Fifth Edition of “300 Best Boolean Strings” & One More String

booleanstrings Boolean Leave a Comment

I am glad to announce that you can preorder the fifth edition of my popular eBook “300 Best Boolean Strings” at

BooleanBook.com

For the 5th edition, I had to replace about 35% of strings that no longer brought up remarkable results, and added new strings.

And here is a new String for you. To X-Ray Facebook for specific content, use this (replace keywords with your terms):

site:facebook.com “text that says * <keywords>”

For example,

Get 300 more strings in the new edition of the eBook!

The Unconventional Boolean

booleanstrings Boolean Leave a Comment

I have realized that I have been using some “unconventional” Boolean Strings in sourcing. This technique applies to LinkedIn or any database, but not to Google (where ORs are rarely helpful and long ORs are tricky).

Let me explain. It is straightforward to search by ORs of synonyms, for example,

Title = (Senior OR Sr. OR snr.) (software OR java) (developer OR engineer OR coder) (etc.).

On LinkedIn, we must do this because its semantic interpretation is flawed. But here is a twist.

Collect keywords intended for the title field and keywords, and, optionally, employers, and skills. Give the word “weights,” depending on how important they are. For example:

  • Java – must have
  • Back-end OR Full-Stack – must have
  • Developer or its synonyms – must have
  • Javascript OR Python – nice to have
  • Elastic search – nice to have
  • MongoDB or similar – nice to have
  • Scalable or its synonyms – a plus
  • Healthcare OR Medical Device industry – a plus

Group must-have, nice to have, and the “plus” keywords into OR statement, and search for the resulting string. (If you wish, use more granular weights.) Depending on the resulting quality and number of results, put the expressions either all in the Keywords or some, in the title and other fields separately. Run something like this:

Keywords = Java (Back-end OR Full-Stack) (Developer OR engineer) (Javascript OR python OR elastic OR mongodb OR nosql) (scalable OR performance OR healthcare OR “medical device”).

Then, you can expand each of the ORs in the string to accommodate the most essential and optional terms and add exclusions if you see false positives (for example, managers). You can also move the terms from the keywords to the title to see if you get more targeted results.

You will be un-digging results that nobody else does.

Try it!

 

 

 

 

 

 

How to Read the News Behind Paywalls

booleanstrings Boolean Leave a Comment

I love reading Recruiting Brainfood and the industry discussions that Hung holds so well.

Unfortunately, in the newsletter and in Facebook discussions great shared content is often behind a paywall. Here is what you can do about it.

  1. Copy the URL and rid of its part after ?
  2. Use the operator cached: followed by the URL, for example:

cache:nationalgeographic.com/magazine/2020/09/the-robot-revolution-has-arrived-feature

Read the post uninterrupted!

If the cached copy does not come up, use Plan B.

Google for a phrase from the news piece, for example: “The robot revolution has arrived · Machines now perform all sorts of tasks…” You are likely to find the full story there.

You will not find this material by any Googling though.

 

 

X-Ray LinkedIn for the Length of Employment and Five More Filters

booleanstrings Boolean Leave a Comment

For the obvious reason, recruiters do not want to see profiles of people who have been employed for less than a year at the current company. The X-Ray technique I describe below allows you to:

  1. Narrow down to longer-term employees
  2. Search better for #opentowork
  3. Narrow to location
  4. Search within the Headline
  5. Search for a keyword within the current job description
  6. Search by school and years of graduation.

Once you follow the steps, you may not need the expensive Recruiter or Sales Navigator subscription! This is free and unlimited.

Here is the idea: if you scrape fields of interest, such as the length of employment, from each result and export that, you can filter out those who:

  1. recently started working at a new employer
  2. liked someone’s #opentowork status or one of “people also viewed” had it on the profile
  3. have worked at the location but live elsewhere
  4. filter by the headline
  5. scrape the last job description and filter by it
  6. scrape school name(s) and filter by it
  7. same with the school dates.

