Based on the below, you need to create an online survey (160 respondants) and An

Based on the below, you need to create an online survey (160 respondants)
and Analyze the research problems with appropriate research methods and using the conceptual frameworks, models presented in the theoretical background Your analysis may include secondary and primary data. Present your results in a professional way and interpret your findings.
(length: 20-30 pages) spss usually has very long pages 1.5 spacing thats why i chose 15 pages
Summarize the main findings of your research. Explain the
relevance of your results and discuss their implications for
your theoretical models and frameworks. Highlight your
academic and managerial contributions. Discuss the
limitations of your work and describe some further research
opportunities.
(length: 4-5 pages)
Data Collection Methods:
An online survey can be utilized as the primary data collection method due to its efficiency and ease of administration. The survey can include structured questions to gather quantitative data on participants’ perceptions, concerns, and responses to AI-driven marketing tactics.
Sample Size:
Based on the provided range (150-160), the target sample size for this study will be 160 participants. This sample size ensures an adequate representation of the target population while maintaining feasibility in data collection and analysis.
Research Instruments:
A structured questionnaire will be developed to gather data on participants’ perceptions, concerns, and responses to AI-driven marketing tactics. The questionnaire will include items related to demographic information, perceptions of AI, concerns about data privacy, and responses to personalized push notifications.
Hypotheses:
H0: There is no significant relationship between individuals’ perceptions of AI-driven data analysis in the hotel industry and their concerns about data privacy. H1: There is a significant relationship between individuals’ perceptions of AI-driven data analysis in the hotel industry and their concerns about data privacy.
H0: There is no significant difference in individuals’ responses to personalized push notifications based on data analyzed by AI in the hotel industry across different demographic groups. H1: There is a significant difference in individuals’ responses to personalized push notifications based on data analyzed by AI in the hotel industry across different demographic groups.
H0: There is no significant association between individuals’ understanding of the implications of AI-driven marketing activities in the hotel industry and their consumer behavior. H1: There is a significant association between individuals’ understanding of the implications of AI-driven marketing activities in the hotel industry and their consumer behavior.
H0: There is no significant relationship between individuals’ perceptions of AI-driven data analysis in the hotel industry and their concerns about data privacy. H1: There is a significant relationship between individuals’ perceptions of AI-driven data analysis in the hotel industry and their concerns about data privacy. H0: There is no significant difference in individuals’ perceptions of personalized virtual services facilitated by AI in the hospitality industry across different demographic groups. H1: There is a significant difference in individuals’ perceptions of personalized virtual services facilitated by AI in the hospitality industry across different demographic groups. H0: There is no significant association between individuals’ concerns about data privacy in AI-driven marketing activities and their likelihood of experiencing churn in luxury hotels. H1: There is a significant association between individuals’ concerns about data privacy in AI-driven marketing activities and their likelihood of experiencing churn in luxury hotels. H0: There is no significant relationship between the implementation of AI-driven marketing strategies and customer loyalty in luxury hotels. H1: There is a significant relationship between the implementation of AI-driven marketing strategies and customer loyalty in luxury hotels. H0: There is no significant difference in the effectiveness of AI-driven marketing strategies on customer retention among different luxury hotel brands. H1: There is a significant difference in the effectiveness of AI-driven marketing strategies on customer retention among different luxury hotel brands.
H0: There is no significant association between individuals’ perceptions of personalized virtual services facilitated by AI in the hospitality industry and their likelihood of recommending the hotel to others. H1: There is a significant association between individuals’ perceptions of personalized virtual services facilitated by AI in the hospitality industry and their likelihood of recommending the hotel to others.
H0: There is no significant difference in customer satisfaction ratings between hotels that implement AI-driven marketing strategies and those that do not. H1: There is a significant difference in customer satisfaction ratings between hotels that implement AI-driven marketing strategies and those that do not.
research questions:
Research Questions
Introduction
In the fiercely competitive environment of the
hospitality sector, it is crucial to prioritize customer loyalty and reduce
customer turnover to achieve long-term success, especially for luxury hotels that
cater to sophisticated customers with demanding standards.
Artificial intelligence (AI) technology provides
hoteliers with effective solutions to improve
marketing tactics focused on decreasing churn rate and
boosting retention rate.
Through the utilization of AI, 5-star hotels can get
more profound understanding of customer behavior, preferences, and interaction
patterns.
This allows them to provide personalized experiences
and implement targeted marketing
strategies.
This research intends to explore the effectiveness of
AI-driven marketing strategies in reducing
customer turnover and promoting customer loyalty in
the luxury hospitality industry.
This study is guided by the following research
questions:
Main Research Question:
• How can 5-star hotels
effectively utilize AI-based customer persona
generation and customized marketing strategies to
reduce churn rate and boost retention
rate?
Additional research inquiries:
• What are the primary
elements that affect the churn rate and retention rate specifically in
the context of 5-star hotels?
• How might AI be
employed to categorize clients into various personas according to their
behavior, preferences, and characteristics?
• Which targeted
marketing methods can be employed, using these client personas, to reduce
churn and improve customer retention?
• What is the relative
efficacy of AI-driven marketing techniques in decreasing customer
turnover and improving customer retention compared to
traditional methods in the luxury
hospitality industry?
• What ethical issues
and best practices should be taken into account when implementing
AI-driven marketing strategies in 5-star hotels to
guarantee client privacy and fairness?
• What impact do new
developments and advancements in artificial intelligence and
marketing have on the future of customer relationship
management and retention strategies
in the luxury hotel industry?
