Resume score explained

No applicant tracking system publishes a per-resume score you can look up. Workday, Greenhouse, Taleo and iCIMS parse your file into structured fields, then let the employer filter and rank on criteria they choose. A resume score is therefore an estimate built from two measurable things: how cleanly your document parses, and how well its content lines up with one specific job description.

Parseability is structural and mostly objective. It is checked with rules rather than opinions, which is why it is the part of your score you can reliably push high.

• Single-column layout — multi-column resumes get read out of order, mixing dates into the wrong role.
• Contact details as plain text near the top, not inside a header, text box, or graphic.
• Standard section headings such as Professional Summary, Skills, Experience, Education — invented headings can be dropped entirely.
• Selectable text, not a scanned image. If you cannot highlight a word in your PDF, the parser sees nothing.
• Consistent, complete dates in one format, with months included.
• No tables, icons, progress bars, or decorative symbols carrying meaning.

Job match compares your resume against one posting. It is contextual, so it moves every time you target a different role — and a single number across all applications is meaningless.

• Coverage of the requirements the posting actually emphasises, weighted toward your summary and first bullets.
• Evidence, not lists: a skill named in a Skills section but never demonstrated in an accomplishment reads as thin.
• The employer's own wording for skills you genuinely have, including both the acronym and the spelled-out form.
• Title alignment between your recent roles and the target role's language.
• Verifiable metrics — scope, volume, time saved, revenue — in place of vague adjectives.
• Trajectory: unexplained gaps and repeated lateral moves invite questions a recruiter reads before your bullets.

Read them as a diagnosis, not a grade. The combination points at a different next action each time.

• High parseability, low job match — the file is fine; tailor the content to this posting and add evidence for the skills it asks for.
• Low parseability, high job match — you are a good fit that software may never surface. Rebuild the layout as plain single-column text first.
• Both low — start with formatting, because the content changes you make afterwards will finally be visible.
• Both high — stop optimising and apply. Further tuning has diminishing returns versus sending more applications.

Every real gain comes from one of three places: fixing structure, using accurate language the employer already uses, or surfacing achievements you have not written down yet. Adding keywords for skills you do not have fails at the interview, and hidden white text keyword stuffing is detected as duplicate or invisible content.

PlotMyCareer only rewrites what you confirm. It flags a missing metric and asks you for the number instead of inventing one, and it will not add a skill you have not verified.

Upload a resume and paste the job description you are targeting. You get a rule-based parseability breakdown, a job-match report with matched and missing requirements, and a list of the specific fixes worth making.