How to Create an Effective LinkedIn Analytics Report

It's reporting day.

You've exported the LinkedIn numbers. There are follower counts, impressions, engagement rates, clicks, demographics, and enough charts to fill a small presentation deck.

Now comes the hard part: turning all that data into a LinkedIn analytics report that actually tells a story.

Which LinkedIn metrics matter? How do you organize them? What should go into an executive summary? And what does a report look like when it's meant for a CMO, a client, or your content team?

This guide walks you through the entire process, from pulling data from your LinkedIn analytics dashboard to building a report that's clear and actionable. You'll learn which LinkedIn metrics to track, how to analyze performance, benchmark competitors, and use AI to speed up reporting.

How to access LinkedIn analytics - Native analytics vs. Third-party tools

Before you can create a LinkedIn analytics report, you need access to the right data.

LinkedIn's native analytics gives you a good overview of your own page's performance. You can access metrics such as:

• Visitor analytics
• Follower analytics and demographic breakdowns
• Post impressions
• Reactions, comments, and shares
• Engagement metrics

The main limitation? Native analytics for LinkedIn only works for pages you manage. It also offers limited historical data, requires manual exports, and doesn't let you group content into themes or content pillars.

When do you require a third-party LinkedIn analytics tool?

A third-party LinkedIn analytics tool becomes useful when you need data beyond your own page.

For connected pages, tools like Socialinsider provide metrics such as reach, impressions, engagement, and audience demographics.

For competitor pages, they can estimate reach and impressions while tracking LinkedIn public engagement metrics, including:

• Reactions
• Comments
• Shares
• Video views
• Engagement rates

They also make reporting easier by storing up to 12 months of historical data, automating exports, and allowing you to benchmark performance against competitors.

If your report focuses only on your own LinkedIn page, native analytics may be enough. If you need competitor benchmarking, campaign reporting, or long-term trend analysis, a third-party tool will give you more flexibility.

What to include in a LinkedIn analytics report?

Your LinkedIn analytics report should be tweaked to your requirements and goals on LinkedIn. But here are some sections that every analytics report generally includes. Let’s look at each of them.

Executive summary

I think of the executive summary as the ‘tell me what happened’ section of my LinkedIn analytics report.

This is important because most stakeholders don't have the time to sift through pages of charts and metrics. They want a quick overview of performance, the major wins and losses, and any actions that should be taken moving forward.

At a minimum, my executive summary includes:

• Total follower count
• Follower growth rate
• Engagement rate by followers
• Key performance highlights
• Major changes from the previous reporting period

I also include why key metrics slowed or increased. This often provides more value than the metric alone.

You should also include 2-3 key insights that summarize the reporting period. 

Instead of doing this manually, I use Socialinsider to generate this section automatically. For example, we can see here through the ‘Key Insights Summary’ that Ahrefs saw an increase in follower count even though the average engagement decreased.

Content performance breakdown

This is one of the most important sections of your report for LinkedIn as it shows how your content strategy is performing. Here are the different elements to include in this breakdown.

• Post-level metrics: You can show metrics for all your posts, such as reactions, comments, shares, video views, and engagement rate. They show the total engagement your content got in a specific period.

• Post type performance: Compare LinkedIn post analytics like engagement across text posts, images, videos, and native documents/carousels. This can reveal format preferences that aren't obvious at first glance. 

For example, here we can see that Ahrefs' image posts generate the highest engagement on LinkedIn, while videos and native documents tend to underperform. 

• Top-performing and bottom-performing posts: Highlight a handful of posts from each category and look for patterns. What topics, formats, or messaging styles are driving results? What should you stop doing?

I use Socialinsider’s sorting feature to find these posts rather than sorting them manually.

• Best posting times: Analyze engagement by day and time to identify when your audience is most active. 

In the example below, Ahrefs sees its highest engagement on Sundays. It's worth reviewing multiple time periods to see if this trend remains consistent.

• Best-performing content pillars: Group content into themes such as thought leadership, product education, customer stories, or industry insights and compare performance across each category.

I get this information via AI-generated pillars in social media.

If I want to create custom pillars, I use the Query Builder feature in Socialinsider to do that. For example, here I created a content pillar named ‘Ahrefs MCP’ to see how those posts are performing.

In the Content pillars, I can now see this pillar added to check its performance.

Campaign performance analysis

If you've run a specific LinkedIn campaign, dedicate a section of your report to its performance.

The goal here is to determine whether the campaign achieved its objectives and which content contributed most to the results.

Include metrics such as:

• Engagement generated: Total reactions, comments, shares, video views, and engagement rate across campaign posts.
• Top-performing campaign posts: Identify which posts drove the highest engagement and why.
• Campaign reach and visibility: How many people saw the campaign content.
• Click-through rate (CTR): How effectively the campaign drove traffic.
• Conversions: Form fills, demo requests, signups, downloads, or any other campaign goal.
• Budget spent: If the campaign included paid promotion, compare spend against results.

