I define E-sourcing as leveraging information systems for active talent identification – searching the Internet, social media, job board resume databases, and applicant tracking systems to find candidates. The proper use of technology in the sourcing and recruiting process should increase your efficiency, productivity, and effectiveness.  I’ve created the SlideShare presentation below to cover a number of different ways for you to maximize your ability to find more of the right people more quickly, to accelerate and enable your recruiting efforts.

Click on the presentation below to review:

• Boolean operators and common query modifiers
• Searching LinkedIn, Twitter, and Facebook
• X-Ray searching Social Media
• Search automation and aggregation
• Semantic search: manual and artificial intelligence matching solutions
• Search ROI – a comparison of the searchability and data depth of the Internet, Social Media, Resume Databases, and ATSs
• Talent Warehouse concepts

BEWARE: This post takes a contrarian (yet fact-based!) view of the Internet as a sourcing tool that may be unsuitable to some readers. If you don’t want to hear anything other than how awesome the Internet is for sourcing and recruiting, please stop reading now. 

The Internet has Free Resumes – SO WHAT?

Okay, so you can find free resumes on the Internet.  So what? What’s the big deal?  The fact that the Internet is free? While free is nice and certainly can’t be argued with, I am sure you have also heard that you get what you pay (or don’t pay) for. Or if it’s too good to be true – it is.

So let’s take a look at what you get for free on the Internet:

Not a lot of resumes

If you are a sourcer or recruiter I am sure that at some point in your career you’ve read somewhere or heard someone say how the Internet has 10X the number of candidates that can be found on the online job board resume databases. I’ve always taken that for face value because, to be honest, it’s really tough to prove or disprove such a figure/statement. However, I am a bit of a skeptic and I don’t just accept what I read or hear at face value – especially grandiose statements/claims, so I’ve taken a critical look into the matter.

While you may be able to find more names/people on the Internet than you can find on any given internal (corporate) resume database or the major online job board resume databases such as Monster, Careerbuilder, etc., the Internet does NOT have more RESUMES, even when it comes to the most common job titles and roles. 

In fact, I’ve found that the Internet has in many cases at least 10X FEWER RESUMES than you can find even on ONE major job board.

Sound crazy or impossible? Would you like some apples-to-apples comparison searches in specific locations comparing the number of resumes you can find on Monster vs. the number of resumes you can find on the Internet via Google? You’ve come to the right place – here are two posts/search exercises that illustrate this point dramatically: Monster vs. the Internet Round 1, and Monster vs. the Internet Round 2.

What’s that? You don’t need resumes to find people on the Internet? Yes, you certainly don’t need resumes to find great candidates – you can search blogs, user groups, company directories, conference attendee lists, etc., and find lots of people. Unfortunately, in most cases, without a resume we can’t reliably determine exactly where these people live (kinda helpful to know), how much experience they have (or how recent it’s been), or what they have been specifically responsibile for. For a detailed analysis – read this post on the intrinsic benefits and advantages of resume database recruiting over any other method of talent identification.

Unstructured data

A database is a structured collection of records or data. Structured data enables more accurate and targeted information retrieval. The Internet is NOT a structured collection of records or data – it’s unstructured, and as such, the Internet is by its very nature an impendiment to targeted and accurate information retrieval.

This can be especially challenging when trying to find people in a specific location, because the Internet is not designed to allow you to do so. Most people try and search for area codes, states (spelled out or abbreviated), or even get more creative and use Google’s numrange functionality and attempt to target zip codes, but any way you slice it – Internet search engines don’t know that you’re looking for area codes, zip codes, or even specific states. So you often get lots of false positive results – hits with the numbers OF the area codes or zip codes, but the numbers themselves are not actually area codes or zip codes. You can also get false positives of pages that happen to mention your target city/state, but the person referenced doesn’t actually LIVE in that city/state.

Trying to specifically target resumes is equally fraught with peril. You can try using the (intitle:resume OR inurl:resume), but then you miss people who do not title their resume as “resume.” If you DON’T use (intitle:resume OR inurl:resume), you open yourself up to a LARGE amount of false positives, even if you try and eliminate job postings and other annoying false positives. This is again due to the fact that the Internet is not a structured database, and no matter WHAT you put in your search strings, the Internet search engines don’t know what you’re looking for. In effect, sourcers and recruiters using the Internet to find resumes are actually performing “work-arounds” in that they are creatively applying search operators and symbols to make the Internet return results they’re looking for, even though neither the Internet nor the Internet search engines were designed for sourcing and recruiting.

A poor search interface

Yeah – I said it.

Yahoo, Ask, and Google don’t even support full Boolean logic. Come on. Performing text-based search without full Boolean logic is like performing surgery with a butter knife – crude and imprecise, and some things simply can’t be accomplished.

MS Live supports full Boolean logic, but has no wildcard/stemming/truncation search. And while Exalead supports full Boolean logic as well as wildcard/stemming AND fixed and configurable proximity searching (WOW!) – it indexes a small fraction of what the other large Internet search engines do. Sigh. Can’t sourcers and recruiters catch a break here?

ALL of the major job board resume databases support full Boolean logic, and Monster supports fixed proximity with the NEAR operator. While they of course have the advantage over the Internet of being designed soley as resume databases – their search interfaces are well ahead of most Internet search engines. Am I the only recruiting professional that loves to leverage the asterisk and be able to use the NOT operator on a parenthetical statement?

