More likely than not, a profound love of math and science isn’t the reason you’re pursuing a career in marketing. Rather, writing talent, creativity, critical thinking and interpersonal skills may have led you in the direction of marketing. But are these attributes alone enough for success in the field? Probably not. The field of digital marketing has transformed into a data and technology driven industry.
Data-driven marketing is essential
While a sharp mind has always been important for marketers, we now have access to more information than ever before. In addition to the usual skills expected of them, today’s marketing professionals must also know how to leverage this wealth of information into actionable insights. We all know the importance of Google Analytics and analyzing data for marketers, but how do you take that to the next level? Enter data science.
“Marketing has become a technology-powered discipline, and therefore marketing organizations must infuse technical capabilities into their DNA.” - Scott Brinker, Chief Marketing Technologist
What does data science mean in a marketing context? Access to real-time, accurate, and relevant information that supports truly data-driven solutions. Data science bridges the gap between mere data and real meaning to improve and optimize marketing efforts. Visualization of this data is key to reporting and communicating new trends or insights to others at your company.
How do you learn data science and visualization as a marketer?
Most marketing companies plan on integrating data science and marketing technology into their business strategies on a larger scale moving forward. Now it begs the question: How can you learn the skills today's employers are looking for? Luckily, a number of predictive data analytic tools exist aimed at helping even the most non-techie marketers make sense of their data.
One of our favorites for getting started with data science? Tableau. Not only does Tableau help marketers connect with data, create simple drag-and-drop visualizations, and easily share findings with a click, it also provides a number of free training resources, including videos, live online training sessions, and a handy starter kit -- all aimed at maximizing the user experience. From making sense of your website’s traffic trends to accelerating decision-making, Tableau is the top performer when it comes to seeing and truly understanding your data. Even better? It connects directly to Google Analytics for even more powerful insights.
“The more visual and vibrant you can make your stories, the more impact your analysis and work will have.” - Joel Stellner, Founder of TableauHelp.com
Visit Tableau’s gallery to see hundreds of examples of data visualizations to gain inspiration on how to enhance your marketing reporting.
Where do you find Tableau training?
The best place to start in learning Tableau is downloading Tableau Public and working through the free training materials. You will have access to free datasets to use and be able to gain familiarity with the tool. Once you’re ready, import your own data from your organization and start generating reportings and marketing dashboards.
Instead of simply learning Tableau on your own, consider attending in-person training sessions with other marketers eager to grow. Nothing beats collaborating with peers in person to solve a data challenge versus solely learning online. Many cities have Tableau user groups or you can find workshops happening in your area. One of our favorite Tableau trainings is provided by the experts at TableauHelp.com.
Time to Conquer Tableau
Ready to learn Tableau and become a more data-driven marketer? Check out Tableau plus read more about data science and the possibilities of becoming a marketing technologist. Also consider applying for the digital marketing apprenticeship where you’ll learn all things digital analytics and receive training from the experts at Tableau Help!Looking to expand your understanding of data science even further? InformationWeek rounded up nine free courses ranging from a basic overview of data science to specialized introductions to Python, R, machine learning, Hadoop and other topics.