aceModerate evidence
More
Chatbots beat human agents at coaxing silent customers to report service failures, studies find
Study title: Breaking the Silence: How Chatbots and Human Agents Persuade Noncomplaining Consumers Following Service Failures
- Evidence type
- Controlled or validated comparison
- Sources
- 1 sourcePeer-reviewed
- Published
- 2 min read
- Truvace record
- TRV-2026-2665cite or check it
Study title: Breaking the Silence: How Chatbots and Human Agents Persuade Noncomplaining Consumers Following Service Failures
A paper in the Journal of Consumer Behaviour reports that chatbots outperform human agents at persuading consumers who stayed silent after a service failure to share what went wrong. Across five scenario experiments, chatbots that used self-benefit appeals produced significantly greater willingness to disclose prior experiences than human agents or other-benefit appeals.
Read the study abstract
ABSTRACT Firms are less likely to identify and resolve service deficiencies when consumers do not voice their complaints after service failures. A pressing question is how to persuade those noncomplaining consumers to provide feedback, yet empirical research in this area remains scarce. Our study draws on key questions of persuasion (i.e., who should say what to whom ?) to explore the matching effect of the persuasion source, persuasion message, and persuasion recipient on encouraging disclosure among noncomplai…
The gain
Across five scenario experiments, chatbots using self-benefit appeals made noncomplaining consumers significantly more willing to disclose a past service failure than human agents using other-benefit appeals.
In brief
The question matters because firms are less likely to identify and resolve service deficiencies when consumers do not voice complaints. The authors say empirical research on how to draw out these silent consumers has been scarce, and they frame their work around who should say what to whom.
The researchers identify self-focus and self-presentation as the mechanisms behind the effect, and find that consumers' self-awareness moderates it. They present the results as guidance for using chatbots in service recovery workflows.
Main points
- The study ran five scenario experiments on noncomplaining consumers after service failures.
- Chatbots outperformed human agents in encouraging disclosure when they used self-benefit rather than other-benefit appeals.
- Self-focus and self-presentation were identified as the mechanisms driving the effect.
- Consumers' self-awareness moderated the relationships between agent type, message and disclosure.
- The authors frame the work around persuasion's core questions: who should say what to whom.
The full story
The research addresses a gap in service recovery: when customers do not complain after a failure, firms lose the chance to find and fix problems. The authors say little empirical work has examined how to persuade these consumers to speak up.
Using a persuasion framework of source, message and recipient, they tested matches between agent type (chatbot or human), appeal type (self-benefit or other-benefit) and consumer traits. Chatbots paired with self-benefit appeals produced the strongest willingness to disclose.
The authors report that self-focus and self-presentation explain why the effect occurs, and that consumers' self-awareness changes how strong it is. They conclude that firms can use chatbots in service recovery workflows.
Sources
1 on file- Journal of Consumer Behaviourdoi:10.1002/cb.70219
Talk it over
Who gets this benefit, and who was left out of the study or story?
Chatbots beat human agents at coaxing silent customers to report service failures, studies findhttps://truvace.com/item/breaking-the-silence-how-chatbots-and-human-agents-persuade-noncomplaining-consu
Who gets this benefit, and who was left out of the study or story?
The gain Across five scenario experiments, chatbots using self-benefit appeals made noncomplaining consumers significantly more willing to disclose a past service failure than human agents using other-benefit appeals.
Answer in the threadHow do we know? What can this kind of evidence show, and what can’t it?
The evidence This rests on a controlled comparison, from Journal of Consumer Behaviour.
Answer in the threadWhat does it leave open? What else would you want to know before acting on it?
The record’s own caveat The evidence comes from scenario experiments, which measure willingness to disclose rather than actual feedback given to firms in real service failures.
Answer in the threadHave you seen AI used this way where you study, work or live? Did it go the same way?
Answer in the thread
The questions are the same on every record. The details under them are taken from this record as written.
What readers say