Anyone who has used a full-featured text search engine that supports not only standard Boolean logic, but also extended Boolean such as configurable proximity and variable term weighting (such as Lucene or dtSearch) on a structured database can tell you that in comparison – using Internet search engines is like trying to tie your shoe laces with mittens on…while handcuffed.

And of course Internet search engine interfaces don’t allow for reliable location-specific searching. This is compounded by the fact that as stated previously, the Internet does not structure any data, let alone location-specific information.

Irrelevant results

Google uses their PageRank link analysis, among other things to determine “relevance,” which has NOTHING to do with the relevance of a potential candidate’s qualifications based on a search. In fact, it’s inherently flawed in that a person who happens to have created their own website and has posted their resume on it may not have ANY links to it, so Google will interpret it as a result of low relevance.

Yahoo and other search Engines do not appear to disclose their relevance ranking/sorting methods – so who really knows what they think are relevant results? Also – am I the only one that thinks it’s ridiculous to get 2.5 million results from any search? Any guess as to how many are actually RELEVANT?

The very fact that the Internet is not a structured database of people makes it intrinsically difficult to get relevant results from any search – the Internet has tons of garbage on it. Trying to look for the term “resume” or “CV” pulls many false positives, as does any search for location-specific information such as area codes, states, or even 5 digit zip codes simply because there is so much STUFF on the Internet, and it doesn’t know what you’re looking for.

No competitive advantage

The Internet is free – anyone with an Internet connection can search it to find people and resumes. While there is no denying that some people are more proficient at searching the Internet, everyone has access to the same information – and there aren’t even that many resumes on the Internet to fight over. I don’t see that as a competitive advantage of any significance.

Even major online job board resume databases offer more competitive advantage than the Internet, because they cost money and not every person or organization pays for access to even 1 job board resume database. Plus – they all have decent search interfaces/engines.

Any recruiting or staffing organization of any significant size should have an internal resume database that affords them a TRUE competitive advantage – access to a large number of unique candidates that other people and organizations do not have (any and/or easy) access to, stored in a structured database with a powerful search engine that supports full (and ideally extended) Boolean. 

Conclusion

• It doesn’t have many resumes
• It’s unstuctured data
• It’s intrinsically difficult to find people in specific locations
• It’s intrinsically difficult to find people with specific experience and qualifications
• It has poor search interfaces
• It has TONS of irrelevant results
• It does not afford any significant competitive advantage

Before some readers cry “blasphemy!” – there is no denying that you CAN leverage the Internet to find fantastic talent – everyone knows that. But let’s not conveniently overlook the fact that using Internet search engines to locate people with specific skills and experience that live in targeted areas is intrinsically difficult due to the fact that you are using Internet search engines as well as the Internet in a manner that they were not specifically designed for (targeting people that live in specific places with specific experience and qualifications). Finding SOME people on the Internet is easy, but consistently finding a solid quantity of the RIGHT people is definitely not.

Because of this, using the Internet via Internet Search Engines for sourcing and recruiting has an intrinsically low ROTI (return on time invested). But hey – don’t blame the Internet or the Internet search engines. That’s like getting upset because your blender/food processor isn’t effective at mowing your lawn.  

If you only need to find a handful of the right people every month, perhaps the Internet alone, with all of its intrinsic limitations, can still fulfill all of your hiring needs. Regardless, there ARE and more effective methods and technologies available.

What really drives me crazy is that I feel that most people don’t even know how to effectively leverage their own internal resume database or even the online job boards if they have access to them - where they can run more precise searches and find more people who live in targeted areas that have specific skills and experience and enjoy a much higher ROTI - yet they spend lots of time searching the Internet where it’s harder to find specifically qualified people in targeted locations and there are less of them to reliably find in the first place.

I’d argue that every sourcer and recruiter leverage ALL resources available to them – but I believe they should START with the rousources that produce the highest ROTI first, and then work their way backwards from there.

I’ll end this post with an analogy:

If you were in the oil prospecting business, would you choose to specifically target and utilize technologies and methods that made it intrinsically difficult to find oil deposits?  And would you specifically target areas where you know there isn’t much oil in the first place and where everyone else has already searched and picked over?

Think about it.

Boolean Contest – come one, come all!

Irina Shamaeva and I were chatting a few weeks back and she asked me if I thought a contest focused on Booolean strings would be a good idea. You can imagine my reaction – “Of course!” She thought offering prizes of ResumeFinder or ResumeGrabber would be a great idea, and Chandra Bodapati, CEO of eGrabber, was gracious enough to offer his fantastic products FREE to the winners!

Here are the Official Rules of the Worldwide Boolean Strings Contest – 2008, sponsored by eGrabber

The contest starts on Tuesday December 9, 2008 and ends on Sunday December 21, 2008.
To participate, you need to complete three steps.

1) Post one new discussion item either on the “Boolean Strings” group on RecruitingBlogs or the “Boolean Strings” group on LinkedIn.
(Your post can be a tip, a question or a reply to somebody else’s question. Post between 12/9/08 and 12/21/08.)

2) Download and try ResumeFinder and/or ResumeGrabber.
(This step is optional but you get one bonus point for this.)

3) Answer questions in this Quiz.
(This is a multiple choice quiz on your mastery of Boolean Strings.)

The contest will have multiple winners! One person for every 25 participants will get the tool of his/her choice, ResumeFinder (a $349 value) or ResumeGrabber (a $495 value).
Plus, eGrabber will offer one month subscription to ResumeFinder to everybody who participates in the Contest! Check the box at the end of the quiz and you will receive a ResumeFinder product key.

