Propeller
Analysis & management of geospatial data
The Propeller Platform
Propeller is an end-to-end solution that enables users to track, map, and measure their worksites in industries such as construction, mining and landfill. Integrating hardware, software and data processing solutions, Propeller users can capture, process, and visualize progress and productivity across their worksites.
The platform was positioned in a broad (and rapidly evolving) ecosystem of survey data and BIM software. Understanding the role that Propeller hardware and software played in customer workflows was key to understanding how to make sure the platform fit usefully in to their day to day needs.
Exploring customer problems
Customer problems and innovation opportunities were identified via multiple channels including feedback coming via Sales and Customer Service teams, and through a combination of site visits and remote interviews. The product design team aimed to understand the day-to-day workflows of customers, and how both Propeller and competitor tools were integrated into those workflows.
Data was analysed using multiple methods and formats to present key insights and themes, visualise customer experiences with journey maps, develop primary personas and to identify pain points and opportunities.
In-platform channels - including platform analytics and product marketing software integrations such as AppCues and Typeform - allowed us to target and understand current user behaviours then use the data to inform feature improvement.
Design Process
The design process at Propeller incorporated a full range of design skills and practices to define and deliver improvements to both current software and hardware solutions, and to identify and act on opportunities for innovation in the market, including: planning and conducting research with customers to uncover needs and opportunities; facilitating ideation, synthesis and mapping workshops to define MVP solutions; co-ordinating usability evaluations of company and competitor software; planning and conducting usability testing of new features; collaborating with analytics teams to facilitate lean UX methodologies and data-driven decision making; and managing and advocating for design processes and workflows.
Analysis of customer research helped to inform design strategies and product roadmaps, with projects being organised into themes and OKRs.
Insights on customer needs and workflows also informed the process of story mapping which helped us to both map the user experience through descriptions of core user activities and tasks and to define the MVP through prioritisation of stories. These verbal definitions provided a robust framework for the ideation activities that followed.
Exploring Solutions
With a defined MVP, the product design team would move into a phase of ideation using sketching and rapid prototyping methods to collaborate with product and engineering on the development of concepts that we could test with customers for early validation of the value proposition.
Early validation of concepts enabled engineering efforts to begin sooner with development of working software that could utilize actual customer data to further demonstrate the value of the solution to customers while also giving us valuable feedback from actual, daily use of the features via alpha and beta programs.
Delivery
With validation of the prototype, design moved into production. Data and insights gained from usability testing helped us to confidently refine and improve the designs for production and release, while providing a roadmap for future enhancements. Product designers paired with engineers to implement interactions and styles.
