My LinkedIn account is having multiple problems with the functionality. It’s happening for the second time in the past few months. I can’t use my RPS account (it is a variation of LinkedIn Recruiter). I hope they will fix it again.

The nice LinkedIn managers, who support my RPS account, point out that I am a power user and am likelier to break a software system than an average user. I suppose, they have a point.

The LinkedIn Support suggests that my problems are created by my large number of connections. Now, that is not true (or so I hope!) , since there are hundreds of people with many more connections than I have. The Support people have also told me to clean the cookies…

Yeah…

Anyway, being locked out of my account – and feeling like I may have put too much pressure on LinkedIn’s functionality by pressing too many buttons – has prompted me to run an exploration of LinkedIn as a user who joins today and simply follows prompts to add connections.

I had created a test account for a non-existing person by the name of Barbara Nelson in order to go through this exploration. What to do, I couldn’t stay away from LinkedIn for several days in a row; I am used to using it all the time! Given that thousands of non-existing people are members of LinkedIn I didn’t feel too guilty.

You know what? In the first hour of being a new LinkedIn user Barbara could see a problem or two as well. Here is a brief report.

Per LinkedIn’s suggestions, Barbara uploaded some contacts. Not to bug LinkedIn members who may not know her, she uploaded some contacts of “open networkers” who are happy to accept invitations, into her Imported Contacts folder, and pressed “invite”.  She got redirected to her Inbox as the result, with no invitations being sent out. This was confusing but she persisted.

She then repeatedly ran into this screen while trying to invite connections and while trying to delete some of the uploaded contacts whom she had already invited:

Needless to say, cookies were enabled and repeatedly cleaned, with no luck.

Finally she succeeded and got the first few connections in. I’ve long been unable to export my connections; Barbara was able to do that! However, look what she got in the export; these are the last names of connections reduced to the first letter where they shouldn’t be. Some were OK; some were not.

Now, the next Barbara’s experience was something even Irina had never seen before! Look how the connection Randy was previewed in the list of connections:

Huh? You see what’s happening? Instead of Randy’s profile preview there’s a window with some pale-colored error report, that looks very out of place.

…The next thing Barbara did was trying out a people search on LinkedIn. She knows from Irina, and from just slightly wrong LinkedIn’s own Tip Sheet, that it’s possible to exclude terms by putting the word NOT in front of a term.

Alas, the LinkedIn Boolean people search was broken for Barbara. Take a look at this example. This is a search for recruiter NOT manager NOT contract (within a geographical area). The results show the second excluded term being not only included but in bold:

What would the Boolean Black Belt Glen Cathey say about this? This seems to be a bug that affects both Irina and Barbara and, my guess is, the rest of the members.

This is five (5) major bugs, found by gentle, suggested use of LinkedIn by a new user, within one hour. If I were managing the LinkedIn Quality Assurance department (I imagine they must have a QA department?) I would never allow a release to go live with these. Would you?

The Dream Software, that was the subject of my talk at SourceCon, is the new generation of sourcing software tools. Please check out my conference presentation slides at this link:

SourceCon-Atlanta-PPT-Irina

The blog post below continues to map out the architecture and the functionality of the future-generation tools. This post is “conceptual”. What I mean to say is, if you are a recruiter planning your budget for the next year, please do not expect to jump to a quick decision which tool(s) to purchase, based on the post.

I have recently written “a proposal” of a new Dream Software design – not as much with the idea of implementing it (am too busy already!), but mainly to name some of the challenges in building this type of software. The point being, collecting and correctly matching the pieces of the same profile from different online sources is not easy – and is worth quite a bit! Somehow, every vendor provides some extra features, but as far as I am concerned as a user, additional functionality is optional. As an example, as a recruiter, when I am already viewing a profile, I don’t need extra intelligence that helps me to assess the profile. As another example, I am not looking for social media tracking done for me, to guess that a person might be ready to make a move; the LinkedIn Signal is plenty. As a  third example, I don’t need to be told which developer writes good or bad code. As my business partner Julia says, “Bad developers write bad resumes”.