The winners will be announced on Tuesday December 23. The top winner will get the title “Boolean Strings Master – 2008″. If you have any questions or comments please email us at contest@booleanstrings.com

Good luck, and good Boolean!

While surfing through the discussions in the Boolean Strings Group on LinkedIn, I stumbled across someone asking for search advice on how to create effective Boolean search strings to find sales professionals and I offered some suggestions – which I will expand upon here, covering resume databases as well as leveraging LinkedIn via Google using the site: command.

Monster, Careerbuilder, Hotjobs, Internal Resume Database

Here is a “core” title-based search that can be used on any resume database that recognizes standard Boolean:

(sales or “account executive” or “account coordinator” or sales rep* or “outside sales” or “inside sales” or “sales consultant” or “business development” or “account development” or “sales executive” or “sales associate” or “account manager”)

In addition to the title-based search, you can add activity-related keywords to experiment and refine results:

(sell or sold or phone or call or called or calls or client* or customer* or clos* or cold or business or lead or leads or prospect*)

To further refine your results, you could add achievement-related keywords, such as:

(increased or lead or led or top or highest or most or exceeded or quota*)

You could add them all together and run this Boolean search string:

(sales or “account executive” or “account coordinator” or sales rep* or “outside sales” or “inside sales” or “sales consultant” or “business development” or “account development” or “sales executive” or “sales associate” or “account manager”) and (sell or sold or phone or call or called or calls or client* or customer* or clos* or cold or business or lead or leads or prospect*) and (increased or lead or led or top or highest or most or exceeded or quota*)

That’s 459 characters with spaces – it will fit and run on Monster and most ATS’s.

Here’s an example of a result from an online job board:

LinkedIn via Google

Moving on to LinkedIn, we could start with a search like this one using Google, targeting Houston:

site:linkedin.com (~sales | “business development”) (~increased | ~lead | ~top | ~ highest | ~most | ~exceed | ~quota) “Houston, Texas Area” -intitle:directory -inurl:updates -inurl:updates

That gives you nearly 18,000 results.

You can further narrow your results by searching for specific industries.

For example – targeting the Oil & Energy Industry:

site:linkedin.com (~sales | “business development”) (~increased | ~lead | ~top | ~ highest | ~most | ~exceed | ~quota) “Houston, Texas Area” “Oil & Energy” -intitle:directory -inurl:updates -inurl:updates -inurl:jobs -inurl:companies

That narrows it down to 688 results.

You could also try and eliminate managers and directors, like this:

site:linkedin.com (~sales | “business development”) (~increased | ~lead | ~top | ~ highest | ~most | ~exceed | ~quota) “Houston, Texas Area” -”manager” -”director” -intitle:directory -inurl:updates -inurl:updates -inurl:jobs -inurl:companies

That search produces 767 results. Here is a sample:

Coupling Oil & Energy and non-managers/directors into one search:

site:linkedin.com (~sales | “business development”) (~increased | ~lead | ~top | ~ highest | ~most | ~exceed | ~quota) “Houston, Texas Area” “Oil & Energy” -”manager” -”director” -intitle:directory -inurl:updates -inurl:updates -inurl:jobs -inurl:companies

That search yields a manageable 121 results.

Anyone need any sales professionals?

I was reading a discussion in the Boolean Strings group on LinkedIn and someone was having difficulty in locating a bilingual (Spanish) WAN Engineer in the Denver, CO area. It sounded like as good of a challenge as any, so I decided to take a crack at seeing what I could find by searching the Internet via Google, LinkedIn, Monster, and an internal database.

As a first swing, I crafted this search that can be run on any resume database recognizing basic Boolean (internal database/ATS, Monster, Careerbuilder, etc):

(WAN or “Wide Area” or ATM or Frame) and cisco and router* and (senior or lead or architect or engineer) and network* and Spanish and (fluently or fluency or fluent or native or bilingual or bi/lingual or “bi lingual” or language* or conversational)

Monster yielded 26 results in a 30 mile radius from Denver.

My internal resume database turned up 166 results in Denver specifically. It pays to have a Talent Warehouse.

As for the search I chose to begin with – while not everyone will mention descriptive words such as “native,” “fluent,” or “bilingual,”  it is a good idea to start there because it nearly guarantees fluency.  

After you exhaust those fluency-related words,  NOT them out to find people who simply mention “Spanish” and sort through them. For example:

(WAN or “Wide Area” or ATM or Frame) and cisco and router* and (senior or lead or architect or engineer) and network* and Spanish and not (fluently or fluency or fluent or native or bilingual or bi/lingual or “bi lingual” or language* or conversational)

Using the site: command via Google to search LinkedIn, I went with this search:

site:linkedin.com (WAN | “Wide Area” | ATM | Frame) cisco ~router  (senior | lead | architect | engineer) ~network Spanish “greater denver area” -intitle:directory -inurl:updates -inurl:updates

That yielded 0 results. Once i took out the Spanish, I got 42 tight results.  So the limiting factor is the word “Spanish.” 

Sourcing LinkedIn can be a challenge because LinkedIn is not a resume database.  Most people do not fill out their profiles completely when it comes to their employment history, and even those that do don’t often provide much detail or information.  I am not surprised at all that there are not many people who mention that they are bilingual on their LinkedIn profile.  LinkedIn is a great source of talent, but it is typically a low yield source of highly specific talent.

