- Team
- Senior UX designer (myself)
- Junior UX design
- Software developer
- Stakeholders
- Product manager
- Techniques
- Mockups
- Prototypes
- Analytics
- Competitive research
- Usability testing
- Design sprints
Objective
Based on previous research, consumers have expressed a strong desire to view their energy usage data. However, the current state of the app has led to confusion and difficulty in understanding this information. Our objective is to create an intuitive mobile energy usage experience that addresses these concerns and delivers a seamless experience for users.
Approach
To align with the developer sprints, we implemented the learning loop method, a lean UX approach involving iterative cycles of designing, testing, and learning to continuously experiment and refine user-centered products. By testing with real users and incorporating feedback, we can create more user-friendly products.
During the learning phase of our process, we conducted a comprehensive examination of the app's design system, identifying limitations that hindered the user experience. Through rigorous user testing, we discovered that users were struggling to locate their highest and lowest usage dates. Based on this insight, we developed an innovative design solution that highlights these dates directly on the bar data display, offering a more intuitive and contextualized data visualization.
Results
We then tested the proposed design. Users found their chart easy to read and were able to identify their least and most usage days without any problems. The comprehension of usage data was well-received by our customers. However, the testing showed that some customers were having difficulty navigating from the overview screen to the usage screen.
Additionally, this round of testing provided valuable feature recommendations. Using an impact-effort matrix, we grouped impactful features desired by users into a roadmap. This resulted in a prioritized list of data-driven enhancements, categorized as 'Now' and 'Later,' providing the product team with clear guidance.
Outcomes
Further testing is needed to address the issue of customers taking too long to locate the usage section. One hypothesis suggests that improving the tab icon's recognizability for consumers could help resolve this problem.
Moreover, a significant portion of our consumer base consists of individuals with solar panels. Analytics have revealed that solar panel owners check their usage significantly more often than non-solar consumers. Therefore, it is important to explore design solutions that can contextually present solar energy data alongside other information.
I propose a comprehensive approach to optimizing our solutions through strategic planning and prioritization, specifically targeting the features located in the High Impact & High Effort quadrant of the Impact-Effort Matrix. A great starting point would be Planning Activities.
To begin, we should conduct a detailed analysis, thoroughly examining the features in the High Impact & High Effort quadrant. This analysis will involve assessing their requirements, identifying challenges, and exploring potential solutions.
Next, we need to engage with stakeholders to gather valuable insights, identify priorities, and align the planning process with both organizational goals and user needs. Their input will be crucial in shaping the direction of our optimization efforts.
Lastly, we must assess the feasibility of the proposed solutions. This will involve conducting a rigorous examination of technical considerations, financial implications, and resource constraints. By carefully evaluating the feasibility, we can ensure that the proposed solutions are realistic and viable.
By implementing this comprehensive approach, we can effectively prioritize and address the features in the High Impact & High Effort quadrant, ultimately optimizing our solutions to maximize their impact and benefit our organization and users alike.
