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Common ATS Resume Mistakes (And How to Fix Each One)
Most ATS rejections come from a small set of recurring mistakes. The good news: they're all fixable in under an hour. Here are the most common errors we see when analyzing resumes — and exactly what to do instead.
Mistake: Using a template from Canva or a design tool
Fix: Export to a text-based format (Google Docs, Word) and rebuild the layout in single-column plain text. You don't need to sacrifice all design — clean typography and consistent spacing are fine. What kills parsability is multi-column layout, text boxes, and image-based graphics.
Mistake: Generic professional summary that mentions no keywords
Fix: Rewrite your summary for each application. Lead with your target job title, include 2-3 of the most important keywords from the job description, and quantify your experience level. Before: 'Experienced professional with a passion for results.' After: 'Data Analyst with 5 years of experience in Python, SQL, and Tableau, specializing in sales analytics.'
Mistake: Listing responsibilities instead of achievements
Fix: Every bullet should start with an action verb and end with a result. Before: 'Responsible for managing social media accounts.' After: 'Grew LinkedIn following from 2K to 18K in 8 months through organic content strategy, increasing inbound leads by 22%.' The second version contains keywords, shows impact, and is specific.
Mistake: One resume for all applications
Fix: Create a master resume with all your experience, then tailor a copy for each significant application. The core content stays the same — you're only adjusting the summary, reordering bullets to prioritize relevant experience, and ensuring keyword alignment with that specific job description. Takes 15-20 minutes per application.
Mistake: Including a photo, logo, or profile graphic
Fix: Remove all images from your resume. ATS systems can't parse image content, and in many countries and companies, photos introduce unconscious bias that HR departments actively try to eliminate. Your photo takes up space that could hold keywords and achievements.
Common mistakes to avoid
- ✗Listing 'Microsoft Office' as a skill when the job requires specific tools like Excel with pivot tables or Power BI
- ✗Using abbreviations without spelling them out once (ML instead of Machine Learning)
- ✗Including irrelevant jobs from 15+ years ago that dilute keyword relevance
- ✗Using the same generic objective statement across all applications
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