I then moved on to running a search on Google to see what I could find on the Internet: 

(intitle:resume | inurl:resume) (WAN | “Wide Area” | ATM | Frame) cisco ~router  (senior | lead | architect | engineer) ~network Spanish 80001..80640 -~job -~jobs

That search yielded 2 results, 1 of which is in Denver, and he’s a TS cleared CCIE. Sweet.

Switching it up from a zip code range to area codes, I ran this:

(intitle:resume | inurl:resume) (WAN | “Wide Area” | ATM | Frame) cisco ~router  (senior | lead | architect | engineer) ~network Spanish (720 | 303) -~job -~jobs

That search only yielded 1 result, which was non-local.

This exercise clearly illustrates the point I try to make over and over – for highly specific hiring profiles (and I don’t limit this to rare skills – just highly specific) – the Internet is not really the cornucopia of resumes (yes, that was a purposefully placed Thanksgiving reference) many people make it out to be, or falsely assume it to be.  LinkedIn also isn’t the panacea of talent for highly specific hiring profiles. The major job boards of course will represent relatively well because they are by design repositories of resumes, and very large ones at that. So even rare/highly specific skills and experience are represented in solid quantities. 

And last, but most certainly not least, a well stocked internal resume database, ATS, or Talent Warehouse can actually be a sourcer’s or recruiter’s most effective weapon in the War for Talent. In this exercise, the internal resume database (166 results) trumped Monster (26), LinkedIn (0), and the mighty Internet (2).

I came across a discussion in Irinia Shamaeva’s LinkedIn Boolean Strings group and found a search string example for a senior executive of bioinformatics in the New Haven, CT area.

I actually tried the original search suggestion, using Google, and got 0 results:

(filetype:doc OR filetype:wpd OR filetype:wps OR filetype:pdf OR filetype:rtf OR filetype:txt) AND (intitle:resume OR inurl:resume) AND 065* AND director OR VP OR “Vice President” AND bioinformatics

So I simplified it and added the necessary parentheses that were missing around the titles:

(filetype:doc | filetype:wpd | filetype:wps | filetype:pdf | filetype:rtf | filetype:txt) (intitle:resume | inurl:resume) 065* (director | VP | “Vice President”) bioinformatics

Still got 0 results.

The issue is the 065* – Google does not recognize the asterisk as most resume databases do, which is as a root-word operator. Google sees the asterisk as a single word wildcard.

So I decided to go for a zip code range:

30 miles from 06517 in New Haven (although 30 miles dips a little into NY) yields a zip code numrange of 06010 to 06890, from low to high.

(filetype:doc | filetype:wpd | filetype:wps | filetype:pdf | filetype:rtf | filetype:txt) (intitle:resume | inurl:resume) 06010..06890 (director | VP | “Vice President”) bioinformatics

This yielded 41 results, but they are sloppy with false positives. The issue is that Google (and most search engines) no not recognize the leading “0” in the number range, so you will get tons of false positives in the number range of 6010 – 6890, such as in the last 4 digits of non-local resumes.

So then I decided to try to go for area codes:

(filetype:doc | filetype:wpd | filetype:wps | filetype:pdf | filetype:rtf | filetype:txt) (intitle:resume | inurl:resume) (203 | 860) CT (director | VP | “Vice President”) bioinformatics

That yielded 14 tighter results, and there is not a single job posting among them, so no need to use -~job and such.

Let’s check out LinkedIn via Google:

site:linkedin.com (director | VP | “Vice President”) bioinformatics “Hartford, Connecticut area”-intitle:directory -inurl:updates -inurl:answers

3 results (4 results, 1 duplicate). Nothing impressive here.

These numbers seem quite low to me, and my instincts are telling me that not everyone will explicitly mention the term “bioinformatics” in their profile or resume, even if they have experience with it. One of the best practices of successful Talent Mining is simply taking a moment to think, as well as to perform some research to figure out if every candidate would necessarily mention any specific term, skill, or title mentioned in a job description or by a hiring manager. The people that most recruiting and staffing professionals seek to hire are not professional resume writers – they often simply forget to explicitly mention everything they do or have done, and often do not describe and label their experience in the ways that we assume they “should.” The operative word being assume. And so a great many candidates are never even seen in lying in the depths of the Hidden Talent Pools of candidates you can’t find because you unknowingly used search strings that simply make it impossible to find them.

But they are there.

So how do you find people with specific experience that you need, such as senior managers/executives with bioinformatics experience who do not explicitly say “bioinformatics” in their profiles or resumes?

I will address this specific challenge in a future post. It’s already in the works.

One of my blog readers recently reached out to me and asked me for help with a search for a Senior Tax or Audit Lead/Manager in a location that’s not in the most populated area of the United States (to put it nicely). They informed me they did not have access to any of the major job boards, but they did have an internal resume database that supported basic Boolean logic queries.

I advised the reader that their database may simply not have a large number of people from the particular area in it – internal databases can only have in them what others have put in them.

I was not provided a full job description, so with only a title to work with, here’s my first pass at a search for the internal database:

(”Tax Manager” or “Manager of Tax” or “Audit Manager” or “Audit Lead”) and (”certified public” or CPA or “C.P.A”) and (tax* or audit*)

I tested that simple search on several databases I have access to and I found that it returns highly relevant results. That search works on all major job boards as well.

