What is conversational AI? Use Cases, examples, and benefits

Best Chatbot Examples for Businesses from Leading Brands

examples of conversational ai

Learn how to join the discussion and drive sales with conversational commerce. A study conducted by WorkVivo emphasised that 98% of HR professionals self-reported burnout, while 94% said they felt overwhelmed and 88% of respondents said they dreaded work. According examples of conversational ai to Demand Sage, the chatbot industry is expected to grow from $137.6 million in 2023 to $239.2 million by 2025. As large enterprises and governments strive to remain ahead of the curve, implementing Conversational AI will become increasingly important.

  • People are developing it every day, so artificial intelligence can do more and more.
  • In fact, according to Google, shoppers are 40% more likely to spend more with a company that provides a highly personalized shopping experience.
  • HR has evolved from traditional personnel management to a more strategic and pivotal role in driving organisational success.
  • These bots are trained using natural language processing (NLP), which makes them capable of interpreting, understanding, and responding to human queries in a human-like way.
  • From here, you’ll need to teach your conversational AI the ways that a user may phrase or ask for this type of information.

By incorporating AI-powered chatbots and virtual assistants, businesses can take customer engagement to new heights. These intelligent assistants personalize interactions, ensuring that products and services meet individual customer needs. Valuable insights into customer preferences and behavior drive informed decision-making and targeted marketing strategies.

Conversational AI Chatbot Examples

You could even describe your symptoms so the AI can recommend a doctor whose specialization is right for your case. Watch our short video about how we’re wowing our customers with the power of AskAI. Customers can also use the bot to book in-store services and even virtually try on various products just by uploading their selfies. Conversational artificial intelligence has become a sensation in the last five years, with application almost everywhere. Although it has been around for decades, according to Google Trends, the search trends for “conversational AI” was almost nil from 2005 to 2017, but grew exponentially after that. Weekly conversion in 7.67x with chatbot launch for your eCommerce solution.

examples of conversational ai

All in a natural and conversational way that your customers will appreciate. Although conversational AI can perform a variety of functions and tasks, it’s still limited to what it was programmed to do. So, there will come a time when the website visitor will need to be redirected from the chatbot to live chat. Customer feedback helps to identify what you should improve and what your shoppers’ needs are. This data can show you what device clients use to make a purchase, what age group they belong to, what products they’re interested in and much more.

Best Use Cases and Examples of Conversational AI in 2024

Unlike some of the other bots in this list, the Insomnobot-3000 is a purely customer engagement bot with no direct sales directives. That said, this chatbot did bring thousands of valuable warm leads to the business for retargeting. The key differentiator between chatbots and conversational AI is that conversational AI uses Natural Language Processing (NLP) to recognize intents and engage in human-like conversations. Traditional chatbots, on the other hand, are generally rule-based and programmed to address specific commands and keywords.

By recognizing specific keywords and patterns, the AI determines the underlying goal of the user’s communication. This step is crucial for steering the conversation in the right direction and offering relevant responses. At the outset, users initiate conversations by providing inputs, which can be text or spoken words. These inputs set the foundation for the subsequent interaction with the conversational AI system, guiding it toward understanding the user’s needs and intentions.

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