Social List Launch!

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Social List is Live

I am happy to let you all know – our new sourcing tool http://SocialList.io is up and running! We are getting our first subscribers, fast!

If you have not heard, Social List is an easy-to-use tool to instantly build lists of target social profiles, matching your search parameters, such as locations, employers, and job titles. We have developed the Social List Agents from our accumulated “know-how” of Internet search behavior, tweaking multiple search parameters “behind the code” to provide high-precision results.

I would like to invite you to see a demo of Social List 1.0, and ask any questions you might have, at one of the two webinar-based sessions I will hold:

  1. Social List Launch – Fri, Mar 24, 2017 9:00 AM – 10:00 AM PDT
  2. Social List Launch (2nd session) Mon, Mar 27, 2017 10:00 AM – 11:00 AM PDT

You can also view a video Demo and send us questions via the Contact page. And here is a detailed description of the tool – The Social List Difference.

If you are currently a Beta tester – thank you for helping us to shape up the tool! Your free access will be ending EOB Monday, March 24.

All new subscribers (at the introductory price of $49/month) will be receiving a two-day free trial, during which you can cancel and you won’t be charged, or you can continue the monthly subscription.

We will only be allowing a limited number of users in this first release. If you want your colleagues to be part of the launch, please tell them to hurry and sign up!

 

The Difference

Here is what our Agents can find, what you won’t find anywhere else:

User Feedback

Over the past month and a half, a group of Beta-testers has tried the tool – and everyone loved it. Here are just a few of our first user’s comments.

“Just found a fantastic candidate using your tool that I hadn’t come across with LI Recruiter. He literally had everything I was looking for and LI hadn’t returned him for me once.” – Katharine Robinson

 “This would be the first tool I would start my search with. I am very happy with the results – hardly any noise! – very focused and targeted answers. No whistles, no bells, just a straightforward, excellent search tool. A (very!) good job! ” – Karen Azulai

 “Fast, reliable, and simple list creation. Maximum results with minimal effort. Fun to find profiles I would have otherwise missed. I like that in addition to GitHub and LinkedIn (often the lowest hanging fruit), Social List offers custom search lists for Meetup, Zoominfo and Google Plus. — Sourcers at all levels will want to hop right in” – Maisha Cannon

What’s Next

We already have tons of ideas on scaling and expanding Social List, its integration with other services, building custom Agents for clients, and more.

I look forward to sharing the adventures of using Social List with you!

Thank you,

Irina Shamaeva

LinkedIn-Based IQ Test

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Whether Boolean, Semantic, or Machine Learning win the global search quality competition, remains to be seen. But a search system quality, by definition, depends on how well users can get results they want. For that, a user’s understanding of what to expect in the results is important (I hope you agree with the last statement).

Many modern systems have advanced search syntax – at a minimum, supporting the Boolean logic and the quotation marks for phrases. Systems also do some interpretation of the user’s intent when searching. For example, we can expect Google to: a) see if there are misspellings and offer corrections b) include synonyms for keywords without the quotation marks and for abbreviations; c) try to find pages where keywords are close to each other, in the same order, and rank those pages higher.

On ZoomInfo, we can expect that searches for VP and Vice President will return the same results.

On LinkedIn, however, there has been little interpretation of searches. It has had some title abbreviation recognition (VP = Vice President) on and off, different in Recruiter and personal, and it’s rather unclear where that stands. We’ve also long noticed that LinkedIn is interpreting people’s names – searches for Bob and Robert return similar (though not the same) results.

In any search, we expect that:

  1. If we add a keyword, the number of results goes down
  2. If we add a condition, the number of results goes down
  3. If we didn’t use the quotation marks, the word order should not matter.

So now, let me present you with an “IQ test”, based on the following searches, which produce unexpected results.

Question for you: what is LinkedIn “thinking” (i.e. what is the internal logic, where does any interpretation come in) when it produces these results? (And yes, it’s not what a user would expect.)

Email me the answers (or hypothesis) of why it works like that, or post in the comments. The first few correct responses will get a ticket at the upcoming

LinkedIn webinar

(sold out for this week but we have scheduled a new session).

Recruiting Recruiters – Sourcing Techniques

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A guest post by Martin Lee

Ironic isn’t it that some of the hardest people to recruit are recruiters?

