Information Package / Course Catalogue
Reputation Management in Hospitality Businesses
Course Code: THM123
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 1
Prt.: 1
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The aim of this course is to enable students to gain practical competence in measuring, analyzing, and managing online reputation in hospitality businesses. The course covers the guest review ecosystem, reputation KPIs, sentiment analysis, and competitive benchmarking methods; KPI tracking, sentiment analysis, and AI-powered review response applications are processed with real data through the Kepsla reputation management system.

Course Content

This course focuses on measuring, analysing and strategically managing online reputation in hospitality businesses. Students explore the review ecosystem across TripAdvisor, Google and OTA platforms, learn core reputation KPIs (NPS, CSAT, GRI, Review Score, Response Rate) and study sentiment analysis methods. The practical component uses the Kepsla reputation management system to perform KPI tracking, department-level sentiment analysis and AI-assisted review response generation with real data. Throughout the course, the direct relationship between reputation management and occupancy rates, pricing strategy and revenue performance is consistently emphasised.

Name of Lecturer(s)
Learning Outcomes
1.Explain the impact of online reputation on revenue, occupancy, and pricing for hospitality businesses.
2.TripAdvisor reviews the review ecosystem and key reputation KPIs (Review Score, NPS, CSAT, GRI, Response Rate) on Google and OTA platforms.
3.Using sentiment analysis methods, it analyzes the tone and trends of emotions in guest feedback.
4.Kepsla uses its reputation management system to track KPIs, perform competitor benchmarking, and conduct reporting.
5.It generates effective, personalized responses to positive and negative reviews using AI-powered tools.
Recommended or Required Reading
1.Anderson, C. K. The Impact of Online Reviews on Hotel Performance. Cornell SHA.
2.Program Kepsla Reputation Management System ?? https://www.kepsla.com
Weekly Detailed Course Contents
Week 1 - Theoretical
The concept and importance of reputation; the transition from traditional to digital reputation management; the impact of online reputation on hospitality business performance; the reflections of digital transformation on reputation management; current examples from the sector.
Week 2 - Theoretical
TripAdvisor, Google, Booking.com, Expedia, and other OTA platforms' place in the review ecosystem; platform algorithms and ranking logic; guest review behavior; review volume, recency, and the impact of ratings on business visibility.
Week 3 - Theoretical
The stages of the guest journey (pre-booking, accommodation, post-accommodation); touchpoints at each stage that affect reputation; the link between online and offline experience and reputation; the digital reflections of service quality.
Week 4 - Theoretical
The impact of review score on occupancy rate, ADR, and RevPAR; the relationship between reputation management and revenue management; research findings and industry data; the correlation between reputation score and pricing strategy; examples from the Turkish hotel industry.
Week 5 - Theoretical
Key reputation KPIs: Review Score, Response Rate, Review Volume, NPS (Net Promoter Score), CSAT (Customer Satisfaction Score), GRI (Global Review Index); calculation and interpretation of each KPI; industry benchmarking values; KPI target setting and monitoring.
Week 6 - Theoretical
The definition of sentiment analysis and its role in reputation management; fundamentals of natural language processing (NLP); classification of positive, negative, and neutral comments; department-based sentiment analysis (front desk, housekeeping, F&B, cleaning); trend identification and operational insight generation.
Week 7 - Practice
Competitive reputation analysis; score comparison with competitors in a similar segment; use of reputation score in market positioning; geographic and category-based benchmarking methods; developing strategic recommendations from benchmarking data.
Week 8 - Intermediate Exam
The exam will assess the topics covered in weeks 1-7. It will cover the concepts of reputation, the review ecosystem, guest journeys, impact on business performance, KPIs, sentiment analysis, and competitor benchmarking.
Week 9 - Practice
The importance of responding to reviews in reputation management; strategies for responding to positive reviews; professional techniques for responding to negative reviews; reputation management in crisis situations; the impact of response speed and quality; principles of language, tone, and personalization; application through real hotel cases.
Week 10 - Practice
The role of AI in reputation management; AI-powered automated comment response systems; personalized response generation; determining which comments require automated and which require manual responses; drafting responses using tools like ChatGPT; the importance of human moderation.
Week 11 - Practice
Introduction to the Kepsla platform and its interface; multi-channel comment tracking via the platform; central dashboard management; notification and alert systems; overview of reporting modules; creating a student account and connecting to the platform.
Week 12 - Practice
Performing sentiment analysis with real hotel data via Kepsla; reading and interpreting department-based sentiment reports; monitoring KPI indicators; trend analysis and time series interpretation; identifying areas for improvement and developing operational recommendations.
Week 13 - Practice
The features include: using Kepsla's AI-powered comment response module; automated and semi-automated response processes via the platform; multilingual response management; generating weekly and monthly reputation reports; and preparing slides and summaries for presenting the report to management.
Week 14 - Final Exam
A final exam will be conducted to review all topics covered in the course. These topics include reputation KPIs, sentiment analysis, competitor benchmarking, comment response strategies, AI applications, and Kepsla platform applications.
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%10
Quiz1%10
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory62224
Laboratory62224
Quiz2114
Final Examination1112
TOTAL WORKLOAD (hours)54
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
OÇ-1
3
5
5
5
5
5
OÇ-2
5
5
5
5
5
5
OÇ-3
5
5
5
5
5
5
OÇ-4
3
5
5
5
5
5
OÇ-5
5
5
5
5
5
5
Adnan Menderes University - Information Package / Course Catalogue
2026