← The Marketing Millennials
The Marketing Millennials
2026 LinkedIn Content Playbook with Mark Jung, Founder of Known | Ep. 381
00:39:39
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- [00:01]
A
Proving your marketing ROI shouldn't be a guessing game. But when results are hard to track, it's difficult to know if your marketing strategy is working. Meet CallRail. In a few clicks, you can connect every conversation to the exact campaign that started it. So you can focus on what works and drive better marketing outcomes all in one platform. Try it free today@CallRail.com proveit welcome to the Marketing Millennials, the no BS marketing podcast. I'm Daniel Murray and join me for unfiltered conversations with the brains behind marketing's coolest companies. The one request I tell our guests stories or it didn't happen. Get ready to turn the up. We are back with another episode of the Marking Millennials podcast. I'm here with Mark Young. You might have heard him in my podcast before. He is a Canadian turned Cayman Islands. Don't ask why he moved to the Cayman Islands. He won't tell you. But he also is one of the best out there at LinkedIn. He's also my business partner. I don't know why I got into business with him, but that's another question as well. And we basically have a LinkedIn agency and we, we help people grow on LinkedIn scale everywhere from founders, CEOs, SaaS, brands, on niches like go to market people. But we're going to talk about how to win on LinkedIn in 2026. What's new the old way, the new way. And what are some things you could do today to uplevel your LinkedIn? But Mark, I want to give you a little time to just go into what's happening on LinkedIn right now. What's the state of the algorithm so people know how to win first because you need to know the rules on the field to be able to play the game.
- [01:59]
B
Yeah. And you know, unlike Daniel, who played, you know, D1 football, you know, go Cincy. I remember we were in Dallas watching a game together and he gave me his jersey, which at the time like went down to my knees when I put it on. No one of us was sporting, the other one coughed. Me and my parents put me in fencing. So that was my sport. But the one thing that I think Daniel and I always agreed on and got along in, you know, in our career was we're scoreboard people. And you know, having the data and the metrics and understanding how to get better when you look at the scoreboard is based on rules. So Daniel and I did a talk similar to this back at Inbound in San Francisco for HubSpot of how we did 607 million organic impressions on LinkedIn in 2024. And we talked about our framework, Juicy. The name is interesting. We had Daniel and I in Juicy couture outfits, those sweatsuits in light blue. But anyways, we named the framework to be memorable. The reason why we wanted to jump on today is we had a lot of people come to us and ask us about the current state of LinkedIn, how do you win on the algorithm right now and what's happening? And the good news is that LinkedIn has probably made the most relevant shift in terms of how they operate since the origin of the platform. So what we're going to talk about today is we're going to take you through the most relevant new state of the LinkedIn algorithm, which TL. Dr. If you don't know this, but Daniel and I is we read every single academic white paper that the LinkedIn engineering team produce, their API team, everything we study, their journals, their white papers, everything to give you tactical tips. And this is a big part of how we put the same kind of effort and strategy into the agency. So I'm going to dive right in. I'm going to talk about the quick hits of what's changing, we're going to talk about the white papers, where to get into specifics, and then if you're lucky, we can talk about Juicy and Daniel can share some of the anecdotes from Stage. But Daniel, anything else? Does that sound good or are you ready to dive in?
- [03:54]
A
Yeah, let's talk about that. I think this is dive in. Mark is a LinkedIn nerd when it comes to the algorithm, so I'm going to let him dive deep into what it looked like before. And now how are you going to win if you know what the algorithm wants you to do?
- [04:11]
B
So I'm going to start with the three key trends that are different right now in the current state of the algorithm. And then we are going to freaking nerd out together. I will explain all of what's changed in LinkedIn, where we're coming from, the timelines, and again, if you all want to know more about this stuff, if you want Daniel and I to do a webinar on it, go deeper on it, let us know, hit us up, make sure that you make yourself known, and we can do deeper content on this. But the three things that matter most right now on LinkedIn, this change happened about October 16th. That's when, at least when LinkedIn, LinkedIn publicly started talking about this, 2025 is LinkedIn have actually moved away from Their old model and the TLDR of their old model was like they used to use what's called like embedding based retrieval, which was how they were doing a number of different things to match you with content. The new world of LinkedIn is they've actually rolled out their own LLM and the report, if you want to like follow along and look this stuff up, it's called large Scale retrieval for the LinkedIn FE causal language models. So bear with me, we're going to get through all the jargon and all.
