E-Commerce Catalog Enrichment with AI-Generated Content

Client: A Fortune 500 global e-commerce retailer Industry: E-Commerce / Retail Technology Services Used: Data Engineering, AI-Generated Content, Multilingual Translation

Challenge The retailer operated across 28 countries with a catalog of 12 million SKUs, but product descriptions were inconsistent, incomplete, or missing entirely for long-tail items. Poor product data hurt search relevance, conversion rates, and multilingual market expansion. Generating high-quality descriptions for millions of products through human writers was economically impossible, but purely automated LLM generation produced generic, off-brand content that hurt rather than helped conversion.

The retailer needed an AI-human hybrid pipeline that could scale to millions of products while maintaining brand voice and category-specific accuracy.

Lifewood Solution Lifewood designed a human-in-the-loop AI content pipeline combining LLM generation tuned on the client's brand voice, category-specific prompt engineering, human review and editing by product category specialists, and multilingual adaptation across 14 target languages. A custom quality scoring model flagged outputs for human review based on category, price tier, and conversion impact, optimizing reviewer effort toward highest-value SKUs. The pipeline ran as a continuous service integrated with the client's PIM system.

Results

• 8.4 million product descriptions generated and reviewed across 14 languages

• 22% lift in conversion rate on products with enriched descriptions

• 67% cost reduction vs. fully human content production

• 94% brand voice consistency score on human evaluation

• 3x faster market expansion for new country launches

Representative Testimonial "The AI-human hybrid was the only approach that worked at our scale. Lifewood built the pipeline, staffed the reviewers, and delivered measurable conversion improvements we could take to the board." — VP of Global E-Commerce, client retailer

Tags: E-Commerce, AI Content Generation, Data Engineering, Multilingual Content, Human-in-the-Loop AI