There is, however, a valuable and a “natural” potential extension of these systems that seems to be right at the creators’ fingertips, as they collect distributed profiles…

There’s an extremely clever add-on to LinkedIn, called Talent Pipeline, that is exactly that type of extension I’m thinking of – in this case, to the LinkedIn members profile database. Talent Pipeline allows recruiters to upload their own sources of data, such as resumes and Excel files with lists of professionals, and attach this data to the system already in place; then access all of the data, both users’ and LinkedIn’s in the same manner. In Talent Pipeline the uploaded data is cross-referenced against LinkedIn profiles (using the most reliable way). If there’s no matching LinkedIn profile for an uploaded record, a LinkedIn-profiles-look-alike is added, marked as “not linked”.

Let’s apply this concept to the Dream Software systems: if I could add my own data and create or update the existing profiles in the system, that would be a delight! What could be a better starting point for a new profile creation than the data from my ATS, or the data I have sourced with my target profiles in mind!

At this point I feel a need of a new term. Shall we call it the Deep Web add-on to the Dream Software systems?

Last week I got a call from yet another up-and-coming Dream Software vendor SwoopTalent that has this Deep Web add-on concept in mind. They have many other extra pieces of functionality planned, but I’d say, if they concentrated on this feature alone, it would be worth while.

Dice.com holds a special place in regards of putting a Deep Web add-on in place. They have already cross-referenced the existing ~2 MLN resume data with theSocialCV’s collection of ~130 MLN profiles, as part of introducing the new Dice Open Web add-on. Hey, the term Deep Web would match nicely with that!

My impression is that they weren’t creating new profiles in the system and refreshing the existing profiles while cross-referencing with resumes in Dice.com. Hopefully they will do that soon, if they haven’t yet. At the same time the brilliant minds behind theSocialCV are planning the Fresh-Up system that would refresh user’s own data, such as a collection of resumes in an ATS and send the results back to the user. So, Dice is in an excellent position to get all of the dream features work together. Of course, Dice Holdings‘ base of acquired job boards and software is very diverse, so it’s not the easiest logistical task to merge it all into one integrated dream system, and what the order of the integration steps might be.

As for LinkedIn’s Talent Pipeline, a better market positioning (not as an ATS replacement) and cleaning up the user interface would give this part of Recruiter functionality the visibility it deserves. I guess LinkedIn is already doing very well as a company! It’s just if you have Recruiter access, don’t miss the Talent Pipeline.

The End of Sourcing Is Near … is a post by Dr. John Sullivan on ERE that is drawing lots of attention. I am not going to argue with this point. Let’s just try to read the article carefully.

Dr. John Sullivan writes: “Finding top talent among professionals is now becoming painless to the point where almost any firm can do it successfully.” The posts says that the only reason there still may be some minor need in sourcing [“phone” sourcing, perhaps?? – IS], is not everyone being online yet.

Let me present the same logic applied to a slightly different field: mining precious metals. Please read carefully:

[1] [Fact.] By now there’s a variety of machinery that can identify, whether there are precious metals underneath the ground below any specific point (longitude, latitude), anywhere in Alaska.

[2] [Conclusion.] Because of [1], locating precious metals in Alaska is a simple matter of using this machinery. Anybody can do this.

[3] [Final Conclusion.] The only remaining problem is how to use those metals in manufacturing.

That’s the same logic. Does it work? There seems to be a logical gap somewhere there.

What about a practical example?

Dear Dr. John Sullivan:

I would challenge you to demonstrate how the wealth of social info makes sourcing easy, specifically in application to this sourcing task posted on another ERE-owned site, SourceCon. I know for a fact, that, using your words, “everyone [in this task – IS] can be found through their “footprint” on some combination of electronic sites.” 

Let me know what you find!

Thanks; Irina Shamaeva

I agree that the selling side of recruiting needs improvement, stressed in the article, but that’s not the point.

The large number of re-tweets and shares of the “the Death of Sourcing” article makes me wonder why the death of sourcing  is such a welcome message – while nothing can be further away from the reality. I’d be curious to hear everyone’s thoughts.

Disclaimer. This post is somewhat technical and doesn’t contain specific sourcing tips. It is relevant to my SourceCon Presentation, where I go over a specific kind of sourcing tools. Those tools are apparently gaining attention among recruiters. I am going to post detailed reviews of the tools – listed at the bottom of this post for your reference – here on the blog over the next few weeks.

