A single job post, on average, gets about 250 applications. 

And if you’re hiring for multiple jobs, thinking about the sheer volume of applications can be overwhelming. 

This is often where resume parsing software comes into play, streamlining the recruitment process, and saving time and resources- but only when done right. 

Whether you're new to resume parsing or looking to refine your existing approach, we’ve laid out some best practices to help you use the software to its fullest potential. 

Read on! 

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6 Best practices to use Resume Parsing Software 

Here are some best practices to use resume parsing software to your advantage:

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1. Choose the Right Software

‍Basics- but crucial. The foundation of successful resume parsing implementation lies in selecting the right software for your organization's needs. 

With so many options available in the market, it's essential to choose a solution that aligns with your specific requirements and integrates seamlessly with your existing recruitment tools.

When evaluating resume parsing software, consider the following key factors:

a) Accuracy: Look for software that boasts at least 90% accuracy in parsing resumes. Higher precision ensures that you're working with reliable data throughout your recruitment process.

b) Integration capabilities: The software should integrate smoothly with your other automation tools, particularly your Applicant Tracking System (ATS). This integration allows for a more cohesive and efficient workflow.

c) Time-saving potential: Assess how much time the software can save in your current process. The right solution should significantly reduce the time spent on manual data entry and resume screening.

d) Multilingual support: If your organization operates globally or receives applications in multiple languages, choose a parser that can handle various languages accurately.

e) Context understanding and format support: The software should be able to understand the context and support different resume formats (e.g., PDF, DOCX, HTML) to ensure comprehensive parsing capabilities.

f) Data security: Given the sensitive nature of candidate information, prioritize software that offers robust data security measures to protect both your organization and your applicants.

By carefully considering these factors, you can select a resume parsing solution that not only meets your current needs but also scales with your organization's growth.

So which tool ticks all these essential features required for effective parsing?
We have an answer for you! Recrew!

Recrew offers a comprehensive suite of API-based solutions designed to transform the way you hire, making your process faster, more efficient, and more accurate.
Powered by cutting-edge AI technology, Recrew leverages the capabilities of large language models (LLMs) to deliver unmatched precision in resume parsing, job description (JD) parsing, candidate search, and recommendation systems. 

Our AI parser goes beyond traditional keyword matching—it understands context, interprets complex language structures, and extracts the most relevant information from resumes, ensuring you never miss out on top talent.

Check out Recrew here!

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2. Use it for Efficient Data Entry and Formatting

Resumes come in various formats. Rather than juggle manually within a sea of . DOCX and PDF files, use parsing software to streamline data entry and standardize formatting. 

Here’s our to-do list for formatting and data entry:

• Choose standard formats: Parse resumes into a standardized format, making it easier to compare candidates and store information uniformly in your ATS or database.

• Automate: Automate the extraction of key information such as contact details, work history, education, and skills, significantly reducing manual data entry time.

• Allow multiple formats: Handle multiple file formats (e.g., PDF, DOCX, TXT) without requiring applicants to submit in a specific format, improving the candidate experience.

• Categorize: Automatically categorize parsed information into relevant fields, making it easier to search and filter candidates later in the process.

The time-saving aspect cannot be overstated in this case. By automating the extraction of key information such as contact details, work history, education, and skills, you're significantly reducing manual data entry time. 

After all, the point is to let the software extract key info while you focus on what really matters - finding the right candidate.

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3. Define the Right Data Fields

Defining the right data fields ensures that you're capturing the most relevant information for each job posting and your overall recruitment needs.

Consider these best practices when defining your data fields:

a) Analyze job requirements: Review your typical job postings and identify the key information you need to evaluate candidates effectively.

b) Customize fields: Configure your parsing software to extract specific data points that align with your evaluation criteria. Common fields include:

• Contact information

• Work experience (including job titles, companies, dates, and responsibilities)

• Education (degrees, institutions, graduation dates)

• Skills and certifications

• Projects and achievements

c) Include industry-specific fields: Depending on your sector, you may need to parse for particular qualifications, licenses, or technical skills.

d) Balance detail and relevance: While it's tempting to extract every possible data point, focus on the information that's most critical for your decision-making process.

And as a bonus tip, periodically review your defined fields to ensure they remain relevant to your evolving recruitment needs.

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4. Use it to Compare Candidates

Resume parsing software excels at standardizing information, which is a great foundation for comparing candidates more easily. 

To do so, start by creating standardized profiles. These uniform profiles ensure you're comparing apples to apples across all applicants.

As the second step, consider developing scoring systems based on parsed data points such as years of experience, relevant skills, or education level. 

You can also automate initial screening by setting up automatic filters based on parsed data to quickly identify candidates who meet minimum qualifications. This initial screening can save you hours of manual review time.

You can then use the parsed data to create easy-to-read comparison charts or matrices for hiring teams to review multiple candidates simultaneously. This way you also reduce any unconscious biases such as resume aesthetics or formatting that might influence manual resume reviews.

Your team can also use parsed data to track key recruitment metrics (e.g., time-to-hire, source of hire) and analyze trends and improve your overall hiring process.

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5. Integrate it with ATS

While many Applicant Tracking Systems (ATS) offer basic resume parsing capabilities, integrating a standalone, specialized resume parsing software with your ATS can significantly enhance your recruitment process. 

Here's how to effectively implement this integration:

a) Choose compatible systems: Ensure that your chosen resume parsing software is compatible with your ATS. Look for pre-built integrations or APIs that allow for seamless data transfer.

b) Map data fields: Align the fields in your resume parsing software with those in your ATS to ensure accurate data population.

c) Automate the workflow: Set up your integration to automatically parse resumes as they're submitted and populate the relevant fields in your ATS.

d) Enhance search capabilities: Use the detailed, structured data from your parser to improve the search and filter functions within your ATS.

e) Maintain data integrity: Regularly audit the parsed data in your ATS to ensure accuracy and consistency.

This way, you'll create a more efficient, accurate, and powerful recruitment system that streamlines your hiring process and improves overall outcomes.

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6. Update the Parsing Algorithm

Like a good chef keeps their knives sharp, a good recruiter keeps their parsing algorithm updated. 

Regular training is crucial, as it helps your algorithm stay updated with current resume trends. To do so, continuously feed your parsing software with new data to keep it updated on emerging resume formats, industry-specific terminology, and changing qualification standards.

Additionally, establish a feedback loop. Let your recruiters and hiring managers weigh in on the parsing accuracy. Their insights can help identify areas for improvement and ensure the parsed data meets their needs.

Lastly, don't forget about industry-specific updates. Train your algorithm to recognize and accurately parse industry-specific jargon, certifications, and qualifications relevant to your field. What's important in tech might be irrelevant in healthcare, and vice versa.

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The Future of Hiring: Parsed and Present

Implementing these best practices for resume parsing isn't just about making your life easier (although that's a nice bonus). 

It's about creating a more efficient, accurate, and fair hiring process. By standardizing data, reducing bias, and freeing up time for meaningful candidate interactions, you're not just parsing resumes - you're paving the way for better hiring decisions.

Recrew makes resume parsing that much easier for you, so you have a lot of time for the other tasks that demand human intervention and attention, like interviewing potential hires.

Remember, the goal isn't to remove the human element from hiring. Rather, it's to enhance our human capabilities with powerful tools. 

With these best practices in your toolkit, you're well-equipped to use your resume-parsing software to focus on what really matters: finding the right person for the job.