Notes from the LinkedIn Field

booleanstrings Boolean Leave a Comment

The field of LinkedIn.com search is currently, unfortunately, full of bugs. Following up on and expanding my last post, here are some observations.

  1. Often, results do not include some or all of the 3rd level connections. It seems random to me; any insights from the analytical minds are welcome!
  2. Sometimes, NOT is not respected. This search for cats not dogs produces a profile with the word dogs. Also seems random.
  3. Terms in the Keyword field are heavily interpreted – have been for a long time. Try, for example, java engineer (NOT java NOT engineer) – it brings up over 200 results. You never know what LinkedIn may decide sounds like a title. Here is how to avoid the interpretation – LinkedIn’s “Verbatim” mode (not entirely though; things may still happen):
  • Put every term in the quotes.
  • Use as many parentheses as you can.
  • Use the explicit AND.

Then, the results will get better.

Note that not all of us are affected by the above (see some differences in the comments.) Some members get reasonable results (but the interpretation part affects all, so use your quotes.)

LinkedIn Boolean Is Crazy

booleanstrings Boolean 7 Comments

Searching on LinkedIn costs many Recruiters low self-esteem. When you see results you did not expect, you may blame yourself for searching “the wrong way.” But it is rarely the case.

What has been happening on LinkedIn and LinkedIn Recruiter (LIR) lately is beyond my (reasonably high) IQ.

Let us compare some searches on LinkedIn.com and in LIR. We vaguely anticipate that Recruiter should produce more results because it is expensive. But which ones? We still see “LinkedIn Member” instead of the names for profiles that are out-of-network on LinkedIn; so what exactly is hidden? (In the past the results’ numbers were the same, and only the visibility was different.)

Examples confirming that LIR is “better”:

  • AWS – 1.3M+ results on LinkedIn.com and 3M+ in LIR.
  • vp marketing (NOT sales) railroads – 10 on LinkedIn.com, 407 in LIR.
  • cats dogs – produces  3.6K on LinkedIn and a whooping 100K+ in LIR. No pay, no cats, no dogs! Who are the mysterious cats and dogs people only found for money? I have no idea.

But sometimes, it is the other way around:

  • janitor – 211K on LinkedIn, only 110K+ in LIR.
  • cats NOT dogs – 210K on LinkedIn.com, only 150K+ in LIR.

The discrepancy is all over the place. I doubt it is LinkedIn’s conscious effort to get more dollars out of its customers.

Have LinkedIn Developers activated a random number generator while celebrating something? Or are their servers under attack?

In the meantime, try our tool Social List (cc upfront, 7-day trial, $50/month after) to generate excel exports of LinkedIn and other Social Network X-Ray results; it also has a Contact Finder. The tool will not be affected by any LinkedIn bugs, I promise.

 

 

 

Big Data for Executive Search

booleanstrings Boolean Leave a Comment

 

Research is a vital part of executive search. You need to be knowledgeable about the industry, the candidate’s background, and the role at your company. You need to find their contact info.

Here are some resources to help you with gathering intelligence.

Any data sets you could share with us?

Several Contact Finders, including contactout.com offer advanced people search dialogs and Excel export (plus contact-finding, of course). Here is what it looks like:

I am sure these profiles can be found on LinkedIn, but LinkedIn does not offer contact info or downloads.

Similarly, SalesQL works over LinkedIn or X-Ray search, scrapes the details and enriches.

In my experience it has the best coverage among Contact Finders.

Join us on December 1st, 2021, for a complete coverage of sourcing for executives!

Change Your Thinking, Rewrite Your Search Strings

booleanstrings Boolean Leave a Comment

Successful Sourcers know the main – secret! – principle of productive search: “Imagine the words and phrases exactly as they should appear in the target results. Then, use those words and phrases in your search”.

We also call it “Visualize Success”.

Rarely do Recruiters get training in the “Visualize Success” skill, yet it is the #1 factor in finding target data even if the data is well-hidden. Once you start thinking this way, your search results world will turn around accordingly, finding never-seen relevant pages. (It implies thinking while searching 😉 )

Here are two practical use cases of implementing the “Visualize Success” principle (that you can start today):

  1. While constructing X-Ray search strings, if possible, review several sample pages to see what information they contain. Prepare your imagination to work, close your eyes, and picture an ideal (or acceptable) candidate’s profile – which words and phrases are there? Use those in X-Ray. Once you uncover and test an X-Ray template and educate yourself on target keywords, you can get to work.
  2. An additional, little-used, source of professional data is online contact lists or directories of organization members, conference attendees, and company staff. Sometimes, pages with lists and directories are posted on the surface web in an Excel format, but often, also in PDF or HTML. You can Google for them.

If you have obtained a list of professionals with contact emails, you can discover their profiles on LinkedIn by uploading a CSV list of the emails (and any names) into your Contacts. After an upload you will know the following about each person:

  • Their LinkedIn URL
  • Confirmed email address
  • Knowledge that they come from that list (e.g.,, spoke at an industry event, etc.)

