【公开学术报告】Open the Black Box of AI Voicebots in Sales Call Automation

Guest Speaker:     Siliang TONG (Temple University)

Time/Date:          9:30 am Thur. 13th, August 2020 (Beijing Time)

Length:                1.5 hours

Meeting ID:         625 902 08872

Password:            598786

Click Link:            https://zoom.com.cn/j/62590208872

Abstract:

Artificial intelligence (AI) voicebots have immense business potentials for automating customer services in call centers. Yet, companies are dubious about the black-box nature of voicebots, and extant research provides little empirical evidence for the underlying mechanisms on how voicebots can converse with customers in automated service tasks. This study exploits a field experiment with customers who are randomized to receive an outbound sales call from either a voicebot or human agent. It utilizes audio data analytics to extract agents’ voice features (i.e., amplitude, speed, and pitch) and speech content (i.e., selling adaptivity) to examine how the voicebot converses with customers. The results show that the voicebot can outperform general human agents in terms of purchase rates and customer satisfaction because of two distinct mechanisms. The first mechanism is related to how to say: the voicebot has a more stable voice, i.e., lower volatility in amplitude and speed, than human agents. The second mechanism is about what to say: the voicebot tends to display a higher selling adaptivity to cater to individual customer needs in the speech content. The former mechanism accounts for more variance in the incremental purchase responses to the voicebot than the latter mechanism. Additional optimization simulations based on heterogeneous customer responses indicate that assembling human agents and the voicebot together can achieve more sales revenues than using only human agents or the bot alone. These findings have useful implications for managers who can leverage sales call automation and unstructured voice data to boost firm performance in the new AI era.

Guest Biography

Siliang(Jack) Tong joined the Fox School in 2016 with the concentration of Big Data Analytics and Mobile marketing. He is one of the competitive recipients of Presidential Fellowships and a research fellow of the Global Center on Big Data in Mobile Analytics. Prior to joining the Fox School, Siliang(Jack) Tong completed his MBA from the University of Wisconsin-Madison. He has six years working experience in digital marketing and eCommerce fields with management positions at Hilton Worldwide China Corporate Office and Wynn Macau Resort.