Free Methods to Extract Candidate Contact Info from LinkedIn

Finding candidate contact details quickly is a major challenge for recruiters. Whether handling a large pool of resumes or searching LinkedIn for qualified leads, extracting emails and phone numbers can boost your recruitment speed. The best part? You can do it for free!

In this blog, we’ll explore free methods to extract contact info from resumes and LinkedIn profiles, plus some HR tools and techniques to streamline the process.

Key Benefits of Extracting Candidate Emails and Phone Numbers

Before we dive into the methods, let’s briefly discuss why extracting contact details from resumes and LinkedIn is critical in today’s recruitment landscape.

1. Faster Recruitment Process: By having direct access to a candidate’s email and phone number, you can reach out more quickly for interviews and job opportunities.

2. Improved Candidate Engagement: With personalized outreach, candidates are more likely to respond positively, ensuring a smoother recruitment process.

3. Talent Pool Building: Extracted contact details can be stored in your CRM for future recruitment efforts, allowing you to nurture long-term relationships with candidates.

Effective Ways to Extract Emails and Phone Numbers from Resumes

Resumes often contain a wealth of information, but manually extracting contact details from hundreds of documents can be tedious. Fortunately, you can use several free tools and methods to extract contact information.

1. Using Python Scripts to Extract Emails and Phone Numbers

Python is a powerful tool for processing data and can be used to extract email addresses and phone numbers from resumes in bulk. You can automate this process with a simple Python script. Here’s how:

Step-by-Step Process:

1. Install Required Libraries: First, you’ll need to install some Python libraries like PyPDF2, re, and docx.

pip install PyPDF2 python-docx

2. Writing the Script: This script will help you extract emails and phone numbers from PDF and Word resumes.

import re
import PyPDF2
from docx import Document

# Function to extract emails and phone numbers from text
def extract_contact_info(text):
    emails = re.findall(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', text)
    phone_numbers = re.findall(r'\b\d{10}\b', text)  # Adjust regex for country-specific numbers
    return emails, phone_numbers

# Function to read PDF files
def extract_from_pdf(pdf_path):
    with open(pdf_path, 'rb') as file:
        reader = PyPDF2.PdfReader(file)
        text = ""
        for page in range(len(reader.pages)):
            text += reader.pages[page].extract_text()
        return extract_contact_info(text)

# Function to read Word files
def extract_from_docx(docx_path):
    doc = Document(docx_path)
    full_text = ""
    for para in doc.paragraphs:
        full_text += para.text
    return extract_contact_info(full_text)

# Replace 'resume.pdf' and 'resume.docx' with actual file paths
print(extract_from_pdf('resume.pdf'))
print(extract_from_docx('resume.docx'))

3. Run the Script: Run the script, and it will extract email addresses and phone numbers from the specified PDF or Word resume.

Why This Method Works:

• Cost-effective: Using Python is completely free.
• Automated: It can process bulk resumes with minimal manual intervention.
• Customizable: You can adjust the script to parse specific patterns, such as international phone numbers.

2. Free Resume Parsing Tools

If you’re not technically inclined, there are free online tools designed specifically for extracting information from resumes.

1. Resume Parser by HireAbility

HireAbility offers a basic version of its resume parsing tool for free. This tool is designed to extract not just email and phone numbers but also skills, job titles, and educational background.

Key Features:

• Multi-Format Support: It can parse resumes in multiple formats, including PDF, DOCX, and TXT.
• Contact Detail Extraction: Automatically extracts email addresses, phone numbers, and other contact information.
• Job Experience Parsing: In addition to contact details, it captures work experience, job titles, and durations.

How to Use:

1. Go to the HireAbility Resume Parser website and upload the resume.
2. The parser will scan the document and extract relevant information, including contact details.
3. You can export the parsed data into Excel or directly import it into your recruitment software.

Pros:

• Supports multiple file formats.
• Quick and accurate parsing of contact details.
• Can be integrated with ATS platforms.

Cons:

• The free version has limited parsing volume.
• Advanced features, such as parsing resumes in non-standard formats, require a paid subscription.

2. Resumator.io

Resumator.io is a completely free online tool that extracts contact information from resumes. It is simple, straightforward, and perfect for small-scale recruitment tasks.

Key Features:

• Email and Phone Number Extraction: Extracts email addresses and phone numbers from uploaded resumes.
• Resume Summary Generation: Provides a brief summary of the candidate’s key details, such as skills and experience.

