Optimize pricing
and protect margins
AI recommends optimal pricing per customer and product, enforces discount guardrails, and simulates P&L impact before you commit - so margins are protected by data, not guesswork.
From gut-feel discounting to data-backed margin protection
Pricing in most organisations is often static - set during annual reviews and adjusted reactively when margins erode. Discounting decisions are made by sales reps under pressure, with no visibility into the cumulative margin impact. A 5% discount on a high-volume product can cost hundreds of thousands in annual margin, but nobody models this before saying yes.
KFactory's Pricing & Margin Engineer analyses historical pricing, customer willingness-to-pay signals, segment profitability, and competitive positioning to recommend optimal pricing per customer and product. Discount guardrails enforce maximum thresholds without approval - "Discount cannot exceed 8% without manager sign-off." Before any pricing change is committed, the system simulates the P&L impact: revenue change, margin impact, and volume sensitivity.
The result: pricing decisions backed by data instead of intuition. Sales teams know their boundaries, managers see the margin impact in real time, and the business stops leaving money on the table.
What you can expect
Protect margins with data-backed pricing. Simulate P&L impact before committing.
Based on pricing optimization benchmarks for B2B operations. Companies implementing AI-driven pricing typically see 2-5% margin improvement (McKinsey). Use the impact calculator to model your scenario.Beyond margin percentage gains, guardrails eliminate the invisible margin leakage that accumulates deal by deal. Every rep negotiates from the same AI-recommended baseline, and every manager approves discounts with full P&L visibility - not just the headline number.