A leading FMCG brand engaged Actowiz Solutions to build a structured, repeatable weekly monitoring programme tracking SKU-level availability across four major Q-Commerce and online-grocery platforms — Flipkart Minutes, Flipkart Grocery, JioMart, and Milk Basket.

Industry

Q-Commerce / Online Grocery

Region

India (multi-city)

Duration

Weekly (recurring)

Platforms Tracked

Weekly

Monitoring Cadence

4–5 Days

Turnaround Time

450+

SKUs Tracked

Contact Sales

Client Overview

The project required pincode-level and locality-level granularity across multiple Indian cities, enabling the client to understand assortment penetration, regional stock gaps, and platform-wise distribution strength on a week-on-week basis.

The Challenge

No centralised view of which SKUs were in stock or out of stock across platforms and cities in any given week.
Inability to measure assortment penetration — how many products were actively listed and available per platform across pincodes.
Limited insight into platform-specific distribution strengths, making it hard to spot where competitors had an edge.
Manual tracking was slow, inconsistent across territories, and could not cover the required scale of pincodes and localities.
No standardised dataset format, making downstream analytics and BI reporting error-prone.

The Solution by Actowiz Solutions

Actowiz deployed a fully automated SKU-availability tracking framework operating across all four platforms simultaneously, engineered for each platform's structural and geo-location requirements.

Platform Coverage & Extraction Architecture

Flipkart Minutes — pincode-based location set dynamically per cycle; availability captured at PDP level.
Flipkart Grocery — separate storefront with independent SKU listings; pincode-level availability tracked independently.
JioMart — location-based inventory by pincode and city mapping; full product URL and EAN captured per SKU.
Milk Basket — subscription-model platform with locality-level delivery zones; locality column added for granular reporting.

Input Parameters & Location Configuration

Input Dimension	Description
SKU List	Client product identifiers mapped to each platform's catalogue system
Pincode Coverage	Approved Indian pincodes per city, applied to each platform's location filter
City Coverage	Approved metro and Tier-2 cities forming the tracking boundary
Platform List	Flipkart Minutes, Flipkart Grocery, JioMart, Milk Basket

Data Attributes Extracted

Attribute	Description	Category
ID	Unique record identifier per extraction row	Record
SKU	Product Stock Keeping Unit identifier	Product
Product Name	Title as displayed on the platform	Product
Brand	Product brand name	Product
URL	Direct product page URL	Product
EAN Code	Barcode identifier	Product
Stock Availability Status	In-Stock / Out-of-Stock as shown	Availability
Platform	Source platform	Platform
Pincode	6-digit Indian pincode	Location
City / State / Locality	Location breakdown	Location
Scrape Date	Date of the weekly extraction cycle	Tracking

Quality Assurance & Validation

Validation Check	Rule Applied
Mandatory field completeness	No required column may be blank in the final dataset
Pincode validation	Only valid 6-digit Indian pincodes, restricted to the approved list
SKU validation	Each record must carry a populated, correctly mapped SKU
URL validation	All product URLs verified as valid and accessible
EAN code validation	Numeric EANs validated against EAN-8 / EAN-13 length rules
Availability status validation	Status values match onsite product status at extraction time
Duplicate prevention	No duplicate SKU–Platform–Pincode–Scrape Date combinations
Platform validation	Platform column restricted to the four approved values
Schema validation	Final output aligned to approved headers and data types
Pincode filtering rule	Reports shared only for pincodes with at least one available SKU

Sample Output (Illustrative)

SKU / Product	Platform / Location	Availability
SKU-1042 — Whole Wheat Atta 5Kg (Fortune)	Flipkart Grocery — Mumbai 400001, Colaba	In Stock
SKU-1042 — Whole Wheat Atta 5Kg (Fortune)	JioMart — Mumbai 400001, Colaba	Out of Stock
SKU-2187 — Refined Oil 1L (Saffola)	Flipkart Minutes — Pune 411001, Shivaji Nagar	In Stock
SKU-2187 — Refined Oil 1L (Saffola)	Milk Basket — Pune 411001, Shivaji Nagar	In Stock
SKU-3305 — Toned Milk 500ml (Amul)	JioMart — Delhi 110001, Connaught Place	In Stock

Technical Approach

Dynamic location injection. Pincode and city parameters applied at session level per platform for geolocation-accurate results.
Anti-bot resilience. Adaptive throttling, IP rotation, and browser-fingerprint management for stable access across the weekly cycle.
SKU matching. Client SKU identifiers mapped to platform-native product identifiers for accurate cross-platform alignment.
Structured output pipeline. Raw output passed through an ETL layer applying schema enforcement, null handling ("N/A"), deduplication, and EAN validation.
QA automation. Automated scripts run pre-delivery checks across all validation dimensions, with exceptions flagged for manual review.

Results & Business Impact

Availability visibility. End-to-end weekly visibility into in-stock / out-of-stock status across all four platforms and every tracked pincode — a capability that did not exist before. SKU-level granularity triggered direct supply-chain corrective actions.
Assortment penetration analysis. City- and locality-level data enabled platform-wise penetration scoring and surfaced regional gaps to prioritise replenishment.
Competitive benchmarking. Cross-platform availability comparison showed which platforms stocked more of the catalogue; consistency scores informed key-account negotiations.
Operational efficiency. Weekly delivery within 4–5 working days removed manual tracking; a standardised schema loaded directly into BI without transformation.

Project at a Glance

Metric	Value
Industry	Q-Commerce / Online Grocery
Client Geography	India — multi-city, multi-pincode
Platforms	Flipkart Minutes, Flipkart Grocery, JioMart, Milk Basket
Tracking Scope	SKU-level availability status
Output Format	Excel (.xlsx) and CSV (.csv)
Delivery Frequency	Weekly recurring
Turnaround	4 to 5 working days
Data State	Clean, validated, deduplicated, analysis-ready

Client Feedback

"Actowiz Solutions gave us unprecedented visibility into our product availability across India's leading Q-Commerce platforms. Their automated tracking framework helped us identify regional stock gaps, improve assortment penetration, and make faster supply chain decisions. The accuracy, consistency, and weekly delivery of actionable data have become an essential part of our retail intelligence strategy."

— Head of Modern Trade & E-Commerce, Leading FMCG Brand

Need a custom data pipeline for your platform?

Actowiz Solutions designs custom, large-scale scraping, extraction, and API-delivery pipelines with rigorous QA. Visit actowizsolutions.com to discuss your data requirement.

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