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Solution Accelerator

Automating Product Review Summarization With LLMs

Pre-built code, sample data and step-by-step instructions ready to go in a Databricks Notebook

Automating product review summarization with Large Language Models (LLMs)
Automating product review summarization with Large Language Models (LLMs)

Keep track of customer feedback at scale

The breadth of digital communication channels has made it increasingly effortless for customers to write product reviews that can significantly impact the perception of a business. With large language models (LLMs), retailers can easily extract and summarize insights from huge volumes of customer feedback to enhance decision-making and product development strategies.

Use this Solution Accelerator to streamline the summarization of customer feedback, allowing your organization to:

  • Process a high volume of reviews at a lower cost
  • Collect feedback from a wider range of products and summarize it regularly
  • Task an LLM to extract different sets of information from each high-level category of reviews
Download notebook

Resources

Automating product review summarization with Large Language Models (LLMs)

Blog

Automated Analysis of Product Reviews Using LLMs

Keep track of customer feedback at scale

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Retail in the Age of Generative AI

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Retail in the Age of Generative AI

10 ways large language models (LLMs) may impact the retail industry

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Fine-Tuning Large Language Models with Hugging Face and DeepSpeed

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Fine-Tuning Large Language Models with Hugging Face and DeepSpeed

Easily apply and customize large language models of billions of parameters

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