The Adventures of Joe’s LinkedIn Resume

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LinkedIn profiles are often considered to be “new resumes.” It’s true, that if a professional fully fills out her LinkedIn profile, that profile works instead of a traditional resume, at least at the beginning stages of interviewing, at many companies. That is one of the innovations LinkedIn has brought into the area of recruiting, quite a game changer!

One the other hand, LinkedIn offers its members to upload and share documents on their profiles. There are hundreds of thousands of members who have uploaded PDF or MS Word resumes to their profiles. When we view those profiles, we see previews of the resumes (or other uploaded documents), which look like this:



Not all uploaded resumes are equal though. There are two kinds of documents, regarding others finding them by searching, depending on what the member did right after uploading a file:


Now, I need your full attention! Further destiny of the resume heavily depends on whether the member selects this option – “publish to SlideShare.”


Slideshare Opt-in. If the member continues and does publish on SlideShare, good for him or her! The member gets an account on Slideshare if s/he didn’t have one, the document is uploaded, and the member has further control over the resume:

  1. Being indexed by Google
  2. Whether others can download the original file (PDF, MS Word, etc.)

If you are a Recruiter or Sourcer searching for those resumes, you might want to try these custom search engines from our CSE collection:

Slideshare Resumes
Slideshare CVs

However, please note that the resumes cannot be found using LinkedIn people search by any keywords that are only on the resume and not on the profile. LinkedIn Recruiter search won’t find them either.

Recruiters: we’ll cover this (and much more!) at the sourcing webinar next week. 

Are you a job seeker? Note that pasting the resume text into the Description section accompanying the document won’t fix the ability for others to find that information either. LinkedIn doesn’t search in those descriptions.

If you want to be found by keywords in that uploaded document on LinkedIn, paste them in the summary or experience sections.

Slideshare Opt-out. It’s a shame if the member selects this option by unchecking the checkbox – assuming the member wanted to be found and was willing to share the resume with interested parties.

Believe it or not, the resume still goes to SlideShare in this case. (This is the correct answer to the question number one in the Sourcing Contest). However, if the member opts-out, the document does not go into the member’s SlideShare account, and he has no further control over this content being found in searching anywhere – on LinkedIn, SlideShare, or by search engines.

What happens then, is that, sometimes, Googlebot will pick the image preview. Recruiters: here’s a related post – Large Free Resume Database Hidden In Plain Sight. I must warn you though, that Google will index the content only of the “opted-in” resumes. I.e. we won’t find the image previews of the majority of “opted-out” resumes when searching by the job-related keywords.

The story of the resume in the opt-out case is fascinating. I will share it in a post soon. As a reminder for Sourcers who like a challenge, there is still a big chance to win the Contest. Monday, October 24th, 2016 is the deadline, and the Grand Prize is worth a lot.


The Fastest Ever Way to Uncover Hidden Names

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LinkedIn shows very little information about members who are out of our networks, even for those of us who pay for premium personal accounts.

This brand new method to uncover the real name, when we see “LinkedIn Member” instead, and view the full profile takes about ONE SECOND to execute. Here is how it works.

Take a very, very careful look at the screenshot below. Need I say more?


This name-and-profile uncovering technique, that you have just figured out, works in the cases where the member has set a custom profile URL. For those members who haven’t, we can also find the name and profile easier than before – it would just take more than one second (but it’s also quick).

I have also figured out ways to lift the limitations for other cases, such as how to work around the commercial search limits (in a way that was never shared online) and more.

Sign up for my (fully redone) lecture

Overcoming LinkedIn Limitations

on Tuesday, October 18, 2016 <– Sold out!

New date: Tuesday October 25, 2016

to learn lots of new tips and techniques. David Galley will hold the optional interactive Practice Session the next day. As always, we provide the slides and video for everyone to keep, and one month of support.

P.S. If you have a Recruiter subscription, I’d recommend getting the LinkedIn Recruiter webinar recording from our Sourcing Training Library. All others, no matter with a free or a paid account, will find this webinar useful and informative. I promise!


A Close Look at “Open to New Opportunities”

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Signaling that one is “Open to New Opportunities” without alarming your boss is certainly a good idea for a job seeker. Recently, LinkedIn introduced this feature.

If you are a job seeker, there are a couple of things to be aware of here.

(1) The signal you send gets only to LinkedIn Recruiter product subscribers. That subscription is quite expensive. For many smaller companies – both potential employers and smaller recruiting agencies (which may be serving large corporations!) – the product costs too much to buy. Just be aware that the signal only goes to some, not all professionals who might want to employ you.

