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AI-Driven Price Prediction System for Construction Material Trading

neoteric.eu

Construction

Trading

Logistics

Challenges in Dynamic Market Pricing and Profitability

The client faces unpredictable market fluctuations affecting material prices, currency rates, and delivery times. These factors hinder data-driven decision-making, leading to reliance on intuition-based pricing, reduced profit margins, and difficulty customizing offers for customers.

About the Client

A European market leader in construction material trading, focused on competitive pricing, fast delivery, and tailored customer services.

Key Project Objectives

Develop an AI-powered predictive model for accurate order price estimation
Enable sales teams to provide precise customer quotes using real-time data
Validate AI's effectiveness in addressing market volatility and improving profitability

Core System Functionalities

Predictive modeling for order value estimation based on historical and real-time data
RPA-driven external data sourcing (competitor pricing, stock exchange rates)
CSV/email workflow integration for sales team accessibility
Real-time market data updates for dynamic pricing adjustments

Preferred Technologies

AI Predictive Models

Robotic Process Automation (RPA)

Required System Integrations

CRM systems for customer data
Stock exchange APIs for material pricing
Competitor pricing databases
ERP systems for delivery time tracking

Non-Functional Requirements

Scalability to handle fluctuating market data volumes
95%+ prediction accuracy for order estimates
Data security for sensitive pricing information
User-friendly interface for sales team adoption

Expected Business Impact

A 30% increase in profit margins within 12 months through reduced pricing errors, improved customer satisfaction from accurate quotes, and streamlined sales processes enabled by AI-driven insights.