Client Overview: Tagg is a forward-thinking e-commerce platform that curates products from top online retailers, delivering personalized fashion recommendations to users. By leveraging a Chrome extension to track online shopping behavior, Tagg tailors product suggestions across multiple retailers, ensuring a unique and personalized shopping experience.
The Problem: Tagg needed to provide users with highly accurate and personalized product recommendations across a vast array of online retailers. However, the challenge lay in normalizing product data from hundreds of different sites. This included pulling essential details like pricing, stock levels, images, and accurate categorization—all of which varied significantly from site to site.
Challenges: Initially, Tagg relied on Open Graph meta tags and specific HTML properties to scrape product details from various sites. However, this approach led to frequent issues, such as miscategorized data and inaccuracies whenever sites underwent redesigns or structural changes. The quality of the data was insufficient to power a robust recommendation engine, necessitating a more sophisticated solution.
The Solution & Implementation: To overcome these challenges, Red Foundry implemented a combination of AWS Personalize, OpenAI, and advanced scraping technology. AWS Personalize was employed to ingest user shopping behavior and generate highly personalized recommendations. Meanwhile, OpenAI was integrated to process unstructured product pages into a well-defined product model and category taxonomy, addressing the issues caused by traditional scraping methods.
By fine-tuning OpenAI’s prompt engineering, we achieved the perfect balance between token count and accuracy, ensuring that product data was accurately categorized and normalized. The advanced scraping technology continuously updated and synchronized the product database, keeping fast-moving data like stock levels and pricing accurate and up-to-date. This comprehensive solution empowered Tagg to deliver curated recommendations that captured the unique style and fashion tastes of each user.
Conclusion: The implementation of AWS Personalize, OpenAI, and advanced scraping technology enabled Tagg to elevate its e-commerce platform, offering users a truly personalized shopping experience. By capturing the unique style and fashion tastes of each user, Tagg’s recommendation engine goes beyond simple product attributes, delivering curated suggestions that resonate with individual preferences. Explore how advanced personalization can elevate your e-commerce platform. Contact Red Foundry to learn how we can design, build, and maintain tailored solutions for your business needs.
