Editor’s Note – Don’t Feed the Vendors is a special series at FOT. The goal of DFTV? We get hammered by third parties who want to write at FOT, so we give them a challenge. Write something cool and significant we can learn from/talk about in the FOT style, and you can roll with the FOT crew. Try to sell our readership your product and/or provide a whitepaper, and we’ll openly mock your company in public for not understanding the DNA of our readership. Many inquire, few follow through once they learn they can’t post a workup of their latest “research”. For those who make the cut, we’ll offer up associate FOT membership as part of the Don’t Feed the Vendors stable.
Steven Duque is one who made the cut and is the marketing manager of Bullhorn Reach. Follow Bullhorn Reach and Steven Duque on Twitter. If you can’t get enough of Steven’s musings on social recruiting, check out the Bullhorn Reach blog.
Making sense of the endless stream of updates from your social media connections can be a headache. Thankfully, new tools are emerging to take the heavy lifting out of interpreting social media data as valuable business intelligence.
Getting Smarter about Social Media Data
As we’re all coming to know, data on our behavior while using social networks are increasingly public, especially if we connect our accounts with an application. And, as we continue to get smarter about social media, we’re discovering that what people do on LinkedIn, Facebook and Twitter can be interpreted as signals that communicate what they’re thinking. (Whoa.)
Marketers have known this for some time. Facebook, for example, aligned its ads with users’ listed interests early on. But that’s just what’s on the surface; anyone who can read can figure that out (“Kris says he’s interested in sports, so I’ll show him ads about sports”). Behaviorally-targeted ads, in comparison, are more indicative of the type of thinking that will begin to drive innovations in social media services.
Imagine, for example, that you’ve recently spent a lot of time looking through the photos of single people you’ve recently “friended” (never happens, right?). You probably wouldn’t be shocked if Facebook showed you ads for dating-related sites and services. This type of thinking is beginning to shape how technologists in the sourcing and recruiting business are thinking about how they can unlock the secrets of data from social networks to find and recruit talent.
Time is Money, and Research Typically Takes Time
No one (except this guy) has the time or energy to constantly monitor their social networks’ feeds for behavioral patterns that may or may not be useful to achieve their business goals. It’s hard to imagine spending a work-day doing that, not to mention a longer period of time to identify broader patterns. (I suppose there are worse things to do with one’s time at work.)
So, in the fast-paced world of sourcing and recruiting, it’s probably fair to say that most folks in the business don’t have the time or energy either. Time is money, and the low-hanging fruit of chats with active job seekers will likely take precedence over the wild goose chase of identifying passive job seekers through social media research, unless…
A Solution in Sight
There’s hope. Increased computing power and wizard-like eggheads have enabled the widespread use of algorithms as an easy fix for automated reasoning, especially when there’s a ton of data to process. With social media usage, there’s certainly enough data to keep algorithms busy.
But, as you know, professional social networks (and social networks, in general) have only recently been widely adopted by the general population. And, the current ecosystem of tools for “social recruiting” reflect that. Most players in the space (including us) have focused their efforts on figuring out the best practices for broadcasting open jobs. Broadcasting, however, is just one facet of how we can communicate through social media.
We know, as humans, that body language can speak louder than words. Similarly, how we behave online — more specifically, the “movements” we make on social networks — can communicate more than we think. By monitoring and interpreting behavioral patterns across social networks, we’ll soon be able to make the wild goose chase of identifying passive job seekers as easy as shooting fish in a barrel.