With the development of digital technologies and e-commerce, the popularity of shopping bots is growing. Such bots help automate routine processes, optimize customer service and increase sales. Thanks to automation, shopping bots can reduce order processing time, improve customer interaction, and increase business efficiency. A shopping bot is software that can automatically perform actions related to the sale of goods. It can include functions such as taking orders, informing customers, processing and tracking sales. The use of a shopping bot varies from retail to online stores, from social commerce to e-commerce platforms. The working principle of a shopping bot depends on its functionality and goals. It is usually integrated with e-commerce platforms, communication networks, messengers or websites where potential customers can ask questions and place orders. Modern shopping bots are powered by artificial intelligence and machine learning algorithms, allowing them to adapt to user requests and improve their performance. Bots connect to websites, managing networks (like Facebook or Instagram) or messengers (like WhatsApp or Telegram) so that shoppers can easily interact with them. Modern shopping bots can integrate with payment systems, allowing users to pay for orders directly in the chat. The bot can also collect shipping data, helping to make shopping as easy and fast as possible. Bots are often used by online stores to automate order processing and customer support. They can suggest the appropriate product, help with checkout and monitor delivery stages. With the development of artificial intelligence technologies, bots are becoming increasingly “smart” and are able to analyze customer requests, take into account changes in their preferences and even anticipate design. For example, banks can collect purchase data and suggest relevant products based on order history, increasing the level of personalization. Any bot requires analysis and regular optimization. It is better to analyze sales data, evaluate the progress of transactions and the level of customer processing. Based on this data, you can improve bot responses, adjust the communication strategy and introduce new features. For example, if the bot shows low conversion rates in sales, it may be worth revising the communication script or adding additional options for user experience. In addition, as strategies evolve, bots will be able to work across platforms and integrate with different trends to provide a more comprehensive and holistic customer experience. Implementing a bot for commodity trading can become a competitive advantage for a business if you approach the process intelligently: think through communication scenarios, integrate with other chains, and constantly analyze the results of your work. This will create a truly useful assistant that will not only increase sales, but also strengthen relationships with customers, fostering loyalty and repeat purchases.