What is natural language processing (NLP)?

NLP is a machine learning technology that makes software capable of understanding and interpreting human language. With NLP, software can understand written text and speech, creating opportunities for businesses to streamline manual processes and replace them with automated ones. For example, NLP helps businesses:

• Analyze customer survey results
• “Talk” to customers and vendors via chatbots
• Parse lengthy documents and summarize the contents
• Classify text according to established parameters
• Answer simple questions

Why is NLP so helpful for HR professionals?

NLP can have applications in every industry, but it’s especially helpful for HR professionals. A typical HR department may receive hundreds or even thousands of documents per week, from job applications to salary survey results. Even with a team of skilled professionals, it’s difficult to analyze all those documents in a timely manner.

With natural language processing, however, it’s possible to analyze vast quantities of data in less time than ever before. Instead of analyzing every document themselves, HR pros can have trained computers do it for them, leaving more time for other activities.

For example, a busy benefits administrator can have a tool review documents to determine how many employees signed up for health insurance or took advantage of the employee assistance plan.

4 ways to use natural language processing in recruitment

Any HR professional can benefit from using NLP, but natural language processing is a big help to recruiters. Whether you’re an experienced recruiter or a department manager, you know that recruiting activities generate a steady stream of information from applicants.

You have to sort through resumes, job applications, background check results, reference forms and other data to learn as much as you can about each individual. On top of these responsibilities, you may also have to conduct phone screenings, schedule interviews or administer pre-employment tests.

If you’re too busy to review documents, you may not be able to fill each opening as quickly as you’d like. Fortunately, there are many ways to use NLP in recruitment. Here are just a few ideas to get you started.

1. Match resume data with current openings

One of the easiest ways to use NLP in recruiting is to match resume data with current job openings. With a resume parser, it’s possible to extract several types of information from a document, such as the applicant’s educational background or how many years of experience they have in your industry.

In the past, recruiters had to review resumes manually and use scoring rubrics to decide if an applicant met the minimum requirements for the job. NLP makes it possible to review thousands of resumes in a short amount of time and determine if any of your current applicants have what it takes to fill one or more openings.

2. Create candidate profiles 

Before you advertise a job, you need to think carefully about the ideal candidate. What skills does the job require? How many years of experience are necessary to do the job successfully?

NLP makes it possible for computers to analyze job descriptions, advertisements and other inputs to determine the minimum qualifications required for a particular job. If you use NLP for this task, you’ll have more time to build relationships with applicants and identify ways to turn your company into an employer of choice.

3. Answer simple applicant questions

With NLP, it’s possible to create a chatbot capable of answering common questions, such as inquiries regarding the hiring process or clarifications to your company’s policies and procedures.

For example, if an applicant wants to know where to send their resume, the chatbot can provide an email address — all without any input from you or your colleagues. A chatbot may even be able to answer questions about job openings and screening requirements, freeing up even more time.

4. Personalize messages to applicants

One way to increase applicant engagement and make a positive impression is to use NLP to deliver customized messages. If you decide to reject an applicant after using NLP to parse their resume, the software can even use information from that resume to craft a custom rejection letter.