Machine learning and qualitative data analysis

Most organizations use a variety of data collection and analysis methods to understand their stakeholders, whether through customer satisfaction surveys, product reviews, or employee pulse surveys. These ways of gaining insights fall into two broad categories: quantitative and qualitative data collection and analysis. Quantitative responses can be tallied and analyzed quickly, efficiently, and accurately with the help of mathematical logic formulas, algorithms, and, now, machines. Analyzing qualitative data is typically trickier, and it largely remains the province of human analysts, given that it requires a high degree of contextual understanding and social intelligence. For qualitative analysis insights to be considered valid--and taken seriously--the old-school method generally involves two or more people separately analyzing (for example, coding or categorizing) the data collected.