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Maximizing Generative AI Potential: Developing AI-Enhanced Product Features #AIinnovation

Unleashing the Potential of Generative AI: building an AI enabled product feature | by Jamie Geddes | Jul, 2024

Trustpilot, a leading online platform for service reviews, has introduced a new AI-assisted review responses feature to help businesses manage the large volume of feedback they receive. With 54 million reviews submitted in 2023, responding to all of them can be challenging. The AI feature generates initial responses, saving time and effort for businesses.

The platform allows consumers to submit reviews on businesses or services they interact with, and businesses can respond to these reviews. Engaging with customers through responses is crucial for businesses to build trust and loyalty. However, responding to reviews can be time-consuming, with an average response time of 3.95 days and a response rate of 38% for service reviews.

For enterprise users managing a high volume of reviews, efficiency is a key challenge. As the monthly review count increases, the response rate declines, highlighting the need for scalable solutions. Using generative AI capabilities can aid in response creation, but businesses must maintain a human touch to connect with customers effectively.

To improve response quality and avoid hallucinations in AI-generated content, Trustpilot uses techniques like Retrieval Augmented Generation (RAG) and cosine similarity to find similar reviews. The platform also tracks usage and adoption of the AI feature to make data-driven decisions for further improvements.

Overall, Trustpilot’s journey with generative AI showcases the potential benefits of using AI wisely to enhance customer experiences. The collaboration across various functional areas, tracking system performance, and making data-driven decisions have been crucial for the success of this project.

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Source link: https://medium.com/@jamiegeddes/unleashing-the-potential-of-generative-ai-building-an-ai-enabled-product-feature-8875d3d80157?source=rss——llm-5

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