Inspiration
Singlife has observed a concerning trend in the customer journey: potential policyholders are expressing hesitation and eventual disengagement during the insurance acquisition process. To address this, Singlife seeks to leverage its dataset.
What it does
The objective is to derive actionable insights from this data to enhance the customer experience. The challenge is to dissect the dataset to uncover the critical touchpoints that conss and personalise communication. The ultimate goal is to predict customer satisfaction tribute to customer drop-off and identify opportunities to streamline the application process and conversion rates, thereby bolstering Singlife's market position.
How we built it
Exploratory data analysis of the raw data such as data cleaning, null value analysis, statistical analysis, data visualization. Modelling conducted using XG boost with 5 fold stratified k fold validation.
Built With
- matplotlib
- pandas
- python
- scikit-learn
- xgboost
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