How to Turn Your LinkedIn Creator Analytics Into a Content Strategy That Actually Works (2026 Edition)

Last Updated: January 15, 2026
Author: Luke Costley-White, DOJO AI
Reading Time: 28 minutes
Word Count: ~7,500 words

Table of Contents

1. What is LinkedIn Creator Analytics?

2. How to Download LinkedIn Creator Analytics

3. What Data LinkedIn Creator Analytics Provides

4. The 6 Core Analyses

5. Building Your Content Strategy

6. Common Mistakes to Avoid

7. FAQ

What is LinkedIn Creator Analytics?

LinkedIn Creator Analytics is LinkedIn's free data export tool that provides 365 days of performance data for personal profiles with Creator Mode enabled. It includes post-level metrics (impressions, engagements), audience demographics (job titles, industries, seniority), and follower growth trends.

Key Definition

LinkedIn Creator Analytics = A downloadable Excel file containing 5 data sheets (DISCOVERY, ENGAGEMENT, TOP POSTS, FOLLOWERS, DEMOGRAPHICS) covering the past 365 days of your LinkedIn content performance and audience composition. Available to any LinkedIn member with Creator Mode enabled, regardless of follower count.

Why It Matters for Personal Brands

LinkedIn Creator Analytics provides the only complete historical view of:

• Which specific posts drove engagement vs. reach

• Who your actual audience is (vs. who you think it is)

• When your audience engages most

• Which topics consistently perform

• How your follower growth correlates with content

Source: LinkedIn Creator Analytics is distinct from LinkedIn's general account analytics and the full data download (which includes connection data, messages, and profile views but lacks the structured content performance analysis).

How to Download LinkedIn Creator Analytics

Prerequisites

• LinkedIn account with Creator Mode enabled

• Desktop computer (mobile export not available as of January 2026)

• No minimum follower count required

Step-by-Step Download Process

1. Navigate to your LinkedIn profile (desktop browser only)

2. Click "Analytics" located under your profile picture

3. Select "Creator analytics" from the dropdown menu

4. Click "Export" button in the top right corner

5. Choose date range: Select 365 days for comprehensive analysis (default: last 365 days)

6. Download Excel file: File downloads automatically as .xlsx format

Download frequency recommendation: Quarterly (every 90 days) to track trends over time.

File size: Typically 500KB-2MB depending on posting volume.

What Data LinkedIn Creator Analytics Provides

The 5 Data Sheets Explained

LinkedIn Creator Analytics exports as an Excel workbook containing 5 separate sheets:

1. DISCOVERY Sheet

Metrics included:

• Total impressions (last 365 days)

• Unique members reached

• Aggregate reach data

Use case: High-level performance overview

2. ENGAGEMENT Sheet

Metrics included:

• Daily impressions (by date)

• Daily engagements (by date)

• 365-day trend data

Use case: Identify posting patterns, seasonal trends, engagement spikes

3. TOP POSTS Sheet

Metrics included:

• Top 50 posts ranked by engagement

• Top 50 posts ranked by impressions

• Post URLs

• Engagement counts

• Impression counts

• Publication dates

Use case: Content performance analysis, topic pattern recognition

Limitation: Post text is NOT included—only URLs. You must manually visit URLs to see content.

4. FOLLOWERS Sheet

Metrics included:

• Total follower count

• Daily new followers (by date)

• 365-day growth trend

Use case: Correlate follower spikes with specific posts

5. DEMOGRAPHICS Sheet

Metrics included:

• Job titles: Top roles following you (with percentages)

• Locations: Geographic distribution of followers

• Industries: Industry breakdown of audience

• Seniority levels: Career level distribution (Entry, Mid, Senior, C-Suite, etc.)

• Company sizes: Follower distribution by company size (0-10, 11-50, 51-200, etc.)

• Companies: Top companies following you (partial list only)

Use case: Verify audience matches Ideal Customer Profile (ICP)

What LinkedIn Creator Analytics Does NOT Include

❌ Missing data:

• Individual post text/content (only URLs provided)

• Detailed engagement breakdown (comments vs. reactions vs. shares)

• Profile views

• Click-through rates (CTR)

• Direct message (DM) activity

• Post-level follower attribution (which post drove which followers)

• Performance data beyond top 50 posts

• Video view duration

• Carousel engagement by slide

Why it matters: You'll need to supplement Creator Analytics with manual tracking for business outcome attribution (DMs → meetings → deals). You can get those insights from your LinkedIn Data Archive.

If you want this to be as fast and painless as possible, you can analyze the whole export with DOJO here.