Arguably they are the easiest people of all to find online by the very nature of the business. Active in advertising, networking, promoting, attending events and being “out there.” Is there a recruiter NOT on LinkedIn? ( I would love to know).

R2R / rec2rec (I think this is mostly a British term) and people responsible for internal hires place great value on their networks. Built up over a period of time from referrals and knowing who’s who in the market from experience. It’s old school, and I like it, but it shouldn’t be just limited to this. One person’s network will differ from another which limits the potential addressable market.

So for someone who recruits recruiters (agency or internal), the challenge lies in sifting through the gazillion profiles to find those genuinely good.

Let’s define “good” into some common requirements that are often looked for and then let’s apply a sourcing head into how we can search for them.

“Top billers” traditionally is a term for agency recruiters. Those that make the most profit for a company and naturally of interest.

Like all searches I start off as simply as possible, just try adding some keywords and phrases into platforms where the target people go, in this case, LinkedIn.

 

Lots of results from individuals and teams and as we are searching posts, not profiles – these are the latest results, people currently performing well.

No prizes for guessing who some of the 19 likes are from.

Of course, we could also run specific searches with a variety of terms: “over target” “promoted to” “exceeded quota” “won tender for” and many other. It would be worth creating a long list of these and saving as an alert if that’s what you’re interested in.

One of the challenges with LinkedIn is that you must think of all possible connotations of these terms. For example a search for “achieved 100% of target” would find different people to “hit my target” and what about all those people who were over 100% of target – do we really want to write “achieved 100% of target” OR “achieved 110% of target” OR “achieved 150% of target”, etc. And then there are the people who don’t mention it all; they just get on with it.

Cue Google.

The asterisk * “fills in the blanks” and finds any word(s). The two dots .. show numbers above the number specified i.e. 100.. will show all numbers above 100.

So we can run a search like this.

Additionally, we may be interested in people changing job title (often a promotion or further specialization) or returning to a company. We are operating under the assumption that if invited back they must have been successful before, and it’s a good assumption. Using the “new” LinkedIn:

Recruiters post jobs. Across social media, job boards and with their ATS’s – therefore isn’t that also a good place to look at their specific activity as opposed to what they say about themselves on a LinkedIn profile?

There are thousands of these platforms, but common ones include Taleo, Aplitrak (part of Bullhorn), Smart Recruiters and Indeed offers an advanced search option, which also allows you to remove employment agency jobs. There are lots to be found in here and get understanding who does what, where and to what level.

Or a search looking for recruiters at specific companies in a particular field?

Now all of the above is fine but here’s the thing – If the role you have is not a good match then no amount of clever sourcing on its own will do and you have to do your research first. Salary, bonus, benefits, responsibilities, travel, progression, culture & location are all factors recruiters will consider.

I’ll be digging into this important topic much more deeply at my upcoming

Webinar: Recruiting Recruiters 

Date: Tuesday, March 28th
Time: 1PM British Standard Time (Check your local time for the Webinar)

LinkedIn Tip Sheet Error And a New Hack

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We shouldn’t be mixing the level of service, quality of software, and changes in features and pricing as a reason to use or not use LinkedIn. OK, LinkedIn has taken us along for a ride, adding and removing features the platform used to have years ago and making it “news”. BUT – it would be silly and unproductive of us to walk away from the incredible pool of self-entered professional data. It’s just not an option. Besides, we may be getting an adequate search system back, after all!

Apparently, it is hard not just for us, uninformed users, but for LinkedIn itself to ride through so many redesigns and individual roll-outs within such a short period. Let’s take a look at the screenshot above, which is THE guide for advanced searching at the moment. This syntax, as in the example, doesn’t work; please take a note of it.

There needs to be one correction in LinkedIn’s search tip sheet. This syntax –

title:(CMO OR “chief marketing”) (wrong!)

– doesn’t do what you think it should do, i.e. look for one job title or another. Compare with searching for

a:(CMO OR “chief marketing”)

or just

CMO OR “chief marketing”

– and you will see the same results. That means that the operator in front of an OR statement does. The first search above does just a keyword search, not a title search. To search for one title or another, we need to write it differently than LinkedIn tells us –

title:CMO OR title:”chief marketing” (correct, at the moment).

