LinkedIn tests suggested feeds, widening content distribution

LinkedIn is testing a new "suggested feeds" feature that would show users content from outside their immediate network, according to Social Media Today. The mechanism echoes a feed experiment LinkedIn ran in 2024, but the renewed push signals that the platform's product team considers algorithmic content discovery a strategic priority, not a passing curiosity.

The default LinkedIn feed has always been a first-degree and second-degree network affair. You connect, you see. Suggested feeds would introduce a third current: content surfaced by LinkedIn's algorithm on the basis of topic relevance, engagement velocity, or creator signals, without any prior connection between poster and viewer. That is a structural shift in how content circulates.

What the test actually changes

For most of LinkedIn's history, reach has been a function of network size and post quality together. A senior executive at a multilateral institution or an industrial group could produce a genuinely incisive post and still see it go no further than a few hundred connections, unless someone reshared it into a new network cluster. Suggested feeds would decouple reach from network size, at least partially. The quality of the argument, the relevance of the topic, and early engagement signals would carry more weight. Network size would matter less.

That is not a trivial reordering. Smaller brands and newer executive voices, without deep LinkedIn connection graphs, would be competing on content signal rather than relationship capital. A policy director at a philanthropic institution with 900 connections, posting precise analysis on climate finance, could surface to an audience that the institution's company page never reached.

The inverse is also true. Accounts that have coasted on large follower counts and low-insight content would face a harder distribution environment. Suggested feeds optimise for engagement rate, not raw network size. A post that generates 200 qualified comments from a pool of 1,000 viewers will almost certainly outperform one that generates 300 likes from 15,000 passive followers.

The 2024 parallel and what it tells us

LinkedIn tested a variation of this in 2024. It did not roll out universally. The fact that LinkedIn is testing again suggests either that the earlier test returned ambiguous data, that product leadership changed the acceptance threshold, or that the competitive pressure from platforms with fully algorithmic feeds has intensified. Probably all three.

The pattern on platforms that have made this shift is consistent: initial reach gains for high-quality niche content, a short disruption period as engagement benchmarks reset, then a new equilibrium in which editorial quality and posting consistency determine distribution more than follower accumulation does. LinkedIn's audience, which skews toward professionals with finite reading time and genuine occupational stakes in the content they consume, is not identical to a general social platform. But the directional logic holds.

For financial services firms, where compliance constraints already limit what executives can say publicly, this test has a particular implication. The audience that reaches a financial regulation post through a suggested feed is, by definition, self-selected for interest in that topic. The signal from that engagement (saves, follows, DM requests) is more qualified than the same number of impressions served to a diffuse general network. That is the kind of engagement that moves pipeline.

Where this lands for brand and authority building

Brands and executives who have built LinkedIn presence on the assumption that connection accumulation is the primary lever should reconsider the mix. If suggested feeds roll out broadly, the calculus tips toward post quality, topic specificity, and early comment velocity. Posting to prompt a specific response, asking a precise question or staking a clear position, will generate the early engagement signals that algorithm-driven feeds use to decide whether to amplify.

For institutions in the UN system or major industrial groups, where executive communications teams often draft posts optimised for safe internal consensus rather than external engagement, this would be a costly habit. A post that generates zero controversy and twelve likes will not surface in a suggested feed regardless of the organisation's prestige.

The test is not yet global. LinkedIn has not confirmed a full rollout. But the direction is clear: the platform is moving toward rewarding content that earns attention from strangers, not just from people who already know the poster. Building that capability now, before the feature ships widely, is the practical response.