Here’s a “Dream Software” Design Proposal. Both the most challenging and the key piece for the dream software is connecting the parts of a distributed profile. End-users of the dream software don’t appreciate the challenge! For a human, the connection between two online profiles can be clear, while for the computer it is not as easy, since all of the informal clues need to be formally coded.

If the dream software vendor is reasonably careful and tries not to glue profiles together unless it’s very clear that they should be, the end-user will complain about duplicates. If the vendor is boldly making guesses, then profiles from different individuals will be incorrectly collected as one record, which is, in fact, even worse. (My coworker David Galley tests out the software using his own name; if you are one of the vendors, I recommend to try it out using your tool.)

In the proposed design we solve the “matching profiles from different sites” challenge upfront, by only working with unique identifiers, such as an email address, either work or private, a phone number, a combination of a person’s name and a company name that fits only one person, or an image.  If a company uses an email format, then for not-very-common first-and-last names we can reliably construct the work email address that can be verified (using the logic like this) in the process of creating a record. An excellent identifier is a person’s photo that is often the same across different social profiles.

We start building the database with those identifiers. There’s a variety of ways to collect those from the open web. As an example, we could start with recent resumes posted online and get email addresses from them as the IDs. That would collect a very large number of those IDs. (Remember our sourcing challenge asking “How many resumes are there on the Internet?”) There are also sites that list attendees, members, etc. – as we teach each other in people sourcing discussions and classes. There are lists of professionals with contact info in excel and PDF files. If that’s not enough, there are obscured email addresses across email list archives and the like.

From the unique IDs we go to various social networks and blogs to pick additional information by cross-referencing. We know that an email address identifies the member on all major networks, including LinkedIn, Twitter, Facebook, Google+, and more. If we can be friends with Rapportive/LinkedIn, or just with LinkedIn, we get a head start on cross-referencing. In fact, having an agreement with LinkedIn is especially important; worst case, if this is not accomplished, a public LinkedIn profile can be picked dynamically.

For any social profile that lists other profiles – that often happens on Google+, but not only – we add those profiles to the person’s record as well. Mind you, we are still confident that it’s the same person’s social profiles.

We don’t do much else. Rather, we carefully parse and collect the info obtained by cross-referencing into our database and provide reasonable faceted search for the end-user. Parsing can be specifically implemented for a few dozen social networks and forums (which we’ll need to watch for updates of the HTML formats). For online resumes we can rely on a resume parsing tool.

If there are other proven ways (not to guess but) to cross-reference more social profile data from the already-collected data in the records, we’d implement that as well.

While every People Sourcer and all the Dream Software tools do cross-referencing, we’ll need to be extremely careful about privacy issues and explore how to best address them.

If anyone is up for funding the proposal, just give me a ring, will you?

Thanks! and I will be reviewing the existing Dream Software tools in the upcoming blog posts. I will also be sharing an additional design idea for the existing tools that comes directly from experiencing the LinkedIn’s Talent Pipeline.

In the meantime, please take a look at some of the tools (repeating, just in case: I am not affiliated with any):

1. TalentBin
2. Dice Open Web
3. TheSocialCV
4. Entelo
5. RemarkableHire
6. Gild

Please stay in touch about your experiences!

My first (fun!) experience with SourceCon was attending the conference in San Diego back in 2010, after I won the SourceCon challenge in 2009. The final challenge, won by Katharine @TheSourceress was an amazing explosion of creativity. Those were the days, my friend! 

I am coming back to SourceCon as a speaker at the upcoming SourceCon-2013 in Atlanta, GA. If you are also coming to the conference, let’s connect!

My talk will be focused on the “Dream Software” that has evolved quite a bit since the original post back in 2011 .  You can find the back-then descriptions of TalentBin (post on TB in 2011) and theSocialCV (post in 2011) as the pioneers in this type of tools.

Before I continue, let me clarify that:

• I am not affiliated with any of the tool providers, job boards, or with LinkedIn
• Views are my own

I have recently spoken with the founders of Talenbin, Entelo, Gild, and RemarkableHire – all of them representing “Dream Software” tools! Last week I spoke with the CEO of Dice Holdings Scot Melland about the new Dice’s Open Web product, that apparently continues theSocialCV development under the new name and the Dice’s brand.

