1 Lifecycle Pricing Optimization

This chapter describes Lifecycle Pricing Optimization (LPO).

Introduction

Oracle Retail Lifecycle Pricing Optimization Cloud offers the evolution of price optimization capabilities into a lifecycle optimization solution that recommends promotions, markdowns, regular pricing, and targeted offers in conjunction with planned business initiatives, such as time-bound marketing campaigns. It optimizes promotions and markdowns to drive higher in-season sell-through as well as potentially increasing revenue and/or gross margin throughout, to the end of life. It empowers retailers to drive better profit margins and inventory sell-through, to meet forecast expectations with the power of exception-based retailing and advanced machine learning models.

Key Features of LPO

  • Automated pricing recommendations for regular, promotional, markdown, and targeted scenarios.

  • Contextual insight into the estimated impact of promotions, offers, and markdowns, which includes the impacts on sales, margin, and inventory.
  • Weekly updates based on new sales, inventory levels, competitor pricing, and other dynamic data points.
  • Forecasts describing what will happen if the user take the system recommendations versus doing nothing based on the recent data.
  • In-season performance assessment to adjust pricing strategy in real time.
  • New item price estimation based on similar item behavior and historical data.
  • Intelligent re-pricing for items affected by cost changes, competitor shifts, or business objectives.
  • Location or zone-level granularity for pricing, with personalized targeting capabilities.
  • Integration with Oracle Retail Planning and Execution systems to ensure alignment across merchandising decisions.

Types of Pricing Optimizations in LPO

LPO determines the optimal pricing and timing for regular promotion markdowns and targeted price recommendations. These recommendations help retailers maximize inventory productivity, optimize working capital, and drive customer engagement across channels. Promotions and markdowns are managed at the location or price zone level, while targeted recommendations are customer specific. The timing and depth of these recommendations are critical levers for managing inventory throughout the product lifecycle.

  • Regular Pricing Recommendation
    • Regular price is the initial price for a new item or a regular price update at the location (for example, Region or Area) or price zone level.
    • Regular Pricing Recommendation in LPO ensures that the base price of an item is competitive, profitable, and aligned with market conditions by analyzing the cost changes, competitor prices, and demand trends to determine the best price for new and existing items.

      • Regular Pricing Recommendation can be done in two ways - Forecast-based (using historical data to generate forecasts, along with pre-defined business rules) and non-forecast-based (using only business rules).

      • Forecast-Based: This method uses historical data to generate demand forecasts, which are then used to optimize pricing for revenue, margin, or volume. It enables strategic, data-driven decisions based on predicted customer behavior. Example: Raise the price of a top-selling item by $10 if demand is expected to remain high.

      • Non-Forecast/Rules Based (also known as Regular Lite): This method uses a rules-based engine that is triggered by pricing conditions, not forecasts. It relies on data such as current pricing, cost, competitive data, and so on, making it ideal for quick, operational pricing updates. Example: Automatically ensure and update Item A’s price to remain like the competitor's price of Item A in the same zone.

  • Promotional Pricing Recommendation

    • Promotion is a temporary reduction in the item's price to drive sales, based on forecast data and configurations.

    • Promotional pricing recommendations in LPO is optimized to drive sales while maintaining profitability by recommending discounts that maximize revenue and customer traffic without excessive margin loss.

    • Example: Offering a weekend discount on fresh produce to boost foot traffic or running a limited-time sale on jeans to clear seasonal inventory.

  • Markdown Pricing Recommendation

    • Markdown is a permanent reduction in the item's price, typically for clearance or end-of-life management, based on forecast data and configurations.

    • Markdown pricing recommendations in LPO help retailers clear aging inventory efficiently by providing optimal markdown recommendations to minimize margin erosion while maximizing sell-through.

    • Example: Marking down winter coats at the end of the season to clear inventory or permanently reducing the price of a slow-moving snack brand.

