Textio Review: Write Magnetic Job Description Effortlessly

And fill your job vacancies 20% faster

Writing an effective job ad is probably the least skill set that a recruiter possess.

Textio

Just randomly pick out a few job postings from the usual job board.

It can be quite painful to review some of them.

Let’s take a look at a couple I picked out:

This ad surely isn't written by a copywriter

This ad surely isn’t written by a copywriter

Mediacorp Ad

Zzzzzzzzzzz……

Now I have reviewed a number of apps and tools over this year, from payroll solutions to collaboration tools to recruiting crm and many more.

Every single one of them has been amazing. And I’m pretty selective in what I review as I hate wasting time.

But there hasn’t been anything that could possibly address a badly written job posting.

With advancement in machine learning algorithms, that has become a possibility and Textio is the first company to leverage on that solely on improving your job postings.

 

What is Textio

Textio is an AI-powered intelligent text platform that predicts how well text will perform before it’s published.

And they are focusing only on job advertisements (They have recently moved into recruiting emails too.)

The AI will sift through the content of your job postings and make recommendations for edits based on what kind of language is going to appeal — or scare away — certain demographics. For instance, if you use words like “manage a team” or “proven track record,”

For instance, if you use words like “manage a team” or “proven track record,” Textio says you’re going to get more male applicants. Phrases like “passion for learning” and “develop a team,” meanwhile, will attract more women.

Phrases like “passion for learning” and “develop a team,” meanwhile, will attract more women.

And that’s just what it do and do only. Pure simplicity.

 

How To Use It

Again dead simple.

You simply feed it with the content that could be found in your job posting.

A textio score given to a test job posting

That includes:

  • Job Title
  • Type of jobs (e.g. Sales, Admin, etc)
  • Location
  • The job description

Based on my test-drive, the job title and location appears to make no difference.

And within seconds you would be shown a textio score and a summary of the good and bad of your job ad.

To make it easier for the user, words that require attention are highlighted. And they are done so in different colors to symbolize why they were highlighted.

 

How Does It Work

Textio synthesizes job text and outcomes data using listings from over 10,000 companies.

Their proprietary advanced algorithms will determine which jobs fill the fastest and generate the most applicant interest.

It uses a unique combination of machine learning, natural language processing, and statistical analysis to find patterns that work.

And it recognizes more than 60,000 phrases with its predictive technology and that data set is changing constantly as it continues to operate.

All that put together results in a score for the document, based on how likely it is to succeed in whatever the writer set out to do.

I did another one and this is an ad by Microsoft US, which is one of their customer.

MSFT Textio Ad

This one garner a much better 64 points compared to the earlier one.

I was expecting it to be closer to 100 points (which is the maximum) given that Microsoft is their customer.

It would be great if Textio could provide some examples of 90+ points job postings so users could have some point of reference to learn from.

 

 

Conclusion

With over 1,400 companies already using Textio to draw more qualified and diverse candidates, such as Twitter, Atlassian, Starbucks, Square and Microsoft.

In this on-going talent crunch that we are facing, every little bit helps.

And if you could fill an average of 20% faster than listings that haven’t gone through Textio (According to them), I find that worth a try.

You could get a 14-days trial via your initial registration.14-days trial via your initial registration.

Please note: I reserve the right to delete comments that are offensive or off-topic.