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I am a marketing scientist, though nowadays some call me a data scientist. I’ve been working in marketing research for more than 30 years and would like to offer my thoughts on the essential skills I think we must have to be good quantitative marketing researchers. This is not to say qualitative research is unimportant – I am a heavy user of it, in fact!
In this new RW Connect Quant Essentials series, we’ll discuss the most critical methodological skills concisely and entirely nontechnically. The series is aimed at newcomers to the marketing research profession but, along the way, there will be tips I hope even veterans will find useful.
Let’s begin at the beginning. What is quantitative research? It has been defined in numerous ways, and here is one definition:
Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to predict or explain a phenomenon.
In marketing research, it historically has meant consumer surveys. Survey research is widely-used in many fields, and by scholars and government agencies. “Quant” is much more than survey research, though. When I began my career in the 1980s I worked on the client side with a financial services company. We had extensive customer records and, though the IT infrastructure and analytic tools were crude by today’s standards, part of my formal role was what many would now call “data science.” We were just known as marketing researchers in those days.
Now, of course, we have vastly more data from many more sources – nearly everything we do, it seems, leaves a digital trail of some sort. We now also have a much larger array of statistical and machine learning tools at our disposal, plus the computers needed to put all this together. Still, the essentials have remained much the same. Integrating consumer survey data with other data, such as customer records, was less common but already part of marketing research. Until recently, though, marketing researchers who had spent their careers at MR agencies were mostly unaware of that side of quantitative research. The reason, I suspect, is that it has mostly been done by clients themselves or by specialized companies, not by the typical marketing research agency. So, all-in-all, not quite plus ça change, plus c’est la même chose.
Missing Links lists links to interviews with scholars and other authorities on data and analytics that clear up many myths and misconceptions about data and analytics. Other interviews on topics of interest to marketing researcher are also included. There are many other resources, on and off-line, as well as courses and seminars about data and analytics. For example, Data Mining Techniques (Linoff and Berry) is an excellent, jargon-free overview of data science is. If you’d like to move beyond Trad Stats 101, I can hardily recommend An Introduction to Statistical Learning (James et al.). Throughout the series, I’ll be mentioning other sources I’ve found helpful.
We’ll concentrate on the core areas of quantitative marketing research. These will include research design, sampling, questionnaire design, data analysis, multivariate analysis, and presentation and reporting. There are also business development, management and many other important areas we’ll touch upon.
We hope you’ll find Quant Essentials interesting and helpful!
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