Intelligent Prescriptive Pricing

The client faced challenges in analyzing variables that impact pricing and required an intelligent system that would predict the optimal price that aligns with business objectives. There was a need to improve efficiency in the existing RFP and pricing workflow.

• Delays in determining lane-level pricing and bid analysis for shipping contracts
• Analyzing large amounts of internal and external data from various sources was time-consuming
• Low bid win rate

A cloud-based solution that ensures lane/pricing standardization, automates qualification, and integrates predictive pricing for informed decision-making. The solution does this based on changing scenarios and predicts the right outcome with a high level of accuracy.

The solution comprises three modules:

• Shipper file processing
• Pricing advisory
• Market intelligence

The solution enables stakeholders to upload the shipper's RFP and adjust settings such as tender ID, date, origin, industry, destination, mode, services among other parameters. The pricing advisory and market intelligence modules join forces to help streamline the end-to-end pricing process by validating prices from globally indicated benchmarks leveraging AI/ML capabilities.

• 43% increase in overall bid win rate
• 95% faster quoting by enabling standardized pricing across bids
• Highly accurate pricing forecasts with real-time insights
• Automated assignment of lanes based on custom stakeholder criteria

• Real-time view of current bid value and RFP progress, offering a unified source for pricing and dynamic factors. Data is consistently formatted across the organization providing a comprehensive analysis of margins and awards.
• Visualization of historical rates and factors that impact pricing — empowers analysts to quickly compare rates and margins for accurate bidding.
• Automated pricing recommendation leveraging market data, customer data, and business heuristics to estimate pricing that optimizes RFP win rate and overall profitability.

• Google AI
• AWS
• RDS Postgres
• ReactJS, Node.js
• React Native
• EKS
• S3
• Cloudflare
• RabbitMQ
• Docker
• Kubernetes
• Python Pandas
• Naive Bayes - Probability classifier
• TF-IDF based on mono, bi, and trigrams
• Scikit-learn
• Visualization - Histogram