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Microsoft Dynamics 365 AI for Business Insights

Microsoft Dynamics 365 AI for Business Insights

By : Dmitry Shargorodsky
4.4 (7)
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Microsoft Dynamics 365 AI for Business Insights

Microsoft Dynamics 365 AI for Business Insights

4.4 (7)
By: Dmitry Shargorodsky

Overview of this book

If there is one hot topic being discussed in every boardroom meeting today, it’s AI. With Microsoft Dynamics 365 AI proving to be a game-changer, it’s essential for business professionals to master this tool. Microsoft Dynamics 365 AI for Business Insights will help you harness AI across key business functions to streamline processes and enhance customer experiences. Written by a seasoned professional with 15+ years of experience, this book guides you through Dynamics 365 AI’s practical applications across sales, customer service, marketing, and finance departments. You'll learn how to enhance customer experiences, streamline sales processes, optimize marketing strategies, and improve financial forecasting. This book also explores the integration of generative AI tools such as OpenAI Service, Azure Open AI, language models, and Microsoft Copilot within the Dynamics 365 ecosystem. With real-world examples, case studies, and expert insights, you’ll discover the transformative potential of this powerful toolkit. As well as driving sales insights and implementing fraud protection, you’ll explore emerging AI trends, Microsoft's roadmap for Dynamics 365 AI, and the upcoming features. By the end, you’ll be all set to unlock new growth opportunities using Dynamics 365 AI.
Table of Contents (18 chapters)
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1
Part 1: Foundations of Dynamics 365 AI
4
Part 2: Implementing Dynamics 365 AI Across Business Functions
9
Part 3: Advanced Applications and Future Directions
14
Part 4: Looking Ahead

AI-powered sentiment analysis and customer 
sentiment tracking

In the landscape of AI-enhanced customer service, sentiment analysis and customer sentiment tracking stand out as pivotal tools. These AI-driven capabilities extend the function of virtual agents and chatbots beyond mere transactional interactions, allowing them to gauge and respond to emotional undertones in customer communications. This section explores the technical aspects, applications, and impacts of sentiment analysis in modern customer service.

Technical aspects of sentiment analysis

Sentiment analysis in AI systems primarily relies on NLP and ML. NLP interprets and understands human language, enabling the AI to process not only what is being said but also how it’s being said. By analyzing word choice, sentence structure, and even the rhythm of the customer’s language, the AI can identify whether the sentiment is positive, negative, or neutral.

ML for enhanced sentiment detection

...

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