
Retail
Retail has never been under more extreme pressure. This tension comes from the increased expectations of the empowered consumer and the need to have accurate forecasting and inventory in order to deliver goods at a time and location that is convenient for the consumer — all while delivering high operational efficiency and ROI.
Learn how enterprise AI is transforming the retail industry.
Learn how enterprise AI is transforming the retail industry.
AI and Retail
The empowered consumer is more connected and informed than ever before, and they demand that retailers understand their ever-changing shopping habits to provide excellent customer service. At the same time, it has never been more critical to optimize the range of stock and inventory in order to deliver to customers the products they want at the time and place where they want them. All of this needs to be executed by identifying opportunities to decrease costs, increase operational efficiencies, and ensure a frictionless customer experience. Artificial intelligence in retail has the power to help by leveraging your own data about your customers to better understand how their needs have evolved and how your organization can adapt to a changing marketplace.
Empowered Consumer
- Predict next customer CRM state (e.g., activation, regular, high value, decliner, dormant, churn) to inform the strategy of future marketing comms
- Customer satisfaction: using data from surveys and reviews, predict sentiment for the entire customer base
- Based upon prior purchase history, predict the number of days to next order
- Identify the most effective product to present to each customer to influence their buying decisions based on historical data (purchases, web searches, etc.)
- Attribute the value of conversion across digital channels to ensure digital marketing spend is being used in the right channels/campaigns
Product Assortment and Supply
- AI-Driven Demand Forecasting: using a range of historic data sources to inform the level of future demand
- Forecast returns: Use data science in retail to predict the probability of return for every item purchased through all channels
- On-shelf availability: for each SKU by actively detecting or inferring potential lost sales situations at the earliest opportunity to drive corrective action
- Promotions optimization: Identifying the best SKUs and best promotion strategy (e.g., rebate, discount, BOGO, etc.) to achieve targeted revenue or volume
- Price optimization: Identification of optimal price points influenced by multiple factors such as Item, brand, sub-category, category, location, product affinity, competitive and demographic
Operational Efficiency
- Identify best sites to open, expand, reduce, or close stores based on strategic goals without cannibalization of existing store sales
- Predict staffing levels for fulfilling orders, customer service, shipping as demand changes
- Minimize time to deliver the shipment
- Predict channel volumes: (e.g., call center or in-store footfall). Helps to predict staff resources required for any given trading day
- Identify store foot traffic to predict staff resources required for any given trading day

Use Cases for Retail
AI-driven retailers seize every opportunity to use data to analyze customer-changing behavior and shopping habits across multi-channels to align the right product assortment, promotions, and personalized communications. At the same time, they want to have the right product available with the right site selection to ship to customers who want to purchase certain products and have them delivered on their terms.
DataRobot Helps You:
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Learn more about how AI can transform your retail business.