Comparison: LinkedIn Creator Analytics vs. LinkedIn Data Download

Recommendation: Use both. Creator Analytics for content optimization, Data Download for relationship management and networking insights.

The 6 Core Analyses That Drive Better Content

Analysis 1: Content Performance Analysis

Objective: Identify which posts drove engagement vs. reach, then reverse-engineer why they worked.

What to Analyze

• TOP POSTS sheet (both engagement and impression rankings)

• Compare high-engagement vs. high-impression posts

• Calculate engagement rate for each top post

Engagement Rate Formula

The 4 Post Performance Categories

Step-by-Step Process

1. Export your top 20 posts (by engagement from TOP POSTS sheet)

2. Visit each post URL and document:

   • Topic/theme

   • Format (text post, carousel, poll, video, article, PDF)

   • Hook/opening line (first 1-2 sentences)

   • Content elements (personal story, data, contrarian take, tactical how-to)

   • Tone (educational, provocative, vulnerable, analytical, humorous)

   • Post length (short <500 chars, medium 500-1200, long 1200+)

3. Calculate engagement rate for each post using formula above

4. Identify patterns: Which combinations of topic + format + tone appear most in top performers?

Key Insights to Extract

• Format patterns: Do text posts outperform carousels? Do videos underperform?

• Topic patterns: Do strategic posts beat tactical ones? Do personal stories drive more engagement than data analysis?

• Hook patterns: Do question-based hooks outperform statement-based ones?

• Timing patterns: Do certain formats work better on specific days?

Real Example (Author's Data):
Top post: 462 engagements, 30,000 impressions (1.54% engagement rate)

• Topic: Strategic competitive analysis

• Format: Long-form text post

• Elements: Specific data + personal experience + competitive insight

• Pattern identified: Data + personal credibility + strategic depth = highest engagement

Analysis 2: Topic Pattern Recognition

Objective: Identify the 3-5 core topics that consistently drive results, which become your content pillars.

What to Analyze

• Your top 20-30 posts (by engagement)

• Group posts by topic category

• Calculate frequency by category

• Cross-reference with follower growth spikes

Step-by-Step Process

1. Create topic categories relevant to your expertise (5-8 categories maximum)

   Example categories for a B2B marketer:

   • Marketing strategy & planning

   • Personal brand building

   • Founder/CMO lessons

   • Industry analysis & trends

   • Product/tool reviews

   • Attribution & measurement

   • Team management

   • Career development

2. Tag each top post with 1-2 primary categories

3. Count category frequency

4. Identify top 3-5 categories (these are your content pillars)

5. Validate against business goals: Do these topics align with what you want to be known for?

Your Content Pillars Should Be:

✅ Proven: They appear frequently in your top-performing posts
✅ Aligned: They connect to your business goals and positioning
✅ Sustainable: You can create content on these topics for years without running out of material
✅ Differentiated: You have unique insights or experience in these areas

Red Flags

🚩 You're posting topics that never rank in top posts = Wasting effort on content nobody wants
🚩 Your top topics don't align with business goals = Building audience for the wrong expertise
🚩 You have no clear topic focus = Audience doesn't know what you're about

The Strategic Shift:
Stop trying to cover everything. Commit to 3-5 content pillars and go deep. You'll become known for specific expertise instead of being generically "interested in marketing."

Analysis 3: Timing Analysis

Objective: Identify when your specific audience engages most, then optimize posting schedule.

What to Analyze

• ENGAGEMENT sheet (daily impressions and engagements)

• TOP POSTS sheet (publication dates of high-performers)

• Day-of-week patterns

• Seasonal trends

Step-by-Step Process

1. List publication dates of your top 20 posts

2. Calculate day-of-week distribution

3. Identify your highest-engagement days

4. Look for seasonal patterns in ENGAGEMENT sheet (summer slowdowns, end-of-quarter spikes, holiday dips)

5. Cross-reference with your posting schedule: Are you posting consistently on your best days?

Common B2B Audience Patterns (2026 Data)

Important: These are averages. YOUR data may differ. Trust your own Creator Analytics over generic advice.

Posting Frequency Recommendations by Follower Count

Source: Analysis of 500+ B2B personal brands on LinkedIn (DOJO AI internal data, 2025).

Analysis 4: Follower Growth Analysis

Objective: Understand which content attracts new followers vs. which engages existing audience.