As always, be careful when scraping.

As many times before, there is nothing new in the hack, except you now have a choice of five intelligent scraping tools that do not require coding and facilitate deep filtered search.

Who does not like hacks like this? (Please comment.)

With that, I am happy to let you know that the Second Online Sourcing Day is happening on September 17th, 2020, and you are invited!

Our team has grown and we have lots in store to share with you all. Expect to be as surprised and inspired, as the first time.

If you cannot wait, here is six hours of our material from May, 2020.

This is easily the best ROI on content vs. investment if you want to stay competitive in sourcing.

 

The First Name @ Mass-Email-Finding Hack

booleanstrings Boolean 2 Comments

Our online lives depend on little things. Slow performance and lack of functionality caused by limited computing power restrict our data gathering ability in seemingly small but consequential ways. (As always, our perceived needs run before computers’ ability.)

As an example, Google will not search for the symbol @ as a part of an email address. At this time it would be too expensive.

Google does, however, notice the periods, and we can take advantage of that.

While figuring out how to massively source emails, I noticed that many companies predominantly follow the jane.doe@company.com format. And some, follow it diligently.

Here are the unique stats we have collected: of Fortune 500 companies, 72 are E100, and of those, there are 56jane.doe”s and 10jdoe”s:

I am assuming that companies that deviate from the preferred format still have a high percentage of jane.doe emails.

The vast majority of corporate emails start with a first name followed by a period and end with a .com or another extension.

Google handles both the name and .com as separate words. Realizing this gives us instant sourcing power. We can un-dig pages with emails and contact lists that Google won’t rank high otherwise.

To run such searches, first, Google for common first names. Start with a couple of first female and male names. Add professional keywords as usual (but not too many). Do not forget to put “at” before the name. You can generate a series of queries in Excel, run, and collect all emails with our Email Collector.

Here are two sample searches:

The British say “on,” not “at,” so you can collect a few more.

Just dropping “at” is also an excellent idea!

Join us for the always-popular and practical workshop “Find Anyone’s Contact Info and learn various email- and phone-finding techniques this week.

P.S. Notice how many of my latest posts reveal approaches that have been available for years. There is so much more to discover!

Visual Research and Validation

booleanstrings Boolean Leave a Comment

In this post, I outline two uses of image search in sourcing. For these purposes, searching in Google images is “good enough” but Bing and Yandex will also work.

Visual Research

My sourcing projects come from different industries (which I love.) There is a particular way I identify target companies for initially unfamiliar industries. To figure out what a company does, I search for its name in images.

Here are two recent examples.

In a project to hire aviation professionals for a large airliner, I needed to narrow down to companies that do the same. Companies making small airplanes, helicopters, spaceships, or military planes were the wrong targets.

First, I found a list of companies that employ these specialists. I searched on LinkedIn using the job titles and terminology and seeing which companies come up. (It is easily done with Recruiter’s “View Insights”). I then searched for each company name in Google images to find out what they make:

Depending on what I saw, I kept or excluded the companies from the search.

In another project, we were looking for Hardware Engineers to work with complex biotech equipment. Googling company names in Images, I could see what each company makes.

Image search can also help to find out what a word (perhaps in a foreign language) means. You can use it, for example, when searching for unfamiliar job titles:

 

Visual Validation

The second use of image search is verifying whether your Google search is on target. It is obviously applicable to Diversity sourcing.

Here is an example showing that the Boolean String produces the right results:

Having visually verified that your search works right, you can go back to “all” results for review.

Check out our “Sourcing Hacks” book, 3rd edition, almost ready for shipping!

Tomorrow, Friday, I am giving a lecture on all the material (and all our webinars come with a month of support).

 

 

 

Hack: Find LinkedIn Members by Company Size

booleanstrings Boolean Leave a Comment

Recruiter is the only LinkedIn account offering member search by company size. We used to have it in business accounts some years ago – remember this dialog above? –  and now it is gone. We used to be able to search for companies by size but now Sales Navigator is the only account allowing that.

