Back to Search
Start Over
Human vs. Automated Sales Agents: How and Why Customer Responses Shift Across Sales Stages.
- Source :
- Information Systems Research; Sep2023, Vol. 34 Issue 3, p1148-1168, 21p
- Publication Year :
- 2023
-
Abstract
- Customers in sales processes increasingly encounter automated sales agents that complement or replace human sales agents. Yet, little is known about whether, how, and why customers respond to automated agents in contrast to human agents across successive decision stages of the same sales process. Even less is known about customer responses to combinations where both agents assume distinct roles and focus on complementary tasks that are traditionally performed by only one single agent. Against this backdrop, this paper explores the influence of increasingly common sales representative types on customer decisions across sales stages. Our findings demonstrate that customer responses to automated (versus human) sales agents are not stable in sales processes and instead, shift as customers move across sales stages. What is more, the paper shows that combinations of sales agents versus single sales agents do matter, yet their differential effects depend on contextual features of the sales setting. These insights are important because vendors may assume that a certain type of sales agent is always more appreciated by customers, whereas in fact, different sales agent types bring distinct attributes to the table, and customers' appreciation of these attributes shifts across sales stages. Customers in sales processes increasingly encounter automated sales agents (ASAs) that complement or replace human sales agents (HSAs). Yet, little is known about whether, how, and why customers respond to ASAs in contrast to HSAs across successive decision stages of the same sales process. Even less is known about customer responses to HSA-ASA combinations, where both agents assume distinct roles and focus on complementary tasks that are traditionally performed by only one single sales agent. Against this backdrop, this paper explores the influence of increasingly common sales representative (rep) types (i.e., ASA, HSA, and HSA-ASA) on customer decisions across sales stages. Drawing on information processing theory and the literature on hedonic-utilitarian decision making, we investigate customer responses to text-based ASAs from vendor companies in two common early stages of email sales processes (i.e., sales initiation stages) when customers successively decide whether to indicate their initial interest in an offer and then, whether to provide their contact information. Specifically, we conducted two complementary multi-decision experiments, namely (1) a randomized field experiment in a high-stakes sales initiation setting (n = 325) and (2) a subsequent randomized online experiment to complement the real-world insights (n = 408). Our core findings reveal reversing effect patterns of sales rep types across stages: although customers are more likely to indicate their initial interest to HSAs (versus ASAs) because of HSAs' higher levels of social presence, they are less likely to provide contact information to HSAs because of HSAs' lower levels of performance expectancy and effort expectancy. We also show that HSA-ASA combinations can be reasonable options for single ASAs, yet contextual features of the sales setting may affect differential customer responses to HSA-ASA combinations (versus ASAs) in each sales stage. Taken together, we uncover shifting effect patterns in customer responses to sales rep types across successive sales stages and shed light on the consecutive underlying mechanisms that explain these shifts. These findings have significant implications for vendor companies seeking to allocate HSAs and/or ASAs effectively across various decision stages in sales processes and beyond. History: Wonseok Oh, Senior Editor and Khim Yong Goh; Associate Editor. Funding: This work was supported by the Center for Responsible Digitality (ZEVEDI) and the German Research Foundation (DFG) [Grant 471168026]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1171. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10477047
- Volume :
- 34
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Information Systems Research
- Publication Type :
- Academic Journal
- Accession number :
- 172369259
- Full Text :
- https://doi.org/10.1287/isre.2022.1171