Nice, isn’t it? So Googling for lists of professional contacts is an excellent idea as a step in your sourcing process.

To find lists of professionals, prepare your imagination again. Clearly, Googling for “contact lists (<keywords>” will only land you on contact vendor databases ads. Everyone’s usual “Googling” using a few terms will never take you there.

The best list-finding search strings have two or three values of the same category (or more than one category) such as:

  • names
  • companies
  • job titles
  • email extensions
  • phone area codes
  • (etc.)

You can Google for lists of values like country phone codes or top companies in an industry and then use the values in search strings.

Here are some examples that work like magic (even though I have not used any advanced operators):

What are some clever Google search strings that helped you find unique  contact lists? Please share.

How to Clean Up CSV Export

booleanstrings Boolean Leave a Comment

As Sourcers, we have to work with exported data. LinkedIn Recruiter, Instant Data Scraper, and other scraping tools provide export to CSV with the wrong coding, that may look like this:

Looks familiar? Here is how to straighten it out (thanks to David Galley for the tip!)

Step 1. Open a new Excel file and choose Data/From Text/CSV:

Upload the CSV file.

Step 2. Choose “Unicode (UTF-8)” and load:

Done. The coding is straightened out:

My favorite scraper is the contact finder SalesQL because it provides:

  • Excellent coverage across industries and locations
  • Private and work emails and phone numbers
  • Adding lists of LinkedIn URLs from a LinkedIn search as well as LinkedIn X-Ray
  • Generous 100 free credits per month
  • Bulk LinkedIn URL upload

The dashboard looks like this:

Try it out if you haven’t!

 

 

 

 

 

 

The US vs Europe: Cultural Differences

booleanstrings Boolean 4 Comments

I recently gave a private training which included an overview of cultural differences. I thoroughly enjoyed it!

I moved to the US from Russia in 1991, having received a three-month contract as a Mac Developer at the Smith-Kettlewell Eye Research Institute in San Francisco. They converted it to a full-time position midway and helped me obtain a Green Card, at which point I could leave.

It was my first trip abroad, and I had no clue about the American language and culture. But it was quite a soft landing: the staff were friendly and accommodating. My first boss was entertained by my exotic background and was teaching me about the culture. He has even gone through a comic book with me explaining why this was funny.

Later on, I took a helpful Berkeley Extension course on business behavior.

I live in a very diverse area. One of my software teams had an Indian, a Chinese, a Bulgarian, and a German (who could drink 12 bottles of beer). One of my son’s schools had 12% white kids.

In Russia, my environment was Math students and professors, about a hundred people who knew each other. Here, I was exposed to “everybody.”

I am still fascinated by cultural differences and feel better chemistry with my European friends and colleagues than Americans.

I wholeheartedly recommend the book The Culture Map – by Erin Meyer – it covers differences between cultures in business.

I recommend https://relocate.me as an informative resource for relocation between countries.

Here are some “starter” cultural differences.

  • The US is all about success – education, career, family, owning a house.
  • English has different spelling and meaning in the US and the UK – Google it.
  • Americans love expression from baseball, American Football, and basketball in business
    • To keep the ball rolling
    • To drop the ball
    • To stay ahead of the game
    • To call the shots (etc.).
  • Americans call March 14 the Pi Day (3-14).
  • Reddit, Discord, and Slack are popular but not Telegram or WhatsApp.
  • It is OK to use Facebook Messenger work-related – not so in Western Europe.
  • Americans go overboard about Diversity– take a look at https://help.apple.com/applestyleguide. It is no longer OK to write “he or she,” “men and women,” “Grandfathered in,” “Blacklist,” or “white-hat hacker.”
  • We do not have GDPR.
  • The most expensive real estate is in San Francisco and New York.
  • Americans write “Hi <name>,” Europeans, “Dear Ms./Mr. <lastname>.”
  • Americans drive everywhere, and restaurant portions are enormous; being overweight is a national problem.

What can you add to this?

We are planning a live webinar soon.

Whom to Follow

booleanstrings Boolean Leave a Comment

Speakers and Sourcers

  • David Galley (US)
  • Glenn Gutmacher (US)
  • Aaron Lintz (US)
  • Andre Bradshaw (US)
  • Glen Cathey (US)
  • Guillaume Alexander (France)
  • Victor Soroka (Ukraine)
  • Balazs Paroczay (Hungary)
  • Hung Lee (UK)
  • Vanessa Raath (South Africa)
  • Josef Kadlec (Czech Republic)
  • Юлия Кузмане (Russia)
  • Bas Westland (Netherlands)
  • Marcel Van Der Meer (Голландия)

Best sourcing conference by Phil Tusing – Sourcing Summit

Best newsletter by Hung Lee

Sourcers vs. Recruiters: I Have Changed My Mind

booleanstrings Boolean 6 Comments

When I started sourcing and teaching sourcing, I believed that Sourcers should be separate. Sourcers are nerdy, introverted, and know the technologies. (As an introvert, I get tired after speaking with two or three people, then need down time.) Making Sourcers reach out to potential candidates is not utilizing their top skills. Recruiters are good communicators, extroverted, friendly, and outgoing. The best personalities for the two roles are different.

