Marketing 911
Marketing 911, is the podcast where we tackle the toughest marketing challenges at the executive level.
Whether you're navigating complex strategies, trying to reach your target audience, or facing shifting market dynamics, we're here to provide you with actionable solutions.
From digital transformation to customer retention, if it's a marketing crisis, we're here to help you solve it—before it turns into a full-blown emergency.
Marketing 911
Why Your LinkedIn Reach Dropped And What To Do Next
Your LinkedIn reach didn’t just dip—it fell off a cliff because the rules changed. We unpack how the platform moved from mechanical engagement scores to an AI-driven, context-first model that reads who you are, how you write, and whether your content truly serves the people you claim to help. If the old playbook was “get 10 comments in an hour,” the new one is “prove you belong in the conversation.”
We dive into how LinkedIn now interprets role, authority, and topical relevance by analyzing your profile history, your comment quality, and the patterns of your audience across the network. Pods, fluffy line-break posts, and “great post” replies aren’t cutting it because the system can tell they add little. Influencer accounts that lived on manufactured engagement are seeing 50 to 80 percent drops in impressions, while practitioners who share clear, specific, and useful insights are gaining traction with smaller but more qualified audiences.
The fix isn’t a hack—it’s alignment. Bring marketing, sales, and leaders under one message rooted in a crisp ICP. Write in real language that explains the buyer’s problem, the stakes, and the steps to solve it. Encourage thoughtful comments that add examples or counterpoints. Shift some energy to longer posts and articles that let you teach with detail; the AI needs depth to route your work to the right people, and buyers increasingly find you through AI intermediaries. Treat every profile line, post, and comment as a signal of credibility that compounds over time.
If your strategy needs a reset, this conversation gives you the map: clarify your ICP, tighten your narrative, raise the quality bar, and let substance outlast shortcuts. Subscribe, share this with a teammate who owns LinkedIn results, and leave a review telling us the one change you’ll make this week.
You're listening to Marketing 911. I'm Richard Bliss, Mike, and I'm joined by my co-host, Brian Baxtrand. And we are joining you today to talk about a lot of different things, and we've uh enjoyed, especially all the changes that are happening in marketing right marketing at the moment. And you have a lot of questions. Market, uh, Brian, what are we going to talk about today?
SPEAKER_00:Yeah, this is pretty exciting, and it's very timely. Um, LinkedIn has been had a great algorithm reset. I'm sure folks have seen this in the news. And why this is so interesting is I don't know the specifics of the reset. I know you're an expert in this area, but everybody in marketing uses LinkedIn. Everybody is trying to figure out how to get more views, right? The big debate. I've got 3,000 people that I'm connected to, but I put a post up and you'll LinkedIn only sends it to 10, and I need to do comment. So this is very, very relevant. So I'm excited to talk about it. So let's start with this.
SPEAKER_01:All right, let's talk about that. And let's do a let's do a reset then. Um, in the past, well, as of the time of this recording, it's 2025, uh, there's been a dramatic drop in the reach of our content on LinkedIn for everybody. 50 to 80 percent drop. You've seen it, I've seen it, uh, influencers have seen it. They're the ones that are screaming the most because they've been kind of targeted. Uh, and what we've seen is this massive drop where things in the past aren't necessarily working anymore. And what I mean by that is, you know, Brian, you and I have known each other for quite some time, and you've sat in on some of my training and listened to my presentations, and it had to do with kind of a numerical scale. If you get a certain number of comments, if you get a certain amount of time, if you get a certain number of likes and reposts, and a like is less than worth less than a comment. All of this went into a numerical score that would then cause the algorithm to determine the value of your post and then determine how many people actually see it. That's the kind of how and you remember I, you and I have talked about that, right?
SPEAKER_00:Yeah, so I put I put up a post. I remember we talked about, and I used to do this send a note to 10 people saying, I just posted something. I think at I think LinkedIn gave you an hour or something. And if you could get 10 comments, it would view that as, oh, this must be really interesting content. They've got 10 comments in an hour. Let me send it to more people.
SPEAKER_01:And absolutely. Yep.
SPEAKER_00:Yep.
