A global health and wearables technology leader serving millions of users worldwide engaged Akraya to establish quantitative UX research capabilities for their emerging AI-powered products.
Challenges Faced
This section outlines the core difficulties and pain points the client was experiencing. It provides context on the hurdles that needed to be overcome before achieving the successful outcome.
No Baseline for AI Product Performance
As the team prepared to launch a new AI-powered health chatbot, they lacked established metrics to measure user trust, engagement, and satisfaction.
Limited Quant Research Infrastructure
The Rapid Insights team had focused primarily on qualitative research, with minimal expertise in psychometrics, statistical analysis, or programmatic data collection.
Complexity of Measuring Abstract Constructs
Leadership needed to understand how users perceived and trusted the AI chatbot. Traditional survey methods (e.g., "Do you trust us? Yes/No") would not yield actionable insights.
Akraya’s Strategic Solution
We deployed a quantitative UX strategy with psychometrics, statistical analysis, and AI product measurement to build scalable research infrastructure -
Akraya designed and implemented comprehensive measurement frameworks for AI-powered features, translating abstract concepts like "user trust" and "engagement quality" into measurable elements.
Engineered automated workflows for survey deployment (Qualtrics, Dscout, UserTesting) and log data analysis, reducing manual processing time and enabling rapid iteration.
Developed an LLM-based classification system to process and categorize large volumes of unstructured text data from user inputs across multiple platforms.
Measurable Outcomes
Operational
50% reduction in reporting turnaround with automated analysis pipelines.
Financial
$12.8M annualized cost avoidance by eliminating reliance on third-party agencies for data analysis and reporting.
Business
Created foundational metrics for AI chatbot performance that enable data-driven product decisions from launch.
Conclusion
Akraya transformed the research capabilities of a global health technology leader by embedding quantitative UX expertise into their product development lifecycle, engineering automated data pipelines, developing LLM-powered text classification systems, and establishing psychometrically valid measurement frameworks for AI features.
