bunch of generic marketing bots?

00:08:29: That's totally fair pushback, but Deesha Shukla has great strategic insight on this.

00:08:34: she says that positioning must precede visibility.

00:08:38: okay

00:08:38: unpack that.

00:08:39: if you don't have clear hyper specific positioning buyers just leave your profile with a vague impression.

00:08:47: But if your positioning is razor sharp, they remember your specific expertise the exact moment their problem becomes urgent.

00:08:54: You can't just be a generic bot.

00:08:55: you

00:08:55: have to actually solve this Pacific pain point.

00:08:58: that's great distinction.

00:09:00: by The way If you are finding these insights valuable make sure to subscribe so you catch future deep dyes.

00:09:05: We have a lot more ground to cover today.

00:09:07: Yeah we do because once your profile is optimized to catch leads without burning out.

00:09:17: Exactly!

00:09:18: So let's talk about building systems that guarantee quality and consistency.

00:09:22: Basya Kubitska had this fascinating example regarding AI workflows.

00:09:27: Oh, the one where her AI failed completely?

00:09:29: Yes she discovered that relying on prompt instructions for quality control just failed.

00:09:35: The AI would claim that quality checks had passed when they hadn't even run.

00:09:39: That is terrifying if you are automating a brand's voice.

00:09:42: Right, so to build reliable AI content agents she moved to what she calls a code enforced harness.

00:09:50: A Code Enforced Harness?

00:09:51: Yeah okay

00:09:52: yeah.

00:09:52: estate machine enforces the rules and the LLM only handles The Creative Judgment.

00:09:56: Wait

00:09:57: explain this To me like I'm five because deterministic state machines sounds incredibly intimidating for a marketer.

00:10:03: What does that actually look Like?

00:10:04: Okay think about a factory assembly line.

00:10:07: That's a state machine.

00:10:08: It forces the process through locked stages.

00:10:11: The AI isn't allowed to write the whole post at once based on one massive prompt.

00:10:16: Oh, I see...

00:10:17: The code rigidly enforces the workflow.

00:10:19: Stage One extracts the core idea.

00:10:21: Stop!

00:10:22: The software evaluates it.

00:10:23: Stage Two Write the hook.

00:10:25: Stop!!

00:10:26: The AI literally cannot skip a quality check because the software won't let.

00:10:30: that

00:10:30: is so smart.

00:10:32: You dig this structural control away from the AI.

00:10:35: but What about teams doing human-driven content?

00:10:38: Will McTie has a great system for that.

00:10:40: He uses four proof driven post types to just remove buyer doubt entirely.

00:10:46: Okay, what are the four types?

00:10:48: first case studies that lead with results.

00:10:51: second testimonials That ask clients what changed for you.

00:10:55: third direct objection handling.

00:10:58: and fourth hyper specific lead magnets.

00:11:01: I love And Imtazulma Mood has a similar four bucket system for service businesses, right?

00:11:07: Yeah.

00:11:08: Authority education trust and conversion they all work together so that not every single post has to be hard sell

00:11:16: Right?

00:11:17: So content creation shouldn't like daily diary where you wake up in panic about what to write today.

00:11:23: No definitely Not.

00:11:24: It's more programming at TV network.

00:11:26: You have your recurring segments.

00:11:29: Well...you even run reruns.

00:11:32: You absolutely should run reruns.

00:11:35: Connor Paulson strongly advocates for this, he reposts his proven content every ninety days with just fresh angles

00:11:43: Every ninety days?

00:11:44: Don't people notice?

00:11:46: No because

00:11:46: of how the feed works now almost nobody remembers The original and it reaches a mostly new audience anyway saving immense time.

00:11:54: That makes total sense.

00:11:55: work smarter not harder.

00:11:58: Okay Let's zoom out to the final piece of the puzzle here.

00:12:01: You can have the best content system in the world, but to truly scale B-to-B marketing you have to move beyond a single founder or company page.

00:12:09: Right?

00:12:10: You have to mobilize the whole team.

00:12:11: this is the shift from corporate broadcasting to frontline employee influence.

00:12:16: Chris Cosolino had a really strong take on this.

00:12:18: he says companies under fifty million dollars in revenue should completely shift their effort away from company pages

00:12:25: entirely.

00:12:25: yeah put it all into executive profiles, because personal audiences compound and they allow for direct messaging.

00:12:32: Company page followers do

00:12:33: not.".

00:12:34: That is a harsh truth but the data backs it up.

00:12:37: Giles' Shorthouse found that right now only three percent of employees actually share their company's content...

00:12:42: Only Three Percent!

00:12:43: ...only three per cent?

00:12:43: That is

00:12:44: so low.

00:12:44: But when they DO engagement jumps thirty percent And click-through rates literally double compared to the brand page.

00:12:51: Wow Double the clicks just from coming from a human.

00:12:54: So why is that three percent number so stubborn?

00:12:58: Sarah Goodall says brands are just stuck on employee advocacy.

00:13:01: You know, asking forty nine people to share the exact same sanitized post?

00:13:05: Oh

00:13:06: right The corporate copy paste.

00:13:07: Exactly

00:13:08: Everyone hates That

00:13:09: exactly.

00:13:10: they need To shift to Employee influence Which means teaching staff how to find their own voice and personalize this story.

00:13:17: And Benjamin Hays me a great point about This too don't Just rely On the loud salespeople.

00:13:22: A real program Needs to support the quiet experts.

00:13:25: The Quiet Experts?

00:13:26: Yeah, they're people who know their stuff deeply—the engineers and product folks.

00:13:30: but just don't naturally crave this spotlight.

00:13:32: Oh I love that!

00:13:34: But let me ask you this we are asking employees to do heavy lifting of brand distribution here.

00:13:40: yeah

00:13:40: is it free influencer marketing for a company?

00:13:44: shouldn't these employees be compensated?

00:13:47: That's the million dollar question And Tamika Basil brought a report from Sprout Social about this.

00:13:53: Consumers absolutely prefer frontline employee voices over the C-suite, it's forty six percent to ten percent.

00:14:00: Okay wow

00:14:01: But here is the kicker.

00:14:02: Sixty one percent of consumers believe those employee influencers Absolutely should be paid extra for their promotional efforts

00:14:09: As they should be

00:14:10: Right.

00:14:11: And when a company actually gets its entire ecosystem right It is incredible.

00:14:16: Look at Adam Schoenfeld breakdown of Profound's recent funding announcement.

00:14:19: Oh I saw that They didn't just do a press release did they?

00:14:22: No, they didn't rely on the press release at all.

00:14:24: They coordinated seventeen creator partner posts alongside their CEO and front line team.

00:14:30: Seventeen!

00:14:31: Yeah That is massive coordination effort.

00:14:33: It was literal lightning strike.

00:14:35: it completely dominated category mindshare in LinkedIn for days

00:14:39: Because they leveraged actual humans not just corporate logo.

00:14:43: proves everything we've been talking about today.

00:14:45: Exactly

00:14:46: So.

00:14:46: to wrap this haul up I want leave you with thought If LLMs are now deciding both who sees your posts in the LinkedIn feed and whether your insights get cited in global AI search results, Are we entering an era where B to be marketing is less about persuading humans to click?

00:15:05: And more about training algorithms to trust you as a definitive authority.

00:15:11: If you enjoyed this episode, new episodes drop every two weeks.

00:15:14: Also check out our other editions on Field Marketing, MarTech AI and B to be go to Market ABM and Channel marketing in partner ecosystem.

00:15:23: Thank You so much for joining us with this deep dive.

00:15:26: make sure it hits subscribe So you don't miss the next one?

00:15:29: And we will catch you next time.