

Technology-Driven In-Home Usage Testing (IHUT): Faster Insights, Better Data
Consumer and Product Experience
Overview
A global healthcare company partnered with Eolas International to modernise its In-Home Usage Testing (IHUT) programme. The objective was to replace traditional, resource-intensive research methods with a technology-driven solution capable of delivering faster consumer insights and improved data accuracy.
By leveraging the Eolas QualX platform, Eolas streamlined data collection, enhanced participant engagement, and enabled scalable multi-market research. The result was a more efficient and cost-effective IHUT programme that provided high-quality consumer feedback in real time.


Client Objectives
The client sought to modernise its In-Home Usage Testing(IHUT) process by implementing a more efficient and scalable approach to consumer research. Key objectives included reducing operational complexity, improving data quality, accelerating access to consumer insights, and supporting research programmes across multiple international markets.Â



The challenge
Traditional In-Home Usage Testing programmes relied heavily on manual processes, extensive fieldwork management, and paper-based or fragmented data collection methods. These approaches increased operational costs, delayed reporting timelines, and created challenges in maintaining consistent data quality across multiple markets. The client required a solution capable of capturing authentic consumer feedback while improving efficiency and scalability.Â
Our Solution
Eolas implemented a technology-driven In-Home Usage Testing (IHUT) solution powered by the QualX platform. Participants completed surveys, uploaded feedback, and reported product experiences through a digital interface, enabling real-time data collection and improved participant engagement.
The platform supported multilingual questionnaires and standardised workflows, allowing the client to conduct consistent consumer research programmes across multiple international markets while maintaining high data quality standards.









