Welcome to the 4th part of our series! We started Part 1 explaining why job posts are important, in Part 2 we talked about how to attract candidates and in Part 3 we shared how to engage them by presenting the role and your company well. How can you actually convince them to apply? I’ll be sharing data in this article that shows why the words you use matter.
Have you ever written something that you thought was great, only to have it scrapped by the first reviewer? This happens with job listings all the time. Lots of companies use req writing as a collaborative process to decide what a role will entail. This is messy (and can lead to the Franken-listings that we talked about in part 2). But it doesn’t have to be this way.
One of the hardest parts about writing is that it seems subjective. I used to work in Public Relations (yay, career changers!). I’ve drafted more press releases and client emails than I can count. I consider myself a decent writer, but my version #1 was usually unrecognizable by the time it was approved at version #15.
I used to take it personally, until I realized that I do the same thing when I’m the reviewer. Almost everyone has an opinion when it comes to writing — especially business writing, like job posts.
But I’m here to spread some good news. It may come as a surprise to some that with the right data, you can take the subjectivity out of writing.
With the right data, you can take the subjectivity out of writing.
It’s actually possible to quantify how “good” job posts are. Most companies are already tracking this by recording how many people apply, how fast the role fills, and whether or not they’re attracting qualified and diverse candidates.
Now take that individual company data and multiply it — by millions. To draw conclusions about what makes your company’s job posts work, you need enough data to detect statistical patterns. Textio is constantly analyzing job posts, adding almost 10 million job listings and their outcomes each month to a database of more than 70 million.
It’s possible to quantify how good job posts are.
This massive database of job posts and how they perform allows Textio to detect patterns. Patterns like: what words ultimately convince candidates to apply?
Let’s stop for a quick exercise. Can you guess which three of these phrases will cause a job listing to fill more slowly? No cheating!
Here’s the Textio Unicorn who will quietly judge you if you scroll down without guessing. Guess!
Technology-driven sounds good, right? You’ll probably attract some smart techies, right? Wrong! It may surprise you, but Textio found that the words listed in orange statistically make a job listing perform worse. Green phrases are good words that you want to use. They lead to faster time-to-fill and attract more qualified candidates.
Why is “every day” in a box, you might ask? While “every day” doesn’t have a negative effect on your job listings, it’s not positive, either. But what happens if you add a single word? (Pun totally intended — sorry).
Changing “every day” to “every single day” makes your job listings fill more quickly. Even good writers are better when they have data to back up their instincts.
Next week I’ll share more examples to show how real-time data can help you use the words and phrases that will convince applicants to apply. In the meantime, the Textio blog is a great resource if you’re wondering about what language to use. Here are a few examples to get you started:
- “Perfectionist” in the list above is a great example of how fixed mindset language performs worse than growth-mindset.
- HR buzzwords perform better than you might think. Candidates actually care enough to see past the jargon!
In case you missed the other parts in our series, you can find them here: Part 1, Part 2, Part 3, and Part 5.