Wellness Tourism Package Purchase Prediction Model
Overview
This model predicts whether a customer is likely to purchase a wellness tourism package based on demographic, travel behavior, and sales interaction information.
Business Problem
Travel companies spend significant effort pitching tourism packages to potential customers. This model helps identify customers with a higher likelihood of purchasing a package, allowing sales teams to prioritize outreach and improve conversion rates.
Input Features
- Age
- Type Of Contact
- City Tier
- Duration Of Pitch
- Occupation
- Gender
- Number Of Person Visiting
- Number Of Followups
- Product Pitched
- Preferred Property Star
- Marital Status
- Number Of Trips
- Passport
- Pitch Satisfaction Score
- Own Car
- Number Of Children Visiting
- Designation
- Monthly Income
Output
Binary Classification:
- 1 = Likely to Purchase
- 0 = Not Likely to Purchase
Deployment
The model is deployed through:
- Hugging Face Model Hub
- Hugging Face Spaces
- GitHub Actions CI/CD Pipeline
MLOps Architecture
Dataset Repository → Data Preparation → Model Training → Model Registry → Automated Deployment → Hosted Prediction Application
Author
Arjun Mathuram
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