UX-Benchmarking Study Documentation

The UX-benchmarking study is a practice to measure and compare the UX of different versions of a product. It involves running iterations of the same summative study, called a benchmark study, on different product versions to gauge UX improvements. Metrics such as success rate, task time, and user satisfaction are used to compare the versions, and statistical analysis is done to judge the observed differences.

Contents

• Study Methodology: Details of how the benchmark study was conducted for each product version.
• Tasks: A list of important tasks that need to be completed during the study.
• Screener: Criteria for selecting study participants.
• Collected Metrics: Definitions of metrics used to compare different product versions.
• Raw Data: Data obtained from the benchmark study.

Study Methodology

The study methodology explains how the benchmark study was conducted for each product version. It includes details of the study environment, protocol followed, and the type of study conducted (e.g., in-person, remote unmoderated).

Tasks

The task list mentions the important tasks that need to be completed during the study. These tasks should be common across the different product versions being compared.

Screener

The screener criteria explain the process of selecting participants for the study. The screener variables will vary based on the product being tested, the target audience, and other factors.

Collected Metrics

The collected metrics are the criteria used to compare the different product versions. Common metrics include success rate, task time, and user satisfaction. It is important to define the metrics and how they will be measured before conducting the study.

Raw Data

The raw data obtained from the benchmark study should be stored in the research repository for future reference. The data should be organized in a way that allows easy data analysis and manipulation.

In conclusion, documenting a UX-benchmarking study is important, and all details of the study methodology, tasks, screener, collected metrics, and raw data should be stored in a research repository for future reference.