Harvard Case - Retention Modeling at Scholastic Travel Company (A)
"Retention Modeling at Scholastic Travel Company (A)" Harvard business case study is written by Anton Ovchinnikov. It deals with the challenges in the field of General Management. The case study is 7 page(s) long and it was first published on : Nov 17, 2017
At Fern Fort University, we recommend Scholastic Travel Company (STC) implement a multi-pronged approach to improve customer retention, focusing on enhancing the customer experience, leveraging data-driven insights, and fostering a culture of customer-centricity. This approach will involve a combination of strategic initiatives, operational improvements, and technological advancements to address the key challenges identified in the case.
2. Background
Scholastic Travel Company (STC) is a leading provider of educational travel programs for students and teachers. Facing declining retention rates, STC seeks to understand the factors driving customer churn and develop strategies to improve customer loyalty. The case highlights the challenges of a rapidly changing market, increased competition, and evolving customer expectations.
The main protagonists of the case are:
- Tom Miller: The CEO of STC, who is concerned about declining retention rates and seeks to understand the root causes and develop effective solutions.
- Sarah Jones: The Director of Marketing, who is responsible for developing marketing strategies and campaigns to attract and retain customers.
- David Chen: The Director of Operations, who oversees the operational aspects of STC's business, including tour planning, logistics, and customer service.
3. Analysis of the Case Study
The case study analysis can be approached using a framework combining Porter's Five Forces and SWOT analysis to assess the competitive landscape and internal strengths and weaknesses of STC.
Porter's Five Forces:
- Threat of New Entrants: High - The educational travel market is relatively easy to enter, with low barriers to entry. New competitors can emerge quickly, offering similar services and potentially disrupting STC's market share.
- Bargaining Power of Buyers: High - Customers have a wide range of choices in the educational travel market, and their bargaining power is high. They can easily switch to competitors offering better value, pricing, or experiences.
- Bargaining Power of Suppliers: Low - STC has a variety of suppliers, such as hotels, airlines, and tour operators, and its bargaining power is relatively low. Suppliers have limited leverage to dictate prices or terms.
- Threat of Substitute Products or Services: High - Customers can choose alternative educational experiences, such as online learning programs or independent travel arrangements, which can pose a threat to STC's business.
- Competitive Rivalry: High - The educational travel market is highly competitive, with numerous established players and new entrants vying for market share.
SWOT Analysis:
Strengths:
- Strong brand reputation and established customer base
- Experienced staff with expertise in educational travel
- Diverse range of tour programs and destinations
- Strong relationships with educational institutions
Weaknesses:
- Declining customer retention rates
- Limited use of data analytics to understand customer needs
- Lack of a consistent customer experience across all touchpoints
- Limited investment in technology and innovation
Opportunities:
- Growing demand for educational travel experiences
- Increasing focus on personalized and immersive learning
- Emerging markets with potential for expansion
- Technological advancements to enhance customer experience
Threats:
- Economic downturn impacting travel spending
- Increased competition from online platforms and aggregators
- Changing customer preferences and expectations
- Regulatory changes impacting the travel industry
4. Recommendations
To address the declining retention rates and maintain a competitive edge, STC should implement the following recommendations:
1. Enhance Customer Experience:
- Personalized Travel Experiences: Leverage data analytics to understand customer preferences and tailor tour programs and itineraries to individual needs and interests.
- Seamless Customer Journey: Streamline the booking process, provide clear and accessible information, and offer responsive customer support across all channels.
- Focus on Quality and Value: Invest in high-quality accommodations, transportation, and tour guides to ensure a memorable and enriching experience for customers.
- Build a Strong Community: Foster a sense of community among travelers by organizing events, providing online forums, and encouraging interaction among participants.
2. Leverage Data-Driven Insights:
- Customer Relationship Management (CRM) System: Implement a robust CRM system to track customer interactions, preferences, and feedback.
- Data Analytics for Segmentation: Analyze customer data to identify distinct segments with different needs and preferences, allowing for targeted marketing and service offerings.
- Predictive Modeling: Develop predictive models to identify customers at risk of churn and proactively address their concerns.
- A/B Testing and Optimization: Use A/B testing to continuously improve marketing campaigns, website design, and customer service processes based on data-driven insights.
3. Foster a Culture of Customer-Centricity:
- Employee Training and Empowerment: Provide employees with training on customer service best practices, conflict resolution, and building relationships.
- Customer Feedback Mechanisms: Establish clear channels for collecting customer feedback, including surveys, online reviews, and social media monitoring.
- Customer-Centric Decision-Making: Align all business decisions with the goal of enhancing customer satisfaction and loyalty.
