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Today, retailers are already experiencing the many benefits of using artificial intelligence (AI), and its importance will only grow as the industry continues to innovate. As artificial intelligence becomes more widely accepted, so too is its implementation.
Check out these use cases to see how AI in retail can change the industry for the better.
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Use Cases of Artificial Intelligence in Retail
The retail industry epitomizes how brick-and-mortar businesses can interact with AI. Retailers use this technology to give their customers a more personalized experience and better interaction with their stores. AI is also changing the overall way retailers do business—tracking inventory and resource consumption, forecasting sales, presenting new products and offering them to potential customers.
Retailers use the technology to help retailers make better decisions, increase business scale and profitability, and automate tedious or repetitive tasks.
1. Chatbots for better customer service
The prospect of using chatbots to enhance customer service is one of the most welcome developments in e-commerce. Providing this functionality allows online retail businesses to address potential buyer queries with a more personalized experience. Chatbots have proven helpful in customer service tasks like answering FAQs.
Integrating a chatbot into a retail website or app is an excellent decision for businesses looking for ways to assist customers and increase customer satisfaction. These chatbots will be able to handle the majority of your customer inquiries and help increase retention and engagement in the process. Additionally, personalization, virtual assistants, and artificial intelligence all present opportunities to overcome contact center underperformance.
2. No cashier
It is a major trend that artificial intelligence technology will take over traditional jobs. Retailers such as IBM, Walmart, TJX and Amazon are testing the technology in a new generation of cashierless stores. This new way of retailing brings automation, efficiency, and convenience to customers and store owners — and no more waiting in line. A cashierless store that uses AI to predict help needs is the next big step in automation.
3. In-Store Assistance
Retailers have been investing in technology that helps customers and employees shop. Kroger Edge installed smart shelf labels to eliminate the need for paper price tags in the store.
The technology allows advertisers to deliver visual advertisements, nutritional information and promotions on device displays. Lowebot is an autonomous robotic store assistant device launched by Lowe's stores, designed to help customers easily find what they are looking for in the store in different languages. Thanks to real-time monitoring, the robot's inventory management capabilities are also expanded.
Brick-and-mortar retailers often aim to provide extra assistance during the shopping process. In-store retail robots could be the next big thing: a new automated system that helps customers find what they're looking for while shopping.
4. Retail store price adjustment
AI can also make price adjustments more accurate and artificial, and according to a Deloitte study, AI can even help manage prices during times of uncertainty. ML enables autonomous and efficient AI-based price adjustments in retail stores. result? Consumers enjoy fairer prices, smarter product positioning and a better shopping experience.
Algorithm-based price adjustments occur when, after a product is purchased in a store, the price changes automatically according to a specific pattern set by the owner. AI pricing can have a huge impact on the in-store experience. However, any method of price adjustment should focus on what customers are willing to buy at a given time and requires appropriate analytical resources to make it work.
5. AI-Based Price Prediction
As the pace of change in the global economy continues to accelerate, disruptions in financial services could cause current price forecasting models and methods to Services become irrelevant on the Internet—it needs to figure out how to continue adapting to new, changing demands by adopting disruptive business models and new technologies.
Price forecasting is the determination of which products can be purchased at a particular price point to satisfy the demand for those products. If you want to know how prices will change, AI-based price prediction models can be helpful. With the help of artificial intelligence-based software, retailers can make better pricing decisions, which in turn generate more revenue.
6. Supply Chain Management and Logistics
The impact of artificial intelligence on the supply chain, logistics, and trucking industries is enormous and increasingly understood. The space is full of struggling companies and exciting new technologies trying to solve some of the industry's most significant pain points. The next generation of artificial intelligence will break down barriers in supply chain management and logistics by collating demand, increasing coverage and tracking shipments.
To keep up with the latest innovations and continue to meet the challenges, innovative companies are combining cloud-based AI technologies with increased communication (social media) to better manage their supply chains. Unfortunately, the increase in communication has brought a new challenge - data overload. Collecting and filtering data is critical to the efficient operation of a business.
7. Product classification based on machine learning
Machines are getting smarter, retailers are turning to data, and online shoppers demand a personalized experience. All of this means that now it's harder than ever to understand what's going on in your store. Machine learning using neural networks is widely used in the retail industry to automate product classification tasks, such as searching.
Assortment has been a problem for retailers for decades. They can be done manually or by learning from customer data. Sales and marketing expectations have increased, and we see ML as a replacement for this manual process. Using ML, retailers can improve product assortment and reduce costs.
8. Customer Behavior Prediction
As pressure on retailers to deliver relevant customer experiences mounts, companies are using artificial intelligence to predict how potential customers will engage and personalize the shopping experience — ultimately transforming it and improving retention.
In addition, AI will help retailers identify customer needs more comprehensively. The ultimate goal is to provide the company with a comprehensive picture of the marketing stage landscape and a complete forecast of its future needs and actions. Other predictive behaviors include timing, loyalty, and sales conversion.
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epilogue
Machine learning and artificial intelligence are no longer just futuristic buzzwords. Now, the technology is finding its way into several large industries, including retail, where it promises to provide cost-effectiveness and improved customer experience.
Article reference:
《Using AI In The Retail Industry: Use Cases In 2023》
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