Case study · Logistics & Mobility
Supply, risk and customer-experience analytics at Porter
Forecasting, a supply-performance score and risk analytics that lifted Fulfillment Rate by 4% and cut Tickets per Order from 4 to 0.6.
- Fulfillment Rate
- +4%
- Tickets per Order
- 4 → 0.6
- Porter Prime adoption
- Company-wide
Context
In a logistics marketplace, the unit economics depend on matching demand with the right supply at the right time, and on keeping bad debt and support costs under control.
What we built
Demand and supply forecasting
We built demand and supply forecasting models and led supply-management analytics covering driver and fleet planning and allocation. Better matching of supply to demand lifted Fulfillment Rate by 4%.
Porter Prime
Porter Prime is a score-based supply-performance model. It gave the business an objective, shared way to evaluate supply quality, and it was adopted as a company-wide benchmark.
Risk & fraud analytics
We stood up a risk and fraud analytics capability that reduced bad debt and revenue leakage across the marketplace.
Customer experience
Analysis of support drivers helped cut Tickets per Order from 4 to 0.6. That materially improved customer experience and reduced support load.
Product and customer foundations
- Set up a Product Analytics function with event instrumentation, tracking-plan standards and an A/B testing framework.
- Built a Customer Data Platform (CDP) that provides unified customer profiles and segmentation for targeted marketing and personalization.