How Applicant Tracking Systems Actually Read Your Resume

When you apply for a job online, your resume usually goes into an applicant tracking system (ATS) before any person reads it. Workday, Greenhouse, Lever, iCIMS and Taleo are some of the most widely used. Knowing what these systems actually do, and what they don't, helps you spend your effort where it matters.

What an ATS actually does

An ATS is first and foremost a database for job applications. For each candidate it typically:

• Stores your resume file and the answers you typed into the application form.
• Parses the resume: extracts the text and tries to sort it into fields such as name, email, phone, job titles, employers, dates, education and skills.
• Lets recruiters search and filter all applicants, usually by keywords, job title, location or answers to screening questions.
• In some systems, ranks or scores applicants by how closely they match the job description.

The “75% of resumes are rejected by ATS” myth

You will often read that most resumes are automatically rejected by an ATS before a human sees them. That figure is repeated widely, but it isn't backed by solid evidence, and it doesn't match how most systems work. Most ATS platforms don't silently delete resumes because of a font or a column.

Applications usually drop out for more ordinary reasons: a “knockout” screening question (for example work authorisation, location or a required certification), or a recruiter searching for specific skills and your resume never coming up in the results. So the real goals are simple: make sure your resume is parsed correctly, and make sure it can be found.

How parsing works, and where it goes wrong

Parsing happens in two steps. First the system extracts the raw text from your file. Then it guesses which pieces of text belong to which field. Problems in either step can scramble your profile:

• Multi-column layouts and tables can make text come out in the wrong order, so a job title ends up next to the wrong employer or dates.
• Text boxes, headers and footers are sometimes skipped entirely. If your name or phone number lives in the header, it may not be captured.
• Anything inside an image can't be read: a scanned PDF, a photo of your resume, skill-level bars, or icons used instead of words.
• Unusual section headings such as “My Journey” or “Where I've Been” make it harder to recognise your work history.
• Inconsistent or creative date formats can break the calculation of how many years of experience you have.

What parses reliably

• A single-column layout that reads top to bottom.
• Standard section headings: Summary, Experience, Education, Skills, Projects, Certifications.
• Contact details as plain text in the body of the page, not in the header.
• Consistent dates, such as “Mar 2022 – Present” throughout.
• Simple bullet points and standard fonts.
• A PDF with selectable text, or a DOCX file. Always follow the format the job posting asks for.

How recruiters search the database

Once applications are in the system, recruiters search them much like you would search a website, often with exact keywords or Boolean queries such as “React AND TypeScript”. That has a few practical consequences:

• Exact wording matters. If the posting says “project management”, include that phrase rather than only a synonym.
• Write acronyms both ways the first time: “Search Engine Optimization (SEO)”.
• Mention important skills inside your experience bullets, not only in a skills list. It reads as real experience to the person who opens your resume afterwards.

The bottom line

You don't need to “beat” an ATS. You need a resume that a machine can parse cleanly and that uses the same language as the jobs you want, so that a recruiter searching for those skills finds you. After that, the resume still has to convince a human, which is where clear, specific, achievement-focused writing makes the difference.