more: Healthcare Sourcing Techniques

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In sync with the times, I want to share some Healthcare sourcing tips to implement in addition to what you are already doing.

I know that sourcing for Healthcare professionals is challenging from experience. Last year, I ran a project sourcing for (bedside) Registered Nurses with 2-3 years of experience for a hospital in Texas. While LinkedIn is a site that can verify the length of experience, it produced a ridiculously small outcome: 200 RNs out of tens of thousands RNs who live in Texas.

However, the industry has its advantages in terms of finding info online, including:

  • There are searchable databases
  • Hospital websites have bios and contact lists
  • Hospital websites have “structure” for filtered search via Custom Search Engines

Sites, where you can search for doctors and nurses, include doximity.com, healthgrades.com, vitals.com, and zocdoc.com (Google these together and you will find more). Physicians’ profiles usually have degrees, licenses, specialization, education, affiliation, address, phone number, and ranking. Some profiles have more info, including email or gender. However, searching within the sites is limited.

Luckily, these sites have public profiles, which we can X-Ray, for example, like this:

site:doximity.com/pub gastroenterology intitle:”San Francisco”.

Examine profile titles and URLs for each site to see if it’s possible to search for specific values such as specialty with inurl: or intitle:, like I did in the example.

And we can do even better using Custom Search Engines (CSEs). I used to work with doctors back when I was a Software Developer and have found them to be “computer-unfriendly”. So I was surprised to discover that healthcare-related sites like the ones above, as well as websites of hospitals, are rich with structured Schema.org-based information, which we can query. (Hospitals may have strong IT staff or use some standard hospital website-building tools, I don’t know.)

Schema.org provides healthcare webmasters with many Objects such as Hospital, Physician, and MedicalOrganization. Now, if you are prepared to deal with gibberish-sounding “more:p:” search operators, you can take advantage of searching for Objects’ values. If you are not, sorry! Please read some other posts.

In the following examples, I will be using the CSE Search Everything, which has no restrictions. (The reason to use a CSE vs. Google.com is that only CSEs support operators to query pages’ structure.) You can modify each of the links below to serve your needs.

Physician search across sites:

more:p:physician plastic surgeon cleveland.

If you start seeing many results from one particular site in searches like the above (which is likely to happen), you may want to X-Ray that site alone and also search excluding the site.

Search for Physicians by specialty (add your keywords):

more:p:physician-medicalspecialty:dermatology.

Search for keywords in description:

more:p:physician-description:ear*nose*throat

(The Asterisk * serves as an AND operator).

Search for hospitals by name:

more:p:hospital-name:saint*mary

Whoever worked on creating Schema Objects had a weakness for all things medical:

There is even an Object for Medicalwebpage. There is lots to explore.

Among general search sites, Doximity provides especially rich structure to query:

Our tool Social List has Agents for Doximity and Healthgrades, allowing you to search without writing out operators and export results in Excel.

If you have any questions, please let me know.

 

 

 

 

 

 

LinkedIn Activity Called Working from Home

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I have just discovered that X-Raying LinkedIn on Google in the following manner:

site:linkedin.com/in “image for * * activity called <keywords>”

– finds profiles that have shared a status on LinkedIn that includes <keywords>. Combined with professional terms such as skills and job titles, the search can point you to people who are more open to new opportunities, as an example. We are sort-of getting a flavor of structured search, similar to this example, since the <keywords> after “activity called” would be searched for in member’s shares only. (I’ll work on saying the above more clearly if you feel you need it.)

Here are some examples (to be combined with other parameters):

These X-Ray searches can provide value, both as a sourcing tool, looking for individuals, but also as a research tool, looking, for example, where work from home is popular or who is hiring and firing.

If you have other ideas on what to include along with the “activity called,” please share!

 

Hack: Search for Female Names with This CSE

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Are you searching for diversity? Using the same “synonyms” trick as described in Hack: Use 500 Keywords, Not 32, on Google, I have created a Custom Search Engine that looks for the 50 most popular women’s names. Add location, title, or skills, and you will get a list of women’s LinkedIn profiles with the required qualities.

