How does Intuilize's price optimization solution work?

Exploring the AI-powered price optimization process that helps distributors increase margins and improve pricing consistency

Intuilize's price optimization tool uses advanced AI and proprietary analytics models  to analyze your past transaction data and recommend the best pricing options.

Here's how it works:

Data Analysis and Pattern Recognition Our AI engine analyzes your sales history, looking at every line item which includes the product, customer, quantity, and price. The system identifies patterns in your pricing behavior, understanding how you price specific products to specific customers at various volume breaks.

Customer and Product Segmentation The system automatically segments your customers into categories:

• Core: Your most valuable, strategic customers
• VIP: Growing customers with high potential
• Standard: Regular customers with consistent purchasing patterns
• Drain: Customers with high service demands and low profitability
• Dormant: Inactive customers who haven't purchased recently

Products are also segmented based on factors like sensitivity, competition, and strategic importance.

Price Optimization Calculations For a typical distributor, our AI model runs millions of combinations (sometimes 40-160 million) to determine the optimal pricing for each product-customer combination. The system considers:

• Price sensitivity for each product
• Customer purchasing behavior
• Competitive factors
• Volume breaks
• Strategic importance
• Win rate probability

Pricing Recommendations Based on this analysis, Intuilize provides specific pricing recommendations designed to optimize your gross margin while maintaining sales volume. The system can:

• Update pricing multipliers or discounts in your ERP system
• Create custom price pages for specific customers
• Apply different strategies for different customer segments
• Adjust pricing based on changing market conditions

Performance Tracking Once implemented, the system tracks the performance of the price recommendations, measuring:

• Adoption rate by salespeople
• Override frequency and reasons
• Gross margin lift achieved
• Win rate at different price points

This creates a continuous improvement cycle, with the AI learning from each transaction to refine future pricing recommendations.