For those interested in extended Boolean - if you have access to a database that enables configurable proximity, you could avoid the limitations of exact title searching with something like this:

(Tax* or Audit*) w/5 (Manager or Lead or Director or Senior) and (”certified public” or CPA or “C.P.A”) and (tax* or audit*)

That search will ONLY return results of candidates that mention any variation of tax or audit within 5 words of (Manager or Lead or Director or Senior) – and of those words are mentioned in such close proximity, they are most likely a title or a statement of responsibility. This kind of search allows us to break free of trying to think of every possible title companies and candidates can come up with, while keeping the semantic relevance high.

Moving back to basic Boolean, for subsequent searches, I also made note of these additional, broader titles:

(”Sr. Tax” or “Senior Tax” or “Sr. Audit” or “Senior Audit” or “Lead Audit” or “Lead Auditor” or “Senior Auditor”)

I then recommended they could try going higher in the food chain and target Directors to network and referral recruit:

(”Director of Tax” or “Tax Director” or “Audit Director” or “Director of Audit”) and (”certified public” or CPA or “C.P.A”) and (tax* or audit*)

And here’s a Big 4 search to add and try, if desired:
(”big 4″ or “big 5″ or deloitte or Andersen or Accenture or PWC or KPMG or coopers or “price waterhouse” or pricewaterhouse* or Ernst* or “E&Y” or capgemini or bearingpoint or “bearing point” or “cap gemini”)

Then I moved on to LinkedIn. I found a zip code for the location and used that in LinkedIn to find what LinkedIn calls that particular location. I won’t share the specific location in order to protect the privacy and confidentiality of the search.

So I took a crack at “x-raying” into LinkedIn via Google:

Search #1

site:linkedin.com “XXXX, XXXX Area” (”Tax Manager” | “Manager of Tax” | “Audit Manager” | “Audit Lead”) (”certified public” | CPA | “C.P.A”) (~tax | ~audit) -inurl:jobid -inurl:find -intitle:directory -inurl:answers -~inurl:updates

That search returned 0 results in the target area. However, it returned 649 in all of LinkedIn – so the search worked well – it appears that the location is the limiting factor. 

Search #2 – going looser on title

site:linkedin.com “XXXX, XXXX Area” (manager | lead | senior | Sr.) (”certified public” | CPA | “C.P.A”) (~tax | ~audit) -inurl:jobid -inurl:find -intitle:directory -inurl:answers -~inurl:updates

Results: 0 in the target area, however, I did find 4770 in all of LinkedIn. Again, the search is good, the location has slim pickings.

Search #3 – super loose

site:linkedin.com “XXXX, XXXX Area” (”certified public” | CPA | “C.P.A”) (~tax | ~audit) -inurl:jobid -inurl:find -intitle:directory -inurl:answers -~inurl:updates

Results: 2 people in the target area. Neither was a match -but one could definitely know people who are given their role. Opening up the search up to the entire nation yields over 10,000 results in all of LinkedIn.

I also checked my own LinkedIn network with a really loose search just for CPA’s with some mention of audit or tax for the target location. I have over 6000 first degree connections, and I only pulled 3 people in the target location, 2 of the same from Search #3, and the other was not a match.

Just out of curiosity, I also ran a search just to see how many total people were in LinkedIn that live in the target area. There’s over 10,000 – it’s just that there aren’t many CPA types that live there, let alone Senior Tax/Audit Leads or Managers.

I also checked for resumes on the Internet and came up with very few and no decent matches in the target area. That wasn’t too surprising – I typically don’t find many finance and accounting professionals with resumes on the Internet.

It was a worthy exercise – I’m hoping that the reader has some people in their internal database. If not, cold calling and network recruiting may in fact be the only productive option given the location challenge.

In response to my post of Resumes on the Internet: Monster vs. Google one of my readers commented that “While it may be true that Monster has more resumes than Google, using a zip code search is not a fair comparison for Google. People who post their resumes on Monster are required to enter their zip code, while people who resumes are stored online will generally only put their email and/or phone number. Also, even using the term resume can be limiting in Google. Because it was not built to only index resumes, you have to get more creative to filter out the noise. You can try the ~CV or ~Resume, you can also take that out completely and search for types of documents, .DOC, .PDF, etc. and look for words commonly found in CV’s like education, objective, etc.”

His comment inspired me to get these industry heavyweights into the ring for a second battle and experiment with not using zip code ranges or the word “resume” when searching for resumes on the Internet using Google. Let’s begin with the same searches as Monster vs. Google Round 1.

Search #1 – Java, Oracle, Sprint or Nextel, State of MD

Google #1 Zip range (original search) = 4 results

(intitle:resume | inurl:resume) java oracle (sprint | nextel) 20601..21930 (MD | Maryland) -~job -~jobs

Google #2 No zip range, using area codes instead = 3 results

(intitle:resume | inurl:resume) java oracle (sprint | nextel) (301 | 410 | 443 | 240) (MD | Maryland) -~job -~jobs

Google #3 No zip or state = 6 results, 3 are not local to MD, but we did gain 1 new resume

(intitle:resume | inurl:resume) java oracle (sprint | nextel) (301 | 410 | 443 | 240) -MD -Maryland -~job -~jobs

