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.


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

Contact Oracle Retail

Reach out to discuss the next steps with a retail solution expert.

See the Oracle Retail RACK

Explore research, reports, webinars, and more that can help you better understand the power of Oracle Retail products.

Connect with the Oracle Retail user community

Led by retailers like you, licensed customers meet regularly to share best practices and build networks.