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The Complete Guide on Conversational Chatbots in 2021

What is a chatbot? Why chatbots are important? Can I build a chatbot from scratch or use some chatbot platform? What are the best strategies for leveraging chatbots for business growth?

Must be wondering — Is this for real? We know the idea of chatbots can be a little intimidating to begin with but robots aren’t here to take over our jobs or control humans, seriously!. They’re here to make our day to day life easier. The year of 2021 is set to become the year of the chatbot and businesses are gearing up themselves with chatbots to interact, engage and up-sell their customers at scale.

In this comprehensive guide, we’ll show you how to deploy smart chatbots for your business to free-up yourself from monotonous and time-consuming tasks. And raise customer experience to the whole new level by providing immediate assistance to your existing customers, potential clients and of course window shoppers to spread the word around.

What are chatbots?

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The Ultimate Chatting Machine For Your Business

Chatbot 🗣️ ˈCHatbät/ - aka virtual assistant or conversational agent - - is a computer program based on predefined logic trying to emulate human speech or textual conversation. The entire experience is based on mimicking the real-life conversation between two or more individuals. Today, such applications are widely seen in the customer service space, assuming roles conventionally performed by living, breathing human beings in the customer support or tele-calling department.

Chatbots leverage chat mediums like SMS, website and social messaging platforms like Facebook, Slack, Twitter, Whatsapp to receive and respond to messages.

How do chatbots work?

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Understanding Architecture Models of Chatbot and Response Generation Mechanisms

From architecture perspective, a chatbot can look like a normal app. There’s an application layer, AI engine (optional), a database, and APIs to call external services except rich UI which is deliberately replaced by chat interface. On the contrary to mobile application which comes with a rich UI interface having multiple tabs & drawers, chat interface is primarily governed by dialogue flow to allow peer to peer messaging focusing on what the user wants and how to deliver that.

What are different types of chatbots?

There are two kinds of modern chatbots.

  • Rule-based chatbots that can respond to specific commands.
  • Artificial intelligence chatbots that respond to natural language.

There also exist third category — Hybrid chatbots, having the best of both worlds

Rule-based chatbot (Basic chatbot)

You might have seen this conversation pattern in some of the chatbots. The primary goal is to guide the user in the process of getting the service he wants. The chatbot can simply start with few suggestions and let the user choose one. This is followed by series of questions in the attempt to narrow down the search further to acquire important user information while the conversation continues. This one-on-one pattern continues until the chatbot has all the information to assist the user with the relevant information.

Rule-based conversations might seem pretty basic to the user who’s expecting more but it’s actually designed not to bother the user as much as possible and stick to the business objectives all the time. Some businesses find rule-based conversations very convenient to design with different scenarios good enough to engage the user and drive the conversation smartly.

The complexity is a bit increased when chatbot allows user to enter input as a free text message. At this point, the bot expert has to make provision to ensure that chatbot can understand the input by interpreting it correctly. For instance when chatbot ask simple question to the user “what’s your email address?” In the ideal world, one expects a person’s response with a valid email address but very often users unintentionally enter email addresses in the wrong format. To deal with such a nuisance, some sort of validation is always required to ensure the correct input.

In short, from learning perspective, the rule-based chatbots mostly follow the linear conversational flow and knows how to handle answers, leaving less work for the chatbot owner to be done in terms of guesswork.

AI chatbot (Smart chatbot)

Everybody knows how Google Assistant or Amazon Alexa works. You may ask anything and expect some sort of reply which answers your query or in some cases, it might prompt bot to ask few questions back to you in order to narrow down the scope of the search.

Such conversational chatbots are trained with the help of Artificial intelligence. The bot making process for building AI chatbots is quite sophisticated. Broadly, it does always include these three protocols -

Data processing — Multi-step natural language processing workflow to correctly recognize and infer free input text. The process requires serious engineering efforts when input is multi-line &/or multi-objective. We’ve outlined some basic NLP steps required to process the raw text or voice (converted to text for NLP processing)

