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Erschienen in:
2019 | OriginalPaper | Buchkapitel
8. Reducing Data Complexity
verfasst von : Chris Chapman, Elea McDonnell Feit
Erschienen in: R For Marketing Research and Analytics
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Abstract
Marketing data sets often have many variables—many dimensions—and it is advantageous to reduce these to smaller sets of variables to consider. For instance, we might have many items on a consumer survey that reflect a smaller number of underlying concepts such as customer satisfaction with a service, category leadership for a brand, or luxury for a product. If we can reduce the data to its underlying dimensions, we can more clearly identify the underlying relationships among concepts.