What to Analyze

• FOLLOWERS sheet (daily new follower counts)

• TOP POSTS sheet (publication dates)

• Correlation between posting dates and follower spikes

Step-by-Step Process

1. Identify follower growth spikes (days with 10+ new followers for accounts under 5K; 20+ for accounts over 5K)

2. Note what you posted on spike dates or 1-2 days prior (LinkedIn algorithm delay)

3. Compare follower-driving posts to engagement-driving posts

4. Identify differences in:

   • Topics (broader vs. niche)

   • Formats (more visual vs. text-heavy)

   • Accessibility (tactical vs. strategic)

   • Shareability (quotable vs. deep analysis)

The Two Types of Content You Need

The Strategic Balance

Recommended content mix:

• 40% Follower Drivers (attract new audience)

• 40% Engagement Drivers (deepen existing relationships)

• 20% Experimental (test new topics/formats)

Posting pattern:

• Week 1: Follower Driver → Engagement Driver → Follower Driver

• Week 2: Engagement Driver → Follower Driver → Engagement Driver

• Alternate to maintain both growth and depth

Red Flag: Follower Growth Without Engagement

Problem: You're gaining followers (100+ per month) but engagement rate is declining (<1%).

Diagnosis: You're attracting the wrong audience. Your content promises don't match audience expectations.

Fix:

1. Review demographics of new followers (DEMOGRAPHICS sheet)

2. Identify if they match your ICP

3. If not, shift content to attract better-fit audience (even if growth slows)

4. Quality > quantity for business outcomes

Analysis 5: Audience Composition Analysis

Objective: Verify your audience matches your Ideal Customer Profile (ICP) and business goals.

What to Analyze

• DEMOGRAPHICS sheet (all sections)

• Compare actual audience to your ICP

• Identify gaps and mismatches

ICP Alignment Checklist

Use this framework to assess audience fit:

Common Audience-ICP Mismatches and Fixes

Mismatch #1: Job Title Gap

• Problem: Want to sell to CMOs, but 80% of audience is Marketing Managers/Coordinators

• Diagnosis: Content is too tactical, not strategic enough

• Fix: Shift to strategic frameworks, budget planning, team management, executive communication

Mismatch #2: Industry Gap

• Problem: Target B2B SaaS, but most followers are agencies or consultants

• Diagnosis: Content is too generic or service-provider focused

• Fix: Use specific SaaS case studies, product-led growth topics, MRR/ARR metrics

Mismatch #3: Seniority Gap

• Problem: Want senior buyers, attracting junior practitioners

• Diagnosis: Content depth doesn't match senior experience level

• Fix: Reduce "101" content, add strategic depth, assume higher baseline knowledge

Mismatch #4: Geography Gap

• Problem: Want global reach, but 75% of followers in one city

• Diagnosis: Content has local references, local networking focus

• Fix: Use international examples, avoid hyper-local content, post at globally-friendly times

Mismatch #5: Company Size Gap

• Problem: Target mid-market (100-500 employees), attracting startups (<50)

• Diagnosis: Solutions are startup-focused or budget is discussed as too accessible

• Fix: Address scaling challenges, team structure, established company problems

When Your Audience DOES Match Your ICP

Validation signals:
✅ Top job titles are decision-makers in your target market
✅ Top industries match your sales focus
✅ Seniority levels include buyers (Director+)
✅ Company sizes match your product's sweet spot
✅ Locations align with your go-to-market strategy

Action: Double down on what's working. Document your successful content patterns and systematize them.

Analysis 6: Engagement Rate Benchmarking

Objective: Understand if your engagement rates are strong, average, or weak compared to benchmarks.

Engagement Rate Formula (Reminder)

Example:

• Post with 5,000 impressions and 150 engagements = 3.0% engagement rate

• Post with 20,000 impressions and 200 engagements = 1.0% engagement rate

Result: The first post (3.0%) is higher quality despite lower reach.

LinkedIn Engagement Rate Benchmarks (2026)

Based on analysis of 1,000+ B2B personal brands, January 2026:

Source: DOJO AI analysis of B2B personal brands with 1,000-50,000 followers, Q4 2025.

Engagement Rate by Follower Count

Benchmarks vary by follower count (larger accounts typically see lower engagement rates):

Why engagement rates decrease with follower growth:

• Larger, more diverse audience = less consistent resonance

• Algorithm shows content to broader audience (lower intent)

• Passive followers who don't engage regularly

How to Calculate Your Engagement Rate

Individual Post Level:

1. Open TOP POSTS sheet

2. For each post: (Engagements ÷ Impressions) × 100

3. Identify your highest and lowest engagement rate posts

4. Average your top 10 posts' engagement rates = Your "best" benchmark

5. Average ALL your posts' engagement rates = Your overall benchmark

Account Level (Annual):

1. Sum total engagements from ENGAGEMENT sheet (365 days)

2. Sum total impressions from ENGAGEMENT sheet (365 days)

3. Calculate: (Total Engagements ÷ Total Impressions) × 100

4. This is your annual average engagement rate

Why Engagement Rate Matters More Than Reach

Key principle: High engagement rate signals quality to LinkedIn's algorithm, which leads to expanded reach.