The original outline for the upcoming SourceCon talk is below. I also plan to write several posts here on the blog, highlighting the Dream Software products’ functionality, as well as the general tendencies and challenges. If you use any of these products, I’d love to hear from you, here in the comments, or reach me out directly.

http://falcon.io/ is called “Rapportive for the web.” but it may be a bit misleading. Many of us have used Rapportive and love it. I often go to Rapportive before getting with someone on the phone, as a good way to “Google” the person when I know the email address. (Of course, its “official” integration with LinkedIn is priceless.)

Falcon is not a substitute for Rapportive at all, but rather an extra addition to our toolboxes. The word about Falcon is already spreading out fast among People Sourcers. I hope to make it even more popular with this post.

Falcon.io works like no other tool I know of.

Falcon.io has the look of Rapportive, but the way it works is very different. While Rapportive crawls the data and accumulates information, with an email address as its identifier, Falcon looks up the data dynamically, starting from an existing profile that you mouse over. It implements a variety of algorithms in order  to find extra  online data for members on each of the five networks it currently “serves”, including Twitter and Github.

There are advantages to both ways of looking up profiles. An email address identifies the right person 100% of the time; but crawling takes time, so Rapportive has some outdated data and some data may not have been crawled yet. On the other hand, Falcon tries to glue together profiles of the same person, which cannot be done perfectly, but it can do this for anyone, here and now. I’d say that Falcon “prompts” in a useful fashion. Strong sourcers can probably reproduce some of the Falcon’s  looking up logic but this would need to be done for individual profiles each time. In a way, Falcon does a light version of what TalentBin and other “Dream Software” may be doing in the background, but without storing the data.

There are endless ways in which Falcon can be useful. As an example, on Twitter it can look up people whom Twitter suggests for you to follow; people who are posting interesting things, or are using a #hashtag, say, for a conference; people from lists; or those who are being RT’ed or mentioned by others.

Don’t miss the tool! Let’s support and follow its author Gwendall Esnault. Well done!

I am excited about the first upcoming session of the People Sourcing Certification Program in 2013! We begin on January 29th.  Enrolled already are: Apple, Dell, PwC, Capgemini, All-State Insurance, Verizon… US, UK, Canada, Australia, India… Our international team is growing and we are on our way to become the world-wide standard for training and measuring the skills in our profession. Two more sessions are coming up in 2013.

I thought I’d share some cool graphics with our followers.

These are the countries that participated in the Program in 2012:

These are some companies that took my training in 2012 (it’s a partial list):

We are looking forward to continued success of our Program and our profession in 2013!

Join us for a Webinar on January 22

Space is limited.
Reserve your Webinar seat now at:
https://www2.gotomeeting.com/register/581053314

This webinar will cover name generation as well as searching for hidden profiles of target professionals.

Who should attend: Recruiters, Recruitment Managers, Teams, Sourcers, Staffing Managers, Talent Hunters, Inside Sales Managers, Business Development, Executive Search Firms, Searchers, Researchers, and Hiring Managers. Some familiarity with Google searching and MS Excel would be helpful.

“There comes a point when I don’t know where else to go and look for resumes other than LinkedIn and Monster, where most of the profiles are same.” wrote a recruiter in an email to me. While most recruiters do know other places to look for target candidates, everyone can benefit from reviewing “the big picture” about those sites and learning productive ways to navigate them.

In this webinar I will concentrate on finding and extracting human capital data from industry-specific sites vs. general networks.

Outline
* Navigate the 10 major people search engines
* Identify data-rich sites in the target:
– industry (forums, associations; certifications)
– geography (local chapters, meet-ups)
– time (recent conferences)
* Extract lists of professionals from the sites:
– by X-raying
– by deep web search
* Locate social profiles on professional niche sites
* Find contact information:
– email address templates
– email addresses for leads
– phone numbers
* Pre-qualify people for calling and make the call warm

Think you have found everybody there is? Join us, try these techniques and you will be surprised! In the end, you may notice that many if these additional leads do have LinkedIn profiles, but would be hard to find by searching LinkedIn alone.

Date: Tue, Jan 22nd
Time: 10 AM PST/1 PM EST
Duration: 90 min
Price: $79.
After you have registered your name, please wait 10 sec or go straight to http://bit.ly/nam–gen for payment.

