Solutions in Social Recruiting: Improving Candidate Identification Strategies
The challenges in our industry are clear. The recruiting industry must quickly look toward social recruiting techniques to improve results and revenues. In this article, I’ll review the challenges we face as recruiters – all thanks to data and “improved” technology – and offer solutions for moving our respective careers, employers, and the careers of those whom we recruit forward.
The Gift (and Curse) of Technology
In today’s social and mobile world, we have access to 200 million people via LinkedIn alone. If you include Facebook, that number quickly escalates to approximately 1B. On the surface, this is amazing for recruiting. In days prior to social networks, our industry spent much of its collective time on the hunt for talent using any means necessary. Today, there’s a waterfall of candidates flowing into our pools.
The problem is that we’re drowning in those pools.
Yes, we have more candidates to choose from. Yes, we can type in a simple search and have thousands of possibilities returned. But in (seemingly) solving our data problem, we’ve created another: Which candidates in these search results are the best use of our time and how do we predictively index anywhere from 200 million to 900 million people?
Solving the Data Problem
Predictive indexing, although new to recruiting, has been in practice for years within marketing (for a powerful, on-topic read, pick up Competing on Analytics by Thomas Davenport). Your marketing team has segmented customers, scoring them based on transaction data or behavior, and stack ranking them based on the level of reinvestment needed. Recruiting is now at a place where we have too much data and we need this segmentation to stay above water. Let’s have a look at how it’s being performed, the tools and steps necessary, and then look at solutions that take candidate identification to the next level.
Corporate recruiting organizations are using tools like LinkedIn Recruiter, Boolean searches on Google, and functionally specific communities like GitHub (tech/developers), Kagle (data scientists), or Behance (graphic designers). Once we identify candidates, we’re hunting down their contact information on sites like Data.com and Plaxo so we can reach out to them. We combine all of that data with the historical data from our applicant tracking systems and voila! We have a candidate profile. We then hunt down their Twitter information, find a Facebook profile and see what’s publicly available, and perform article searches on Google. Now we’re in business and we can deploy Radian6 to socially listen to the candidate for the next 60 days. And note – all of these steps are being performed manually.
To effectively develop a candidate’s social profile, organizations must:
1. Hire two or three computer scientists to write algorithms, spiders, and bots that pull all of the information from these sites into a CRM (if you have one).
2. Include a database marketer or data scientist on your team who can score and index the information your computer scientists pull into your CRM and stack rank it. Companies like Salesforce and Facebook have gone this route.
But why scoring and indexing? So you know that you and your recruiting team as a whole are spending time with the best possible candidates. This is the difference between getting 100,000 random results back via multiple tools and getting a list of candidates stack ranked in order of 1 to 100,000. There must be a more efficient way to get from that random list to one that’s stack ranked. And there is.
You can now outsource the data aggregation and scoring to a new set of big data companies that are emerging in recruiting. Gild, Entelo, and TalentBin are just some examples. These companies offer hand-delivered candidate lists, stack ranked by your specified data, and at a considerable cost savings to having multiple full-time staff performing the same tasks. This will deliver you more quickly than ever from candidate identification to social listening to help you hone your candidate list.
Cue Social Listening
With your stack ranked list in-hand, you can then load a highly targeted list of candidates into social listening tools, such as Radian6, HootSuite, SproutSocial, and others. Third-party tools like these make it easier to track candidates, assign relationship owners, invite key groups of candidates to in-person events like meetups and hackathons, and learn when the right time to engage might be. Do they hate their commute? Has there been a key management shift at their current company? It’s all waiting – we just have to listen.
Benefits and the Next Steps in Social Recruiting
What good is stack ranking and getting out from under the data deluge? There are more than a few benefits from sorting out your organization’s social recruiting techniques and tools:
- Increase in recruiter productivity – better data means a more efficient workflow.
- Declining interview-to-offer ratio – better candidates mean less time spent on the wrong ones.
- Frictionless closing – passive candidates trend towards a simpler hiring process. Close should be easier as candidates are passive.
- Decline in cost-per-hire – efficiency breed efficiency on multiple levels.
We’re looking at not just increased efficiency and shorter time to hire, but a better experience for everyone in recruiting. From the recruiters tasked with filling mission-critical positions to the candidates looking for their next career home, social recruiting methods aren’t just powerful. They’re necessary and kind. I dare to imagine a kinder world where we can connect talent with missions, people with projects, and companies with creative resources. We’ve been beating ourselves up for too long with technology that’s supposed to make our lives easier. Isn’t it time we used it, shaped it, and put it into action to better serve everyone powering the companies of tomorrow?
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