Overview
Sales representatives and approvers need guidance in determining the 'right price' and ‘right discount’ which will maximize revenues and margins. In addition to controlling this discounting, customers need to reduce the cycle time, effort and cost of approvals; improve the quality of their quote data, and optimize their quoting process flow.
Deal Negotiation
Deal negotiation guides sales representatives in achieving optimal prices and discounts for their customers using analytics and metrics. Through metrics such as Price Scores and Last Price Paid, sales representatives can better negotiate prices to drive profitability. Administrators can select predefined calculations for price scoring, with results displayed graphically to sales representatives on Commerce Transaction and Transaction Line UIs. To further support deal negotiation, sales representatives can use the Deal Comparison Scatter Plot Analytic to display key price-related data for comparable Transactions and Transaction Lines. They can also use Time Series Analytics to display Transaction and Transaction Line pricing trends. For more information refer to the following topics:
Price Optimization
Price Optimization uses mathematical analysis to predict how customers will respond to different prices for products or services in order to optimize net revenue or margin. Oracle CPQ provides out-of-the-box machine learning price optimization and price guidance solutions. Since Oracle CPQ customers use different metrics to determine revenue and profitability, these features support selection of custom attributes to provide an easy, code free setup. Customers with low or zero marginal costs, such as software companies, can manage the discount percentages off standard list prices, without capturing costs or margins. Customers with meaningful variable costs, such as manufacturers, can capture costs and margins in CPQ, and manage either net revenue or margin percentages. For more information refer to the following topics:
See Also
