In the retail industry nowadays, the competition is getting tougher and tougher. So, many organizations are looking at different forms of artificial intelligence to make themselves stand out. E-commerce companies, in particular, are starting to use technologies like chatbots and augmented reality (AR) interactive technology. These have become quite popular in dealing with customer service in the business world. But, we don’t really know much about how consumers feel and how much they engage with these new technologies when they’re used in a retail setting. That’s what we’re going to explore here. I. The Use of Chatbots in E-commerce 1. What Chatbots Do 2. How Customers Engage with Chatbots II. The Use of AR Interactive Technology in E-commerce 1. What AR Does 2. How Customers Engage with AR III. The Need for a Research Model 1. Understanding Motivational Mechanisms 2. Decision-Making Both chatbots and AR interactive technology have a lot of potential in e-commerce. But to really make the most of them, we need to understand how consumers engage with them. By looking into this and creating useful research models, e-commerce companies can use these technologies in better ways to improve the shopping experience and boost sales.

Hello everyone, I’m excited to share a technology that’s rapidly transforming how businesses interact with the world: Conversational AI. You’ve probably heard the buzz, but let’s really look into it. It’s more than just chatbots. It’s a fundamental shift in human-computer interaction, and understanding it is crucial for businesses looking to stay ahead. How Conversational AI Works: The Technology Behind the Talk At its heart, Conversational AI is about enabling computers to understand and respond to human language in a way that feels natural and conversational. This isn’t just about recognizing keywords. It’s about deciphering intent, context, and even sentiment. So, how does this magic happen? It’s built on a stack of sophisticated technologies. NLP and ML Technology: Natural Language Processing (NLP): This is the bedrock of Conversational AI. NLP allows machines to process and understand human language, whether it’s spoken or written. Think of it as the AI’s ears and reading comprehension. NLP breaks down language into components a computer can understand, analyzing grammar, syntax, semantics, and even nuances like sarcasm. Machine Learning (ML): Machine learning algorithms allow Conversational AI systems to learn from data. The more conversations a system has, the better it becomes at understanding different phrasing, […]