Can’t make the time? No problem. Everyone who signs up you will get the recording, the slides, and one month of support.

Some professional sites with software developer population that charge recruiters arm and leg to access the user data, like stackoverflow, are quite hard to search. It’s possible, but it’s not easy. Github is a place where excellent developers hang out, that provides its own clean ways to search for its content – and its users:

If you are not a fan of search operators, you can simply do this:

Start searching for users…

Select a programming language…

Add a couple of clever keywords… (not necessarily these, but this example may give you some keyword ideas) and see results like this:

I never said that we should be emailing people as soon as we get hold of lists like this. More research and pre-qualification is always a good idea. But that’s quite a bit of sourced data in one quick shot!

X-raying on Google is also possible but the results are a little harder to browse. Try this:

site:github.com “joined on” “San Francisco” “gmail.com”

X-raying on Bing, however, will not find a single thing:

site:github.com “joined on” “San Francisco” “gmail.com”;

guess, why.

I will be explaining this type of people sourcing techniques in-depth at the upcoming webinar on how to source on professional sites, coming up on Tuesday, January 22nd. As usual, the slides, a video-recording, and one month of unlimited support will be provided for all who sign up.

LinkedIn says it has reached 200 million profiles. It is a great number!

I do love LinkedIn and I care about its growth. People Sourcers know for a fact that LinkedIn is an incredibly rich source, the best world-wide, even if the claimed number of profiles was larger than the number of real live professionals on LinkedIn.

LinkedIn critics say that many LinkedIn members  “do not use the site actively”. That’s OK with me though. I can try reaching members through a message or an InMail, even if they do not hang out at the site.

Here is where the growing problem is though. LinkedIn is being increasingly polluted with fake profiles and the   content they generate. LinkedIn doesn’t weed them out well and doesn’t give its users enough power to weed them out.

Issue #1. Junk names, no real person’s info. Here are some names of LinkedIn members, as listed on the site alphabetically:

 more:

and more:

and more:

(etc.) These “profiles” perhaps wouldn’t be right to claim among the 200 MLN. But they are not a problem for someone who does people search; these profiles usually wouldn’t even show up in the search results.

There are also LinkedIn members with first and last names being “company”, “business”, “software”, etc.; I am sure you’ve all seen them.

*** Here’s a little sourcing challenge for my fellow sourcers: find a keyword that cannot be a name (such as “company”) with the largest number of results in people search, used as either the first or the last name on LinkedIn, and post in the comments here.  Example: Last Name = company ***

Issue #2. Fake profiles – personal spammers. Some of the fake profiles, are, unfortunately, active, “log into the site”, and actively add junk content. Those are becoming a real issue.

Here is an example of some invitations I have received recently:

I assure you that these are not real people. The images are generic; the profiles contain very similar info in broken English, claiming an advanced degree from one of the top schools (ha!)  and a link to a junk site. The profile images are reused  for similar profiles.

An extra connection with a fake profile is somewhat unpleasant to have. It increases the amount of spam messages for anyone who accepts these connection requests.

Dear LinkedIn: can you please look up some profiles like these, tag and remove them automatically?

Issue #3. Fake profiles – group spammers. Now, these are a real pain. Profiles like this one:

actively join groups and mass-comment on every post before the group moderator knows it. LinkedIn Customer Support says (quoting from a reply to me):

We do have some proprietary algorithms that track spam-like activities on the site, but we largely leave the group content decisions up to the individual group management. 

The problem is that many of these “users” are apparently software-generated. Moderating a larger open group is either becoming a huge time consuming effort, or – as it’s done in most groups- junk is accepted and the group is a wasteland.

The group moderator is only a person. There’s little we can do against armies of non-existent  “members” that are created by software and generate junk messages through software. Here’s a typical example. There’s a lot of pointers to the same job-related sites – of questionable value – spread over the groups, like this:

Dear LinkedIn: please block at least some of the junk content. You can do it!

First, please block at least some non-existent users who are actively inviting and posting. I am sure the user jerseywebsite will not complain.

Second, please give group moderators tools to mass-block mass-spam. The existing moderation tools are not adequate. I’d like to be able to auto-flag messages that have “jerseys” and “make money from home” in my groups. I’d also like to be able to flag the same link posted more than once by the same person.

I imagine that some group moderators would second that.