How to Export LinkedIn Post Likers to Excel: A Complete Guide.

How to Export LinkedIn Post Likers to Excel: A Complete Guide.

LinkedIn has evolved into a powerful platform for professionals to connect, share content, and build meaningful relationships. While the number of likes on a post may seem like a vanity metric, it's actually a goldmine of valuable data for marketers, sales teams, and recruiters. 

Understanding who is engaging with your content and why can provide insights into your target audience, help you generate leads, and optimise your LinkedIn strategy.

However, manually gathering this data can be time-consuming and frustrating. LinkedIn doesn't offer a straightforward way to export a list of users who have liked your posts. 

This is where Scrupp, a cutting-edge LinkedIn data scraping tool, comes into play.

In this guide, we'll show you how to efficiently export LinkedIn post likers using Scrupp and explore the various ways you can leverage this data to boost your LinkedIn engagement, generate leads, and optimise your content strategy. Let's dive in!

What are LinkedIn Post Likes?

At its core, a LinkedIn post like is a quick, one-click way for someone to express that they find your content interesting, relevant, or worth acknowledging. When a user reads your post and hits the “like” button, it signals that your content has made a positive impact.

Beyond just the traditional "like," LinkedIn offers several other reaction emojis that allow users to express different sentiments toward your post. These include:

• Celebrate 🎉: When someone wants to applaud an achievement or milestone shared in your post.
• Support 💙: A way for users to show empathy, encouragement, or solidarity.
• Love ❤️: Used for content that resonates emotionally or demonstrates passion and care.
• Insightful 💡: A recognition of content that offers valuable knowledge or thought-provoking ideas.
• Funny 😂: When a post brings humour or light-heartedness to the professional sphere.

These reactions go beyond a simple "like," offering more nuanced feedback on how your audience perceives your content. Each one gives you insight into the emotional impact or message your post conveys.

Understanding who is interacting with your posts and how they are responding—whether through likes, support, or insightful reactions—helps you measure the effectiveness of your content. 

It also provides a window into your audience's preferences, allowing you to tailor future posts to maximise engagement and appeal to their interests.

Why Scrape LinkedIn Post Likers?

Scraping LinkedIn post likers can transform the way you approach networking, marketing, and data analysis on the platform. But why is it so crucial to gather this specific data? 

Here are the key reasons:

1) Lead Generation: Knowing who likes your posts helps you identify potential leads who are already interested in your content. This interest can be a starting point for personalised outreach, significantly increasing the likelihood of converting engagements into tangible business opportunities.

For example, if I offer website design services and someone engages with my content marketing campaign on LinkedIn, there is a high likelihood that they will consider purchasing my services

2) Audience Insights: Scraping liker data enables a deeper understanding of your audience. By analysing who interacts with your posts, you can uncover trends in demographics, job titles, and industries. This insight is invaluable for tailoring your content strategy to better meet the needs and interests of your target audience.

3) Content Optimization: Engagement data tells you what works and what doesn’t. By focusing on the types of posts that generate the most likes and reactions, you can refine your content strategy to produce more of what your audience wants to see, enhancing overall engagement and reach.

4) Competitive Analysis: Understanding your own engagement is vital, but so is knowing how you stack up against competitors. Scraping liker data allows you to benchmark your LinkedIn activities against those of similar profiles or companies, giving you a strategic edge in your content and outreach efforts.

5) Efficiency and Automation: Manual data collection is not only time-consuming but also prone to errors. Using a tool like Scrupp automates the process, ensuring you get accurate and timely data without the tedious effort. 

6) Building Stronger Relationships: By recognizing and interacting with those who frequently engage with your posts, you can build stronger, more meaningful relationships. Personalised thank-you messages, invitations to webinars, or sharing relevant content directly can turn casual likers into loyal followers and advocates.

How to Export LinkedIn Post Likers Using Scrupp

Manually exporting LinkedIn post likers can be time-consuming, especially if you receive high engagement. Scrupp streamlines this process, automating the export of post likers into Excel or CSV formats, making it easy to gather details like names, job titles, and industries.

Here’s a step-by-step guide to exporting LinkedIn post likers:

Step 1: Visit Scrupp.com and create your account. Get started for free with the included credits.

Step 2: Sign in, navigate to the "LinkedIn Post Likers" tool on the Scrupp website, and click the "Launch Export" button. 

Step 3: Connect your LinkedIn Account & Proceed to the next step

Step 4: Visit your LinkedIn account, locate the post you want to scrape, and copy its link.

Step 5: Return to your Scrupp account, and paste the link into the "Source Link" section.

Step 6: Specify how many post likers you want to scrape from the LinkedIn post. Set the "Page Start From" field to "0" and select whether you'd like to scrape emails from the leads.

Step 7: Once the leads are scraped, you can download them in the excel sheet. 

Check the sample excel file here: LinkedIn Post Likers

This completes our guide on how to scrape LinkedIn post likers to excel. 

