Predictive Analytics

Predictive Marketing Analytics

1. ZAP Subscribe Swarit Yadav

2. Business Objective Increase the Revenue Increase the operational efficiency

3. Create model for dynamic pricing for App Create model for converting casual customers to registered Fleet Management Research Objective

4. Total Bikes- 100% Fleet-10000 Owned Bikes- 20% Operational Cost- $0.20/hour Leased Bikes- 80% Operational Cost- $0.10/hour Price Casual- $1/Hour Casual-Owned Bikes- $0.80/Hours Margin Casual-Leased Bikes- $0.90/Hours Margin Company Data

5. Company Data Registered - $0.5/Hour Registered-Owned Bikes- $0.30/Hours Margin Registered-Leased Bikes- $0.40/Hours Margin Operational Cost(At full Capacity) Owned fleet- 2000 * 0.2 = $400/hour (Fixed) Leased Fleet- 8000 * 0.1= $800/hour (Variable) Total- $1200/hour

6. Dynamic Pricing Project Predicting the demand on a particular day of week and predicting demand on hourly basis. Keeping in effect of weather conditions on that day

7. Deliverables Managing the fleet percentage Discount dropping event management to increase conversion of casual to registered Increased profitability by dynamic pricing for the App

8. Revenue Implications If the Leased fleet is reduced by 60% permanently Owned fleet- 2000 * 0.2 = $400/hour (Fixed) Leased Fleet- 4800 * 0.1= $480/hour (Variable) $11520/Day $345,600/Month $4.1 Million

9. Revenue Implications 4 Probability Casual-Owned Bikes- $0.80/Hours Margin Casual-Leased Bikes- $0.90/Hours Margin Registered -Owned Bikes- $0.30/Hours Margin Registered-Leased Bikes- $0.40/Hours Margin

10. Dynamic Pricing and Cross supplementing Demand vs. Fleet Price Users Owned( OC $0.2) Profit Leased(OC $0.10) Profit Casual $1 200 $40 $160 $20 $180 Registered $0.5 800 $160 $240 $80 $320 Matrix 1 : Unsorted Allocation(Currently used) Matrix 2 : Casual(Owned)+Registered(Leased)=$420/hour Matrix 3 : Casual(Leased)+Registered(Owned)=$480/hour

11. Thank You! Presented by- Shruti Tryambak Swarit Yadav Kajal Chauhan