Why You Need Technology to Find the Right Creative Talent

Marketers often adopt buzzwords to justify their strategies. “Let’s publish more snackable content, Larry.” “I want to be sure not to newsjack, Sandra.” “Penelope, let’s talk bottom-funnel next meeting.” The specialization of marketing terms, we’ve found, is an epidemic.

But there’s one buzzword that probably doesn’t get enough burn: talent. Marketers are realizing that you can’t just ask anyone to run a blog and expect her to suddenly turn into Kara Swisher or Jane Pratt. While some brands hire in-house editorial talent, others are turning to freelance content creators as a nimble way to scale their marketing efforts with experts who have the right voice and experience.

But finding talent is much easier than finding the right talent. The sheer number of freelance creatives on the market today can make finding contributors a lot like spotting Justin Bieber in a sea of tatted blondes. Contently’s freelance network alone has grown to roughly 60,000 self-employed creatives.

With so many options out there, how can brands build the perfect freelance team?

Data to the rescue

At Contently, we realized the only scalable and sustainable way to pair brands and freelancers was to build an algorithm that could act as matchmaker. It doesn’t help us or our clients for people to waste time and resources manually sifting through thousands of freelancers.

Each of the 60,000 freelancers on our platform create a portfolio to showcase their clips and add in a brief bio that teases their expertise. From these portfolios, we have access to over 1.2 million clips that have been published in just about every media outlet you can think of, as well as data that shows the social shares for every piece of content

For example, Russ Banham is a writer who regularly contributes to freelance projects for financial brands through the Contently platform. His profile includes the article “Why CIOs Should Be Happy About Shadow IT,” which was published on Forbes and generated 901 social shares. All of this information, along with data from Banham’s other 155 articles, goes toward the algorithm.

For people like Banham who work with our clients, we also have internal data that tracks factors like on-time percentage, engagement, and how often the freelancer communicated with the client. Outside of the Contently platform, third-party tools like Klout help us track social media influence.

With this information, we can measure each freelancer in specific ways that are important to brands, just as Pandora categorizes music on a very granular level through its Music Genome Project. We then use the insights to accurately pair brand publishers with the freelancer best suited to join their operation, whether for a single project or as a regular contributor.

We can measure each freelancer in specific ways that are important to brands, just as Pandora categorizes music on a very granular level through its Music Genome Project.

When you break it down, algorithms recognize that people desire things—whether it’s music, restaurants, clothing, or freelancers. The thing about data sourcing is that once you get passed the term “algorithm,” the process is actually quite intuitive.

Finding the golden nugget faster

As a data scientist at Contently, I continually have to ask: Why does this feature exist? What do these algorithms help us achieve?

The answer, in this case, is simple. Brands are able to quickly and accurately acquire talent to meet their content creation goals.

If you’re a marketer from a national doughnut chain looking for a writer to cover a story about an event hosted at our franchise in Austin, all you have to do is tell the algorithm that your need someone located in the Austin area who is familiar with the food and culture beat. That quick input will save you from needing to fly out a marketing or PR representative from your headquarters in Boston, who may not have time to churn out a story.

Once the algorithm makes recommendations, our internal talent managers can then work with the clients to sort through the short list of candidates and make final choices.

The application of this feature is broad. Brands can use the freelancer network to find creatives for a specific assignment—like the hypothetical Austin doughnut event—or to staff an editorial team for the long haul. The same process can even be used to source pitches from potential contributors.

The point of this project is to refine the way brands approach staffing so they can focus on the big picture. And just think, with technology guiding these talent decisions, you won’t need to call upon Larry from HR to write your snackable content ever again.