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Principles to Design a Smarter Conversational Chatbot for any Business


Manoj Rupareliya

A lot of digital marketing enthusiasts are pitching the idea for chatbot integration on various platforms. Artificial Intelligence has been around for five decades, but the advent of Machine Learning has opened the door to newer horizons. Chatbots are a hot favorite when it comes to enterprise applications. In fact, more than half of millennials (59%) and Gen X (60%) have already interacted with bots (Business Insider.) This article is a quick guide to designing smarter conversational chatbots in a nutshell. Dive in deeper to explore more!

A chatbot software is a computer program that interacts with human users in a manner that replicates the interactive exchange of information, as in the case of two human beings. They are based on artificial cognition technologies and are classified into three major categories based on their application:

Support Chatbots:

They are designed to address subject-specific interactions such as business functions, processes, and common queries. Simplicity and extensive expertise in the concerned domain with multi-turn backdrop awareness are essential requirements for such bots.

Skills Chatbots:

They are relatively simple and don’t need contextual awareness since they are single-turn. They are meant to obey user commands given in a pre-defined manner through the speech without operating the device.

Assistant Chatbots:

They share their architecture with both support and skills chatbots in order to serve a multitude of requirements. Famous examples include Siri and Google Assistant.

A Capgemini research report on conversational commerce states that 87% of users find it satisfactory to make a purchase with the help of voice assistants in case of food products, 87% for financial transactions, and 83% in case of taxis.

As an internet user, you might have found websites hard to navigate, and finding the required information would demand tonnes of surfing. When websites/platforms take more than expected time to provide relevant information, it will decrease their chances of generating leads and solving queries. When you face difficulty in managing the operation costs and lead generation, using an enterprise chatbot would work like a charm as they provide value to your customers on a consistent basis with personalization. If you clearly visualize that the conversion ratio is lower with respect to visitors or find yourself struggling with the increasing engagements, a chatbot is the right choice for you.

When you start building a bot, you should develop a basic outline of the value proposition delivered to the users. Then decide the medium in which communication is to be made (voice-based/text-based) along with the type of bot. It will help in creating a profound user experience by communicating brand identity through its interactions. Then start building anticipatory use cases with relevant replies and NLP considerations. However, a conversational bot is different from intelligent assistant technologies. Like the Graphics UI, the conversational UI needs to be considered from both user requirements and the enterprise’s end to provide a smooth mediator platform.

According to Gartner, 2020 will witness 85% engagement with self-servicing and chatbots instead of a human to human communication.

It has to be simple, effective, and relevant to the purpose of interaction for the customers. While building a conversational bot, the designer shall keep in mind that the entire focus should be on making it useful rather than packing it with features and sophistication. Using complex UI would feel like using a luxury coupe in mountainous terrain- it might excite you but won’t suit the purpose. So here are the nine principles which will help in designing a smarter solution.

Keep it Simple Stupid

A lot of the designers build too intricate designs that would risk the effectiveness, and this leads to the first principle. The conversation should be kicked off with clear ‘bot’ identity message as confusing the identity to human can aggravate the situation by increasing the expectations of users. Keeping the perimeter to a minimalistic level regardless of the bandwidth of queries will help in serving the purpose better, and customer persona is equally essential. The medium and engagement spans for them play a vital role in tapping opportunities, so having them in your favor is a must.

Set Deliverables for your Bot

The deliverables such as giving quick responses, registering complaints, referring to policies and detailed explanations, facilitating a financial transaction, suggesting a product/service after noting inquiry, fetching contact details, and gathering feedback. This will make UI intuitive, prompt, and garner value to the interaction. This can be achieved by understanding the requirement from the user’s point of view. The communication should be lucid, intuitive, require minimum inputs, and provide the necessary information quickly to meet the expectations of the customers.

Build Platform-Friendly Bot with User Group Information

Understand the user demographics such as spending capacity, urgency, age group, income, attention span, and their preferences in general. By harnessing this information, one can play smarter in channelizing replies, suggesting the products and grievance resolving. A straightforward answer could go better with some social media platforms, while some web portals may require detailed explanations and product suggestions based on the nature of requirements. Narrowed and segmented information also helps the business in understanding the customers and how they expect their interactions to go. Giving a preview of reference URLs and keeping the native trends in conversations are some of the most common value additions.

Build Language Corpus and Predict the Task Flow for Interactions

As discussed above, the use of language and context is essential in the success of chatbots. The designers need to build a natural language corpus along with the sales and marketing team. Interweaving user-centric language processing will increase the conversion ratio. The bot will be as good as the data fed to it since most of the AI technologies need to learn from the information continuously. Natural language pattern (NLP) processing will increase the relevance of the bot to the customers as the task flow is developed on the basis of the course of chat interaction. The conversation shall be kept as short as possible

Reflect the Brand for Better Value Proposition

This is a part of the bot identity as the users will find it more appealing and trustworthy. Using friendly, localized tones helps in making the conversation relatable and boosts confidence at the same time. One thing to be noted is that computer programs serve the customers without any bias or preference, which helps people in being more open, contacting in more frequency, reduces stress and boosts confidence. Interestingly, being heard adequately also de-escalates the entire situation, and this has been used by salesmen since the starting of commercial pursuits. Tommy Hilfiger recorded an 87% return rate for customers by using Facebook’s Messenger App with chatbot integration (source.) This is one of the good examples of placing the value proposition by a brand.

Go Beyond Text

However, using texts is not engaging enough beyond a certain level. You can add contemporary art forms such as memes along with GIFs to instill a humorous tone for the conversations. If a person is willing to book a movie ticket for a Bond flick, a confirmation message with that movie’s meme congratulating them will engage the customers in an enchanting manner while simple confirmations don’t have an emotional impact on the human brains.

Soak in the User Persona for Better UX

Many a time, it becomes imperative to understand the requirements of recurring customers to improve their experience. This can be explained with the example that we change hair styling as per the current trends, but we avoid changing the salon or hairdresser. The same goes for chatbots. Predicting the repetitive transactions such as booking a cab or paying credit card bills on due dates helps in building trust by providing reliable assistance to the customers. A designer shall embed such functionalities to feed the system with personalized data to improve the user experience dramatically.

Use Structured Replies and Action Buttons Whenever Possible

In order to make the conversations more relevant to the user and chatbot, the use of structured reply buttons is a brilliant move since they reduce the complexity of communication by providing a direction to the course of interaction. Much confusion is created when the user can’t anticipate the right way to communicate and end up inputting long messages which aren’t suitable for software to understand. Instead, providing them with answers as options in reducing the time required to address the concerns. Adding Call To Action (CTA) buttons will increase the conversion ratio by leaps and bounds as customers can make prompt decisions.

Ensure Quick Back End Support

Of course, you’ve done a great job, but the aim is to ease communication and not to replace humans from things they do better. When the user finds it necessary to communicate with a real human being or bot finds it to be so, it is better to transfer the conversation to the human mediators so that things remain under control. As an example, the integration in payroll software will require human intervention when there are complications in compensation or in the case of legal liabilities where accountability cannot be transferred freely.

Follow each Principle as Long as it Serves your Requirement

As a matter of fact, most of the requirements have a unique customization trait that needs a particular feature more than the others. Being bound by strict rules and principles is not the right choice for software developers, especially when it comes to enterprise chatbots. Having them in mind will help in designing smarter solutions by simplifying the line of action.

Every revolution occurs after evolution, and this shall be the basis of design philosophy for developing smarter chatbots. Having these principles is like bulletproof jackets; they don’t change the situation, but it does help in dealing with them.

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