Browse by title

You are looking at 1 - 10 of 1,116 items :

  • Research Methods in Business and Management x
Clear All
This content is available to you

G. Scott Erickson

You do not have access to this content

G. Scott Erickson

Chapter 5 covers other areas of research impacted by the big data and marketing analytics trend, those beyond the research designs of previous chapters. The chapter reviews traditional concepts before discussing what changes are apparent. Specifically, the chapter looks at determining decision problems and research problems, ethics, sampling and administration, SWOT analysis and competitive intelligence. Each has been affected by big data and new collection and analysis techniques. In particular, data mining and continuous collection of information have made explicit decision and research problems less critical, new ethical considerations arise with the constant unobtrusive collection of individually identifiable data, large samples and even entire populations used in contemporary research can be reached easily by internet and mobile devices, SWOT inputs can be gathered widely and continuously, and competitive intelligence can take advantage of the constant interaction between marketers and their targeted customers.

You do not have access to this content

G. Scott Erickson

New Methods of Market Research and Analysis prepares readers for the new reality posed by big data and marketing analytics. While connecting to traditional research approaches such as surveys and focus groups, this book shows how new technologies and new analytical capabilities are rapidly changing the way marketers obtain and process their information. In particular, the prevalence of big data systems always monitoring key performance indicators, trends toward more research using observation or observation and communication together, new technologies such as mobile, apps, geo-locators, and others, as well as the deep analytics allowed by cheap data processing and storage are all covered and placed in context. This book can be used as a supplement to a traditional marketing research text or on its own.
You do not have access to this content

G. Scott Erickson

Chapter 2 looks at the basics of exploratory research design, chiefly characterized by qualitative data, small samples, and the search for new insights. Standard approaches through existing data, observation and communication are reviewed as are familiar techniques such as focus groups, depth interviews, ethnographic studies and projective techniques. With this background, contemporary research from qualitative research providers such as ReD Associates is examined, stressing both the similarities and differences in current practice. In particular, new initiatives enabled by big data and analytics are highlighted, showing the impact even on qualitative studies. The blending of observation and communication, longer or repeated data-gathering opportunities, and gamification are all discussed in the context of traditional exploratory designs.

You do not have access to this content

G. Scott Erickson

Chapter 3 discusses the nature of modern descriptive research design, quantitative data collected from large samples but without the rigor of a formal experiment. Traditional descriptive approaches and techniques are presented, including existing data, observation and communication. The chapter includes common concerns with questionnaires such as respondent cooperation, instrument design and method of administration. The emphasis is on broad trends in observation research (or observation combined with communication), ongoing relationships with respondents, and engagement. In particular, examples from advertising evaluation, social media observation, shopper tracking, and insight panels/enthusiast groups are employed to explain current trends.

You do not have access to this content

G. Scott Erickson

Chapter 4 explores trends in causal/experimental research design, usually quantitative data used in a structured manner to test a hypothesis. Approaches in typical marketing research texts are briefly covered, including the logic and structure of experiments, sources of bias, test markets, and experimental designs, including quasi-experiments. Although existing data often aren’t appropriate for experiments, ongoing collection programs can be employed, using observation or communication techniques. New approaches that can unobtrusively test responses in both the real world (field experiments) and virtual environments (laboratory experiments) are included. Extended examples cover advertising testing, pricing variation and dynamic pricing, shopping environments and beta tests. Important trends such as ongoing mini-experiments in day-to-day operations, individualized experiments, and unobtrusive testing are all covered.

This content is available to you

G. Scott Erickson

Chapter 1 covers definitions and methods related to big data systems. Placing big data monitoring systems in the context of loyalty programs developed by Tesco/dunnhumby and Caesar’s, the discussion characterizes what big data is, how systems collect and share it, and how it is used to enhance day-to-day decision-making. Concepts like key performance indicators and action-oriented algorithms are included. Coverage then moves to more in-depth marketing analytics related to big data. Here, the marketing approaches of Spotify and Bloomberg are used to illustrate and explain how analysts cut the data in different ways looking for insights as well as conducting predictive and clustering analysis.

You do not have access to this content

G. Scott Erickson

Chapter 7 explains new analytic techniques designed to study and obtain insights from big data basics. It covers linear regression concepts, decision trees and clustering analysis, the first two tied specifically to predictive analytics. Each is illustrated with the SAS Visual Analytics software and large data sets, explaining what the software is doing and what the results mean. All are then tied back to practical examples in previous chapters.

You do not have access to this content

G. Scott Erickson

Chapter 6 discusses the differences between traditional data gathering, categorization and reporting and current practices with big data. Measurement scales, response formats and the relationship between them are reviewed. The chapter introduces SAS Visual Analytics software and runs through descriptive statistics, tabulation, cross-tabulation and visualization according to the different measurement types. The tools are related back to a number of the practical examples covered in previous chapters.

This content is available to you

Patrizia Hoyer, Chris Steyaert and Julia C. Nentwich