Smart Energy Management Platform

AI-powered energy platform integrating real-time utility pricing with smart home devices.

Product Lead — Discovery, User Research, PRDs, Go-to-Market Planning

Figma

User Research

Data Analysis

PRDs

Market Research

20-30%

Potential cost savings

B2B & B2C

Market segments

Complete

MVP defined

The Problem

Consumers and businesses lacked tools to optimize energy consumption based on real-time utility pricing, leading to unnecessary costs and inefficient energy usage.

The Solution

Led product discovery, user research, and requirements definition for an AI-powered energy platform. Defined PRDs, user stories, and MVP scope for both B2B and B2C use cases. Conducted data analysis to validate potential cost savings.

Product Artifacts

PRD

Product Requirements

Coming soon

MRD

Market Requirements

Coming soon

Wireframes

Figma Designs

View

Case Study

Context

Consumers and businesses lack tools to optimize energy usage based on real-time pricing.
Smart home devices exist but aren't integrated with utility pricing intelligence.
Rising energy costs create demand for AI-powered consumption optimization.

Decision

Lead product discovery to validate market opportunity for both B2B and B2C segments.
Define MVP scope that demonstrates core value proposition: automated cost savings.
Prioritize user research to understand different needs of residential vs. commercial users.

Execution

Conducted extensive user research across residential and commercial energy consumers.
Created detailed PRDs, user stories, and MVP scope documentation.
Performed competitive analysis and market sizing for go-to-market planning.
Defined product requirements for real-time utility pricing integration.
Collaborated with cross-functional stakeholders on technical feasibility.

Outcome

Validated potential cost savings of 20-30% through data analysis.
Defined clear market segments: B2B (commercial buildings) and B2C (smart homes).
Created comprehensive product roadmap from MVP to full platform.
Established partnership requirements with utility data providers.

Learnings

B2B and B2C segments require fundamentally different product approaches and pricing models.
Early market validation prevents building features users don't need.
Data partnerships are critical dependencies that must be validated early.

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