Right now, big data is all about catering to the needs of customers by providing personalized content. The algorithms behind these recommendation engines can be a bit hard to understand if you’re not a tech person, but their results should speak to everyone. While these algorithms make the most headway in the consumer space, they could also help employers hire smarter and recruit leaner.
What We Use it For Now
Even if you’re not keyed into all of the technical aspects of algorithms, you’ve probably had some experiences with them. Ever watched a movie or TV show on Netflix? Then you’ve taken part in an algorithm. Netflix uses several different kinds of algorithms to make sure you continue using their service, and looks at the kinds of things you watch, the ratings you dole out, and how long you linger on menus to recommend movies you’re more likely to watch. If you’ve ever bought something on Amazon, many of the same numbers determine what items they’ll show you on the home screen.
However, these personalizations are about more than crunching numbers. Brian Ballantine, previously a Lead Software Engineer for the Gilt Groupe, described how many personalization algorithms also factor in experiences and other methodologies when making their recommendations.
“… the heuristic techniques we [at Gilt] use for our personalization initiatives help us to gain a better understanding of how our millions of users thought. Like our data, these methods aim to capture how our users shop and make purchases; what they want, what they “need,” and how to recommend products to them that they’ll actually buy. Our work is driven by algorithms. But it also involves examining user behavior in order to produce really rich customer experiences that enable us to recommend products across categories and find complimentary items based on behavioral similarities."
If you read that and thought “business potential,” you’re not alone. There are all kinds of uses for these kinds of algorithms. How can these algorithms improve, and how can employers use them?
What We Could Use It For In the Future
As powerful and prolific as personalization algorithms are, they still need work. For one, they haven’t quite yet figured out how to take advantage of “invariables.” The Harvard Business Review describes a few cases where personalized recommendations based on traits that don’t change could be immensely helpful to consumers: only showing properly-sized shoes after someone’s bought a certain size online, automatically asking people to make monthly payments and having them confirm, or automatically booking flights customers make regularly.
You can see how this could empower employers, as well. Eighty-five percent of job seekers are open to new employment opportunities, but they may not have the time or motivation to follow through on applying to multiple jobs. But what if algorithms could do this work for them? LinkedIn already recommends jobs to users based on their skill set and what jobs they’re looking for. What’s stopping someone else from compiling common application data, using a candidate’s resume, and asking them “This job you might be interested in opened up. Want to apply right now?” then doing all the hard work for them? If applicant tracking systems find and track applicants for jobs automatically, why not provide that same autonomy to candidates?
What You Can Do
If you’re interested in harnessing the power of data personalization for your recruiting, you have a few routes open to you. You could begin hiring your own team learned in coding, data mining, and problem-solving (wouldn’t be a job ad if it didn’t mix hard and soft skills!) If you want to hire smart, go with senior developers, as they’re the most productive and the ones you’ll have to spend the least amount of time training.
It’s also possible to hire outside firms to do your data mining for you. Analytics Suites (like Broadbean’s) automatically do what your newly-hired programmers would do: take information from your recruiting tools to determine their efficacy, then let you know which of your recruiting avenues work best, and which need some work. You can then use that data to create your own personalization algorithms in the recruiting process, giving you better candidates and ultimately better employees. And nothing’s better than building that personal connection.
Interested in learning more about the capabilities of Broadbean’s Big Data Analytics Suite? Sign up for a demo today to see how big data can mean big business for your recruiting.