Can You Export LinkedIn Post Analytics?

Yes, you can export LinkedIn post analytics.  

LinkedIn offers a built-in analytics tool that provides detailed insights into your post performance. You can export this data as a CSV or Excel file to analyze it further or share it with others.  

Here's a quick guide:

a) Go to your LinkedIn profile.

b) Click on the "Analytics" tab.

c) Select the "Posts" section.

d) Choose the time period you want to analyse.

e) Click on the "Export" button.

Sample Post Analytics: Link

Can You Export LinkedIn Post Views?

LinkedIn's built-in analytics tool provides valuable insights into your post performance, including the number of views. To gain a more comprehensive understanding of your audience engagement and reach, you can export this data for further analysis.

Here's how to export LinkedIn post views:

1) Access your LinkedIn profile: Log in to your LinkedIn account and navigate to your profile page.

2) Open the Analytics tab: Click on the "Analytics" tab located on your profile page.

3) Select the "Posts" section: In the Analytics dashboard, choose the "Posts" section to view your post performance metrics.

4) Choose the desired time period: Specify the timeframe you want to analyse your post views. You can select a custom range or choose a predefined option like "Last 7 days," "Last 30 days," or "Last 90 days."

5) Locate the "Export" button: Look for the "Export" button, typically located near the top or bottom of the post analytics section.

6) Download the data: Click on the "Export" button to download a CSV or Excel file containing your post view data.

Utilise the exported data for:

• Audience segmentation: Identify the demographics of your viewers based on factors like location, industry, and job title.
• Content optimization: Analyse which types of content resonate most with your audience and tailor your future posts accordingly.
• Performance tracking: Monitor the effectiveness of your LinkedIn marketing campaigns and identify areas for improvement.
• Lead generation: Use post view data to target potential leads and build relationships with your audience.

By exporting and analysing LinkedIn post views, you can gain valuable insights into your audience engagement and optimise your content strategy for maximum impact.

Benefits Of Exporting LinkedIn Post Likers Data

1) Easier Data Analysis: Once you've exported the data to Excel, you can perform various types of analysis that aren't possible within LinkedIn’s interface. You can segment your likers by job title, industry, or location, and create visual reports, charts, and graphs for clearer insights into your post's reach.

2) Personalised Outreach: Having a list of people who engage with your content allows you to craft personalised messages for follow-up. Whether you're looking to connect with potential clients, partners, or industry influencers, exporting likers makes targeted outreach simple and efficient.

3) Streamlined Workflow: Exporting your liker data into an organised spreadsheet (or CSV file) means you can easily share it with your team, import it into your CRM or marketing automation tools, or integrate it into other workflows. This helps sales and marketing teams work together seamlessly when using LinkedIn as a lead-generation platform.

4) Tracking Engagement Over Time: Exporting and saving the data allows you to track how post engagement evolves. By comparing past data, you can spot trends, see which types of posts perform best, and make adjustments based on solid metrics.

5) Targeted Retargeting Campaigns: With access to the names and industries of your post likers, you can create targeted retargeting campaigns through LinkedIn Ads or other platforms. Knowing who has engaged with your content previously makes it easier to retarget those individuals with highly relevant offers or updates.

6) Lead Nurturing: If you are in sales, exporting your LinkedIn post likers data helps identify potential leads who have already shown interest in your content. You can then move these prospects through your sales funnel by nurturing them with follow-up content, personalised outreach, or offers.

7) Database Building: Exporting this data regularly allows you to build a robust engagement database over time. As you keep exporting LinkedIn post likers across multiple posts, this database becomes an invaluable resource for recurring outreach, lead generation, and even LinkedIn automation campaigns.

How to Analyse LinkedIn Engagement Data In Excel

After exporting your LinkedIn post likers' data using Scrupp, the dataset you receive contains detailed information across various categories. This data, which includes fields like name, LinkedIn profile, email, job title, company details, and industry, can be analysed in Excel to derive meaningful insights.

Below is a practical guide on how to clean, sort, and analyse the data effectively, with a focus on key metrics like job positions, industries, and company information.

Step 1: Importing LinkedIn Post Likers Data into Excel

The scraped data usually comes in a CSV file that you can open in Excel:

1. Open Excel.
2. Navigate to File > Open and locate the CSV file containing your exported LinkedIn data.
3. Once imported, the data will appear in a table with columns such as first_name, last_name, industry, company_name, email, and more.

Step 2: Cleaning and Organizing Data

To ensure that your analysis is accurate and efficient, clean the data by removing duplicates and standardising formats.

1) Remove duplicates:

• Go to Data > Remove Duplicates.
• Select columns like email or LinkedIn URL to ensure no repeated entries.

2) Filter out empty or irrelevant fields:

Use Sort & Filter to eliminate rows with missing critical data, such as email or company_name.

