Case Study
AI-Powered Data Enrichment for a Marketplace Client
Client Profile
Industry: Online Marketplace
Size: Mid-sized B2C e-commerce platform
Need: Missing or incomplete product data was negatively impacting user experience, SEO, and seller onboarding.
Challenge
The client’s internal product catalog lacked key metadata (descriptions, specifications, tags), which caused:
- Poor search relevance
- Low conversion rates
- Increased manual workload for internal teams
The issue stemmed from product feeds that were inconsistent across sellers and had no centralized enrichment process
Solution
Our team designed and deployed a fully automated data scraping and enrichment pipeline:
🔧 Technologies Used:
- Python for custom scraping scripts
- Google Custom Search API to discover and rank relevant external product sources
- OpenAI API to generate clean, human-readable product descriptions
- ETL pipeline to consolidate, clean, and standardize metadata across sources
🧠 Key Innovations:
- Combined LLM-powered text generation with targeted scraping to fill in missing fields
- Used prompt engineering to ensure descriptions matched the client’s brand tone
- Implemented error handling and confidence scoring to flag weak outputs for manual review
Results
📈 Within 3 weeks of deployment:
- 95%+ reduction in manual data entry time
- 70% of products enriched with high-quality metadata
- Significant boost in internal search accuracy and product discoverability
Fully scalable pipeline now enriches new listings in real time
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At Aiintegrate, we believe that artificial intelligence isn’t just about automation—it’s about empowerment.