- [05:19]
A
The crap and you can tell that was written by an engineer, not a marketer.
- [05:24]
B
Yeah, exactly. They publish this stuff in Arxiv, which is their abstract technical journals. So if you actually want to find it, you have to go in and anyways you can download all the PFS and go through it. The TLDR though, of what's changed and I'll try to tee this up as relevant as possible into three core changes. Number one is that this LLM is actually looking at what's called like entity relationships. Specifically if you are thinking about something really basic like Wikipedia, Wikipedia is a really good example of how like entity relationships work. Let's say that Daniel was looking at like Tim Cook of Apple. Tim Cook has a ton of stuff that's written about him publicly. People know who Tim Cook is, they know what Tim Cook's relationship is to Apple, they know what Apple's business strategy is. So it's very easy for someone to form a web using entity relationships. About Tim Hook, Tim Cook, his position in Apple and what Apple was trying to do. What the new kind of like llama3llm model that LinkedIn rolled out is doing now is they're actually being able to look at like the meaning behind your potential entity relationship on LinkedIn and the intention behind what you're trying to accomplish. Specifically. What matters more now is Your bio on LinkedIn matters way more than it used to. Your relationship to other entities, as in what, what LinkedIn calls here cohort seating, who specifically you're engaging with. And LinkedIn has actually changed their engagement model. LinkedIn used to have a mix of positive and negative signal, as in negative signal, like if something showed up in your feed and you ignored it, didn't engage with it, LinkedIn used to take that into account before. They've actually gone away with that completely. LinkedIn now is a positive signal only platform, meaning only what you engage with is part of what this LLM is now painting a picture of related to what it wants to show you. And what you think basically like LinkedIn is trying to make a bet on like how to monetize the silent majority or the net new creators.
- [07:29]
A
Yeah, it's kind of like what they do on TikTok where if you like a video on TikTok they're going to show you more of that topic.
- [07:38]
B
Actually completely different in this case. And what's interesting is very, very different. But there's a new engagement window on LinkedIn unfortunately now there is both a compressed window of about 30 minutes from time of what engagement looks like. But there's also a really interesting thing that you can gamify which is called token compute power weighting. What this means is that LinkedIn's new LLM and they've actually gone on record to say this, the first 60 tokens that they're using to analyze content is the highest weighted in terms of its analysis and how much it's going to boost you relative to basically your audience, what you say your content is for and what it's doing. So we'll get into specifically of how you can front load the depth in your post with this new 60 token compute rule. But the last thing that really matters here is that LinkedIn's big bet on video. If you remember LinkedIn used to have a video button. It was like create video, they've gone on record, they're VP of product to say that this experiment that they bet on didn't work and that they're finding new ways to basically try to monetize the people on LinkedIn, that they want to become more active creators. So the benefit of this, and we'll get into the specifics now, is as a net new LinkedIn creator you can have 50 followers and still have the reach of someone with 50,000 followers if you are following these new rules. So recap before we get into stuff is like your bio and your profile and your entity relationship matter a shit ton more than they ever did. You have positive signal only in the feed, which means what you engage with needs to be hyper intentional to match what you're saying your content is for. Your audience is should only be engaging with the right people that match your cohort. Seating your engagement window in the first 30 minutes and the first 60 token computes analyzing your post really matter a ton now and then more overall is what this actually means going forward. So did that make any sense to you?
- [09:44]
A
There's a couple of things that I'll simplify it for some people which I interpret what not to do is one, what I think a Lot of problem with people do in the algorithm is they send their posts to the whole company which aren't in their ICP or a pod of people that aren't in the icp. And what you're doing basically telling the algorithm when you do that is I have all these random people in my ICP and show my content to like I. They don't know who to show your content to. So you're engaging with random people and you're out. And that's why the algorithm gets. Your feed gets all messed up because you start engaging with random people. So I always tell people that company boost thing that they do is actually a deterrent on, on your post. Secondly, what I also got from this is that LinkedIn like they did with stories can't figure out how to monetize ads and video. So they're not going to do it anytime they like. That's the whole point of creating a new feature is like finding more places to create revenue. And they can place an ad into your video so into that video feed. So they're not going to do more of it just because they can't place ads. It's not a video first platform. So that's something else I got from it. And then also I think it's just so hard for video to bring people off the platform versus like images and text like because the, the text gets so compressed in the video when you, when you write that nobody really clicks see more on a video as much as they click see more on an image and tech. So those are the kind of things that I high level I got takeaways from is like, it's like who you, if you want intentional stuff you have to engage intentional intentionally on the platform. And also like video, they can't monetize like stories. It's cool that they try to be like other platforms, but they're never going to be other platforms and they need to find other ways to win. And that doesn't mean stop doing video by the way. If you're great at video, keep doing video. It's a great way to win. But if you're not, it means that video is not the only way to win on LinkedIn.
