How to Use LinkedIn's Post Performance Table to Grow Your Audience (2026)

LinkedIn rolled out a unified Post Performance Table on desktop. Here is how to track out-of-network reach, view who followed you, and export your data.

Charleston Smith

Founder, Vantr

Nov 5, 2026 · 8 min read

Photo by Priscilla Du Preez 🇨🇦 on Unsplash

On November 3, 2026, LinkedIn began rolling out a unified Post Performance Table within its desktop Creator Dashboard. Announced by Sam Corrao Clanon, LinkedIn's product lead for creator tools, the new view consolidates post-level data into a single, exportable table. Instead of clicking into individual posts one by one to check performance, you can now review, sort, and compare all your published posts in one place.

The update introduces several deeper reporting elements. For the first time, the table connects follower growth directly to specific posts, letting you see the actual member profiles of people who followed you from an update rather than just a total count. It also splits post discovery between in-network connections and out-of-network feed discovery, while surfacing private engagement signals like post saves and direct message sends.

As of November 5, 2026, the Post Performance Table is rolling out globally on desktop, with mobile app access scheduled to follow. If you publish professional content, write educational breakdowns, or pitch sponsors on LinkedIn, here is how the new table works and how to put the data to work.

What LinkedIn's Post Performance Table Actually Tracks

In the past, tracking post metrics on LinkedIn required manual logging. You had to click the analytics button below every single update, copy the numbers into a personal spreadsheet, and calculate conversion rates yourself.

The new desktop interface brings all historical post data into one structured grid that can be exported as a spreadsheet. The table displays your content chronologically alongside several core and newly expanded metrics:

Basic delivery: Top-line impressions (how many times your post appeared on a screen) and total members reached (unique accounts that saw the post).
Video consumption: Total video views along with cumulative watch time in hours and minutes.
Public engagement: Standard reactions (likes, celebrations, insightful marks), text comments, and public reposts.
Private engagement: Saves (members bookmarking your post to read later) and Sends on LinkedIn (members sharing your post via direct message).
Audience attribution: Total new followers gained directly from the post, paired with clickable profile links for those members.
Distribution source: A split between in-network reach (existing connections and current followers) and out-of-network reach (members discovering you through algorithmic feed recommendations, search, or reshares).

Having these signals in one screen makes it easy to spot which post formats bring in qualified industry peers and which posts merely collect passive views.

How to Find and Export Your Post Performance Table

The table lives inside LinkedIn's desktop Creator Dashboard. If the rollout has reached your account, you can access it through the following steps:

Open LinkedIn on your desktop browser.
Click your profile picture icon at the top of the homepage and select View Profile.
Scroll down to the Analytics module on your profile and click Show all.
Under Content analytics, click on Post impressions.
Locate the section titled Most recent post performance and click Show all posts.
The full Post Performance Table will load, displaying your recent updates in a multi-column list.
To review older updates, scroll to the bottom of the table and select Load more.
To take your data outside of LinkedIn, click the Export button in the top right corner of the table to download a CSV spreadsheet.

A good habit is to export this CSV file at the end of every calendar month. Storing your monthly exports in a dedicated folder lets you build a long-term archive of your content history that you control independently of LinkedIn's native interface.

Reading the High-Value Columns in the Table

Not every metric in the table carries equal weight. To refine your posting routine, focus on three specific data columns that reveal audience intent.

1. In-Network vs. Out-of-Network Discovery

Top-line impression counts can be misleading. A post that earns 10,000 impressions entirely from your existing connections means you are keeping your current audience engaged, but you are not expanding into new industry circles.

The out-of-network percentage shows you how much discovery the platform generated beyond your immediate circle. Posts with high out-of-network reach typically succeed because they offer structured, practical takeaways that encourage second-degree connections to read, comment, and share. When a post shows an out-of-network rate above 60 percent, study its structure, topic, and opening lines. It struck a chord with professionals who did not know you beforehand.

