Resume Parser CEOs’ advice for your resume

I decided to refresh my knowledge and get the best advice possible by going straight to the CEOs, Presidents, and technical experts of the top 5 resume parsing companies. [ladders-logo@2x.png]‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ Good Monday morning {NAME},  I’ve been asked for a lot of advice on resumes this year. Recently, an old friend stumped me when he asked ‘should you submit your resume in PDF or Word?’ I hadn’t thought about this question in probably four or five years, which in technology is a lifetime.  So I decided to refresh my knowledge and get the best advice possible by going straight to the CEOs, Presidents, and technical experts of the top 5 resume parsing companies: HireAbility, DaXtra, Sovren, Textkernel and Hiretual. These five companies power essentially all of the resume parsers that you’ll encounter in applying for jobs on corporate sites globally.  They were each very generous with their time, and shared their expert advice on [what you need to know before your resume is parsed](  What does a typical Ladders professional, submitting their resume, need to understand about how their resume is parsed?  Ninh Tran, Founder Member, [Hiretual]( "My advice for professionals when it comes to resume parsers is try to stay away from fancy resumes."  Robert H. Ruff, Co-Founder and President, [Sovren]( "People want their resume to look unique. I can guarantee you that the longer you spend formatting your resume and making it unique, the less likely it is it's going to get you hired."  [Christine Watson]( Marketing Director, [DaXtra Technologies]( "A resume parser is a technology that uses Natural Language Processing (NLP) to ‘read’ and convert the text of a resume to language a computer can understand. Resume parsers automatically extract and analyze resume data so the information is able to be categorized, coded, sorted and searched over by the recruiter."  Steve Kenda, CEO, [HireAbility]( "Your best bet for parsing is to use Word or PDF format. Both of those are readily convertible into a text structure that lets the parser do its thing."  Mihai Rotaru, Head of R&D, [Textkernel]( "First of all, make a clean resume. Try to not be very creative. So I do know that all of the parsers struggle with designers’ resumes. Designer resumes are the ones that it's the hardest for us to parse. Don't go too designer on it."  What are common errors people make in their resume formatting or structure?  Steve Kenda: "I think the two biggest ones are not using your contact information early on in your resume. Most of the parsers are looking to be able to identify a name and address, a phone number, to know that, one, they're actually looking at a resume. And two, they're starting in the right order.  If they've got the contact information early on and have not included a header or footer, the parser just clicks right away and gets started and makes it just a whole lot more orderly.  The other is, people are throwing in jpegs of themselves, pictures, or tables or graphs. That's going to complicate the process. The easier you can make it for the parser to perform what it's doing, the more likely you are to have success with your data being more readily found when it comes to search time."  Christine Watson: "Avoid complexities. The simpler, the better. A straightforward MS Word document with system font text is best.  Include your city, state and postal code so this is picked up in searches. As recruiters typically search by location.  Don’t abbreviate your name."  Can you discuss how bar charts, graphics, and other visual communications are handled by parsers?  Robert Ruff: "They're ignored.  Visual information is not going to be understood by the machine. And what you have to think about is, I actually have two resumes. I've got a resume that the computer needs to see and understand, and I've got a resume that I want to impress a human being with.  It's okay to have a reference to the fancier resume in your plainer resume. It's also okay to put information in graphics, as long as it's not information that is needed to be understood by the machine.  So, I'll give you a ‘for instance’. I have seen a few resumes where people do not give us the name of the company. They give us the logo of the company. That logo can be read or understood by humans, but a parser is not going to get the text from that."  Minai Rotaru: "We actually do not handle those. Some of the resume generators - there are a lot of websites that generate resumes - those might actually put out resumes with visual bars. At Textkernel, we currently do not process those at all."  Ninh Tran: "Usually they're omitted. Graphics and images that are meaningful to the human eye are not meaningful to the parser."  Christine Watson: "Bar charts, graphics, and other visual communications are not handled well by parsers."  Why do HR departments use parsers?  Christine Watson: "Parsers are automated, quick and accurate tools that are able to handle large volumes of resumes, breaking them down into a format that can be stored and searched over. A parser takes on rote tasks freeing up time for the recruiter to concentrate on other duties that are more human-focused, like one-on-one interviews. It’s a tool that’s used to benefit HR departments and recruiters by increasing the speed of matching candidates to jobs."  Robert Ruff: "Nobody can do searching and matching to find out who you are, what you’re best at, until we've turned your resume into plain text, and then hopefully extracted the information accurately."  Steve Kenda: "Whereas in the old days, the resumes would just come in and they get stored in a searchable text database, and when someone ran a search, they were just getting a lot of information that they really didn't need. So instead of getting 30 resumes now when a search is run, they get three because you can have tagged data."  Ninh Tran: "HR departments use parsers because they don't have time to process a thousand resumes at once. It's a problem of too many applicants, too little time.  Resume parsing is deconstructing whatever file that your resume is in. Then we convert that into raw text.  