  • Tokenization - Tokenization breaks sentences down into discrete words or tokens, stripping out punctuations that are linguistically significant or otherwise useful for the application.
  • Named entity recognition (NER) - Looks for categories of words, like the name of a product, a person’s name, or an address. or custom defined entities.
  • Text Normalization - Processes text in an effort to find common spelling or typographical errors that can change the intended meaning of the user’s request.
  • POS (Parts-of-speech) tagging - Identifies parts of speech — nouns, verbs, adjectives - in the text with the goal to identify complex sentence structures and how those structures might impact meaning.
  • Dependency parsing - Looks for subjects and objects in the given text to find dependent phrases.
  • Sentiment analysis - Watches to learn if the chat conversation by any chance is going south, it will prompt the human agent to take over the conversation.
  • For instance, let's take a simple chatbot, and it does only one thing: Orders takeout. When someone texts the message "I want to order a Black Forest cake" the bot would hopefully recognize the command ("order") and the entity (“black forest cake") as request. It then proceeds to perform the next action i.e asking person’s name and email address. While this method simply allows chatbot to understand basic commands, they’re a far cry from actually understanding the structure and purpose of language
  • Now add some complexity to the above example - the sentence "Please deliver Black Forest cake with cherries on the top" might confuse a basic chatbot that can only process simple commands, but dependency parser would hopefully recognize that ("cherries") is meant to modify ("black forest cake") Understanding dependency parsing allows bots to understand and act upon a much wider array of actions, or even ask the user additional questions until they understand the request.

Contextuality — Availability of previous chat conversations (message logs) to build knowledge graph. This helps program to learn interdependency between dialogues and the course of action so that chatbot can drive the conversation in the right direction.

Chatbot training — Provision to learn new conversations all the time to improve chatbot’s performance with the help of unsupervised methods based on machine learning techniques or in the supervised manner assisted by humans.

From learning perspective, it offers advantage to the user to initialize the conversation as per his or her need rather than guided by the bot in the conversation. Overall such user experience is quite reassuring that the user has some sort of control over the conversation.

How to get started with chatbot?

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Basic Steps to Getting Started with Building Chatbots

How to create your own bot? You might want to know the answer that how much does it cost to build a chatbot, well! it depends. There are three variables which affect the cost of chatbot development -

Business vertical — Companies developing chatbots for verticals like e-commerce, travel, fashion & hospitality usually lookout for better customer engagement with robust design while government-regulated sectors like healthcare, finance, insurance, etc. lookout for data privacy protocols in place which adds up to significant overhead to the overall chatbot cost.

Type of interaction — If the chatbot is based on the menu-driven approach and uses pre-defined options for the user to select, the cost is usually low. But if the chatbot uses NLP methods to recognize the user utterance enabling human-like interaction, it will leads to a higher cost.

Third party integration — For building simple lead generation flow or automating FAQs, the development cost is usually low. If you want your chatbot that books a flight or notifies user on leaving the abandoned cart, these chatbots require deeper integration with the backend system and will lead to a higher development cost.

Building chatbot from scratch

Building chatbot from scratch is not a piece of cake. Having sound knowledge on how to mimic conversation programmatically, understanding utterances and training the chatbot to respond humanlike is a skilful work. It’s not like that you deploy the chatbot once and it will keep up and running on its own. It’s a full-time job to maintain the chatbot with improved content and developed technology. Both time and money are required especially given its adoption.

Chatbot builder platform (Chatbot As A Service Platform)

Many times using out of the box solution works better in terms of saving resources, especially when you want to immediately try out the product and understand customer or visitor’s behavior. This gradually and eventually reduces customer support turn-around time.

Secondly, companies working chatbot technology keep adding new features so you will remain up to date in terms of technology. Platform providers also keep a tab on the method of conversation prevalent in the industry. They only use best-trusted interactions and methods which are applicable to the wider population, covering the most common case scenarios.

If the current solutions aren’t sufficient enough to serve your needs, then you must talk to these companies for customization. They will relatively do it in a better way catering to your specific needs.

How to design chatbot?

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Designing Chatbot Conversations like a Professional

Let’s grab a bag of chips! and be with us to learn about what brands and businesses need to look out so that chatbot conversation is fun, engaging and easy on hands both for newbie and experts.

Identify goals of your chatbot

Before jumping on to design conversational flow, make sure you have figured out real problems that should be handled by chatbot. For instance — do you want your chatbot to be informational? Or do you want it to complete some task like collecting feedbacks or doing surveys? Ask yourself these questions and then start designing your chatbot.

Offer proactive tips & suggestions to the user

Many times users don’t know what to say. To take the take pressure off from the user, the chatbot should provide some or suggestions to kick off the conversation as well as navigate the user throughout the conversation.

Personify your chatbot with the help of avatars

People like to respond to faces and that’s why chatbots should be personified to derive maximum attention. Choosing an avatar that could represent itself as the face of a company, can play a major role in shaping the right perception for the brand. It is not necessary to come up with the avatar always, but something that can add some personality to the chatbot.

Choose language wisely

Pay close attention to the language and vocabulary of your chatbot that it uses to interact with users, as well as the info you can convey in association with the messages it sends — The choices you make here will shape your user’s perception of its persona, which sets the tone for the entire interaction.

