Decision Flow Scenarios Based on Available Data (Agents)

Pricefx Agents capabilities depend on the data available, its level of detail, and how consistently products, customers, and commercial events are linked. Use the scenarios below to identify the appropriate setup.

Each scenario below explains the data condition (Data), why it matters (Why it Matters), and what to do about it (Advice).

Scenario	Product Data	Customer Data	Transaction or Quote Data	Trigger Condition	Main Advice
Standard Case	Product Id Product Name Hierarchy Relevant attributes	Customer Id Customer Name Hierarchy Geography	Line-item transactions with: Date Quantity Price Discounts Costs Margin, as total values Currency, UOM	Products, Customers, and Transactions are all present with stable IDs.	Start with the Curated Agents. Load core fields first. Add context fields incrementally.
Enhanced Standard Case	Standard product data plus cost, competition, stock, availability, or other commercial signals	Standard customer data	Standard transactions plus dated enrichment data	Standard case data is enriched with cost, competitive pricing, inventory, or other signals.	Document whether values are actual, estimated, or externally sourced. Define one canonical source per data type.
Limited Transactions and History	Product Ids and attributes where available	Customer Ids and attributes where available	Sparse or short-window transactions; quotes or datamart copies may supplement them	Transaction data is sparse, scoped to a subset, or covers less than a year; Quotes may supplement it.	State the coverage period and population explicitly. Do not treat Quotes as realized sales.
Configured products	Feature/option attributes or a configuration fingerprint; no stable product Id	Customer Id where available	Quote or transaction lines containing configuration features	Products lack a persistent Id and are instead defined by feature combinations.	Define which feature combinations make configurations comparable. Use a configuration fingerprint as a comparison key.
Limited Customer Data	Product Ids and attributes	Customer Ids with incomplete hierarchy or segmentation; optional cluster Id and label	Transactions linking products and customers	Customer IDs exist, but hierarchy, segment, or geography attributes are incomplete.	Use customer clustering to fill the gap. Document its inputs and treat it as enrichment, not master data.
Multiple Business Units and Currencies	Product definitions by business unit	Customer definitions by business unit	Transactions with: Business-unit scope Currency Dated exchange rates	One instance spans divisions with different policies or data definitions, possibly in different currencies.	Use one Agent per non-comparable division. Convert to a single reference currency with dated exchange rates.
Quote Only	Product Ids or configuration features where available.	Customer Ids and attributes where available.	Quotes with: Quote date Status Pricing Outcome indicators No realized transactions	Only Quote data is available. No realized transactions or insufficient transaction history exist.	Use the Flex Agents for deal velocity and price compliance. Copy Quote data into a Datamart for deeper analysis.

Decision-flow Diagram

Real data situations often overlap. The tree picks the first matching condition top-to-bottom, so it is a reading aid, not a strict algorithm.