How to attract remote candidates using structured data & Google Jobs

How COVID-19 changed the way we work

In early 2020 the world was hit with the unexpected – a Global Pandemic. By March, widespread lockdowns were rolling out and companies were required to adapt to this new normal seemingly overnight. 

For business to continue, many organizations that were mostly, or even entirely office based needed to convert their workforce to be entirely work from home for the foreseeable future.

Per Google Trends, interest in work from home jobs has remained fairly steady over the past 3 years. Popularity spiked in March of 2020, and has continued to have more interest compared to previous years.

The remote workforce trend

As 2020 went on, and employees continued to work from home, a few things came to light for many businesses:

1. With the right tools, employees are able to work just as effectively at home as they could in-office
2. Not requiring an office space (or securing a smaller office space) is excellent for a company’s bottom line
3. Remote working gives Employers access to a greater pool of potential employees, as location is no longer a limiting factor

At any company, when a position becomes available, the goal is to ultimately fill that position with the best possible candidate. By lifting the restriction of location, Employers have access to a much larger pool of candidates – if they know how to reach them.

The most efficient way to attract top tier talent is by using Google Jobs.

What is Google Jobs and how does it work?

Google Jobs is a massive job posting aggregator, first launched in 2017. It uses artificial intelligence and machine learning to crawl qualified job postings on other websites, and then displays them to Job Seekers right in Google’s dashboard. Google jobs is an excellent tool for both Employers, and Job Seekers.

Optimizing for Google Jobs requires implementing Structured Data in the page’s html. This optimization allows the job posting to appear in Google Jobs, massively increasing the potential visibility of the open role. So Employers no longer need to rely on potential candidates to find the job posting on their website, or pay for the job posting to appear on a third-party job listing website.

While many Employers have implemented Structured Data so their job postings appear in Google Jobs, they have failed to make updates to the Structured Data for remote specific jobs. This oversight leads to the job postings not being seen by thousands of potential job candidates. 

Structured Data for remote jobs

Two years after the initial launch of Google Jobs, Google announced the ability to mark up jobs that are work from home. With the COVID-related boom of remote working, it is now more important than ever for Employers to remain competitive and ensure their remote job postings are being seen by the best job candidates. 

To increase a job posting’s reach and be displayed as a remote position in the Google Jobs dashboard, additional Structured Data is required. 

There are two properties to include that will help Google understand that a job is remote:

1. “jobLocationType: TELECOMMUTE” Use this property to specify that the job is remote
   
2. “applicantLocationRequirements:” Use this property to specify which where the remote job needs to be performed

In the image above, the additional Structured Data makes it easy for Google to understand that this job is completely remote, and can be done anywhere in the USA.

With that information, Google is now likely to show the Employer’s job posting to Job Seekers all across the country, instead of only to Job Seekers who are located in the area that Google associates the hiring organization with. 

Case studies

Below are two case studies that demonstrate the value of implementing remote job Structured Data onto job listings. Clients A and B are both in the staffing industry and rely on Google Jobs as a traffic source. Both clients had already implemented standard Structured Data for job postings, and then added the additional Structured Data to remote jobs in August of 2020, shown in the images below with a vertical red line. 

The provided images are screenshots of each client’s Google Search Console Impressions, filtered for “Job Listings” as the Search Appearance. 

Client A

Client A Overview: Has approximately 1,800 job postings available at any given time. All job postings are for remote positions. 

Date Implemented: Remote job Structured Data added to all job postings August 5th 2020.

Results: By two months post implementation, Client A experienced:

• 383% Increase in Impressions of Job Listings
• 315% Increase in Clicks on Job Listings
• 78% Increase in Entrances to the website from Google Jobs
• 79% Increase in Conversions

Client B

Client B Overview: Has approximately 35,000 job postings available at any given time. Roughly 5% of total job postings are for remote positions.

Date Implemented: Remote job Structured Data added to all remote job postings August 10th 2020.

Results: By two months post implementation, Client B experienced:

• 103% Increase in Impressions of Job Listings
• 115% Increase in Clicks on Job Listings
• 46% Increase in Entrances to the website from Google Jobs
• 53% Increase in Conversions
• 4% Increase in Conversion rate
  

Summary

Removing location as a hiring factor provides Employers access to a much larger hiring pool, theoretically giving them the ability to cherry pick the best available candidates. 

However, in order to have access to these top tier candidates, ensuring that job postings are visible to as many Job Seekers as possible is critical, and this is where work from home Structured Data comes in. 

When hiring for remote positions, Employers and staffing agencies alike, should be implementing work from home Structured Data across all job postings, in order to attract top remote talent.