AI-Enhanced Pricing Optimization

Region Global

Industry Manufacturing

Focus Area Pricing Analytics & Optimization

AI Involvement High (ML-driven price waterfall optimization)

Outcome Margin insights, optimized discounts, improved segmentation

Relevance to NexZ Basis of NexZ’s Pricing Advisory AI Agents

Overview

A multinational manufacturer was seeking advanced capabilities in pricing analytics to optimize its discounting and margin strategies. Our team led a pilot project focusing on price waterfall optimization.

Problem Statement

The client lacked visibility into margin leakages and struggled to apply consistent pricing rules across different markets and segments. Their internal data was underutilized, and they needed data-backed insights to improve pricing decisions.

Solutions

Applied machine learning to segment customers and products based on historical data and behavior.

Designed a rule-based price waterfall model to optimize list price, discount, and net price levels.

Configured AI-driven solvers to align price recommendations with business constraints and profit targets.

Delivered scenario simulations and visual insights to support decision-making.

Generated pricing proposals exportable to ERP or pricing systems for implementation.

Results

The pilot implementation empowered the client to uncover untapped pricing opportunities and inconsistencies across customer segments. Machine learning-driven segmentation revealed hidden behavioral patterns, and optimized price waterfall strategies led to more precise discounting and improved margin control. Within weeks, the client saw a measurable uplift in pricing accuracy, reduced manual interventions in pricing decisions, and built confidence in AI-assisted strategic pricing processes.

AI-Enhanced Pricing Optimization