Due to specialized prompt engineering and direct integration with OpenAI's GPT-4, SquarePeg can turn your job description into specific candidate targeting criteria. This saves you valuable time and results in more specific targeting, ultimately leading to better-fitting and more qualified applicants.
SquarePeg sends your job description to GPT-4 to generate targeting criteria. However, the ability of the AI to understand which targeting criteria to select is due to specialized prompt engineering.
Engineering the prompt
A prompt takes advantage of natural language processing and allows anyone to easily direct an AI's response. If you've ever used chatGPT, then you've written a prompt. However, it's very difficult (if not impossible) to provide definitions of each criteria along with the large amount of structured data required to make each criteria selection inside the small text input for chatGPT.
SquarePeg is able to generate targeting criteria using AI thanks to direct integration with OpenAI's API, a large amount of structured data, and a very detailed explanation of each targeting criteria.
These detailed explanations cover key facets of candidate targeting, such as:
- Relevant companies (which companies hire for similar roles)
- Company funding (i.e. that fundraising is related to startup experience)
- Required experience (determining experience based on the job being described)
- Skills and industries (access to our matching algorithm skills and industries ontology)
The importance of targeting criteria
SquarePeg uses targeting criteria to source passive candidates through targeted email campaigns and to review and score applicants. Your targeting criteria ultimately determine the quality of candidates that SquarePeg is able to source for you.
Thoughts and feedback
Have feedback related to targeting criteria or ideas on how SquarePeg can enhance the talent acquisition process through AI? Please send an email to our product team or schedule a short call to chat about your ideas.