Big Data and New Marketing Research Techniques

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Introduction

Marketing research always involves analysing a large amount of information because it should address a number of significant factors, including product characteristics, market conditions, and consumer behaviour. New methods of collecting and processing data enable more efficient design and verification of research hypotheses. According to Constantiou and Kallinikos (2015), “Big data and the mechanisms by which it is produced and disseminated introduce important changes in the ways information is generated and made relevant for organisations” (p. 44). This paper examines the impact of Big Data and new research techniques on conducting market and consumer research.

Market Research

Market analysis involves evaluating existing products, competitors, and economic trends, including supply and demand. Big Data is a set of approaches, tools, and methods for processing structured and unstructured data of vast volumes and a great variety in order to draw meaningful conclusions (Constantinou & Kallinikos, 2015). This phenomenon appeared due to technological developments, including the increasing influence of digital space. In modern times, market information is more transparent and accessible, as much of the data is contained on the Internet. Therefore, new marketing research techniques are related to its effective collection and analysis.

Consequently, market research is increasingly focused on digital data and social media. According to Erickson (2017), Big Data analysis methods, including neural networks and advanced statistics, make it possible to examine entire market segments and predict specific outcomes. Market researchers can use Big Data to determine the best placement channels for their products and adjust their supply chains. However, a thorough market analysis requires employing information technologies and complicated mathematical algorithms and calculations. The significance of the data collection phase decreases over time as the digital environment provides free access to information, but the choice of methods of data processing and analysis is paramount.

Consumer Research

It should be noted that consumer research most often implies generalisation of study findings to a broader population. Digital data enables access to “the reality of public opinion” and allows for making the “rationale of consumers’ tastes, opinions and judgments appear through their formatted individual expressions” (Boullier & O’Hagan, 2017, p. 35). Social media and other digital sources provide researchers with insights into consumer identity. Surveys and questionnaires are still in active use, but due to Big Data methods, they can be presented to a more significant number of potential customers. In addition, direct forms of consumer expressions and judgments are also available to researchers.

At the same time, social media can contain excessive amounts of contradictory and false information about consumers. Big Data analysis is also valuable because it processes large volumes and a variety of data with high velocity, which significantly exceeds human capacity (Erevelles, Fukawa, & Swayne, 2016). For example, neural networks can compare and evaluate information, identifying obviously irrelevant or most valuable. In this way, researchers may use these methods to construct an image of consumers’ real needs and values.

Conclusion

It may be concluded that Big Data and new research techniques have greatly influenced the market and consumer research. They imply the use of advances in information technology to explore vast and diverse volumes of information, including digital content. These methods require more competence and training but provide enhanced opportunities to analyse market conditions, products, competitors, and consumers. The methods of processing and assessing huge volumes of information are the basis of the modern approach.

References

Boullier, D., & O’Hagan, J. (2017). Big data challenge for social sciences and market research: from society and opinion to replications. In F. Cochoy, J. Hagberg, M. McIntyre, & N. Sörum (Eds.), Digitalizing consumption, tracing how devices shape consumer culture (pp. 20–40). London, England: Routledge.

Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897-904.

Erickson, G. S. (2017). New methods of market research and analysis. Cheltenham, England: Edward Elgar Publishing.

Constantinou, I. D., & Kallinikos, J. (2015). New games, new rules: big data and the changing context of strategy. Journal of Information Technology, 30(1), 44-57.

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