Startup Expansion

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Quick Summary

Role: Senior Data Analyst & BI Developer
Industry: Startup Growth & Retail Expansion </aside>

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Live Links

🔗 Interactive Power BI Dashboard: Click Here
GitHub Repository (Data Processing & Analysis): Click Here </aside>

Executive Overview

A US-based startup approached me to support a critical expansion decision, as they lacked clarity on where to open new branches and how to allocate marketing investments effectively.

I developed a data-driven expansion analytics solution that evaluated store performance, regional demand, and marketing ROI, enabling leadership to confidently identify high-potential locations and optimize expansion strategy.

Why it mattered: Poor expansion decisions could lead to significant financial losses and wasted resources.
What changed (result): Data-driven location selection led to successful expansion, with the new branch becoming one of the top-performing locations in annual sales.

Interactive Demo

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Quick Walkthrough: From Raw Data to Business Impact ✨

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https://drive.google.com/file/d/15QV-LmI-ecoKoydLKYxAVhyuXZ376hXS/view?usp=sharing

The Business Challenge

What was broken / costly / risky?

The Solution & Strategic Approach

Methodology (thinking)

Goal definition: Identify the most profitable and high-potential locations for expansion based on performance and demand indicators.
Success metrics:
- Revenue growth in new locations
- Marketing ROI improvement
- Store performance consistency
Analytical approach: Comparative analysis between new and existing stores, regional performance evaluation, and ROI-driven decision modeling.
Validation plan: Cross-analysis of revenue, profit, and marketing spend across different locations to ensure decision reliability.

Execution (doing)

Data sources: Sales data, store performance metrics, marketing spend data across regions, cities, and stores
Modeling / transformations: Cleaned and structured multi-source data using Python and SQL to enable consistent performance comparison
Dashboard build: Developed an interactive Power BI dashboard with filters for regions, cities, and store types to support decision-making
Deployment / handover: Delivered a scalable analytics solution enabling leadership to explore expansion scenarios and optimize strategy

Measurable Impact

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Successful Expansion Decision — Identified high-performing regions for new store openings
Top-Performing New Branch — The selected location became one of the highest revenue-generating branches annually
Improved Marketing ROI — Optimized budget allocation across locations based on performance insights </aside>