Data analysis in Qualitative research

Data analysis can tell you what is happening, but it won't tell you why. So qualitative approaches are a must to bring together the what and the why! An enticing thought advancing towards AI, ML, and predictive analytics is that more data is better. Why wouldn’t it be? As data is the new fuel of the upcoming digital economy, the quantity of data matters. But does quantity ensure quality data? How does it impact companies? The technologies required in qualitative research data analysis exist in a wide range. It helps to explain the varied use — by organizations and vendors. Every organization uses data widely today. Although not all data is used for analytics; analytics cannot be conducted without data. 

Qualitative data is typically more tedious to analyze. It is under the domain of human analysts due to the high level of contextual understanding and social intelligence. Qualitative methods include interviewing groups of people, holding focus groups, and conducting in-depth observations. Here are some aspects of Data Analytics that you must consider:

Data Analytics for Marketers - For marketers, big data is a weapon that gives businesses a competitive edge in modern markets. Consumers are willing to pay for personalized goods and services. But, companies keeping a track of all customers’ online activities can be a bit challenging. So, data helps with detailed insights on consumer behavior and can assist from consumer’s initial interest to final purchase. In the last decade, data analytics has revolutionized the marketing industry.

Data Analytics for Businesses - Strategic thinking and planning are essential for growing your business, especially during difficult times. With the introduction of data-driven decision-making, businesses have increasingly turned to data analytics to assist in decision-making. However, to extract meaningful insights, the data analysis should be efficacious. You’ll need the right qualitative data analysis tools for this.

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