In this session, you will learn how a user researcher approached research activities for implementing AI in a cloud platform. Specifically, we cover:
- Research Methodologies: We show how we conducted research that ensures users truly want AI integrated into the product, rather than simply adopting it because it sounds appealing. We focus on asking the right questions without biasing the results.
- Data-Driven Decision Making: Next, we show how we analyzed research data, defined the product’s scope, and refined the roadmap. We focus on gathering quantitative data from qualitative insights to ensure we’re on the right path.
- Validation and Metrics: Finally, we show concrete examples of how we validated AI solutions, including key metrics tracked during usability testing. We focus on benchmarking AI performance and enabling repeat usability testing as the solution evolves.
Overall, this session guides you through an end-to-end research approach tailored to AI, highlighting the critical role of user researchers in questioning whether certain functionalities are truly necessary – or just following a trend.