Methodology:
Intro
The success of 5-star hotels in the modern hospitality
sector depends not only on providing
outstanding services and experiences, but also on
cultivating long-lasting connections with
customers to guarantee their ongoing loyalty.
This project aims to tackle the issues of customer
churn and retention in a highly competitive
market by utilizing artificial intelligence (AI)
technologies in marketing strategies specifically
designed to cater to the distinct requirements and
preferences of luxury hotel guests.
This section provides an overview of the methodology
used to examine the effectiveness of AI-
powered marketing strategies in reducing customer
churn and improving customer loyalty
(retention) in the setting of luxury hotels with a
five-star rating.
The methodology involves gathering and examining
customer data, utilizing spss to create customer profiles and predict customer
churn, executing customized marketing strategies, and assessing results in
terms of churn rate, customer retention rate, and
ethical considerations.
1. Data Collection:
Survey Design: Develop an extensive survey
questionnaire to gather data on customer
characteristics, inclinations, contentment levels, and
actions associated with luxury hotels.
Sampling Methodology: Utilize a stratified sample
method to guarantee the inclusion of various
consumer segments in the target population of
customers staying at 5-star hotels.
Sources of information: Gather survey feedback from
customers who have lodged at several luxury hotels with a five-star rating,
complemented by supplementary information such as their
reservation records and expenditure trends.
2. Analysis using SPSS:
Data preprocessing involves the cleaning and
preprocessing of survey data, which includes
addressing missing values, outliers, and category
variables.
3. Execution of Marketing Strategy:
Persona-Based Marketing: Create customized marketing
tactics specifically designed for each
customer persona found through machine learning
analysis.
Execute focused marketing efforts over several
channels, including as email, social media, and
loyalty programs, utilizing the insights obtained from
persona research.
Continuous Optimization: Continuously assess the
efficacy of marketing initiatives in real-time
and make iterative adjustments based on client input
and performance indicators.
4. Assessment:
The churn rate is determined by calculating the
percentage of customers who have ceased utilizing the services of a 5-star
hotel within a specified time frame, using survey responses and historical
data.
Retention Rate Calculation: Calculate the retention
rate by assessing the proportion of consumers
who persist in utilizing the services of a 5-star
hotel throughout the identical time frame.
Comparative Analysis: Assess the impact of AI-driven
marketing techniques on customer retention by comparing the churn rate and
retention rate before and after their implementation.
Ethical Considerations: Assess the ethical
consequences of employing artificial intelligence in
marketing, guaranteeing adherence to data protection
standards and equity in algorithmic decision-
making.
5. Plan for Creating Personas: Data Preparation:
Organize the data that has been cleansed and preprocessed for the purpose of
generating personas. This includes incorporating
important characteristics and consumer groups
that have been identified through clustering.
Persona Creation: Utilize k-means clustering to
generate 6-8 unique personas by analyzing client
attributes and activity patterns.
Persona Profiling: Generate comprehensive profiles for
each persona, encompassing demographic data, preferences, motives, and
prospective marketing tactics.
Validation: Verify the accuracy and effectiveness of
the created personas by conducting expert
evaluations and gathering input from stakeholders.
This process ensures that the personas
accurately represent the target audience and can be
effectively used in marketing efforts.
6. Constraints:
Sample Bias: Recognize the possible biases in the
survey sample, such as self-selection bias or
inadequate representation of specific client segments.
Assumptions of the model: Identify the underlying
assumptions and constraints of the machine
learning models employed for persona development and
churn prediction, encompassing the
adequacy and accessibility of the data.
Generalizability: Take into account the fact that the
research findings may be specialized to a
particular context and may not be easily applicable to
other industries or market segments.
7. Ethical Considerations:
Data Privacy: Guarantee the preservation of survey
respondents’ personal information by
maintaining their anonymity and confidentiality, while
also adhering to applicable data protection standards.
Transparency: Ensure the use of AI algorithms for
marketing reasons is transparent, including
explicit explanation of data usage and privacy
regulations to customers.
Equity: Alleviate prejudice in machine learning models
and marketing techniques to guarantee
impartial treatment of all client categories, irrespective of their
demographics or attributes.
Research Objectives:
The primary objective of this research is to examine the role of artificial intelligence (AI) in marketing activities, specifically focusing on customer acquisition, retention, and assurance within the hotel industry. Additionally, the study aims to understand individuals’ perceptions, concerns, and acceptance of AI-driven marketing tactics, particularly regarding data analysis and personalized push notifications.
Research Questions:
How do individuals perceive the use of AI in analyzing their personal data for marketing purposes within the hotel industry?
What are the main concerns and fears individuals have regarding AI-driven marketing tactics, particularly in relation to data privacy and security?
How do individuals respond to personalized push notifications based on data analyzed by AI in the context of hotel services?
To what extent do individuals understand the implications of AI-driven marketing activities on their consumer behavior and decision-making processes?
Research Method:
Given the nature of the research questions and the preference for an easy-to-analyze method, a quantitative approach is most suitable. 
Sampling Method:
A convenient sampling method can be employed, targeting individuals who have recently stayed at hotels. This approach allows for the recruitment of participants readily accessible to the researcher, facilitating data collection within the specified time frame.
Population/Target Group:
The target population includes individuals who have experience staying at hotels, spanning various demographics such as age, gender, occupation, and socioeconomic status. This diverse sample ensures the representation of different perspectives and opinions regarding AI-driven marketing in the hospitality industry.