Adopt, Adapt, Transform: AI Integration in Customer Feedback Management

This teaching case traces the AI-driven transformation of re:spondelligent, a Swiss startup specializing in customer feedback management for the hospitality sector. Originally offering fully manual, high-quality review responses written by professional authors, the company embarked on a multi-year journey to integrate AI incrementally into its operations. Through a collaborative innovation project, re:spondelligent developed tools for sentiment analysis, response quality control, automated drafting, and difficulty scoring. These tools not only streamlined internal workflows but also enabled the company to transform its business model – introducing a tiered service offering and a triage system aligned with review complexity and client preferences. The case illustrates how small firms can leverage dynamic capabilities and combinatorial innovation to adapt in rapidly changing technological environments. It invites discussion on strategic AI integration, business model transformation, and the human-AI balance in service delivery.

Publication Details

Journal
Universität Zürich, ZORA
Published
2025-11-10
DOI
https://doi.org/10.5167/uzh-280425
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Adopt, Adapt, Transform: AI Integration in Customer Feedback Management

Universität Zürich, ZORA
AI in Service Interactions
article

Adopt, Adapt, Transform: AI Integration in Customer Feedback Management

article en

Abstract

This teaching case traces the AI-driven transformation of re:spondelligent, a Swiss startup specializing in customer feedback management for the hospitality sector. Originally offering fully manual, high-quality review responses written by professional authors, the company embarked on a multi-year journey to integrate AI incrementally into its operations. Through a collaborative innovation project, re:spondelligent developed tools for sentiment analysis, response quality control, automated drafting, and difficulty scoring. These tools not only streamlined internal workflows but also enabled the company to transform its business model – introducing a tiered service offering and a triage system aligned with review complexity and client preferences. The case illustrates how small firms can leverage dynamic capabilities and combinatorial innovation to adapt in rapidly changing technological environments. It invites discussion on strategic AI integration, business model transformation, and the human-AI balance in service delivery.

Universität Zürich, ZORA
Industry, innovation and infrastructure
Openalex Percentile: Top 22%
AI in Service Interactions
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