While most enterprises use the terms bots and conversational AI interchangeably, the two technologies have their key differences. In the last few years, bots have presented a new way for organizations to adopt NLP technologies to generate traffic and engagement. Understanding what is a bot and what is conversational AI can go a long way in picking the right solution for your business.
Bots are text-based interfaces that are constructed using rule-based logic to accomplish predetermined actions. If bots are rule-based and linear following a predetermined conversational flow, conversational AI is the opposite. As opposed to relying on a rigid structure, conversational AI utilizes NLP, machine learning, and contextualization to deliver a more dynamic scalable user experience.
Conversational AI platforms feed off inputs and sources such as websites, databases, and APIs. In contrast, bots require continual effort and maintenance with text-only commands and inputs to remain up to date and effective. Conversational AI platforms benefit from the malleable nature of their design, carrying out fluid interactions with users.
For example, if a user changes their mind mid-conversation and has a seemingly random query than what they initiated, a conversational AI platform can keep up with human randomness and automatically break out of the conversation flow to provide a sensical, timely response. A bot in comparison doesn’t have this ability to topic switch and is more confined within its predefined script, as well as the nature of its static rules means it cannot produce any output that was not manually placed in its flow.
Companies are making an investment in conversational AI due to their potential to have noticeably personalized, fluid conversations with customers. Conversational AI mimics human-to-human interplay to the extent that it’s hard to inform whether or not the person is speaking to a human or an AI. But first, reflect on it. Does your enterprise really want that stage of personalization? Can you gain all of your targets with bots instead?
Bots also can customize conversations to an extent. They can speak to the person with their call and feature a persona too. For a small enterprise loaded with repetitive queries, bots are very beneficial for filtering out leads and offering applicable records to the users.
In recent years, companies have found bot to be stopgap short-term solutions as opposed to effective fixes to their interfacing challenges, leaving disconnected bots that don’t cohesively feed into each other across their sites. With Conversational AI, the ability to build effective Digital Assistants is viable and efficient. Customer interactions with these platforms are consistent and quality across the brand, whether customers are interfacing with in-depth sales questions, or troubleshooting a support issue.
Conversational AI can also harness past interactions with each individual customer across channels-online, via phone, or SMS. It effortlessly pulls a customer’s personal info, services it's engaged with, order history, and other data to create personalized and contextualized conversations. Most bots on the other hand only know what the customer explicitly tells them, and likely make the customer manually input information that the company or service should already have.
You can certainly use bots to alleviate some of your challenges, but if your objective is to create a competitive advantage and build truly great customer interactions, then you must use a more advanced set of tools to build conversational AI.
The first set of analytics that is important to admins are generic usage statistics. Is the bot used, on what devices...