FMCG Quick Commerce Market Intelligence
Web ScrapingData AnalysisData Science Services

FMCG Quick Commerce Market Intelligence

We built a comprehensive market intelligence system for a leading Indian FMCG conglomerate to track 200+ SKUs across every serviceable pincode in India on three major quick commerce platforms, providing actionable insights for sales and distribution strategy.

Client

Indian FMCG Conglomerate

Industry

Fast-Moving Consumer Goods

Client Partner

A leading Indian FMCG conglomerate with hundreds of SKUs across multiple product categories nationwide

The Challenge

With India's rapid quick commerce expansion, the client had listed hundreds of SKUs across major players like Blinkit, Zepto, and Swiggy Instamart. However, they lacked a unified view of real-time product visibility, platform-wise coverage, and region-specific availability. Unlike typical engagements that focus on a few cities or key SKUs, the client wanted to track 200+ SKUs (including competition) across every serviceable pincode in India on three major quick commerce platforms. The objective wasn't just price and availability tracking—it was about extracting deep competitive and market intelligence to power decisions related to sales, distribution, and regional strategy.

Our Solution

Large-Scale Web Scraping Infrastructure

  • Engineered platform-specific crawlers optimized for pincode-level granularity, running across thousands of SKUs and regions.
  • Implemented parallel scraping architectures and distributed scheduling to manage load and ensure timely data capture across the country.

Data Lake + Semantic Layer Design

  • Consolidated the data into a structured repository with schema support for SKU, brand, pincode, platform, timestamp, availability, MRP, and selling price.
  • Built an abstraction layer for analytical queries and KPI calculation (availability %, penetration %, city-level product presence, etc.).

Advanced Availability & Penetration Analytics

  • Availability: Measured product visibility in each serviceable pincode.
  • Penetration: Calculated the ratio of the client's product availability across all operational pincodes on each platform.
  • Competition Mapping: Identified gaps where competitor SKUs were listed but client SKUs weren't—supporting geo-targeted sales strategies.
  • Platform Activity Mapping: Identified all pincodes where platforms were operational vs. non-operational—valuable for route-to-market planning.

Market Intelligence Dashboard

  • Delivered a dynamic dashboard to slice and dice data by Brand, SKU, Platform, State, City, Region, and Time Range.
  • Equipped client teams with automated alerts, benchmark comparisons, and trend charts to spot pricing inconsistencies or growth opportunities.

The Impact

Key MetricApprox. Improvement
Expansion Opportunities2,500+ pincodes identified
Improved Product Penetration~10% increase in 8 weeks
Faster Decision MakingFrom ~14 days to <24 hours
Manual Effort Reduction~70% decrease
Geo-targeted Action Plans35+ Tier 2/3 cities identified

The solution provided unprecedented visibility into the client's quick commerce footprint, revealing 2,500+ pincodes where competitor products were live but client SKUs were not. This intelligence led to a ~10% increase in product listings across serviceable pincodes over 8 weeks. The system mapped 9,000+ pincodes where platforms are inactive—helping refine the go-to-market strategy. Decision-making speed improved dramatically, with insight turnaround time reduced from ~14 days to less than 24 hours, while internal teams experienced a ~70% decrease in time spent on data collection and reporting. Most importantly, the system identified 35+ Tier 2/3 cities for focused sales expansion based on competitive presence analysis.

"The market intelligence dashboard has transformed our quick commerce strategy. The pincode-level visibility across platforms has revealed opportunities we didn't know existed and helped us close competitive gaps much faster."

Sales & Distribution Head

Indian FMCG Conglomerate

In a nutshell

We built an automated web scraping system that fetches data—like product price, availability, and discounts—from quick commerce platforms (Blinkit, Zepto, Swiggy Instamart) across every pincode in India. We then cleaned and structured this data into a centralized system and built an easy-to-use dashboard on top. This helps the client see where their products are showing up, where their competitors are active, and what their online shelf looks like in real-time—enabling smarter decisions at scale.

Technologies Used

PythonSeleniumAWSPostgreSQLAirflowPowerBI