Abstract
Purpose: The aim of the paper is to address the persistent uncertainty surrounding the effectiveness of chatbot-led service failure recovery (SFR) in delivering a satisfactory online customer experience. Prior studies have not explored how chatbot-led SFR processes influence customers’ actual experiences. This gap in the literature may exist because current understanding of chatbot–customer interactions obscure how individuals’ adoption of chatbot-led SFR shape their experiences. Design/methodology/approach: Drawing on frustration–aggression theory and signaling theory, and building on a social constructivist philosophical paradigm, this paper interprets participants’ narratives on chatbot-led interactions and online experiences. Empirical data was generated through 52 in-depth interviews conducted with participants from the USA, France, Italy, and the UK. Findings: Through thematic analysis of interview data, the study presents two key contributions. First, this paper elucidates the dynamics unfolding between customers and chatbots in a service recovery journey, encompassing customers’ priorities and expectations. Second, this paper delineates three customer typologies based on their interactions with chatbots during chatbot-led SFR, including their emotional responses. These interactions could either positively or negatively signal future patronage of chatbots. The identified three customer types can assist managers to reshape their strategies to effectively turn negative customer experiences into opportunities for enriching online customer experiences. This could involve providing multiple touchpoints, including human-led and chatbot-led interactions in the SFR process. Originality/value: This study proposes that chatbots are not just technological tools that support customers during service failures and facilitate connection with the brand, but also function as signals that trigger emotional and cognitive responses, thereby influencing the customer experience.
| Original language | English |
|---|---|
| Pages (from-to) | 493-512 |
| Number of pages | 20 |
| Journal | Journal of Services Marketing |
| Volume | 39 |
| Issue number | 5 |
| Early online date | 2 May 2025 |
| DOIs | |
| Publication status | Published - 11 Jun 2025 |
Keywords
- Artificial intelligence
- Chatbots
- Frustration–aggression theory
- Online customer experience
- Qualitative research
- Service failure recovery
- Signaling theory