The compounding effect:

1. Post gets early engagement (first 1-2 hours)

2. High engagement rate signals "valuable content" to algorithm

3. LinkedIn shows post to broader audience

4. Reach expands, engagement continues

5. Post enters "viral" cycle

The death spiral:

1. Post gets low early engagement

2. Low engagement rate signals "not valuable"

3. LinkedIn stops showing post to broader audience

4. Reach stalls, post dies

Strategic implication: Optimize for engagement rate first, reach will follow. Writing for your core audience (who will engage) is more valuable than writing for broad reach (who won't engage).

Turning Insights Into an Actionable Content Strategy

Now that you've completed the 6 core analyses, here's how to build a data-driven content strategy.

Step 1: Define Your Content Pillars (3-5 Topics)

Based on your Topic Pattern Recognition analysis (Analysis #2), commit to 3-5 core themes.

Content Pillar Criteria Checklist

Your content pillars should be:

✅ Proven by data: They appear frequently in your top-performing posts
✅ Aligned with business goals: They support what you want to be known for
✅ Sustainable long-term: You can create content on these topics for years
✅ Differentiated: You have unique insights, experience, or perspective
✅ Audience-validated: Your ICP cares about these topics

Example Content Pillar Frameworks

B2B Marketer (Growth-stage SaaS):

1. Marketing attribution & measurement (unique expertise)

2. AI in marketing operations (emerging trend, you have hands-on experience)

3. Competitive strategy & positioning (case studies from your work)

4. Personal brand for B2B leaders (you're building one, teaching what you learn)

5. CMO/Founder marketing lessons (lived experience)

SaaS Founder:

1. Product-led growth tactics

2. Founder mental health & sustainability

3. B2B sales & closing enterprise deals

4. Fundraising & investor relations

5. Building remote teams

Marketing Agency Owner:

1. Client services & agency operations

2. Performance marketing tactics

3. Agency positioning & differentiation

4. Team building & hiring

5. Case studies & client results

Content Pillar Distribution

Once you've defined pillars, distribute content evenly:

Example for 3 posts/week (12 posts/month):

• Pillar 1: 3 posts (25%)

• Pillar 2: 3 posts (25%)

• Pillar 3: 2 posts (17%)

• Pillar 4: 2 posts (17%)

• Pillar 5: 2 posts (17%)

Rule: Don't post the same pillar twice in one week unless responding to a timely event.

Step 2: Identify Your Winning Formats

From your Content Performance Analysis (Analysis #1), you should have identified 2-3 formats that consistently work.

Common LinkedIn Content Formats (2026)

Note: These are averages. YOUR data may show different patterns.

Format Selection Framework

Rules for choosing formats:

1. Start with what YOUR data says works (not what works for others)

2. If a format consistently underperforms (<1% engagement), stop using it

3. Double down on your top 2 formats (80% of content)

4. Test new formats sparingly (20% of content)

5. Match format to content type:

   • Strategic insights → Long-form text

   • Tactical frameworks → Carousels

   • Personal stories → Video or long text

   • Quick takes → Short text

   • Data/trends → Carousels with charts

   • Debates → Polls

Example Format Strategy:

• 50% Long-form text posts (proven winner)

• 30% Carousels (consistent performer)

• 20% Experiments (polls, video, short text)

Step 3: Create a Content Calendar Based on Data

Use insights from Timing Analysis (Analysis #3) and Follower Growth Analysis (Analysis #4) to structure your calendar.

Weekly Content Structure Template

Adjustments based on YOUR data:

• If Tuesday is your best day, post your highest-quality content then

• If weekends work for your audience, shift Friday content to Saturday

• If carousels outperform text, increase carousel frequency

Posting Frequency Recommendations

Content Calendar Best Practices

✅ Plan 2-4 weeks ahead (but leave 20% flexible for timely content)
✅ Batch content creation (write 3-5 posts in one session)
✅ Rotate through pillars (don't repeat topics within one week)
✅ Alternate reach vs. engagement content (see Analysis #4)
✅ Track performance weekly (adjust based on results)

❌ Don't plan too far ahead (content gets stale, reduces authenticity)
❌ Don't overschedule (leaves no room for timely commentary)
❌ Don't post just to hit frequency targets (quality > quantity always)

Step 4: Set Up a Performance Tracking System

Beyond Creator Analytics, track these metrics to connect content to business outcomes.

