Customers expect more today from your business than just products or services. They expect experiences – specifically, experiences that are personalized, and that offer relevant responses in real time, through the channels they prefer.
In recent years, big names like Facebook and Google have popularized chatbots by allowing consumers to participate in human-like conversations with these bots to receive relevant, data-driven information to meet their needs. As more consumers have grown comfortable interacting with brands via chatbots, more businesses have also begun to explore how to leverage this technology to facilitate their own client experience.
But before you jump feet first, it’s important to understand the two different types of chatbots available (AI chatbots and Rules-based chatbots), and which is best suited for your business needs.
The difference between AI chatbots and Rules-based chatbots
Generally speaking, AI chatbots leverage machine learning. This type of chatbot is fed a large amount of data, is trained on the data to “learn” how to respond appropriately to incoming queries, and then uses this body of knowledge to provide answers based on the kinds of solutions that have worked in the past.
Suppose you work in telco and want to implement a chatbot. If you want your chatbot to mimic a live chat scenario where your customers can enter anything related to your business and receive a result, you’d want to explore an AI chatbot because it searches for meaning in the sentences provided by the customer, and will provide results based on what it has learned from your business operations.
A Rules-based chatbot, on the other hand, answers questions based on the workflows that have been defined for it. These rules can be simple or complex, and can leverage data from your CRM or other sources to provide personalized answers to customer queries in real time.
If you want your chatbot experience to provide more guidance to your customer and give them an experience that moves faster by replacing the friction of typing on a mobile keyboard with the modern messaging conveniences of quick replies, buttons and images, you’d want to explore a Rules-based chatbot which is less concerned with answering any possible topic and more focused on addressing specific queries as quickly and efficiently as possible.
Which type of chatbot is right for your business?
While we see tremendous future promise for artificial intelligence and chatbots, the reality is true consumer-grade AI solutions are expensive and time-consuming, and many of the practical applications for chatbots can be handled today by Rules-based chatbots.
When considering the chatbot that’s right for you, consider this:
1. Faster time-to-value
While an AI chatbot requires months or even years of data to be collected and analyzed before it can start generating answers to consumer questions, a Rules-based chatbot only requires a Subject Matter Expert to help create the conversational workflows.
With a Rules-based chatbot, you’re not collecting tons of data and then spending time training the chatbot to respond appropriately to this data; you’re mapping out the queries you want your chatbot to handle and then designing the conversation paths that will guide your customers to their intended destinations.
Because of the logical constraints of these guided conversations, your customers won’t be asked illogical questions and your business will see a much faster time-to-value. Out of the box, you’ll be able to address common customer queries quickly while retaining the flexibility to adjust existing conversational workflows or add new use cases as needed.
2. Easier to modify
As customers interact with your chatbot, you’ll discover room for improvements – this is true of both AI chatbots and Rules-based chatbots. The question then becomes: How do you adjust your chatbot to account for these discoveries?
With an AI chatbot, you’ll typically need to adjust the existing algorithms or commission a new learning project. Again, these are time-consuming tasks.
With a Rules-based chatbot, you can easily update your existing conversations or create entirely new conversations. Depending on the level of change, this could be minutes or hours of work, instead of days or months of research and training.
3. Conversational insights
While AI chatbot conversations can sometimes feel more “natural,” they are not always accurate. When these misfires occur, it’s not usually possible to determine exactly why the AI did what it did because the intelligence operates inside its own opaque environment.
This is frustrating because it makes correcting these mistakes more difficult – and, with more and more regulations providing citizens with a right to understand how their data is being used, if you cannot explain how your chatbot applied its logic to arrive at its decision… that could be truly problematic for your business.
With a Rules-based chatbot, this is not an issue. You can review the chat transcript and simply trace the workflow to understand why the bot did what it did, and then adjust the workflow to improve the results.
Both types of chatbots have a time and a place
Undeniably, advances keep coming in the realms of artificial intelligence and machine learning. Pitney Bowes continues to invest in these technologies because, one day, chatbots with true intelligence will be here.
Considering the current drawbacks to AI chatbots and the many benefits of the Rules-based approach, today Rules-based chatbots are the safer, more practical option.
Learn more about EngageOne Converse, the quick, affordable, low-risk chatbot solution from Pitney Bowes.