Hyperlocal Grocery Price Intelligence from Blinkit, Zepto, BigBasket

Introduction

Grocery prices vary dramatically across neighborhoods, cities, and platforms. For brands, Q-commerce players, and analytics firms, hyperlocal price visibility is essential to optimize pricing strategies, manage regional promotions, and align inventory levels with demand. iWeb Data Scraping was engaged by a leading FMCG insights company to extract daily grocery prices from Blinkit , Zepto, and BigBasket at the pin code level, covering over 30 Indian cities.

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objectives

Objectives:

  • Scrape product pricing for over 5,000 SKUs across grocery, dairy, snacks, and beverages.
  • Capture price variations by pin code, platform, and product pack size.
  • Deliver real-time datasets for price parity and visibility monitoring.
  • Enable dashboards for trade marketing and supply chain teams.

    • Challenges:

    iWeb Data Scraping deployed a customized scraping API that collected structured data from top-performing restaurants on Zomato and Swiggy. Our Food Delivery Data Scraping Services captured key parameters by city, cuisine, and popularity, enabling precise analysis of local markets.

    What We Scraped:

    • Each platform uses geo-fencing and dynamic catalogues per location.
    • Product SKUs differ slightly by brand-pack-size combinations.
    • Zepto and Blinkit frequently change product URLs and structure.

    Sample Comparative Insights (Delhi vs Hyderabad):

    the-challenges
    iWeb Data Scraping’s Strategy:

    iWeb Data Scraping’s Strategy:

    1. Pin Code-Based Session Simulation:

    • Automated session switching to simulate over 100+ pin codes daily.
    • Used GPS coordinates and address selectors to localize each scrape.

    2. Cross-Platform Product Matching:

    • Applied fuzzy logic to align SKU descriptions across Blinkit, Zepto, BigBasket .
    • Grouped products by brand, quantity, and packaging.

    3. Daily Price Extraction Pipeline:

    • Extracted fields: Product Name & Brand , Quantity / Pack Size , MRP (if shown) , Offer/Discount % , Availability (In stock / Out of stock) , Pin Code

    Sample Output Table:

    Platform Product Name Brand size Price MRP Discount Pincode Availability Date
    Blinkit Toned Milk 1L Amul 1L ₹58 ₹62 6.4% 110001 In Stock 2025-06-06
    Zepto Toned Milk 1L Amul 1L ₹60 ₹62 3.2% 110001 In Stock 2025-06-06
    BigBasket Toned Milk 1L Amul 1L ₹57 ₹62 8.0% 110001 In Stock 2025-06-06

    Results:

    Tracked Over 150,000 Price Points Daily

    • Across 5,000+ SKUs and 100+ pin codes.

    Detected Price Variance of 12–20% Across Platforms

    • Enabled client to trigger price parity campaigns by region.

    Improved Trade Promo ROI by 18%

    • Data used to realign city-wise discounting and in-app offers.

    Enabled Smart Replenishment Strategy

    • Integrated OOS data into restocking forecast models.
    result
    Dashboards Delivered

    Dashboards Delivered:

    • Pin Code-Level Price Heatmap
    • SKU-Wise Platform Comparison Table
    • OOS Tracker by Region & Platform
    • Daily Discount Leaderboard

    Technology Stack:

    • Languages: Python, JavaScript
    • Scraping Tools: Selenium, Playwright
    • Database: MongoDB, PostgreSQL
    • Delivery: REST API, S3 Buckets, Excel Reports
    • Visualization: Power BI, Tableau, Google Data Studio
    Technology Stack
    Why-iWeb-Data-Scraping

    Why iWeb Data Scraping?

    • India-focused hyperlocal scraping experience
    • Daily retail intelligence at pin code granularity
    • Trusted by FMCG brands, retail analysts, and Q-commerce firms
    • Scalable infrastructure and smart SKU-matching engine

    Client Testimonial

    "Working with iWeb Data Scraping gave our team the clarity and edge we needed. We didn’t just guess—we knew what our customers wanted in each city. The data on cuisines, pricing, and delivery patterns helped us customize every part of the launch. It’s the difference between launching and launching smart."

    – Head of Strategy, Cloud Kitchen Brand

    Next Steps:

    • Expand coverage to include Instamart and JioMart.
    • Add delivery ETA and serviceability metrics per pin code.
    • Include visual elements like banner offer extraction and flyer tracking.
    Next Steps:

    Conclusion

    Hyperlocal grocery price monitoring is no longer optional—it's essential. With iWeb Data Scraping’s robust, pin code-based extraction engine, brands can monitor pricing, availability, and discount trends across Blinkit, Zepto, and BigBasket with precision and scale.

    Let’s Talk About Product

    What's Next?

    We start by signing a Non-Disclosure Agreement (NDA) to protect your ideas.

    Our team will analyze your needs to understand what you want.

    You'll get a clear and detailed project outline showing how we'll work together.

    We'll take care of the project, allowing you to focus on growing your business.