Optimisation only means something relative to a target. A resume is not 'optimised' in the abstract — it is optimised for the Senior Data Analyst role at a particular company, whose posting emphasises SQL, dbt, stakeholder communication and healthcare data, and mentions Python once.
So this tool does not grade your resume in isolation. It compares one resume against one posting and tells you the difference between them.
Six sub-scores, because 'match' is not one thing
Splitting them apart is the point. A 68 overall means something very different when it is caused by keyword coverage than when it is caused by four years against a seven-year requirement — the first is an afternoon's editing, the second is not.
- ATS compatibility — will this file parse cleanly, independent of content fit
- Skills match — required and preferred skills from the posting, checked against your listed skills and evidenced experience
- Experience match — years of experience against the stated requirement, plus job-title relevance
- Keyword match — coverage of the posting's ranked critical and important terms
- Education match — degree level and field against stated requirements, adjusted for missing certifications
- Responsibility match — how many of the posting's listed responsibilities have real supporting evidence in your bullets
What you get back
- Matched keywords — what you already cover, so you do not over-correct
- Missing keywords — ranked by how heavily the posting emphasises each one
- Important requirements — each responsibility marked covered or not, with the line from your resume that covers it
- Potential gaps — graded high, medium or low, with an honest note on whether it is fixable by editing
- Recommended changes — ordered by impact, each with what to do and why it matters
Optimising honestly
The missing-keyword list is a prompt, not an instruction. If the posting wants Kubernetes and you have never touched it, adding 'Kubernetes' to your skills section is how you fail a technical screen and burn a relationship with a recruiter.
The useful case is the common one: you have done the work but described it in different words. You built dashboards; they said 'data visualisation'. You ran the month-end close; they said 'financial reporting'. Those gaps are real, they cost you real matches, and closing them is legitimate.
For the genuine gaps, the tool says so plainly and suggests where to address them — a cover letter sentence, a course, or a decision that this role is a stretch worth making explicitly rather than accidentally.
AI tailoring
On Pro, one click generates a tailored version of the resume: the same verified facts, reprioritised and rephrased for this posting. The most relevant roles and achievements move up, bullets adopt the posting's vocabulary where it truthfully applies, and the summary is rewritten toward the target title.
It is saved as a new version linked to that job description, so your base resume is untouched and you always know which document went to which company.
Frequently asked questions
- What is a good job match score?
- Above 80, apply — you cover the requirements and your remaining work is polish. 60–80 is the normal range for a reasonable fit before tailoring, and tailoring typically moves it 10–20 points. Below 60, read the gaps carefully; sometimes it is keywords, sometimes the role genuinely is not a fit.
- Should I tailor my resume for every application?
- For roles you actually want, yes — and it is the single highest-return activity in a job search. The whole point of keeping one master profile is that tailoring takes minutes instead of an hour.
- Will adding missing keywords guarantee an interview?
- No. Keyword coverage gets you found and shortlisted; it does not decide the hire. It also cannot compensate for a genuine experience gap, and pretending otherwise costs you at the screening call.
- Is keyword stuffing detectable?
- Yes, by both parsers and people. Hidden white text is a known trick and is checked for. A skills section listing thirty technologies with no supporting bullets reads as noise to any experienced recruiter.
- How many keywords does the analyzer extract?
- Up to 40 matchable terms per posting, ranked critical, important or supporting by frequency and position, combined with explicitly extracted skills, tools and certifications.