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Everything You Must Know About Voice AI in Marketing
Voice recording and AI systems have been rapidly evolving, pushed by new and exciting technological advances breaking the boundaries of what we thought was possible in the world of data and marketing. New systems can analyse a business’s customer base with impressive efficiency, collecting information and processing it rapidly

Everything You Must Know About Voice AI in Marketing

Voice recording and AI systems have been rapidly evolving, pushed by new and exciting technological advances breaking the boundaries of what we thought was possible in the world of data and marketing. New systems can analyse a business’s customer base with impressive efficiency, collecting information and processing it rapidly. The latest development in AI is introducing the concept of customer profiling – the use of voice data to compile information on an individual’s physical as well as emotional and speech characteristics. While this technology can provide businesses with an impressive array of information to be utilised in marketing and targeted sales, there are both flaws and regulations that businesses must be aware of before launching these systems.

How do voice recording and AI profiling work?

 

Collaborative approaches to voice recording and AI are usually founded on Conversational AI, Natural Language Processing (NLP), and Automatic Speech Recognition (ASR). Conversational AI is used to provide automated messaging systems, facilitating communication between humans and technology. NLP provides the means to combine machine learning with human language models, which can then be used to improve Conversational AI and the processing of voice data. The translation of data from a verbal format to text and the identification of certain language features can then be provided through ASR. Together, these systems can detect, record, and analyse customer interactions for several purposes, including AI profiling. The information can also be valuable input for machine learning systems, which learn from their recorded history to provide improved algorithms for various purposes.