Posted April 03, 2019 by

How to optimize your job posting ads in the era of Google for Jobs and Google Cloud Talent Solutions

College Recruiter was one of the first job boards to replace its proprietary job search technology with what is now called Google Cloud Talent Solutions (CTS).

We went live about 15-months ago in January 2018 and have been very, very happy. As I discussed on a recent episode of The Chad and Cheese Podcast, the results we’ve seen have been superb: far more candidates searching far more jobs and far more applying to those jobs. In addition, our costs have plummeted because we’re saving a ton of development and customer service time.

But the transition has also been eye opening to us in terms of pretty minor adjustments that very few employers are either aware of or are willing to make yet which would yield great results for them. Here are just some:

  • Include compensation, even if it is a range. Most employers are still reluctant to disclose compensation range because, they typically claim, it undermines their ability to negotiate with the candidate. That reveals a problem with their negotiation skills and that’s understandable, but fix the negotiation skills. Some employers want to underpay employees and that’s why they don’t want to reveal the salary ranges, but it isn’t 1952. Employees can easily find out if they’re fairly paid and those who aren’t will become disgruntled and leave, which leads to a lack of productivity and so any money they may have saved in wages will more than be offset by the productivity issues.
  • Include street address, city, state/province, postal code, and country for every job. If the jobs are remote, denote that in your location field using a word like “remote” so that Google can easily identify those. Without the street address, Google has a harder time figuring out the exact location of the job and that leads to problems with the new commute search feature. College Recruiter built a bunch of code to get around this problem, but few job boards will do that. If we don’t get the street address, we use the Google Maps API to look-up the address and then we feed that to the CTS API, but some employers have multiple locations in a city and so our look-up may identify the wrong location. Also, some employers don’t have every location listed in Google Maps, such as those who have field offices. If your field office isn’t listed, then a Maps API look-up won’t work properly. Our search is now commute time driven rather than location driven. With Google CTS powering 4,000 job boards and ATS sites, the days of looking at candidates looking at location and inferring commute time are, thankfully, quickly coming to an end.
  • I know from The Chad and Cheese Podcast that Chad Sowash and Joel Cheesman hate the use of words like “ninja” in job descriptions and that’s fair, but the use of those words isn’t a problem if the employer also uses more standard language like “sales representative.” The standard language will allow CTS to infer what the job is about, and it is amazing how accurately CTS does that.
  • For years, Joel and other SEO experts have tried to convey to employers and others that they need to think of a job posting as a web page and that web pages need to be SEO optimized. That’s still the case, but isn’t as critical as it used to be because Google is smarter than it used to be. Still, the most important signal to Google and therefore to job boards and ATS that use CTS about what the job is about is the job title. Do not use internal jargon like SE II to refer to a Software Engineer Level 2. In fact, don’t refer to “Level 2” at all because that’s only meaningful internally. Use for the job title language like, “Software Engineer Team Lead” as that’s more meaningful externally. If your lawyers tell you that you need to use SE II, well, get new lawyers or stop lying about what they’re telling you as that’s bullshit. Second, use the internally approved language in the body of the job description but use externally accepted language in the job title field.
  • Think about Amazon recommendations when writing a job title. If you like A, you’ll also probably like B. Include language like that in your job descriptions. “If you like math, then you’ll love this job as our programmatic job ad buying manager”. Google will understand that someone who searches for jobs using the keyword “math” should be shown that job because of the keyword, but it will also understand to show that job to someone who searches for jobs using keywords like statistics and physics. This is starting to happen. One of our employer customers is hiring hundreds of people for a maintenance technician job and they started to see respiratory therapist applying. They interviewed some, hired some, and want to hire more. I didn’t get the connection until they told me that respiratory therapist know how to operate machinery and that’s what the technicians do.
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