Marketing reseach is not short on new trends, methodology nicknames, acronyms, and trendy skills. Sometimes it reminds me of the Subway's "Sandwich Artists." Not a day goes by where you will not see an article about either big data, data visualization, or business intelligence (BI). One of the growing professions in the field has been what is called a "Data Scientist."
What is a data scientist?
A data scientist is a person who can perform advanced forms of analysis to generate insights and findings from data. Essentially, it is a glorified research analyst. Because of the amount of data companies hold these days between web analytics, syndicated data access, and CRM systems, management teams do not know which direction to turn on these platforms to generate insights. Oftentimes firms hire "data scientists" to assist them in analyzing all of this data, merging the systems, and drafting data-driven strategies as an outcome of the process.
What particular set of skills does a data scientist have?
These analysis skills can range from regression, to correlation, to data mining, to predictive analytics. Research and data analysis is very much 20/20 hindsight. It is very informative but relies solely on past behavioral data. Applying past data to future behavior is the next step in the marketing research process as companies look to expand predictive analytics and modeling capabilities. Here are 6 tips to assist you with your next predictive model.
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