(2) The “exact” employer, i.e. a registered company on LinkedIn, will not see your status. But any company working in a close relationship with your employer, for example, other divisions registered as separate companies and third party recruiters, can still find you as someone looking. Then, people from different companies who are friendly can also ask each other to search. An employer without the subscription can ask someone with a subscription to look. (Etc.) Here’s a related discussion in our group.

It’s progress, though – Recruiters, no matter which subscription they have, have not been able to search for members with paid “Job Seeker” accounts. So for people who are openly looking, I’d advise raising the flag on your account. For those who want to keep it a secret, I am not sure.

If you are curious how widely members have used the “Open to New Opportunities” signal, here are some statistics, measured this morning using LinkedIn Recruiter.

The global stats are the following – please note that (for a variety of reasons) the numbers are approximate:



Members who have set the status:


The “Open” members amount to 0.25% of all the membership, as of now.

It’s the early days, so perhaps the stats show more of the membership using this function vs. those looking to leave. However, the stats narrowed down to the hiring company’s industry, and location can be examined for employers who are potentially in trouble. Those would be the companies with the percentage of employees looking to leave, out of employees with LinkedIn profiles, being high compared to the average. In fact, I would say it is a way to investigate companies that might be good to research when sourcing for talent. (Right?)



Deadline and Prizes for the Sourcing Challenge

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As I have promised, here are the formal rules for the Sourcing Challenge.

Answer the questions in a comment here – Are You an Advanced Sourcer or Researcher? Partial answers are welcome; you do not have to post all the answers in one comment. It’s OK to add an extra comment where you change your mind on an answer as well.

The post has 12 questions. Each correct answer to a question gives the participant one point, except the correct answer to the question number 4 gives a whole five points. The first person to answer each question correctly gets one additional point. The answers need to be explained.

The person with the largest number of points is the winner. In the case of a tie, we’ll take a look at the explanations; we might have more than one winner, too.

The prize is a choice of a one-hour consultation – where we can source together, or talk about sourcing tools and tips – with your choice of: me (Irina), David Galley, or Martin Lee; access to one webinar of your choice from our Training Library; and participation in our new tool Beta-testing (now, developed in a stealth mode).

Additionally, here is the grand prize for anyone who answers all 12 questions correctly: access to all of our Training Materials.

Deadline: Monday, October 24th, 2016.

Best of luck, Sourcers!

Are You an Advanced Sourcer or Researcher? Can You Answer These 12 Questions?

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Hello Sourcers and Internet Researchers:

Here are some questions, that I would like to offer, based on just one collection of professional data, that has an interesting implementation, and that is – documents uploaded to LinkedIn by its members.

How good are you at understanding what data can be found and how?

Please post your answers as comments – and please provide your reasoning for the answer. Responses to only some of the questions are welcome. I anticipate a nice discussion here!

[Updated!]  We have launched a contest based on these questions!

Here you go:

If a LinkedIn member, say, Joe D. wants to upload a resume (or another document) to his profile from his PC, LinkedIn will ask him whether he would like to store the document on Slideshare or not. (If you haven’t, try it, you’ll see.)

Suppose Joe said “no” to posting the resume on Slideshare and uploaded it to the profile. When we view Joe’s profile, while logged-in, we now see Joe’s document’s preview as an image (or series of images if there is more than one page).

  1. Joe said “no” to storing on Slideshare, so where (to which site) did it go?
  2. Is a preview available on Joe’s public profile? That means, is it available when you are not logged-in?
  3. Can the preview image(s) be viewed in an incognito window, i.e. without logging into LinkedIn?
  4. Can we download the original resume or document (say, PDF or Word)? From which site? Please note, the question is about finding the original doc, not trying to recreate it by using “print to PDF” or character recognition.
  5. (Easy) What does LinkedIn call the part of the profile that stores those uploaded documents?
    • (5a, harder) Is there a URL pointing to that part of the profile (for logged-in members)?
  6. Can we find Joe’s profile by searching on LinkedIn “people search” …
    • (6a) for the resume keywords, if they are not included elsewhere on his LinkedIn profile?
    • (6b) for keywords in the title and description, that Joe adds when he uploads the document to the profile?
  7. Is there a URL that you can share with a colleague, for them to see the resume if the resume has more than one page, for example, three pages, – not on LinkedIn, but on that site, that stores the resume?
  8. Will Google find the uploaded original document if there are no other copies of it online? The options are “yes,” “no,” and “sometimes, when…”
  9. (This is a tough one!) Will Google find the uploaded original document’s image preview in the Image search? The options are “yes,” “no,” and “sometimes, when…”
  10. Can Yandex find Joe’s original resume?
  11. Can Bing find it?
  12. On which cloud is the document stored (Amazon, etc.)?

