Data science began its life in the latter half of the 20th century, emerging slowly as a niche field until it grew into the large discipline we now know. That’s a remarkably short life span for a domain that has radically changed the way businesses market to customers, saving businesses money and delivering insights and opportunities that were once completely inaccessible.

Clearlink is a prime example of this slow adoption followed by rapid progress: we spent fifteen years out of our seventeen-year history without a data science department. Just two years ago, that changed with a fledgling initiative. Now at 40, our data science team is fully integrated with the marketing and sales sides of the business, and we benefit from a staggering amount of collaboration with one another each year, especially considering the department’s short history at Clearlink.

When working to forge a place for data science alongside marketing and sales at your organization, you’re probably going to feel some resistance from other teams due to a lack of understanding. After all, data science can be intimidating at organizations that have no previous experience using it. If you’re experiencing that kind of hesitancy towards data science now, rest assured — it can be overcome.

At Clearlink, we’ve seen both the challenges and benefits of integrating data science with digital marketing, and the knowledge we’ve gained can easily be applied to your organization as you start down a similar path.

Start Slowly and Provide a Lens

I’ve had many experiences in my career where I had to start from scratch trying to define and then continuously prove the value of data science. When I arrived at Clearlink, however, I was incredibly lucky to walk into an organization that already had an innate curiosity about data and a desire for more information.

No matter what situation you walk into, start by having genuine, passionate discussions with people about their challenges and goals. Take the time to explain data science to individuals and teams. Then discuss how it could alleviate pain points and help teams move in the direction they want to go. Give people a data science lens to see their concerns through, and you’ll pave the way for more open conversations and collaboration.

Our goal at Clearlink is to make data science accessible so it can accelerate our customer-focused strategy. We want to give marketers tools that allow them to deliver a more meaningful product and service to customers. Keeping that shared end goal at the forefront of your early discussions and regularly communicating it with all team members will remind everyone that you’re united around the same goal. Making data science accessible is key to encouraging mutually beneficial collaboration.

One way we’ve seen this recently is with a request brought to us by some members of Clearlink’s marketing team about using data science to create a new form of online content. Right now we’re working on creating some new television scripts, based on Recurrent Neural Networks (RNNs)—similar to AI-written fan fiction. It’s a buzzy, somewhat silly form of content that has real potential to help this team accomplish their goals, and another way for our team to demonstrate value and create meaningful gains for Clearlink.

Demonstrate Real Change Early On

Whenever possible, try to humanize data science by showing your coworkers how it impacts the business in a practical way. If your organization hasn’t been using data science, there’s probably room for you to make immediate improvements to processes and outcomes from the start. By demonstrating exactly what you can do for a specific department, you help transition your first impassioned discussions about data science from theory into into real, applicable tactics that encourage further collaboration.

For example, when I first started at Clearlink, I was fortunate to quickly spot a way to make real improvements. At the time, the sales department was using 1-800 numbers to help track customers who visited our sites and then phoned into our call center. The system worked well, but they didn’t have an accurate idea of how many numbers they actually needed to lease each year. This simple lack of insight meant they were paying far more than necessary to ensure coverage. To the data science team, that was a simple fix. We immediately saw where we could better track customers and forecast the exact amount of numbers needed — minute-by-minute, day-by-day — in real-time. Within months, we did exactly that, and wound up saving Clearlink hundreds of thousands of dollars.

More recently, we’ve successfully collaborated on an enormous consumer database compiled for the marketing department. This database gives the department the ability to fine-tune messaging and experiences in ways they’ve never been able to before. When it comes to connecting on a human level and identifying who can truly benefit from your product, the message matters far more than the method of delivery.

If you can make a connection with a person, you can help them find what they’re looking for. Our data helps our talented marketing teams connect with people more efficiently and on a deeper level, and allows them to use their expertise to craft and deliver the best messages for people who are going to benefit from our products and services.

Move Forward by Appreciating Collaboration

Of course, data science can’t solve every problem. It’s important to remember this and appreciate other people’s skills and knowledge. As data scientists, we can deliver an array of tools that aid digital marketing, but we need to trust that others have expertise that allow them to use those tools to their best advantage as well.

Whatever stage your data science department is in at your organization — just an idea, brand new, or a few years old — stay humble, be willing to learn, and remain patient. Clearlink may have had an innate appreciation for data science from the start, but you can foster a similar kind of appreciation in a more hesitant organization by focusing on common goals and forging a positive and genuine relationship with the rest of the business.

Landon Starr
Author
Landon Starr

Landon Starr leads the data science organization at Clearlink, which includes the information management, advanced analytics, reporting, and CRO teams. His organization builds AI/machine learning capabilities, manages experimental design and creative A/B testing processes, optimizes UX, and architects the information management backbone to support the breadth of data capabilities that enable Clearlink’s intelligent customer experience platform.