Glossary
A plain-language definition from the Curriculo hiring glossary.
Resume parsing is the automatic extraction of details from a resume, such as titles, dates, skills, and education, into fields a system can search.
Why it matters
Parsing is the first step in almost every applicant tracking system. Screening, search, and ranking all work on the parsed data, not the original file. If the parser reads a resume badly, a strong candidate can look weak or vanish from search results before anyone sees them.
How it works
- The system reads the file, often a PDF or Word document.
- It pulls out the text and works out the layout, such as sections and columns.
- It labels each piece: this line is a job title, this date range belongs to that job, this list is skills.
- It saves the results as fields on the candidate's record.
A short example
A resume shows Senior Analyst, Acme Corp, 2021 to 2024. A good parser saves the title as Senior Analyst, the employer as Acme Corp, and a start and end year. A weak parser might merge the line into one field, so a search for analyst roles at Acme misses it.
Common mistakes
- For employers: trusting parsed fields without checking a sample of original resumes.
- For employers: rejecting candidates because a parsed field is empty, when the data is in the file.
- For candidates: putting key details in images, text boxes, headers, or footers that parsers often skip.
- For candidates: using complex tables or multiple columns that scramble the reading order.
What to look for in a parser
Test it with your own resumes. Include a two-column layout, a scanned PDF, and one in another language if you hire abroad. Check that dates, titles, and employers land in the right fields.
Read how an ATS works from parsing to ranking, see why candidates vanish at the parsing layer, and learn how candidate import brings resumes in.