To help you here’s a (randomly picked) example of a profile with an uploaded resume.

What say you? 🙂

I’ll reveal the answers in a future post.


P.S. Just launched a formal contest around these questions. I think, these are great questions for anyone who searches, to understand the Surface, Deep, and Dark Web.

Advertising as a Researcher’s Friend

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Not every advertising option is equally useful for research, and I don’t think truck advertising or billboards can play a big role. But some other advertising platforms can give us invaluable data – even before we invest any money in them.

The two social networks with giant amounts of professional data, LinkedIn and Facebook, offer to explore to whom to advertise. While we do that exploration as the potential users of the ads, we can assess available talent pools. This is a largely underutilized resource to use in research.

Take a look at these screenshots of the dialogs to help define the audiences for advertising. These dialogs can answer the questions any self-respecting Sourcer would try to answer before looking for candidates:

Where are the skills we are looking for? – Companies, job title, locations, graduates from which schools?

(To illustrate the ad audience exploration capabilities in the screenshots, I have inserted some parameters, such as target company names, skills, etc.)

LinkedIn Ads (note – this data is available to any user, even the basic):



Facebook (this data is also available to anyone):



For each entered set of parameters – locations, employers, skills, and more – these tools show us the available pools of professionals. Spending some time with these and similar tools is a solid way to get some market intelligence data – and to be much better prepared to source for individuals with target skills.

Nerdy Custom Search on GitHub

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Ever since we started making use of structured web search capabilities, I have been fascinated by the precise results we can obtain from a general search engine via this mechanism.

Here is an investigation and multiple examples of precise X-Raying on, which is a truly useful site to know if you are looking for software developers.

For those (few) Sourcers who love working with advanced search operators – here is where you will find tons of long and barely readable expressions, that you can change to your liking! For your convenience, I have placed a search box for Custom X-Raying Github below as well.

For those who’d rather skip the cryptic search syntax, the good news is that we have a new, unique Sourcing Tool in development – currently, in a stealth mode – that will relieve end users of needing to use these operators. (Please follow us for more news!)

For now, just take a look at the search results. You will find them to be precisely finding what we are looking for in each case – a big difference with “general” Google and most social sites.

Here you go:

Examples – Github Precise XRay Member Search

Want to build your own? The Custom Search Engines Webinar is coming up!

And here is a

Github Custom XRay Engine

This Webinar will Change the Way You Source

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“Like writing poetry or tweeting, searching without operators allows us to be creative and make discoveries.” – David Galley

Searching without Boolean is a new webinar with how-to, step-by-step guide to creating amazing searches in English; here is a quick write-up on its content.

If you search the Web on a regular basis, you will want to obtain the webinar materials, to instantly improve your sourcing performance. Promise, you will never search like you used to! Tune into the best ways to build queries, that are now simpler and cleaner than before, yet produce superior results.

Recruiters: want to get on the phone with potential candidates fast? The webinar teaches more than a dozen easy to use “plain English” search patterns, which do not require advanced search skills. (But they do require thinking it through and understanding what to expect; we’ll go over that in the presentation).

Major search engines, including Google, are rapidly becoming more semantic-oriented, meaning – they try to guess the intent of the person who Googles and respond appropriately. In many practical cases, Google is now giving better answers to searching “in English”, without advanced operators, than when using complex Boolean constructions. That’s great news!

At the lecture, I demonstrate finding “hidden” professionals, locating and exploring previously unknown sites full of candidate details, by using creative patterns and templates, searching in English “without Boolean”.

Equipped with the search patterns that are easy to keep in mind and apply, you will be able to put your new skills to work as soon as the webinar ends.

Who should attend: Recruiters who need to find target professionals outside of the mainstream sites, but dislike or don’t have enough time to write complex Boolean Strings. Everyone who wants to find more professional information on the web by using additional search patterns.

Included: The slides and video recording from the session(s) for you to keep and one month of support for any questions about the Boolean free Sourcing techniques demonstrated in the webinar.

The webinar materials are available (including one month support): Searching without Boolean.

Search Like a Pro in Three Simple Steps

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Want to search the Web like a Pro? Here is a fast way to get there.

