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Development of a Global Marketplaces Data Extraction and Analytics System for Consumer Product Insights
  1. case
  2. Development of a Global Marketplaces Data Extraction and Analytics System for Consumer Product Insights

Development of a Global Marketplaces Data Extraction and Analytics System for Consumer Product Insights

dashbouquet.com
Consumer products & services

Challenges in Real-Time Data Collection and Market Monitoring from Global Online Marketplaces

The client faces significant difficulties in systematically extracting accurate and timely data on skincare and cosmetic products from various international online marketplaces. These challenges include active protection of marketplace data through request throttling, anti-scraping measures like CAPTCHA and request rate limiting, and frequent layout changes that hinder reliable data extraction. As a result, the client lacks comprehensive insights into product components, pricing, and market trends essential for informed decision-making.

About the Client

A large-scale consumer goods manufacturer with global marketing and retail presence seeking to monitor and analyze product listings across multiple online marketplaces.

Goals for Implementing a Robust Marketplaces Data Extraction and Analytics Solution

  • Develop a scalable and reliable data extraction system capable of monitoring over 21,000 SKUs across 18 countries and multiple marketplaces including major platforms.
  • Implement intelligent request mechanisms and AI-driven techniques to bypass protections such as scraping detection and request throttling.
  • Create a system capable of accurately recognizing product ingredients and components directly from webpage content.
  • Ensure the system is resilient to dynamic layout changes and marketplace anti-scraping measures.
  • Provide weekly analytics reports and access to historical data to facilitate trend analysis and strategic decision-making.

Core Functionalities for Global Marketplace Data Extraction and Analysis

  • Automated web scraping modules that emulate human-like browsing behavior for data collection.
  • AI-powered component that recognizes and extracts product ingredients and details directly from webpage content.
  • Adaptive request management that employs intelligent endpoints, request throttling, and anti-detection techniques.
  • Layout change resilience through machine learning models or AI-based recognition to maintain extraction accuracy despite webpage updates.
  • Automated weekly data aggregation and analytics reporting tools.
  • Historical data storage for trend analysis and strategic planning.

Preferred Tech Stack and Architectural Approaches for Implementation

Cloud-based storage solutions (e.g., AWS S3) for scalable data management.
Container orchestration platforms such as Kubernetes (K8s) for deployment flexibility.
Workflow automation using Apache Airflow for scheduling and managing data pipelines.
Headless browser frameworks (e.g., Puppeteer) for web scraping.
NLP and AI libraries, such as SpaCy, for ingredient and component recognition.

Essential External System Integrations for Data Enrichment

  • Marketplace APIs where available for more direct data access.
  • AI and ML services for recognition and layout adaptation.
  • Security and proxy services to mask scraping activity and prevent IP blocking.
  • Business intelligence tools for analytics and visualization.

Critical Non-Functional Attributes for System Success

  • System scalability to handle data extraction from multiple marketplaces simultaneously with over 21,000 SKUs monitored.
  • High availability with 99.9% uptime for continuous data collection.
  • Security measures to prevent data leaks and protect access credentials.
  • Request response times optimized for weekly reporting cycles.
  • System resilience to frequent webpage layout modifications and anti-scraping countermeasures.

Projected Business Outcomes from the Marketplace Data System

The implementation of this sophisticated data extraction and analytics system is expected to enable the client to effectively track and analyze product offerings across global marketplaces, leading to more informed product positioning, competitive insights, and strategic pricing decisions. The system's resilience features and AI capabilities reduce manual effort and increase data accuracy, supporting ongoing market competitiveness and decision-making efficiency.

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