2. Follower Attribution and Member Profiles

Before this release, LinkedIn only showed an aggregate follower count across broad time windows. Now, you can click on the Followers gained number for any individual post to see the specific member profiles who hit the follow button after reading it.

This qualitative data is valuable. If you write an analysis of supply chain software and gain 15 followers, clicking those profiles lets you see whether those followers are supply chain directors, procurement leads, or college students. Knowing the job titles and industries of the people your content attracts allows you to judge relevance over pure volume.

3. Saves and Sends

Public likes are low-friction interactions. A reader can tap like in half a second without reading past your first sentence. Saves and direct message sends require genuine interest.

Saves: When someone saves your post, they treat it as reference material. High-save content includes checklists, resource lists, step-by-step guides, and data breakdowns.
Sends on LinkedIn: When someone sends your post in a private message, they are sharing it directly with a colleague, client, or team member. A high send count means your post addressed a specific workplace problem or sparked an internal discussion inside a company.

How to Adjust Your Content Strategy Using the Data

Once you review your table, you can sort your content by specific metrics to adjust your production schedule.

Metric Pattern	What It Indicates	Practical Adjustment
High Impressions, Low Out-of-Network	Strong engagement from existing network, but minimal algorithmic feed discovery.	Broaden your opening hook, explain industry acronyms, and address broader sector trends.
High Out-of-Network, Low Followers	Content reached new people, but gave them little reason to follow your ongoing work.	Add a clear bio statement, pin related posts to your profile, and close with what you write about each week.
High Saves, Low Comments	Readers value the post as utility, but do not feel a need to add public commentary.	Continue posting practical templates and guides, but add an open question at the end to invite discussion.
High Sends, Steady Views	Content solves specific, peer-to-peer work problems that people discuss behind closed doors.	Consider turning this topic into an in-depth document carousel or a long-form newsletter edition.

Map Content Types to Specific Goals

Creators often make the mistake of expecting every post to do everything at once. Use the table to evaluate posts based on their intended purpose:

Growth posts: Designed to drive discovery. Evaluate these strictly by out-of-network percentage and followers gained.
Authority posts: Designed to establish your technical or industry expertise. Evaluate these by profile views generated and the job titles of the members who follow you.
Resource posts: Designed to provide practical utility. Evaluate these by saves and direct sends rather than public comments.
Community posts: Designed to spark conversation with peers you already know. Evaluate these by comments and in-network interaction depth.

If you work with B2B sponsors or software brands, the Post Performance Table provides clean attribution figures to include in your partnership reports.

Instead of showing a sponsor an aggregate screenshot of overall monthly views, export the table and filter by the specific sponsored post. You can present the sponsor with verified numbers for:

Unique members reached.
Direct message sends, demonstrating peer recommendations inside companies.
Video watch time in total minutes or hours.
Audience seniority, backed by the job titles of the members who followed you or engaged during that campaign run.

Presenting clean, exported data helps you stand out from creators who only offer estimated views or generic engagement percentages.

Four Mistakes to Avoid When Using the Table

To get the most out of the new desktop table, avoid these common analytical pitfalls:

Judging content solely by impressions: A post with 50,000 impressions that generated zero followers and zero saves is rarely as valuable as a post with 4,000 impressions that gained 25 qualified industry peers and 60 saves. Look at the columns that represent retention and intent.
Ignoring the mobile experience: Remember that while you are analyzing the table on a desktop screen, most of your audience reads on mobile. Keep your text formatting readable with short paragraphs and clean line breaks.
Over-reacting to single-day anomalies: A single post can perform unusually well or poorly based on platform maintenance or publishing timing. Look at your exported CSV over 30-day or 60-day periods to spot genuine trends before overhauling your content pillars.
Failing to review follower profiles: Do not just record the number of new followers. Spend two minutes clicking through the profiles of members who followed you. If they match your target audience, note the angle of that post and plan a follow-up piece expanding on the same topic.