Because we know that not everyone actually titles or saves or refers to their resume as a “resume,” we’ll try to search for words commonly found on resumes. Note – I am not a fan of ~resume or ~cv because I tend to get lots of junk. I am not fooled by a larger quantity of results when the quality goes down – it’s not about quantity, it’s about relevance. Also, not every mention of “cv” is actually referring to a curriculum vitae – I get all kinds of strange false positives with the letters CV. “CV” is more common internationally than in the U.S., and in this case, we’re searching for U.S. based candidates. Additionally, as one observant reader pointed out, many online resumes are of people at educational institutions (.edu) – and many of those contain mention of CV. For most positions, people with only educational experience are not viable candidates. So, instead of shooting for the word “resume,” we’ll go for common resume words:

Google #4 No mention of “resume,” using zip range = 33 results, however – no resumes I can see

NOT “resume” (objective | summary) education (history | experience) java oracle (sprint | nextel) 20601..21930 (301 | 410 | 443 | 240) (MD | Maryland) -~job -~jobs

Note – for you search geeks out there, using -intitle:resume -inurl:resume did not work as the syntax suggests it should – it still includes the word “resume” in the url. For example, this search:

-intitle:resume -inurl:resume (objective | summary) education (history | experience) java oracle (sprint | nextel) 20601..21930 (301 | 410 | 443 | 240) (MD | Maryland) -~job -~jobs

Yielded results like this:

Verdict: Monster crushed Google

Search #2 Java, Oracle, State of MD (very simple and broad search)

Google #1 – Zip range (original search) = 220 results

(intitle:resume | inurl:resume) java oracle 20601..21930 (MD | Maryland) -~job -~jobs

Google #2 No zip range, using area codes instead = 218 results. HOWEVER, these results have significant overlap with Google search #1

(intitle:resume | inurl:resume) java oracle (301 | 240 | 443 | 410) (MD | Maryland) -~job -~jobs

I tried to shoot for mutually exclusive results by negating the zip code range from search #1, however, I could not negate the zip code range and get it to run properly. For example, I tried all 3 variations below to no proper effect:
-20601..21930
-(20601..21930)
NOT 20601..21930

Google #3 No mention of zip or state – just area codes = 375

(intitle:resume | inurl:resume) java oracle (301 | 240 | 443 | 410) -MD -Maryland -~job -~jobs

While this search returned 375 results – most of the results are false positives of non local candidates. See below:

As you can see, the MD-specific area code numbers come up as false positive hits in non-local resumes

I will not bother with not using (intitle:resume | inurl:resume) – as stated previously, although I concede that targeting the word “resume” is limiting, whenever you go beyond it, you get tons of garbage false positive results (see Search #1 above). I (and most sourcers and recruiters) should have better (higher yield) sources to tap for Talent rather than having to dig through large quantities of false positives to find a handful of relevant results.

Monster – 592 results @ 1 month, 1000+ @ 3 months

Java and oracle – in MD

Verdict: Monster destroys Google

Conclusion
After seeing the results of Search scenarios #1 and #2, I will not bother to repeat the other searches I executed in Monster vs. Google Round 1. I’ve seen enough to know that regardless of how you spin Booleans searching for candidates on the Internet (zip codes, area codes, resume or not resume, etc…), the quantity of candidates with resumes on the Internet is not as large as many would believe or assume, and certainly not even close to as large as even 1 of the major online job boards.

The reader who inspired this post made an excellent point – Google and other search engines are not designed to index resumes. That’s why I have never been crazy about finding resumes in the Internet – while it certainly can be done, it’s like using a screwdriver as a hammer – you’re trying to use a tool for something other than it’s original or intended design.  That certainly explains the results of this exercise.

If you’re looking for resumes – why not leverage systems specifically designed to index resumes, like the job boards (paid and free), as well as your own internal database/ATS? Which, by the way, is also free.

And if you happen to believe the hype that the job boards have poor quality candidates – please read this post on the quality of job board candidates that will provide you with a reality check.

I hope you enjoyed round 2!

So where do you think you can find the most passive candidates?

I think it depends heavily on how you define a passive candidate. Some would argue that anyone can qualify as a “candidate” if they can be found. That would mean that anyone on the Internet is a potential candidate. I see the reasoning behind this, but I don’t really agree. Just because you’re alive and breathing doesn’t mean I am going to label you as a “candidate.”

Let’s level-set here and define the term candidate.  According to Merriam-Webster’s dictionary, a “candidate” is “one likely or suited to undergo or be chosen for something specified.” 

For me, in order for someone to be suited to be chosen for a position I am recruiting for, I have to know some things about them – at the minimum, location and profession. Ideally, I’d like to know their career history – where they’ve worked, what they’ve done, and for how long. If you want to source and recruit people who you don’t really know anything about – be prepared for a low rate of return (what I refer to as “low yield” sourcing and recruiting).

For the sake of this post, I will define a candidate as a person for which we have (or can find) either a profile or a resume that gives SOME level of detail as to the person’s location, career history and qualififcations. 

So – now that we have that out of the way, I’ll ask the question again, albeit a little differently: Where do you think you can find the most passive candidates with a profile or resume?

LinkedIn? The number is growing every day – last I heard it was 34 million or so globally. Now, I could argue that not everyone on LinkedIn is a passive candidate – there’s probably a good number of folks on LinkedIn who are actually looking for a new position. But we won’t get into the definition of active and passive in this post. Also – while LinkedIn members do have professional profiles - not everyone actually fills them out. There are many LinkedIn profiles that list an employer and a title, but nothing else. In many professions, a title itself can be essentially meaningless and may not offer any reliably accurate clues as to the person’s responsibilities and experience. Some don’t even list a title – so I could argue that you can’t really consider everyone on LinkedIn as a candidate – but I’ll leave that alone.  For now.

