A global technology company wanted to collect feedback on potential in-product support features, scenarios, and concepts.
A global technology company wanted to explore opportunities to improve in-product support features and concepts for support across products. To achieve this goal, research was needed to understand ideal user in-product support experiences across the product ecosystem, identity preferences for support features, and uncover perceptions of AI-generated support help.
We conducted 90-minute one-on-one interviews in four different countries. The interviews had participants share their opinions and rate 20 potential in-product support features. After identifying preferred features, they were presented high- and low-urgency scenarios and asked to describe how they would use those features to navigate each scenario. Finally, they were asked provide feedback on concepts incorporating those features.
Through analysis of participant feedback and rankings, our team provided the client with insights on which features participants preferred, which concepts offered them the support options they wanted, and their perceptions of AI-generated support options. We also provided insight into how support features would factor into participants’ approaches to navigating both high- and low-urgency scenarios.