I just did the free trial and pasted in a current JD I have on some job boards. The user interface is nice and easy to use. I like that I was able to make updates and it would show my improved score in real time. However, now that I have improved one of my JDs, I will use that knowledge to improve the rest. So I feel like I have received all the value already present from the product. I'm not sure there is enough of a draw to spend $99 a month to check the content of my JDs. Also, I wish that it would give me suggestions for female oriented phrases as my JD uses 100% male language. I can't just come up with female phrases, I'm a guy! Overall, I like the product and I wish overall it had more advice to give in helping improve my recruiting process.
Yeah, but if each job ad is costing you, conservatively, $10K in time, labor & recruiting costs to fill, are you really going to quibble over $99 a month? Even if it can only improve the ad 1%, it still seems worth it.
Not for large companies, but for startups this type of mentality is dangerous, not because of the $100 per se, but because all these little things add up quickly to a big burn rate.
I find the categorization of masculine and feminine words in this tool to be very presumptuous.
This is what I got from a few random JD samples.
Masculine Words
- manage
- manages
- under pressure
- best-in-class
- whatever it takes
- drive to
- exhaustive
- overseeing
Feminine Words
- community
- interpersonal
- be part of
- serves
- strive
- care
- encourages
- connection
- helpful
- comfortable
Isn't this just enforcing false assumptions about gender differences rather than preventing gender bias? Who is to say that women don't want to oversee, manage, or have the drive to be the "best-in-class"? Who is to say that men aren't interested in fostering community, working in teams, being helpful and caring?
Pretty interesting study that proves that gendered wording of applications actually makes a significant difference in the gender ratio of folks who apply. The gender biases we've been socialized with might be false assumptions many times, but it's still the programming many people operate on.
This is a really interesting study. But I wouldn't assume correlation implies causation here.
Just because there are more male or female applicants to job postings that contain specific words does not mean the words themselves are attracting certain types of applicants.
Many of the masculine words are words associated with higher-level management and higher pay jobs. There are less women who make it to this level so naturally there are less women applicants to these types of jobs.
Jobs associated with the feminine words such as "caring" and "serves" tend to be lower-level service-oriented jobs. Women don't apply to these because they are attracted to the words. They apply to them because more women are in the economic position to apply to these jobs over high-status high-skilled jobs because of historical and societal issues.
I'm not sure categorizing these words as masculine and feminine is doing anything more than reflecting the existing gender-imbalance in labor although it is interesting to think about how this knowledge could be used constructively.
Did you read the whole paper? They control for the type of job in the multiple studies conducted in this paper - the job same job is advertised with differently worded postings. They also ran tests with male-dominated professions, female-domainated professions, and neutral professions - the result was the same.
I was skeptical when I started using the product; I've been hiring for nearly two decades and figured that the company's algorithm wasn't going to be able to improve on my experience. Now I'm pretty sure I was wrong. The suggestions make sense and are, for the most part, clearly improvements. I've had readers look at "before and after" without knowing which is which and they uniformly prefer the "after".
I strongly recommend trying the free trial out, if it's still available, and seeing for yourself. I find it well worth the $99/month.
I wish recruiters would use this to revise their InMail messages... if they saw their whole email highlighted in red "very negative, corporate jargon" perhaps there would be fewer spammers out there.
I'm a writer and consider myself to understand people pretty well, so I didn't think I'd benefit. Lo and behold, my JD scores were 80ish. Not terrible, but room for improvement. I re-wrote 5 of them using the tool and not only were they so much shorter and more compelling, but I got many more applicants from a bigger pool w/o having to use a headhunter (which is a huge cost savings by itself). We are now using this to re-write all of the JDs in my bigger org.
One other thing I'm going to do is use the tool for a bunch of our website copy. That's not quite the same as JDs, but I do want to understand the "tone" we're using.
I have access to and have been performing detailed analysis of a much much larger data set than they have access to. Location, salary, which job boards you use, and how high you come up in the rankings of which job boards you post to will have an effect that absolutely swamps their "magic number".
When someone has a proprietary number that they show you to describe something - "Textio Score", "KLOUT NUMBER", etc, you're being sold snake oil.
There may not be an alternative, but that doesn't mean it isn't snake-oil. (It doesn't mean it is either. Those two things are independent)
But, what he's saying has a good point, whether or not textio is snakeoil: it's better to have numbers other people can compare to, even if the method for determining those numbers isn't made public.
Mostly turned we statements to you statements, softened some language (should vs. must,) went a little more gender neutral (premier vs. top tier,) and added an equal opportunity statement. It is recommending to use longer sentences and add more you statements to improve further. Thoughts?
I had the same question. If they truly have job ad & outcome data from 10,000 companies, I feel like they could build a lot more interesting things than a fancy word processor.
One thought I have of where it might come from is some other job sites list how many people applied for a particular job. If they scraped that information plus the job posting they could gather this type of data pretty quick.
But, if that's the case, then that's measuring the wrong thing. In many ways, a lot of applicants are an anti-signal. It means you're spending time sifting through a huge haystack searching for that 1 needle. Ideally, they have data on like, the 5 year performance review for the candidate hired or something like that which is why I said I have no idea how they would get such data.
That depends on what question you are trying to answer. To get a lot of people to apply is one metric. You seem more concerned with the quality of the applicants which is fair enough but it's implied yourcvio or human beeings will take care of that part. I could still see some use for this even if I wouldn't pay too much attention to the score itself.
Yeah, I wonder about the gender discrimination too. So a plurality of men/women, at this point, are more likely to apply if you emphasize certain words. But won't that keep changing? The dataset isn't going to remain static, especially for non-overt language. (Their website mentions women prefer premier to top tier, and I remember reading the same about expertise and specialty).
Most people now get that synergy is a terrible word. But they'll just replace it with something that won't show up on the radar until it seriously starts putting people off.
And, if they do have access to such a rich dataset, why not be more precise, as someone mentioned? Find out what kind of listing is most likely to appeal to a networking person who is looking to switch into dev ops.
Are you aware that your front page has "more women will apply" highlighted in a colour that looks almost identical to your negative highlight? I only saw the difference when I looked at the images full res.
