A recruiter posts a job and wonders, "Are these all the qualified candidates?" On the other side, a job seeker runs a job search and thinks, "Are these all the available jobs?" How does anyone know?
Analyzing Job Postings Against Relevant Searches
One way to see how well recruiters and job seekers find each other is to compare a set of job postings against relevant searches that should return those job postings. I'll evaluate Indeed because they are the industry leader according to CareerXRoads, iCIMS, SEMrush, comScore, Compete, and Alexa. I will use job postings for Information Security Analysts as an example, and I will (1) build a list of relevant searches, (2) prioritize keywords, and (3) evaluate job postings against those keywords.
(1) Build a List of Relevant Searches
First, I build a list of job searches that should return "Information Security Analyst" job postings. I identify relevant searches using my thesaurus of job titles and O*NET's Lay Titles File. I pull search volume data for these searches. I use Google Adwords because Indeed does not publish search volume data. This results in 34 relevant job searches. When someone runs any of these searches, I assume that they would want to see "Information Security Analyst" job postings.
Cyber Security Jobs Network Security Analyst IT Security Professional Information Security Analyst IT Security Consultant Computer Systems Security Analyst Information Security Jobs Cyber Security Specialist Computer Systems Security Jobs IT Security Jobs Data Security Analyst Data Security Specialist Security Analyst Information Security Consultant Database Security Expert Network Security Jobs Information Systems Security Jobs Database Security Jobs Computer Security Jobs IT Security Specialist Information Security Advisor Computer Security Specialist Cyber Security Consultant Information Systems Security Analyst Cyber Security Analyst Data Security Jobs Information Systems Security Specialist IT Security Analyst Information Security Professional Information Technology Security Analyst Information Security Specialist Info Security Analyst Internet Security Jobs Internet Security Specialist
(2) Prioritize Keywords
Next, I create a prioritized list of keywords. Eleven searches account for 90% of the search volume. I make a list of the words used in the eleven searches. I ignore the word "Jobs" because it is ignored in searches. Eight words are identified as being relevant.
These eight keywords should be in every job posting for an "Information Security Analyst." If the word "Cyber" is missing, then the job posting will not show up in Indeed's search results when someone searches for "Cyber Security Jobs."
(3) Evaluate Job Postings Against Keywords
The final step is to see how well "Information Security Analyst" job postings include each of the prioritized words. I will identify the "Information Security Analyst" job postings as those that have the words "information", "security", and "analyst" in the job title. Therefore, all the job postings that I'm analyzing will have the words "information", "security", and "analyst", so I can ignore those three words. That leaves five words. Each word can either be included or excluded. This results in 32 combinations.
Because it is a bit technical, here is a link you can use to see how I performed my analysis of job postings. The analysis connects the percent of search volume to the number of job postings that use each combination of keywords. I run queries on Indeed, such as ...
... and note the total number of jobs returned. The first query returns the 4 jobs that have all five keywords. The second returns the 220 jobs that are missing cyber and specialist. The third returns the 58 jobs that are missing all five words. These numbers were out of 705 jobs that had the words information, security, and analyst in the t.... (Analysis performed in February, so your numbers may be different.)
The Result: The majority of Information Security Analyst jobs reach 30-59% of the relevant searches. If the final 10% were analyzed, the majority of jobs might reach 40-69% of relevant searches.
Interpreting the chart: I only analyzed the job postings for 90% of the relevant searches. Four job postings are included in 90% of relevant searches. If the final 10% of relevant searches were analyzed, the four job postings might be included in 100% of relevant searches. 294 job postings are included in 40-49% of relevant searches. If the final 10% of relevant searches were analyzed, the 294 job postings might be included in 50-59% of relevant searches.
This is the synonym problem. It has a solution: a thesaurus.
What the Mismatch means for Recruiters
In the short-term, recruiters have the opportunity to design their job postings to reach more job seekers and get more referrals. Recruiters can use better job titles and include relevant keywords in their job descriptions. They can use a thesaurus, such as my thesaurus of job titles, to identify effective job titles and keywords. My thesaurus is not perfect, but it is a step in the right direction.
What the Mismatch means for Job Search Engines
The game is not over. Indeed may be winning, but job seekers will use the site that gives them the best results. Just as Indeed surpassed Monster and CareerBuilder, another company could overtake Indeed. A well-known solution in the field of Information Retrieval is for a search engine to use a thesaurus with automatic query expansion. I do not understand why Indeed has not implemented it. If I can create a proof of concept using two laptops, a desktop, and a web hosting provider, a $1 billion company should be able to do it.
One thing is certain: It will be fascinating to see if recruiters or job search engines fix the synonym problem.