Product and eCommerce Search
Webinar Series - AI and Search: Navigating the Future of Business Transformation Session 2
Summary
Enhancing E-commerce Experience
Generative AI can transform the e-commerce user experience by pre-answering common queries and improving response times through conversational search, creating a more engaging and efficient shopping environment.
Fine-Tuning and Domain-Specific Models
Tailoring generative models through fine-tuning and deploying smaller, specialized models can enhance performance in specific tasks such as brand recognition and query segmentation, offering both speed and accuracy improvements.
RAG in E-commerce (Retrieval-Augmented Generation)
RAG methodologies empower e-commerce platforms by indexing products into vector spaces and retrieving relevant data, coupled with consistent embedding models to ensure accurate, context-rich search results and recommendations.
Cost Considerations
Implementing generative models in e-commerce comes with substantial resource and computational costs, but leveraging open-source models and understanding token cost-pricing can provide financial advantages, making the technology more accessible.
Modality Choice
RAG methodologies empower e-commerce platforms by indexing products into vector spaces and retrieving relevant data, coupled with consistent embedding models to ensure accurate, context-rich search results and recommendations.
We're excited to continue the discussion. Be sure to review upcoming webinars in this series.
Session Highlights
"AI not only helps in finding what is needed but also provides expertise and contextually appropriate experiences in e-commerce, which is essential for a good user experience." - Seth Earley
"The integration of search capabilities in e-commerce with AI can enhance search results, create landing pages, improve SEO, and personalize user experiences by understanding customer intent and behavior." — Sanjay Mehta
"The evolving role of generative AI in e-commerce is transformative, but the industry is rapidly changing, and there's still much more to explore in this field." — Patrick Hoeffel
"Fine-tuning and task-specific models enhance efficiency and specificity, though they may sometimes lack the breadth of general knowledge found in larger models." - Phil Ryan