An HR team might receive approx. 50–55 resumes daily. This means that an enterprise will receive 18,000 resumes in a year. Now, segregating each resume as per the requirements, skills, and qualifications may take copious time, hence recruiters opt for AI powered resume parser online. But, which one is the best?
To reduce the substantial time and effort required, today’s businesses are constantly searching for the finest resume-parsing software solution to automate these tedious tasks. One such tool that makes recruiting easier is a resume parser. Thus, everything you need to know about online resume parsers and factors to take into account while selecting the finest resume parser for your company will be covered in this post.
Not only do big businesses receive a lot of resumes every day, but so do staffing companies, consultancies, and recruitment agencies. The majority of this data comes from emails, referrals, online job postings, and employment portal websites. To make the hiring process simpler, you would require one of the various applicant tracking systems (ATS) and HRMS available, most of which are cloud-based. However, the procedure doesn’t become easy until all of the data is correctly entered into the ATS. This is where the resume parser tools are useful. It serves as a go-between to resolve this conflict.
What is a resume parser and what is its importance?
The process of turning resumes and CVs into a readily obtainable set of data that can be correctly analyzed and evaluated is known as resume parsing. Recruiters may handle digital resumes more effectively using this strategy, which also saves a substantial amount of labor and time, which lowers overhead expenses. These days, the material can be converted to a more understandable format with the help of automated resume-parsing tools and software. They also make it possible to archive and store documents for later use.
The top companies drive the best talent, which makes them different in this competitive environment. As per the Recruiter Sentiment Study by the MRI Network, 63% of recruiters say talent shortages are the biggest problem. Therefore, when you identify the right candidate, quickly get them on your list; otherwise, you will be at risk of losing them.
The foremost benefit of resume parsing tools is that they save human efforts, allowing the HR team to work on essential business and recruitment activities. The other benefits of using resume-parsing software are:
- Streamline and sort applications for effective candidate screening so that the best applicants rise to the top. Thus making optimal use of the interviewer’s and other stakeholders’ time.
- An online resume parser uses machine learning technology and can effectively analyze trends and rules set by the recruiter, thus saving HR and stakeholders time.
- Resume parser tools are rule-based, thus reducing the risk of errors. This not only improves the recruiter’s efficiency but also enhances the candidate acceptance ratio and boosts the company’s brand name.
- Human resources information systems (HRIS), applicant tracking systems (ATS), and other HR or recruitment software can all be easily integrated and operated with resume parsing tools. Duplicate data entry and manual data transmission are less necessary when systems are integrated and can communicate with one another.
Application tracking software, or ATS resume parser, is a group of procedures and instruments designed to enhance the hiring process from start to finish. The best applicant tracking systems have realized that the first step in the hiring process is having an effective resume parser.
Types of Resume Parsers
There are multiple resume parsers in the market, hence, these hiring tools are divided into 5 broad categories:
Cloud-based Resume Parser
A cloud-based resume parser is an application that is located on cloud servers that automatically extracts and analyzes data from resumes. These parsers correctly scan and arrange data from different resume formats into structured information using artificial intelligence (AI) and machine learning. By saving time and lowering manual data input errors, this can significantly improve the CV praising, resulting in increasing the effectiveness of HR and recruitment procedures.
Rule-based resume parser
This type of resume parser relies on predefined rules and patterns for resume extraction. These guidelines are usually based on the format and structuring that are frequently seen in resumes, including the sections on talents, education, work experience, and contact information. They are adaptable and can be made to fit particular resume forms. When it comes to typical resume templates, they are usually accurate.
Resume parsing (machine learning)
Machine learning analyzes resumes through algorithms and categorizes them based on different parameters like skill, experience, and more. Training data is used to improve their accuracy over time. Machine-learning resume parsing can handle a wide variety of resume formats, including non-standard layouts.
Industry-specific resume parser
These types of resume parsers are designed specifically to tailor to the needs of specific industries. These parsers can comprehend terms, credentials, and certifications relevant to that industry. They can effectively compute the suitability of the candidate for that specific role, which is peculiar to their sector.
Statistical resume parser
This program examines the syntax and grammatical structure of sentences to derive relevant details about the experiences and histories of candidates, as opposed to only matching keywords. By using linguistic criteria to comprehend the text, it can capture more complex data than just keyword matching.
Step-by-step Guide To Choosing the Best Resume Parser Online
The online resume parser offers unique importance in the recruitment process. You must choose the right resume parser for your business because there are several things that you must consider while choosing a resume parser for your startup, SMB, MSME, or recruitment agency.
Effectiveness
Any quantity of resumes should be efficiently parsed by the resume parser within a shorter amount of time. It should swiftly evaluate the candidate’s location, phone number, and other crucial information.
Time-saving
To save time and money, we are utilizing a compiler. So, it ought to perform that task flawlessly. Ideally, a resume parser should be fast enough to process several resumes in a matter of seconds.
