SERO

This question became the driving force behind the "Energy Insights" feature for the Sero Life App. Many users lacked real-time visibility into their solar energy generation, battery storage, and home demand, leading to confusion and distrust in their energy system.

Sero’s existing paper-based energy statements failed to provide the granular insights users needed to understand whether their solar panels and batteries were working as expected. This uncertainty led to frustration and an increase in customer service inquiries, with users questioning:

• How much energy is my home actually generating?
• Is my battery storing and using energy efficiently?
• Am I really reducing my grid dependency and carbon footprint?

With no real-time feedback loop, users often assumed their solar system wasn’t performing optimally, driving unnecessary support calls and reducing confidence in the technology. The challenge was clear:

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Deliver an intuitive, data-driven solution that provides users with real-time and historical insights into their solar energy generation, battery storage, and home demand—while also reducing support costs for the business.

To build a solution grounded in real user needs, I started by collaborating with Sero’s customer service team to analyse customer complaints and support calls. I identified recurring frustrations, such as a lack of real-time solar tracking, uncertainty around battery performance, and no way to measure carbon savings. Users wanted more than static numbers—they needed clear insights to help them trust and optimise their solar energy system.

Key Discovery Activities:

Affinity Mapping:
I categorised and ranked user complaints into actionable themes, revealing key priorities such as real-time solar generation tracking, battery health insights, and historical comparisons to assess long-term efficiency.

Reviewing Existing Statements:
‍Analysing the limitations of the paper-based energy reports highlighted a lack of clarity and personalisation, leaving users uncertain about whether their solar system was working efficiently. Many users assumed their battery wasn’t storing or using energy correctly due to the absence of real-time performance insights.

These findings formed the foundation for our solution: a feature that would transform static solar data into actionable insights, allowing users to confidently monitor their energy system through an intuitive interface.

With the user pain points mapped out, I facilitated ideation workshops with cross-functional teams, including developers, data scientists, and customer service representatives. These sessions focused on exploring potential solutions that would allow users to visualise their solar generation, battery storage, and energy consumption over time in a simple, actionable format.

‍We explored a variety of ideas, from real-time solar generation tracking to personalised insights that help users build confidence in their renewable energy system. To focus our efforts, we prioritised features based on user impact and technical feasibility, ensuring we delivered the most value in the first iteration. Early sketches and rough wireframes allowed us to test different layouts and information hierarchies, setting the stage for detailed design work.

Key priorities included:

• Live Solar Generation & Home Energy Demand: Ensuring users could see real-time insights into how much solar energy they were generating versus how much their home was consuming.
• Battery Health & Performance: Providing clarity on how much charge was stored and when the battery was being used.
• Historical Solar Insights & Carbon Impact: Giving users a way to track their solar performance over time and understand their environmental savings.
• Improving Trust in the System: Addressing skepticism by providing clear feedback on solar panel & battery performance to reassure users that their system is working.

‍While some initial ideas, such as predictive energy forecasting and tailored energy-saving recommendations, were identified as valuable, they required advanced data science models that weren’t feasible for the first release. These insights helped us define the minimum viable experience while laying the groundwork for future enhancements.

Early design exploration:

Before diving into detailed wireframes, we explored various ways to present solar generation, storage, and usage data in a way that was both engaging and actionable for users. The goal was to ensure the information was intuitive, built trust in solar performance, and aligned with technical feasibility.

Real-Time Solar Insights:
Understanding real-time solar generation and energy usage was a core priority. We explored different ways to visually communicate this data, ensuring users had immediate access to meaningful insights.

• Live Solar Generation Tracking: Users could monitor how much energy their solar panels were generating at any given moment.
• Home Energy Demand vs. Solar Supply: A comparative view helped users understand how much of their home’s energy demand was being met by solar generation.
• Battery Storage Insights: Users could see how much charge their battery stored, reinforcing trust that their system was working as expected.

Historical Energy Trends:
We investigated different ways to help users track their solar generation and energy consumption over time.

• Daily, Weekly, and Monthly Comparisons: Allowing users to toggle between different time views to spot trends.
• Solar destinations: Showing where the solar energy was going
• Carbon Impact Insights: Helping users see the environmental benefits of their solar panels in terms of CO₂ reductions.

Building Trust in Solar Performance:
A major challenge identified during research was user skepticism around whether their solar panels and batteries were working correctly. To address this, we explored ways to provide reassurance:

• Contextual Explanations: Tooltips and modals that provided definitions and guidance on how to interpret energy data and status indicators to ensure they understood if their system was live and working
• Tips and tricks and blogs: Helping users understand their solar and tailoring insights to them directly
• Cost & Savings Indicators: Initial explorations included features such as projected cost savings from solar, though this was later deprioritised due to data limitations.

Early Sketches & Wireframes:
Through low-fidelity sketches, we tested different information hierarchies, navigation structures, and layout ideas to determine the most effective way to present these insights. This phase allowed us to explore a range of possibilities while staying mindful of technical constraints.