- [11:59]
B
Yeah, I'll give you three quick tips that Daniel and I have used and if you heard them before then I'll give you the updated version. But there's three relevant things that have changed and then we'll get into kind of the history what's changed in the algo and really like diving into the meat of it. But if you noticed originally in LinkedIn, if you started to see in your metrics or analytics how many people are saving your content, how many sends are there? One of the reasons why LinkedIn started to show comment impressions was because they wanted to find a way to engage this silent majority who maybe don't engage that much. If they're not going to post, they're not going to record videos. They wanted to reward them by showing them some metrics behind what they're doing. So just think about the psychology behind it. You're posting a comment back in the day, you didn't know how many impressions it got. Now you know when your comments are actually doing well, it's encouraging people to double down on that behavior. So LinkedIn said, okay, how can we reward creators who are creating content but now seeing lower organic reach, right, Because a lot of brands saw a big dip in organic reach because LinkedIn dialed it back and then tried to get you to pay to boost your own content. So that's when LinkedIn started to roll out. You'll see it in more kind of like ga, like general availability later on. Saves and sends. The reason these silent metrics matter is they signal to creators that you're creating the right content. Similar to how like Instagram reels and other platforms use saves and send as like an indication. I'll eventually take you through kind of like the 2021 Save link of when they introduced dwell time for the first metric. There's like active dwell time and there's post click dwell time and they're both different and they actually implicate sort of like they have a different weighted ratio in the current state of 2025. But the second thing that is relevant here as like a quick win is if you're familiar with like hey, lawyer style billboards, you've probably seen them in Miami. Like the last time I was in Miami visiting, you know, Daniel, they have these, these billboards from lawyers that say, hey, were you hurt in like a hotel accident? Were you hurt in a parking lot at a big store? You know, did you get like, I saw one that was like, did you get a DUI in a boat? Like whatever it was, it was like hyper specific, calling out the audience. With LinkedIn's new cohort seating, being able to quickly signal who your post is for and who it is not for is one of the most important signals with both the LLM analyzing your content and you actually reaching the right cohort of people to engage with it. So that's something we're going to talk about, but getting really tactical. One thing that Daniel and I have been big proponents on and have pretty much been testing since like we joined LinkedIn is how to use links in your LinkedIn content. One of the ways that still wins today that is super valuable is called the 14% rule. And Daniel and I talked about this in, you know, on stage at Inbound for HubSpot. And I'll give you a 90 second recap. Now you can edit your post after like 10, 15 minutes, up to a total of. We use 14% of the total character count. You can technically do 15, but we found 14 to be kind of the right amount. So if you wrote 1000 characters, you can edit your post up to 175 characters. My math is about correct, about 14% without penalty. So one of the easiest ways, if you want to direct people to like a newsletter, an event, something like this, do not put your link in the comments. There's like a misconception for LinkedIn that the link in the comments is the right thing to do. It is absolutely not. What you need to be doing is that LinkedIn in its current form of the algorithm, doesn't actually care if you have a link in your content. What they care about is how many people see that link and how many people click it. What LinkedIn wants are, are people actively engaging with what you're doing. And if your intention is saying, hey, here's a free resource, but then it's a web page that's taking you to like an event or something like that, it's a paid promo or it's like a buy. They want to make sure that you aren't bait and switching people. So the problem with link in the comments is that people think it's the right thing, their comments. They comment themselves as the first comment on their own post, which LinkedIn already sees as spammy behavior when you're commenting in your own content after it just gets published, then you're putting a link in there, which by itself originally LinkedIn started to deprecate and downrank. Now they don't do as much. What you want to do Instead is wait 15 minutes till your post has some organic engagement, go back and edit your post up to 14% of the total character count and put that link either in the second line so it's still visible in the feed above the fold, or at the end of your post. And you want to make it so that people will actually click this link. So add white space around it, add an emoji, add brackets, but like make sure there's clear white space of like the link and it's very clickable. The other thing that you can do with links that's super, super relevant and Daniel and I talked about this is you can do resource posts on L. So the second type of way you can use links is if you wanted to publish something that was like, hey, here's like I've curated a bunch of winning ads. Here's like my mirror board, my figma, whatever it is. If you're publishing a link roundup, you can actually use four to five links in a post. And as long as you see the right metrics, as in like link clicks, saves and shares, that post will do way better than a post that you just did naturally and put a link in the comments. So typically by default we default to these two styles. Don't post something that has a link in it by default unless you're making that link very visible. Or if you do wait 15 minutes, edit 14% of the character count, add it as the second one or the last line or if you use links, use a bunch of links as a resource heavy post that will get fed into the algorithm with saves and shares. So anything you want to add to that? Before we talk kind of history and.
