With machine learning, convoluted algorithms, and advanced modeling, #data science has an intimidating aura, leading many marketers to believe that all data science requires super advanced analytic and programming skills most do not possess. Not true.
Talk to data scientists about what they actually do on a daily basis and that impression quickly changes. Generally, to reach a major analytic achievement, the work is quite mundane up until the very end. So what do data scientists really do? They find new sources of data, determine whether they’re relevant and what can be learned from them, clean them up so they are usable, prepare them for analysis, and then run an analysis that everyone can understand. It’s only then that the hardcore modeling begins, and even then, technologies like Nutonian’s Eureqa, Qlik, Teradata Aster, Platfora, Alteryx, and many others can make advanced analytics much easier.
There’s no reason to be afraid any longer. Every marketer should be an amateur data scientist. Marketers can do 90% of the work of data scientists and doing so can have a tremendous benefit. Sure, you might not be doing your own models, but you don’t need to in order to get value from data science.
The first step in embracing data science is to break the mold of how most marketers use data. Too often, marketers are passive receptors, relying on Google analytics to analyze websites or Hootsuite to track social media. If instead, you grab raw data sources and imitate the ways a data scientist works, you’d likely make new discoveries.
Here are a few ways to get started:
Use external data
There are an abundance of public data sets online. For instance, Amazon Web Services has a helpful list of the public data it offers. These types of data sets provide essential context for making business decisions, for example, knowing the start time of the school year across the country can benefit a company in deciding when to push school campaigns to individuals in certain cities and states. Census data is also free and valuable.
Start with simple visualizations
Excel, Google Analytics, and Tableau are just some of the more common examples, but there are a lot of free tools online for data visualizations. Visualizations are great way to probe— they help to see what you might miss from looking only at the data.
Correlation and basic statistics
Even if you’re just using Excel, you can hone your skills to get a lot more out of your data. With simple calculations and pivot tables, marketers can find correlations that can lead to more targeted campaigns.
Eventing
Knowing when there might be a sudden demand spike or a lull that’s caused by outside events can give marketers a competitive edge. Marketers should track major events and work campaigns around them. By monitoring prices from online hotel and airline websites, for instance, companies can track anomalous price information indicating high demand.
There’s no reason marketers should think data science is something only for those with a Ph.D. Data science is something marketers can and should incorporate into their daily operations.
So you’ve crunched the data, but now what? It’s time to act on your insights with killer marketing collateral.