SPEAKER_01:So that was basically a numerical mechanical scoring system. 10 comments, uh, you know, the quality of the comment kind of didn't really come into play. All of those things happened. Well, this last couple of months has all been thrown out.
SPEAKER_00:Really?
SPEAKER_01:It's all been thrown out because now, and we've talked about this in a past episode, and we're going to talk about this in a future episode. AI. LinkedIn has now shifted from this mechanical scoring system that was like a factory that a piece of content would come out, come in, and it would be first go through one filter, and then that filter would send it through another filter, and then filter and filter, you know, just like you described, number of comments, length of comments, the uh dwell time, speed, velocity, all of these things. I've been teaching this for years. Yeah. And we we've proven over and over that it works. It still kind of works. And I was in Las Vegas last week doing a standing room-only presentation to 150 people at IMEX, a big international meeting expo uh for event planners, and uh drove a post into the multiple thousands within a couple of hours because of what we were able to do. But with that said, the shift has been now a fundamental shift away from this mechanical numerical approach and instead to a contextual approach.
SPEAKER_00:I don't know, does that make sense? Explain, explain what you mean by if I'm assuming context meaning the quality of the actual post itself.
SPEAKER_01:Yeah, kinda. So here let me dive into that. What it means is that now LinkedIn is using an AI engine that can, I'm gonna put this in air quotes, understand the context of what you're saying, who you're saying it to, what they said, and the value of that conversation, not by keywords, but by context. Just like you and I are having a conju conversation right now, if AI was listening, and it probably is, the AI tool can then kind of start to figure out what you and I are talking about. That's what's happening on LinkedIn. It now will figure out what your title is, and it's not using your keyword title. It's figuring out basically your role. It's looking at your history, who you are, the experience you have. It's then seeing other topics you've talked about, other topics you've liked or commented on. It's looking at the relevance of the people you've talked to. Are you talking to C-suite people? Are you talking to not C-suite people? Who are you talking to? It's then looking at the interest that you've shown in this. It's by your actions. Oh, you've liked three of these things, you know, so far in a row. You must want more of that. All of this is going into now an AI tool, an LLM, that's now figuring out contextually, you probably want to see content around this topic because you have shown so much interest around this contextually. The quality of your comments, not just that you left a comment and not just you left it on who, but what did you say in that comment that showed that you actually had a reason and a legitimate, legitimate uh responsibility, not responsibility, that you had a legitimate purpose for being in that conversation?
SPEAKER_00:Let me so let me stop you there and just ask you this. So if I understand this correctly, are you saying that if I put up a post, LinkedIn is doing analysis on what I've written, but then looking at who I'm connected to and determining which of those connections LinkedIn should show my post to based on what those connections like, have commented on, etc.
SPEAKER_01:Is that yeah, not yes, so very close. Not just liked and commented on. That's a kind of a checkbox. Did they like it? No. What did they like? Now you might put out content about you do a variety of things, and you and I were just talking about a variety of things. Maybe you're gonna put out a post about a holiday, you're gonna put out a post about marketing, you're gonna put out a post about sales, and and so what they're gonna do is they're gonna watch not just who commented or who liked, but what content did they comment on contextually? And have they commented on that kind of content in the past for other people as well? So is there relevance for them to see your content based on an overall contextual uh approach rather than a keyword or mechanical approach? Oh, they've liked Brian's content in the past, so they're probably gonna like this.
SPEAKER_00:So let me just let me take go to the extreme. Yeah. I do a post on uh making signs, something I know nothing about, and very rarely do you see it on LinkedIn. How to make a cardboard sign. Is it possible? LinkedIn says, There's nobody in your network, Brian, that has ever shown any interest or uh value in how to make a sign. We're not going to send this to anyone.
SPEAKER_01:In addition, you've never actually talked about this in the past, and we can't find any relevance where you have actually the authority to talk on this. So we think you're just blowing smoke. So we're not gonna show it to anybody.
SPEAKER_00:That's exactly right. And then where comments come in when you started at the beginning, people say, Hey, Richard, excellent post. Is it LinkedIn's gonna say that's there's no context to that?