Example search: python developer bay area. Here is what it looks like:

The results may have false positives, but the majority will be on target.

You can create other diversity CSEs using synonyms, for example, a list of Latino last names, or African-American colleges. Let me know if you want me to make one for you.

Please join us for the updated webinar “Sourcing Hacks” on March 18th, 2020. We will share some new hacks (and some old ones are gone).

Google CSEs Go Wild with LinkedIn URLs

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This post will be of interest to those who use or create Custom Search Engines, in particular, to X-Ray LinkedIn for profiles (and avoid high LinkedIn subscription fees). The post is somewhat technical except for the first few paragraphs. We have a webinar on CSEs if you want to dig deeper into CSEs.

You might have noticed that the LinkedIn X-Ray Custom Search Engine you may have bookmarked, that used to work, will now return few or no results on seemingly open-ended queries.

Here is a new CSE to X-Ray LinkedIn that fixes that issue – I recommend using this one:

http://bit.ly/BetterLIXray

Now, for the technical part. For those who use advanced CSE search operators and create CSEs, here is what has happened over the past few months. We are seeing more than one unexplained behavior; it applies to LinkedIn URLs only. Nobody seems to have any clue why this is happening, so this information below is more like a weather report, not a “how” and “why” post. (We had to work very hard to “fix” the LinkedIn Agent in Social List).

  1. CSEs no longer “see” the Person object in public LinkedIn profiles, and neither do CSE APIs. Profiles indexed more than a few months ago still have “Person” in Google’s cache and can be queried, but newer profiles don’t have it (and do not have “Hcard” either). Because of that, searching with more: operators will find only older, indexed a while ago, profiles. Creating a Person-based CSE, where you specify the object in the Control Panel, will also limit the results to old.
    (There is info on “Person” – for which we would love to search – when you examine the source code for public profiles, but somehow Google fails to see it).
  2. If you include both “linkedin.com/in” and “linkedin.com/pub” as sites to X-Ray in your CSE, it will be producing very few results, with the keywords mostly in page titles.
  3. If you include “site:linkedin.com/in OR site:linkedin.com/pub -pub.dir” as a string to add to each query and make the CSE search everywhere, it will work for a CSE definition. That is how I built http://bit.ly/BetterLIXray. However, if you make an API call for that CSE, it will be finding pages on LinkedIn, but all sorts of pages, like jobs – not just profiles. Odd.
  4. You can find profiles in particular countries by including URL templates, with the use of the asterisk (which you shouldn’t have to do), like “uk.linkedin.com.in/*”. You can make refinements for a list of countries in one CSE, but make sure you append the asterisks to the templates. Here is the current list of all countries if you need it: LinkedIn Countries.
  5. When searching, avoid using ORs, search several times instead – otherwise, you will be getting fewer results.

Social List (which is based on CSE APIs) is up and running! We have found a way around all of the weirdness.

It’s hard to say what to expect in the future months, but let’s hope that mutual understanding between CSEs and LinkedIn will be restored – and improved. It would be nice to search not only for schools, companies, and headlines but also for locations.

Cheers!

Competitive Intelligence from Open Datasets

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Do you know about Open (public) Datasets? Google got its Dataset Search out of Beta, and you should bookmark it.

Lee Candiotti has asked this question on our group

Great question.

Let’s start with ways to locate datasets, in addition to Google’s tool. You can simply Google to locate datasets. And once you start looking, it’s endless! There’s Google-owned Kaggle.com. There are lists of datasets. There are gigantic lists of datasets and lists of favorites, and suggestions on Ycombinator.

There is an alternative way to find datasets, and that is in a Custom Search Engine, using a schema.org Object “Dataset”. I have created one, try it.

What can we expect to find in datasets? Industry, employment, and demographic data, but also, sometimes, contact lists and organizational charts. Datasets can be awesome for Competitive Intelligence.

Here are some nice finds.

I got lucky having found a downloadable list of 60K+ CEO and VP email contacts. (You are welcome! Please use it with care.)

