Top-Selling Configurations Recommendations

Starting with Oracle CPQ 26B, CPQ will use machine learning to recommend top-selling configurations for configurable products, based on actual sales data from past transactions. This dynamic approach offers more commercially accurate and relevant suggestions compared to static Favorites defined by users.

• Significantly reduces the time sales users spend configuring products from scratch, leading to faster deal closures.

• Provides quicker, more efficient, and more complete configuration recommendations.

• Removes the need for manual analysis or custom solutions to identify well-selling product configurations, delivering better sales guidance directly within CPQ.

Steps to enable and configure

Refer to the Oracle CPQ Administration Online Help once this feature is generally available in Oracle CPQ Update 26B.