Google's new service, Hire allows customized applicant tracking and optimized board postings, among other features. They’ve also modified the content visible for job searches, much to the chagrin of big job search aggregators like Indeed and Monster. But why?

Job Hunting Sucks for Both Companies and Candidates

If you’ve tried to hire or looked for a job recently, you’ve probably noticed that the market is ripe for that disruption. On the employer side, companies spend an average of about $4,000 per candidate on costs related to interviewing and assessment, even after advertising with recruitment boards like Indeed or Monster. This doesn’t include all the soft costs of time, wasted effort, and trying to close candidates who are entertaining multiple offers. It often feels like throwing money at a haystack in order to convince it to produce the needle.

For prospective employees, it’s just as bad. It’s not always immediately apparent from search results whether an available position matches your experience, fits your salary requirements, and is within a reasonable commuting distance. Recruiters frequently aren’t responsive, and candidates are sometimes relegated to a limbo of uncertainty about the positions for which they’ve applied. The uninformative job descriptions from a wide array of sources, poor interaction with staffers, and lack of feedback make for a truly frustrating experience. It’s so bad that 83% of candidates rate their job search experience as poor.

Bad Data Creates Bad Outcomes

Job descriptions are often outdated, inaccurate, or badly written. Many organizations even use internal jargon (“Revenue Specialist Level 2”), complicating a dense market in which hundreds of different jobs may all fall under the same sort of designation (“Sales Manager”). A lack of coherent industry standards has led to confusing inconsistencies, making it nearly impossible to find the kind of job you want.

Google has been paying very close attention to this problem for a few years now. As I’ve written before, around 40% of recruiters aren’t even required to respond to candidates at all. Most applicant tracking systems are old and not user friendly, and the HR technology in their Google Hire platform seeks to replace these outmoded systems. Additionally, Google changed how jobs appear in search results back in June of this year. They’ve allowed for structured data schema markups that pull in things like your company logo, the job’s base salary, its location, when it was posted, how long it’s valid for, and other descriptive information that candidates want to see.

Great. So, what is structured data, and how do I pull it into my job descriptions?

Structured Data Helps Humans and Bots

Structured data is a system that pairs a name and a value in order to help search engines like Google properly categorize and index your content. When a search engine looks at text or image files on your website, structured data informs the engine what kind of data it is: say, a person, a place, a set of concert dates, a creative work, or a product review. Each of these markups might have additional properties that describe the item in greater detail. A book might have properties like name, title, author, ISBN, or publisher. The schema helps inform engines what the data does, not simply what it says.

This data pulls through in the search results, which is incredibly helpful for the user. The evidence suggests that this additional, rich information directly improves clickthrough rate, which in turn indirectly elevates search visibility. It doesn’t require any additional coding skills, just adding the schema markup to HTML microdata. A full list of all the schema data markups is available at schema.org.

Station Four provided programmatic schema markup services for a large recruiting client recently, and the results speak for themselves. We compared three months of data since launch to the previous period. Application goal conversions went up by 6%, session duration increased by 30%, new sessions increased by 57%, pages per session increased by 13%, and bounce rate dropped by 10%. All from incorporating a few lines of code to each job listing. It’s amazing what actually letting users know what they’re looking at can achieve.

If you’d like to read more about our analysis of the current landscape of the staffing industry in Northeast Florida, check out our latest whitepaper here.