- [17:37]
A
Specifics, as marketers we're all trying to answer the same question. Which investments are actually driving driving revenue? And too often the honest answer is an educated guess. CallRail replaces that guesswork with proof. With the help of AI, you can connect every lead to the exact campaign that drove it, analyze your conversations and capture leads around the clock. That's why over 220,000 businesses use CallRail to market smarter. Stop estimating impact and start proving it. Try CallRail for free@CallRail.com prove it. I just think I want to I mean we, we we talked a little bit that we said juicy in the front as our like framework but I want to double down since you brought it up already of like the sea of juicy that we use is commoding and the one of the biggest ways that I we saw in 2025 that I at least saw in the marketing millennials that got I would say double the amount of reach than just feed posts are from comments and the reason this works and we'll go into some other things of what other things they had but common impressions signals that LinkedIn wants you to do more commenting so they're rewarding comments and seeing you can see it more in the feed and that's actually helping follower growth more than anything especially on company pages. So if you have a company page and you want to win on company pages, it's so much easier to win on commenting. Second, they just releasing reposts and shares. I mean saves it. Since this is the most important metric I think on Instagram And I think LinkedIn saw that and now they're doing it as well on there. But this is how you know you're creating content that's winning if you can get that save and share button. And there's easy ways to get those numbers up simply by saying save this post for later or share this with a teammate or if you could signal a CTA to get people to do that. But something that I've been looking at more and more, and I think we're in the shareability era of content right now, is like if you, you need to create content that is worth sharing with in the, in the DMs and that's on Instagram, that's on LinkedIn, that's on a newsletter. If you can optimize for shares and have CTAs to say share it, you're going to win. Because algorithms inboxes want to see more engagement with your email or your or your post. So optimize for those two metrics now. Now that LinkedIn showed it. And that means that LinkedIn wants more of those actions and more activity in the dm. So those are two things I'm going to add. It's like double down on commenting in 2026. And when you're creating content, figure out ways to up get those sends and shares up. And that's why resource posts wins, right? I think like they win because people are sharing resource posts like they're sharing, they're screenshotting it for their team, they're spending time on the post. So I just wanted to add to those two quick points. Yeah.
