Abstract
Customer surveys rely on structured questions used to reflect on reality. Surveys, in general, rely on sample observations derived from a population frame that can be statistically analyzed. Eventually, a survey is judged by the quality of the information it provides. The paper discusses how to apply the information quality (InfoQ) framework to discuss various aspects of customer survey design, deployment and analysis. InfoQ involves 8 dimensions: 1) Data resolution, 2) Data structure, 3) Data integration, 4) Temporal relevance, 5) Chronology of data and goal, 6) Generalizability,7) Operationalization and 8) Communication. The goal is to generate high InfoQ from a customer survey, by properly addressing these dimensions, . Various models like CUB, Bayesian networks, Non-linear PCA and decision trees used in analyzing customer surveys will be presented from an InfoQ perspective. A new concept of InfoQ integrated modeling is proposed that is based on combining analysis using several models for increased InfoQ.
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