Telemarketing is a strategy marketers commonly use to promote products or services to customers because it is more cost effective than conducting roadshows. Banks, too often adopt telemarketing. But, this pool of customers may be too huge and contacting all of them is extremely resource intensive and inefficient. Hence, if banks can find out who among this pool of customers are more likely to subscribe, and target them, banks can stretch their marketing expenses to the fullest, which in turn increase sales revenue and thus profits.
Future work:
- Among those who subscribed, how do u ensure they would not be exhausted from frequent/lengthy engagement (i.e. avoid customer fatigue)
Accompanying article: Optimising customer engagement efforts using machine learning: Application on retail banking
├── README.md
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
│
├── models
│
├── notebooks
│
├── references
├── reports
│ └── figures
│
├── test-campaign <- build flask app and deploy on Heroku
│
Data obtained from: https://www.kaggle.com/psvishnu/bank-direct-marketing
Project based on the cookiecutter data science project template. #cookiecutterdatascience