We Used Data to Prove Just How Long a Job Description Should Be to Attract Candidates
Searching for your dream job can be exhausting. People might look through dozens or hundreds of jobs postings in search of ones that stir their soul and inspire them to actually sit down to begin the process. Companies, eager to quickly get the attention of the most talented seekers, might nevertheless want to explain the specialness of both their culture and opening to attract the best matches.
When should a company strategically include detail in a job posting, and when is it best to be concise? To begin to approach this question using data, we plotted the word count distributions of all jobs posts ever featured on The Muse and grouped them according to type:
Within each group, parts of the plot that are widest correspond to the highest numbers of jobs with a given word count. We can see that posts for editorial jobs, for which skill with economical wording is perhaps highly valued, tend to be least lengthy. Job posts regarding “fundraising & development” are the most typically highly-worded, and also are quite broadly distributed in this measure.
Do long and thorough job posts get more or less “apply” clicks? To approach this question, we joined the data set above with each job’s “apply-clicks-per-unit-time” for all jobs posted on The Muse since we started tracking these data.
Interestingly, we find that this can depend on the type of job. For most categories there is no obvious correlation— job posts containing less than 250 words get about the same amount of clicks as those over with 1000 words. For jobs in social media, however, jobs under 750 words get about 2.8x more “apply” clicks than those above. The broader trend suggests that for social media jobs posts, like social media communication, short and to-the-point is most effective. For legal and education jobs, the trend is the opposite; job posts with over 750 words get about 1.9x and 2.0x as many clicks as those below, respectively. For these jobs, longer descriptions that explain an organization’s mission or special needs might help attract talented applicants.
Myriad data sources can be used to understand how to make matches in “HR-heaven” between seekers and employers. The development team at The Muse is working hard to analyze our data and operationalize this into products that meet clients and job seekers’ needs.
If you're excited about working on problems like these, please have a look at our open jobs page and get in touch.
Chris Ryan is a data scientist at The Muse. He loves writing code to discover stories told by patterns in data, and spent many years doing this for problems in biophysics before taking on his current role. When he's not doing that, he's often planning his next kitchen experiments, going to see bands play in remote parts of NYC, or trying to hold crow pose just a little longer.More from this Author