![]() "It's very rare for someone to stand up with a megaphone and shout to the whole office and everyone's like, 'Great, I want to hear more from this person yelling at us with this megaphone,'" Roth says. No single discussion is relevant to every person across every team - just as no single piece of content should be relevant to everyone across LinkedIn. He says it's helpful to think of LinkedIn as a digital version of the workplace, where there are a lot of teams with a lot of individual conversations. That's a big reason why, as Roth said earlier, the LinkedIn system does not reward virality. Instead of just reaching lots of people, they say, they want LinkedIn users to focus on reaching the right people. It can be a useful brand-building tool, and can lead to more business.īut they want users to think differently. Roth and Xiong know: Some people want a lot of likes and followers on LinkedIn. "We really appreciate creators taking creative liberty and using their personality," Xiong says. But because I added perspective that reached a target audience, it resonated and grew. Had I just posted the photo of the funny sign, LinkedIn would have shown it to fewer people. In part, it's looking to see whether a post is offering generic information (which is less rewarded) or is drawn from the writer's perspective and insights (which is more rewarded). LinkedIn uses artificial intelligence to classify posts into different categories - including, for example, whether a post contains opinions and/or advice. Xiong said my post is a "classic case" of a "share, opinion, advice" post. The post did well, getting more than 2 million impressions. To understand how LinkedIn evaluates posts, I showed Roth and Xiong one of my own - a post in which I shared a funny sign from outside a coffee shop (that I found online), and offered some related advice about how to feel empowered after someone insults you. "Our system is like, 'This is a conversation, and people want to be part of this conversation. If you respond to the comments on your post, that's also a positive sign and could get the post more attention, Roth says. ![]() If a lot of marketing professionals comment on your post, LinkedIn sees that as a positive sign. LinkedIn is also considering who these commenters are - are they random people, or are they from a particular group? For example, imagine that you post something about marketing. Now it rewards posts that get what Roth calls "meaningful comments." This means that people aren't just dashing off empty comments - stuff like "great!" or "so true!" - but are instead actually responding to the content of the post. As a result, some users banded together into "engagement groups" - essentially agreeing to quickly like and comment on each other's posts, as a way of boosting them. In the past, LinkedIn would amplify posts that got a lot of comments. "So if I put that up there, LinkedIn has an obligation to be like, 'Hey, this is not the highest quality content, Dan has none of the skills in this area, and we have not seen him have success with geology content in the past.'" Roth offers an example: He has zero background in geology, so what would happen if he posted on LinkedIn about how to be a great geologist? "That is useless, because I don't know what I'm talking about," he says. "Because we have the professional profile of record," Roth says, "it helps us be able to make sure that we are getting the right content to the right people." It is now also evaluating you - and whether you're an authority in the thing you've posted about. When you post something on LinkedIn, the platform isn't just evaluating the value of your post. The author is writing in their core subject area. ![]() "That is the kind of thing that will likely get you to reach the right audience as well."Ģ. "Advice to give to the creators out there is, think about what kind of knowledge you have to offer to help people," Xiong says. Or maybe you've posted about B2B marketing, and the system will start showing it to people inside that community. ![]() Sometimes, the answer is a small number of people - maybe you've posted about your family, and so the system decides it's only relevant to your closest connections. Its system looks at every post and basically asks: Who is this relevant to? ![]()
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