ClearGlass Analytics is an independent data analytics company that enables asset owners, investment advisors, and asset managers to evaluate the Value for Money (VfM) of their investments through transparent cost and performance data.

As part of the product team, I contributed to the development of a SaaS platform designed to serve all sides of the asset management market, delivering structured cost transparency and advanced analytics across the UK and European investment ecosystem. The platform integrates industry frameworks such as the Cost Transparency Initiative (CTI) and the Cost Transparency Standard (CTS), enabling consistent data collection, benchmarking, and more informed investment decision-making.

Designing for this product presented unique challenges due to the highly cyclical nature of the industry. The platform operates around critical annual reporting cycles that determine when new features, improvements, and data submissions can be tested and adopted by users. These overlapping cycles created a distinctive product development rhythm and required careful prioritisation to ensure the platform evolved without missing key market opportunities. As one of the first platforms of its kind, the product played a pioneering role in bringing transparency and benchmarking capabilities to the asset management industry.

The organisation operated with a strong product-led mindset, with well-informed stakeholders actively collaborating across teams. Continuous experimentation, research, and rapid shifts in focus were embedded in the company culture, creating a fast-paced environment where multiple teams ran parallel initiatives to validate ideas and improve the product.

Conducting UX research in this domain presented additional complexity. Many users interacted with the platform only periodically during reporting cycles rather than daily, which made recruitment and engagement more difficult. To overcome this, we conducted regular user interviews (approximately every two weeks) and supplemented qualitative insights with internal data analysis and feedback from customer-facing teams. Asset owners were generally more open to participation than asset managers, which influenced our research strategy.

We triangulated insights from multiple sources to inform design decisions, combining user feedback with behavioural data from analytics tools such as Google Analytics, Hotjar, and Mixpanel. These insights were shared across the organisation on an ongoing basis, ensuring that product development remained aligned with real user needs and market dynamics.