  • Targeted Pricing Recommendation

    • Targeted recommendation is personalized price or offer designed for a specific customer segment or individual, based on forecast data and configurations.

    • Targeted recommendations in LPO allow retailers to offer personalized discounts based on customer behavior and segmentation. LPO ensures that price adjustments maximize conversion without unnecessary discounting.

    • Example: Providing a special loyalty discount on organic vegetables for frequent buyers or offering an exclusive promotion on handbags for high-value customers.

Business Values

  • Maximize Profit Across the Product Lifecycle

    • LPO enables retailers to capture the highest possible gross margin by recommending optimal prices at every stage, from new item introduction to final clearance.

    • Example: For a seasonal item like a winter jacket, LPO can start with a high regular price, apply promotions during peak season, and intelligently trigger markdowns as demand wanes-maximizing margin across the season.

  • Improve Inventory Turnover

    • By aligning pricing decisions with inventory levels and sales performance, LPO suggests markdowns and promotions based on real-time inventory status, ensuring timely sell-through and minimizing the need for heavy end-of-season discounts.

    • Example: If a particular size or color of a product is under-performing, LPO can recommend a localized markdown while keeping stronger-performing variants at full price.

  • Respond Quickly to Market Changes

    • Weekly data refreshes and re-optimization allow businesses to adapt pricing strategies quickly.

    • Example: If a competitor introduces a lower-priced version of the same product mid-season, LPO can adjust pricing to remain competitive while preserving margins wherever possible

  • Enable Customer-Centric Pricing

    • With Targeted Recommendations, LPO supports personalized pricing strategies based on customer segments or individual preferences. This improves offer relevance, drives engagement, and enhances loyalty, without eroding margins for the broader audience.

    • Example: Offer a special discounted price to loyal customers or high-value segments, while maintaining standard pricing for general consumers.

  • Operational Efficiency

    • LPO automates complex pricing decisions using machine learning and optimization techniques, which reduces the manual effort of analyzing sales trends, setting promotions, and managing markdowns.

    • Example: A merchant managing hundreds of SKUs across multiple regions can rely on LPO to generate location-specific recommendations in a fraction of the time.

LPO Use Case Example

Figure 1-1 LPO Use Case Example

This image shows an LPO use case.

Overview of the User Interface

The LPO user interface, at a high level, consists of the following components in a JET UI.
  • AIF Task Pane

    • When the user logs in to the application, the Task Pane is displayed on the left side of the application. This allows the user to navigate between AI Foundation (AIF) applications and their respective subtasks, such as LPO.

      Figure 1-2 AIF Tasks

      Description of Figure 1-2 follows
      Description of "Figure 1-2 AIF Tasks"
  • Lifecycle Pricing Optimization - Task Pane
    • Clicking Lifecycle Pricing Optimization from the AIF Task Pane opens the LPO Task Pane, displaying the following links:
      • Run Overview - Manage runs and business rules, or view and edit results.
      • Multi-Run Request - Manage multi-run entries.
      • LPO Recommendations - Manage recommendations, view reports and metrics, and review, approve, or submit recommendations.
      • Legacy Links - Opens LPO in older ADF screens.

        Figure 1-3 LPO Tasks

        This image shows lpo tasks.
  • Contextual Panel
    • This panel, located on the right side of the application, displays graphical insights that help in setting up runs and interpreting optimization results.

      Figure 1-4 Contextual Panel

      This image shows the contextual pane
  • Oracle Digital Assistant (or Chatbot)
    A floating icon appears in the bottom-right corner of the screen (movable across the screen). This functionality, called Artie, offers voice or chat-based assistance. Users can interact with the chatbot to ask queries (see Integration with Oracle Digital Assistant), and LPO responds with relevant answers.

    Figure 1-5 Oracle Digital Assistant Connected

    This image shows oracle digital assistant.

Administering Lifecycle Pricing Optimization

For information about the administration of LPO, see the Oracle Retail AI Foundation Cloud Services Administration Guide.