The field of retail and eCommerce is evolving rapidly under the influence of technological advancements and changing customer preferences that expect business to be tech-savvy. Artificial intelligence for the retail industry is one of the dominating technologies that global brands adopt for their business processes.
Thus, let’s find out how artificial intelligence retail solutions may be used with the goal of making the eCommerce business more competitive, customer-centric, revenue-generating, and optimized.
Know more: How the Application of Artificial Intelligence Assists Businesses?
Artificial Intelligence in the Retail Definition
According to the Artificial intelligence in retail: The AI-enabled value chain research, “Most extant conceptualizations of AI make reference to computer systems with human-like intelligence, which encompasses these systems’ abilities “to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”.
In their definition, the Oxford Dictionary includes tasks such as visual perception, speech recognition, decision-making, and the translation between languages, with the Merriam-Webster Dictionary emphasizing that AI imitates intelligent human behavior.”
To put it simply, artificial intelligence retail solutions refer to the smart systems that are able to work with large data arrays, identify patterns and anomalies, as well as make data-driven predictions while being guided by real-time and historical information.
How Are AI and ML Used in Retail?
Since each business has different data to extract actionable insights from, there can be a lot of retail machine learning use cases. For example, machine learning and artificial intelligence may be used in the following retail business processes.
- Marketing. The simplest example of the ways to apply ML and AI in retail is recommendation engine usage. In a nutshell, this is an eCommerce website-embedded system that captures and analyses the behavior of each user and suggests the products they may be interested in, according to their search and shopping history. However, there are more advanced examples. For example, with the help of AI, making retail websites 100% personalized, i.e, each customer may see such a version of the website that is accurately tailored to their interests, needs, and solvency.
- Customer service. AI-powered chatbots are one more example of artificial intelligence in retail usage. However, modern technologies go beyond chatbot only and are ready to offer robotic solutions that may partially replace human force and successfully deal with routine tasks.
- Staff management. Machine learning algorithms may also successfully be used for the purpose of staff optimization. For example, the system may analyze the prime time of a store, correlate this information with the number of workers needed to cope with this load, and allow the store to optimize working shifts accordingly.
- Price prediction and optimization. Perhaps, this is one of the best opportunities retail may get by adopting AI and ML. Artificial intelligence becomes even more powerful when it comes to its predictive capabilities. Taking historical and real-time data into account, the system may suggest the volume of demand for a specific good at a specific time, take the real solvency and the mood of the customers into account, and suggest the best price to make the deal happen.
- Supply chain optimization. Having a well-developed and optimized supply chain is especially essential for retailers that deal with perishable goods. AI opens up better opportunities for route planning, and it becomes even more powerful when taking demand predictions into account. Thus, retailers may supply only those amounts of food that will be actually bought and consumed by the customers, thereby avoiding food waste, fuel costs, and money losses. Also, the usage of robots for warehouse picking may significantly streamline this process while reducing the level of mistakes.
- Following safety and manufacturing standards. Continuing the example above, food retailers and manufacturers may use AI as a part of their production processes. For example, empowered with vision AI solutions may help at the stage of separating fruits of unsatisfactory quality from those that meet all the necessary standards. As for the safety measures, such a system may control employees and the ways they follow hygienic rules, which becomes especially relevant in pandemic times.
What Are the Benefits of Artificial Intelligence in Retail?
The use cases described above directly point out the benefits the retail industry may get by adopting artificial intelligence and machine learning.
See more: Artificial Intelligence(AI) Will Not Become Truly Smart
How AI Is Changing the Retail Industry?
Thus, there is no doubt that machine learning and artificial intelligence are driving changes and innovations in retail. Here is how AI retail solutions are changing the industry right before our eyes.
- AI and ML make retail predictable. With the help of AI, retailers and manufactures may predict the actual demand and the realistic price the buyers would like to pay for a certain good. However, this benefit provokes concern. With the help of predictive analytics, retailers will be able to manufacture and sell more and more goods that the consumers really need, and thus, the process of polluting the planet will go on until all the brands will be able to adopt ethical and green approaches.
- AI and ML make retail eco-friendly. Fortunately, artificial intelligence is already on the way towards making retail greener. Even the opportunity to reduce food waste matters since now, one-third of all food manufactured is wasted. Plus, by optimizing supply chains, AI may help companies to reduce fuel emissions.
- AI and ML make retail optimized. With data-driven insights in their pockets, retailers will be able to optimize everything that’s subjected to optimization – from their trading premises and product layouts on shelves to advertising strategies and customer support.
- AI and ML make retail customer-centric. The wide opportunities for all-covering customers’ data analysis are already here, and tech-focused retailers will employ them further to make their business customer-centric in the best meaning of the word.
- AI and ML make retail innovative. Robotic assistance and delivery are quite innovative opportunities but very soon they are going to become quite common. There is also a prediction that at least two of global retailers will establish Robot resource organizations to manage nonhuman workers by 2025.
AI in Retail in 2021 – Innovative Use Cases
What’s more, some of the innovative AI and ML solutions (for example, like the one developed by SPD Group that’s suitable for the retail and banking industry as well) are already adopted by the leading retail brands. Below are some of the most prominent examples.
- Walmart. This global retailer has introduced an AI-powered service that allows the customer to send a text message with the goods they need and get their orders delivered. Further, the company is going to use the data obtained from customers for making quite accurate predictions and suggestions.
- Nike. Nike uses a powerful mix of artificial intelligence and augmented reality. The mobile solution helps shoppers to scan their feet digitally and find out the shoe size that will perfectly suit them.
- Kroger. Kroger is going to replace traditional shelves with digital ones that will be fully personalized and AI-powered.
- Lowe. This brand employed a customer service robot that may help with searching for a certain good in store. The only thing the customer needs to do is to ask him, and the robot will show the way.
Also Read: Why blockchain based cloud computing could be the future of IoT?
Conclusion
Thus, artificial intelligence in retail is already here. What’s more, this is the most powerful technology that is able to provide retailers with a cutting-edge competitive advantage, so your company’s development strategy is better to have room for their introduction into your business processes.
