How to Analyze LinkedIn Contacts

Your LinkedIn connection list is more than just a digital rolodex, it's a goldmine of professional data waiting to be explored. Buried within that list are trends about your career path, opportunities for partnerships, and clues about who you should be talking to next. This post will walk you through exactly how to export, clean, and analyze your LinkedIn contacts to unlock those insights.

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Why Bother Analyzing Your LinkedIn Contacts?

Taking a closer look at your network isn't just an academic exercise. It's a strategic move that can directly impact your career or business. Before we get into the "how," let's quickly cover the "why."

Analyzing your contact list helps you:

• Understand Your Network's DNA: What companies are most represented? What are the common job titles? This shows you the professional circles you naturally move in and where you might have unseen influence.
• Identify Key Opportunities: You might discover you have a dozen contacts at a company you've been trying to partner with or sell to. That's a huge collection of potential warm introductions you didn't know you had.
• Spot Network Gaps: Maybe you're pivoting into the renewable energy sector but notice you have zero connections there. That's a clear signal to start targeted networking.
• Refine Your Personal Brand: Understanding who your audience is (and isn't) helps you tailor your content, posts, and comments to provide more value and resonate more deeply.
• Track Your Networking Progress: By looking at when you connected with people, you can see how your networking activity has evolved over time, highlighting both active and slow periods.

Simply put, analyzing your network transforms it from a passive list into an active asset.

Step 1: How to Export Your LinkedIn Contacts

The first step is to get your hands on the data. For privacy reasons, LinkedIn has limited what information is in the basic export, but there's still plenty of value in what you can get. The primary file we'll work with is Connections.csv.

Here's how to download it:

1. Log in to your LinkedIn account on a desktop browser.
2. Click on the “Me” icon in the top navigation bar (the one with your profile picture).
3. Select “Settings & Privacy” from the dropdown menu.
4. On the left-hand menu, click on “Data privacy.”
5. In the main section, find the header “How LinkedIn uses your data” and click on the option “Get a copy of your data.”
6. You'll be presented with two choices. Select the first one: “Want something in particular? Select the data files you're most interested in.”
7. Check the box for “Connections” and then click the blue “Request archive” button.

LinkedIn will email you a link to download your data archive, which usually only takes about 10 minutes. Once downloaded, unzip the file, and you'll find a CSV file named Connections.csv inside. This is the file we'll work with.

A Quick Note on the Data: For a long time, this export included emails. That is no longer the case. The modern Connections.csv file includes five key columns: First Name, Last Name, Company, Position, and Connected On. While this is less information than before, it's still more than enough to gather powerful insights.

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Step 2: Clean and Prepare Your Data For Analysis

Now for the least glamorous - but most important - part of data analysis: cleaning. Before you can create any meaningful charts or tables, you need to tidy up your CSV file in a spreadsheet program like Microsoft Excel or Google Sheets.

Open Connections.csv and you'll immediately see why this is necessary. Data entered by humans is inherently messy.

Common Data Cleaning Tasks:

• Standardize Company Names: You'll likely see variations like "Google," "Google Inc.," and "Google LLC." For accurate analysis, they all need to be the same. Use the "Find and Replace" function (Ctrl+H or Cmd+Shift+H) to standardize them. Pick one version and stick with it.
• Group Similar Job Titles: People use different titles for the same role, like "VP of Sales," "Vice President, Sales," and "Sales VP." While you can't automate this perfectly, you can do some manual grouping for your most common roles. For example, you could create a new column called "Title Category" and manually label these as "Sales Leadership."
• Handle Missing Data: Some contacts might not have a "Company" or "Position" listed. You'll have to decide how to handle these. You can either filter them out of your analysis for certain questions or leave them as-is, where they'll show up as "(blank)" in your reports.
• Format the 'Connected On' Date: Make sure the "Connected On" column is formatted as a date in your spreadsheet program. Select the entire column, go to Format > Number > Date, and choose your preferred format. This is critical for analyzing your networking activity over time.

Take 15-20 minutes to clean up your data. Your future self will thank you when you start building pivot tables.

Step 3: Uncover Insights with Pivot Tables

This is where the magic happens. Pivot tables are the fastest way to summarize large datasets in a spreadsheet. They allow you to slice, dice, and group your connection data to answer specific questions without writing a single formula.

Let's walk through creating a few key reports in Google Sheets or Excel. The steps are nearly identical for both.

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Question 1: What Companies are Most Represented in My Network?

This report will show you a ranked list of companies where your connections work. It's perfect for spotting clusters of colleagues, alumni, or potential business opportunities.

1. Select all of your data (Ctrl+A or Cmd+A).
2. Go to Insert > Pivot Table. A new sheet will open with the Pivot Table editor.
3. In the editor sidebar:
4. Sort the results in descending order by the COUNTA of First Name to see the top companies first.

You'll instantly see a ranked list. This could reveal surprising patterns, like discovering you have a strong contingent of contacts at a particular company you hadn't realized was so prominent in your network.

Question 2: What Are the Most Common Job Titles I'm Connected With?

This is similar to the company report, but it helps you understand the professional roles and seniority levels within your network.

1. Create another pivot table from your cleaned data source.
2. In the editor sidebar:
3. Sort the table in descending order to bring the most common job titles to the top.

This analysis is especially useful for content creators and marketers. If you notice a large number of "Product Managers" in your network, you can start creating content that directly addresses their unique challenges and interests.

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Question 3: How Has My Network Grown Over Time?

This report helps visualize your networking momentum. Are there specific years or months where you were particularly active in making new connections? This can correlate with job searches, conference attendance, or content campaigns.

1. Create a final pivot table.
2. In the editor sidebar:
3. Now, you need to group the dates. Right-click any date in the row labels of your pivot table and select Create pivot date group. Choose "Year-Month" or just "Year" to group the connections accordingly.

With this summarized data, create a simple line chart to visualize the trend. You'll see a visual representation of your entire LinkedIn networking history, with peaks and valleys telling the story of your professional journey.

Turning Your Analysis into Actionable Steps

Data is only useful if it drives action. Now that you have these reports, what do you actually do with the information?

• If you find a cluster of contacts at a target company: Don't just let that insight sit there. Reach out. Send a personalized message referencing your analysis and your shared connections. Ask for an introduction to key decision-makers if you're in sales.
• If a specific job title dominates your network: Tailor your next LinkedIn post to that group. If you're connected to a hundred "Software Engineers," write about a new development or framework you're excited about. It shows you're a valuable part of their professional community.
• If you identify gaps in your network: Make a concerted effort to fill them. Join groups and engage in conversations relevant to that industry or role. Search for people with specific titles and send personalized connection requests, explaining why you'd like to connect.

Final Thoughts

By exporting your LinkedIn connection data and giving it a quick analysis in a spreadsheet, you can move from passively collecting contacts to actively understanding and leveraging your professional network. This straightforward process unlocks value by revealing hidden clusters, strategic gaps, and prime opportunities for engagement.

Of course, manually pulling and creating reports like this can be time-consuming. As your network grows, this approach becomes less feasible. Consider integrating tools that connect to your marketing and sales platforms, like your CRM, ad accounts, and analytics tools, to automate insights and build dashboards just by asking questions in plain English, giving you back time to focus on strategy and relationship building. For instance, consider using Graphed for easy management of your data and analytics needs.