Our friends from Social Talent have also noticed the discrepancy and reflected in a recent post. Unfortunately, the wrong tip sheet gets propagated by bloggers copying it:

It would be nice if LinkedIn either implements the syntax it documents or fixes the tip sheet to reflect what it does. Agree?

And here’s a new LinkedIn HACK for you.

Step 1. Let’s take the original string (like in the tip sheet) title:(CMO OR “chief marketing”). Now, replace the : for =

title=(CMO OR “chief marketing”)

Step 2. Run a search for people – for example, this.

Step 3. Append what we got in Step 1 to the end of your search URL, after a &. And here is a search for the current job title:

Given that there are multiple UI versions out there and things are still in flux, this may or may not work for you- sounds like it does, for most!

Tip. If you examine how we have changed the search URL to perform the job title search, you may come up with other “hacks” that will expand the search functionality.

We will tell you how to work with and work around the newly redesigned LinkedIn in the upcoming webinar – Wednesday, March 15, optional practice Thursday March 16, 2017.

Don’t miss it!

 

Googling for Recently Updated Profiles?

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Can we find web pages, including social profiles, that have recently been updated? (We all know that updates may mean warming up for a new employment opportunity).

On Google, you can set a date range for the search results, then sort by date. However, I have long noticed that, even if we set a date range from the beginning of times until now, we will be losing some search results. Apparently, for some pages, Googlebot cannot define the last updated date, and those pages would be missing from the results if sorted by date.

Greg Lindahl, Founder and CTO of (now defunct) search engine Blekko, acquired by IBM Watson in 2015, provides an excellent overview of web page dates’ challenge for search engines on Quora:

“There are two huge problems for date sorting of search results.

The first is that date sort — and I really mean date sort, not relevance sort of a date range like “past hour” or “june 3” — means you only get 1 bit of relevance, where something is included or excluded. This means you may get a lot of spam…

The second is what date should be assigned to a webpage. The first date it was crawled? The date on the page? If a page changes slightly, does it get a new date? If a website puts the current date and time on every page, what do you do?”

If we are X-raying a site for profiles, the “spam” issue is not as significant, since all the results would be profiles. But the second problem Greg states is there – depending on the site. A pages’ last updated date depends on “how well” the site “tells” Googlebot about the date.

Here is a TIP: to find out whether Google has the last updated date for a page, and what it is, X-ray for the page, while setting a wide date range.

It turns out, for the majority of LinkedIn profiles the date is a question mark and, therefore, the date is absent in Google’s index. Compare, for example, these two X-Ray searches:

Some LinkedIn public profiles do have a date, but that’s pretty inconsistent. (Of course, as an additional factor in identifying recent changes is the frequency of Googlebot’s visits to various profiles. I’ll talk about that in another post).

Bottom line, it’s impossible to Google for the most recently updated LinkedIn profiles.

X-Raying other websites? Take a look whether those sites are “better disciplined” in providing the dates. Please share what you discover!

Seven Fun X-Ray Strings for Tech Talent

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Those of us who search for Technical Talent, know how competitive the industry has been. Let me offer some X-Ray searches to help to discover potential IT candidates – and to help to grow your X-Ray skills. As always, pay attention to the URL structure and common phrases that are unique for the target pages, and you’ll find what you are looking for! I have included Google searches that that you probably have not seen on other blogs; take a few minutes to try and figure out why they produce the results they do.

Here you go:

  1. site:stackoverflow.com/users/story machine learning – Developer stories, that represent their professional history
  2. site:stackoverflow.com/users London Devops “last seen today OR yesterday” – recently active users (hoping that Googlebot has caught up fast)
  3. site:meetup.com “member since” geeks 94105 – members of Meetup gatherings happening at the zip code 94105
  4. “10.. results for repositories written in Python” inurl:repositories – users who have written a lot in Python (though you may argue that this is not an X-Ray string J)
  5. site:github.com inurl:repositories javascript golang Berlin – profiles of people who have written code in both JavaScript and Go
  6. site:github.com/*/resume developer “mountain view” javascript – built-in Github resumes
  7. site:github.io resume angularjs Chicago – resumes on Github “pages”

To learn more about sourcing for Techies, consider registering for the webinar How To Find and Attract Technical Talentattendees get a month of sourcing support. We got rave reviews and will be repeating the webinar later this month. (Let us know if you can’t wait and want to get the recording from a few days ago instead).