If your campaign spans multiple posts, it's helpful to group them together before analyzing performance. 

Use the same Query Builder feature to create a custom content pillar for a campaign and measure its overall engagement, reach, and performance.

This makes it much easier to answer questions such as:

• Which campaign generated the most engagement?
• Which campaign drove the highest conversion rate?
• Was the campaign worth the investment?

Competitor benchmarking

“But how exactly is our LinkedIn performance as compared to Brand X?”

This is a common question your CMO would want to know. That's where competitor benchmarking comes in.

Instead of looking at your performance in isolation, compare it against the brands you're competing with for attention on LinkedIn.

Instead of running this LinkedIn analysis manually, I use competitor analysis tools like Socialinsider that give me a quick analysis. 

I can even get a side-by-side comparison of key metrics.

In the LinkedIn analytics report, I include metrics such as:

• Follower growth: How quickly are competitors growing their audiences compared to you?
• Engagement rate: Are competitors generating more engagement from their audience than you are?
• Posting frequency: How often are competitors publishing content?
• Content format mix: Are they relying on images, videos, carousels, or text posts?
• Top-performing content pillars: Which topics and themes generate the most engagement for them?

This analysis helps answer questions that your own metrics can't. For example, low engagement might seem concerning until you discover that engagement is down across your entire competitive set. Or you may find that competitors are seeing stronger results simply because they're investing more heavily in a particular content format or topic.

Lead generation and conversion analysis

This section connects your LinkedIn activity to actual business results.

You can include metrics such as:

• UTM traffic: Website visits generated from LinkedIn content and campaigns.
• Form fills: Leads captured through landing pages or lead generation forms.
• Demo requests: Prospects who expressed interest in your product or service.
• Conversion rate: The percentage of visitors who completed a desired action.
• Cost per acquisition (CPA): How much it costs to generate a lead or customer.
• Assisted conversions: Conversions where LinkedIn played a role in the customer journey.
• CRM attribution: Revenue, opportunities, or customers attributed to LinkedIn activity.

Remember, not every LinkedIn report needs this section. But if LinkedIn is part of your lead generation strategy, these metrics help demonstrate the platform's impact beyond likes, comments, and shares.

Goals vs results

End your report by comparing performance against the goals you set at the start of the reporting period.

This section helps stakeholders quickly understand whether your LinkedIn strategy is moving in the right direction and what should happen next.

In this section, I include:

• Target vs. actual results: Compare goals for follower growth, engagement, reach, traffic, or conversions against actual performance.
• Wins: Highlight areas where you exceeded expectations.
• Misses: Identify goals that weren't achieved.
• Reasons behind the results: Explain the factors that contributed to strong or weak performance.
• What's working: Content formats, topics, campaigns, or tactics that consistently deliver results.
• What's not working: Areas where performance is declining or falling below expectations.
• What to test next: Experiments, content ideas, or strategic adjustments for the next reporting period.

What a good LinkedIn analytics report actually looks like for different audiences?

Not everyone consumes data the same way.

The mistake many marketers make is sending the same LinkedIn report to everyone. Your CMO, your client, and your content team all have different questions they need answered.

Here’s how to present your LinkedIn analytics report in different formats for your audience.

H2: How to use AI to create a LinkedIn analytics report

With AI tools and features, you no longer need to spend days crafting the perfect report. You can automate a lot of work and focus just on strategy and in-depth analysis.

Here’s how we use AI at Socialinsider to create social media reports.

Use AI for data gathering

One of the most time-consuming parts of creating a LinkedIn analytics report is collecting and organizing the data.

Traditionally, this means exporting spreadsheets, calculating engagement rates, sorting posts into content pillars, and manually compiling metrics from different sources before you can even start analyzing performance.

AI-powered LinkedIn analytics tools can automate much of this process.

For example, instead of manually calculating engagement rates or reviewing dozens of posts to identify content themes, tools like Socialinsider automatically organize your LinkedIn data into report-ready insights.

Moreover, Socialinsider also offers automated summaries so your team can quickly get an idea of what’s happened on your and competitors’ pages in the last month.

Ask AI to analyze the data gathered

Often, when you're short on time, you ask yourself, “I wish there were a way to get an analysis of this data quickly.”

Turns out, you can absolutely do that now. 

Instead of manually analyzing metrics, you can ask questions to the Socialinsider AI assistant in plain language and receive structured, data-backed answers.

For example:

• What were my top-performing content pillars this quarter?
• How does my engagement rate compare to competitors this month?
• Which content formats improved the most compared to last quarter?
• What changed between this reporting period and the previous one?

The best part? The data is already on the platform, so you don’t even need to manually extract data and then get answers.

