Recommender systems are software applications that help users to find items of interest in situations of information overload. Current research often assumes a one-shot interaction paradigm, where the users' preferences are estimated based on past observed behavior and where the presentation of a ranked list of suggestions is the main, one-directional form of user interaction. Conversational recommender systems (CRS) take a different approach and support a richer set of interactions. These interactions can, for example, help to improve the preference elicitation process or allow the user to ask questions about the recommendations and to give feedback. The interest in CRS has significantly increased in the past few years. This development is mainly due to the significant progress in the area of natural language processing, the emergence of new voice-controlled home assistants, and the increased use of chatbot technology. With this paper, we provide a detailed survey of existing approaches to conversational recommendation. We categorize these approaches in various dimensions, e.g., in terms of the supported user intents or the knowledge they use in the background. Moreover, we discuss technological approaches, review how CRS are evaluated, and finally identify a number of gaps that deserve more research in the future.
In today's cluttered marketing world, there are many buzzwords that are commonly used by the industry professionals. To ease up the process, we'll first start with the basics before diving into the context of behavioral segmentation marketing. Market segmentation refers to the process of dividing a market of potential customers into groups, or segments, based on different characteristics. Simply put, any market segmentation based on customer behavior or customer buying behavior is behavioral segmentation. With the use of behavioral segmentation marketing, an e-business owner can quickly categorize his customers on the basis of number of times they have visited their online store, what products they have bought, what categories they prefer, if they are registered members and target them accordingly through several marketing channels.
The implementation of AI in ecommerce should come as no surprise. Online businesses have always been quick to adopt new technologies, and this is how the industry thrives; enhancing the customer experience, discovering new markets, and driving further sales. And with the continued development of AI technology like chatbots, visual search, and personalized recommendations, the world of ecommerce is transforming again. But just how effective and useful is AI-powered tech? Where is it being used?
Artificial intelligence has the power of transforming anything remotely stupid into an intelligent object! Yes, AI has been doing this for quite some time now and with the rise of voice assistants, things have become more exciting. Businesses around the world, have now understood the importance of "Voice Commerce". It all began with speech-to-text technology developed by Google. 'Google Voice Search' has been launched for iPhones, this advance app utilized data centers so that it can easily compute data and can analyze data, this is actually a good example of human speech.
Do you find Artificial Intelligence (AI) and Machine Learning (ML) too overwhelming? Think AI and ML applications are limited to the technological domain? If yes, then let us enlighten you with the fact that both these technologies have more ordinary use cases than you can imagine. In fact, we all are already using AI and ML in our day-to-day lives – right from using real-time navigation to surfing the web. AI and ML are simplifying our routine operations in more ways than one.
We've assembled a detailed list of 25 of the most impactful use cases for AI in eCommerce to help you get a grip on where to focus now and in the future. Artificial intelligence is changing how marketers can collect customer data and drive business intelligence. This is evident in the way data is being used to inform marketing outputs in ways that marketers hadn't been able to access (or scale) before. Descriptive analytics is the foundation of all analytics -- it's concerned with "what happened" and the basic analytics infrastructure including Google Analytics. Descriptive analytics help ensure your house is in order before tackling more advanced kinds of analysis. Diagnostic analytics helps explain "why" things happen.
Artificial Intelligence as a breakthrough technology is continuing to transform our lives in myriad ways. From intelligent chatbots capable to answer questions and guide users to virtual assistants responding to our commands for fulfilling tasks to smart and intelligent cars adjusting to typical user preferences, there is a multitude of ways artificial intelligence has penetrated our lives. Naturally, ecommerce cannot be left without reaping the benefits of AI for customer-centric product search, customer support, personalized recommendations, and customer support. Magento as the most popular and widely used ecommerce CMS platform has integrated AI with a whole array of plugins and extensions. If you have a Magento ecommerce store you can easily give your customers sophisticated AI-based shopping experience.
Artificial Intelligence (AI) is by far one of the most praised trends in Silicon Valley. Yet, in the "real world", opinions tend to be split into two camps: those who desire AI-driven personal assistants on the one hand, and those who fear that such AI solutions will steal their jobs in the future, on the other. Nevermind that Hollywood-like scenario though – the truth is that AI is already here, reading our emails, listening to our conversations, recognizing our faces, and even smelling our breath! AI is not a shiny addition. It is a must-have for any business innovations, and e-commerce seems to be in the avant-garde.
There is for all intents and purposes no industry that has stayed immaculate by the effect of Artificial Intelligence, be it Education, e-Commerce, Agriculture or Employment. The savvy approach it equips any business with, without a doubt empowers these organizations to be progressively effective at providing to their clients. Furthermore, something beyond being one more of the main tech-trends of these years, m-commerce has demonstrated to be a growing popular modern way for shopping. Artificial Intelligence has allowed m-commerce with new trends in 2019 to make more pleasant and comfortable shopping experience for shoppers. Supported by Artificial Intelligence, the e- commerce and m-commerce platforms are prepared to use the extensive data related to the customer behavior.
Commerce moved beyond brick-and-mortar stores, seized the online space, and is steadily crippling into mobile. Modern online shopping offers unparalleled flexibility of access and selection of available interfaces. You can shop away while on a bus. You can buy your next favorite gadget while relaxing on a lawn on a beautiful sunny day. That's why mobile commerce is such a fast-growing niche that caters specifically to smartphone users and their respective app ecosystems.