What is Resume Parsing?
Definition: Resume parsing is the automated process of extracting and categorizing information from resume documents into structured data fields, enabling Applicant Tracking Systems and recruiting software to store, search, and analyze candidate information.
Also known as: CV Parsing, Resume Data Extraction, Resume Parser
Quick Summary
TL;DRResume parsing is the automated process of extracting structured data (name, contact info, work history, education, skills) from unstructured resume documents. ATS and recruiting software use parsing to populate candidate databases, enable searching, and automate screening. Parsing accuracy depends heavily on resume formatting.
Key Facts
What It Does
Extracts data from resumes
Core function
Accuracy Range
60-95% depending on format
Industry benchmarks
Used By
ATS, CRM, Job Boards
Technology adoption
Failure Cause
Poor resume formatting
Parsing analysis
Why Resume Parsing Accuracy Matters
Recruiters rely on parsed data to search candidates, match to jobs, and generate reports. When parsing fails, candidate information is incomplete or incorrect—skills may be missed, job titles garbled, or contact info lost. This causes qualified candidates to be overlooked, ruins database integrity, and creates manual work to correct errors. For staffing agencies processing hundreds of resumes, parsing problems compound quickly.
Common Pain Points
- 1Qualified candidates overlooked due to parsing errors
- 2Manual data entry to correct parser mistakes
- 3Incomplete candidate profiles in ATS databases
- 4Search and match features returning inaccurate results
How Resume Parsing Works
Understanding parsing helps you optimize resumes for better accuracy.
- 1
Document Intake
The parser receives a resume file (PDF, DOCX, etc.) and converts it to processable text, stripping formatting.
- 2
Section Identification
AI/rules identify sections: contact info, summary, experience, education, skills. Standard headings help accuracy.
- 3
Field Extraction
Within each section, specific fields are extracted: company names, job titles, dates, degree types, skill keywords.
- 4
Data Normalization
Extracted data is standardized (date formats, job title matching) and stored in structured database fields.
Result
Better resume formatting leads to better parsing, which leads to better candidate data.
Resume Parsing Deep Dive
Parsing Technology Types
Modern resume parsers use three approaches: rule-based (pattern matching for known formats), statistical (machine learning trained on resume data), and AI/NLP (natural language processing for context understanding). Most commercial parsers combine all three. AI-based parsers handle varied formats better but still struggle with creative designs.
What Breaks Parsing
Common parsing failures: headers/footers (often ignored by parsers), tables (content extracted in wrong order), text boxes (may not extract at all), images with text (completely invisible), unusual fonts (may not render), PDF created from scans (requires OCR which adds errors), and non-standard section headings (parser doesn't know where to put data).
Parsing for Staffing Agencies
Staffing agencies face unique parsing challenges. They receive resumes in every format imaginable from candidates. Before adding to their ATS or submitting to clients, these resumes need to parse accurately. Many agencies reformat incoming resumes to a standard template specifically to ensure clean parsing into their systems.
Common Misconceptions
- All resume parsers work equally well
- PDF is always better than Word for parsing
- Modern AI parsers can read any format
- Parsing errors only affect candidate data entry
Parsing Accuracy by Resume Format
| Format Type | Parsing Accuracy | Common Issues | Recommendation |
|---|---|---|---|
| Simple .docx | 90-95% | Few | Best choice |
| Simple PDF | 85-92% | Text extraction | Good choice |
| Creative design | 60-75% | Layout confusion | Avoid for ATS |
| Scanned/image PDF | 50-70% | OCR errors | Convert first |
| Multi-column | 65-80% | Wrong order | Avoid |
How format affects parsing success
Related Terms
Frequently Asked Questions
Related Resources
Ensure Perfect Parsing Every Time
iReformat creates resumes optimized for ATS parsing