Tag Archives: boolean

3 Techniques for Candidate Sourcing Using Boolean Search

aaIt’s a normal tendency for recruiters to use Keyword Search when using databases such as Naukri or Monster, or when scanning profiles through LinkedIn and other social recruiting platforms. Here you insert some commonly applicable keywords relevant to the JD and expect good results to pop up. However, in most scenarios, after a certain point, you start observing that you are getting the same set of results and feel saturated.

In contrast, there’s another technique, which is less commonly used but much more efficient, and that’s the Boolean Search. Here you use keywords along with the operators such as:

  • AND
  • OR
  • NOT or – (minus sign), depending on the database being searched
  • ” ” (double quotes)
  • ( ) (parentheses)

Using boolean search, you are much more in control of what you are searching for and therefore widen your scope of finding newer results every time. While we can discuss the advantages of such search at length in another post, let’s discuss how you can make the most of this search. Here are some smart tips:

#1 X-Ray Search: Use Google Search to X-Ray any site having public profiles. For example, a very basic X-Ray search to find profiles on LinkedIn, for say a social media manager in Gurgaon, may look like this:

site:linkedin.com ("Social Media") (Gurgaon OR Delhi OR Noida) -inurl:jobs

What this does is – it looks for all the profiles on LinkedIn who have social media and either of Gurgaon, Delhi, or Noida mentioned on their profile page. The last part “-inurl:jobs” instructs Google to exclude all the results which are job postings, giving better filtered results.

Note that we have used all the boolean operators here except “AND”. This is because Google considers blank space as AND by default.

Various complex variations of the above seemingly simple search format are possible. Try Googling to learn more!

The best part of X-Ray on LinkedIn - you get more flexibility in the number of searches you can conduct than what you can through the LinkedIn’s inbuilt search box before you reach the commercial limit. Nice workaround, right? :)

#2 Spider Search: It’s a technique where you look for profiles which are similar to a specific candidate profile.

For example, while searching on LinkedIn, if you land up on a relevant profile, look at the sections “People Also Viewed” and “People Similar to” on the right. There are very good chances that these sections may give you some more relevant results. Continue the process i.e., going from one profile to another under these sections, till you start getting completely non relevant results.

Paid databases like Naukri.com provide a similar feature called “Similar Resumes” which is again very useful.

#3 Pin Code Search: Not very commonly used, but can turn out to be a great time saver in certain scenarios. Consider, for a certain position, you want to source candidates who are located within 5 kms or 10 kms of the company’s location, how will you do it?

While in Naukri / Monster you can do a city specific search, unfortunately there’s no option to filter by locations within a specific city. There’s a smart workaround though:

a) Identify the company location on the map

b) Mark all the areas that fall within the 5 km/ 10 km (whatever applicable) range

c) Put the names of all those areas ORed in the boolean search in the database

OR a much efficient and convenient approach would be to

c) Put all the PIN codes covering those areas in the boolean search

and Voila, you get the filtered profiles of candidates who have mentioned the specified PIN codes in their correspondence address.

I hope you’ll use the above techniques and benefit from them, and if you’re already using them, would love to hear your experiences. Feel free to add more techniques in the comments below!

About the Author: Vineet Arora is the Chief Executive of TalentNiti, a boutique talent search company catering to IT, Hi-Tech, and Consulting/Research sectors. He can be reached at vineet@talentniti.com.

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