There is a downloadable 7 MLN  US companies dataset at Peopledatalabs. It includes Company Name, Domain, Linkedin, # of Employees, Year Founded, Industry, and Location (city, state, country).

Here is a list of 5K job titles and relevant skills, which might help if you are searching in an unfamiliar industry.

Some dataset sites have visualizations, like this – Diversity in Tech. Many offer Dynamic Insights in interactive dialogs.

Come to our new webinar on CI to learn more! Today’s class was sold out but we have scheduled a repeat. Don’t miss it!

 

 

 

“Dynamic Insights”, a Competitive Intelligence Concept

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I am excited to be presenting our first “Competitive Intelligence for Recruiters” class on Tuesday, February 25th, with an optional workshop on Wednesday.

“Competitive Intelligence” (CI) is gathering and analyzing information about the industry, business environment, competitors, products, and services. CI is typically associated with business decision-making, but I know you would agree with me that it’s entirely applicable to Sourcing. (It helps when generating those long OR strings with company names, for example!)

Advanced search dialogs on the platforms where it is available supply useful intel right in the user interface. Entering search criteria will cause the search dialog to generate “Dynamic Insights” – a new term we are introducing – into the distribution of the results across various categories (e.g., companies, locations, industries, or salary bands).

For example, on Indeed Jobs and Resumes, you can enter a location and job title or skill and get a list of company names. Or, enter skills and see a list of common job titles for people with those skills. You can gain these insights without a paid subscription.

LinkedIn also offers interactive search dialogs, so it’s another site to gain Dynamic Insights. The dialogs working for the purpose are the Alumni and Company Employees search and the “old” version of LinkedIn Recruiter’s “View Insights” function.

Note that you can achieve a similar effect (to using interactive dialogs) by scraping and parsing search results, from Google or elsewhere, since you can then filter and sort the data in Excel.

Even without a standardized term, many Recruiters intuitively incorporate Dynamic Insights into searches. But if you are not doing so, now is the time to start!

If you want to learn how this and other CI methods can help improve your Recruitment performance, please join us at the Competitive Intelligence class. We expect this course to fill up quickly, so register now to reserve your place!

Dealing with the Sales Navigator Death

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So many professionals on all social channels are complaining about the imminent loss of the Gmail Sales Navigator extension that it is hard to believe LinkedIn that the tool was underused.

While there are many tools identifying people by email, the power of the extension was that it matched exactly right, for obvious reasons.

Not all is lost, though! Here are some options:

1) Look up contacts with Outlook 365
2) You can find a person from an email in LinkedIn Recruiter (or do so for a list). The import function got much worse in the “new” version but will still work with 50 records or so (vs. 5K in the “old” version).
3) You can upload a list to your personal LinkedIn.com account, then check this link –https://www.linkedin.com/mynetwork/import-contacts/results/member. This function has been there forever, is buggy, and seems to have been forgotten. There are no ways to delete people from the list and no sensible order when it shows profiles. With a bit of a volume, it becomes a challenge to recognize “who is who.” However, with the increased need, we should revisit it. (And perhaps come up with some automation as well).

The Best Boolean String for Secret Clearance is Indirect

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This is a guest post from David Galley, Director, Training Programs at Sourcing Certifications.

The #1 question people have when they start sourcing is, “what is the best Boolean string to find the people I am looking for?”

Searching for Secret Clearance is not straightforward, and there’s a significant demand for cleared specialists, especially in the Technology sector.

Sometimes a search is as easy as “I am looking for” “have secret clearance”, and other times it’s sufficient to flip through your favorite thesaurus to find some word variations to develop a monster like this one. But sometimes the key criterion cannot be found with a keyword search, no matter how many ORed variations you include.

Let me paraphrase a perennial example on various recruiting Facebook groups: How do you find people who hold US security clearances (e.g., Secret, Top Secret, TS/SCI, Q, or L)? A search for specific types of clearance, or even the terms “cleared” or “clearance”, finds a tiny fraction of the 4MM actively cleared workforce. Sure, not everyone is on LinkedIn, but even so, the numbers fall short of expectations.

