Retail Artificial Intelligence and Analytics

Use AI-powered analytics to create offers your customers want to see. Efficiently and effectively develop strategies to anticipate and influence your customers’ next moves and deliver the right offers.

Discover how your retail business can use AI to help predict the unpredictable.

Key use cases for AI in retail

  • Improve cross-selling and upselling

    AI-driven suggestions can help store associates guide customers to trendy alternatives or goods they might not otherwise have considered buying or substitute items for ones that are out of stock.

  • Automate inventory management

    Retailers can use AI to reduce waste and help boost revenues and margins by ensuring items are in stock in the right amounts at the right time.

  • Optimize pricing strategies

    Retailers can use AI to analyze data on demand, competition, and the cost of goods to recommend optimal pricing strategies.

  • Forecast supply

    Retailers can use AI to identify potential supply chain disruptions, helping ensure that popular products remain in stock, and can dynamically determine the best location from which to source items for every order to minimize shipping and labor costs.

Why is AI important in retail?

Retail analytics and AI solution features

Consolidate the volumes of data generated by your retail applications for planning, buying, moving, and selling, and use the analytical value of that data for your senior executives, marketing analysts, and data scientists.

Oracle Retail AI Foundation

Leverage core retail AI and machine learning to make decisions on assortments, offers, inventory placement, forecasts, planning, buying, pricing, etc.

Advanced clustering (PDF)

Cluster your stores based on traditional approaches of volume, square footage, and region, or leverage ML to cluster stores based on similar selling patterns.

Affinity analysis (PDF)

Determine how items interact with each other for an effective promotional strategy within your financial planning process.

Attribute extraction and binning

Extract item attributes from free-form descriptions, correcting short forms, misspellings, and other inconsistencies, and apply them to demand transference, customer decision trees, advanced clustering, and more.

Customer segmentation

Group customers based on attributes, behaviors, and transactions to tailor offers, pricing, and assortments.

Forecasting engine

Provide an intelligent starting point for your planners to increase automation and accuracy.

Innovation workbench

Leverage open source along with your data science team to create your own AI and ML models.

Profile science

Determine the best size ratio for your buys by understanding the true demand of your sizes, considering stockouts.


Gain analytical insights with Oracle Retail Lifecycle Pricing Optimization Cloud Service solutions

Lifecycle Pricing Optimization Cloud sits atop Oracle Retail AI Foundation, which provides analytical insights to drive planning, buying, moving, and selling decisions. These capabilities enable you to drive profit and remain flexible to the changing retail environment.

Innovate with speed and scale while increasing profits

Engaging omnichannel customers with personalized offers while increasing profits requires modern applications in planning and retail analytics. Oracle Retail provides a single view of the enterprise, enabling you to innovate with speed and scale. Win over customers with promotions, targeted offers, and markdowns while maximizing results.

Optimize the item lifecycle

Gain lifecycle promotion, markdown, and targeted offer recommendations in conjunction with planned business initiatives, such as time-bound marketing campaigns. You’ll drive better profit margins and inventory sell-through and meet forecast expectations with the power of exception-based retailing and advanced machine learning models.

Power of a single view

Delivering an effective pricing strategy that engages the customer in an omnichannel environment requires a single view of the customer, inventory, orders, demand, and pricing/promotions. When optimized results are presented across the enterprise—directly as a promotion or indirectly as a forecast—you can maximize the value of a unified strategy for pricing, promotions, and markdowns.


Acquire new customers with Oracle Retail Consumer Insights

Consumer Insights is a strategic collaboration with Oracle Data Cloud. It brings an unprecedented level of insight to retail marketing teams, enabling them to better understand their customers, optimize new customer acquisition campaigns, and support consumer data-driven buying decisions, personalization, and more.

Rethink marketing strategies and put the customer at the core of every decision to

  • Enrich your data with the world's largest cloud-based data management platform, creating a holistic picture of your customers
  • Find new audiences through Consumer Insights’ direct integration with Oracle Data Cloud’s massive data collective, which spans more than 1,500 retailers, 1,000 product categories, 115 million households, 375 customer attributes, and 5 trillion transactions
  • Identify common attributes and new segments with predictive analytics and retail AI for individualized offers and promotions
  • Reduce customer acquisition costs by up to 2.6X

Maximize supply chain efficiencies to accelerate optimal inventory placement

Get better visibility into supply chains and leverage AI and machine learning to manage inventory levels, improve demand forecasting, identify risks, and provide recommendations to guard against inventory shortages or delays.