This is particularly useful when you're:

• Auditing LinkedIn performance
• Comparing reporting periods
• Identifying trends and anomalies
• Preparing insights before a client or stakeholder meeting
• Looking for opportunities to improve content strategy

Connect your analytics data to the AI tools you use

Do you want to show overall marketing performance by connecting different tools together? You can now use MCPs to pull data from different tools in your preferred AI tool, enabling it to perform a comprehensive analysis.

For example, Socialinsider's MCP lets you connect Socialinsider data to AI assistants such as ChatGPT and Claude. This gives the AI access to your actual LinkedIn performance data, competitor LinkedIn benchmarks, content analysis, and historical trends.

This unlocks use cases such as:

• Summarizing competitor content strategies
• Drafting executive summaries for stakeholders
• Generating client-ready performance reports
• Combining LinkedIn page analytics with conversion or CRM data
• Identifying trends and opportunities across multiple channels
• Creating recommendations without manually formatting data

For example, I used the following prompt:

"Write a one-page campaign recap: goals, performance highlights, top content, lessons learned, and next steps for the Ahrefs LinkedIn profile in my Base project in Socialinsider."

And here’s the result:

Best tools for LinkedIn analytics reporting

The right reporting tool depends on the type of report you're building. Some tools are great for accessing raw LinkedIn data, while others are better for LinkedIn competitor analysis, automation, and visualization. 

LinkedIn native analytics

LinkedIn's native analytics is the simplest place to start.

If you manage a LinkedIn company page, you can access metrics such as follower growth, audience demographics, visitor analytics, post impressions, and engagement directly within the platform. For many marketers, this is enough to understand how their page is performing and create a basic monthly report.

The biggest advantage of native analytics is accessibility. The data comes directly from LinkedIn, requires no setup, and gives you a reliable view of your own page's performance.

Its limitations become apparent when reporting needs grow more complex. Analytics are restricted to pages you manage, competitor benchmarking is limited, historical reporting isn't particularly flexible, and there's no easy way to group content into campaigns or content pillars.

Socialinsider 

Socialinsider is built for marketers and agencies that need more than a snapshot of their own LinkedIn performance.

In addition to tracking your own page, it allows you to benchmark against competitors, analyze content strategy, group posts into custom content pillars, and automate recurring reports. 

Instead of manually calculating engagement rates or reviewing posts one by one, you can quickly identify trends, compare performance across brands, and surface AI-driven insights that are ready to present to stakeholders.

Features such as Query Builder, competitor benchmarking, AI-powered analysis, executive summaries, and report exports help transform raw data into actionable insights much faster than a manual workflow. 

Looker Studio

Looker Studio serves a different purpose altogether.

Rather than focusing specifically on social media analytics, it acts as a reporting layer that combines data from multiple sources into a single dashboard. LinkedIn metrics can sit alongside website traffic, CRM data, advertising performance, and conversion metrics, creating a broader view of marketing performance.

This makes it particularly valuable for executive reporting. Instead of showing LinkedIn performance in isolation, you can demonstrate how LinkedIn contributes to lead generation, revenue, and other business outcomes.

The trade-off is that Looker Studio generally requires more setup and maintenance than a dedicated LinkedIn analytics tool. It's incredibly flexible, but you'll often need connectors, dashboard configuration, and ongoing management to get the most value from it.

Best practices for Linkedin analytics reporting

• Lead with the ‘so what’. Start your report with what changed, why it matters, and what you're doing next. For example, "Engagement increased by 22% after shifting to educational content" is far more useful than simply reporting an engagement rate of 4.8%.
• Focus on trends instead of weekly fluctuations. LinkedIn moves slower than platforms like TikTok or Instagram. A dip in engagement over a few days is often just noise. Monthly trends are usually more meaningful, while quarterly comparisons are better for evaluating the impact of larger strategic changes.
• Make your reports visual. Charts, screenshots, and visual comparisons help stakeholders understand performance much faster than tables full of numbers. 
• Provide context for every major metric. A number on its own rarely tells the full story. If engagement increased, explain why. If follower growth slowed down, identify potential causes. 
• End every report with recommendations. The best reports don't stop at reporting results. Include a short section on what's working, what's not, and what should be tested next so stakeholders leave with clear action items.

Build a LinkedIn analytics report that actually drives decisions

The best LinkedIn analytics reports don't overwhelm readers with charts, screenshots, and dozens of KPIs. They answer a handful of important questions: What's changing? Why is it changing? How do we compare to competitors? And what should we do next?

Whether you're reporting to leadership, clients, or your content team, the goal remains the same: turn LinkedIn data into clear actions. 

With the right metrics, the right level of context, and the help of AI-powered reporting tools, you can spend less time compiling numbers and more time uncovering opportunities. One such tool that helps automate most stuff for you is Socialinsider. Take it for a free spin for 14 days.