How to choose the best resume parser?

Today most of the companies invest a significant amount of time and money in finding software to track their hiring process. Applicant tracking system (ATS), human resources information management systems (HRIS/HRMS) are available to simplify recruitment process, but it works well only if parsed data can be inserted into them.

Staffing firms, job boards, recruiters, and enterprises receive a lot of applications each day. Their HR department needs to analyze applicants individually to reduce the cost of hiring and maintain accuracy. These companies pick data most of the time from website job portal, online job postings, old database, email applications, or referral sources. But these methods may result in inadequate data. Also, while filling data into online portals or job posting sites, most of the candidates quit before completing the form or not receiving updated resumes. Data process outsourcing can be a solution to review bulk resumes but, it increases cost and time per hire.

A resume parser is a solution to this problem. It acts as a mediator between the source of resumes and ATS/HRIS software. A good resume parser parses resumes, cover letters quickly and pushes into ATS/CRM or HRIS software automatically. 

While choosing the best resume parser, keep a few things in mind:

  • Accuracy: The parser should analyze common conventions for language syntax, addresses, places, phone numbers, case management, etc. It should identify relevant information from resumes of any format such as PDF, Doc, RTF, etc.
  • Multilingual: The CV parser should support major languages worldwide to parse.
  • Enrichment: Few of the resume parsing software are available with resume enrichment feature to help in updating resume database as per candidates’ social profile data even though the candidate is passive.
  • CV automation: It should be able to automate your recruitment process with a click approach.
  • Compatible: It should be compatible with your recruitment software such as ATS, Job boards, HRIS.
  • Speed: The parser should parse resumes quickly and efficiently.
  • Scalability: The architecture of the system should be expandable so that you can handle a large volume of resumes. It should be easily expandable in less investment to fulfill company’s demand.
  • Easy to integrate: The parser should be easy to integrate and maintained by your IT team along with keeping track of the daily record.

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