How to Merge LinkedIn Analytics & Resume Performance Reports

If you’ve ever wondered how to turn LinkedIn’s rich engagement data into actionable insights for your resume, you’re in the right place. In this guide we’ll walk through a step‑by‑step process that merges LinkedIn analytics with resume performance reports, helping you fine‑tune your personal brand, beat applicant tracking systems (ATS), and land more interviews. By the end you’ll have a repeatable workflow, a handy checklist, and answers to the most common questions.

Why Combine LinkedIn Analytics with Resume Performance?

Employers increasingly use both LinkedIn activity and resume metrics to gauge candidate fit. According to a recent LinkedIn Talent Solutions report, 71% of recruiters use LinkedIn data alongside traditional resumes to assess cultural fit and industry relevance. When you align the two data sources you can:

• Identify which skills and keywords drive the most profile views and translate them into resume bullet points.
• Spot gaps between the jobs you’re targeting and the roles that generate the most engagement on LinkedIn.
• Optimize your resume for the same algorithms that rank LinkedIn profiles, improving ATS pass rates.

Resumly’s suite of AI tools—like the AI Resume Builder and ATS Resume Checker—makes this integration painless.

Prerequisites

Before you start, gather the following:

1. LinkedIn Analytics Export – You need a Premium account or access to the “Analytics” tab on your profile.
2. Resume Performance Report – This can be a download from an ATS tracker, a Resumly Resume Roast, or a simple spreadsheet tracking interview callbacks.
3. A spreadsheet tool – Google Sheets or Excel works fine.
4. Resumly account – Optional but recommended for AI‑powered keyword matching.

Step 1: Export LinkedIn Analytics

1. Log into LinkedIn and navigate to Me > View profile.
2. Click Analytics (you’ll see tabs for Visitors, Search Appearances, and Post Views).
3. Choose Export at the top‑right of the page. Select the date range (30‑day, 90‑day, or custom) and download the CSV.
4. Save the file as linkedin_analytics.csv.

Tip: If you don’t have a Premium account, you can still copy the table manually into a sheet.

Step 2: Gather Resume Performance Data

Your resume performance report should capture metrics such as:

• Applications Sent
• Interviews Secured
• ATS Pass Rate
• Keywords Highlighted

If you use Resumly’s Application Tracker, export the data as CSV. Otherwise, create a simple table:

Save this as resume_performance.csv.

Step 3: Align Metrics – Building a Unified Dashboard

Open a new Google Sheet and import both CSV files into separate tabs.

1. Create a Master Tab – Use IMPORTRANGE (Google Sheets) or Power Query (Excel) to pull key columns.
2. Standardize Date Formats – Ensure both datasets use the same date format (YYYY‑MM‑DD).
3. Map Keywords – In the LinkedIn tab, locate the Top Skills column. In the resume tab, locate the Keywords Highlighted column.
4. Add a “Engagement Score” column:

   =IFERROR(VLOOKUP(A2,LinkedIn!A:B,2,FALSE),0)
   

   This pulls the number of profile views for the same day you applied.
5. Calculate Correlation – Use =CORREL(range1, range2) to see how LinkedIn views correlate with interview callbacks.

Sample Dashboard Layout

When you spot a spike in Profile Views followed by a higher Interview? rate, you’ve identified a winning content‑to‑application pattern.

Step 4: Use Resumly Tools to Sync Keywords

Now that you know which LinkedIn skills drive traffic, feed them into Resumly’s AI engine:

1. Open the AI Cover Letter tool.
2. Paste the top 5 LinkedIn skills (e.g., Data Analysis, Agile Methodology, Stakeholder Management).
3. Let Resumly suggest bullet points that incorporate these terms naturally.
4. Run the updated resume through the ATS Resume Checker to verify score improvements.
5. Save the new version as resume_optimized.pdf.

Result: Your resume now mirrors the language that LinkedIn’s algorithm rewards, increasing the likelihood of ATS matches.

Step 5: Visualize & Interpret Insights

A visual representation helps you communicate findings to mentors or career coaches.

• Bar Chart: Profile Views vs. Interview Rate per week.
• Heat Map: Keyword frequency in LinkedIn vs. ATS score.
• Line Graph: ATS Score trend after each resume tweak.

Tools like Google Data Studio or Microsoft Power BI can pull directly from your Google Sheet. Export the final dashboard as a PDF and keep it in your Resumly Career Guide folder for future reference.

Checklist: Merging LinkedIn Analytics with Resume Performance

• Export LinkedIn analytics CSV.
• Export resume performance report CSV.
• Standardize date formats.
• Map LinkedIn top skills to resume keywords.
• Calculate correlation between views and interviews.
• Update resume using Resumly AI tools.
• Run ATS check and record new score.
• Visualize data and note actionable trends.
• Review checklist weekly and iterate.

Do’s and Don’ts

Mini Case Study: Sarah, a Product Manager

Background: Sarah had a 45% interview rate but wanted to increase it. She exported LinkedIn analytics and noticed that posts about “Roadmap Planning” generated 30% more profile views.

Action: She added “Roadmap Planning” and related metrics to her resume bullet points using Resumly’s AI Resume Builder. After running the ATS checker, her score rose from 68% to 84%.

Result: Within two weeks, Sarah’s interview rate jumped to 62%, and she secured an offer at a Fortune 500 company.

Key takeaway: Aligning LinkedIn‑driven keywords with resume content can dramatically improve ATS performance.

Frequently Asked Questions (FAQs)

1. Can I merge data without a Premium LinkedIn account?
   • Yes. You can manually copy the analytics tables or use third‑party tools like ShieldApp to export data.
2. What if my LinkedIn analytics show high views but low interview callbacks?
   • Review the quality of traffic. High views may come from unrelated industries; adjust your headline and summary to attract the right audience.
3. How often should I update my resume based on LinkedIn insights?
   • Aim for a quarterly refresh, or after any major shift in your career focus.
4. Do Resumly’s free tools help with keyword alignment?
   • Absolutely. The Job‑Search Keywords tool suggests high‑impact terms based on your LinkedIn activity.
5. Is there a way to automate the CSV merge?
   • Yes. Use Google Apps Script or Zapier to pull LinkedIn data into Google Sheets automatically.
6. Will merging these reports improve my salary negotiations?
   • Data‑driven proof of impact (e.g., “Increased profile views by 40% leading to 3 interview offers”) strengthens your case during negotiations.
7. Can I share my merged report with recruiters?
   • Definitely. Export the dashboard as a PDF and attach it to your application or LinkedIn message.
8. What if my ATS score drops after adding new keywords?
   • Re‑run the ATS Resume Checker and tweak phrasing. Sometimes a keyword is too generic; replace it with a more specific variant.

Conclusion: Mastering the Merge for Career Growth

By following this guide you now know how to merge LinkedIn analytics with resume performance reports in a systematic, data‑driven way. The process turns raw engagement numbers into concrete resume improvements, boosts ATS scores, and ultimately increases interview callbacks. Remember to iterate—data evolves, and so should your personal brand.

Ready to supercharge your job search? Explore the full suite of Resumly tools, from the AI Resume Builder to the Career Personality Test, and watch your career metrics climb.

Happy hunting!