Finding new candidates by diversifying your recruitment methods can be a nightmare as there are often 100s of ways of describing precisely the same role. In fact, over the last year, we’ve looked at several thousand searches and in each case, recruiters are missing out on a straightforward technique to find more candidates.
So what steps can recruiters take to diversify their recruitment methods and how does it enable you to find new candidates effectively?
Strategies For Finding Free Candidates Across The Web
The ability to find free CVs is a valuable skill, particularly now that the free LinkedIn party looks like it’s over.
Here we’ll show you how to find candidate CVs that are on the web free of charge.
Indeed Candidate Sourcing
First up, use Indeed! I’ve lost track of the number of clients that use it for advertising but didn’t even realise they had a free CV database.
Indeed’s mission is global domination, so while it may not yet have the depth of candidates of a Monster, it’s got a decent pool that is growing by the day.
Niche Candidate Sourcing
Take “PHP Developer” for example. Every time we ever see a search looking for this, or any other kind of Developer, it will contain “PHP Developer”, then maybe a couple of other variations.
What’s never present is “Developer PHP”. A quick check on LinkedIn shows that adding this into your search will increase your candidate pool by 11% – a substantial increase for one small tweak.
On top of that, because the vast majority of Recruiters aren’t searching like this, the extra 11% are less likely to have been contacted than “PHP Developer” candidates – so more chance of engagement and getting them placed.
The reason why you achieve such good results with this technique is that a significant number of candidates will present their title and follow it with their key skill/area of expertise.
All of the below candidates were picked up simply by typing “Developer PHP” as LinkedIn will automatically exclude special characters and commonly appearing words such as ‘with’.
This technique isn’t exclusively for the tech world, it’ll work across most industries – here are a few examples:
So a really straightforward technique to find you more candidates, with a minimum of extra effort or training required.
X-Ray Techniques
Second up, you can use X-Ray techniques to uncover candidates and their contact details that you might not otherwise find.
Start by looking for CVs / Resumes. The inurl: operator does exactly what it suggests – searches within the URL (or address bar) for the words that you specify. In this instance, words relating to CV / Resume.
inurl:CV OR inurl:vitae OR inurl:resume
Then start adding the skills and locations you’d like to see. In this instance, we’re going to look for a PHP Developer in London, so start adding your Boolean search here. (Pro tip – you don’t need brackets or AND when searching on Google, but if you’re new to it, it helps avoid confusion)
inurl:CV OR inurl:vitae OR inurl:resume
PHP AND (Developer OR Programmer OR Engineer) AND London
As you can see, this gives us some false results such as templates, jobs pages, so we’ll start excluding those terms that are giving us bad results.
inurl:CV OR inurl:vitae OR inurl:resume
PHP AND (Developer OR Programmer OR Engineer) AND London
-template -sample -jobs
So now we’ve got some pretty reliable results, we can quickly and easily contact these people about vacancies. You’ll find that with different skill sets, the quality of your results will vary. If you find you get a lot of irrelevant noise, have a look at the words that feature that are irrelevant and just exclude them from your search, like we did with template.
To get even more results, you can remove the inurl: before CV, Resume, Vitae and it will return more pages. While this will increase the number of results you find, it will also increase the noise.
So the message is to adapt based on what you’re looking for!
Finding 50,000+ Data Scientists as an Example
One of the most sought after skill sets these days is the Data Scientist. Commanding high salaries and high fees, these candidates are worth their weight in gold, but a huge proportion of them are currently being missed.
Each of the hundred odd Analytics-focused Recruiters we’ve worked with tend to start their Data Scientist Boolean search with:
“Data Scientist” AND …..
A logical way of searching, but it misses a significant proportion of candidates who represent the same title differently – “Data Analytics Scientist”, “Scientist – Data”, “Principal Scientist”, “Lead Scientist” and countless other variations.
By searching just for Scientist, along with relevant keywords such as Hadoop, Python etc. that ensure you find Data Scientists rather than other types of Scientists, you’ll dramatically widen your pool of candidates.
As ever, this won’t just find you more candidates, but it will find you candidates who are being contacted less often and so are more likely to respond to your attempts to engage with them, increasing InMail and email response rates.
Here’s an example of how we found an extra 50,000 candidates worldwide with this technique, at the same time excluding anyone who calls themselves a Data Scientist, so as to only bring up people we might otherwise have missed.
As you can see, without even adding many data related keywords, we’ve brought up an extra 50,000 candidates worldwide. Not bad for a quick tweak of a search!
If you’d like to find out more about how SourceBreaker can find you 1000s more highly skilled candidates, please don’t hesitate to get in touch.
TL;DR Key Takeaways
- Searching for candidates with specific job titles can be limiting, as candidates may represent the same job with various titles.
- Diversifying recruitment methods can help find more candidates effectively.
- Indeed has a free CV database, which can be used to find candidates.
- Adding job titles with variations can increase the pool of candidates and provide a better chance of engagement and placement.
- X-Ray techniques can uncover more candidates and their contact details, making the recruitment process more efficient.
- Excluding irrelevant terms in Boolean search can lead to more reliable results.
- Searching for the keyword (for example “Scientist”) with relevant keywords (e.g. Hadoop, Python, etc.) can widen the pool of candidates and find more potential candidates who are less likely to have been contacted before.