Here is how to search for LinkedIn members by company size by X-Raying, using a technique similar to this.

Step 1. Let us start with company pages X-Ray. This search –

“51-200 employees” site:linkedin.com/company “new york” “hedge fund”

– will find Hedge Funds in New York employing between 51 and 200 people. To proceed with searching for people who work at these companies you could scrape the company names and run an “OR” of them. However, various Boolean limitations, both on LinkedIn and Google, can make this cumbersome. You can search for current and past employees of these identified companies in a better (and fun) fashion.

Let us modify the above search by going to Images and restricting results to LinkedIn and images size 200 by 200 (which is both company and school standard LinkedIn logo sizes).

Now you have a collection of company logos used on LinkedIn.

Step 2. Drag each company logo into the reverse image search box and add your member search parameters (site:linkedin.com/in plus a job title, skills, or location):

Note that this search will find both past and present employees of the company. Since the current company name is in the profile page title, you can also look for companies past but not present with this technique by adding -intitle:<job title> to your search.

You can apply the exact same technique to search for schools’ alumni.

Please join me this Friday to watch a parade of hacks in a fun and useful 90-minute webinar. Each hack will ad power to your sourcing toolbox. You will spend less time on the same project, find matches that you could not before, automate repeated tasks, and view relevant data (vs. false positives). Register at

Sourcing Hacks – webinar Friday, August 14th, 2020.

Seating is limited. The webinar includes one month of “hack” support.

 

 

Five Tools to Scrape Search Results

booleanstrings Boolean Leave a Comment

When you X-Ray on Google or search on LinkedIn, Facebook, or Github (etc.), you see results that are links with previews (called “snippets” in Google). The problem is that snippets never provide enough information to qualify a result. You can try very hard to phrase your search yet you should always expect false positives. It is time-consuming to click and review every result. Additionally, saving “good” results is a challenge.

Here is an example. If you X-Ray LinkedIn trying to narrow to a location, false positives are unavoidable. This search – site:linkedin.com/in “san francisco” intitle:sourcer intitle:facebook – will find not only Sourcers at Facebook in the Bay Area but also those who used to work in San Francisco and now live elsewhere.

Scraping the information under results’ links and exporting it in Excel can speed up individual reviews many times. This is because, in Excel, you can sort, search, and filter columns (such as “Location”). If you have access to such functionality, you can do wide searches and catch results you would not find otherwise after filtering.

Another use case for scraping under links is delivery to your client. For example, you might have a Recruiter project with identified prospects and need to put the results in a Google doc for sharing with a client. (This is what I do every day).

Here is a list of the best five non-technical tools for under-links scraping that I am aware of. None of them require any coding.

  1. Phantombuster. Search on LinkedIn and parse the results. The output is impressive, having lots of variables scraped. However, you cannot do volumes (hundreds).
  2. Outwit Hub – somewhat tiring to use since it slows down fast. But pointing Outwit Hub to scrape within each result is just one mouse click away. It can scrape your connections, including email addresses, out of the box. (On a fast computer, I got 7K+ records!)
  3. Ally from include.io (Beta). Ally allows you to scrape search results (on Google, LinkedIn, Facebook, or other sites), save results in an internal list, and do a second round of scraping the links. The advantage is that you get data from search previews as well as results themselves, combined.
    Since I have started using Ally in Recruiter, both for results filtering and sharing with the clients, my sourcing speed went up. (I do 80% less copying and pasting).
  4. ScrapeStorm is a new and promising application. It is downloadable. (I hope they will do a web version). I was able to tune ScrapeStorm to go through LinkedIn X-Ray just in a few minutes.
  5. Social List. While the underlying technology does not rely on scraping (we use Google CSE APIs), you can search and export results in Excel. A big plus is that Social List gets its data through Google Custom Search Engine APIs and does not even “touch” LinkedIn.
    Here is what a result (using “Github Agent”) may look like:

(Please note that new Social List users must submit a credit card. But you will not be charged if you cancel early.)

