User-Centered & Data-Driven
Design a sales-enabling tool, cutting quote time by 75%
2022
6 Months
Product Design
Case study on the impact of UX design, team collaboration and user feedback on the development of a product.
Context
Analyzer helps internal Sales Analysts simulate different tariff and battery options to find the best fit for a building. By inputting energy usage, tariffs, and battery details, the app estimates energy output, cost savings, and breakeven time.
Sales Analysts then use these insights to generate quote estimates and present clear, data-driven recommendations to building owners.
Problem
The current Sales Team's workflow is outdated and inefficient, involving multiple back-and-forth interactions and manual data migration across multiple program, leading to:
High risk of inaccuracies (e.g., copy-paste errors)
Inefficiencies in decision-making
Prolonged proposal timelines
UX was introduced for the first time to support the external launch of the product. However, there was no existing documentation, user workflow insights, or information architecture for the app. To address this, I prioritized key story points to ensure a structured and user-friendly foundation.
Approach
Analyzer was developed in an Agile environment, requiring a fast-paced, iterative approach. As the UX lead, I designed and facilitated the following process to address gaps, improve usability, and prepare for external launch:
User Research — Understanding the problem
📎 Interviewed 2 internal users to uncover workflow inefficiencies and validate pain points, ensuring design decisions were grounded in real user needs.
📎 Monitored the Slack help desk to capture real-time feedback and recurring issues, allowing for quick iterations.
📎 Facilitated stakeholder brainstorming sessions to align business goals with user needs.
Design Documentation – Establishing a UX Foundation
📎 Mapped out personas and workflows for internal and external Sales Analysts to clarify user roles and use cases.
📎 Documented existing workflows, gaps, and pain points, creating the first structured UX foundation for the product.
Wireframing & User Testing – Validating Solutions
📎 Designed a step-by-step framework to simplify assessments, ensuring clarity and usability.
📎 Prototyped and tested solutions in biweekly sprints, gathering insights to iterate efficiently.
📎 Developed and facilitated a structured testing plan, launching a Beta version with trusted partners to validate the external release.
Feedback, Product Strategy and Next Steps
📎 Documented and synthesized feedback, ensuring product management had clear, actionable insights.
📎 Hosted a Lean UX workshop to align the team on product impact and prioritize efforts, ensuring the next sprint was data-driven and user-centred.
Highlighted Findings
Gathering enough data to put into the system is the biggest issue
A new building might not have historical energy usage data
Data are sometimes hard to get from the utility
Different utility providers have different way of formatting their data, this can sometimes interfere with how Analyzer read the file
Users don't know what energy storage system they want, and want to try out multiple product and see the differences.
If there are 10 systems that the users want to simulate, the process can be repetitive and time consuming, as each simulation takes about 5 mins to complete running
Facilitating Alignment in a Tight Timeline
With three weeks until the roadmap deadline, the Analyzer team faced misalignment, and the PM struggled to prioritize competing internal and external requests.
To streamline decisions, I led a Lean UX workshop aligning business needs, user goals, and development effort to provided clarity, enabling the PM to make informed, strategic decisions. The sessions were participated by the Product Manager, Product Marketer, Front-end Developer and the engineering team.
This resulted in a clear analysis of:
✏️ What features to implement and why
✏️ Who benefits from each feature
✏️ Business impact and development effort
UX Impacts on the product in 6 months
Increased Efficiency and Reduce Errors
📎 300% increase in task completion rate
📎 Reduce the time it takes to complete an estimate by 75% to about 20 mins per project
📎 Significantly fewer data errors, making reports in the Slack help desk a rarity
Stronger Customer Trust & Team Buy-In
📎 Engaging users in product development and enhancements built trust, proving the tool's reliability and accuracy
📎 The development process became more data-driven and objective, increasing internal team buy-in
Hailey
Nguyen
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