Investment Assessment Platform & Tourism Spend Prediction
Client: Federal Tourism Agency
(2023–2025)
Role: Design and Solution Delivery Lead
Worked with: UX&UI Designer, Project Managers, Product Owners, Executive Stakeholders, Solution Developer, Data Engineers, Data Scientist and Economist
Objective
Stakeholders at the Federal Tourism Agency sought to develop advanced, data-driven products for enhanced market segmentation and tourism spend forecasting insights. Although the initial MVP was built, low usability highlighted a critical gap in the user experience, necessitating a new design approach to guide strategic investment decisions.
The Design Solution and the Value Created
I led the design process and orchestrated the cross-disciplinary team (Economists, Cloud Engineers, Data Analysts, and Data Scientists) to ensure the user-centric outcome of the product development. We established a rigorous user-centric design and Agile delivery approach through multiple iterations, ensuring delivery within a constrained timeline.
Rather than developing "cover-all" features, we focused on one or two key personas (investors and destination stewards) to define the core objectives and features. This approach was vital to mitigate insights overload and guarantee intuitive user interaction on the platform. We synthesized interview insights to establish core product objectives, which directly drove feature design and guided data modelling requirements.
We mapped the data and insights narrative flow and iterated wireframes that adhered to the initiative's brand guidelines. This outcome defined the blueprint for the GIS-powered segmentation platform embedded in their data hub initiative website.
We engaged and iterated with diverse user representatives and key decision-making stakeholders (including the Steering Committee) through a regular cadence to secure governance and alignment. We captured the product backlog, actively participated in larger program PI planning and product progress presentations, and created a roadmap for future scaling.
My team's involvement with the initiative spanned several phases, including the UX/UI design of the GIS-powered segmentation platform and the later integration of a Machine Learning Model with cloud-based automation for another product.
Outcome
The outcome successfully drove increased user traction and interest. By empowering users with intuitive geospatial analytics and near real-time insights, the solution enabled data-driven investment and resource planning and accelerated innovation.