Weekly Tracking (Every Monday)

Track in a simple spreadsheet:

Time investment: 15-20 minutes weekly

Monthly Review (First week of each month)

Deeper analysis:

1. Best-performing post of the month:

   • What made it work?

   • Can I replicate this pattern?

   • What pillar/format was it?

2. Worst-performing post of the month:

   • Why did it flop?

   • Wrong topic, wrong format, wrong timing?

   • Should I avoid this in the future?

3. Engagement rate trend:

   • Improving or declining month-over-month?

   • If declining: audience mismatch? content fatigue?

   • If improving: what changed?

4. Follower growth rate:

   • Accelerating or slowing?

   • Quality of new followers (check DEMOGRAPHICS)

5. Audience composition shifts:

   • Are demographics moving toward or away from ICP?

   • Do I need to adjust content strategy?

Time investment: 1 hour monthly

Quarterly Deep Dive (Every 90 days)

1. Download fresh Creator Analytics (365 days)

2. Re-run the 6 core analyses (abbreviated version)

3. Compare to previous quarter:

   • What's improving?

   • What's declining?

   • What patterns have shifted?

4. Adjust content strategy:

   • Update content pillars if needed

   • Shift format mix based on recent data

   • Refine posting schedule

   • Update ICP alignment

Time investment: 2-3 hours quarterly

Step 5: Experiment Systematically

Once you have a baseline, run structured experiments to improve performance.

The Scientific Method for Content Experiments

Rules for valid experiments:

1. Change only ONE variable at a time (topic, format, timing, hook style, length)

2. Run for minimum 3-4 posts (one post isn't statistically significant)

3. Compare to baseline (your average performance)

4. Document results (write down what you learn)

5. Decide: adopt, adjust, or abandon (based on data)

Example Experiments to Run

Experiment 1: New Topic Angle

• Hypothesis: "My audience will engage with [new subtopic] within [existing pillar]"

• Test: Post 3-4 pieces of content on new subtopic

• Success metric: Engagement rate ≥ your average

• Timeline: 2-3 weeks

Experiment 2: New Format

• Hypothesis: "Video will drive higher engagement than text posts for [specific topic]"

• Test: Create 3-4 videos on proven topics (where you have text post benchmarks)

• Success metric: Video engagement rate ≥ text engagement rate for same topics

• Timeline: 2-3 weeks

Experiment 3: New Posting Time

• Hypothesis: "Posting at [time/day] will increase reach and engagement"

• Test: Post 4-5 pieces at new time, compare to usual time

• Success metric: Impressions and engagement rate ≥ average

• Timeline: 2-3 weeks

Experiment 4: New Hook Style

• Hypothesis: "Question-based hooks drive more engagement than statement-based hooks"

• Test: 4 posts with question hooks vs. 4 posts with statement hooks (same topics)

• Success metric: Question-based engagement rate > statement-based

• Timeline: 2-3 weeks

Experiment Tracking Template

Common Mistakes (And How to Avoid Them)

Mistake #1: Chasing Reach at the Expense of Engagement

The Problem:
You optimize for impressions (vanity metric) but your engagement rate declines (<1%).

Why It Fails:
LinkedIn's algorithm prioritizes engagement rate, not raw reach. Low engagement signals "content isn't valuable" → algorithm reduces future reach → you enter a death spiral.

The Fix:
Optimize for engagement rate first (target: 2-3%+). Focus on writing for your core audience who will engage. Reach will follow if engagement is strong.

How to Implement:

• Calculate engagement rate for every post

• Aim for consistent 2-3%+ (not viral spikes)

• Prioritize depth over breadth in topic choice

• Write for your ICP, not for everyone

Mistake #2: Copying Other People's Winning Formats

The Problem:
You see someone succeed with daily carousels/videos/polls, so you copy the format—but yours flop.

Why It Fails:
Their audience ≠ your audience. Their voice ≠ your voice. Their content pillars ≠ your pillars. What works for them may not work for you.

The Fix:
Use YOUR Creator Analytics data. If carousels consistently underperform for you (<1% engagement), stop making them. Do more of what YOUR data says works.

How to Implement:

• Run Analysis #1 (Content Performance) on YOUR posts

• Identify YOUR top 2-3 formats

• Double down on what works for you specifically

• Ignore generic advice that contradicts your data

Mistake #3: Posting About Topics Your Audience Doesn't Care About

The Problem:
You want to be known for Topic X, but your audience only engages with Topic Y.

