Conversational Ai That Delivers On Customer Service

Adaptability should be a key element of a successful product, and that means allowing partners or other features to be built on top of your solution. The best AI chatbots have the capacity to integrate to third party software, such as CRM, HR platforms, or inventory management tools. Inbenta’s NLP technology and intent detection detects a user’s sentiment Conversational AI Chatbot through the interaction and escalates the conversation to human agents if the issues cannot be resolved by a bot. Having seen all the ways that Conversational AI platforms are helping businesses become more competitive, improve customer engagement and boost brand loyalty, the next step is to determine how to frame a conversational AI project.

No matter what channel they’re using, time of day they’re searching, or native language they speak, our AI chatbots are ready to reach out and help your customers along every step of their journey. Overall, the conversational AI market in the customer service space is divided into three key categories, Roberti explained. The first are conversational AI specialists, with platforms that have user interfaces tailored for both the technical and non-technical user; out-of-the-box integrations; and a wide variety of channels. “Those are the ones that Gartner has called out as leaders in the space,” he said. Conversational AI uses multiple technologies to converse with customers in natural, human-like language.


It automates FAQs and streamlines processes to respond to customers quickly and decreases the load on agents. With instant messaging and voice solutions, CAI encourages self-service to resolve queries, find relevant information and book meetings with technicians. Conversational Chatbots allow e-commerce and retail companies to reach out to their customers in real-time and around the clock through two-way conversations. E-commerce companies can provide pre-and post-purchase support, enable catalogue browsing on multiple channels and share notifications on shipment, refund and return orders. With conversational AI, companies can retarget abandoned carts and increase sales. AI chatbots can interact with students at any time of day, through multiple channels and in many languages. Chatbots can also access student data and past interaction to know the level they are in with regards to the lectures and keep them updated, while recommending relevant learning content, making learning easier. The Inbenta chatbots understand customers in their natural, colloquial language.

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Additionally, deciding the conversational AI design is an important process. The interactions in the conversational AI platform must be aligned with the company’s business model, goals and customer personas. Additionally, human language includes text and voice inputs that can easily be misinterpreted such as sarcasm, metaphors, typos, coversationla ai variations in sentence structure or strong accents. Programmers must teach natural language applications to recognize and understand these variations. While symbolic AI makes things more visible and is more transparent, one of the main differences between machine learning and traditional symbolic reasoning is how the learning happens.

Conversational Ai Examples

The semantic search engine has been a success, managing nearly 15,000 requests per month. As expected, this relieves pressure on contact centers and helps human agents who need access to accurate information. Insurance firms are also using conversational AI, albeit chatbots or knowledge bases to assist in internal processes. By leveraging the features of Natural Language Processing technology, these solutions can understand the true intentions behind customer’s questions and instantly retrieve the right answer from a knowledge base. Businesses therefore must look for the best forms of ensuring self-service to their clients. These can be chatbots, dynamic FAQs, semantic search engines, customer knowledge bases and more.

  • Proactive chatbots are another approach to using chatbots and conversational AI.
  • You can also help retrain the AI if it did not provide the correct response in a specific scenario, enhancing the experience over time.
  • From conducting in-depth analysis to uncover actionable business insights to the creation of data-driven recommendation systems, technological advancements allow big data to be utilized in different ways.
  • It provides customers with fast, consistent and accurate answers across applications, devices or channels.