How Should Retailers Be Incorporating AI?
AI can be used for retail in all sorts of ways, and more use cases are popping up every day.
Retailers can leverage AI algorithms to analyze customer data, such as browsing history, past purchases, and preferences, to deliver highly personalized product recommendations.
For instance, some retailers use AI to recommend clothing items based on a customer's previous searches, style preferences, and even weather conditions in their area. Customers who log into the website might see a curated collection of outfits that align with their style, size, and seasonal trends. AI can also adjust these recommendations in real time based on the customer's current activity, further enhancing the personalized shopping experience.
Customers can even take an active role in personalization. Wayfair, for example, lets customers upload images taken inside their homes and then uses AI to make product recommendations that match the rest of their furnishings.
AI can optimize supply chain operations by predicting demand, improving inventory management, and streamlining logistics. For example, some retailers use AI-powered demand forecasting to analyze historical sales data, market trends, weather patterns, and even social media activity.
By accurately predicting customer demand, retailers can optimize inventory levels, reducing both overstock and stockouts. AI can also help in dynamic route optimization for deliveries by analyzing traffic conditions, fuel costs, and driver availability in real time, ensuring faster and more cost-efficient deliveries. This reduces operational costs, minimizes waste, and improves customer satisfaction.
When Walmart recently expanded its fresh food delivery capabilities, it leveraged AI to enhance efficiency, speed up handling times, and improve perishable food quality when it reaches the customer.
AI-powered chatbots can handle common customer inquiries 24/7, such as answering questions about product availability, return policies, or order tracking. These chatbots provide quick responses, freeing up human agents to focus on more complex issues.
Starbucks' AI chatbot, My Starbucks Barista, is available on the Starbucks mobile app. Customers can use voice or text to place orders, ask questions, and get drink suggestions.
Target uses an AI chatbot companion for its employees that can answer on-the-job process questions, coach new team members, support store operations management, and more.
For tasks like inventory, AI can continuously track stock levels in real-time, monitoring product sales data, current inventory, and customer demand patterns. When stock levels fall below a certain threshold, the AI system automatically triggers purchase orders with suppliers or manufacturers. It can even optimize orders based on supplier lead times, minimizing stockouts, and reducing excess inventory.
The fashion retailer Zara uses an AI system that continuously analyzes sales data, store traffic, and customer demand to predict when stock levels are running low. If a certain size or style is selling faster in one location, the AI system automatically triggers restocking orders and redistributes inventory between stores as needed. It also predicts future demand by analyzing trends and adjusting orders accordingly.
AI has a wide range of potential use cases in retail operations, ranging from workforce management and fraud detection to dynamic pricing strategies.
Amazon uses AI algorithms to adjust prices in real time based on various factors such as demand, competitor pricing, time of day, and inventory levels. Brick-and-mortar locations can pair dynamic pricing with electronic price tags of the kind used by Best Buy to digitally update prices right on the store shelf, instead of having an associate walk around putting out new price tags.
AI can power in-store experiences like AI kiosks and augmented reality (AR) fitting rooms. Retailers like H&M and Uniqlo use AI-driven smart mirrors in fitting rooms. These mirrors allow customers to "try on" clothes virtually using AR. The AI can suggest outfits based on what customers are trying, recommend complementary accessories, and even show different colors or sizes available in-store, enhancing the shopping experience without physical effort.
AI is a powerful tool for preventing downtime and spoilage in retail using predictive maintenance. For example, Walmart's AI systems continuously track data from refrigeration units, including temperature readings, energy usage, and operational patterns. It then analyzes this data to identify patterns and detect anomalies that could indicate potential issues, such as malfunctioning components or failing cooling systems.
Retailers can use AI to analyze shopper behavior, sales data, and foot traffic patterns to optimize the layout of their stores. AI systems gather data from various sources, including in-store sensors, sales transactions, and customer movement patterns. Machine learning algorithms then analyze this data to understand how customers navigate the store, which areas attract the most traffic, and where products are most frequently picked up or overlooked. The AI generates optimized store layouts or planograms based on this analysis. It can suggest the best placement for products to maximize visibility and sales, such as placing high-margin items at eye level or near high-traffic areas.
Grocery Retailers Are Using Mobile Technology to Drive Digital Transformation In this episode, Ahold Delhaize USA's Retail Business Services talks us through what's happening in the industry, the challenges, and how he measures success.
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