A Z-test is a parametric statistical test used in quantitative research to evaluate whether observed differences between two groups, such as brand preference scores or concept appeal ratings, are statistically significant or likely due to chance. The test calculates a Z-score by measuring how many standard deviations a sample statistic sits from the population mean. Z-tests are most reliable when sample sizes exceed 30 and population variance is known or can be reasonably estimated. In market research and consumer insights, Z-tests for proportions are especially common, helping teams determine whether response rate differences across segments, markets, or time periods reflect genuine shifts in customer behavior rather than sampling noise.