It is easy to understand why data-driven marketing is quickly becoming the status quo, but do you need analytics or data science to be successful – that depends on what questions you need answered.
Data science and analytics compliment each other but there are fundamental differences between the two. At a basic level, analytics tend to be more tactical and departmental, while data science is more strategic and organizational.
Data analysts leverage analytic tools to read and study historical marketing data. A subset of data science, analytics are adept at identifying historic trends and communicating the results of previous performance.
Data science, on the other hand, is responsible for understanding how all available 1st, 2nd and 3rd party data can be leveraged to gain competitive business intelligence. Data scientists are business analysts that are typically more concerned with forecasting the impact of future business decisions than looking back at historical trends.
Where analytics are needed to understand past marketing performance, data science is needed to answer more difficult forward looking business questions. Both disciplines and technologies are needed to extract marketing intel from data and turn that intel into business knowledge.