Project FlashCart
Strategic Dark Store Location Analysis & Hyperlocal Fulfillment Network Design for Kolkata Market Entry.
Executive Summary (60-Sec Brief)
Seed-funded quick-commerce startup needed to strategically deploy 5 dark stores in Kolkata with minimal cannibalization and low rental overhead.
A Weighted Location Score (WLS) model analyzing 12 candidate zones on density, target age cohorts, rent per sq ft, and competitor clusters.
5 key dark store nodes selected (Sector V, Ballygunge, New Town, Jadavpur, Shyambazar), unlocking 1.2M addressable customers with 15-min delivery coverage.
5
Dark Stores Planned
1.2M
Addressable Consumers
4.55
Top Location Score (Sec V)
1. Executive Summary
FlashCart is a quick-commerce startup preparing to launch 30-minute grocery and snack delivery in Kolkata. With limited initial capital, the founding team must select exactly five dark store locations that maximize customer coverage while minimizing cannibalization and rental cost.
This report applies a Weighted Location Score (WLS) model to 12 high-potential Kolkata zones, evaluating each on population density, target customer concentration, commercial rent, competitor proximity, and delivery radius overlap.
The analysis recommends a phased rollout starting with Salt Lake Sector V, Ballygunge, New Town, Jadavpur, and Shyambazar, capturing an estimated 1.2 million addressable consumers within 3 km delivery radii.
2. Problem Statement & Context
FlashCart aims to deliver daily essentials, snacks, and beverages within 30 minutes. Unlike metros with saturated q-commerce footprints, Kolkata presents a unique mix of high-density heritage zones, rapidly growing IT corridors, and affordable real estate.
The startup has secured seed funding for five dark stores (each ~1,500 sq ft) and must place them where:
- Population density justifies quick delivery demand.
- Target customers (18–40 age group, working professionals) are concentrated.
- Rental costs are manageable to extend cash runway.
- Competitor dark stores are not already saturating the zone.
- Delivery radius coverage minimizes blind spots.
3. Methodology & Scoring Model
The Weighted Location Score (WLS) model was built on five core criteria:
| Criteria | Weight | Rationale |
|---|---|---|
| Population Density (PD) | 30% | Higher density translates to higher order volumes per square km. |
| Target Customer Index (TCI) | 25% | Measures concentration of tech-savvy working professionals and students. |
| Commercial Rent (CR) | 20% | Inverted metric (lower rent = higher score) critical for unit runway. |
| Competitor Proximity (CP) | 15% | Avoids head-on saturation with entrenched legacy dark stores. |
| Delivery Radius Coverage (DRC) | 10% | Capacity to serve adjoining dense clusters without wasteful overlap. |
4. Phased Rollout Plan
Open in Sector V and Jadavpur covering 500k+ users.
Deploy New Town, Ballygunge, and Shyambazar for full metro reach.
Fine-tune SKU assortment and explore expansion to Behala / Dum Dum.
Table of Contents
6 min readNetwork Blueprint
Phase 1: Criteria Setup
Defined and weighted key evaluation metrics based on SME logistics capabilities.
Phase 2: Geospatial Analysis
Identified high-density residential zones and mapped competitor dark stores.
Phase 3: WLS Modeling
Scored 12 zones to isolate the 5 highest-performing locations.
Phase 4: Network Optimization
Simulated 10-15 minute drive-time polygons to ensure minimum overlap.
Project FlashCart Executive Summary
Project FlashCart is a strategic dark store location analysis and hyperlocal fulfillment network design for Kolkata market entry. Using a Weighted Location Score (WLS) model, five optimal dark store locations were identified: Salt Lake Sector V, New Town, Jadavpur, Ballygunge, and Shyambazar.