Artificial intelligence and machine learning have taken various industries to the next level. Among others, retailers are also reaping the benefits of AI. And it is an increasing trend: artificial intelligence in the retail market is expected to grow at a CAGR of up to 35% from 2019-2024.
This article will explore the main uses of artificial intelligence in e-commerce and retail, how it helps retailers grow their businesses, and how Intellias will help you step up your AI game.
Artificial Intelligence and Machine Learning in Retail: Benefits
Source: Robotics Business Review
According to the Capgemini Research Institute report, 98% of interviewed retailers who are using AI expect the number of customer complaints to reduce by 15%, while 99% of responders expect an increase in sales by 15%. These high expectations have valid reasons behind them. The advantages of artificial intelligence in retail are hard to exaggerate. Let’s share the most obvious.
Machine learning capabilities
The ability to process large volumes of data at speed is the main benefit of artificial intelligence and machine learning in e-commerce and retail. Provided with sales records, market information, and consumer data, AI can discover market trends, predict consumer behavior, forecast sales, minimize customer churn, optimize restocking, and more.
Based on consumer feedback, state of inventory, and sales trends, AI can make specific business predictions that arm retailers with the information they need to enhance productivity, reduce waste, prevent errors, improve scalability, and boost success rates of marketing campaigns.
Improved consumer experience
Artificial intelligence systems can provide customers with 24/7 support, releasing you to focus on other important tasks. Such support includes in-store assistance, virtual mirrors, cashless checkouts, mood tracking, customer recognition systems, etc. By automating tasks that have been traditionally reserved for humans, AI helps retailers boost customer satisfaction while reducing labor costs and preventing fraud.
Optimization of inventory design and space usage
Artificial intelligence can also optimize inventory design and space usage. Taking into account consumer preferences, expiration date, color scheme, location, season, and weather, AI-driven robots can better improve the design of shelves and produce them at a faster rate than human beings. The result – a boost in sales and a reduction in the waste of space.
Examples of AI Implementation from Top Retail Enterprises
Artificial intelligence and machine learning technologies have the potential to revolutionize the retail industry by adding efficiency, accuracy, and personalization capabilities. From what we see, it’s already happening. The examples below reveal how AI-powered technologies help retailers improve consumer experience, restocking and inventory management, delivery, and price adjustment.
Consumer experience
Building fruitful and long-term relationships with customers is a crucial part of the retail industry, and artificial intelligence offers endless possibilities in this respect. Here are a few examples:
- There is nothing worse than standing in line for the fitting room only to discover you’ve grabbed the wrong size or want another color. American Eagle’s interactive fitting rooms have solved this problem. Using AI-driven technology, customers can browse for the needed items, see if they are in stock, and notify a store employee to bring these items to them.
Interactive dressing rooms are not the only AI-backed advancement of American Eagle. Their customers can also take advantage of a visual search. By uploading images of desired clothing, they can find similar products that are in-store and even get recommendations of items that complement them. - Kroger, a chain of grocery stores, takes the idea of smart shelves to the next level by demonstrating the proven benefits of computer vision in retail. If the customer shops with the app open, the system identifies their needs and highlights products from the shelves based on their preferences and even health condition.
- ThredUp is an online consignment store that uses AI to remember consumer preferences and thus boosts customer loyalty. By analyzing the clothes that customers return, the system adjusts its recommendations to their preferences. Such recommendations can be found in the Goody Boxes.
- Using AI-driven cameras in every check-out lane, Walmart’s facial recognition system detects the customer’s mood. If the system detects an aggravation, for example, the personnel will immediately be notified and flagged down to address the issue.
Restocking & inventory management
Ineffective inventory management can lead to missed sales opportunities, inaccuracies, and insufficient customer experience. Fortunately, AI systems are quite efficient in restocking. By crunching enormous volumes of data and identifying repeated customer behavior patterns based on trends, the state of inventory, sales history, weather, location, and other parameters, AI can minimize out-of-stock instances and avoid stocking up on items that won’t be popular with customers.
For example, Walmart’s AI-driven robots scan shelves for missing products, prices that weren’t updated, and items that need to be restocked. The pharmacy chain Walgreens collects data on the number of antiviral prescriptions filled to track the flu. This not only helps to inform customers of the flu spreading in certain areas, but also empowers Walgreens to stock more anti-flu products in infected areas.
Delivery
AI has the potential to revolutionize delivery processes. However, retailers are just testing the waters in this respect. For instance, Dominos is working on its DRU, a robotic unit designed to find the most optimal route to destinations. Meanwhile, Amazon is planning to use drones for delivery purposes, which can ensure 30-minute deliveries to any part of the world.
Price adjustment & prediction
Retailers have increasingly realized the potential of artificial intelligence in terms of price adjustment. Based on information about demand, seasonal trends, promotional activities, and other data, AI systems can predict the possible outcomes of different pricing strategies. eBay and Kroger currently use AI for these purposes.
AI Solutions Implemented by Intellias
AI is a powerful tool that can help retailers reduce costs, streamline decision-making, quickly adapt to the market changes, and personalize customer experiences. However, many enterprises are still reluctant to utilize AI and ML in their processes. The main reason for this barrier is the lack of in-house experts who specialize in AI technologies.
Luckily, Intellias has you covered. Combining tried-and-proven software development practices with the latest technologies, we help businesses grow with the power of AI. We’ll analyze your case and help you deploy the specific AI-driven solution for your business needs. Below are the solutions we’ve already implemented for our clients.
- Online context in-store: CV-powered mobile apps that recognize different in-store products and provide contextual information.
- Personalized experience: The facial recognition system which boosts customer loyalty levels by identifying regular customers.
- Shopper measurement: A computer-vision system that recognizes the gestures, poses, and emotions of customers to provide more insight regarding the footfall, pass-by traffic, and specific customer satisfaction.
- Inventory management: An item and planogram recognition systems that enable real-time, shelf-management, and inventory optimization.
- In-store theft prevention: CV technology that monitors cameras and alerts security staff if potential risks are identified.
- Checkout-less sales: LBS and CV technology that enables checkout-less sales to eliminate long queues, improve customer experience, and to free salesforce for other tasks.
- Robotization: The AI-driven camera that provides data to build an indoor navigation map for stores, and also enables object and edge detection for sorting arms.
- Delivery optimization: LBS- and CV-driven route optimization function for the transport management system.
- Content improving: Text and image content recognition technologies that identify incorrect product attributes, increasing the Product Information Management efficiency.
- Intelligent pricing: The AI-driven product pricing system which adjusts prices based on customer interests and activity, as well as stock availability forecasts.
- Demand planning: Generative AI models can analyze historical sales data and market trends to improve demand forecasting accuracy.
Conclusion
Artificial intelligence technologies span throughout every aspect of the retail industry. Leveraging the power of big data, machine learning, deep learning, and natural language processing, artificial intelligence allows retailers to effectively analyze massive data volumes, make timely decisions, build meaningful relationships with customers, improve supply chain, and much more.
Retail giants, like Amazon, Walmart, and eBay, already reap the benefits of these next-age technologies. Yet, over 70% of retailers have not discovered the power of AI. Is this the case for you? That’s where Intellias comes into play.
Whether you are a budding startup or a seasoned enterprise, Intellias, a trusted retail software development company will help your business get on the artificial intelligence rails in the most profitable way. Just share your case with us and we will reach out!
