- Overview
- Platform setup and administration
- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
- Connecting a customer-managed data lake
- Creating an AWS IAM role for Data Bridge
- Connecting a Snowflake data warehouse
- Connecting a Redshift data warehouse (public connectivity)
- Connecting a Redshift data warehouse (private connectivity)
- Reauthorizing a Snowflake OAuth connection
- Using Snowflake with Peak
- SQL Explorer overview
- Roles and permissions
- User management
- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Prepare and deliver the required data for the UiPath Commercial Pricing solution, including the product, customer, and pricing datasets needed to generate insights.
This page lists the data Commercial Pricing needs and what each dataset is used for. To connect your systems and load this data into the platform, see Data ingestion.
The solution works from data you already have — product and customer metadata, historical quotes, sales transactions, cost and list prices, and competitor and region context. During onboarding these are mapped and ingested from your existing systems; you don't create or edit them in the solution.
The solution then analyses win/loss behaviour, demand response, and margin trade-offs to generate pricing insights and recommendations for you to review and act on. The consistency and historical depth of your data directly affect how accurate those recommendations are.
How the solution uses your data
- Product and customer data define what's being priced and who it's sold to.
- Quote and sales data are the historical decisions and outcomes the solution learns from — win/loss behaviour, demand response, and pricing effectiveness.
- Cost and list price data give the financial context for weighing margin, revenue, and competitiveness.
- Region and merchant data add segmentation context, so pricing can differ across geographies and business units.
Required datasets
The following datasets are required to run Commercial Pricing.
| Dataset | Description | Dataset(s) in this guide |
|---|---|---|
| Products dataset | Stores detailed information about products, including identifiers, names, categories, bespoke status, and update timestamps. | Products dataset |
| Customers dataset | Stores key information about customers, including identifiers, names, and categorization. | Customers dataset |
| Merchants dataset | Stores merchant metadata, including identifiers and categorization. | Merchants dataset |
| Projects dataset | Stores project-level metadata used in pricing contexts. | Projects dataset |
| List price dataset | Stores product list prices for specific quote stages. | List price dataset |
| Product cost dataset | Stores cost price information for products. | Product cost dataset |
| Competitor prices dataset | Stores observed competitor pricing per product and region over time. | Competitor prices dataset |
| Quote line dataset | Stores quote-level line item data for pricing analysis. | Quote line dataset |
| Sales dataset | Stores completed sales transaction data for demand and performance analysis. | Sales dataset |
| Region dataset | Stores geographical region definitions used for pricing differentiation. | Region dataset |