Why It Fails:
Positioning-audience mismatch. You're creating content for the expert you want to be, not the expert your audience needs you to be.

The Fix:
Either (1) reposition how you talk about Topic X to make it relevant to your audience, or (2) accept that your content pillars should include Topic Y.

How to Implement:

• Run Analysis #2 (Topic Pattern Recognition)

• Identify which topics actually drive engagement

• If your desired topics don't appear in top posts, test new angles or pivot

• Align content pillars with what your audience wants + what you want to be known for

Mistake #4: Ignoring Audience Composition

The Problem:
You're building a large following (5,000+ followers), but none of them are potential customers, partners, or hires.

Why It Fails:
Vanity metrics (follower count) don't translate to business outcomes (deals, partnerships, opportunities). You're building the wrong audience.

The Fix:
Run Analysis #5 (Audience Composition) regularly. If your audience doesn't match your ICP, adjust content to attract the right people—even if growth slows.

How to Implement:

• Quarterly: Check DEMOGRAPHICS sheet

• Compare to your ICP

• If mismatch: shift content depth, topics, examples

• Track: Are new followers getting closer to ICP?

Mistake #5: Not Tracking Business Outcomes

The Problem:
You obsess over likes and comments (vanity metrics) but don't track DMs, meetings booked, deals closed, job offers (business outcomes).

Why It Fails:
Engagement is a leading indicator, but business outcomes are the actual goal. You can't prove ROI of your LinkedIn presence without tracking outcomes.

The Fix:
Manually track qualitative outcomes:

• Inbound DMs per week (and source if they mention a post)

• DMs → meetings conversion rate

• Meetings → opportunities conversion rate

• Which posts drove the highest-quality outcomes

How to Implement:
Create a simple tracking spreadsheet:

Pattern to track:

• Which content pillars drive most inbound?

• Which formats lead to highest-quality conversations?

• Lag time between post → DM (typically 24-72 hours)

Advanced: Connecting LinkedIn Performance to Business Outcomes

The Attribution Gap Problem

The uncomfortable truth:
LinkedIn Creator Analytics shows content performance (impressions, engagements) but NOT business outcomes (DMs, meetings, deals, revenue).

The gap:
Content performance → ??? → business outcomes

Most personal brands can't connect these dots, which means they can't prove ROI.

Manual Business Outcome Tracking System

Since LinkedIn doesn't provide this data, you must track it manually.

Step 1: Log All Inbound DMs

Create a simple spreadsheet:

Step 2: Track Conversion Funnel

Step 3: Attribute to Content

When someone DMs you, ask (casually):

• "What made you reach out?"

• "Have you been following my content? Any post in particular stand out?"

Document if they mention:

• Specific post (record URL)

• General topic/pillar

• Format that resonated

• Timeframe (how long they've been following)

Step 4: Identify High-Value Content

Over time, you'll identify:

• Topics that drive inbound: Which content pillars generate most qualified DMs?

• Formats that drive conversations: Do long-form posts drive more DMs than carousels?

• Quality vs. quantity: Does a post with 50 engagements drive better outcomes than a post with 200 engagements?

Real Example: Quality Over Vanity Metrics

Post A (Viral):

• 15,000 impressions

• 300 engagements (2% engagement rate)

• 25 new followers

• 0 qualified DMs

Post B (Niche):

• 2,000 impressions

• 80 engagements (4% engagement rate)

• 3 new followers

• 5 qualified DMs → 2 meetings → 1 closed deal

Result: Post B is more valuable for business outcomes despite lower vanity metrics.

Strategic implication: Once you identify which content drives business outcomes, prioritize that content—even if it doesn't get the most likes.

The DOJO AI Advantage: Automating This Analysis

Everything in this guide is achievable with manual analysis of your Creator Analytics export and a spreadsheet.

The problem: It's time-consuming (3-5 hours per month). Most people don't do it consistently.

How DOJO AI Automates LinkedIn Analysis

DOJO AI's content intelligence system automatically:

1. Pulls your personal LinkedIn performance data

2. Runs the 6 core analyses continuously (no manual work)

3. Identifies your top-performing topics and formats (AI pattern recognition)

4. Tracks engagement trends over time (automated dashboards)

5. Compares your performance to benchmarks

6. Suggests content ideas based on what's working for you

7. Connects LinkedIn performance to business outcomes

The result:
You spend less time analyzing data and more time creating content that drives business outcomes.

Additional capabilities:

• AI-powered content voice analysis (ensure brand consistency)

• Content pillar recommendations (based on your expertise + audience response)

• Optimal posting schedule (personalized to your audience's behavior)

• Competitor benchmarking (how do you compare to others in your space?)

