LinkedIn search hasn’t always delivered the content that users were hoping to see, but with a new overhaul that could be a thing of the past.

Its techies have been busy over the winter and created a new search experience that should help deliver better and more relevant results.

How has LinkedIn refined its search results?

LinkedIn explains how it refined its search results in this blog post, but the answer is incredibly techy and the post can be really hard to follow.

Basically, LinkedIn’s search results used to be drawn up based on your interests – information the system gathered from your engagement over time. That means you’ll be seeing content posted by people or about topics that you’ve told LinkedIn you’re interested in over a long period.

But now results will be thrown up from a wider variety of sources. So, you’ll now be able to discover content from more accounts than you previously did.

Data backed decision making

Searches for posts have increased 35%-year-on-year, so it makes sense for LinkedIn to re-engineer how that happens on site. With more engagement comes a greater incentive to give people content that will keep them liking, sharing and commenting.

How and why might this help businesses?

LinkedIn will now show users a wider range of content that relates to their search, which is good for brands because it increases the chance of discovery via organic means. More eyeballs on your carefully produced output can only be a good thing and can lead to more brand exposure and potentially more revenue.

A new algorithm

We mentioned earlier in the article that LinkedIn will now produce a broader set of search results. It will do this because the algorithm signals it looks out for have been tweaked to consider user intent, the relevance of the post to your search, quality, engagement, recency of the post and personalisation.

That last point, personalisation, is significant because it marks the start of a new approach for LinkedIn and the continuation of a trend we’re seeing across most of social media. Users will now be presented with more content that an algorithm thinks it will like, rather than content from accounts they follow.

The new system varies from the old one in some significant ways. For a start, search results can be personalised better because the new system will take into account real-time signals for members’ intent, as opposed to historic signals used under the old system.

In turn, that will increase the chances of a user discovering vital content or trending searches and posts will be ranked better when shown among other types of results.

Finally, search navigation will be given an overhaul and now users can search for posts from a specific author, view recently viewed posts and find posts that match quoted queries.

Big impact

The new approach should lead to more interaction and engagement because a wider range of people will now be shown your approach. For brands, this should be good news as your organic discovery should increase – provided you’re publishing good content.

The good news for marketers is that there’s already evidence of this.

Amol Chandla, Software Engineer, LinkedIn

“Pertinent results, which are highly relevant to the user’s search query, have led to an aggregate click-through rate improvement of over 10%. Increased distribution of posts from within the searcher’s social network, their geographic location, and in their preferred language has led to a 20% increase in messaging within the searcher’s network.”

What’s more, the time it takes to deliver search results is down as well.

More improvements coming

LinkedIn isn’t going to stop there, though. It says it will continue to update search – including a bit of software that understands the semantic meaning of searches better, an ability to show users the newest results for searches about trending topics, extra filters for Post search and the ability to handle a wider range of content.

Creators will also feel the benefits of LinkedIn’s new focus. 

Amol Chandla, Software Engineer, LinkedIn

“Results are ranked today mainly by using viewer-side utility functions such as likelihood of a click, user action originating from search, etc. To support our creators, we will evolve this ranking, along with our experimentation and testing stack to also optimize for creator-side utilities, such as content creation or distribution for emerging creators.”