How to Use:

1. Visit Resumator.io and upload the resume you wish to parse.
2. The tool will automatically extract the contact details and display them on the screen.
3. You can then copy the details or export them to a CSV file for further use.

Pros:

• Completely free with no hidden fees.
• Easy to use, no technical skills required.
• Fast and accurate extraction of emails and phone numbers.

Cons:

• Lacks advanced parsing features like education or skill extraction.
• Limited to contact detail extraction only.

3. Jobalytics – LinkedIn Resume Parser

Jobalytics is a Chrome extension that automatically parses resumes and LinkedIn profiles to extract contact details. It's an excellent free tool for recruiters who often source candidates through LinkedIn.

Key Features:

• Extracts Contact Information: Scrapes email addresses and phone numbers from LinkedIn profiles and resumes.
• Keyword Matching: Identifies relevant keywords based on job descriptions, helping you filter resumes more efficiently.
• Profile Parsing: Captures details from LinkedIn profiles, including work history, education, and certifications.

How to Use:

1. Install the Jobalytics Chrome extension.
2. Navigate to a LinkedIn profile or upload a resume to the extension.
3. The extension will parse the document or profile and extract key contact details, which can be exported to a CSV or spreadsheet.

Pros:

• Integrates with LinkedIn for seamless parsing of profiles.
• Easy to install and use for free.
• Provides additional features like keyword matching for better candidate screening.

Cons:

• Limited features in the free version.
• Bulk parsing may require a paid upgrade.

4. Rchilli Free Resume Parser

Rchilli is another robust parsing tool that offers a free version for small-scale usage. It is a cloud-based tool that efficiently parses resumes in multiple languages and extracts key details such as contact information, work history, and skills.

Key Features:

• Multi-Language Support: Can parse resumes in several languages, making it ideal for global recruitment.
• Contact Detail Extraction: Extracts email addresses, phone numbers, and other key details like job titles and experience.
• ATS Integration: Compatible with several ATS platforms, allowing seamless integration for recruiters using applicant tracking systems.

How to Use:

1. Visit Rchilli Resume Parser and create a free account.
2. Upload the resumes you want to parse.
3. The tool will extract email addresses, phone numbers, and other details, which can be exported to your ATS or downloaded in Excel format.

Pros:

• Excellent multi-language support for global recruiters.
• User-friendly interface with ATS integration options.
• Free tier available for limited usage.

Cons:

• The free version has usage limitations.
• Advanced parsing features require a paid subscription.

5. Sovren Resume Parser (Free Tier)

Sovren is known for its powerful parsing engine, and while most of its features are available in a paid version, there is a free tier that allows basic parsing. Sovren’s parser can extract contact details and other structured information from resumes and CVs.

Key Features:

• Multi-Format Support: Parses resumes in PDF, DOC, and TXT formats.
• Customizable Parsing: Allows you to customize what information is extracted, such as emails, phone numbers, and experience.
• Free for Small Scale Use: Offers a free tier for smaller recruitment needs.

How to Use:

1. Sign up for a free account on Sovren’s website.
2. Upload the resume or CV you want to parse.
3. The parser will scan the document and extract details, including contact information, which can be downloaded in various formats.

Pros:

• Offers a robust, customizable parsing engine even in the free version.
• Excellent for small-scale recruiters needing a powerful parsing tool.
• Integrates with ATS and other HR platforms.

Cons:

• Limited resume uploads in the free tier.
• Some advanced features require paid access.

6. Parsing API by DaXtra

DaXtra offers a parsing API with a free trial version that allows users to extract contact information, work experience, skills, and more from resumes. It’s suitable for developers who need a parsing tool that can integrate into their existing HR systems.

Key Features:

• API-Based Parsing: Allows you to integrate parsing functionality into your recruitment software or website.
• Contact Information Extraction: Extracts key contact details such as emails and phone numbers.
• Structured Data: Provides output in structured formats like XML and JSON, making it easy to integrate with databases or ATS systems.

How to Use:

1. Visit DaXtra Parsing API and sign up for the free trial.
2. Use the API to upload resumes and extract data.
3. The extracted contact details can be output in XML or JSON format for easy storage or analysis.

Pros:

• API-based, allowing integration into your own systems.
• Powerful parsing engine with accurate contact detail extraction.
• Supports a variety of file formats and output options.

