You can create customized keyword mappings to associate common terms used in candidate conversations with terminology found in your organization’s job feed. This feature makes it possible to better connect candidates' searches with the right jobs.

For example, the term “Cashier" is a common job keyword that a candidate would think to search by, but most organizations title their “Cashier” job requisitions as “Sales Associates” or “Customer Service Representatives.” With this feature, you can map these keywords together, ensuring that when a candidate searches for “Cashier”, Sales Associate jobs will populate.

Add keywords

To map keywords commonly used by candidates in job search to your jobs, users with full access to Client Setup can complete the below steps.

1. Select All Apps in the top left corner of the header and then Settings in its drop-down menu.
2. When the Settings page opens, select Client Setup under the Paradox Tools section.
3. Client Setup will then open. From the left panel, scroll down to and open the Job Search section.
4. Under the enabled Keyword Mapping setting, an Add a new keyword to map field will display. Input your job feed title into this field and then select Add.
   • Example: If you are trying to map associated keywords to “Sales Associate” in your job feed, this is where you would input “Sales Associate.” 
   • Note: Your keyword mapping title will populate the Job Feed Keyword field in the modal. This is to ease configuration time, but it is editable.
5. Select the field that the keyword will be pulled from in the job feed.
   • Examples:
     • If you want to target “Sales Associate” and this is found as a job title in the job feed, you would select the Job Title/Category option.
     • If you want to target “San Jose, CA”, then you would use the Job Location option.
   • Notes:
     • Job Title/Category is combined because the system treats the extraction of a job title from a candidate’s search phrase as either a job title or category. Matches to job title(s) in the feed will take a higher relevancy over matches to job category(s), as per our standard Relevancy Match Scoring.
     • Job Location allows the system to search for job city, state, and country. This field will run through location match normalization to ensure that the input is a fully validated location.
       • Location Validation Steps:
         1. NLP Location Validation: The inputted value will be validated using location checking within our NLP system.
         2. Google Places Validation: If our NLP system cannot validate the inputted location, it will run through Google’s location check.
         3. If the inputted location still cannot be validated with either of these checks, the input will error and the user will have to re-evaluate the input to ensure that it is an accurate location.
6. In the Associated words field, enter all of this keyword's related words based on common candidate phrases/behavior.
   • Example: I know candidates search for “Cashier,” “Checkout Person,” and “Customer Service Rep” when referring to “Sales Associates” at the organization, so those are the associated words that I’ll input.
   • Configuration Note: You can keep adding more keywords by hitting Enter/Return after every keyword you input.
7. Select Save in the bottom right corner of the modal.
8. Repeat steps #4-7 for each keyword mapping.
9. Select Save in the bottom right corner of the Job Search section.

Important job feed datapoint logic

The datapoints available to select from when mapping keywords is as follows:

• Job Title/Category
• Job Location
• Job Employment Type
• Job Status

For all but the Job Title/Category datapoint, it is crucial to input correct values for a successful candidate search experience.

Job Location

The Job Location mapping needs to be entered as an identifiable location. This means more complete location data: City, State; City, Country; or State, Country. This is to remove the ambiguity when mapping that leads to downstream impacts when searching.

For example:

• Job Feed Keyword = “Paris”
• Associated words of “Arlington” and “Savoy” are added
• Detection of either of their associated words will be replaced with “Paris,” but “Paris” alone is too ambiguous of a location, and the system cannot tell that the use is intending to map to “Paris, TX,” rather than “Paris, France” or “Paris, TN”
  • Because of this, the correct input for Job Feed Keyword should be “Paris, TX” in this case

Job Employment Type

The Job Employment Type mapping is a defined value in the system, meaning all data consumed from your job feed gets associated with one of the set values on the parameter. This means the two parameters will only accept the following values during feed processing:

• Full Time
• Part Time
• Contractor
• Temporary
• Entry Level
• Intern
• Volunteer
• Per Diem
• Seasonal
• Fellowship

Job Status

The Job Status mapping is a defined value in the system, meaning all data consumed from your job feed gets associated with one of the set values on the parameter. This means the two parameters will only accept the following values during feed processing:

• Hourly
• Salaried