So – could it be the Internet? Certainly there are lots of people online – but how many have enough information about them for a sourcer or recruiter to make even an educated guess as to whether or not they are potentially qualified for the openings they are recruiting for and trying to fill? Let’s not forget the definition of a “candidate.” Interestingly, I recently ran a little experiment to compare the number of resumes the Internet (via Google) vs. Monster, and Monster manhandled the Internet when it came to specific hiring profiles in specific locations. So from my own research – I don’t really find a whole lot of candidates on the Internet.

Could it be Facebook or MySpace? Certainly those sites have TONS of people on them – however, in spite of those large numbers – most users don’t post much information for a sourcer or recruiter to use to determine if they could be potential candidates for specific job openings. I’m an certainly not saying that you can’t find candidates on Facebook or MySpace, but these sites are “shallow” sources of professional information and can be a low yield recruiting source when it comes to accuracy and precision.

Could it be the job boards?  No, you say?  Why’s that?  They’re “active channel?” Hmmm – I’ve heard that term used quite a bit to describe the major online job boards, such as Monster, Careerbuilder, and Hotjobs. Being the “question everything” guy, I decided to look into this perception that the job boards consist of only “active” job seekers.

I’m aware that many sourcers and recruiters who use the job boards focus predominantly on searching for candidates who have posted their resumes within the past 30 days. Presumably, if someone posts their resume online, they’re “actively” looking for employment, right? Although I could easily argue that’s not necessarily true – I’ll give you that point for the purposes of this post.

So, if we assume that resumes that have been posted to a job board within the past 30 days are “active candidates,” what about all of those candidates on the job boards whose resumes are over 30 days old? Yep – you guessed it – let’s assume they are “passive candidates.” Did you know that some of the major job boards have resumes that are up to and over 3 years old?  Can you see it coming yet?

I did some digging on the 3 major job boards to see exactly what percentage of candidates had resumes updated or entered in the past 30 days versus the percentage of candidates who had resumes with a post or update date older than 30 days.

Consistently, I found that 75% – 80% of the candidates on every major job board had resumes over 30 days old. Let’s do some math now. As with LinkedIn, the total number of people with resumes Monster, Careerbuilder, and Hotjobs is a moving target, but based on their published figures, all together they easily have over 75,000,000 resumes. That means that there are approximately 56,000,000 to 60,000,000 “passive candidates” on the 3 major job boards.

Wait – I’m not done yet. LinkedIn’s 34,000,000 and growing population is international. The 56,000,000 to 60,000,000 figure for the 3 major job boards is just in the United States alone.

So where can you find the most passive candidates with profiles and/or resumes that offer you some degree of insight into their location, experience, and qualifications? It could be the place that most people would least suspect – the online job boards.

If you are a sourcer or recruiter I am sure that at some point in your career you’ve read somewhere or heard someone say how the Internet has 10X the number of candidates that can be found on the online job boards. I’ve always taken that for face value because, to be honest, it’s really tough to prove or disprove such a figure/statement.

However, I am a little bit of a skeptic by nature and I tend to question everything. Socrates and I would have been fast friends. I don’t typically accept what other people say or write just because they say or write it. So that whole “there are TONS more candidates on the Internet than the job boards” thing has been slowly eating away at me and I’ve decided to take a stab at dispelling the myth by pitting The Internet (via Google) vs. Monster.

Before you jump all over the Boolean search strings I settled on for this little exercise - I’m going to keep them relatively simple for easy apples-to-apples comparisons. I am well aware that the searches you see below can be tweaked in many ways – and just so you know, I did experiment with them before settling on a particular search string format. I did not find any significant variation in the results by tweaking the approach I took to pulling resumes. For example, when I used intitle:~resume, I got a couple extra CV hits, but also a bunch of false positives that were not resumes – so I kept it pure and simple at intitle:resume.

I chose to go with 1 Internet search engine (Google) and 1 major job board (Monster). Yes – I know that there are resumes that you can only find using other search engines (hey – I do have a Black Belt in Boolean) - but I figured I would let the 800 lb gorillas of their respective niches battle it out. Plus, there are other major job boards – so we’re even.

It is important to bear in mind that I set out to just run a little experiment to see how many resumes I could find via Google for particular search terms/skills in specific locations vs. how many I could find on Monster with the same search terms and locations.  I chose the state of Maryland and a 20 mile radius of 94118 in San Francisco, CA. 

Google – are you ready? Monster – are you ready? Now, LET’S GET IT ON!!!

Search #1 – Java, Oracle, Sprint or Nextel, State of MD

Google – 4 results
(intitle:resume | inurl:resume) java oracle (sprint | nextel) 20601..21930 (MD | Maryland) -~job -~jobs
 
Monster – 123 results, ALL resumes
Java and oracle and (sprint or nextel)

Search #2 Java, Oracle, State of MD

Google – 182 results
(intitle:resume | inurl:resume) java oracle 20601..21930 (MD | Maryland) -~job -~jobs

Monster – 592 results @ 1 month, 1000+ @ 3 months
Java and oracle – in MD

And just out of curiosity – I ran a simple 1 word search of Java in the state of Maryland on Google and got 316 results. (intitle:resume | inurl:resume) java 20601..21930 (MD | Maryland) -~job -~jobs

Then, to add insult to injury, I decided to up the ante on Monster and add a whole bunch of other junk to give Monster the squeeze. But even so, with this search, I still got 120 results going with the ALL resumes date range: java and (weblogic or websphere) and apache and J2EE and XML and unix and (shell or script*) and oracle and PL/SQL
           
Let’s go to the other coast (West SIIIIIIDE!)

