Language is constantly changing; the world we live in demands consistently finding new ways to define the previously undefinable, describe the indescribable (or inconceivable) and reflect our ever evolving society.
Take the term “human resources,” which first appeared in 1958; even that inescapable and omnipresent phrase “big data” only showed up in print for the first time in 2001.
Of course, the rate of linguistic change in the talent function pales in comparison to the frequent, frenetic changes in technology.
Tech-related buzzwords and business terms evolve every day, and one of my favorite aspects of Textio is our ability to actually see the way that language changes in real time.
Nowhere is this phenomenon more evident than in word choice within job listings. As of today, we’ve recognized over 50,000 distinct phrases that impact the quality, quantity and diversity of applicants through such a seemingly superficial change as the language recruiters use to attract top talent.
The list of the most effective phrases for job ads, as you can imagine, is as dynamic as the technology market itself, largely mirroring both hiring demand and bigger industry trends. For example, one of the most hackneyed of business buzzwords, “synergy,” which experienced such inexplicable popularity only a few years ago,has been reduced to such a cliche that its very presence within a job description serves as a strong predictor of negative job ad performance.
With this in mind, we took a look at our job listing data over the last 12 months to find out the biggest winners and losers when it came to speaking the language of top tech talent to effectively drive applicants and convert candidates from job ads.
And even in such a short period of time, we were able to produce strikingly clear evidence that not only does language change, but it changes fast: none of today’s losing lexicon had a negative impact on average job listing performance only one year ago, and only two of today’s top terms were even on our lexical map back then.
The 10 Best and Worst Words For Your Tech Job Ads.
So if you’re looking to improve your tech job posting performance, here are five winning words you should try to target – and five that you should try to avoid at all costs. ‘
The biggest winners and losers in tech job ads over the last year:
Tech Recruiting Terms: 5 Top Terms for 2015
- Artificial intelligence (or AI). This is the biggest winner in our data set over the last year, and we swear we’re not just saying that because we’re an AI company and we’re hiring. The phrase has been around a long time, but over the last six months its usage among the strongest performing tech job listings has quintupled.
- Real-time data. It’s not news in 2015 that software built on a static foundation has a hard time competing, and tech companies are increasingly bringing this forward in their job listings. Real-time data shows up twice as often in the top 25% of job listings as it does in the bottom 25%.
- High availability. Creating personalized and relevant experiences means that you’re making products that are always available. High availability (along with its close kin high availability service and high availability architecture)shows up in 42% more job listings than it did a year ago.
- Robust and scalable. Both robust and scalable have shown up in tech job listings on their own over the last couple of years, but the use of the two together broke big in tech job ads over the summer and it’s still on the rise: usage has tripled over the last two months alone.
- Inclusive. The diversity conversation looms large in tech, so it’s not surprising that job ad language reflects it. But the specifics are changing. Last year, equal opportunity statements were fifty times more likely to contain the words diverse or diversity than any other phrase. While diverse is still everywhere, its positive impact on attracting applicants from underrepresented groups is slowing down. Over the last six months, many forward-thinking tech companies have replaced diverse with inclusive in the broad workplace culture statements that have themselves begun to replace conventional equal opportunity statements.
Tech Recruiting Terms: The Year’s Biggest Losers
- Big data. Two years ago big data was everywhere. Companies bragged about using it. New investment funds and top 40 bands were named after it. Engineering job listings containing big data were significantly more popular than those that did not. But today, big data has become so highly saturated that its use has passed into cliché; engineering job listings that include it perform an average of 30% worse than those that do not.
- Virtual team (or v-team). Corporate jargon performs poorly in every industry, but nowhere more so than in tech. Job seekers are neutral on distributed team and working group, but virtual team is more than ten times as likely to appear in job ads with low applicant counts as it is in more successful listings.
- Troubleshooting. Both IT people and software engineers are excellent troubleshooters, hopping on problems or debugging challenges wherever they pop up. But while the skill remains relevant, the term to describe it has shifted. Job posts containing troubleshooting perform twice as poorly as those containing problem solving, fixing, or diagnosing in a similar context.
- Subject matter expert. In many senses the subject matter expert is the opposite of the full stack engineer: the subject matter expert knows one thing very well, but only one thing. Listings containing full stack engineerperform an average of 32% better than listings containing subject matter expert. In a world where versatility and job mobility are the way to make more money, no one wants to be a one-note piano.
- Drug-free workplace. Want to torpedo your tech job listing? Advertise that you’re a drug-free workplace. Job listings containing the phrase are over twenty times more likely to perform in the lowest quartile of listings – and six months ago, the effect was only half as strong.
The language that works in recruiting changes as time passes; what was hot a year ago, or just a few months ago, may leave candidates cold today. And if you’re trying to reach top talent, it’s imperative to make sure you’re speaking their language – or else, it’s likely you’ll never truly be heard.
Read more at the Textio Word Nerd Blog.
Kieran Snyder is the co-founder and CEO of Textio, a recruiting technology startup based in Seattle. Kieran holds a PhD in linguistics and has held product and design leadership roles at Microsoft and Amazon. She has authored several studies on language, technology, and document bias.
Kieran earned her doctorate in linguistics and cognitive science from the University of Pennsylvania and has published original research on gender bias in performance reviews and conversational interruptions in the workplace over the last year. She participates actively in Seattle-based STEM education initiatives and women in technology advocacy groups.
Follow Kieran on Twitter @KieranSnyder or connect with her on LinkedIn.
By Kieran Snyder
CEO and Co-Founder of Textio. Long-time software product leader, accomplished data writer, recovering academic with a PhD in Linguistics and Cognitive Science from the University of Pennsylvania. Deep experience in product management, product marketing, pricing and licensing, and SaaS across the board, with specific technical strengths in natural language processing and data science.
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