Challenge

One fund, two digital worlds

The merger brought together ~170,000 members and ~$30 billion in funds under management. Yet members were still navigating two websites, two brand experiences and complex product histories. A single platform was essential to creating a unified fund and reducing the burden of managing parallel digital estates.

The new website had to serve existing members, prospective members and employers, while making fees, investment performance, products, forms and retirement information easier to understand. It also needed to support strict disclosure requirements, accessibility, secure data handling, and organic search, and transition smoothly from the legacy sites by a fixed early-2026 deadline.

Solution

Starting with member needs

Stakeholder workshops, content and analytics audits, and Top Tasks research revealed what members valued most: understanding fees, checking balances, comparing funds, consolidating super and planning for retirement. These priorities reshaped the information architecture, navigation and key journeys. We then created a responsive design system with accessible colours, typography and interaction patterns, designed to meet WCAG 2.2 AA standards.

We engineered a headless Storyblok CMS and Next.js front end on AWS Amplify, with reusable components, publishing workflows, server-side analytics and CloudWatch logging. Secure forms used AWS Lambda, encrypted S3 storage and SQS queues before a separate worker transferred data over SFTP. This decoupled architecture kept submissions fast and resilient when the receiving system was unavailable.

Results

One platform, ready for more

Launched in early 2026, the website consolidated two digital estates into one experience. Vision Super gained a flexible content platform, a reusable design system, and a secure infrastructure, all ready for new services.

Since launch, analysis covering 434,000 users has informed design refinements, new components and security updates. Predictive Algolia search has gone live, with governed natural-language search in the planning stage.

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