Search: Java, Oracle, 20 mile radius of 94118 in San Francisco, CA

Google – 575 results
(intitle:resume | inurl:resume) java oracle 94005..94979 (CA | California) -~job -~jobs
           
Monster - 301 @ 1 month, 613 @ 3 months, 911 @ 6 months
Java and oracle – 20 mile radius of 94118 in San Fran

Search: Java, Oracle, Weblogic or Websphere, Apache, J2EE, XML, UNIX, shell or script*, oracle, PL/SQL – 20 mile radius of 94118 in San Francisco, CA

Google – 12 results
(intitle:resume | inurl:resume) java (weblogic | websphere) apache J2EE XML unix (shell | ~script) oracle PL/SQL 94005..94979 (CA | California) -~job -~jobs

Monster – 81 results (date range = all) 
java and (weblogic or websphere) and apache and J2EE and XML and unix and (shell or script*) and oracle and PL/SQL
      
Okay – now that we’ve taken a swing at some simple Information Technology searches, let’s move onto Accounting.

Search: Accountant in the state of MD

Google – 19 results
(intitle:resume | inurl:resume) “accountant” 20601..21930 (MD | Maryland) -~job -~jobs
           
Monster – 711 results @ 1 month
accountant

Wow – Monster crushed Google on that one. Let’s load up and see how many CPA’s with Big 4 experience Monster can find in Maryland:
 
accountant and (CPA or “certified public”) and (”big 4″ or “big 5″ or deloitte or Andersen or Accenture or PWC or KPMG or coopers or “price waterhouse” or pricewaterhouse* or Ernst* or “E&Y” or capgemini or bearingpoint or “bearing point” or “cap gemini”)

210 results in MD, all resumes date range.

And now, let’s show some accounting love to San Fran.

Search: Accountant in 20 mile radius 94118 in San Francisco

Google – 30 results
(intitle:resume | inurl:resume) “accountant” 94005..94979 (CA | California) -~job -~jobs

Monster – 333 @ 1 month, 773 @ 3 months, 1000+ @ 6 months
Accountant
           
Monster’s not even breaking a sweat. Let’s try the CPA with Big 4 search: 
accountant and (CPA or “certified public”) and (”big 4″ or “big 5″ or deloitte or Andersen or Accenture or PWC or KPMG or coopers or “price waterhouse” or pricewaterhouse* or Ernst* or “E&Y” or capgemini or bearingpoint or “bearing point” or “cap gemini”)
           
155 @ all resumes date range.
 
I’ve tried a basic IT and F&A searches – let’s go a little more off the beaten path (for some).

Search: Chemist with degree in chemistry or biochemistry in a 20 mile radius of 94118 in San Francisco

Google – 17 results 
(intitle:resume | inurl:resume) “chemist” (chemistry | biochemistry) 94005..94979 (CA | California) -~job -~jobs

Monster - 254 results @ all resumes
Chemist and (chemistry or biochemistry)

Monster still isn’t breathing heavy. Must be all of the high altitude training.  Once again, let’s load up to try and test Monster with something more challenging:   
      
Chemist and (chemistry or biochemistry) and (HPLC or “Liquid Chromatography” or GC* or GPC or LC* or “gas chromatography” or UV* or FT* or NMR) and (USP or ICH or GMP* or cGMP* or GLP*)

84 results @ all resumes
 
Back to the East coast for chemists
 
Search: Chemist with degree in chemistry or biochemistry in the state of MD
Google – 10 results 
(intitle:resume | inurl:resume) “chemist” (chemistry | biochemistry) 20601..21930 (MD | Maryland) -~job -~jobs

Monster – 572 results @ all resumes data range 

Is anyone else seeing a trend here?

Once again, I will try and stress Monster: 
Chemist and (chemistry or biochemistry) and (HPLC or “Liquid Chromatography” or GC* or GPC or LC* or “gas chromatography” or UV* or FT* or NMR) and (USP or ICH or GMP* or cGMP* or GLP*)
           
161 results @ all resumes date range
 
Let’s go even farther off the beaten path and look for something like a senior executive of medical device product development/improvement in CA.

Google – entire state of CA – 1 result
(intitle:resume | inurl:resume) (VP | “vice president” | Director) (quality | regulatory) (”cfr 820″ | 13485) (~product | ~process) ~improve (~health | ~medical) ~device 90001..96162 (CA | California) -~job -~jobs

Monster – entire state of CA – 153 results
(VP or “vice president” or Director) and (quality or regulatory) and (”cfr 820″ or 13485) and (product or products or process or processes) and improve* and (health* or medical) and device*

Conclusion
Although this little experiment wasn’t very extensive, it does serve as a fair apples-to-apples comparison of the number of resume results you can get on the Internet (via Google) and on Monster with specific searches in specific locations.

The numbers speak for themselves. The Internet via Google didn’t stand up to well to the hype that the Internet has tons more resumes than the job boards – heck, it had sand kicked in its face by just one job board – Monster.

We also confirmed that there are more Information Technology resumes on the Internet than non-I.T. folks, such as accountants and chemists – at least in Maryland and the Bay area. Although I suspect this is true across all 50 states, and perhaps the world.

I had fun with this comparison – look for more coming soon.