Learn more about DOJO AI →

Frequently Asked Questions (FAQ)

Q1: How often should I download my LinkedIn Creator Analytics?

Answer: Download quarterly (every 90 days) to track trends over time. Each download gives you a rolling 365-day window, so quarterly downloads let you compare year-over-year and spot seasonal patterns.

Recommended schedule:

• Q1: Early January

• Q2: Early April

• Q3: Early July

• Q4: Early October

Q2: What's the difference between LinkedIn Creator Analytics and LinkedIn Data Download?

Answer: They're two separate exports with different data:

Creator Analytics:

• Content performance metrics (impressions, engagements)

• Top 50 posts

• Audience demographics

• Follower growth trends

• Best for: Content strategy optimization

Data Download:

• Connection data

• Message history

• Profile views

• Your posts (text, but not performance)

• Best for: Personal data archive and relationship management

Recommendation: Use both. Creator Analytics for content strategy, Data Download for networking insights.

Q3: What's a good engagement rate on LinkedIn in 2026?

Answer: Depends on your follower count, but general benchmarks:

• Under 1,000 followers: 2-4% is good

• 1,000-5,000 followers: 1.5-3% is good

• 5,000-10,000 followers: 1-2.5% is good

• 10,000-50,000 followers: 0.8-2% is good

• 50,000+ followers: 0.5-1.5% is good

Context matters: A 1.5% engagement rate from 100% ICP-matched audience is better than 3% from a mismatched audience.

Q4: How many posts do I need before this analysis is valuable?

Answer: Minimum 30-50 posts over 3-6 months. Below that, patterns aren't statistically significant.

If you're just starting:

• Post consistently (3x/week) for 2-3 months

• Then download Creator Analytics

• Run the 6 core analyses

• Use insights to optimize going forward

Q5: Should I optimize for engagement or impressions?

Answer: Engagement rate, not raw impressions.

Why: LinkedIn's algorithm rewards engagement. High engagement signals valuable content → algorithm expands reach → impressions grow organically.

The compounding effect:
High engagement → More reach → More engagement → Even more reach (virtuous cycle)

Low engagement → Less reach → Low engagement → Even less reach (death spiral)

Strategy: Write for your core audience who will engage. Reach will follow.

Q6: How do I know if I'm reaching the right audience?

Answer: Run Analysis #5 (Audience Composition). Compare your DEMOGRAPHICS data to your Ideal Customer Profile (ICP).

Red flags:

• Job titles don't match buyers/decision-makers

• Industries don't overlap with your target market

• Seniority skews junior when you need senior

• Company sizes don't match your product's sweet spot

If mismatched: Adjust content depth, topics, and examples to attract your ICP (even if growth slows temporarily).

Q7: What if my best-performing topics don't align with my business goals?

Answer: You have three options:

1. Reposition the topic: Find the angle that connects audience interest to your business goals

   • Example: Audience engages with "career advice" but you sell marketing software → Angle = "how to advance your marketing career by mastering [your software category]"

2. Accept the mismatch and adjust: Include high-engagement topics as 20-30% of content (audience building), use 70-80% for business-aligned topics (business outcomes)

3. Pivot your positioning: If audience consistently engages with unexpected topics, maybe that's a signal your positioning should evolve

Don't ignore the data. Your audience is telling you something valuable.

Q8: How long does it take to see results from optimizing my LinkedIn strategy?

Answer: Timeline for results:

• 2-4 weeks: You'll notice which specific posts perform better with new approach

• 1-2 months: Engagement rate trends become clear

• 2-3 months: Follower growth changes become measurable

• 3-6 months: Business outcomes (DMs, meetings, opportunities) compound

Important: Consistency matters more than perfect execution. Posting 3x/week with 80% optimization beats posting 1x/week with 100% optimization.

Q9: What if I don't have Creator Mode enabled?

Answer: Enable it immediately. It's free and gives you access to Creator Analytics.

How to enable Creator Mode:

1. Go to your LinkedIn profile

2. Click "Resources" in your profile section

3. Select "Creator mode"

4. Toggle on

5. Choose up to 5 topics you post about

Benefits:

• Access to Creator Analytics

• "Follow" button becomes primary (instead of "Connect")

• LinkedIn Live access (if eligible)

• Profile shows up in search for your topics

Downside: None. Enable it.

Q10: Can I use Creator Analytics if I have a company page instead of a personal profile?

Answer: No. Creator Analytics is only available for personal LinkedIn profiles with Creator Mode enabled.

