Resume Parser - What is it and how it works

Khushi Dholakia

• 8 min read
Resume Parser - What is it and how it works

Recruiters get a lot of resumes everyday. Every resume is different – formats, structures, lengths etc. It is very hard for recruiters to read them one at a time. A resume parser is a computer program that reads a resume and extracts relevant data and standardizes them into tables. Resume parsers are used in the recruitment industry widely to simplify the process of entering candidate data into Recruitment systems automatically. 

1. What is a resume parser?

A resume parser is a software tool that is designed to automatically extract and organize information from a resume or job application. The purpose of a resume parser is to make it easier for employers and recruiters to review and analyze job applications by extracting key information such as the applicant’s name, contact information, work experience, education, and skills.

Resume parsers are typically used by companies that receive a high volume of job applications, as they can save time and effort by automating the process of extracting and organizing this information. Some resume parsers are also able to identify certain keywords and phrases that are relevant to the job being applied for, and may use this information to help identify the most qualified candidates for a position.

Resume parsers can be integrated into an applicant tracking system (ATS), on Job boards or used as standalone tools. They are commonly used in the hiring process to streamline the review and selection of job candidates.

2. What are the benefits of using a resume parser for a recruiter?

A resume parser is a software tool that can automatically extract and structure information from a resume or CV (curriculum vitae) document. Some benefits of using a resume parser include:

Time-saving: A resume parser can quickly and accurately extract information from multiple resumes, saving time that would otherwise be spent manually reviewing and inputting data into excel sheets and ATSs /recruitment systems. 

Improved accuracy: A resume parser can accurately extract and structure information, reducing the risk of errors that can occur when data is entered manually.

Consistency: A resume parser can extract and structure information in a consistent format, ensuring that all data is organized and presented in the same way.

Enhanced searchability: A resume parser can extract key information from resumes, such as job titles, skills, and education, and store it in a structured format that can be easily searched and filtered.

Efficient recruitment process: A resume parser can streamline the recruitment process by automating the initial review of resumes and enabling recruiters to quickly identify and shortlist candidates who meet the required criteria.

Increased Application Rates: Job board application button can be automated using a parser. When a candidate uploads a resumes, they then get a prefilled form that is used for the application process after that. 

Overall, a resume parser can help organizations efficiently process large volumes of resumes and quickly identify and shortlist qualified candidates, improving the efficiency and effectiveness of the recruitment process.

3. How does a resume parser work? How can I use one?

To use a resume parser, you typically need to upload the resume or CV document to the parser tool, which will then analyze the document and extract the relevant information. The extracted information is usually organized into a structured format, such as a database record or a spreadsheet, and can be accessed and searched by recruiters or hiring managers.

APIs to ATS/ CRMs 

This would typically require that the parser and an ATS talk to each other. So when a resume is uploaded into the ATS, it would be sent to the Resume parser through  an API call. The parser would then return a JSON/ XML to the ATS with a structured format. This typically works on a licensing pricing model by volumes of resumes parsed.

Proprietary to recruitment systems/ ATS

Some of the leading ATSs have their own Resume Parser built into the software. They typically tend to pick up only the most important fields that are required by the recruiter to be autofilled(name, email, phone number) and typically tend to be less accurate and less detailed than stand alone parsers that work through APIs

Email Resume Parser 

Some recruitment systems have functionalities to forward resumes to specific email addresses for parsing or might have a workspace extension which might allow a user to mark an email attachment to be parsed. 

Tobu provides a way more advanced option for Email parsing where Tobu will automatically identify resumes from Emails without any user intervention. This will automatically identify and extract the candidate information from your email history as well as emails going forward.

Desktop Resume Parser

Tobu provides a Dropbox like feature where Tobu can automatically identify resumes from folders /sub-folders on the desktop and parse them into a database. This allows mass uploading of resumes at large scales across recruitment teams.  

Job Boards

Job boards use parsers when a candidate hits the apply button after searching for a job. When the candidate uploads the resumes, an application form is autofilled with all the details picked up including the Name, Email Phone number etc. This could also be combined with a chatbot in some cases to fill out the initial forms.

Career Pages

Similar to job boards, Career pages of companies also have an apply button which allows a candidate to upload a resume which is then parsed and is used to auto fill a form for the candidate during the application process. 

4. What does a Resume Parser Identify from a resume?

A resume parser is designed to extract and structure information from a resume or CV document. Depending on the specific capabilities of the parser tool, it may be able to identify a range of different types of information, including:

  • Contact information: name, address, phone number, email address
  • Personal details: date of birth, nationality, language skills
  • Work experience: job titles, companies, dates of employment, duties and responsibilities
  • Education: degree, institution, major, GPA (grade point average)
  • Skills: technical skills, software proficiency, certifications
  • Awards and achievements: professional accolades, publications, patents
  • Professional summary: a brief overview of the candidate’s experience and qualifications

Some resume parsers may also be able to identify additional types of information, such as specific skills or keywords related to the job the candidate is applying for.

