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Why build a Chatbot?

Why build a Chatbot?

In the history of Chatbot , the year 2020 will be remembered as the year in which chats made their presence difficult to ignore. One of the most discussed and watched commercials in Super Bowl 2020 was the one for Amazon Alexa with Ellen DeGeneres and Portia de Rossi. When a company decides to pay millions of dollars for a 30-second ad during a break,…Build a chatbot is a priority.

What is a Chatbot?

A chatbot is a conversational software that allows companies to communicate with their audiences instantaneously and in a personalized way without having to cut back on automation. Most people associate intelligent chatbots with AI. However, AI is not essential to creating a smart, functional bot.

Here are the different types of chatbots:

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Menu/button-based chatbots

Menu/button-based chatbots are the most basic type of chatbots currently implemented in the market today. In most cases, these chatbots are glorified decision tree hierarchies presented to the user in the form of buttons. Similar to the automated phone menus we all interact with on almost a daily basis, these chatbots require the user to make several selections to dig deeper towards the ultimate answer.

While these build a chatbot are sufficient for answering FAQs that makeup 80% of support queries; they fall short in more advanced scenarios in which there are too many variables or too much knowledge at play to predict how users should get to specific answers with confidence. It’s also worth noting that menu/button-based chatbots are the slowest in terms of getting the user to their desired value.

 

Linguistic Based (Rule-Based Chatbots)

If you can predict the types of questions your customers may ask, a linguistic chatbot might be the solution for you. Linguistic or rules-based chatbots create conversational flows using if/then logic. First, you have to define the language conditions of your chatbots. Conditions can be created to assess the words, the order of the words, synonyms, and more. If the incoming query matches the conditions defined by your chatbot, your customers can receive the appropriate help in no time. 

However, it’s your job to ensure that each permutation and combination of each question is defined, otherwise, the chatbot will not understand your customer’s input. This is why a linguistic model, while incredibly common, can be slow to develop. These chatbots demand rigidity and specificity.

3

Keyword recognition-based chatbots (build a chatbot)

Unlike menu-based chatbots, keyword recognition-based chatbots can listen to what users type and respond appropriately. These chatbots utilize customizable keywords and an AI application – Natural Language Processing (NLP) to determine how to serve an appropriate response to the user.

These types of chatbots fall short when they have to answer a lot of similar questions. The NLP chatbots will start to slip when there are keyword redundancies between several related questions.

It is quite popular to see chatbots that are a hybrid of keyword recognition-based and menu/button-based. These chatbots provide users with the choice to try to ask their questions directly or use the chatbot’s menu buttons if the keyword recognition functionality is yielding poor results or the user requires some guidance to find their answer.

4

Machine Learning chatbots

Ever wondered what is a contextual chatbot? A contextual chatbot is far more advanced than the three bots discussed previously. These types of chatbots utilize Machine Learning(ML) and Artificial Intelligence (AI) to remember conversations with specific users to learn and grow over time. Unlike keyword recognition-based bots, chatbots that have contextual awareness are smart enough to self-improve based on what users are asking for and how they are asking it.

For example, a contextual chatbot that allows users to order food; the chatbot will store the data from each conversation and learn what the user likes to order. The result is that eventually when a user chats with this chatbot, it will remember their most common order, their delivery address, and their payment information and merely ask if they’d like to repeat this order. Instead of having to respond to several questions the user just has to answer with ‘Yes’ and the food is ready! 

While this food ordering example is elementary, it is easy to see just how powerful conversation context can be when harnessed with AI and ML. The ultimate goal of any chatbot should be to provide an improved user experience over the alternative of the status quo. Leveraging conversation context is one of the best ways to shorten processes like these via a build a chatbot

5

The hybrid model (build a chatbot)

Businesses love the sophistication of AI-chatbots, but don’t always have the talents or the large volumes of data to support them. So, they opt for the hybrid model. The hybrid chatbot model offers the best of both worlds- the simplicity of the rules-based chatbots, with the complexity build a chatbot of the AI-bots. 

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Voice bots

To make conversational interfaces even more vernacular, businesses are now beginning to use voice-based chatbots or voice bots. Voice bots have been on the rise for the last couple of years, with virtual assistants like Apple’s Siri, to Amazon’s Alexa, and why? Because of the convenience they bring. It’s much easier for a customer to speak rather than type. A voice-activated chatbot brings frictionless experiences directly to the end customer.

 

What Type of Chatbot do you build a chatbot?

While deciding if a chatbot is right for you, place yourself in the shoes of your users and think about the value they’re trying to receive. Is conversational context going to significantly impact this value? If not, then it is probably not worth the time and resources to implement at the moment.

 

Another thing to consider is your target user base and their UX preferences. Some users may prefer to have the chatbot guide them with visual menu buttons rather than an open-ended experience where they’re required to ask the chatbot questions directly. All the more reason to have users extensively test your chatbot before you fully commit and push it live.

 

The right chatbot is the one that best fits the value proposition you’re trying to convey to your users. In some cases, that could require enterprise-level AI capabilities; however, in other instances, simple menu buttons may be the perfect solution.


 

 

 

 

 

 

 

 

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