Dark Mode
Wellness Tourism Customer Propensity Dataset
Mental Health & Wellness
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset aims to enable "Trips & Travel.Com" to establish a viable business model for expanding its customer base by efficiently targeting customers for a new "Wellness Tourism Package". The company previously faced high marketing costs due to random customer outreach, with only 18% of customers purchasing existing packages. By leveraging available customer data, this dataset supports the prediction of potential customers most likely to purchase the newly introduced travel package, thereby optimising marketing expenditure. Key indicators from the data suggest that customers with a Designation as Executive, possessing a passport, residing in Tier 3 cities, who are single or unmarried, and are involved in large businesses, have higher chances of purchasing new packages. Additionally, customers with a monthly income between 15,000 and 25,000, aged 15-30, and those who prefer 5-star properties also show a higher propensity to purchase. Wellness Tourism is defined as travel supporting the maintenance, enhancement, or initiation of a healthy lifestyle, and fostering an increased sense of well-being.
Columns
- CustomerID: A unique identifier for each customer.
- ProdTaken: Indicates whether the customer purchased the product (0 for No, 1 for Yes).
- Age: The customer's age, ranging from 18 to 61 years.
- TypeofContact: Describes how the customer was contacted, either 'Self Enquiry' (70%) or 'Company Invited' (29%).
- CityTier: The development tier of the customer's city (Tier 1, Tier 2, or Tier 3), based on factors like population and living standards.
- DurationOfPitch: The length of the sales pitch delivered to the customer by a salesperson, ranging from 5 to 127 minutes.
- Occupation: The customer's occupation, with 'Salaried' (48%) and 'Small Business' (43%) being the most common.
- Gender: The customer's gender, predominantly 'Male' (60%) and 'Female' (37%).
- NumberOfPersonVisiting: The total number of individuals planning to travel with the customer, ranging from 1 to 5.
- NumberOfFollowups: The total number of follow-up interactions performed by the salesperson after the initial pitch, ranging from 1 to 6.
- ProductPitched: The type of product package pitched by the salesperson, with 'Basic' (38%) and 'Deluxe' (35%) being common.
- PreferredPropertyStar: The customer's preferred hotel property rating, typically 3, 4, or 5 stars.
- MaritalStatus: The customer's marital status, with 'Married' (48%) being the most frequent.
- NumberOfTrips: The customer's average number of trips taken in a year, ranging from 1 to 22.
- Passport: Indicates if the customer possesses a passport (0 for No, 1 for Yes).
- PitchSatisfactionScore: A score reflecting the customer's satisfaction with the sales pitch, on a scale of 1 to 5.
- OwnCar: Indicates whether the customer owns a car (0 for No, 1 for Yes).
- NumberOfChildrenVisiting: The total number of children under 5 years old planning to travel with the customer, ranging from 0 to 3.
- Designation: The customer's designation within their current organisation, with 'Executive' (38%) and 'Manager' (35%) being common.
- MonthlyIncome: The customer's gross monthly income, with a mean of approximately 23.6k.
Distribution
This dataset is provided in CSV file format. The file size is 468.5 kB and it contains 20 columns. The dataset includes approximately 4888 records, although some columns may have a small percentage of missing values (e.g., Age has 5% missing, MonthlyIncome has 5% missing).
Usage
This dataset is ideal for building predictive models to identify customers most likely to purchase new travel packages. It can be used for customer segmentation, informing targeted marketing campaigns, and optimising marketing spend. Insights derived can also support recommendations for policy makers and marketing teams within the travel industry.
Coverage
The dataset reflects customer data, including demographics such as age (18-61), income (ranging from 1,000 to 98,700), marital status, gender, occupation, designation, and city tier. It also covers travel preferences, contact methods, and sales interaction details. The data points concerning previous package purchases relate to observations from the last year. There is no specific geographic scope mentioned beyond city tiers.
License
CC0: Public Domain
Who Can Use It
- Marketing Teams: To identify key customer segments for targeted campaigns for wellness tourism packages.
- Policy Makers: To formulate strategies for expanding the customer base and improving sales efficiency.
- Data Scientists/Analysts: To develop and evaluate machine learning models for customer purchase prediction.
- Business Strategists: To gain insights into customer behaviour and optimise product offerings.
Dataset Name Suggestions
- Customer Travel Package Purchase Prediction
- Wellness Tourism Customer Propensity Dataset
- Travel Customer Segmentation for New Offerings
- Trips & Travel Customer Conversion Data
Attributes
Original Data Source:Wellness Tourism Customer Propensity Dataset
QUALITY