5. What technologies are used in Resume Parsing?

Resume parsing technology typically uses a combination of natural language processing (NLP) and machine learning techniques to extract and structure information from resumes and CVs.

NLP is a field of artificial intelligence that deals with the interaction between computers and human languages. It involves using algorithms and machine learning models to process and analyze natural language text, such as resumes and CVs, and extract meaning from it.

Machine learning is a type of artificial intelligence that enables computers to learn and make decisions without being explicitly programmed. In the context of resume parsing, machine learning algorithms can be trained to recognize patterns and structure in resumes and CVs and use this information to extract and structure the relevant data.

Other technologies that may be used in resume parsing include:

  • Optical character recognition (OCR): This technology is used to convert scanned documents or images of text into machine-readable text. It can be useful for parsing resumes and CVs that are not in electronic format.
  • Data extraction: This technology is used to extract specific pieces of information, such as names and addresses, from unstructured or semi-structured text. It is often used in conjunction with NLP and machine learning techniques to extract more complex information from resumes and CVs.
  • Database management: Many resume parsers use a database to store the extracted information in a structured format. This can allow recruiters and hiring managers to search and filter the data to identify qualified candidates.

Overall, the technologies used in resume parsing are designed to enable computers to automatically extract and structure information from resumes and CVs, improving the efficiency and accuracy of the recruitment process.

6.  How much does a resume parser cost?

The cost of a resume parser can vary widely depending on the specific features and capabilities of the tool. Some resume parsers are available for free, while others can cost several hundred dollars or more per month.

Free resume parsers may have limited capabilities and may not be suitable for large-scale use or for extracting complex or specialized information. Paid resume parsers, on the other hand, may offer a wider range of features and may be more suitable for large organizations or for extracting more complex or specialized data.

Paid resume parsers typically are charged based on the volume of resumes parsed every month by end user.

In general, it is a good idea to carefully evaluate the features and capabilities of different resume parsers and consider your specific needs and budget before deciding on a particular tool. Some factors to consider when comparing the costs of different resume parsers may include:

  • The complexity of the information being extracted: Some resume parsers may be better suited to extracting simple, standard information, while others may be more capable of handling more complex or specialized data.
  • The volume of resumes being processed: If you expect to process a large volume of resumes, you may need a more powerful and scalable resume parser that can handle the workload.
  • The level of customization and integration: Some resume parsers may offer more customization options or may be more easily integrated with other systems and tools, which may be important considerations if you have specific needs or requirements.

7. Top ranked resume parsers

Tobu.ai:
Tobu.ai is a smart tool for reading resumes. It's good at understanding language and can be adjusted to fit what each recruiter needs. It can handle different languages, making it useful worldwide.

Why Tobu.ai? It's not just accurate, it's fast too. It goes through resumes quickly, so recruiters spend more time with potential hires and less time typing. It also works well with other recruitment tools.

Sovren:
Sovren is another tool for reading resumes. It's great at understanding the meaning behind words, not just looking for specific keywords. It can be adjusted to fit different situations in hiring. It also helps make sure everything is legal in the hiring process.

Advantages: Sovren is strong at reading complicated resumes. It works well for both small and big hiring teams. Once you get the hang of it, Sovren becomes a powerful tool in your hiring process.

Disadvantages: It might take a bit of time to learn how to use Sovren fully. But once you do, it's worth it because it can do a lot.

Daxtra:
Daxtra is good at searching for candidates with specific skills. It can understand different languages, and it works smoothly with other hiring tools.

Advantages: Daxtra can read lots of different parts of a resume. It's easy to use for recruiters with different levels of technical knowledge. It also works well with different hiring systems.

Disadvantages: While Daxtra is generally easy to use, setting it up might need some technical know-how. Recruiters might need a short practice to get the most out of it.

Rchilli:
Rchilli stands out because it looks at a person's social media along with their resume. Recruiters can adjust it to fit their needs, and it works well with different amounts of resumes.

Advantages: Rchilli is quick at pulling out information, so recruiters don't have to wait. It works well with different systems. It's a reliable choice for efficiency without giving up on making things just how you want.

Disadvantages: While Rchilli lets you adjust things, it might not have as many options as some other tools. If you want super customized parsing, some features might feel a bit limited.

Overall, it is important to carefully evaluate your specific needs and budget when choosing a resume parser and to carefully compare the costs and features of different tools to find the one that best meets your needs.

About Tobu.Ai

Tobu.ai is revolutionizing the way companies build their resume databases. As the world’s first email and desktop resume extractor, Tobu.ai automatically identifies and backs up all resumes from your emails and desktop, making it easy to create a searchable resume database for your organization. By linking Tobu.ai to your existing email account or downloading the desktop app, the software will scan, identify, and parse all resumes you currently possess into an internal searchable private database. With Tobu.ai, you no longer need to manually search for resumes or worry about losing track of important candidate information.