AI is transforming the face of the retail industry, and it’s the right time to put it into good use.
FREMONT, CA: As per a recent IBM report, which surveyed nearly two thousand retail and consumer product companies across twenty-three countries, 85 percent of the retail organizations plan to implement intelligent automation for supply chain planning by the next two years. Along with it, the retailers believe that the advent of AI will result in 10 percent annual growth, and AI will transform the entire retail industry.
Better Customer Service:
AI can revolutionize the retail industry by making webshops a possibility that can lend a hand to the companies in marketing their items as per the past purchases of the consumer and their search habits. Retailers know that superior customer service is crucial to run a successful business. As a result, it is significant to have an effective customer service solution, which is fulfilled by AI. Offline shops can also benefit from AI in numerous ways. There can be robots serving the customers as salesmen in a retail store who can answer every query of the customer promptly.
Minimum Advertised Price (MAP) is known as the lowest price in which the retailer can advertise his/her product for sale. The items that are sold at a price lower than their MAP price can poorly affect the business for retailers. It can lead to the dissolution of the brand in the eyes of the customers, so it is critical to track the sellers who violate MAP pricing. Ai is utilized by the retail analytics firm and Intelligence Node to help the brands that are selling online to prevent the breach of their MAP pricing. It works to track the products in real-time and monitors them, as well as, report if there is a violation of MAP pricing to take action against it.
Better Data Gathering:
AI can help retailers and organizations with massive customer data to better accumulate information. AI can collect precise conclusions and create a more customized shopping experience for users. By utilizing the data, retailers can help in creating a more engaging experience for the users, depending on their likes and dislikes. Apart from that, retailers can predict the market conditions and how their product is performing in the marketplace by referring to their past; hence, come up with strategic decisions.
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