It might seem like the principles of good writing are universal. But when you’re writing for hiring, it turns out that what attracts or deters people from applying for a job can differ significantly depending on where you are hiring, what kind of job it is, and when job seekers will be reading your post. Want to know how Textio knows all this? Read on.
Say you’re a hiring manager at a manufacturing company on the West Coast of the U.S., and you’re using Textio Hire to draft a job post for an Operations Manager role in San Jose, California. You’re thinking about how important it is that people at all levels of your organization be willing to roll up their sleeves and dig in with as much energy as the hardest-working person on the production line. So in your list of qualities you’re looking for, you add: “You have a great work ethic.”
Textio highlights your phrase green — that means it’s going to improve the statistical likelihood of your job filling faster. Nice work!
But wait. You make a copy of your strong listing to hire for the same role at your other facility in Everett, Washington. Now Textio highlights “work ethic” in orange.
What’s going on here? Since Textio sees the ways that language varies from region to region, it knows that while this phrase goes over great in California, it’s not going to play so well with job-seekers in Washington. Up here in the Pacific Northwest, the phrase “work ethic” is actually associated with longer time to fill. Good thing you can fix it before you publish your job ad. You change the Everett version to “You are dedicated and diligent,” and now you’re back in business.
Sometimes this guidance feels counterintuitive. So how do you know it’s right? Where does it come from? Most writing programs that give you advice are simple tools that use hard-coded, unchanging rules that a “subject matter expert” came up with. Those rules are limited by biased, imperfect human judgment about what’s going to work. Textio is different. Its predictive engine is constantly learning from new data to find the patterns that are working right at the moment you need to use them, right in the places you are hiring, for the exact types of jobs you’re hiring for. The times where Textio’s advice is not what you expect are actually the times when it’s most valuable: it’s giving you insights that can only come from a vast amount of data.
Know more about the data behind your document
Textio has recently released a new feature to let you see exactly how much data it’s currently learning from to produce these insights. Underneath your to-do list of the most impactful things you could work on next, you’ll see a real-time count of the number of job posts for your job type and location that it’s learning from right now. This number changes as Textio ingests more data and older hiring language becomes stale.
Want to know why Textio gives you different advice for, say, Accounting jobs versus Finance/Insurance? Now you can see the hundreds of thousands of listings for different job types that Textio is learning from to make that distinction.
Wondering if Textio understands how English is used differently in London versus Hyderabad versus Auckland versus Stockholm? You’ll see just how many recent job posts Textio has looked at from each of those locations and many more around the globe.
The power of augmented writing comes from its ability to draw quantitative insights from millions of documents and make them useful to you as you write. And now you can see a little bit more detail about the size and shape of the data that informs the guidance Textio is giving you, updated in real time, right before your eyes.