New Ranking Question for Diary, Express, & Recruit
Introduction
Participant ranked choice data is utilized in a variety of foundational experience research designs. Insights professionals leverage ranking questions for feature prioritization and concept feedback. dscout is increasingly supporting broader, more diverse research efforts that benefit from an ordering of responses, and is excited to release a powerful and flexible ranking question for the Diary, Express, and Recruit tools. This new question type also brings with it two new analysis views, which aid in the digestion and socialization of results from ranked-choice response data.
Question Customization
The ranking question is customizable in a number of ways, meant to support a range of potential use cases and participant experiences. First, participants can be forced to rank all response options created or a custom limit set by the researcher. "Custom limit" is good for getting a list of "Top 3" or "Bottom 3", whereas "rank all" is good when you want participants to order all options and feel confident they'll be able to. Second, when asking participants to rank all response options, researchers can enable participants to mark any unfamiliar or irrelevant options as "N/A", for more accurate data. Third, participants can write-in a response option and rank it accordingly, offering a discovery moment to the question. Finally, researchers have the option to randomize response options. As with any question in dscout, stim—in the form of a static image—can be added, creating a quick way to clarify response options or focus on an aspect of an experience (e.g., "Think about the home screen and rate your favorite features.").
Ranked-choice data can present complex output, depending on the number of response options. That's why in addition to the question itself, we're releasing two new views to help researchers unpack and make sense of the data. Found within the "Closed-Ended Responses" section of the data view, these charts offer both table and frequency distribution views, with the former offering a breakdown of how each response was ranked vis-a-vi the others, and the latter showing the final ranked order (calculated using a weighted average) and each response's ranking range.
(A Few) Use Cases
The ability to compare, contrast, and drill into specific favorites enables a host of use cases, especially when paired with other dscout platform tools. For example:
- Competitive intelligence, with context around users' rankings and why
- Prototype or concept comparison, using question stim to share
- Feature prioritization, paired with in-context examples of use cases
- Brand awareness explorations, useful in aligning product-market fit