For 300+ more Boolean Strings check out the second edition of the Boolean Book, fully reworked for the new year. Over 460 470 480 of your colleagues have obtained the e-book by now.

 

Amazing Hiring

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AmazingHiring.com is a People Aggregator that has recently made a debut in the US. Like the majority of aggregators, it concentrates on finding technical candidates. It is paid, as all other aggregators are. If you are in the market for one, there is a variety of aspects to consider, that depend on both the functionality and aggregated data – and I don’t think there’s one solution for all in the “aggregation” category.

The way AH stands out though is the special option to search for people with no profiles on LinkedIn or shallow profiles, that don’t have “the right” keywords. (I recall seeing a similar option in an early version of SwoopTalent). In my own tests, using this flag in AH combined with search terms, I was finding people with LinkedIn profiles that had not been updated for years, who nevertheless were viable potential candidates for the target skills. So – you might want to give it a try (contact the folks at AH).

 

Two Excellent Questions for a Sourcer/Recruiter Interview

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While some tasks in Sourcing can be automated, a Sourcer cannot! These two questions can serve well in an interview when assessing the candidate’s ability to search – and to think while searching.

Question #1. Will Google find every page that is on the web?

The answer is, of course, “no” (if the interviewee says “yes,” that is a huge red flag!), but it is a beginning of collective brainstorming and open-ended questions that can follow.

Correct, Google cannot find most pages on sites where you pay for a membership and log in to get access. It will not find most pages on sites where the membership is free, but you need to log in to get access, either. It will not find most pages that are created “dynamically,” as a response to someone’s query – though it might find some. It will not find most pages that other pages don’t link to. There is a lot more to discuss here.

Why ask this question? It’s a critically important skill for someone who mines the web for information to know what can and cannot be found by search engines vs. specific sites.

Question #2. How would you look for this person’s full profile?

hidden-profile_

(A related question is – did this person set their profile as “hidden” in the preferences? If the interviewee doesn’t provide the correct answer, that is a minus. A big one.)

If the person says – “we can reverse-search the photo” or “we can Google the phrases on the profile” – that are both fine answers, from someone who did the homework! However, that reflects a bit of an “automatic” quality in sourcing as well. You would want a person on your team that has her eyes open. In this case, you would want the person, ideally, say – “look, it’s right here in the URL!” – and -“I would remove everything beyond the question mark and look again.” You’d want them to be interested in testing it out (assuming this “feature” is new to them.)

This particular question would be relevant only for so long (though this particular “hole” has been around for a few months now), but it shouldn’t be hard to come up with other simple questions that test approaches. Thinking, creative, curious, open-minded would be the candidate’s qualities we are looking for.

If you are looking to update your Boolean search skills, join me for the upcoming webinar later this week –

300 Best Boolean Strings for 2017 (Thu Jan 21st) –

coinciding with the second (updated, expanded) edition of the Boolean Book.

Intelligent Searching and Matching

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Intelligent searching and matching resumes against job descriptions is not an easy task, not for a recruiter and not for software. At the end of last year, I became interested whether recently released tools in the “match” category can help to speed up searching, by offering “short-listed” candidates for review and contact. I’d like to share some observations on intelligent searching and matching and will go over some tools in a future post.

Let’s take a closer look at what “matching” means for a job description and a candidate’s resume. I think you would agree that finding a matching resume would rarely be productive if it is only done by crafting a Boolean string with long lists of keywords and synonyms separated by ORs, based on the job post. (As just one example: the job and resume “context” matters for matching; in one case, a person with either Linux or Solaris, both being Unix variations, would be okay; in another instance, it has to be Linux.)

A naive assumption of some job hunters – and even systems that assist them (such as Resunate and Jobscan) – is that “resumes must contain the most prominent keywords from a job post” for a candidate to have a chance to be hired for the job. A junior recruiter (or poorly constructed system) can pull out only keyword-matching resumes as “the” ones worth reviewing – but this rarely works to solve the matching challenge. The reality is that keywords on job posts and resumes of those who get the jobs differ quite a bit!

