AI Cloud for Retail

AI Cloud for Retail is uniquely designed for retailers to overcome today’s retail challenges and embrace tomorrow’s retail opportunities with actionable insights that have the power to reshape the industry.

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AI in Retail

AI Cloud for Retail delivers data-driven solutions for retailers to optimize operational efficiency, while maximizing revenue and driving customer loyalty. In the face of mounting supply chain disruptions, evolving consumer buying patterns, and staffing and inventory shortages, AI Cloud for Retail provides insights to drive solutions impacting the entire footprint of an organization, from forecasting demand of staffing and improving product assortment to implementing sustainable processes and reducing food waste.

DataRobot Customers Include 30% of Top Global Retailers

AI Cloud for Retail is transforming the retail industry

AI Cloud for Retail enables retailers to innovate across their operations and maximize business impact

Retail must become multifaceted, connected, agile, competitive— and above all—responsive to the ever-changing demands of the empowered consumer. AI Cloud for Retail provides data-driven insights that help retailers solve their hardest problems, drive success, and deliver real impact.

forecast daily demand by store
Forecast Daily Demand by Store

Demand forecasting / sales forecasting with AI/ML helps reduce overstocks and out of stocks, helping you optimize your supply chain and working capital.

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maximize conversion rates on seasonal catalogs
Maximize Conversion Rates on Seasonal Catalogs

Predict the likelihood of response to catalogs on a seasonal basis.

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forecast the demand of new products aka cold start modeling
Forecast the Demand of New Products (aka Cold Start Modeling)

Forecasting the demand of to-be-launched products enables retailers to optimize inventory, logistics, and working capital and be better prepared to serve their customers.

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predict shipment arrival
Predict Shipment Arrival

Foresee and mitigate potential disruptions to your supply chain by predicting whether shipments will arrive on time.

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supply chain management
Supply Chain Management

Develop intimacy across your customer base by predicting which customers are likely to churn within a defined period of time.

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predict next best offer
Predict Next Best Offer

Offer products that customers are most likely to purchase to maximize cross-sell and up-sell opportunities.

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predict customer lifetime value clv
Predict Customer Lifetime Value (CLV)

Understand the long-term value of your customers to make better-informed, short-term decisions on which customers to prioritize.

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forecast demand for staffing in retail dc warehouse
Forecast Demand for Staffing in Retail / DC / Warehouse

Forecast the volume of inbound shipments required over the next month to allocate the right levels of staffing.

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improve in store product assortment
Predict the Likelihood a Credit Card Customer Will Default

Predict which credit card customers will default on their credit card loans to strengthen credit card portfolio.

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predict performance of sellers
Predict Performance of Sellers

Maximize the productivity of your sellers by predicting the performance of each seller throughout the determined selling period.

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vendor invoice fraud
Vendor Invoice Fraud

Predict the likelihood that a vendor invoice is fraudulent.

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DataRobot AI Cloud Partner Ecosystem

See how our partners utilize DataRobot AI Cloud for Retail to activate the full potential of retail solutions.

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demo

AI Cloud for Retail Demo: Demand Forecasting

See how AI Cloud for Retail can be used to solve forecasting challenges such as out-of-stock issues and automatically perform unsupervised clustering to find like-groups of products.

Frequently Asked Questions

  • How is AI used in retail?

    AI is used across the entire end-to-end lifecycle of a retail company. From product development to production to supply chain to marketing, there are use cases for virtually every retail capability. DataRobot customer use cases include:

    • Forecasting demand for new products in order to accurately plan inventory and resources
    • Pricing optimization to maximize profits
    • Maximizing the effectiveness of marketing campaigns by delivering the right message to customers through the right channel
  • What are the benefits of AI in retail?

    The benefits of AI in the retail industry are wide; however, there are three key areas that remain the most common:

    • Maximizing revenue with price optimization
    • Reducing costs with demand forecasting
    • Increasing efficiency by enabling analytics teams to accomplish more with their time
  • How can AI be utilized for grocery retailers?

    Grocery retailers can utilize AI in a number of ways including optimizing the number of delivery or pickup slots; forecasting demand by SKU and by store; utilizing markdown optimization; leveraging “Next best offer” to reach individual customers with the right offer, channel, and message to drive conversion; and modeling propensity for individual customers to purchase newly launched private label items.

  • How is AI used to enhance in-store experiences?

    Today, AI enables stores to deliver personalized shopping experiences – the same customers see online –  in-store. Here are a few examples of how AI helps retailers:

    • Create and deliver customized product offerings
    • Deliver personalized messaging to each customer
    • Optimize in-store displays to maximize customer engagement
  • Which types of retailers will benefit from AI?

    All retailers across the board – from large department stores to small business grocers– can reap the benefits of AI. Retailers can use AI to collect and manage data for customers, products, and operations to further enhance their business.

  • How does AI impact sustainability in retail?

    Sustainability is one of the most important issues for retailers today. AI impacts sustainability in a number of significant ways, including:

    • Demand Forecasting: By predicting the right amount of customer demand, retailers can eliminate waste by not overproducing goods.
    • Markdown Optimization: By being able to price perishable products effectively, grocers can make sure they sell out of inventory and help eliminate the waste of unsold items.
    • Transparency: AI can be used to generate real-time predictions of the carbon footprint of individual products, providing the transparency and data that consumers increasingly desire.
  • Will AI affect the future of retailing?

    The future of retailing is rapidly evolving – both in-store and online – as retailers leverage AI to continue personalizing the shopping experience. The ecosystem of data available to retailers is growing. For example, as consumer behavior data grows, the usage of AI will continue to grow within retail to personalize the entire experience to consumers – wherever they are.

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