P.S. As a matter of caution, all sites have protection against scrapers. Do not do too much at a time. On LinkedIn, especially.

Combine Reverse Image with Boolean Search to Find Who Likes What

booleanstrings Boolean 18 Comments

Here is a neat trick involving a “part-visual” search.

Did you know that, in Google Images, you can combine reverse image search with additional search parameters such as X-Ray? Neither Yandex, no Bing offer to enter anything else when you upload an image.

The search pictured above finds public LinkedIn profiles in a unique way; here is how.

Since Google captures profile activity, including shares and likes when it gets a copy of each profile, you will find people who share that they got certified or “like” that their colleague got certified. Searching for likes (which reminds us of Facebook!) is not possible within LinkedIn.com. But this example “multi-media” search will find us people who know others who are certified and could be certified themselves.

So – you can search for likes from Google.

You can also expand the technology from the search for AWS-Certified people to search for anything expressed by a logo or an image – think organizations, skills, or technologies.

Here is another example. These people either posted “I am hiring” or liked someone else’s post:

Many more people “like” something vs. posting themselves. Those who are “passively” open to a new job would often hang out on LinkedIn and “like” job posts of interest. We can locate them this way. They are potential candidates or references.

Can you think of other creative combinations of searching by words and images together?

 

Your Homework

booleanstrings Boolean Leave a Comment

Motivating recruiters to source outside of LinkedIn is topic managers often bring up when signing up their teams for training. Yesterday, I spoke with a potential client, a thriving agency manager whose recruiters “won’t step outside of LinkedIn.” “How do I motivate them?” The conversation has prompted me to write my thoughts down.

Sourcing is not Rocket Science, but it is not science either! It never follows one channel of potential candidates. There is no tool, dataset, or process leading to the best results. Data is spread between sources. Sources differ in demographics they cover. Search capabilities vary, and some are paid. Things change daily.

But most importantly, search systems, even general search engines like Google, are increasingly skilled in interpreting the purpose of your search. (I am fascinated by the GTP-3 news.) Sourcing in 2020 is more of an Art and requires both intuition and hands-on practice and experience with a variety of search techniques.

One excellent – but involving substantial commitment from participants – way to stimulate learning without procrastinating – is to sign your team up for the Certification Exams. This past round, the exam takers passed 100%. We attribute that to each of them utilizing the new ebook “Sourcing Answers.” as part of their subscription. The ebook has 120 diverse questions with solutions, similar to our exam’s questions. (You can also use the book alone to assess your team.)

If you want, at least for starters, to only train your team in the sourcing basics, or have a custom webinar (or a series) delivered for your organization, encourage them to click every link in the presentations. It is just as vital that they try to modify examples to adjust to different sourcing needs. While the attendees can keep the materials forever, they should ideally practice in the first week after the webinar.

To promote the practice, we have started populating our materials with “Your Homework” slides in-between the content sections. Let me give you an example from today’s “Sourcing for Diversity”  slides:

Here is another one:

(Can you answer these? If you like these questions, send me your responses, and I will share more.)

The audience has received the homework with enthusiasm. Many said they are committing to doing it (we’ll see). One attendee was solving the homework during the lecture!

I trust you can complete all homework for the Diversity class in two afternoons (if you attended, let me know if you feel otherwise). You are welcome to send us your solutions as part of online support.

One of the teams of sourcers that we have been custom-training has a lively Slack channel, and everyone contributes their responses to the homework following each lecture. (Sure enough, there are Birthday wishes and baby photos, but there is a lot on the sourcing topic, and team members are engaged in discussions.) If your organization has a social channel, they would learn from each other – and develop a collective “team” language.

Part of the motivation is the enjoyment everyone will feel once they get amazing results!

Let me know if you agree or disagree.

Expect our future classes to come with “Homework.”