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AI-powered revenue optimization for modern CPG Leaders
Pricing, promotions, pack architecture, and trade investments are often managed in silos, which slows decision-making and obscures true incrementality, cannibalisation, and trade spend performance. Sigmoid iNRM unifies all revenue growth levers into a unified, analytics-driven view of pricing, promotions, mix, and trade terms; enriches it with predictive modelling; and enables cross-lever simulation while optimizing actions. With an agentic AI layer, commercial teams get always-on monitoring, instant diagnostics, and targeted recommendations embedded directly into decision workflows.
Sigmoid iNRM features
Integrated cross-lever framework
Connects pricing, promotions, PPA/assortment, and trade terms under a single analytical logic to eliminate silos and support more effective CPG pricing strategies.
AI-powered end-to-end planning and simulation
Brings together CPG-specific models, knowledge code-base, and planning tools to power scenario planning and insights across brands, channels, and retailers.
RGM-ready data foundation
Creates a harmonized, NRM-specific semantic layer by integrating POS, finance, promo, trade terms, panel, and digital commerce data with AI-powered matching and standardization.
Agentic AI command centre
Provides always-on monitoring, automated root-cause diagnostics, and recommended actions, embedded in daily workflows through alerts, dashboards, and conversational interfaces.
Persona-based decision work
Delivers tailored views and actions for RGM, sales, category, finance, and leadership teams, with guardrails and approval flows that align with your business decisions.
Rapid time-to-value deployment
Accelerate rollout with pre-configured analytics, reusable templates, and guided workflows that reduce implementation time and boost adoption across teams.
Sigmoid iNRM architecture enabling holistic revenue growth management
Sigmoid iNRM is powered by PRISM, a modular, cloud-native and AI-powered RGM suite that unifies diagnostics, simulation, optimization, and actioning into a single, integrated workflow. These four modules help commercial and RGM teams plan, test, and execute revenue strategies with speed, accuracy, and scale.
Model Outputs Dashboard | Diagnostic Layer
Granular model outputs across price, promo, assortment, and trade terms form the analytical foundation of revenue growth management. Teams can benchmark performance, understand demand drivers, and identify where value is being created or lost.
Cross-lever Simulation | Predictive Layer
Run integrated “what-if” scenarios across price changes, promo mechanics, pack shifts, and portfolio actions. The simulation engine quantifies upside, risk, and cross-lever dependencies that enable informed planning before execution.
Cross-lever Optimization | Prescriptive Layer
AI and advanced algorithms optimize revenue, margin, volume, and retailer KPIs within business guardrails. This engine identifies the most profitable combination of pricing, promo, mix, and trade strategies.
Agentic-AI Insights Edge | Intelligence Layer
Always-on monitoring and automated diagnostics deliver real-time alerts, root-cause insights, and recommended next actions, embedded into role-based workflows. This transforms NRM into a proactive, continuous capability.
Sigmoid iNRM pillars that orchestrate integrated planning and execution
Sigmoid iNRM enables commercial, RGM, category, and revenue teams to solve high-impact challenges across the full net revenue management spectrum.
Strategic Use-Cases that drive Revenue and Margin Growth
Sigmoid iNRM enables commercial, RGM, category, and revenue teams to solve high-impact challenges across the full net revenue management spectrum.
Pricing Analytics
Strengthen pricing decisions using advanced elasticity modelling, threshold price detection, competitive impact assessment, and portfolio cannibalization analysis. This provides the analytical rigor needed to shape modern CPG pricing strategies across markets, packs, and channels.
Promotion and Trade Optimization
Improve efficiency of promotional investments through baseline decomposition, uplift attribution, ROI evaluation, and long-term impact measurement. iNRM’s predictive and prescriptive capabilities support end-to-end trade promotion optimization and calendar planning with confidence.
Pack Price Architecture (PPA) & Assortment Optimization
Optimize portfolio mix with attribute importance insights, incrementality vs. transferability studies, switching behaviour matrices, and walk-rate analysis. These capabilities help teams design channel-specific PPA frameworks that maximize revenue and reduce duplication.
Trade Fund Management and Efficiency
Strengthen customer-level financial decisions with enhanced P&L visibility, fair-share evaluation, and trade spend benchmarking. iNRM helps identify overspend, under-investment, and true drivers of customer profitability that maximize ROI across trade promotion management and optimization programs.
Customer success story
Franchise transformation for a global food & beverage company with unified GTM budgeting and revenue-management across 22 LATAM markets
- ~ 7% incremental topline growth post-transformation
- 6.2 M in savings from reduced operating costs and lower risk during budgeting and execution cycles
- 9% improvement in ROI for cooperative investments across 8 core LATAM markets
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