Textio is the augmented writing platform that instantly transforms your rough ideas into powerful language with a single keystroke. Building on the words you type, Textio's data-fueled predictive engine generates highly effective writing that sounds like you.
Super interesting and smart to focus on one specific use case to start with: job applications.
What other use cases are people using this for, @jensenharris / @kieransnyder?
@rrhoover@jensenharris People want every use case! We recently created a beta explicitly for recruiting email because we saw that people were putting a lot of related content through Textio already.
We have seen recruitment and other marketing content, sales content, course syllabi, pitch decks, love letters... but we are trained on and promise to be great at talent and hiring docs.
@kieransnyder You're on to something here. Would totally use this for any kind of content, reminds me of Hemingway Editor. Do you have any plans to support additional languages, let's say German?
@zedpelin We will support other languages, but not quite yet. I started my tech career in internationalization and multilingual support is important to me, but we're not quite ready. (We support regional tailoring for different varieties of English right now.)
Thanks for the kind words!
How do you decide what phrases are gender biased? Is there any data or research to back up the claim that the phrase "proven track record" attracts more men to a job, while "passion for learning" attracts more women? I'd love to see the science behind this.
@ashocka18@pawtiko Hi! Textio is a quantitative system. It starts by looking at many previous job listings and information about who has actually applied for them,. Then Textio finds the patterns that consistently drive various application and hiring outcomes.
Language that is judged "masculine" or "feminine" is language that has statistically driven high proportions of male or female applicants for similar jobs in the past. When a job listing comes in to Textio, Textio compares it with other similar job listings whose previous outcome is known.
Inclusive language ("green") language is language that statistically draws more applicants, draws more highly qualified applicants, and fills roles faster. Masculine and feminine language drive higher %s of male and female applicants respectively compared to the baseline for the job. Negative ("red") language is language that everyone across demographic groups disprefers.
@kieransnyder@pawtiko That's nice, but I still don't see any data. @rrhoover what is PH's stance on this?
Problems I see with this startup:
Lack of any data that would support your stereotypical claims.
The copy misuses the word "gender bias", probably to earn sympathy of the less informed. "Gender bias" means "unequal treatment in employment". Using certain words in a job description will not solve this problem. Changing the mentality of those in HR will solve this problem.
This startup's definition of "genders" is "male or female". This means they're actively discrediting all other gender identities. Again, not helping the diverstiy problem at all.
Taking on this challenge, the founders should have predicted the PC backslash and have the data ready (and a PR person able to handle it).
Textio enables talent pros, entrepreneurs and anyone trying to hire people better and faster through the "smartest" job description and messaging. It's an efficient product where you can foresee success or failure.
Signed up and tested this out on a couple of application my company is hiring for right now. The listings started out as "ordinary" but as soon as I add Textio's canned "equal opportunity statement" (a sentence stating you're an equal opportunity employer) the listing goes to "very good". Seems.... not quite right. I didn't actually change any aspect of the "description" portion of the job description. Just adding a disclaimer adds 30 points? Calling shenanigans.
@drdandini Thanks for giving us a try! The impact of the equal opportunity statement depends on the prior quality of the listing (sometimes you get a little, sometimes a lot). It's also worth noting that the statement in Textio has been specifically optimized for performance - not all statements perform the same way.
All of that said, the impact of an authentically worded statement on your job listing performance is significantly greater than most people expect. Jobs with good EOE statements not only draw more applicants from underrepresented backgrounds (which shows in our measurements as well as in the numerous academic studies on this), they draw more (and better) candidates from majority backgrounds as well.
It turns out that most people genuinely prefer an inclusive workplace, and in an era where more and more companies (especially tech companies) are taking the time to be thoughtful about this, applicants have a choice and can avoid workplaces that do not. And so they often do.
Thanks for the feedback!
This is a great product - I tested it out and it helps you really improve your job listing overall, not just for gender bias. #rock (I also adore the CEO, Kieran.)
Hello,
I am a big fan of your product..
and I see tremendous potential for this as every job posting should be filtered before posted.
I see an opportunity for you to market your product by using your Textio Technology on jobs/economic development speeches by Presidential Candidates for the US elections 2016!
If you can find the text documents of each top candidate's speech regarding jobs/economic development and test them with Textio and compare the results.. This will be very interesting for anyone of relevance (US voters/gender equality activists/political parties/etc..)..
and hence create more awareness of your great product..
I hope my insights were an interesting read if they prove not be implementable..
Thanks for your time and consideration regarding my suggestion.
Jaswinder Brar
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