- [20:53]
B
And you know, you may be listening to this and go like, you know, why should I listen to these? You know, these two guys, like, you know, can they really deliver what they're saying? So, you know, Daniel and I have created tens of thousands of LinkedIn posts for our clients that we represent. And you know, we run a kind of like a stealth agency. We don't talk about our clients, but what we do is we tend to use the exact same strategies for our own content. You know, my last kind of five posts, I've shipped 10% of the content I typically post in a year. This year, because we've been creating so much content. You know, that classic social thing is like your design portfolio is empty because you've done thousands of design projects for clients. Even though I have posted a ton less personally this year, typically if I'm doing five to seven posts a week, my posts are averaging between 200,000 to 400,000 impressions per post because Daniel and I are using the exact same system ourselves. So in the period where I'm doing five to seven posts per week, we're doing over a million impressions easily per week. Now, one thing that's super interesting and I'll talk more about this and this related to kind of like the current state of the algorithm that I'm going to rewind back to 2020 at a very pivotal moment of when the algorithm changed and come back to tell you about the current state and what's going on. Post cadence and cannibalization of engagement is the best it's ever been on LinkedIn. Here's what I mean when I say that back in the day in like early to mid 2024, you had a six hour window that LinkedIn would analyze your engagement, a one hour window and an 18 hour window. And what this meant was that if you posted more than once in an 18 hour window, you'd be cannibalizing your own reach and engagement. What we have found is that actually content velocity is one of the most important metrics to success in the current state of the algorithm. We have net new pages that Daniel and I are grow now that are posting 21 times a week, three times per day, seven days a week, and they're still averaging 7 to 8 million impressions per month per page. And one of the reasons why is coming back to the long tail and the video bet that kind of failed for LinkedIn. So I'm going to talk a little bit about that and then we'll get into the specifics and then we'll get into kind of the meat of the current algo. So if you noticed before that LinkedIn moved away from that like plus to make video button, their bet was LinkedIn wanted to monetize the silent majority. You know, the 90% of LinkedIn that don't actively create content, they're either just maybe commenting or they're just viewing. So their bet was hey, if we have like a one click video where any executive, any person on LinkedIn can just share their take, we can add subtitles and we can give it distribution. As in like give them that taste of what getting a reach felt like. That's why typically when LinkedIn ships a new feature, polls, anything like that you can tell the engagement is typically off the charts when it starts because they're trying to psychologically reward you to do more of that thing. So their bet was that people would actually start creating video. Those people would then become more active on LinkedIn and they'd pay for premium features. They failed because the problem was people were uploading really premium, high fidelity, polished videos that made people not want to share video content. Content, right? Like there wasn't a low bar for entry, as in, hey, everyone's doing this and it looks good and I feel good. People were publishing their like really premium Instagram and YouTube videos. So by default people were like, no, I don't want to do that. And then their bet on video and like video being the thing for LinkedIn to monetize, these people didn't work. So LinkedIn went back to the drawing board and they said, okay, like, how do we get more people on LinkedIn to spend money and spend more time? So what they found, and this was like early in 2020, 2020, in May, it was like May 12, 2020 was the first time they ever publicly talked about this. This is when LinkedIn introduced dwell time as a metric. And if you're unfamiliar with dwell time, basically what it means is there's two types. There's on the feed dwell time, which means once a post, I'm holding up my phone here. Once a post comes into 50% of your viewport, like your screen, it's measuring how long you're spending looking at that post before you click or have any interaction. So they're looking at like how long you're dwelling on stuff. The second thing they're looking at is called after the click, dwell time, which is how long you actually spend on the content after clicking it. And what they found was that when they used dwell time as an indicator to rank content, they were able to serve better performing content for people. And I think they increased like engagement and like monetization by a few percentage points back in this like 2022 E, which was like an aha moment for them. So I'm going to skip forward to like a lot of the technical crap because like, you guys don't really need to care about that. But essentially what, what mattered as a result of that was LinkedIn started to have all these little experiments of how they could get people to be more engaged and how they could get more money out of them. So later that year in 2024, they published this study called Like Li Rank, which was like a study of how they were Scaling what's called like the non technical version of it is they basically created what's called towers of engagement. It's like the technical term that they used in these studies. And what they looked at was something called a click tower and a contribution tower. The click tower was predicting how likely you were to click on something and how likely you were to dwell on something based on a past record of what you had done. So this was what Daniel was talking about before of TikTok. TikTok has a really good way of serving you stuff that it thinks you're going to like. So LinkedIn then had another tower called the contribution tower which was, they were predicting comments, shares, votes for polls, things like this. But the, the TLDR was like both of the towers were meant to like help you serve more content that was ideally going to keep you on the platform and making you pay. So they did a bunch of stuff and they had a few percentage points lifts, blah blah blah. So they've been doing a lot of these tests under this current model for the past like four or five years. But in 2025, as of October, they've made a really big architectural shift. So Daniel, this is where I'm going to talk about where we were before and where we are now. So the old way is LinkedIn used to have five separate very specific retrieval stacks. What I mean by that is remember at the beginning when I talked to you about