How to build chatbots with conversational AI?

Irrespective of the business, there is an increasing need for brands to interact efficiently with their customers. The adoption of AI chatbots has seen a rise in recent times. They solve many customer concerns, including reducing wait time, improving customer service, enhancing customer engagement, and most importantly, staying available to customers round the clock.

This blog will discuss the various methods to create a chatbot and the parameters to keep in mind while building one for your business.

Identifying the purpose

A few years back, building a chatbot could take months – from writing the script to writing the answers to questions asked by consumers. With recent advancements in NLP, creating conversational bots has become much more efficient and user-friendly. The first step in making a chatbot is to identify your goal. Do you want to build a chatbot to reduce resolution, improve customer satisfaction, or bring on proactive top-notch customer service? Finding answers to these questions would help you move on to the next step in creating a chatbot.

Rules-based or conversational AI chatbots?

Have you been frustrated by a website chatbot when it continually raises the same question or gives you an irrelevant answer to your query? That’s a traditionally scripted chatbot. In other words, the former requires manually writing out responses to anticipated customer queries beforehand. At the same time, the latter one is powered by understanding the various ways of asking the same question without being trained on every form of utterance.

The main concern with traditional chatbots is that they have to be trained manually with every possibility of a question or phrase, which cannot provide the desired response when replaced by a synonym. So, companies have to come up with every possibility of a customer query manually and provide a suitable response to it. On the contrary, conversational chatbots can relate to similar phrases and synonyms and understand the context of what the customer is trying to say.

Let us consider an example. Zylker is an e-commerce company that initially started with a traditional rules-based chatbot and moved on to a conversational AI chatbot. Here’s why:

For the question “How do I pay my bill?”, Zylker had to develop more than 500 variations for a straightforward question like the above one. That’s when they decided to move to conversational AI chatbots that can apprehend what a customer is trying to say and resolve their intent.

Another exciting aspect of conversational bots is the answer bots, wherein instead of scrolling through pages of articles and FAQs, users can receive a response in seconds. This way, issue resolution time is significantly reduced, and customer service is improved.

Low-code, pro code, & no code

There are three ways to build a chatbot: minimum coding, writing code from scratch, or going codeless. While it is considered effective and advantageous in terms of customization to build something from scratch, pro code platforms for conversational chatbots have their disadvantages. Riddled with puzzling software terms and heaps of code, building chatbots become complicated and time-consuming and are limited to only a few skilled developers.

On the other hand, as the names suggest, low-code and codeless platforms empower businesses to set up chatbots quickly. There has been an increasing trend in low-code and no-code platforms, as they drastically reduce development time and investment costs for businesses.

Quoting the above example, Zylker uses a drag-and-drop interface to create a simple and effective conversational AI chatbot that can provide personalized recommendations, process orders, help with billing, and even pick out answers for user queries from their resource library.

Use chatbots to gain more prospects

Communicating and resolving user queries is the primary goal of using chatbots, but more is that. A conversational chatbot also becomes an extension of the brand and helps to turn more prospects into valuable customers.

Taking Zylker as an example again, they created a welcome message for visitors landing on their website, with a chatbot lead form in it. Once an interested prospect enters their email address, the company could contact them and address their requirement. In addition, they also created flows to encourage existing customers to review their products.

Ultimately, the thing is to create a chatbot that’s beneficial to a prospect/customer, reduces manual intervention, and improves your brand visibility and experience. Chatbots give customers a personal experience of your brand that email campaigns don’t. 

Creating a conversational AI chatbot with Zobot

With SalesIQ’s chatbot platform, Zobot, you can build a pro code chatbot from scratch or a codeless bot using our drag-and-drop interface. SalesIQ also provides an Answer Bot that understands customer queries and provides prompt answers from your resource library. Sign up today for a 15-day free trial and build a conversational AI chatbot for your business in a hassle-free way.