Have you ever wished you had a reference that would talk you through the basic building blocks of using Search Engines and Boolean?
The idea of using a Search Engine to find information about people is natural to some and a totally new idea to others. Search Engines like Google and Bing can be a valuable addition to your candidate sourcing toolbox.
When you have searched your database, checked the job boards and scoured LinkedIn, do you then turn to Google or Bing to access information available to all on the Internet?
This handbook aims to explain the basics of querying a search engine – add in your own industry knowledge and creativity and you should be able to track down anything (as long as it is out there in the public domain to be found).
We will start with AND, OR and NOT (the three Boolean operators) then look at other commands that will make your searches more targeted.
A copy of the handbook will be given to all attendees of tomorrow’s Talent Sourcing conference in London. If you are not coming along to the event then follow proceedings via Twitter using the hashtag #TSUK – if you are unsure what a hashtag is, then check out this guide to hashtags that we published earlier this month.
Last week I was the guest speaker at Reconvers’ Direct Sourcing event in London.
Jamie had asked me to show the group what sort of candidate information is out there on the web and freely available if you know how to look for it.
I gave a very brief intro to sourcing, and Internet research in particular, followed by a live sourcing demo, just to show what you can find with a little knowledge of search engines and boolean logic. I asked the recruiters in the room to give a profile they were looking for and I started a search there and then.
Example – Interim Datastage Consultant in Watford
One attendee was looking for an interim contractor specialising in an old IBM product called Datastage. This person would have to work in Watford.
I started by using Google Maps to look at the area surrounding Watford and choose some appropriate place names to include in my search – something like this might work:
(London OR Watford OR “St Albans” OR Slough OR “Hemel Hempstead” OR Cheshunt OR Enfield OR Luton OR Harlow OR “High Wycombe” OR Stevenage OR Dunstable OR Uxbridge OR Amersham OR Hatfield)
Then because we were uncertain how candidates might write Datastage, we included in our search string some different permutations. I also added some job titles to help us find pages that were mentioning people:
(datastage OR “data stage”) (developer OR programmer)
We’re now running into lots of job postings, so I look to take out some words that commonly appear on job ads. I also include words that will help us find people willing to work on a contract basis. Giving us a final boolean search string of:
(London OR Watford OR “St Albans” OR Slough OR “Hemel Hempstead” OR Cheshunt OR Enfield OR Luton OR Harlow OR “High Wycombe” OR Stevenage OR Dunstable OR Uxbridge OR Amersham OR Hatfield) (datastage OR “data stage”) (developer OR programmer) (interim OR contractor OR freelance) -job -jobs -vacancy -required
Because the key difficulty with this search is that we need someone still working with an old technology, we need to look for people that are using Datastage in their current role.
You’ll notice on LinkedIn profiles that your current job is listed separately to your past positions. So if we tell google to search linkedin.com for UK profile pages with the word “current” near to the word “Datastage”, we should get what we’re looking for.
“Current * Datastage” site:uk.linkedin.com/pub
Google brings us LinkedIn profiles that look relevant. You might also choose to add our list of place names onto this string to make sure you are getting people in the right part of the country.
I had an excellent question from the Reconverse crowd about using search engines other than Google. If you put the search query above into Bing then you get some great results on the first page, but not as many results in total.
I always recommend mixing up the search engines you use and trying your strings on more than one.
I use brackets (or parentheses) in my search strings above. This is purely to keep my own thoughts in order – Google actually ignores brackets completely. Bing does not ignore brackets, but that is a post for another day.
For more details of my “Live Source” – check out this video recording. Unfortunately you can’t see what I am typing or the results on the screen, but the audio, despite being quite quiet, might prove informative.
Check out the Reconverse website for more great events. I think the glass of wine to one side of the shot above sums up the atmosphere nicely! 🙂
I’m about to share one of the most common things that people don’t realise about Boolean searching.
Boolean logic covers the operators AND, OR and NOT. The name comes from English born mathematician George Boole – his work with algebraic logic is the basis of the modern computer.
When were you last nagged about using capital letters? When you were in Primary school? Not if you’ve recently been in a training session with me.
When using these Boolean operators with a Search Engine, like Google or Bing, it is important to capitalise them.
A Search Engine automatically strips small words like and, or, if, but etc. out of your query. It only searches for what it considers to be a real keyword. By capitalising AND, OR and NOT we make sure the Search Engine takes notice of them as a Boolean operator.
Most job boards do not enforce this rule, so if you don’t usually capitalise your ANDs, ORs and NOTs you have probably still been having success when you search there. I tend to capitalise these operators as a rule – then my string will work everywhere.
The only problem is, I now automatically capitalise OR all the time – not just when I’m searching – Doh!
It is important to understand a bit about search engines before using them to make very exact queries. Here’s a brief introduction. You might like to add your thoughts in the comments.
Search Engines are the most common means of finding information on the web. They find relevant information by matching keywords or phrases found in (and attributed to) pages on the web.
Search Engines build a database of text retrieved from web pages by automated software programmes called spiders. Spiders are configured to follow links around the web and collect specific information about the pages they find. The Search Engine then builds a database of all this information.
When you use a Search Engine, you are not searching a live interface to the web. You are searching information collected about web pages, saved in a huge database.
There are already billionsof pages on the web and some estimates say that there are up to 7 million pages added every day. It is therefore very unlikely that a search engine will ever index them all. No two search engines will have indexed exactly the same pages. There will be considerable overlap for heavily trafficked sites. So, to access even just 50% of the documents on the web, you need to use a variety of search engines.