Client Overview
A global consumer goods brand required a scalable solution to monitor Minimum Advertised Price (MAP) compliance across hundreds of e-commerce platforms and retail aggregators.
Challenge
The client needed detailed visibility into how their products were listed and priced by third-party sellers. Information such as fulfillment methods (pickup, delivery, shipping), seller identity, and bundled promotions often impacted MAP compliance. Manual checks couldn’t keep pace with scale or frequency.
Solution
We deployed a high-scale, cloud-based web scraping framework to extract MAP-relevant data efficiently and accurately.
Key Technical Highlights
- Massive Scale Data Extraction: Our pipeline scrapes data from hundreds of websites weekly, processing extremely large volumes of records across regions and marketplaces.
- Granular Location-Wise Scraping: Captures product pricing and metadata across thousands of retail locations for each marketplace.
- Seller-Level Visibility: Extracts detailed seller-specific data, including fulfillment methods and promotional offers, enabling deeper MAP compliance analysis.
- Advanced Anti-Blocking System: Combines proxy rotation, human-like fingerprinting, CAPTCHA bypass, and the latest AI-assisted evasion methods to bypass leading bot-detection technologies.
- Centrally Managed Job Queue: Jobs are securely queued and intelligently distributed across a pool of dedicated scraping servers, based on resource availability and system load.
- Automated Data Validation: Post-scrape data flows through a QA pipeline built with Python, PySpark, and Databricks for structured and accurate delivery.
The Impact:
✅ High-Fidelity MAP Monitoring at Scale
✅ Accurate Pricing, Fulfillment, and Seller Metadata
✅ Minimal Downtime via Intelligent Job Management
✅ Fully Automated, Scalable Infrastructure
Case Study:
Automated MAP Compliance Monitoring for E-Commerce Platforms
Client Profile
A multinational consumer goods manufacturer sought an enterprise-grade solution to enforce Minimum Advertised Price (MAP) policies across 500+ global e-commerce platforms and retail aggregators.
Core Challenge
The client lacked real-time insights into third-party seller compliance, particularly regarding:
- Pricing discrepancies influenced by fulfillment methods (in-store pickup, delivery, shipping)
- Unauthorized seller activity and bundled promotions violating MAP terms
- Inability to manually monitor dynamic pricing at scale
Deployed Solution
A cloud-powered data extraction and analytics system designed for MAP enforcement, featuring:
Key Technical Components
- High-Volume Data Collection
- Weekly extraction of millions of product listings across regional marketplaces
- Multi-threaded scraping optimized for large-scale e-commerce platforms
- Geolocation-Specific Data Capture
- Granular price tracking across 10,000+ retail locations
- Localized metadata analysis (currency, promotions, inventory status)
- Seller Behavior Analytics
- Identification of fulfillment patterns impacting pricing
- Detection of promotional bundling strategies
- Dynamic Evasion Mechanisms
- AI-driven fingerprint rotation mimicking human browsing patterns
- Integrated CAPTCHA-solving and proxy network with 99.8% uptime
- Centralized Task Orchestration
- Load-balanced job distribution across dedicated scraping nodes
- Priority-based queue management for critical SKUs
- Automated Quality Assurance
- PySpark-powered validation pipelines
