ElectrifAi | Retail and CPG

Retail and CPG

Customer expectations are on the rise. Stores with passive engagement are not going to entice customers when they can go to a store that cares about the customer's experience. AI and ML leverage your own data to understand customer demands and help you find solutions to meet those requirements.

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Accurately forecast supply and demand to appropriately maintain inventory levels so stores are stocked but liquidation of inventory is not necessary.


Online shopping has never been more popular. Customers can now shop around with ease. Understanding customer desires helps to beat fierce competition.


Supply chain optimization and vendor management are crucial for CPG companies to meet retail demand, grow the brand, and capture additional market share.

Use Cases

Use Cases That Make Us Different

  • Marketing

    Marketing is an important tool Retail and CPG companies must use effectively to stand out in a crowded industry. Specific marketing campaigns that target customers individually rather than placing them in bucket categories is ideal to draw in customers. Machine learning helps by providing solutions and recommendations to prevent email fatigue opt-out, optimizing email campaigns, customer segmentation, determining upsell and cross-sell opportunities, and much more.

  • Personalization

    Personalizing offers is key to drawing in customers who have countless retail store options. With competition so fierce, knowing exactly what a customer is looking for and providing a specific offer for that item will encourage the customer to shop with you. Machine learning can provide that specific customer knowledge by processing thousands of data points—such as behavior, spend, and demographics—to provide a targeted recommendation for that customer.

  • Demand Forecasting

    Retail and CPG companies must understand product demand to remain competitive. Keeping customers satisfied by having enough product in supply to satisfy demand is crucial to maintaining brand loyalty. If companies run out of supply, it is easier than ever to shop around for a store that does carry what the customer seeks. On the other hand, oversupply is not ideal as clothing can go out of season or a trending item may no longer be sought after, causing companies to lose money by putting items on sale or having to liquidate. Machine learning can help determine the ideal level of supply based on demand forecasting, ensuring your company remains in stock and reducing oversupply problems.

  • Dynamic Pricing

    Supply and demand are something Retail and CPG companies must consider. A dynamic pricing strategy can help solve fluctuating supply and demand problems by changing the price of an item or service to meet consumer demand. Machine learning is the best way to leverage pricing power. ElectrifAi machine learning models have proven to be very capable at producing reliable results through deep domain expertise, helping companies increase revenue.

  • Spend and Contract Management / Operational Efficiencies

    Retail and CPG companies have many customer and supplier contracts and invoices to analyze. But why manually process tedious contracts and invoices when most tasks can be automated? Machine learning can help extract key terms to indicate when contracts expire, renew, or when they should be renegotiated. Machine learning can also help to spot invoice inconsistencies, such as a suspicious amount or a wrong due date based on the terms in the contract.