Cons:

• Requires technical knowledge to implement the API.
• Free version is limited to trial use.

How It Works:

1. Upload the Resume: Upload your PDF or Word document to the tool.
2. Extract Contact Information: The tool will display extracted details such as email, phone number, and more.
3. Export the Data: You can export this data to Excel or save it directly into your ATS.

Advantages:

• No coding required: These tools are user-friendly and require no technical skills.
• Free to use: Most of these resume parsers offer a free tier or trial.

Step-by-Step Guide: Extracting Candidate CSV Files with Contact Details from LinkedIn Job Posts

Extracting candidate contact details from LinkedIn job posts can be a powerful technique for recruiters, especially when managing multiple candidates. While LinkedIn doesn’t offer a direct option to download candidate data as a CSV file, there are methods and third-party tools that can help you automate this process. Here's a step-by-step guide to extracting a CSV file with candidate contact details from LinkedIn job posts:

Step 1: Post a Job on LinkedIn

The first step is to post a job on LinkedIn. This allows you to attract candidates who will apply for the role and provide their contact information.

1. Log in to your LinkedIn Recruiter account.
2. Navigate to the "Jobs" tab at the top of the LinkedIn homepage.
3. Click on “Post a Job” and follow the instructions to fill in the job title, company, job description, and requirements.
4. Once the job is posted, you will begin receiving applications, including resumes and profiles with contact information.

Step 2: Collect Applications

When candidates apply, LinkedIn gathers their profile details and allows you to manage applicants through the LinkedIn Recruiter dashboard.

1. Go to the "Manage Job" section where you will find all your job postings.
2. Select the job you want to review and click on the "Manage Applicants" button.
3. Review each candidate's profile to ensure it meets your requirements. LinkedIn allows you to view resumes, profiles, and sometimes contact information directly within the application.

Step 3: Use a LinkedIn Data Extraction Tool

Since LinkedIn doesn’t provide a built-in feature to export contact details, you will need to use third-party tools to extract the information and convert it into a CSV file. Several tools and browser extensions can assist with this task. Here are some of the popular ones:

LinkedIn Recruiter System Connect (RSC)

• If you're using LinkedIn Recruiter, RSC helps integrate LinkedIn data into your ATS, making it easier to export details.
• Candidates’ profiles, including contact information, can be directly synced with your recruitment software, which may allow you to export them into CSV format.
• Other method is to first transfer applicants from talent pool to pipeline in linked recruiter projects section and then select the resumes. Then download as CSV. You can download 25 candidate details at once. 

Octoparse

• Octoparse is a web scraping tool that allows you to automate data extraction from LinkedIn job posts. With a simple configuration, you can scrape candidate profiles and export the data into a CSV file.

Steps for using Octoparse:

1. Install and open Octoparse on your computer.
2. Go to the LinkedIn job posting you want to extract data from.
3. Use Octoparse's Point and Click Interface to highlight candidate names, contact details (like email), and any other required information.
4. Run the extraction process. Once completed, export the data into CSV format directly from Octoparse.

Phantombuster

• Phantombuster is a LinkedIn automation tool that can be used to scrape profiles and extract email addresses and phone numbers.

Steps for using Phantombuster:

1. Install Phantombuster and sign up for an account.
2. Choose the LinkedIn Profile Scraper or LinkedIn Job Applicants Scraper.
3. Enter the URL of your LinkedIn job posting, and Phantombuster will start scraping candidate profiles.
4. After scraping, you can download the candidate contact details into a CSV file.

Step 4: Export Data into CSV

After extracting candidate contact details using one of the third-party tools, the final step is exporting this data into a CSV file.

1. Once the extraction process is complete, most tools like Octoparse and Phantombuster offer an option to download the scraped data in CSV format.
2. Simply click on the “Export to CSV” button within the tool interface.
3. Open the CSV file to verify that the contact information (e.g., emails, phone numbers) is correctly formatted.
4. Save the file to your system for further use.

Step 5: Organize Candidate Data

Now that you have your candidate contact details exported in a CSV file, you can organize the data for easier management and outreach. Here are a few tips:

1. Filter and Clean Data: Ensure the contact details extracted are accurate. Some candidates may have incomplete profiles, so it's important to clean the data (remove duplicates, empty fields, etc.).
2. Segment Candidates: Use Excel or Google Sheets to segment your candidate data based on qualifications, experience, or location for targeted outreach.
3. Import into ATS: If your company uses an Applicant Tracking System (ATS), you can upload the CSV file directly into the system to streamline your recruitment process.

