Resumes on the Internet: Monster vs. Google

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

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
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*

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.

  • Just wanted to say HI. I found your blog a few days ago on Technorati and have been reading it over the past few days.

  • admin

    Thanks for checking out my blog. I’m going to do my best to keep it as interesting and engaging as possible. Let me know if you have any suggestions.

  • I am guessing that restricting the Google search to things with resume in the title is over-restrictive, yet likely necessary to maintain relevance in the query results. As you know, depending on the publishing tool or CMS, web page titles are often not formulated well, if at all. Just do a search on “untitled” or whatever the default title is for no title to see how many web pages have no title at all. I would not doubt that Google has more resumes, but since they are indexed with everything else under the sun and prioritized with Google’s own bias for ranking certain types of results, it’s no wonder they are hard to find (reliably).

  • Kameron Swinton

    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 numbe. 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.

    Really enjoy reading your blog, keep it up!

  • Boolean Black Belt

    Thank you for your comment – you raise excellent points. The fact that Google is not specifically designed to index and retrieve resumes makes it especially cumbersome to wield as a resume sourcing tool. I did consider the approaches you commented to, but I decided to choose the zip code method because it yields the “cleanest” results with the fewest false positives (in other words, you get mostly local resumes).

    You’ve inspired me to stage a rematch between Monster and Google, taking zip codes out and using other methods to find local candidates. Look for it soon!

  • Kameron Swinton

    Looking forward to seeing the rematch, though I suspect the results won’t change drastically.

    One other thing I’ve noted in sourcing resumes through Google is a large percentage of the resumes indexed are from educational institutions. This was even more evident when PageBites was still around to act as a Google for resumes stored online. Many of these resumes are for professors, research assistants, post docs and new grads. Adding to the search string eliminates these resumes from your search results. For example, in your {Java, Oracle, 20 mile radius of 94118 in San Francisco, CA} search, it eliminated 15% of the results.

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  • ABCxyz

    Hey Author!!! good work…
    Infact very interesting “MATCH”… May be this is stupid enough question but why do you add

    -~job and -~jobs

    at the end of string..

    Removing it gives more wider result (may be irrelavavent)

  • Boolean Black Belt


    I added the -~job and -~jobs at the end of the string to eliminate the large volume of false positive results that come from searching for the term “resume” that are job postings or resume sample sites. You are correct, removing that from the search does increase the results, but most (if not all, in most cases) of the results are false positives/irrelevant.

  • jojo

    hw do u translate a 20 mile radius frm a zip code to a search term

  • @jojo – you can use a site such as|e_rad.html to enter a zip code and choose a radius of say, 20 miles. The results come back as a list of zip codes ordered from lowest to highest numerically. You can then take the lowest number and highest number of the range and use them with Google’s numrange function, which is two periods. For example: 33503..34695. Combine that with a resume search, and you can find resumes of people who list an address with a zip code. Here is an example with many hits on the zip code: Thanks for asking!

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