The key to success in this situation is the concept of indirect (aka inferential or implied) search. What evidence can we search for, which implies that the people we find meet the criteria? Let’s start with the idea that there are companies, especially contractors in the intelligence and defense industries, that make active security clearance a prerequisite for specific roles. Whether or not professionals working in those roles list the clearances in online social profiles, we know they must be cleared.

So, which roles and companies are these? An example search path to learn which roles require clearances would be:

Step 1) Find a list of top contractors for the industry (e.g., defense), with a simple Google search list of top defense contractors

Step 2) Pick a list to work from, like this one from Wikipedia

Step 3) Search on job boards with terms relevant to the clearance you need, to learn which roles (and locations) within a given company require them. This search on Indeed active secret clearance company:Lockheed turns up several job ads, including a Senior Mechanical Thermal Engineer in Orlando, FL.

Step 4) Since we now know that Lockheed requires an active Secret clearance for Mechanical/Thermal Engineers in Orlando, we can search on LinkedIn for Thermal Engineers who work at Lockheed, located in the Orlando, Florida Area.

(A search for all Thermal Engineers on LinkedIn who mention “secret” on their profile finds far fewer people!)

Note that you can apply this same process to any search, even ones where direct keyword searches perform well, to discover “stealth” talent that you (and your competitors) may have previously overlooked.

Check out our next Sourcing Webinar – How to Find and Attract Technical Talent – Tuesday, February 18. Register and receive the slides, recording, and a month of support. Seating is limited – sign up now.

(And, we have a Competitive Intelligence webinar in the works. Stay tuned!)

Scrape Google Maps

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If you are sourcing for professionals who provide services such as Accounting, or looking for office locations for a specific company, searching on Google Maps will provide valuable information. Scraping a Maps search results page allows you to filter and enrich the data, and you can do it quite simply, with no coding involved.

PhantomBuster is a wonderful collection of automation scripts; they recently released a Google Maps Search Export. However, my preference for scraping Maps is a favorite tool Instant Data Scraper because it goes over all the results vs. partial. (There are also many specialized map scraping tools but I don’t think anything more complex is more beneficial).

Let’s look at an example. I have searched for accountant near manhattan and ran the Instant Scraper:

Within seconds, I got this table with 309 rows, type of business, whether it is a Certified Public Accountant, office addresses, websites, ratings, and numbers of ratings submitted:

Where else would you find a list of CPAs in Manhattan this fast? 😉

Please join me for an updated sourcing class Web Scraping For Recruiters on Tuesday, February 11th, with an optional hands-on practice the next day. Seating is limited, and the class is one of our most popular, so register now!

 

 

 

 

 

Sourcing for Devs on Dev.To

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Dev.to is a relatively new site where developers discuss how to build software, and it is quite a Sourcer-friendly site. 😉

A profile can have a location, education, skills, links to other profiles, content keywords, and, often, public email contact:

Internal search for members is too weak to be useful. But we can X-Ray the site for profiles like so:

site:dev.to -site:dev.to/*/* “united kingdom” javascript.

Since Google recognizes hashtags in search, and the site widely uses hashtags, we can search in a more targeted way, for example:

site:dev.to -site:dev.to/*/* #javascript “gmail.com”.

With a Google search like the above, it is not hard to scrape the results and get a list of prospects along with emails. It is a matter of picking the right scraping tool.

Please note, we are going to run an updated version of our always-popular Scraping Webinar on Tuesday, February 11th. If you are curious about the topic, it is a place to be.

This Custom Search Engine – http://bit.ly/devtoprofiles (X-Ray Dev.To) – will look for Dev.to profiles. Using it eliminates the need for the operator site: and allows to search for members’ profiles, for example:

#javascript amsterdam

There is not a whole lot of “structure” on the profiles (much less than on Github’s, for example), but we can search specifically for bios with a Custom Search Engine:

more:p:person-description:java.

I hope the resource will prove useful to some! Let me know if you have any questions.

We are running the How to Find and Attract Technical Talent on Tuesday, February 18th. Join to get a complete IT Sourcing toolbox. (Some tools are cross-industrial.) Seating is limited.