Scenario:
Data in Motion Travel Analytics is a consulting firm that specializes in providing data-driven insights to tourism companies. A major tourism company has approached Data in Motion Travel Analytics to gain insights into their customer base, optimize their marketing strategies, and improve their product offerings. The dataset provided by the company contains information about various customers who were pitched different tourism products.
Detailed Overview:
The dataset encompasses a range of customers, from those who have made just one trip to frequent travelers, and from solo travelers to families. The diverse customer data showcases information about the customer’s demographics, their preferences, their interactions with the company’s sales team, and their buying behaviors.
The primary goal of the analysis is to help the tourism company:
- Understand their customer base better.
- Optimize their marketing and sales strategies.
- Design and pitch products more effectively.
Deliverables
You can analyze the data in any tool you like (Tableau, Power BI, python, R, Excel, etc.) But, your manager would like a dashboard. The dashboard will be used by upper management to monitoring performance.
She would also like for you to generate a slide deck to present your analysis and recommendations to the VP of Marketing of the company. She would like to know the factors that impact attrition and which areas of the company are impacted the most.
The slide deck can be done in Google Slides, PowerPoint, or any other tool. Just save it as a PDF.
Get the Data
Download the data and data dictionary here.
Challenge Questions:
Exploratory Data Analysis (EDA):
- How is the age distribution of our customers?
Relevance: Understanding the age distribution helps in tailoring product offerings more effectively. - What is the correlation between Monthly Income and Number of Trips made?
Relevance: This can provide insights into whether income level affects the frequency of travel. - Which occupation type tends to have the highest pitch satisfaction scores?
Relevance: Knowing this can help in customizing pitches for different occupational groups.
Customer Segmentation
- Can you segment customers based on their demographics and travel preferences?
Relevance: Creating customer segments can help in more personalized marketing and product design. - Which segment of customers is most likely to purchase a product after a pitch?
Relevance: Identifying high-conversion segments allows for more targeted marketing efforts. - How does monthly income influence product choice among different occupations?
Relevance: By analyzing the relationship between income, occupation, and product choice, businesses can better understand the purchasing power and preferences of their customers.
Predictive Analytics
- How does the duration of the pitch affect the likelihood of a product being taken?
Relevance: This can guide the sales team on optimizing their pitch duration.
Marketing Optimization
- Which type of contact (Self Enquiry vs. Company Invited) results in a higher conversion rate?
Relevance: Understanding the most effective channels for customer acquisition can optimize marketing spend. - How do different city tiers contribute to sales? Is there a specific city tier that the company should focus on?
Relevance: This helps in region-specific marketing campaigns. - Among customers who prefer higher-star properties, how does the type of product pitched and number of follow-ups influence the decision to purchase?
Relevance: This analysis can help businesses understand the effectiveness of their sales strategies, especially for high-value customers. If certain products or follow-up techniques result in higher conversions for luxury-seeking customers, businesses can allocate resources more efficiently.
Submission Instructions
Post your solutions in the Look What I Did discussion group. I am looking forward to seeing your submissions.