What is the best conversational AI? Chatbot vs conversational AI
So, while the robots are doing this, your teams can move their skills to more immediate and less mundane jobs. Plus, there’s less chance of bot breaks, and a lighter load placed on Live Agents. Consumers use virtual assistants for a few different reasons, the most popular being to access information, consume content, and issue simple tasks like checking the weather. Conversational AI provides the chance for brands to feel more human, providing that authenticity that chatbots lack. So, if chatbots are scripted, rule-based, and pre-determined, conversational AI is the opposite.
You can turn the creativity up or down (like you might in the OpenAI playground) and even customize the look and feel of your bot. And you can even train the bot on specific documents, so it can serve as a knowledge source based on your documentation. Or you can start with a pre-made template like the Business Coach bot, the Explain bot, or the ZapChat bot. Instead of building a commercial chatbot like all the competition, it decided to launch its own AI model with a generous open licensing framework.
Customer support bot deployed by a major telecom provider
Apple’s Siri is an example of a conversational chatbot that learns the more you use it. Smart chatbots leverage more machine learning and NLP to understand the user asking the questions or provide contextual answers and responses. Conversational chatbots learn, allowing them to pick up on preferences and provide recommendations. A chatbot is a type of computer program or software that simulates human conversation with your customers. You can use chatbot technology to help customers find answers to common questions, answer inquiries, and even provide basic support to improve the customer experience.
They can also provide irrelevant or inaccurate information in this scenario, which can lead to users leaving an interaction feeling frustrated. Users can interact with a chatbot, which will interpret the information it is given and attempt to give a relevant response. When you understand how much customers hate waiting on hold, you can appreciate how much this improves the customer experience. Of course, there are difficult customer cases that require the attention of a skilled human operator. However, it would be a mistake to imagine that the latest generation of conversational AI chatbots suffers from the same problems as old-fashioned chatbots.
Pros of Chatbots
If you are confused between ‘Machine Learning vs Rule-based’, you should first understand what is AI and bots! Let us take a tour of rule-based and conversational AI to help you choose the best tool for your business. Chatbot training is a manual process and requires programming every flow and utterance of a question. A human workforce also identifies and implements ongoing improvements.
These bots are similar to automated phone menus where the customer has to make a series of choices to reach the answers they’re looking for. The technology is ideal for answering FAQs and addressing basic customer issues. Conversational AI, NLU, & NLP, together with help computers to interpret human language by understanding the basic speech parts. The most basic difference between the two is that Conversational AI is AI-based and chatbots are rule-based. Simply put, It allows computers to process text or voice into a language they understand.
This is a frequent problem which leads users to question the smartness of the bot. Consider the use case of a conversational AI agent deployed for a hospital or healthcare institution to disseminate health and wellness content to customers and patients. It may be considered smart if it provides useful information via its responses 80% of the time. But if the hospital is more interested in reducing the workload of its operations and administrative team scheduling and actualisation, then the benchmark for smartness may be different. So, in the context of voice assistance and multilingual, conversational AI stands ahead of chatbots again.
Instead, customers can block credit cards, file insurance claims, upgrading data plans, scan invoices and much more – directly from the chat window. One of the most common conversational AI applications, virtual assistants — like Siri, Alexa and Cortana — use ML to ease business operations. They are typically voice-activated and can be integrated into smart speakers and mobile devices. Last but not the least, the “smartness” of the conversational AI depends heavily on the data set used for its training.
Virtual Assistants and Conversational AI are more advanced than chatbots. Well, Virtual Assistants and Conversational AI are driven by the latest advances in cognitive computing; natural language processing, and natural language understanding. Virtual assistants use conversational AI and can engage in complex, multi topic conversations. Virtual assistants utilise natural language processing, like our friend conversational AI, in order to understand and perform tasks from the user. But unlike conversational AI, virtual assistants use their AI technology to respond to user requests and voice commands on devices such as smart speakers.
In fact, the global conversational AI market is forecasted to reach $15.7 billion by 2024. Organizations often have apprehension about how technology could impact the human element. Your agents hold critical insights and information, and conversational AI can help you tap into that by sourcing pasting tickets, knowledge bases, and time-saving shortcuts. It solves the challenge of manual work involved in locating all these resources. Much of the time, there is an expectation that tickets will grow at certain times, such as during the holidays. For retailers, shipping companies, and others moving products throughout the ecosystem, their customer contact numbers can double or triple.
Also, conversational AI is equipped with a simulated emotional intelligence, so it can detect user sentiments, and assess the customer mood. This means it can make an informed decision on what are the best steps to take. Chatbots have a very limited ability to tackle the minute details of customer complaints, as they are restricted by their scripts.
Read more about Chatbot vs Conversational Differences You Should Know here.