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ATS or Applicant Tracking Software is constantly evolving and plays a huge part in the life of recruiters, HR and Talent Acquisition to sift out the most highly matched candidates for the role.

Each ATS system may have many individual features in how they parse (keyword, grammar and statistical) store, and manage information, but they are all based on the same fundamental basic process; to support the recruiter.


CV parsing involves the automated analysis, organisation and storage of CV data. It entails extracting relevant information from a CV by searching for specific keywords or using grammar analysis or other techniques to select CVs that contain the preferred criteria for a vacancy. Since many candidates use a similar format for their CV, recruiting managers can use CV parsers to extract the relevant information and store it in a database with a unique entry for each candidate.


After parsing all the CVs, the recruiter can search the database for keywords and phrases to generate a list of qualified candidates. The software may also store applicant information for future vacancies (if you opt in for this) and it is usually this process that prompts a contact from a recruiter in the future after your initial application has been submitted.


ATS systems vary hugely and the format of your CV is paramount as CV’s/Resumés that have tables, text boxes, columns and pictures, as well as CV’s in PDF format can struggle to be read. ATS can only read your CV's text not your formatting or images.


The use of artificial intelligence (AI) based systems and Machine Learning (ML) to save time and reduce the complexities of screening processes is on the rise.


Applicant Tracking System (ATS) is also built into all major job boards.


Types of Parsing

Grammar based parsing may be more accurate than other parsing techniques but it requires a significant amount of manual encoding by engineers skilled in language analysis.


Statistical parsing involves using numeric models to interpret the words in a CV. It assesses various types of information, including addresses and dates. Like grammar-based parsers, statistical parsers can also distinguish between the same word or phrase when the candidate has used them in different contexts.


Keyword based CV parsers work by detecting key words in a CV. They use industry specific terms to enable recruiters to select suitable candidates. This method may be beneficial when HR professionals want to choose candidates based on their skills. For example, employers may scan several CVs for keywords, such as article writing or SEO writing, for the role of a content writer. Keyword-based parsing is the most basic type and other types may be more accurate

CV/Resumé Parsing

The task of interpreting language and information is multi faceted, which presents a significant challenge when it comes to relying on a computer to sort through large quantities of information. Language is both highly varied and ambiguous. For example, in the case of the former, there are numerous ways to write down a date. With the latter, the same word means different things in different contexts. Effective CV/Resumé parsing software, therefore, must be smart enough to interpret the complex nuances of language.

CV’s/Resumés for ATS and Parsing

The key is to avoid templates and keep your text, font and style simple.

  • Include your name in the filename of your CV/Resumé

  • Submit your file as a .doc format for maximum parsing compatibility

  • If you use a pdf, export it from the MS word .doc. Don’t scan your document as an image.

  • Avoid headers and footers

  • Use one standard font throughout the entire document

  • Avoid tables and columns

  • Don’t mess with spacing

  • Keep your Resumé chronological

  • Use basic names for sections i.e.: “Education,” “Work Experience,” etc.

  • Use Day, Month Year for date formatting

  • Spellcheck

  • Don’t overuse keywords

  • Remove special characters and avoid creative bullets that are often illegible to an ATS.

  • Avoid special fonts, font treatments and colours. Stick to ‘clean’ fonts such as Arial, Georgia, Lucinda, Tahoma.

  • Avoid underlining words, which can mess up the legibility of lower case letters such a g, j or y.

  • Include contact information in the body of your Resumé, not in the header or footer.

  • When writing your employment history, present the information for each employer in the same order, i.e., company name, title, city, state, and date and in reverse chronological order.

  • Avoid templates, which are a combination of fields and tables and can confuse ATS systems.

  • Also, avoid page numbers.


Now that you’ve got the formatting nailed down, take a look at the actual content of the CV and make sure it is compatible with an ATS.

  • Maximise your skills section. To improve your chances of being discovered by the ATS, make sure to include any certifications you’ve received and mention any industry specific terminology (i.e. Salesforce for sales professionals or Haematology for healthcare professionals). Include both the spelled out version and abbreviations of the same word


Targetting CV’s and Cover Letters against Job Specs

  • Remove unique headings and stick to common headings like Summary, Work Experience, Education and Skills.

  • Remove images, columns, tables, fields, text boxes and graphics so the ATS can scan your text for keywords and phrases. The ATS may not be able to read data placed in images, tables, and text boxes, so it’s best to avoid them altogether.

  • Include any education, certifications, or licenses relevant to the job you are applying for.

  • Include keywords relevant to your industry. You can find these keywords by doing a Google search for “[industry] keywords.”

  • Distribute the keywords throughout the “Summary”, “Education”, “Experience”, and “Skills” sections, and use them in your cover letter as well.

  • Review your CV for the correct spelling of keywords and proper use of abbreviations (as used in the job posting).


Optimise your professional summary with bulleted achievements and skills that relate to the job description. Then, find a natural way to include those keywords and phrases in your summary and throughout your CV.

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