Building a customer feedback analyzer.

Format:

Video

Contributor:

Schrooten, Bernd, instructor.

Packt Publishing, publisher.

Language:

English

Subjects (All):

Artificial intelligence--Marketing applications.

Artificial intelligence--Industrial applications.

Customer relations--Management.

Customer services.

Physical Description:

1 online resource (1 video file (28 min.)) : sound, color.

Edition:

[First edition].

Place of Publication:

[Birmingham, United Kingdom] : Packt Publishing, [2025]

Summary:

Understanding customer feedback is essential for informed business decisions, but analyzing large volumes of text data can be challenging. By combining data analysis, sentiment analysis, and AI-driven text summarization, you can quickly extract insights and transform raw feedback into actionable intelligence. Integrating AI into your workflow can streamline the process, saving time and improving accuracy. In this code-along, we'll build a Customer Feedback Analyzer using real-world data from a hospitality business. You'll learn how to measure customer sentiment with Net Promoter Score (NPS), perform text analysis to uncover trends, and visualize results for better decision-making. We'll also use AI-assisted coding to generate Python scripts that automate analysis, making business intelligence tasks more efficient. By the end of this session, you'll have a practical tool to analyze customer sentiment and drive data-driven improvements.

Notes:

OCLC-licensed vendor bibliographic record.

"DataLab" : DataLab is a learning solution designed to empower individuals and teams to explore data, build skills, and solve real-world problems. With interactive content, hands-on exercises, and a focus on practical application, DataLab helps learners turn data curiosity into confident capability—no matter where they start.

ISBN:

9781806025695

1806025698

OCLC:

1514318804