the embedding based retrieval matching thing. What they call EBR is basically embedding based retrieval. The way they used to do it was they had one for members. So you'd have one basically embedding based retrieval matching for similar members to you. So content that was seen by similar members, they then had one for global trending topics that were popular across LinkedIn in general they had ones that were trending for specific geographies so they could match what's popular in your location. They had cohort specific EBRs that were like people similar to you are engaging with content like X and then they had like trending in industry. So like what's popular in your field. This is the first time that they've actually moved away from the system based on what they've talked about here to this new like LLM model where they're actually saying okay, I'm actually going to look at your profile and I'm going to create like you know how you create a prompt for GPT or CLAUDE or whatever it is and you like are trying to do prompt architecture. What LinkedIn are doing is they are actually doing the exact same thing, almost like the Matrix was doing for every single person on the platform. They are making a prompt about you. It has your name, your headline, your company, your industry, it has your content type of whatever you typically post about. And then what they do is they actually benchmark your popularity. So one of the interesting things about the state of the algo and like I talked about was like they can't parse raw numbers. So what they did is they started grouping creators into popularity bands. So they would say actually like you typically see, you're typically in the top 7% of creators in this niche and you see that in your first 30 minutes. And then they're still, they didn't talk about if they're still benchmarking at the 6 hour and the 18 hour mark. But what we've seen is that like it's more about your overall band of engagement. And I'll talk about the benchmarking and how to gamify that later. But basically what's happening here is this is the first time in like LinkedIn's history where they have started to do this without you. If you rewind back to like Daniel, do you remember when we used to get the AI contributions from LinkedIn?
- [29:38]
A
Yeah, that's so that was the most annoying thing in the world.
- [29:41]
B
So that was actually LinkedIn's bet. If they could have us as people on the platform do this work for them. Them. We had to go and select a category we belong to five keywords. We had a maximum of five keywords of things that we posted about. And then we were basically creating content to earn like an AI badge, saying we were like a top marketing badge or whatever it was. LinkedIn now are doing that work for you based on what's in your bio. So the one thing that's super important now is like back in the day you could have a lot more freedom of what's in your bio. Now you actually need to craft your bio with, with a lot of your past credibility, your metrics, your exact title, your company, your industry, who you're trying to reach, because you need the LLM. It's kind of like LLM TXT, where some people, you know, like AI search said it doesn't matter that much. For LinkedIn, this matters a lot. So my number one reco in the current state of the algo is go back and actually evaluate your bio based on the current state of the algorithm and you want to look at these very specific things. If someone who didn't know you landed on your profile, could they tell you what your ICP is, what your industry is, exactly what you do, and does it have credibility metrics that I should trust you? If the answer is no to those questions, you need to front load your profile to have these. And you want to think about how the LLM is actually going to be going through and like parsing. And one of the reasons why LinkedIn's doing this is like they're trying to reduce technical debt. They have a ton of technical debt from the old system. So they're trying to reduce compute power and simplify this stuff. So think about how a bot would parse your profile and how it would analyze you as a creator, headwind and being hyper specific. So don't say, hey, I'm like a lot of people say I'm VP of marketing and then they talk a little bit about what they do. I'm a B2B SaaS marketing VP. Right. Who specializes in like account based marketing for this audience or whatever it is. You want to get hyper specific with your headlines and your taxonomy as it relates to your entity relationship in the field. It's like the way that we need to map it.
- [31:51]
A
Let's get into one or two things that someone could do today to win on LinkedIn. You could start with one and I can add on and then we'll wrap it up with that.
- [32:03]
B
Yeah. So the first thing that you want to do outside of doing the bio is you really want to think about in the current state of this new algorithm, because LinkedIn are trying to save compute power. One of the things that's really relevant for them is they're really starting to analyze you and who they think your content is meant to be for. So I know that I talked about kind of like the hey lawyer style of signaling for content, but. But if you remember at the beginning I talked about LinkedIn's 60 tokens of compute power, there's a really interesting thing that they published in the report that I thought was helpful because I'm the kind of person that wants to understand whatever they've publicly said here and addressed. I want to know what they've gone on record to say in this so that I can kind of reverse engineer how to win. And one of the things that they've actually gone on record, publicly to say is that the first 60 tokens of compute power in analyzing your content have the most weight. Do they tell us exactly how they weigh it? No, but what matters is that if you had a video, let's say you Had a video piece of content and it was like a POV that takes a lot of compute power to analyze that video. LinkedIn are doing these in under 50 milliseconds each. The hook of your content in the past used to be could be like oh I failed this time in my career and here's what it taught me. But blah blah blah. These more engagement bait style of storytelling hooks used to be, they used to work well. LinkedIn are looking for signals of authority and credibility now as part of this compute power for their tokens. So my big belief is that actually depth driven hooks with very specific metrics, the exact situation and calling out the exact cohort of audience you want to reach in your text hook and rehook will actually start performing way better than more of the bait and hook FOMO like getting people to click to see more on the hooks. So I'd say take some time and test out more of like that style of hook content because they've gone on record to say that that is actually what matters more in the waiting for your how you show up in the algorithm.
