
Overview
The increasing adoption of electric vehicles (EVs) presents a significant challenge for parking lot operators who must efficiently manage energy consumption while ensuring reliable and cost-effective charging services.
The brief I set out with on this journey is to characterize a digital platform that will help managers streamline and optimize the management of electric vehicle (EV) charging within organizations.
Market and Target Audience: Organizations managing electric vehicle fleets face increasing challenges related to peak-hour electricity costs, station availability, and charging efficiency. Optimizing user charging habits has become critical to reducing operational costs and improving sustainability efforts.
Objective: This project explores how data-driven tools can help operators manage EV infrastructure efficiently and intuitively.
Problem Statement
Managing EV charging at scale is complex, requiring real-time monitoring of station availability, power consumption, and ongoing maintenance.
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Electricity demand fluctuates throughout the day. Without smart load balancing, peak usage can lead to excessive costs and inefficient power distribution
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Dynamic electricity tariffs offer cost-saving opportunities, but operators often lack the tools needed to effectively optimize charging schedules
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Managers are already juggling multiple responsibilities. Without the support of data analytics and AI-driven insights, making timely and efficient decisions becomes nearly impossible
Benchmark Analysis
Competitive Landscape of EV Charging Management Platforms
I compared three key platforms offering EV Charging Management Systems (CSMS) as SaaS solutions. Each platform brings a unique strength—GreenFlux scales, Driivz analyzes, ChargeLab simplifies—but all leave room for UX and personalization improvements.
SWOT
User Research
Personas
To better understand the challenges of managing EV charging at scale, I interviewed facility and operations managers responsible for parking lots, buildings, and energy systems. I asked them about their responsibilities, the challenges they face in managing charging stations., I wanted to get to know their day-to-day operations: How they track? What it requires of them? How they deal with the electric company’s changing rates? and What tools they lack?
After interviewing the selected managers, I built three personas to help me further characterize the product.

Michal Levi
Operations Manager, Ramat Aviv Mall
Oversees daily operations, including parking lot maintenance and EV charging station functionality.

David Cohen
VP of Operations, Migdal Insurance.
Responsible for managing multiple buildings, including electrical infrastructure and EV charging logistics.

Yossi Biton
Operations Manager, Property management Firm
Leads maintenance for a portfolio of high-rise buildings, coordinates service teams, and oversees energy efficiency initiatives.
You are invited to get to know them a little more in depth:
Empaty Maps
To better understand our users' experiences, I created empathy maps for each persona. This tool helped me capture what users see, hear, think, feel, say, and do in their daily work, allowing me to uncover hidden frustrations and emotional drivers that guided the design decisions.
User Journy
To characterize the User journey, I chose to continue with one persona: David Cohen.
David has the greatest responsibility: on the one hand, the free charging service is a benefit given to the company's employees, on the other hand, he must be careful not to exceed a budget defined by the company he works for.
I chose a common scenario from David's daily life: a new employee starts working at the company. David needs to add her as a user of the system, find her a charging station that will not burden electricity costs but will also be accessible to her when she needs it, set up alerts for the new employee, and in general, monitor and report to management once a quarter.
HMW
How might we support David in making faster, data-driven decisions about EV charging performance and energy costs?
User Flow Chart
I chose a common scenario from David's daily life: a new employee starts working at the company. David needs to add her as a user of the system, find her a charging station that will not burden electricity costs but will also be accessible to her when she needs it, set up alerts for the new employee, and in general, monitor and report to management once a quarter. This flow ensures new employee setup is efficient and monitored.

Prototyping
Design Principles
Early Layout Exploration
During the screen design process for David, I focused on aligning each layout with the needs identified in the customer journey. The goal was to make key information — especially KPIs — instantly accessible and easy to understand. In every screen, I integrated AI-powered insights to help David quickly discover trends, understand usage patterns, and take informed action with confidence.

system architecture
This system architecture diagram maps the EVR platform modules by user persona, feature scope, and external integrations. At this stage, only David's dashboard and related components were fully designed. The structure lays a clear foundation for expanding future modules for additional personas (Michal and Yossi), as shown at the top.

UXI Design
This section showcases selected interface designs from the EVR platform. Each screen was crafted to support operational decision-making through data clarity, smart visualizations, and contextual AI insights.
The design emphasizes simplicity, speed, and scalability—ensuring that users like David can quickly understand key metrics, take action, and maintain efficient control over their EV charging infrastructure.
Design System

Reflection On The Project
I’ll admit — when I started this project, I couldn’t tell a kilowatt from a charging socket.
The world of EV infrastructure was totally foreign to me. But curiosity (and a healthy amount of Googling) pulled me in. I created personas, ran through scenarios, and yes — even had long, thoughtful chats with ChatGPT pretending to be frustrated operations managers named Michal, Yossi, and David.
Key takeaways and reflections:
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Leveraging AI in UX research
ChatGPT wasn’t just a shortcut — it helped simulate realistic user conversations, surface meaningful needs, and inform product thinking from the earliest research stages. -
Designing for clarity and action
One major insight: David doesn’t need more data — he needs clear, actionable insights. That led me to focus on smart filtering, data visualization, and AI-powered recommendations within a clean, user-friendly dashboard. -
System-level thinking in product design
I enjoyed stepping into the mindset of developers, product managers, and users — exploring the product from multiple angles, mapping user journeys, and shaping complex workflows into intuitive user flows. -
UX as the connector between logic and people
This project deepened my appreciation for how thoughtful UX design bridges system logic and real human needs — creating one cohesive and useful experience. -
Exploring modularity and scalability
If I had more time, I would have pushed the system’s modularity even further — adapting it more precisely to the workflows and digital behaviors of users like Michal and Yossi. Balancing scalability, flexibility, and simplicity is exactly the kind of challenge I love.