Data Science Case study - Banking Campaign

Objective: Select 3,000 clients for the second round of an investment campaign based on data analysis.

Offer: Clients will receive a 1,000 CZK cash-back bonus directly deposited into their bank accounts in the second round.

Goal: Optimize the trade-off between costs (e.g., cash-back, campaign preparation time) and expected client investment to maximize revenue.

Phase 1 Deliverables: Use various modeling approaches to select client IDs. Submit a CSV file ("second_phase_target.csv") with the chosen IDs and an evaluation of expected campaign performance to [Email Address].

Phase 2 Task: Prepare a 10-minute presentation summarizing business insights from exploratory data analysis, modeling, and the second campaign run. Use dashboards for visualization. Compare expected and actual campaign performance. Evaluate the data-driven approach against random selection. Suggest a smarter strategy for client portfolio exploitation based on data insights.

Important Note: If short on time, prioritize completion and include a "Next Steps" section in the presentation. Also, share "Lessons Learned" for others' benefit.