How to extract keywords from Greenhouse Job Applications using generative AI
How to Extract Keywords from Greenhouse Job Applications using Generative AI
As a recruiter, you receive hundreds of job applications for each open position. It can be overwhelming to manually review each application and identify the most important information. That’s where keyword extraction comes in. In this post, we’ll show you how to use generative AI to automatically extract keywords from job applications in Greenhouse, a popular recruiting software.
What is Keyword Extraction?
Keyword extraction is a natural language processing (NLP) technique that involves identifying the most important or relevant words or phrases in a piece of text. You can use it to extract key information and themes from text has many applications, such as search engine optimization (SEO), content analysis, and topic modeling.
Keyword extraction can be performed manually, but it can also be automated using machine learning algorithms. These algorithms learn to recognize patterns and features in the text that are associated with important words or phrases, and can be trained on a labeled dataset of text.
You can use keyword extraction to analyze and summarize large amounts of text data to quickly identify the most important information and themes.
Example Use Cases
Use cases for extracting keywords from Greenhouse job applications include:
- Categorizing and prioritizing job applications
- Identifying top skills and qualifications of applicants
- Identifying common themes and trends in applicant resumes
- Improving efficiency and speed of applicant review process
- Tracking diversity and inclusion metrics in applicant pool
Teams that might find these use cases helpful include: recruiting, HR, talent acquisition, and diversity and inclusion.
Finding your input data and identifying preliminary keywords
You first need to identify the data that you want to work with. Here, we are looking at job applications in Greenhouse. You can extract this data using the Greenhouse API, export it in CSV format, query a list of applications from your data warehouse or BI tool, or copy and paste with an example application.
For more information on the Greenhouse API see here: https://developers.greenhouse.io/harvest.html
Next, it can be helpful (but not necessary) to identify common keywords that you may want to extract from job applications. Generative AI tools can be used to both identify and measure frequency of keywords but also to suggest additional keywords you may not have been aware to look for. For example - you might find that recurring skills and qualifications of top-performing employees may differ from what you originally thought.
Once you have your data and preliminary keywords identified, you can use generative AI to automatically extract the most important keywords from job applications in Greenhouse. This will help you quickly identify top candidates and improve the efficiency of your recruiting process. This can help you both reduce time to hire and improve the quality of your hires.