End-to-end Data Analytics for Product Development

6Consumer Voice

6.1 Introduction

Understanding how a new product, solution, or technology is delivering against consumer expectations is one of the key steps in innovation. Many different aspects can be considered, from consumer characteristics to product usage, features, and performance. The way in which they are dealt with in relation to expectation, preference, and purchase intent is key.

Previous products or a competitor's product can generally be benchmarked to assess the relative results and better predict market potential.

In many cases, product developers wish to evaluate the correlations between purchase intent, consumers, and product features or ways of using products. This is relevant to understanding what it is important to focus on in terms of consumer target (gender, age, economic situation, etc.), communication, and possible product improvements.

Very often, the consumer voice is assessed through categorical variables representing opinions, judgments, or preferences, measured on binary or ordinal scales, such as: satisfied/not satisfied; not preferred/slightly preferred/preferred/highly preferred.

In this chapter, several statistical techniques for categorical variables are reviewed to deal with different issues in the evaluation and optimization of consumer experience.

The first case study considers data from a consumer survey in which a sample of respondents were randomly selected to evaluate, by means of a questionnaire, their subjective assessments of the ...