Shipping Cost Analyzer

Pro v1.0.0 1 view

Analyze shipping invoices from multiple carriers to identify cost optimization opportunities with specific savings estimates.

What You Get

Get prioritized recommendations for carrier routing, service level optimization, and dimensional weight reduction with estimated monthly and annual savings.

The Problem

Logistics managers and ecommerce businesses struggle to optimize shipping costs across multiple carriers. They lack visibility into which carrier is cheapest for different zones, can't easily spot billing anomalies, and don't have data-driven negotiation leverage. Freight shippers face sudden cost spikes from NMFC reclassifications without understanding root causes.

The Solution

This skill consolidates multi-carrier shipping invoices into unified analysis, comparing carrier costs by zone and service level. It uses statistical anomaly detection to flag overcharges, identifies dimensional weight penalties, and generates actionable recommendations with specific savings estimates. The output includes carrier routing rules, negotiation talking points, and implementation timelines.

How It Works

  1. 1 Parse and validate shipping invoice CSVs with fuzzy column matching for FedEx, UPS, USPS, DHL, and freight carriers
  2. 2 Normalize data across carrier formats and calculate derived metrics (cost per pound, dim weight penalties, base costs)
  3. 3 Perform aggregate analysis by carrier, zone, service level, and time period
  4. 4 Benchmark carriers for similar shipments and identify optimal routing by destination zone
  5. 5 Detect anomalies using statistical methods (100+ shipments) or threshold-based methods (smaller datasets)
  6. 6 Generate prioritized optimization recommendations with estimated monthly and annual savings
  7. 7 Format professional executive-ready report with implementation timeline

What You'll Need

  • Shipping invoice data in CSV format from one or more carriers
  • Required columns: Date, Weight, Cost (plus carrier identification and zone/destination info)
  • Python 3 with pandas for data processing