How Actowiz Solutions Built a Private API POC for Blinkit, Zepto & Instamart

introduction

2.8 Million+

SKU-level data points refreshed weekly

600+

Store locations monitored across cities

3 Platforms Unified

Blinkit, Zepto, Instamart

Plan

Enterprise Premium – Private API Integration

Industry

Retail, FMCG, Q-commerce Data

Our client

A global FMCG insights company working with top brands to track consumption trends across India. Their analytics teams rely on real-time price, stock, and assortment data from Blinkit, Zepto, and Instamart to optimize promotions, packaging, and competitive pricing.

As Q-commerce platforms update prices every 20–40 minutes, the client needed live product feeds, not slow or inconsistent crawlers.

The Challenge

The client previously attempted:

• Basic HTML scrapers
• Manual store sampling
• Static price monitoring tools

But these approaches repeatedly failed because:

Platforms use private APIs not visible in the browser

Most Q-commerce platforms rely on:

• encrypted API calls
• GraphQL operations
• device-level headers
• geolocation-bound tokens

Standard scrapers cannot access this data.

Prices and stock change too quickly

The client was missing:

• flash sales
• discount bursts
• demand-based availability
• store-level variability

leading to misleading analytics.

Their datasets weren't unified

Blinkit, Zepto, and Instamart each store:

• product IDs
• categories
• variants
• images
• attributes

in different schema formats, making aggregation painful.

Their previous vendor lacked flexibility

They experienced:

• slow support
• no custom logic
• hard-coded scripts
• no scaling beyond 50 stores

The client needed both POC speed and enterprise stability.

The Solution

Actowiz Solutions delivered a Private API POC Integration across Blinkit, Zepto, and Instamart — built exactly around the client's data workflow.

We engineered a customized pipeline offering:

Comprehensive coverage

Monitoring across 600+ stores and 20+ cities, capturing:

• price
• MRP
• discount %
• stock availability
• delivery ETA
• category mapping
• product variants

Real-time updates

Our system refreshes:

• Blinkit: every 10 minutes
• Zepto: every 12 minutes
• Instamart: every 15 minutes

New pricing events are processed instantly and pushed to the client through API/webhook.

Unified data schema

Actowiz normalized:

• product naming
• packaging sizes
• variants (500ml, 1L, multipack)
• brand identifiers

So all three platforms map into one clean dataset.

Custom-built POC engine

We reverse-engineered:

• Blinkit's JSON structure
• Zepto's GraphQL queries
• Instamart's microservices API

Using:

• device fingerprinting
• rotating mobile proxies
• token auto-refresh
• header signature replication

This allowed clean, stable access to store-level data.

Enterprise-grade monitoring

Automated alerts detect:

• sudden price hikes
• out-of-stock items
• new product launches
• category expansions

Dashboard-ready feeds were delivered directly to the client's BI tools.

The Impact

With Actowiz Solutions, the client now operates with real-time consumer intelligence across the fast-growing Q-commerce ecosystem.

They gained:

Live visibility across India

The brand can track SKU-level movements across hundreds of stores and regions.

Accurate, high-frequency data

Errors dropped by 92% compared to their previous vendor.

Faster decision-making

Their pricing, marketing, and supply chain teams now receive insights within 10 minutes, not hours.

Massive operational savings

The automated API removed:

• manual monitoring
• spreadsheet merging
• platform-by-platform scraping
• losses from outdated datasets

Better competitor benchmarking

Unified cross-platform comparisons made it easy to track:

• Blinkit vs Zepto
• Zepto vs Instamart
• price gaps
• discount depth
• city-wise trends

The POC succeeded so well that the client upgraded to a full enterprise subscription.