LinkedIn Algorithm Shift: Alicia Teltz on Posting Frequency vs. Quality

In a recent LinkedIn post, former LinkedIn employee Alicia Teltz offers a fresh perspective on content posting frequency and its impact on impressions, suggesting a significant shift in the platform’s algorithm.

Teltz challenges the long-held belief that simply posting more content guarantees higher reach. Citing data from TheShieldIndex, she highlights a recent algorithm change that appears to penalize excessive posting.

“It proves that your impressions will drop by 65% if you publish content more than 4+ times a week vs. just once every two weeks.”

This observation directly contradicts the intuitive notion that higher volume should lead to higher overall visibility. Teltz illustrates this point with a hypothetical scenario involving three individuals, each with 10,000 followers, to demonstrate the diminishing returns of frequent posting.

The Diminishing Returns of High-Volume Posting

According to Teltz, the common assumption that more posts equate to more overall impressions may not hold true under the current algorithm. She presents a comparative analysis:

• Person A: Posts 3 times per month, achieving an average reach of 16% per post, resulting in approximately 4,800 total monthly reach.
• Person B: Posts 10 times per month, with an average reach of 10% per post, yielding around 10,000 total monthly reach.
• Person C: Posts 20 times per month, experiencing an average reach of 5.55% per post, leading to roughly 11,100 total monthly reach.

While Person C achieves the highest total reach, Teltz points out the disproportionate effort involved. “Yes, more posts can increase your total reach. But doubling your output only adds 1,100 impressions. A lot more effort for barely more payoff,” she writes.

Unpacking the Algorithm’s New Logic

Teltz posits that the recent algorithm update, driven by LinkedIn’s new Large Language Model (LLM), is designed to prioritize two key factors: persona-relevancy and content quality. She theorizes that the platform now assigns a “spam score” to each post based on both content and engagement quality.

“For 2., *my theory* is that LI’s new LLM gives every post sort of a spam-score based on two things: 1️⃣ Content Quality… 2️⃣ Engagement Quality… If both scores are low, *I assume* LinkedIn throttles your post.”

The AI signals, promotional intent, and harmful content are assessed under content quality. Engagement quality, particularly within the first 90 minutes of posting, is evaluated based on factors like AI or pod engagement, promotional spam, and the depth of discussion in comment threads. Teltz suggests that creators who treat LinkedIn purely as a “systemized content machine” are most vulnerable to this throttling.

Prioritizing Quality and Genuine Engagement

For creators whose content is genuinely valuable and drives authentic engagement, Teltz believes posting frequency becomes less critical. “If your content is GOOD, it will drive genuine engagement, and therefore, posting frequency doesn’t matter. Your posts will still perform,” she asserts.

However, for those struggling with declining impressions, especially those posting frequently with diminishing returns, Teltz advises a strategic shift. She recommends reducing posting frequency to dedicate more time to:

1. Improving content quality.
2. Engaging genuinely with the community through comments, connections, and direct messages.

Teltz acknowledges that her analysis is a simplified take due to platform character limits, but her core message emphasizes a move towards strategic, high-quality content creation and meaningful interaction over sheer volume.