ROLE: PRODUCT & SERVICE DESIGN LEAD / YEAR: 2025 / CLIENT: MOTLEY AI
Motley: turning customer data into actionable AI insights
As a result of this work:
- Designed and launched Motley’s first product.
- Shaped the product through testing with early adopters.
- Motley went on to raise $1.5m in pre-seed funding.
Motley AI is an AI-powered intelligence platform that automatically generates tailored Customer Success reports for CSM teams.
As the Product & Service Design Lead, I worked with the CEO, Tech Lead and developers to design Motley’s first product and take it from concept to launch. I led the UX from discovery and prototyping through user testing and implementation.
Challenge: Turning a powerful AI engine into a simple, useful product experience
Rapidly prototype, test, and refine a frictionless experience around a powerful AI engine that generates tailored Customer Success reports. Through continuous iteration with early adopters, the goal was to validate product-market fit, accelerate time-to-insight, and lay the groundwork for a scalable SaaS solution.
1. Map & Prototype
Working closely with the Tech Lead, I mapped the end-to-end service in a Service Blueprint, connecting user needs, product touchpoints, data sources and backstage processes. I then translated this into interactive prototypes covering the core experience, from accessing customer insights and client information to selecting data sources and generating reports.
1.1. Service Blueprint
1.2. Marketing site
1.3. Product Pages
Dashboard: quick access to the most important data
Client Profile: bringing customer information together
Report creation: selecting data sources and generating a report
2. Test
We ran product-market fit interviews with Customer Success Managers from early partner companies, using the prototype to test the proposition in context. The sessions explored the full experience, from onboarding and AI insights to report customisation, integrations and workflow efficiency, while assessing where users saw the most value and what could limit adoption. Findings were synthesised into product priorities that shaped subsequent iterations.
3. Prioritising Web Reports
Testing the full experience revealed one clear priority: users didn’t want reporting to depend on data they had to upload or connect themselves. They wanted Motley to do the research too.
We made this the focus of the next iteration, introducing Web Reports — AI-generated reports built from publicly available web data. This removed a major barrier to getting started, broadened the product proposition, and allowed users to get value before connecting internal data sources.