However, I now believe that, in most cases, it is best for Recruiters to source. It is not rocket science. Everyone can learn to Google, LinkedIn, and use productivity tools.

The reasons to not separate the roles include:

  1. If a Sourcer speaks to a candidate, then, Recruiter, and only then, the Hiring Manager, it creates a poor candidate experience.
  2. In this economy, you are likely to lose the best candidates amidst all the scheduling.
  3. Information gets lost in the communication between the participating parties.

It is best to train your Recruiters and let them both search and reach out.

A separate Sourcing function at your company can serve three purposes:

  1. Looking for hard-to-find talent
  2. Working with urgent requisitions
  3. Building talent pipelines.

My partners and I offer Sourcing Services covering those needs. We generate a list of matching prospects along with contact info, and the client reaches out themselves. We have worked in all industries and across locations, and it has not been boring!

It is often hard to sell our services to the companies’ management since we cannot guarantee any outcome – not a given number of leads or placements. But almost all of our clients come back with more projects since it works well for them.

What do you think? Should Sourcers and Recruiters be separate functions? Should Sourcers talk with potential candidates? It is funny that, after so many years, we are not on the same page!

 

Asterisk * vs. AROUND(X) on Google

booleanstrings Boolean Leave a Comment

Both the Asterisk * and AROUND(X) are proximity operators on Google and provide their own benefits.

The Asterisk stands for one word or a few shorter words. “<keyword1> * <keyword2>” will find phrases where the keywords are close together. Example, exploring company email formats:

Using more Asterisks will find phrases where the keywords are further apart:

You cannot use the Asterisk with other operators: intitle:”account * at salesforce” returns nothing.

Using the Asterisk at the beginning or end of a phrase usually pushes the phrase into snippets:

AROUND(X) looks for the terms to be X or fewer words apart, and in either order. Example:

Even when Google documented all of its operators, they said nothing about AROUND. Right now, the operator works, but there have been years when it did not.

You can use AROUND with other operators:

The keywords in AROUND are not interpreted: manager AROUND(8) people site:linkedin.com/in -manager produces no results.

Here are some applications of AROUND.

Search for <firstname> AROUND(2) <lastname>: 

will find jones mary, mary l. jones, and mary lisa jones.

AROUND gives the LinkedIn X-Ray “Graphic” hack a nice spin:

will find LinkedIn members belonging to organizations with the word women or latino. It is a way to search for Diversity.

On LinkedIn public profiles, the word “connections” is next to the location. So you can search for locations like this:

Search for a title at a past company:

Can you suggest other applications?

Unfortunately, Yandex has dropped its proximity operators and Bing’s near(X), while being documented, does not currently work.

You will find the full list of 21 Google search operators here. Join me next week for the class Boolean Strings Basics & Beyond and learn about every one of them!

 

Can You X-Ray for Profiles? A Simple Test

booleanstrings Boolean Leave a Comment

Can you X-Ray for profiles on LinkedIn, XING, Facebook, Instagram, Github, Stackoverflow, Meetup, Behance, Quora, Slack, Discord, Snapchat, VK, Slideshare, CrunchBase, etc.? There is a simple way to find out.

Public profiles uniformly have members’ names in the page titles. Pick a common name like Jim Smith or Mary Jones, use it with the intitle: operator and combine with site:<site.com>. If you see profiles in the results, X-Ray is on. That’s it!

Try:

site:LinkedIn.com intitle:”jim smith”

site:XING.com intitle:”jim smith”

site:Facebook.com intitle:”jim smith”

site:Instagram.com intitle:”jim smith”

site:Github.com intitle:”jim smith”

site:Stackoverflow.com intitle:”jim smith”

site:Meetup.com intitle:”jim smith” (uh-oh – previously public Meetup profiles went down)

site:Behance.net intitle:”jim smith”

site:Quora.com intitle:”jim smith”

site:Slack.com intitle:”jim smith”

site:Discord.com intitle:”jim smith”

site:Snapchat.com intitle:”jim smith”

site:VK.com intitle:”jim smith”

site:Slideshare.net intitle:”jim smith”

site:CrunchBase.com intitle:”jim smith”

Additionally, you can examine the resulting profile pages for common structure such as URLs, titles, and standard wording and derive a precise X-Ray template. Keep in mind that sites shift – URLs, page titles, and common wording change, and previously X-Rayable sites may become private.

Join us tomorrow for a repeat of the Advanced X-Ray webinar (only a few seats are left).