ATS & filters · 2026-08-15 · 14 min read

CV mistakes that get you rejected by ATS

The most common résumé mistakes that cause ATS filters to discard or ignore your application — and how to fix them with before/after examples.

Many candidates lose opportunities not because of weak experience, but because the ATS cannot understand the file. The system tries to turn your CV into fields: name, email, roles, dates, skills. When the format is hostile, those fields stay empty or wrong. Recruiters see an incomplete profile, or ranking drops you before a human reads.

This guide lists the mistakes that discard résumés most often in practice, with clear symptoms, fixes, and before/after examples. The tone is career coach plus SEO editor: concrete, no white-text hacks, no magic promises. The goal is zero friction: real text, standard sections, and evidence aligned with the posting.

For the full method (structure, parseable PDF, and keywords), read how to make a CV for ATS filters. This page focuses on what knocks you out of the process.

ClarCV helps when you already have a PDF or Word file and want a fast diagnosis: upload, get AI notes on clarity and structure, then regenerate a clean ATS-friendly version. Start free; Pro is €7/month with clear pricing. Spanish and English depending on the application.

1. Unreadable formats (image PDF, scan, broken Canva export)

Symptom: you cannot select text in the PDF; paste into Notepad is empty or garbage. Cause: the file is an image, a scan, or an export where fonts became drawings. The ATS sees a picture, not words. Fix: generate the CV from an editor that exports real text (clean Word, Google Docs, or HTML/PDF templates like ClarCV). Never photograph a printed résumé.

Before: PDF exported from a slide deck with backgrounds and outlined text. After: same content in a vertical flow with standard fonts and selectable text. Gold test: select three paragraphs in different zones and paste into plain text. If it fails, do not send.

2. Creative or opaque section names

Parsers look for predictable labels: Experience, Education, Skills, Languages, Contact. If you call experience My journey, Battles won, or What I have built, the block may not classify. Same problem when skills hide under Superpowers.

• Use standard headings even if the design feels modern.
• Be creative in bullets, not in section titles.
• Avoid mixing two languages in section headings.
• Do not hide the email only in a footer or an icon.

Before: Trajectory and vibes plus icon-only skills. After: Work experience plus bullets with verbs and tools. Recruiters still see personality in the content; the ATS finds the right block.

3. Columns, tables, and text boxes that scramble order

Two-column templates look polished on screen, but many parsers read top-to-bottom and left-to-right awkwardly: they may join a left-column date with a right-column title, or index skills before your name. Merged tables and floating text boxes make the mess worse.

They do not always fail, but they raise risk. If ATS is the priority, use one main column. If you need two, keep contact and experience in a clear linear flow and avoid putting critical data only in the sidebar. Text skill lists beat level bars.

4. Ambiguous dates or roles without employers

The ATS tries to compute years of experience. Writing 2020–present without months when roles overlap, or various freelance projects 2019–2024 without breakdown, breaks the math. Worse: listing a title with no company. The parser cannot attach the role to an entity.

Before: Product Owner | 2021–now. After: Product Owner — Company X — 03/2021–Present. For freelance, group by client or service line with readable periods. Honesty beats inventing dates to fill gaps.

5. Skills only as icons or bars

A Python icon or an 80% bar is not indexable text. Filters look for the words Python, Salesforce, Power BI. Write skills as a list or inside achievement bullets. You can add level in words (advanced, daily use) if useful, but the term must exist as plain text.

Before: five bars without clear labels. After: Python (pandas, FastAPI), SQL, dbt, Airflow. The ATS finds matches; humans see depth.

6. One generic CV for every posting

Even with perfect parsing, a CV that does not speak the posting language loses keyword ranking and loses the recruiter in the first seconds. You do not need a full rewrite: tailor the summary, 3–5 bullets on the most relevant role, and the skills list. Use true terms from the ad; do not paste the whole job description.

Example: the posting asks for customer success, churn, Salesforce, onboarding. Your base says customer support and CRM. Rewrite with vocabulary that matches real work. If you never used Salesforce, do not invent it.

7. White-text keywords, repetition, or lies

Hiding an endless keyword list in white text is an old trick, detectable and often penalized. Repeating Java Java Java with no context also looks like stuffing. Lying about tools or titles is worse: you pass the filter and fail the interview. The sustainable strategy is evidence plus aligned language.

• Place keywords in summary, experience, and skills with context.
• One natural mention inside an achievement beats five empty repeats.
• If you are learning a tool, say so honestly (course, project).
• Remove trendy keywords you do not use when they do not apply.

8. Incomplete or unreadable contact details

Without a plain-text email or phone, the process breaks even if everything else is perfect. Avoid email as an image only, phone numbers split with odd symbols, opaque shortened LinkedIn links when the portal wants a full URL. Put name, email, phone, city/country, and a professional link at the top.

9. Mixing languages without a plan

English titles with Spanish bullets (or the reverse) confuse parsers and humans when the posting is monolingual. Match the ad language and stay consistent. If you apply in both markets, keep two ES/EN versions, not a hybrid. ClarCV supports Spanish and English depending on the application.

Quick anti-reject checklist

• Can I copy text from the PDF?
• Are section names standard?
• Does each role show title, company, and clear dates?
• Are skills written as text, not only icons?
• Are email and phone visible at the top?
• Are summary and bullets tailored to the posting without lying?
• No decorative tables or hidden keywords?

If you fail two or more structural points, fix them before you apply. A clean CV beats a pretty one that will not parse. Once the base is solid, iterate content per posting.

How to fix this with ClarCV

Upload the problematic PDF or Word file. AI highlights clarity and structure friction; then you apply an ATS template and download a PDF with real text. It does not replace your judgment about which achievements to tell, but it removes hours of fighting broken columns. Fair pricing: free to start, Pro at €7/month with no shady trial.

Before you send, ask someone outside your field to read the CV for twenty seconds and say what you do. If they cannot answer, the summary or first role needs more clarity. That human test complements ATS checks and prevents surprises in real processes.

Keep one stable base version and create variants only when the posting changes role family. That reduces date errors and keeps consistency across applications. ClarCV helps regenerate clean variants without rebuilding layout by hand every week.

If your path has gaps, do not hide them with confusing dates: parsers and recruiters notice. Explain the period briefly in one line or prepare for the interview. Clarity usually builds more trust than cosmetic calendar cover-ups.

Also check consistency with LinkedIn: same titles, employers, and approximate dates. A large mismatch creates unnecessary doubt even when the CV parses well and keywords match the posting.

Prefer evidence over adjectives. Replace excellent communicator with an achievement that proves communication: client presentations, docs the team adopted, or fewer tickets after better internal guides.