Learn about the primary skills necessary to become a citizen data scientist for your marketing organization including curiosity, an appetite to ensure performance, data modeling, statistical know-how, scientific experiment know-how, and an analysis toolset.
- This course was developed with you in mind. Yes, you. Even though we may not know one another, I can say that confidently. Whether you're the head of marketing at a Fortune 500 company, an account manager at an advertising agency, a visual media wunderkind, or have some other job title. Now, there's an old story about a wealthy land owner who lived a very comfortable life on his own farm. One day, this man was paid a visit by someone who told him about diamonds for the first time. This precious material, glimmering, beautiful, and valuable. The land owner became obsessed with finding diamonds himself and sold his land.
He never did find the diamonds that he set out to discover, but years later, the very property he sold became one of the world's largest diamond mines. So, what does this story say about your marketing? The point is, that there are rich nuggets of insights hidden in your marketing data at this very moment. The barrier to unlocking these for most marketing organizations is only perceptual. We envision these insights might be somewhere else, or we think of them as someone else's responsibility. Perhaps the elusive VP of data science, for example.
Now, as you go forward through this course, and in your role as a marketer, there are some things you'll likely need to advocate for to ensure you get as much traction as you can. You have to take ownership in collaboration with your peers in finding and taking action on that data. You also have to hold marketing accountable and exhibit its positive impact on the business. Finally, you have to speak a common vernacular. In view by data science, not obfuscated by it. You're going to learn some phrases in this course and in your journey as a citizen data scientist for marketing that will present a barrier to communication if used as jargon.
It's the dawn of a new day. Let's embrace that fact, let's advocate for it. Let's think differently and create the change in our organization to allow data driven insights to take root.
In this course, discover how to gain valuable insights from large data sets using specific languages and tools. Follow Chris DallaVilla as he walks through how to use R, Python, and Tableau to perform data modeling and assess performance. As Chris dives into these concepts, he shares specific case studies that come directly from his own work with clients. Plus, he shares three essential—and practical—best practices for data-driven marketing that you can use to bolster your organization's marketing performance.
- Installing R, Python, and Tableau
- Navigating the UI for R, Python, and Tableau
- Using R, Python, and Tableau
- Exploratory analysis
- Performing regression analysis
- Performing a cluster analysis
- Performing a conjoint assessment
- Stakeholder alignment