From Forecast to Execution: Bringing More Insight and Connectivity to Pricing and Revenue Management

Commercial teams are being asked to make better decisions in an environment where demand, costs, purchasing volumes, and capacity can change quickly. But anticipating change is only part of the challenge. Organizations also need to translate insight into pricing and revenue decisions, then execute those decisions efficiently across commercial workflows. 

The latest innovations across Conga’s pricing and rebate management capabilities are designed to help organizations close that gap. From AI-powered forecasting and more sophisticated price book management to connected rebate workflows and new revenue optimization capabilities for freight, cargo, and logistics companies, these enhancements help teams move from understanding what is happening to anticipating what may happen next and acting on those insights. 

Look Ahead with AI-Powered Insights for Smarter Commercial Planning 

Many commercial decisions depend on understanding how important business variables may evolve over time. Historically, that can mean relying on spreadsheets, manual trend analysis, and backward-looking data. 

Time Series Forecasting (TSF) introduces an AI-powered way to generate forward-looking predictions from an organization’s own historical business data. Users can configure forecast entities and relevant business variables to generate forecasts at the level of detail their business requires. 

For pricing and revenue teams, the value goes beyond forecasting itself. TSF can support use cases spanning demand, cost, revenue, volume, capacity, and utilization forecasting, helping organizations identify important trends and potential deviations earlier and incorporate that insight into commercial planning. With better forward visibility, teams can use these data-driven insights to inform decisions across pricing and revenue planning, inventory, and rebate management. 

Organizations can use Time Series Forecasting to:

• Improve forecast accuracy with AI-powered predictions. 
• Support more proactive pricing and revenue decisions by anticipating demand and cost movements earlier. 
• Strengthen commercial planning by identifying trends and anomalies that could affect business performance. 
• Reduce reliance on manual and spreadsheet-based forecasting. 

The result is a shift from simply responding to historical performance toward using forward-looking insight to support more proactive commercial decisions. 

Scale Account-Specific Pricing with Enhanced Price Book Management 

Accurate pricing is only valuable if organizations can communicate and operationalize it effectively for the right customers and channels. 

Enhanced Price Book Management gives organizations greater flexibility to create and manage sophisticated account-specific price books by defining pricing recipient types. These are configurable categories of business entities that independently define which accounts receive the price book and how pricing within it is structured, enabling businesses to support complex pricing models across different customer, product, channel, geographic dimensions, etc. The enhancements also connect Price Book Management with Conga Document Automation, helping organizations generate formatted, account-specific price lists. 

With the enhanced Price Book Management, organizations can: 

• Support more complex pricing structures by independently defining price book recipients and the level at which pricing is organized. 
• Automate pricing document generation and formatting, reducing manual effort and maintenance. 
• Improve account-specific pricing accuracy and governance, supporting more consistent pricing communications across their customers and channels. 

For manufacturers and distributors managing complex customer, regional, and channel pricing, this provides a more scalable path from pricing strategy to execution. 

Connect Rebates Directly to the Deal with Smart CPQ and Agreements 

Pricing decisions don’t happen in isolation. Negotiated incentives, quotes, and contractual commitments can all affect the economics of a deal. When those elements are managed separately, sellers may need to move between systems and manually reconcile information. 

New integration between Conga Rebate Management, Smart CPQ, and Agreements brings rebate information directly into quote-to-agreement workflows. 

Sellers can see applicable incentives, create and link rebates, and assess their impact while structuring a deal, rather than managing rebates as a separate downstream process. This helps create a more connected view of pricing, incentives, and contractual commitments during sales negotiations. 

The connected workflow can help organizations: 

• Give sellers visibility into applicable rebates during quoting. 
• Understand rebate impact as part of deal economics. 
• Create and link rebates within quote-to-agreement workflows 
• Reduce system switching and manual calculations. 
• Improve consistency between negotiated incentives and agreements. 
• Support faster, more transparent negotiations and stronger margin protection. 

For businesses managing complex customer agreements and volume commitments, connecting these decisions can help sales, deal desks, and commercial operations teams execute deals with greater visibility into pricing, incentives, and their impact. 

Make Smarter Capacity and Revenue Decisions in the Freight, Cargo, and Logistics Industry 

For air cargo organizations, optimizing revenue requires teams to balance shipment demand with finite flight capacity. Revenue managers need visibility into remaining capacity and bid-price behavior, as well as the ability to evaluate potential actions before executing them. 

The new Capacity Steering Workflow brings those activities together in a dedicated revenue management experience. Revenue managers can now visualize available flight capacity, simulate bid-price levels, analyze bid-price development based on days to departure and remaining capacity, apply their own steering strategies, and pass approved pricing decisions into Conga Price Management. 

This helps revenue management teams: 

• Identify flights and capacity that may require action. 
• Evaluate bid-price and capacity trade-offs. 
• Simulate scenarios before applying steering decisions. 
• Prioritize higher-value revenue opportunities, helping to improve capacity utilization and yield. 
• Move more efficiently from analysis to pricing execution. 

The goal is to give cargo revenue teams a more connected way to manage the relationship between capacity, pricing, and revenue performance without relying on fragmented analysis. 

Overbooking Optimization is also being enhanced to give air cargo revenue teams more information and granularity for overbooking decisions. The enhancements incorporate additional shipment attributes from each carrier’s own booking data, including product and commodity information, to help improve materialization-rate predictions, while adding asset-class-level optimization to support more granular utilization decisions across different asset types. 

Together, these enhancements help revenue teams: 

• Improve materialization-rate predictions using additional shipment information. 
• Make more granular overbooking and utilization decisions at the asset-class level. 
• Better manage available capacity. 
• Support stronger revenue performance across asset types. 

From Predicting Change to Acting on It 

Together, these innovations address different stages of the commercial decision process. The common thread is a shift from fragmented analysis and execution toward more connected commercial decision-making. 

By connecting forward-looking insight with pricing, incentives, agreements, and execution, Conga continues to expand how organizations can use their own data and AI to make better-informed commercial decisions and operationalize them across the commercial lifecycle. 

If you’re interested in learning more, or seeing these capabilities in action, book a demo today.