Scalable
Your company may expand faster than you anticipated. Selecting any software that can effectively grow with your startup is crucial. You should also take into account the possibility that the hiring team will receive 3 resumes on one day and 3000 resumes on another. Choose a resume parser online that can handle these two scenarios effectively.
Adaptable or Customizable
The resume parser’s primary task is to convert inputs from human-readable (Doc, PDF) forms to machine-readable (XML or JSON) formats. In both situations, there are numerous other formats besides these. A resume parser of the perfect design should accept inputs and produce outputs in a variety of forms. Additionally, the software must provide the user with the benefit of customization to their needs.
Multiple Language Support
The CV-praising tools must support major languages worldwide. It can seamlessly scrutinize and automate time-consuming tasks in different languages and extract data from CVs.
Library of Taxonomies
Can the software distinguish between different iterations of the same business name or between abbreviations for a course or degree? To guarantee that the most recent businesses are added to the list and that resumes in various word formats are automatically taken into consideration and shortlisted, the library must be extensive and updated regularly.
Accurate and Impartial
In the current context, openness and diversity are receiving more attention. Can the software’s algorithm be objectively based on factors like physical limits, color, nationality, religion, ethnicity, or any other factor? Is it possible to disable specific fields to reduce prejudice and select resumes solely on merit?
Resume Parser API Integration
If you could link your resume parser with your current ATS or HRMS that you are using, it would make things easier. So that you don’t have to download the output and submit it to your automated transfer station (ATS).
Simple to Utilize
Above all, regardless of the features, the user or customer should be able to comprehend and utilize them with ease.
Compatible with ATS
The free resume parser you choose should be able to provide results that work with the ATS or HRMS you currently have.
How does an online resume parser work?
The resume parser online works in this manner:
Input Data:
The resume parser starts working when a resume or CV is submitted for parsing. These CVs can be in different formats, like Word documents, PDFs, plain text, or even scanned images.
Extraction of Text:
The automated resume parser software must extract the textual content from the documents, despite their format. Here, optical character recognition is used for scanned documents to convert images into texts.
Segmentation
The resume parser software divides the text into distinct sections like contact information, work experience, education, skills, and others. All these sections are identified using common patterns and formatting cues found in resumes.
Identification of Data Fields
The software locates and extracts particular data fields inside each segment. As an illustration:
- Name, address, phone number, email address, and so on are the contact details.
- Work Experience: Job descriptions, job titles, dates of employment, firm names, etc.
- Education: A student’s degree, the colleges they attended, when they graduated, etc.
- Technical know-how, linguistic proficiency, credentials, etc.
Standardized
To ensure consistency, the extracted data is normalized. This means the date format is changed into a standard format like (e.g., DD/MM/YY), categorizing skills, and standardizing job titles.
Matching Keywords
Many resume analysis software allows for keyword matching. Here, the recruiters can define specific keywords or phrases that relate to the job specification. The resume parser identifies and highlights those resumes that contain those keywords, making it easier for the recruiter to analyze.
Database Storage
An applicant tracking system (ATS) or HR software may immediately integrate the parsed and categorized data, or it may be stored in a structured database. An information repository for candidates is provided by this database.
ATS Integration
ATS is a prevalent practice that facilitates the smooth integration of parsed data into an organization’s recruitment cycle. Within the ATS, recruiters may quickly access and manage candidate profiles.
User Interface
A user-friendly interface provides recruiters and HR specialists with access to the parsed candidate data. Candidate profiles can be found, filtered, and sorted using this interface by using predefined criteria.
Customization
Systems for parsing resumes can frequently be adjusted to meet the particular requirements of a company. Recruiters can specify keyword lists, data fields, and classification criteria based on their hiring needs.
Explore HireLakeAI: An Effective Resume Parser Software
The modern industries in the recruitment market are realizing the need for effective hiring tools and technology. The industry understands that becoming tech-driven is necessary in this competitive landscape.
For new-age hiring, AI-based resume parsing tools like HireLakeAI will simplify your hiring process as they can screen, evaluate, and filter out the best candidates as per your requirements using three parameters- technical skills, communication skills, and personality traits. Along with it, HireLakeAI can extract information from documents and videos, and then filter the candidate’s important information into a detailed report.
Apart from matching job descriptions with resumes, the HireLakeAI resume parser tool can predict job acceptance by the candidate. The seamless API integration can help you collect, process, and share data, allowing the HR team to get assistance at each stage of recruitment. These are just some of the amazing benefits of using HireLakeAI.
Book a free demo now to integrate HireLakeAI to ease your recruitment process.
Conclusion
Organizations may maximize resume parsing by selecting the appropriate parsing software, personalizing parsing rules, keeping up with industry developments, and placing a high value on data privacy and accuracy. Organizations may find and hire the most qualified individuals more quickly by incorporating resume parsing into their recruitment procedures. This will ultimately result in best-fit hiring decisions and a more productive workforce.
If you are a modern or a traditional recruiter looking for innovation, then HireLakeAI is for you. It’s easy to use and integrates with your current ATS system. So rather than holding back, take a step forward and address your recruitment challenges with impactful results.