An Applicant Tracking System is, underneath the recruiter-facing dashboard, a document parser attached to a database. When you submit a resume, the system doesn't "read" it the way a person does — it runs the file through a parsing engine that tries to extract specific fields (name, contact info, work history, education, skills) and slot them into a structured record. Everything downstream — search, filtering, ranking — operates on that structured record, not on the original document.
The extraction step, concretely
Most ATS parsers work by reading the document's raw text stream in the order it's encoded, then applying pattern matching and layout heuristics to guess which text belongs to which field. A single-column resume with clear section headers gives the parser an easy job: text flows top to bottom, left to right, exactly as a human would read it, and a header like "Experience" is a strong, well-known signal for where a work-history block starts.
A multi-column resume breaks this assumption. Many parsers extract text in the order it appears in the underlying file structure, not the order it's visually laid out — so a two-column resume can come out with the left column's first line, then the right column's first line, then the left column's second line, interleaved into something unrecognizable. This isn't every parser, and some modern systems handle columns correctly — but since you can't know which parser a given employer uses, a single-column layout removes the risk entirely.
What gets extracted well
- —Plain text in a linear, single-column layout
- —Standard section headers: Experience, Education, Skills, Summary
- —Dates in a consistent, unambiguous format
- —Contact information placed in the main body, not a header or footer some parsers skip
What gets extracted poorly or not at all
- —Text embedded inside an image, icon, or graphic — there's no text to extract
- —Tables used for page layout, which most parsers read column-first, scrambling row order
- —Non-standard section headers — a parser trained on common resume structures may not recognize a creatively titled section as 'Experience'
- —Text boxes and floating elements, which some parsing engines skip entirely
Why this matters more than keyword density
A resume that parses cleanly but has weaker keyword coverage still shows up in a recruiter's search — just lower in the ranking. A resume that fails to parse can lose entire sections outright: if your most recent job title lands in the wrong field, or your skills list doesn't get extracted as a skills list, that information effectively doesn't exist to anyone searching or filtering candidates by it. Structure is the precondition; keywords are the optimization on top of it.
How to check your own resume against this
The fastest way to know where you stand is to run the actual extraction, not guess at it. Career Copilot's free ATS checker parses your resume the way these systems do and shows you which sections it found, which it didn't, and what to fix — in under a minute, no signup required.