- 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.
Надежда Иванова
User Researcher
Nadezhda is a user researcher with a background in Software Engineering and a Master’s degree in Artificial Intelligence. For the past four years, she has worked as a UX researcher at SAP, leading research activities across various products and services within the SAP cloud platform ecosystem. She focuses on establishing a standardized approach to user research, enabling researchers and dev teams to quickly adapt to SAP’s ever-changing cloud environment.
She believes that understanding what users want and how they want it is key to a product’s success. This is especially true for software products – no matter how optimal the backend or how robust the functionality, a poor user experience can undermine the efforts of everyone involved in the product’s development.