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How Can Sentiment Analysis Be Used to Improve Customer Experience?

Interaction Metrics

Sentiment analysis reveals the emotions your customers feelbut knowing how they feel is only useful if you know why they feel the emotion in the first place. We provide comprehensive text analysis services that include sentiment analysis to deliver actionable insights you can use to improve the customer experience.

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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

AWS Machine Learning

Extracting valuable insights from customer feedback presents several significant challenges. Scalability becomes an issue as the amount of feedback grows, hindering the ability to respond promptly and address customer concerns. Large language models (LLMs) have transformed the way we engage with and process natural language.

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Guest Post: How to Design a Customer Success Program That Works

ShepHyken

Regularly update training materials based on customer feedback. Account management Offer workshops on relationship-building, active listening, and consultative selling for identifying upsell or cross-sell opportunities. Encourage shadowing experienced account managers who can disseminate their best tips and tricks.

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Guest Post: 4 Ways to Transform Customer Experience While Growing Rapidly

ShepHyken

Through a variety of surveys and feedback forums, XGS realized that we had some work to do to create an internal culture that drove employee engagement and satisfaction. Net Promoter Score (NPS) — Establishing baseline ratings and gathering key customer feedback . Happy Enabled Employees = Happy Customers.

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What is Voice of the Customer? [+ how to get data analysis]?

Lumoa

Analyzing the feedback that you do get can be overwhelming, especially when it’s coming from so many different sources. The term “Voice” is used in a metaphorical sense, as customers may not express their thoughts and feelings verbally or through traditional feedback channels. But listening isn’t always that easy.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

Observability empowers you to proactively monitor and analyze your generative AI applications, and evaluation helps you collect feedback, refine models, and enhance output quality. Security – The solution uses AWS services and adheres to AWS Cloud Security best practices so your data remains within your AWS account.

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Revolutionizing clinical trials with the power of voice and AI

AWS Machine Learning

This step provides an accurate and efficient conversion of spoken words into a format suitable for further analysis. This streamlines the process of data collection, analysis, and decision-making for clinical trial stakeholders, including investigators, sponsors, and regulatory authorities.