Inventory Planning Optimization Cloud Service empowers retailers to more accurately predict demand

Oracle Retail Inventory Planning Optimization Cloud Service empowers retailers to better predict demand and optimize it throughout an item’s lifecycle. During an item’s lifecycle, the solution can react to changes in consumer behavior by adjusting inventory deployment and demand methodologies. That lets retailers manage their current and future inventory at scale to ensure the right products and the right quantities are in the right place at the right time. The solution

  • Helps fuel profitable growth by optimizing costs with unified, end-to-end, and integrated supply chain plans
  • Provides transparency across the entire supply chain
  • Enables analytical processes so end users can understand and engage with the forecast, increasing inventory productivity
  • Automatically optimizes replenishments based on demand forecast, inventory, and past performance
  • Seamlessly adapts to recent trends, seasonality, out-of-stocks, and promotions
  • Leverages AI and machine learning to continuously learn from past data and automatically adapts to new patterns and market changes
  • Enhances allocation accuracy and drives replenishment precision
  • Recommends scaled order quantities that maximize truck utilization

Oracle Retail Assortment and Space Optimization maximizes product placement

Optimize return on space

Optimize assortments to available space to maximize planogram performance, return on space, sales, revenue, and profits.

Drive profit and remain flexible to the changing retail environment

Optimize assortments to store- and cluster-specific needs to maximize return on space, sales, and gross profit while maintaining visual merchandising standards and supply chain considerations.

Improve customer satisfaction

Optimize assortment and placement for the available space for each store to improve customer satisfaction.

Turn data into value

  • Conduct macro-space optimization what-if analysis to maximize profits
  • Create assortment and facing recommendations while balancing supply chain constraints, business rules, and visual merchandising standards
  • Leverage fixture data to dynamically create store and space clusters
  • Use item-level demand transference in calculations to create the optimal assortment mix

Oracle Retail Data Store helps leverage retail data

Oracle Retail Data Store is a low-cost, low-code environment that enables retailers to innovate, take control of their data, and extend the capabilities of their Oracle Retail cloud services.

Oracle Retail Data Store is highly scalable and configurable to support the constantly changing retail landscape. It consolidates data on sales, inventory, pricing, promotions, customers, orders, demand, fulfillment, items, suppliers, consumers, and channels to support a retailer’s unique business processes and journeys.

Retail Data Store includes powerful tools to leverage all of this data

  • Oracle Retail Home
  • Oracle Analytics
  • Oracle APEX
  • Oracle REST Data Services


Collect and Receive: Retail gets reimagined with same-day delivery

Reimagine how retail moves with a collection of processes called Collect and Receive enabled by Oracle Retail Data Store Cloud Service. It lets retailers better serve their customers by understanding how their available inventory should be distributed across the retail estate. Collect and Receive aligns with traditional plan-buy-move-sell processes that tap into the power of data to elevate same-day delivery. With this new capability, Oracle technology, and a partnership with Uber Direct, retailers can gain agility by moving and placing assets, including customers, inventory, and fixtures, across the last mile of the estate that is closest to the point of purchase.


Oracle Retail customer success

Explore more customer stories
  • Helzberg Diamonds

    Helzberg Diamonds shares how Oracle Retail analytics and planning cloud services help retailers reduce inventory by leveraging key data.

    Watch the Helzberg Diamonds video (1:42)
  • Cape Union Mart

    To better meet customer demand, leading South African retailer Cape Union Mart transforms its IT landscape by transitioning to Oracle Cloud.

    Watch the Cape Union Mart video (1:04)
  • Hibbett Retail

    Hibbett Retail shares how Oracle Retail Assortment Planning and Oracle Retail Merchandise Financial Planning provide a connected view of inventory planning for buyers, planners, and execs.

    Watch the Hibbett Retail video (1:43)

Get started with retail analytics


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