AboutAlex J. Caffarini Expertise I can answer questions on any of the following:
* Determining the best marketing research method for your needs;
* Conducting surveys (including questionnaire design);
* Measuring the effectiveness of marketing promotions;
* Determining market size or market share;
* Data analysis;
* Statistical modeling;
* Sales or business forecasting; and
* Market segmentation.
Experience I have 15 years of marketing research experience across several different industries, including banking, insurance, retail, and non-profit.
Organizations American Marketing Association
Education/Credentials M.B.A. in Marketing and Quantitative Methods, and B.B.A. in Economics, both from Loyola University Chicago.
Question Hi Alex, Briefly, what are the main 'statistical tools' used in market research today? To what extent does a practitioner need to understand the mathematics behind these tools, or is there a trend towards 'black box' tools?
Answer Mary,
There is a wide breadth of statistical tools used in market research. Hypothesis testing is frequently used to determine whether significant differences exist between groups, or between expected responses and actual responses. Regression analysis is used to identify potential drivers of customer behavior and satisfaction (cross-sectional analysis) or to forecast future sales (time-series analysis). Discrete Choice Modeling and Conjoint Analysis are frequently used to determine optimal pricing and product features. The list of statistical tools used in market research is endless.
The extent to which a practitioner needs to understand the mathematics behind the tools depends largely on the level to which he/she works with the data and draws conclusions from it. If the practitioner is significantly involved with these tasks, then he/she should know how what the business problem that must be solved; the data available to answer the problem, the nature of the data, the appropriate statistical tool to use, how the tool works, the theory behind the tool, and the meaning of the output the tool generates. If the practitioner is simply a decision-maker or presenting the findings, he/she should at least understand the results of the tool, and why it was the most appropriate tool to use.
Sadly, there is a trend in favor of "black box" tools. Mathematical acumen is sorely lacking among many professionals. And although black box tools can generate highly accurate and actionable results, there is a great chance they can be greatly misused if the practitioner doesn't understand the uses and limits of that tool.