Company pages have separate analytics in LinkedIn Page Analytics, which shows:

• Page views

• Post impressions and engagement

• Follower demographics

• Visitor demographics

Different from Creator Analytics: Company page analytics lack the detailed top-post export and 365-day historical data that Creator Analytics provides.

Recommendation: If you're building thought leadership, prioritize your personal profile. Company pages have 10-20x lower organic reach than personal profiles on LinkedIn.

Key Terms Glossary

Engagement Rate: (Total Engagements ÷ Total Impressions) × 100. Measures percentage of people who engaged with your content after seeing it.

Creator Mode: LinkedIn profile setting that unlocks Creator Analytics, LinkedIn Live, and other creator features.

Content Pillars: The 3-5 core topics you consistently post about to build topical authority.

ICP (Ideal Customer Profile): The specific job titles, industries, seniority levels, and company sizes that represent your target audience.

Follower Drivers: Content designed to attract new followers (broader appeal, tactical focus).

Engagement Drivers: Content designed to deepen relationships with existing audience (strategic depth, niche focus).

TOP POSTS Sheet: Tab in Creator Analytics export showing your top 50 posts by engagement and impressions.

DEMOGRAPHICS Sheet: Tab in Creator Analytics export showing audience breakdown by job titles, industries, seniority, company size, and location.

Summary: The 5 Most Important Takeaways

1. Download LinkedIn Creator Analytics quarterly (365-day window) to track content performance, audience composition, and follower growth trends.

2. Run the 6 core analyses (content performance, topic patterns, timing, follower growth, audience composition, engagement rates) to identify what actually works for YOUR audience.

3. Optimize for engagement rate (2-3%+), not raw reach. High engagement signals quality to LinkedIn's algorithm, which expands reach organically.

4. Define 3-5 content pillars based on what your data shows resonates, not what you think should work.

5. Track business outcomes manually (DMs → meetings → opportunities) since Creator Analytics doesn't connect content to revenue.

Next Steps: Your 7-Day Action Plan

Day 1: Download your LinkedIn Creator Analytics (365 days)
Day 2: Run Analysis #1 (Content Performance) and Analysis #6 (Engagement Rate)
Day 3: Run Analysis #2 (Topic Patterns) and define your 3-5 content pillars
Day 4: Run Analysis #3 (Timing) and Analysis #4 (Follower Growth)
Day 5: Run Analysis #5 (Audience Composition) and assess ICP alignment
Day 6: Build your data-driven content calendar (4 weeks ahead)
Day 7: Set up weekly/monthly tracking system

Week 2+: Execute your strategy, track results, iterate based on data.

Want the Prompts to Analyze Your Data Faster?

This guide shows you what to analyze and why it matters. But the actual analysis takes 3-5 hours per month.

I've created a LinkedIn Creator Analytics Prompt Library with ready-to-use AI prompts that speed up the entire process. Just plug your data into the prompts and get instant insights on:

• Content performance patterns

• Topic analysis and content pillar identification

• Timing optimization

• Follower growth drivers

• Audience composition gaps

• Engagement rate benchmarking

• Business outcome tracking frameworks

The catch: It's only for existing DOJO AI users.

For DOJO Users:

Access the DOJO Academy here: [Coming Soon]
Password: Check the DOJO shared Slack channel

Or check your recent DOJO dispatches, we smuggled them out yesterday [27/01/2026]

Not a DOJO User Yet?

If you want access to the prompt library (and the full DOJO AI platform that automates all of this), book a demo with me here.

We'll walk through how DOJO AI can turn your LinkedIn data—and all your other marketing data—into actionable insights that drive real business outcomes.

About This Guide

Author: Luke Costley-White
Company: DOJO AI
Mission: Help marketers and founders leverage data and AI for measurable growth
Updated: January 15, 2026
Version: 1.0 (AEO-Optimized)

More Resources

• The LinkedIn Data Download Masterclass - How to analyze your full LinkedIn data export (connections, messages, profile views)

• DOJO AI Blog - Marketing strategy, data analytics, and AI insights

• Connect with Luke on LinkedIn - Follow for content on marketing data, personal branding, and AI

Citation Information

To cite this guide:

Costley-White, L. (2026). How to Turn Your LinkedIn Creator Analytics Into a Content Strategy That Actually Works. DOJO AI. Retrieved from https://www.dojoai.com/blog/how-to-turn-linkedin-creator-analytics-into-a-content-strategy-that-really-works

Last Updated: January 15, 2026
Reading Time: 28 minutes
Word Count: ~11,500 words

Your Creator Analytics is a 365-day record of what works. Most people ignore it. You shouldn't.