Revolutions are happening in many industries as the trend of Big Data prevails in recent years. To occupy an advantageous spot in the data era, companies are aggressively seeking for their conjunctions with the Big Data. More traditional mindsets and methods that have dominated over the past decade are shaken by the occurring data wave. People are always asking whether Big Data will become a transitioning point that can overturn all the previously established systems of certain industries. Doubts and debates around this issue seem to be endless. In the marketing realm, the emergence of big data is shocking the traditional marketing research. In 2014, there had been 48% of companies using consumer behavior data to generate consumer insights (Martin, 2014). The heated debate aroused about whether the big data research can finally replace the traditional consumer research in the process of making decisions. To have a closer glance at this question, the core difference of big data marketing research and traditional consumer research should be addressed.
(http://www.datameer.com/company/datameer-blog/the-state-of-big-data-adoption-a-glance-at-top-industries-adopting-big-data-top-use-cases/)
There is no doubt that “Big Data” has become a buzzword. However when it comes to the difference between big data and traditional marketing research, the majority of non-data experts may only know that big data distinguishes itself by using a large volume of data to guide the marketing decision-making process. In other words, compared to the traditional method, the big data marketing research is more quantitative. However, what’s deep-rooted beneath its data-driven method is its big data mindset, which is completely different from the traditional marketing mindset.
So what’s the unique big data marketing research mindset? I happened to realize the existence of big data mindset in my Big Data course two weeks ago. We were assigned a task to generate a business report for NBC from a pile of data. Just as what I usually do, I began by deciding the theme “How can NBC find its valuable clients according to the data information?”. Then, before actually accessing the data, I started to brainstorm what kinds of clients could be considered as valuable. After narrowing down the types of valuable clients, I used data to locate them. Seems to be a well-organized logic, right? However, my professor commented on my report that I was not using the big data mindset but a traditional marketing mindset to solve the problem, which means I came up with presumptions of how to answer my business question before analyzing the data. Nevertheless, the big data mindset requires people not to let preexisting knowledge and the hypothesis lead the analysis but to firstly extract information from data without a specific purpose and then think about how to apply the findings in the decision-making process. As a paper summarizes, the traditional marketing research mindset is knowledge-based whereas the big data mindset is ignorance-based (Erevelles, Fukawa & Swayne, 2016). To better understand it, let’s take the consumer research as an instance. Traditionally, we observe consumer behaviors to generate some hypotheses. Then we come up with the interview and survey questions based on those hypotheses. Before actually analyzing the consumers, we have already thought about what questions we want to explore, what kinds of data we should collect and even what possible answers we might get from consumers. Thus, it’s called knowledge-based mindset, which requires marketing knowledge and experience to generate better research results. On the opposite, conducting consumer research with big data doesn’t need people to set research directions at first. Data analysts just acquire the consumer behavior data like what they purchased and how much they spent, and then analyze the relations among different variables. Results like “cakes are usually sold with soaps” or “people who buy broccoli are more likely to buy sodas” can be generated. (These relations are randomly made up) We don’t know what kind of results we expect and just find whatever can be found. So this kind of mindset is “ignorance-based.”
(http://www.tieto.com/services/information-management/business-intelligence/big-data)
Is there a better one between the two kinds of mindsets? In order to answer this question, a pros and cons analysis should be done. In my view, the ignorance-based mindset is more creative, flexible and limitless than the knowledge-based mindsets. Sometimes, the hidden relations of consumer behaviors are unexpected and hard to explain with people’s limited cognitions. Just like you can’t imagine why there is a connection between cakes and soaps. In this sense, big data is able to break through human’s cognition and imagination blind points as well as dig out some surprising but valuable insights. The traditional marketing mindset is superior to big data mindset in its explanatory ability of consumer behaviors. There is a dominant voice that although big data is able to perceive “what is happening” and predict “what will happen”, it can never tell us “Why it happens” (Fromen, 2014; Finding a Place for Market Research). Thus, traditional marketing research mindset doesn’t skip the explaining process and directly jump into the conclusion part like the big data mindset does, it tries to discover deep reasons covered by the phenomenon with the guide of preexisting knowledge, hypotheses and marketers’ wisdom. Furthermore, the lack of explanatory ability of consumer behaviors can hinder the development of marketing theories since the result-oriented big data marketing research is so pragmatic that its results may only serve limited cases and lack the generalization ability. Rather than identifying which mindset is better, I am inclined to believe that they are serving as each other’s complementary part. The two different kinds of mindsets will co-exist and even co-operate together in the future because we need both of the fresh and creative insights and deep explanatory findings; we care about both “What consumers’ behaviors are” and “Why they behave like that”.
References:
Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897. doi:10.1016/j.jbusres.2015.07.001
Fromen, A. (2014). Why big data will never replace market research. Retrieved from http://www.greenbookblog.org/2014/05/19/why-big-data-will-never-replace-market-research/
Wharton Business School. (2014). Finding a place for market research in a big data, tech-enabled world. Retrieved from http://knowledge.wharton.upenn.edu/article/finding-place-market-research-big-data-tech-enabled-world-2/
Anonymous. (2015). Getting into the big data mindset. Retrieved from http://www.tieto.com/services/information-management/business-intelligence/big-data
Sebastian. (2015). Big data and market research myths and missteps. Retrieved from http://data-informed.com/big-data-and-market-research-myths-and-missteps/