Searching the Web is not Rocket Science. Everyone can learn to search even for complex information, such as professional bios, quite efficiently, following the three steps that I am about to describe. And the good news is, you do not necessarily have to use advanced search operators to find excellent results.

Steps 1 and 2 are required to prepare to search, while Step 3 is actual searching.

Step 1. Identify where you want to search.

The web is so large – just Googling some keywords, that you would like to see on target profiles, is a long shot! The first step is to narrow down the set of pages where you would like to find the results. A traditional technique for this step is only to look within a given site. Searching only within a given site, using a search engine, is called “X-Raying.”

(Whether you are or are not familiar with the operator site:, just read on. You won’t necessarily need to learn about search operators.)

To find a site that you might want to X-Ray, you can start with a profile you have already found – perhaps linked from another profile or shared by a colleague. Or, if you are starting from scratch, run a simple Google query describing a site. For example, Google for [association of accountants in Canada] or [members oil gas Louisiana].

Step 2. Create a search template to search just for the desired pages on the site.

For that, it helps to take a look at a few profiles on a site (that’s if those are your desired pages) and see what these pages look like; then, use that to start constructing a search. Let’s take a look at an example.

Here is a sample profile:

For people who are familiar with the “formal” X-Raying (i.e. using the operator site:) – from looking at the profile, you will see how to proceed to narrow the search down to this type of pages – at least in this example. You can take advantage of the URL structure:

For those who don’t want to use any operators: use the domain and add a phrase or keywords that any profile on the site would have. Example:

“” “member profile.”

Either of the two sample strings above can serve as a search template.

Depending on the site you are looking to explore, you may find that the site’s profiles have a phrase like “member since”, “connect with”, or “full profile it’s free” (etc.) – those would be the phrases to use in the template.

Step 3. Now you are ready to search.

Add keywords, such as job titles, locations, and skills.

Examples (using the two templates we had created earlier):

You can repeat the search varying the keywords and phrases, to uncover the pages that you want to find. Here’s a diagram with several more examples of the three-step search construction (no Boolean operators are involved!):


For an in-depth exploration of fast and productive searching without special search operators, please join me at the upcoming Webinar

Searching without Boolean

(Lecture – Wednesday, September 7th, 2016. Practice – Thursday, September 8th, 2016. Seating is limited.)

If you do know how to use advanced search operators, I invite you to join as well – to review your search templates, learn how to simplify your searches, and get the results fast.



Who Offers Proximity Search?

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Finding several terms that are close to one another is a way to make the search results more relevant, i.e. make the search more semantic. This feature is called Proximity Search; it’s especially useful when searching on the web and in long, unstructured documents. A familiar example is to search for the word manage close to the word people, to find bios of those who have managed people, vs. profiles that just have both words somewhere in the text. Another example would be to look for a school name close to the year of graduation. Applications of proximity search are multiple.

Google, Bing, and Yandex have all implemented proximity search features. It looks like, however, the first two search engines have dropped the ball. Let’s take a look at some examples.

Google’s has never officially documented its proximity operator. Back in 2010 researchers were excited to read the post “AROUND has always been around” by Google’s Dan Russel. At this time, however, after looking at multiple test searches, I’d say AROUND doesn’t do its job. Compare, for example, these (randomly picked) searches on Google:

  • manage AROUND(9) people “associate partner” accenture atlanta
  • manage AROUND(1) people “associate partner” accenture atlanta
  • manage people “associate partner” accenture atlanta

The results are just identical:


Perhaps there are some cases where AROUND does influence the results, but the operator is certainly unreliable!

The same goes for Bing’s (documented!) operator NEAR. Just compare these simple searches and you will see that it’s not working right:


Let’s hope that Google and Bing engineers will make the proximity search feature a high enough priority to fix it sometime in the future. is the only global search engine that does, in fact, currently support proximity search. For starters, Yandex has the operator & which means “search for the terms to appear in one sentence.” Here is an example I have just created in response to a question on the Boolean Ning Network:

“graduated” & “Georgia Institute of Technology” & 2016

Further, Yandex can search for one term after another, within a certain “distance” in words between the terms. This search –

“Georgia Institute of Technology” /2 2016

will look for the second term (2016) to appear after the first term (“Georgia Institute of Technology”) with no more than two words in-between. You can also search using (for example) /(-2 +2)  to find the terms in either order, within two words from each other.

Conclusion: Yandex wins! If you are looking to use proximity search on the web, Yandex is your search engine.

Your comments and creative proximity search examples are welcome!