How to Integrate multiple spreadsheets file into one Excel worksheet?

To integrate multiple spreadsheets into one Excel worksheet, you can follow a few different approaches depending on your needs and the tools available. Here's a step-by-step guide to integrating multiple spreadsheets into one Excel worksheet using three methods: manual copy-paste, Power Query, and VBA macros.

Method 1: Manual Copy and Paste

If you have a small number of spreadsheets and prefer a straightforward approach, you can manually copy and paste data into a single worksheet.

Step-by-Step Process:

1. Open all the spreadsheets that you want to integrate.

2. Select the data from the first spreadsheet:

   • Click and drag to select all the cells containing data.
   • Press Ctrl + C (Windows) or Cmd + C (Mac) to copy the selected data.

3. Paste the data into the destination Excel workbook:

   • Open the Excel workbook where you want to combine the data.
   • Select the cell where you want to start pasting the data (usually, cell A1).
   • Press Ctrl + V (Windows) or Cmd + V (Mac) to paste the data.

4. Repeat this process for all the other spreadsheets:

   • Make sure to paste the data under the previous dataset so that the new data doesn't overwrite anything.

5. Save the integrated workbook after all data is pasted.

Limitations:

• This method is not scalable for many spreadsheets.
• Time-consuming if you have large datasets.

Method 2: Using Power Query

Power Query is a powerful tool built into Excel (available in Excel 2010 onwards) that allows you to combine data from multiple spreadsheets easily.

Step-by-Step Process:

1. Organize your files:

   • Ensure all the spreadsheets you want to integrate are saved in the same folder. The file names should be easy to identify.

2. Open Excel and Launch Power Query:

   • Go to the Data tab in Excel.
   • Click Get Data > From File > From Folder.

3. Select the Folder:

   • A dialog box will appear. Browse and select the folder that contains the Excel files you want to combine.

4. Load the Files:

   • Once you select the folder, Excel will display a list of all the files in the folder. Click Combine in the top-right corner.
   • Power Query will automatically detect the structure of the spreadsheets. Select Combine & Load.

5. Combine Data:

   • In the next dialog box, Power Query will show a preview of the data. Ensure it’s pulling the correct data from the spreadsheets and click OK.
   • Power Query will combine all the spreadsheets into a single table, and the data will appear in one worksheet.

6. Finalize:

   • Once the data is combined, click Close & Load to load the integrated data into a new worksheet in Excel.

Advantages:

• Automatic data combination from multiple files.
• Ideal for large datasets.
• Can refresh data if you add more spreadsheets later.

Method 3: Using VBA Macros

If you want to automate the process and work with many files, VBA (Visual Basic for Applications) is a powerful way to merge data from multiple spreadsheets into one worksheet.

Step-by-Step Process:

1. Organize your files:

   • Place all the Excel files you want to merge into one folder for easy access.

2. Open Excel and Access VBA Editor:

   • Press Alt + F11 to open the VBA editor.
   • In the editor, click Insert > Module. This opens a blank code module where you can enter your VBA code.

3. Write the VBA Code: Use the following VBA script to combine multiple spreadsheets into one Excel worksheet:

Sub MergeWorkbooks()
    Dim FolderPath As String
    Dim FileName As String
    Dim Sheet As Worksheet
    Dim Wkb As Workbook
    Dim PasteRange As Range
    
    ' Folder path containing the Excel files
    FolderPath = "C:\YourFolderPath\"
    
    ' Start from the first file
    FileName = Dir(FolderPath & "*.xlsx")
    
    Do While FileName <> ""
        ' Open each file
        Set Wkb = Workbooks.Open(FolderPath & FileName)
        
        ' Loop through each sheet and copy content
        For Each Sheet In Wkb.Sheets
            Sheet.UsedRange.Copy
            Set PasteRange = ThisWorkbook.Sheets(1).Cells(Rows.Count, 1).End(xlUp).Offset(1, 0)
            PasteRange.PasteSpecial xlPasteValues
        Next Sheet
        
        ' Close the workbook
        Wkb.Close False
        ' Move to the next file
        FileName = Dir
    Loop
    
    MsgBox "Merge Complete"
End Sub