SPEAKER_01:That's exactly what they're gonna say. They're gonna say, Oh, they really didn't find that that interesting or valuable, they just gave a throwaway comment. And so now your about section, your work history, your comments all need to be written in concise uh prose that allows an AI engine to see and know what in the hell you're talking about. So if you say excellent job, there's no context there for why is that excellent? Why are you congratulating them? What's there's no there's no context. And so LinkedIn's like, yeah, you really didn't add anything, you had nothing to say here, and there was no valid contribution. So eh, we're not gonna really rank you well on this, and you can see why this is a completely different shift because this is all on the fly.
SPEAKER_00:You can't what have you what have you seen or heard from people? You mentioned influencers, like are people recognizing.
SPEAKER_01:Oh, yeah, and they're not happy, they are not happy because over the last year or two, in I'm gonna call them influencers have been gaming the system, and they're using pods and they're using artificial means. I ran into like four of them today. I gotta tell you, I was frustrated. I had to go like take a break because, and they're mostly bros, and these bros have like I started my business four months ago and I went from 4,000 to 400,000 followers on LinkedIn. I'll teach you how to do that too. Like, really? That's not you and Brian, you and I know that's those shortcuts don't work. And so I look at that and I think that can't be legit. And then I go look at the people commenting, and they're all from all over with no seniority or validation or buying power or anything. Oh, this is awesome. Oh, what wisdom. Oh, this is great, right? You're like, uh-huh. What's happened just this year? They used to get, they'll get two to three hundred, four hundred comments. Well, in the old model, that would skyrocket their reach. 100,000 impressions. Now they get a thousand impressions. Maybe they get 2,000 because it's still a lot of people engaging, but LinkedIn's like, this isn't valuable. Or those fluff pieces that these bros are writing, or it's just a line of nothing, a line, break, line, break, line, break, line, break. LinkedIn's like, there's no, there's nothing here. There's a lot of words, and it's kind of it seems clever, but there's no content. And so this all of this is now coming into play about who sees your content and how you get ranked, so to speak. Rank's not quite the right word, but how LinkedIn sees and identifies your value on their platform. Wow, all of that's changed. Oh, and so what I was gonna say is the bros, the influencers, yeah, their content has been shrunk by 80%, and they're just hot, they're mad, they're screaming out there, and I just laugh.
SPEAKER_00:Does uh does does uh LinkedIn recognize when an uh topic or a blog has been written by another AI tool? And if so, does it just dismiss it?
SPEAKER_01:In the in the past, I was gonna say no. And uh because it it measured more not the content itself, but the response of the audience.
SPEAKER_00:Yeah.
SPEAKER_01:Now we haven't tested it thoroughly, but my instinct is yes, now it matters. And that's because LinkedIn's algorithm is evaluating the writing style and the quality of the content of your output, what you wrote. And a lot more than 50% of the content out right now, out there right now is being written by AI. And everyone's referring to it as AI slop. Yeah, so the algorithm is seeing the AI slop, and then oftentimes the comments are also AI slop. And so it's starting to see that. I have to believe that that will start to come into play. It's so new though, we haven't quite figured that one out. And I still tell people look, it's not how your audience reacts to it. If you put out AI slop and your audience loves it, well, in in the past, LinkedIn's algorithm was like, okay, all these people loved it. Now LinkedIn's like, uh, really? Is it really that interesting? Because all you got were a bunch of attaboys. When go. Thanks for sharing. Awesome.
SPEAKER_00:Now, do now does LinkedIn publish how their algorithm works?
SPEAKER_01:Yeah, normally, no, and normally and partly yes and no. Every question you're gonna ask me is gonna be a yes and no. They don't have a single algorithm, they have a whole bunch of different ones that do different things, and this is part of the problem. It was a structure that was built that if you tweaked one thing, you had to rebuild the whole thing.
SPEAKER_00:Yeah, because it was all just intertwined and connected.
SPEAKER_01:Yeah, um, you and I are old enough to know what a tinker toy is, but it's kind of like a tinker toy thing. And if you change one of them, you just got to change everything.
SPEAKER_00:Yeah.
SPEAKER_01:Um, what was the question?
SPEAKER_00:The question was, now you're really showing your age. The question was, does LinkedIn publish their algorithms?
