See how to use JMP and JMP Pro to summarize survey data, extract latent factors from results and identify consumers likely to respond to offers.
Presenter: Jian Cao
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Specialized Modeling Techniques for Interpreting Consumer Studies
Tabulating Survey Data and Testing Hypotheses
The presenter uses employee job satisfaction data to show how to use the Structured option in Categorical Response Analysis to summarize data by key metrics and determine if there are any statistical differences among respondents and across groups.
Using Factor Analysis to Identify Latent Factors Influencing Decisions
The presenter uses automobile market survey data to identify and group related questions and identify latent factors influencing buying decisions. He uses Factor Analysis to identify key latent factors, examines the variable loading on each factor and returns to the original survey questions to determine language which best describes the latent factors. He concludes by using his findings to predict future buying behavior.
Using JMP Pro Uplift Modeling to Identify Prospects Likely to Respond to Marketing Promotions
The presenter builds models to compare purchase patterns of people who received a marketing promotion (treatment group) to those who did not receive the promotion (control group). The goal is to identify characteristics of people most likely to respond to future marketing campaigns by purchasing the product.
Resources related to the information in these videos
- Journal and files used in the presentation
- Jian Cao's blog on Marketing and Consumer Research
- Modern Marketing Research by Ross, Kinnear and Taylor
- JMP add-in for accessing data sets from the Ross, Kinnear and Taylor book (with permission of the authors)
- JMP Add-In for Multidimensional Scaling Using R or SAS Integration