Below, you will find the word clouds for two job ads, along with two resumes of people hired for each of the jobs. Let’s take a look and appreciate the how far apart these word clouds are:

Job 1 (Clinical Nurse)
job-cniiiResume, match #1 (the person works there):
r1-cniiiResume, match #2 (the person works there):

r2-cniii

Job 2 (Developer, machine learning):

job-ml-sde

Resume, match #1 (the person works there):

res1-ml-sde

A filled out LinkedIn profile, match #2 (the person works there):

res2-li-ml-sde

You see? The keyword sets in both cases are dramatically different between jobs and resumes. Clearly, searching and matching in recruiting is more complicated than automatic keyword searching, even with the addition of synonyms.

Recruiters who use databases with resumes or professional profiles may construct searches based on:

  1. Location, job title (with variations), skills (including synonyms, popular technologies, etc.), years of experience, education requirements, (possibly) certifications or licenses, etc. – This is derived from the job post.
  2. (except for new and unique job openings) “Similarity” to people who have been hired for this type of jobs at this company in the past, or perhaps got an offer but didn’t accept – for example, graduates from given schools, employees from a company’s competitor, or a company using the required technology, etc. There can also be “preferences” input from Hiring Managers that is not present the job post. – This is additional helpful intelligence.

Constructing productive searches that would find results matching the requirements, as you see, is not straightforward – it is an art. Even in systems providing faceted resume search, allowing (for example) to search for job titles and years of experience, in addition to keywords and phrases, and offering advanced Boolean syntax, choosing search terms requires the recruiter to understand the industry terminology, as well as apply company- and job-specific knowledge. Recruiters, while sourcing, need to run a variety of searches to get the best matches and not miss any top candidates.

Can a computer system efficiently do the job of searching and matching? I’ll write a review of matching systems in an upcoming post.

 

 

Sourcing in 2016 and What’s Ahead in 2017

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This year, we have seen a rapid growth of tools to automate search, match profiles against jobs, and refresh professional data in resume databases. Yet, going into the new year, Sourcing as part of Recruiting seems further away from being trivial – or being automated – than ever.

In 2017 and for at least a few years after that, Sourcing will absolutely require skilled Humans to perform it!

Here is, briefly, how the current Sourcing landscape appears to be.

“BIG DATA”

The amount of online data is growing fast – and it’s not a database where we can search. Data is becoming more distributed: people have a professional presence on various sites. People aggregators, that started appearing back in 2011 (see a section on the Tools page) provide access to unified profile data and help a lot, especially in IT recruiting. But we still can’t rely on any one tool for sourcing. (What is the next BIG sourcing tool concept after aggregators?)

Ways to contact and interact with prospects are multiple, cluttered – and need to be sourced, too. We are seeing new contact-finding apps and increased use of texting in recruiting.

Access to professional data is getting more challenging (e.g. the new LinkedIn limitations, costs, and user-unfriendly search syntax). It’s unfortunate that the largest professional database, that has revolutionized recruiting, is now making access to the valuable data so hard. Will the Microsoft ownership provide positive changes next year and bring back the Economic Graph project? Let’s hope for that.

In the meantime, Google X-Ray is our friend! Google has improved its algorithms and no longer requires complex syntax to get the right results. Custom Search Engines and structed data on websites provide interesting search possibilities.

Facebook Sourcing – and interacting in groups (please join the Boolean Group!) – is gaining popularity. It is tricky to find professional data on Facebook, but we see tool improvements – Shane’s Tools is gaining popularity. Facebook has been making itself more search-friendly as well.

Automation and matching technologies seem to be everywhere, but it is a double-edged sword – sometimes, overpromised and underdelivered. (Please expect a blog post on matching soon). I believe that machine learning, in the right hands, can do wonders, especially in fast-screening backgrounds in volume hiring – but profiles and resumes still need human eyes to properly assess them.

It is interesting what Mobile Sourcing holds! Let us all dig deeper into that this coming year.

We are going to keep providing the most comprehensive Sourcing Training in 2017. You can count on our Sourcing Training Library to be up-to-date and our Exams to assess true Sourcing Skills. With our expanded team of Master Sourcers we will increase availability for custom Team Training and Sourcing Projects for our clients. Additionally, expect us to release a new Sourcing Tool in January 2017, currently in private Beta… watch for announcements soon.

Happy New Year to all!