- [34:06]
A
Now I think I'm going to add something that you have to add that hook that Mark says. But I think an easy low left way to win on any social platform but especially LinkedIn is look at what's working in adjacent or other industries and figure out how you can make content like that for your industry. This is something we do a lot with our content is we'll find posts that have got attraction on other platforms, Reddit x Instagram, TikTok but not in our industry adjacent to our industry and say we look at it and say how can we make this for marketing? This is a very low left way to figure out to start posting the next level is what Mark said is like taking it to the next level and making more original in depth post. But if you're trying to figure out a way to share your ideas but also piggyback off other things that are winning in the algorithm, this is a way to get seen but also piggyback. So I would go look at what's winning, consume a bunch of content and then figure out how to when you're doing that, save it and figure out how to do that for your industry.
- [35:25]
B
Yeah, the 90 second recap here of what matters is that LinkedIn is now using an LL model. They're trying to simplify compute power and what that means is that they want to understand you and find a way to monetize you more as a creator on LinkedIn or a participant and they're trying to do a better job understanding you and your relationship to who you say you create content for or what you're on LinkedIn to do. LinkedIn are trying to show you more like job applications and ads and things based on this entire like semantic profile they're building about you. So the most important thing to think about that is okay, knowing that how can I design my bio in a way that's hyper specific, that positions me as an authority that signals exactly what audience I am for and can help make that easier for the LLM. It's kind of part one. Part two is now that LinkedIn only uses positive signal. You know that you can control what your feed looks like by being very specific about who you engage with. And you're gonna have more people seeing your content as a composite of what you've engaged with. So if you're trying to reach, for example like Rev Ops people, you should only be engaging with people in the rev Ops field because that profile is not only gonna be used as a modifier for your own content, but for who's gonna start to see your content. So you can keep in mind now with this positive only signal model, you shape a bit more of your destiny on LinkedIn. And if you're a net new creator, LinkedIn wants to reward you. They wanna make for you to actually grow. Your follower count doesn't matter as much now. It's more about like you getting benchmarked in what percentage of engagement in your designated cohort. So try to be very specific about calling out exactly who your content is for, trying to front load your metrics and try to take advantage of this new kind of like 60 token compute model. I can't tell you how much compute power those tokens are, like how long it actually gets through your post of analyzing it. What I do know is like front loading the depth of your content and the authority and the POV behind it. Daniel and I do a lot of humor on LinkedIn, but we do what's called edutainment. So we pair entertainment with education. So if we're doing a meme or something funny, you can bet that there's a lot of depth and POV behind it. So at the end of the day, have a strong point of view of conviction. Make sure that that story shows up in your profile and in your content because any type of gamification or stuff that you can do for the algorithm won't work unless actually have something meaningful to say conviction and like craft in what you're doing. So I know that we there's so much to cover this stuff and I literally could talk about this for eight hours.
- [38:02]
A
Yeah, if you guys want us to do a part two on this, please DM me on LinkedIn or DM Mark Young on LinkedIn and or just hit up us@DanielThorityB2B.com yeah, I think this is a topic we can go for hours and hours but I wanted to compress it. But the main takeaway is you can win on LinkedIn. There's strategies to win on LinkedIn and I hope this episode helped. And until next episode, thank you for listening and we appreciate any feedback you have. So see ya. Thanks so much for listening. Keep tuning in in to hear more great insights from the coolest marketers from around the world. If you haven't already, make sure to subscribe and follow the Marketing Millennials podcast on Apple Podcasts, Spotify, YouTube or wherever you get your podcast. And if you like what you hear, I would greatly appreciate you giving us a five star rating. It helps bring more marketers into our community.
- [39:09]
B
Sam.