Data are constantly generated by multitudes of systems and processes around us. Every digital process and social media exchange contributes to Big Data. Systems, sensors, and mobile devices transmit data that are compiled as Big Data. These data are used by some to describe and predict human behavior and interactions. Big Data is also used for tracking and extraction of meaning.
Researchers often strive to answer five basic questions. Some refer to these as the “Five W’s:” Who, What, When, Where, and Why. Traditionally, market researchers employ methodologies to answer all five questions.
Four components of the Five W’s are provided by structured Big Data and other data sources.
- The who question identifies the various players in a problem or solution.
- The what question tries to ascertain what consumers are buying, trends, and services used.
- The when question considers various time based events and activities such as when customers are buying products or services, e.g. day part, date range, or life stage, etc.
- The where question addresses geographic and/or logistical aspects of a solution.
Big Data allows market researchers to answer some questions without interviewing or surveying existing and potential customers. However, with the advent of Big Data and sophisticated data mining techniques there is no need to create data if the data already exists. Of course, traditional methodologies such as surveys still need to be employed when there isn’t a data set for every question or set of questions. Also, market research methodologies are still required to tackle the most important question of the Five W’s – the Why. Knowing why our customers and clients choose to behave the way they do is highly critical to being able to tailor our products and services to them.
Why is the why question the most important and hardest to discern? Simply put, humans are inconsistent, impulsive, dynamic, and subtle. Emotional, rational, and irrational drivers of behavior cannot be explained by Big Data and analytics. Additionally, as Big Data becomes more and more prevalent and accessible, the number of questions pertaining to customers’ emotional, psychological, and irrational motivations will increase. Answering the why question is most effectively achieved by the integration of quantitative and qualitative research methodologies with qualitative being used to answer the why question and quantitative being used to verify and quantify the findings.
Qualitative methods used to answer the why may include focus groups, in-depth interviews, observation (ethnography), social networks, and guided online chats. Applied appropriately, these methods will result in a collection of textual, visual and oral data that will need to be analyzed through textual analysis. This qualitative analysis provides insight into customers’ attitudes, behaviors, and their thought processes.
While Big Data is sometimes touted as the magic bullet to address all market research questions, it is not the answer to all questions and insights to be obtained. Big Data has its place in the array of market research methodologies and is an ever growing presence. Before Big Data, primary research conducted by market researchers focused on what was happening. Now with that requirement increasingly solved by Big Data, market researchers can focus on why there are deviations from trends. Nothing beats knowing why people make the choices they do. Big Data finds the patterns, market researchers test the hypotheses.
Xavier Alvarez is a Project Analyst at Q2 Insights, a market research consulting firm with offices in New Orleans and San Diego. He can be reached at (985) 867-9494 or email@example.com.