They want to have your data, your title, your location, your email, all in their nice fields inside their tracking systems that is central, because it makes it more searchable. So let's say that they want to find, hey, how many candidates do we have with Python in San Diego? They want to index your data in a more meaningful way."  Mihai Rotaru: "HR departments need to take the information that you have given to them and put it in their applicant tracking system, ATSs, so they can track your information. And, especially when you have many applicants for a position, to be able to search.  This transformation from a format that it's easy to read by people to a structured format that is used by computers is the actual parsing. And it's crucial for being able to be found by recruiters.  So if you have a recruiter that needs to screen 200 CVs, you search for the information rather than review each resume. So parsing is essential from that perspective.  Another thing that parsing helps is to extract information that might be implicit in the document. So for example, the number of years of experience that you have, or your experience in a certain domain, how much you've used a skill, other meta information, like, ‘Do you have international experience? Have you changed many jobs?’ and so on. This type of information can be automatically derived and inferred from your document."  Should I submit my resume in MS Word, Google doc, or PDF? How do parsers manage these different file formats?  Steve Kenda: "MS Word is good. Google Doc's good. Text or RTF is good. What you want to avoid are OCR [Optical Character Recognition] situations, jpegs or pngs, or any other picture type formats."  Robert Ruff: "So, obviously PDF is the big issue. PDF has always been a problem. People don't understand that PDF is not a text format. It's actually an image format. And what I mean by that is that there is no concept underneath a PDF, inside of it, of text. There is literally just specified fonts and where those characters, using whatever font, are placed like a pixel on a picture.  So, to extract text from a PDF is actually part science and part guesswork."  Ninh Tran: "Any of those would work. MS Word is probably the best. Or Google Doc.  Because PDFs are locked usually, we have to have a PDF reader, an OCR system, to read it.  So if I were advising a friend, I'd say MS Word or Google Doc."  Chrstine Watson: "The best way to submit your resume is in a simple word processor format like an MS Word document or a Google doc. PDFs are a bit more complicated because they can be saved a couple ways – as a text document or as an image document. With text, there is no problem. It’s the image document that can be tricky. Although some systems implement Optical Character Recognition (OCR) tools that can be integrated with a parser and could technically work, optically reading the document then parsing that text, it is not as common and is not worth the risk of your resume not parsing. Therefore I suggest not submitting an image PDF at all."  Mihai Rotaru: "Parsers usually have converters and transform your resume into HTML and then into text. Most of the machine learning works directly on this text. Our experience is that sometimes word documents are easier to process, especially when it comes to tables, because the table information is retained in the document. While for PDFs, the table information is implicit, so that can be a bit more difficult.  So MS Word documents, especially if you use tables, are better."  How do resume parsers handle borders, horizontal lines, tables and text boxes?  Robert Ruff: "Text boxes will either show up in random places, or not at all. Don't use them.  Tables should not be used. If you want to put information that's in a tabular fashion, you should do a poor man's table. Use tabs and spaces and not the actual table object in Word."  Christine Watson: "Borders, horizontal lines, tables and text boxes are complications the parser will need to deal with. Keep it simple and avoid all of these. The parser is looking for text, words and sentences. Graphics only get in the way."  Mihai Rotaru: "Parsers do not really pay that much attention to the lines, all these visual clues like horizontal lines and so on. I do know that the more tables and the more columns you use, the harder it is to parse those documents."  Should I use one column or two on my resume?  Christine Watson: "Keep things as simple as possible. Although it is possible to parse two columns, it is more difficult. One column is preferred."  Ninh Tran: "One. If your objective is to be parsed by these resume parses, make it simple."  Steve Kenda: "Just one. Well, the pdf converters are good, but I still call it an evolving technology for handling columns. It's just an awkward structure for pulling out experience.  My recommendation is you only use one column. I think it will become less of an issue over time. I'm just saying for right now, one column only.  Columns don't make it any easier for the parser. So you're not helping yourself when it comes time to the applicant tracking system that's being used by whomever you're applying to."  Mihai Rotaru: "One column guarantees that your parsing is not affected. Two columns can choke some of the parsers."  Robert Ruff: "Do not use columns. Do not use fancy tables of data. Keep that simple."  ~~~  Thank you so much to our friends in the industry at [Hiretual]( [Textkernel]( [Sovren]( [DaXtra]( and [HireAbility]( for their terrific help in understanding more about how resumes are parsed with these phenomenal insights!  I’ll be back next week with the [2nd half of our interviews]( with these experts. Have a great week, Readers!   I’m rooting for you! [Marc] [Marc Cenedella]( Founder [( © 2020 [Ladders, Inc.]( All Rights Reserved [Advertise With UsÂ]( [ Contact Us]( |[ Unsubscribe]( You're receiving this email from our secure server at [Ladders, Inc.]( because you signed up on March 26, 2016 from [{EMAIL}](#) with the ZIP Code 06473. [Ladders, Inc.]( - [55 Water Street, 51st Floor - New York, NY 10041](#) [PrivacyÂ]( Terms of UseÂ]( View in Your Browser](