AI-Based Voice Agent for Automated Sales Calls

This paper presents an AI-based voice agent designed to enhance customer engagement in automated sales. Operating continuously, the agent leverages the power of Large Language Models (LLMs) to interact with potential customers, persuading them to purchase products or schedule appointments with human representatives. Initial performance evaluation gives extremely positive results highlighting the agent's potential to revolutionize sales interactions and improve operational efficiency. These are demonstrated by a conversion rate of 8%, significantly higher than industry averages of 2-5%, high ratings for friendliness, clarity, and realism in customer satisfaction surveys, and an average of 1.7 seconds reaction time during conversation.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/dasa63652.2024.10836508
Primary Topic
Multi-Agent Systems and Negotiation
Type
article
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article

AI-Based Voice Agent for Automated Sales Calls

Yousra Chtouki, Tajjeeddine Rachidi, Ahmed Amarak, Mohamed Igamane
Multi-Agent Systems and Negotiation
article

AI-Based Voice Agent for Automated Sales Calls

Yousra Chtouki, Tajjeeddine Rachidi, Ahmed Amarak, Mohamed Igamane
article en

Abstract

This paper presents an AI-based voice agent designed to enhance customer engagement in automated sales. Operating continuously, the agent leverages the power of Large Language Models (LLMs) to interact with potential customers, persuading them to purchase products or schedule appointments with human representatives. Initial performance evaluation gives extremely positive results highlighting the agent's potential to revolutionize sales interactions and improve operational efficiency. These are demonstrated by a conversion rate of 8%, significantly higher than industry averages of 2-5%, high ratings for friendliness, clarity, and realism in customer satisfaction surveys, and an average of 1.7 seconds reaction time during conversation.

Nanjing University of Posts and Telecommunications (CN), Al Akhawayn University (MA)
Openalex Percentile: Top 76%
Multi-Agent Systems and Negotiation
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