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Retail

Building a Price Scraping and Tracking Solution for Retail Market Insights

For the competitive retail market, understanding price trends is critical for making informed business decisions. Our client wanted to gain a comprehensive view of product pricing across both online and offline channels for three major grocery retailers. The goal was to centralize this data in a single dashboard, allowing the business to monitor pricing patterns, spot opportunities, and react quickly to market changes.

Building a Price Scraping and Tracking Solution for Retail Market Insights

About the project

Industry
Retail

To stay competitive in a rapidly evolving grocery retail market, our client needed real-time insights on product pricing across online and offline channels. We built a powerful PriceTracker system that automates price scraping from competitor websites, integrates physical store price feeds, and centralizes the data into a dynamic dashboard. This solution empowers the client to spot pricing trends, compare channels, and make faster, data-driven decisions, reducing competitor reaction time from days to hours.

01

Challenge

Two-Fold Price Tracking Complexity

  1. Monitor Online Pricing: Scrape up-to-date product prices from competitor websites — even those designed to block bots.
  2. Integrate Offline Prices: Ingest and reconcile physical store prices provided via APIs from multiple branches.

This required a flexible and scalable platform that could handle large datasets, normalize varying data formats, and present insights in a unified dashboard.

02

Solution

A Unified Approach to Real-Time Price Intelligence

We designed and implemented a robust PriceTracker system, focusing on four major components:

1. Web Scraping Pipeline

A dedicated scraper for each retailer was built with:

  • Headless browser automation for dynamic HTML rendering
  • Product mapping using SKU and fuzzy string matching
  • Scheduled scraping to balance frequency and resource usage

2. Offline Price Data Integration

  • Built an automated ingestion service to fetch store pricing via APIs
  • Standardized the feed to align with scraped data formats
  • Mapped and synchronized data from multiple retailers' branches

3. Data Cleaning & Normalization

  • Removed promotional tags and non-essential data
  • Standardized pricing to a uniform currency format
  • Applied product categorization for consistent reporting

4. Centralized Storage & Dashboard

  • Stored clean, structured data in a PostgreSQL database
  • Built a user-friendly dashboard with filters and visualizations
  • Provided pricing insights through charts, heatmaps, and trend indicators
03

Result

Real-Time Price Visibility and Actionable Intelligence

The client gained an integrated platform that:

  • Delivers daily competitive price insights
  • Enables cross-channel comparison (online vs. offline)
  • Supports data-backed pricing decisions across products and regions

Impact

A transformative shift in pricing analytics:

  • 5,000+ SKUs tracked across 3 competitors
  • 4–6 hour refresh cycles for online data
  • Decision turnaround reduced from 48 hours to under 6 hours

Technologies we used

  • Python
  • Flask
  • PostgreSQL
  • Celery

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