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 some thoughts on 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 this new RW Connect Quant Essentials series, we’ll discuss 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 particular phenomenon.
In marketing research, it historically has meant consumer surveys. Survey research is widely-used in many fields, and also by scholars and government agencies. “Quant” is much more than survey research, though. When I began my marketing research 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.”
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 also have a much larger array of analytics tools at our disposal, plus computers able to process and analyze data at speeds unimaginable just a few years ago. 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. So, all-in-all, it’s not quite plus ça change, plus c’est la même chose.
Missing Links provides links to interviews with scholars and veteran marketing research practitioners. A broad range of topics pertinent to marketing research are covered in these interviews. There are numerous 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. If you’d like to move beyond traditional Stats 101, I can 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, presentations and reporting. There is also business development, management and many other important areas we’ll touch upon. We’ll publish a new article on a different topic fortnightly. Coming up next is research design. We hope you’ll find Quant Essentials interesting and helpful!
Kevin Gray, Marketing Research, Statistics and Data Science Subcontracting and Consulting
Kevin Gray is President of Cannon Gray, a marketing science and analytics consultancy. He also co-hosts the audio podcast series MR Realities.