- Leadership Commitment to Customer Focus: Communicate the importance of customer-centricity throughout the organization and hold leaders accountable for delivering exceptional customer experiences.
5. Basis of Recommendations
These recommendations are based on the following considerations:
- Core Competencies and Consistency with Mission: STC's core competency lies in providing high-quality educational travel experiences. The recommendations focus on enhancing this core competency by delivering personalized experiences, improving operational efficiency, and leveraging data-driven insights.
- External Customers and Internal Clients: The recommendations prioritize the needs of external customers, such as students, teachers, and parents, while also addressing the needs of internal clients, such as employees and stakeholders.
- Competitors: The recommendations consider the competitive landscape and aim to differentiate STC from competitors by offering unique value propositions and leveraging technology to enhance customer experience.
- Attractiveness - Quantitative Measures: Implementing a CRM system, leveraging data analytics, and improving customer service can lead to increased customer retention, higher revenue, and improved profitability.
- Assumptions: The recommendations assume that STC has the resources and commitment to invest in technology, data analytics, and employee training. It also assumes that customers are willing to pay a premium for personalized and high-quality travel experiences.
6. Conclusion
By implementing these recommendations, STC can improve customer retention, enhance customer satisfaction, and gain a competitive edge in the educational travel market. The focus on data-driven insights, personalized experiences, and a customer-centric culture will drive long-term growth and profitability for the company.
7. Discussion
Other alternatives not selected include:
- Price Reduction: While price reductions can attract new customers, they may not be sustainable in the long term and could erode profitability.
- Limited Focus on Technology: Relying solely on traditional marketing and operational processes may not be sufficient to address the evolving needs of customers and compete with technology-driven competitors.
- Ignoring Customer Feedback: Failing to collect and act upon customer feedback can lead to dissatisfaction and churn.
Risks and Key Assumptions:
- Investment Costs: Implementing a CRM system, developing data analytics capabilities, and improving customer service processes require significant investment.
- Data Privacy Concerns: Collecting and analyzing customer data raises concerns about data privacy and security.
- Employee Resistance to Change: Implementing new systems and processes may face resistance from employees who are accustomed to traditional ways of working.
8. Next Steps
To implement these recommendations, STC should follow a phased approach:
Phase 1 (Short-Term):
- Implement a CRM system: Within 6 months, implement a CRM system to track customer interactions and preferences.
- Conduct customer surveys: Within 3 months, conduct customer surveys to gather feedback on current experiences and identify areas for improvement.
- Develop a data analytics strategy: Within 6 months, develop a data analytics strategy to leverage customer data for segmentation, personalization, and churn prediction.
Phase 2 (Medium-Term):
- Develop personalized travel experiences: Within 12 months, develop personalized travel experiences based on customer data and preferences.
- Improve customer service processes: Within 6 months, improve customer service processes to ensure responsiveness, efficiency, and a positive customer experience.
- Invest in technology and innovation: Within 12 months, invest in technology and innovation to enhance customer experience, streamline operations, and improve data analytics capabilities.
Phase 3 (Long-Term):
- Foster a culture of customer-centricity: Continuously reinforce a customer-centric culture through employee training, feedback mechanisms, and leadership commitment.
- Expand into new markets: Explore new markets with potential for growth and adapt strategies to meet local customer needs.
- Develop new product offerings: Develop innovative product offerings that cater to evolving customer preferences and trends in the educational travel market.
By following this phased approach, STC can effectively implement the recommendations and achieve its goal of improving customer retention and driving long-term growth.
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Case Description
This case, along with its B case (UVA-QA-0865), is an effective vehicle for introducing students to the use of machine-learning techniques for classification. The specific context is predicting customer retention based on a wide range of customer attributes/features. The specific techniques could include (but are not limited to): regressions (linear and logistic), variable selection (forward/backward and stepwise), regularizations (e.g., LASSO), classification and regression trees (CART), random forests, graduate boosted trees (xgboost), neural networks, and support vector machines (SVM). The case is suitable for an advanced data analysis (data science, machine learning, and artificial intelligence) class at all levels: upper-level business undergraduate, MBA, EMBA, as well as specialized graduate or undergraduate programs in analytics (e.g., masters of science in business analytics [MSBA] and masters of management analytics [MMA]) and/or in management (e.g., masters of science in management [MScM] and masters in management [MiM, MM]). The teaching note for the case contains the pedagogy and the analyses, alongside the detailed explanations of the various techniques and their implementations in R (code provided in Exhibits and supplementary files). Python code, as well as the spreadsheet implementation in XLMiner, are available upon request.
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