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1 Introduction to Rules Based Regular Pricing
Oracle Retail Lifecycle Pricing Optimization (LPO) Cloud Service enables retailers to manage pricing across the full product lifecycle recommending regular prices, promotions, markdowns, and targeted offers that align with planned business objectives.
LPO supports two approaches for generating regular price recommendations:
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Forecast-Based Regular Pricing
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Rules Based Regular Pricing
This guide covers only Rules Based Regular Pricing, which uses configured Non-Forecast (N/F) pricing rules and available pricing, cost, competitor, merchandise, and location data to generate regular price recommendations without relying on demand forecasting.
For Oracle Retail Pricing Cloud Service (PCS) customers, this guide explains how to use the Rules Based Regular Pricing workflow in Oracle Retail Lifecycle Pricing Optimization (LPO) to create runs, review rules-based recommendations, and manage regular price actions through approval and export.
What is Rules Based Regular Pricing?
Rules Based Regular Pricing is an LPO mode that derives regular price recommendations from business rules and current operational data, such as current prices, costs, and competitor prices. It does not require forecast model training, demand parameters, or base period configuration.
The rules based engine evaluates each item against the active Non-Forecast (N/F) rules in the selected strategy. If all applicable constraints cannot be satisfied at the same time, the engine resolves rule conflicts based on rule type and priority and returns the Best Feasible Solution, which is the regular price recommendation that best satisfies the configured rules.
Forecast-Based vs Rules Based Regular Pricing
The table below summarizes the key differences between the two Regular Pricing modes available in LPO.
Table 1-1 Dimension - Forecast-Based Regular Pricing
| Dimension | Forecast-Based Regular Pricing | Rules-Based Regular Pricing |
|---|---|---|
| Forecast Dependency | Requires trained demand model and approved forecast. | None. No forecast setup required. |
| Rule Types Used | Both F and N/F rules. | N/F rules only. F rules in strategy are silently ignored. |
| Primary Decision Driver | Forecasted business outcomes | Business rules and constraints |
Rules Based Regular Pricing User Guide G58167-03 Copyright© 2026, Oracle and/or its affiliates.
Table 1-1 (Cont.) Dimension - Forecast-Based Regular Pricing
| Dimension | Forecast-Based Regular Pricing | Rules-Based Regular Pricing |
|---|---|---|
| Typical Use Cases | Strategic pricing: New item introduction, season entry/exit, demand-driven pricing. | Operational pricing: Competitor response, cost pass-through, margin guardrails, price consistency. |
When to Use Rules Based Regular Pricing?
Rules Based Regular Pricing is best suited for retailers who need fast, operationally driven regular price updates without the overhead of forecast model training.
Note
Rules Based Regular Pricing Optimization is available only when the following configuration flag is enabled: PRO_LPO_REGULAR_LITE_ENABLED_FLG .
Common use cases include:
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New-to-forecast retailers who have not yet completed LPO forecast model configuration and need to begin generating price recommendations immediately.
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Responding quickly to competitor price changes. For example, maintaining a price that is always within 5% of a key competitor.
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Passing through cost increases or decreases. For example, automatically reflecting a supplier cost increase in the item’s regular price.
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Enforcing margin guardrails. For example, ensuring no item in a category falls below a 22% list margin.
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Maintaining price consistency across locations or items. For example, ensuring the same item in Zone A is never priced more than $2 above Zone B.
Rules Based Regular Pricing User Guide G58167-03 Copyright© 2026, Oracle and/or its affiliates.