SPEAKER_01:So different engineers would publish content about the different aspects of the algorithm they used, right? So it was never one, just one algorithm. And what we were able to do with our research was to test that. When I say our research, I sponsor uh the largest LinkedIn algorithm research report every year. And the next one comes out in about two weeks from the from this recording. So it'll come out in October, November 2025, for those who are listening. Now, this time they have been very open about what they're saying. In the past, it was kind of like because you had all these different now, it's this overarching uh system context with this underlying LLM that's being driven by all of this content that's on LinkedIn. Think about it, all this content on LinkedIn has been training their LLM. And that means that you and I, if we want to be relevant on the LinkedIn platform, we need to be relevant on the LinkedIn platform. And what I know I just said the exact same thing, but the point is.
SPEAKER_00:No, I think what you're saying is it's kind of like Twitter. They want you to use LinkedIn more, they want the quality to go up, they want the AI-driven slop to go away. Um, and they're doing what they can to try and put that in place, which I can't blame them for it. I think everybody would want more quality content. So the big question becomes is we're running up against the time here. Yeah. So what's the next step for people? What do they need to do?
SPEAKER_01:I gotta tell you, for me, I got all excited by this. I got all excited. And uh, my wife, who is corporate marketing, you're corporate marketing, she's like, This is terrible. All these come, all these uh marketing teams are gonna have to rethink and recalibrate, and it's gonna be tough inside. And I'm like, yeah, that's awesome. Why? Because that's what I do. I teach these marketing and salespeople how to adjust to the changes that are coming. And uh I'm gonna be that means business for me. I'm right, I'm I'm happy with the changes.
SPEAKER_00:So the so the so the action you're suggesting is to go to Bliss Point.
SPEAKER_01:Bliss point, right? Come hire Richard Bliss to come in and train your marketing and sales teams on the new algorithm. Now, let's be uh that's a that's a semi-serious answer, but let's be serious. Instead of the marketing team being responsible for the content and the sales team responsible for sales and the executives responsible for their thing, you need to bring all of those together and say, look, we need to be focused on talking about our value proposition in clear language to our customers who we have clearly identified, our ICP, our ideal customer profile, we need to be talking to them in clear language that the AI will pick up so that when that conversation comes up somewhere else on the LinkedIn ecosystem, our content will become relevant, our people will become relevant. That means it goes beyond marketing writing a post and everybody sharing it.
SPEAKER_00:This thing, so essentially, this is this is forcing what marketing always should have been. A company aligned between behind the one message, yeah, designed specifically for their ICP, and everything's tying back to that so that your ICP is seeing the business value your company can drive and the problems your company can solve for them.
SPEAKER_01:And here's what's the kicker, Brian. The new ICP is an AI algorithm because your individual people, your customer isn't going to be looking you up. They're gonna go to an AI tool and ask the AI tool, and the AI tool is going to look you up.
SPEAKER_00:100%.
SPEAKER_01:And so now what LinkedIn is saying, you need to write your content in such a way that's not keywords and no, it needs to be prose that explains the problem and the solution clear so that when the AI is asked, it knows exactly the answer and the relevance. And suddenly, this is why I think longer form posts are going to become more important. Articles are gonna come back into their importance because the AI tool is going to be looking for content that can clearly identify the problem, the customer, the problem, and the solution, all in clear language voices and not bullet points and emojis and all of that.
SPEAKER_00:So let let's end on that. Yep. Awesome, awesome uh podcast here. Really, I think people are going to get a ton of value out of this. So, Richard, thank you very much. And I'm Brian Fagstrand, and I hope you enjoyed marketing 911. Talk soon.
SPEAKER_01:Let's do that last part one more time.
SPEAKER_00:Okay. Tell me when. Oh, okay. So let's end on that.
SPEAKER_01:Richard. Take a breath before say take a breath and then start it.
SPEAKER_00:All right, so let's end on that, Richard. Excellent podcast. Uh I think our audience is going to get a ton of value out of this. And there probably should be another follow-up uh as there'll be a ton of questions around uh this discussion. So uh on behalf of Richard Bliss, I'm Brian Backstrand, and thank you for listening to Marketing 911.