Armed with insights from the ideation phase and our key features for phase one, I began developing low-fidelity wireframes to test and refine potential layouts for the Energy Insights feature. The goal was to create an interface that simplified complex data, making it both accessible and actionable for users based on the features outlined in the ideation phase.

‍The initial wireframes focused on testing the overall structure and flow of the Energy Insights feature. During user testing and stakeholder feedback sessions.

Several key challenges and insights emerged:

• Graph Layout Challenges: Users struggled to interpret the provided energy data in the initial graph layouts. To address this, I created multiple graph types—such as pie charts, bar graphs, and line charts—to test which best communicated the information effectively.
• Day view functionality: The 'day view' was slightly confusing to users as it effectively displayed live energy usage.
Feedback indicated the need for clearer labelling and context, such as breaking out day view into its own live view section
• Data Science Constraints: Stakeholder feedback revealed that providing a breakdown of where energy was being used would not be feasible in the first iteration. The data science team experienced delays in completing the algorithm needed to split energy consumption data by category. As a result, we pivoted to prioritising battery health and charge level insights, which were identified as a critical gap in early user testing.
• Tips and Tricks Limitations: Tailored energy-saving tips and recommendations also had to be deprioritised due to data constraints. Instead, we focused on delivering actionable, easy-to-interpret data that users could independently leverage.

Based on these combined insights, I explored alternative layouts and solutions that directly addressed user feedback and stakeholder constraints. The focus was on improving clarity, usability, and providing actionable insights, while balancing technical feasibility. This iterative process set the foundation for the high-fidelity designs, which refined and built upon these concepts to deliver an intuitive and impactful user experience.

With the foundational structure and core features validated in the Mid-fidelity phase, the high-fidelity design process focused on refining these concepts into a polished, user-friendly solution. By addressing user feedback on graph layouts, day view clarity, and the inclusion of battery health insights, the high-fidelity designs aimed to deliver a seamless and intuitive experience. This phase also introduced visual enhancements and micro-interactions to align with Sero’s branding and elevate the overall usability.
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Key Refinements in High-Fidelity Designs:

• Graph Layouts: Bar graphs were selected as the primary visualisations based on user preference for ease of interpretation. Pie charts were included for energy distribution, offering a quick snapshot of how energy was generated and consumed. Interactive tooltips were added to graphs to provide contextual explanations without overwhelming users
• Live View Clarity: A "Live Usage" label and timestamp were introduced to eliminate confusion about real-time data in the day view. Smooth animations on graphs reinforced the live data concept, enhancing user understanding.
• Battery Health Integration: A dedicated battery health and charge indicator was included as a core feature, addressing the lack of energy breakdown data in this iteration. Progress bars and clear icons were used to make this information easy to interpret at a glance.
• Visual and Interaction Enhancements: High-fidelity designs adopted a modern, accessible colour palette, ensuring visual clarity while aligning with Sero’s branding. Subtle micro-interactions, such as hover effects and smooth transitions, were added to improve the overall experience and make navigation intuitive.

After completing the high-fidelity designs for the Energy Insights feature, testing focused on validating key interactions, understanding user comprehension, and ensuring the solution addressed both user and business objectives. Testing included a combination of internal team reviews and external usability testing with a small sample of target users using a fully fledged prototype.

Testing Process:

• Internal Testing: Conducted with cross-functional team members, including developers, data scientists, and customer service representatives. The focus was on ensuring technical feasibility and verifying that the designs aligned with business goals. Feedback emphasised the need for consistent labelling and clear contextual guidance, particularly around the live and historical views.
• External Usability Testing: Conducted task-based testing with a sample group of users who represented typical Sero customers. Key tasks included switching between live and historical views, interpreting solar energy data, and understanding battery health indicators.

Key Insights from Testing:

• Live vs. Historical Views: Users appreciated the separation between live and historical data but needed clearer guidance on how the data was updated. To address this, a “Live Usage” label and a timestamp were prominently added to the live view, while the historical view included navigation for daily, weekly, and monthly summaries.
• Energy Distribution Clarity: The “Solar Destinations” pie chart was well-received as a high-level summary of how energy was used, but some users requested more detailed breakdowns. Due to data constraints, this level of detail was deprioritised for the first iteration but considered for future updates.
• Battery Health Overview: Users praised the battery health feature, with its clear percentage indicator and charging status. Feedback highlighted its value as a critical part of understanding home energy systems, reinforcing its importance in the design.
• Contextual Guidance: New users found some widgets overwhelming initially. To address this, modal overlays with contextual tips were implemented to explain key metrics like “Total Home Demand” and “Battery Storage.”

Following the testing and validation phase, I collaborated closely with the development team to ensure a seamless implementation of the Energy Insights feature. This included creating a detailed design handoff, addressing questions about interactions and layouts, and validating the final build to ensure consistency with the high-fidelity designs. By maintaining open communication with developers, we were able to deliver a feature that remained true to the original vision and user needs.