3) Normalise job titles and industries:

Ensure that similar job titles (e.g., "Marketing Manager" vs. "Manager of Marketing") are consistent for better analysis. You can use the Find & Replace tool to standardize these terms.

Step 3: Analysing Data with Pivot Tables

To analyse LinkedIn post likers data using a Pivot Table, let's use the relevant columns from our scraped dataset. Specifically, we’ll look at industry and num_of_connections to summarise the number of connections based on industry.

1) Select Your Data:

• Highlight the relevant columns of your dataset, particularly industry and num_of_connections.

2) Insert the Pivot Table:

• Go to the Insert tab and click on Pivot Table.
• In the dialog box, make sure your entire data range is selected.
• Choose New Worksheet and click OK.

3) Build the Pivot Table:

In the Pivot Table Field List on the right side of the screen:

• Drag "industry" to the Rows section to categorise data by industry.
• Drag "num_of_connections" to the Values section to sum the total number of connections for each industry.

This table provides a clear breakdown of how many connections your likers have in different industries.

Step 4: Visualizing Engagement Data with Charts

Charts make it easy to visualise trends and patterns in your engagement data:

1) Select the Pivot Table or data you want to visualise.

2) Go to Insert > Charts and select a Bar or Pie Chart to quickly compare industry engagement or company sizes.

Step 5: Automating Future Reporting with Macros and Templates

To save time, you can automate repetitive tasks using Excel Macros and Templates:

1) Create a Template: Set up your Pivot Tables and charts, then save the file as a template:

• Go to File > Save As and select Excel Template (.xltx).

2) Record Macros: Automate recurring tasks, such as importing data or formatting sheets:

• Go to View > Macros > Record Macro, perform the task, and stop the recording. Now you can rerun this Macro to automate future tasks.

Key Metrics to Focus On

Using the detailed data exported from Scrupp, you can focus on several key metrics:

1. Industry Insights: Group likers by industry to see which sectors are engaging most with your content.
2. Job Titles: Analyse the professional roles of those who engage with your posts. This helps tailor content for specific audiences.
3. Company Size: Use company_size data to understand if you're engaging more with small startups or large enterprises.
4. Location Analysis: Filter by location to see which regions are interacting most, enabling geo-targeted marketing efforts.

Common Challenges When Exporting LinkedIn Post Likers

While exporting LinkedIn post likers can provide valuable insights, the process is not without its challenges. Using the Scrupp tool addresses many of these hurdles, but it's important to understand the potential roadblocks and how Scrupp overcomes them.

1. LinkedIn’s Restrictions on Data Access

LinkedIn places strict limits on how users can access and export data. The platform does not provide a direct way to export post likers through its interface, making manual efforts tedious and incomplete.

2. Data Privacy Concerns

Exporting data from LinkedIn can raise concerns about GDPR and other privacy regulations. It’s essential to ensure that any data scraping adheres to privacy laws and doesn't violate LinkedIn's terms of service.

3. Incomplete or Inaccurate Data

One common issue with manual data scraping or using unreliable tools is that the data can often be incomplete, missing key information like emails, job titles, or company names. This hampers your ability to use the data effectively for outreach or analysis.

4. Data Organization and Analysis

Once the data is exported, structuring it for analysis can be a challenge. Cleaning and organising large datasets in tools like Excel takes effort, especially if the data is inconsistent or incomplete.

Conclusion

Exporting and analysing LinkedIn post likers data can significantly enhance your engagement strategy and networking efforts. With Scrupp, the process is quick and efficient, allowing you to gather key insights like industry, job title, and company details. Once exported, analysing the data in Excel helps you identify trends, refine your outreach, and create more targeted content.

By following the steps outlined in this guide, you can streamline your data analysis and continuously improve your LinkedIn presence. With tools like Scrupp and Excel, optimising your LinkedIn strategy becomes a seamless and data-driven process, helping you connect with the right audience and maximise your influence.

FAQs

1) Can I export LinkedIn post likers manually?

LinkedIn doesn’t offer a direct feature to export post likers. Manually copying and pasting details from each liker is time-consuming and inefficient, especially for posts with high engagement. Using tools like Scrupp automates this process.

2) How often can I export LinkedIn post likers using Scrupp?

You can use Scrupp as frequently as you like, depending on your plan or subscription. The tool allows for automated exports, making it easier to collect data regularly without manual intervention.

3) Can I use Scrupp to scrape post likers from multiple LinkedIn posts?

Yes, Scrupp allows you to scrape likers from multiple LinkedIn posts, helping you collect and analyze data across different content types to better understand your audience.

4) Does Scrupp provide email addresses of post likers?

Yes, if available, Scrupp can extract email addresses from publicly accessible profiles. However, not all LinkedIn users share this information publicly, so it may not be available for every liker.

5) Is Scrupp compliant with LinkedIn’s policies?

Yes, Scrupp is designed to adhere to LinkedIn’s terms of service and privacy policies by scraping only publicly available information. It does not violate LinkedIn’s guidelines.