Book chapter
Reducing Data Complexity - Chapter 9
01 Jan 2020
Abstract
Marketing datasets 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 questions (e.g. 9) on a consumer survey that reflect a smaller number (such as 3) 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.
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Details
- Title
- Reducing Data Complexity - Chapter 9
- Creators
- Jason S SchwarzChris ChapmanElea McDonnell Feit
- Publisher
- Springer International Publishing
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Marketing
- Other Identifier
- 991019189315304721