Many companies are now considering chatbots as a powerful medium to carry out meaningful interactions with their valuable customers — which proves the rich potential that chatbots offer in their simplicity and intuitiveness/p>

Forms vs. Website Chatbot — Which One Serves Better?

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Your Conversational Form needs a better home — It’s your Website

We all have gone through the miserable experience of filling bank, insurance, property, and mutual fund forms. You have to put all the mandatory inputs and even when one column is missing or wrong the web page will prompt you to fill the entire form or at the least ask you to fill the required fields again. This really frustrates the user at times and is the notable culprit for higher bounce rate. On the contrary, a chatbot offers you whole new experience by mimicking the human element in filling forms. With two way communication, a bot can offer better way to funnel leads and interact with customers online. Here are some top reasons why -

Chatbots are here for instant gratification

Suppose you are interacting with a chatbot regarding current offers on a specific make & model of the car — let’s say Hyundai Verna 2021. During the conversation it may ask you “Which colour do you like Red, White or Silver”? What type of engine do you prefer, Petrol or Diesel? Do you want to know the finance options on Hyundai cars? Are you planning to book a test drive?

ou may not notice but with each user input, the form is filling in the background. Steadily, the conversation derives you to the point when it asks for the personal information with human touch. So it’s like hitting two birds with one stone. There is a cherry on the top called "Partial leads". What if someone leaves the conversation in the middle, still you have some information & self-reported preferences which business can utilize for re-marketing campaigns on Google or Facebook. Bada Bing Bada Boom! 😃

Personalize user experience for every customer

Since chatbots are dynamic in nature allowing logical jumps or , it can smartly adjust the question based on previous response. For instance, if user has shown interest in Apple’s iPhone X. Then the bot will tailor its next question based on the previous response “Would you like to buy Airpods for your new iPhone X?”

Displaying questions to the user based on the initial response and subsequent responses makes entire experience surreal and human too. What we call this up-selling at it’s best. The experience that conventional web form may not be able to offer.

Chatbot versus live chat: which one serves what purpose & why?

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The Best Conversational Strategy for Your Business

The last time you were on a live chat, did you get instant response to your question, or were you asked to drop your email address so that they can call back you later? More importantly, you may not have appreciated dropping an email address in the first go!

It’s annoying when you need an instant response to your query but you can’t get it. It’s frustrating!. You will either leave for another brand or send the email and expect a reply soon — which often takes more than 48 hours. It is sad, right?

Live chat is an awesome technology if implemented with ample human resources, it can help you move your visitors to the bottom of the sales funnel faster. However, when enough attention is not given to live chat due to lack of resources since it’s a costly affair after-all. It eventually leads to unhappy endings and delivers the worst possible customer experience ever imagined by the businesses.

Another reason, GEN Y & GEN Z (millennials) act promptly and today’s most interfaces of big brands are still not able to cope up with these generations.

Although sophisticated chatbots can be very responsive, they are still limited to what they can do. In fact, it can’t give more answers beyond what it’s taught to say — come on, it’s programming.

So, is live chat winning the customer service game over chatbots?

We’ve gathered some top reasons why chatbot together with live chat can offer a better engagement experience.

Chatbot can repeat itself

One of the top benefits of deploying chatbot is freeing up yourself from doing repetitive tasks like answering FAQs or helping customers with common case scenarios without involving a human being. Psychologically, humans do find it frustrating to answer the same set of queries again and again. By automating such rote tasks, a business can save time, resources and energy.

Chatbots are here to build the trust

Chatbots are like for your business. They are the mouthpiece of your business, they converse with the customers and build trust for your brand. More importantly, they are not biased and user experience is always unified.

Chatbots are available 24x7

The 24x7 availability of chatbots makes them some sort of marvel’s comics character with supernatural power. They never need a coffee break, never sleeps, never get sick and never take a vacation. Wow!

A worth mentioning application would be the implantation of a chatbot on the . It can serve thousands of customers simultaneously, making their shopping easy at any given point of time.

Chatbot, decision trees & business goals

Most AI chatbots are programmed based on the decision trees to serve important business goals. Customer buying metrics such as time on the landing page, visitation history, past preferences, items purchased and similar other insights form the basis upon which chatbot can take decisions autonomously in the best interest of the business.

Save money on live agents by bringing more automation

Every business strives hard to save resources. Instead of recruiting, training and paying multiple agents for the customer support, chatbots offer excellent alternative way to deploy less resources and bring more automation to the overall process and improve productivity.

Hybrid approach — chatbot to human handoff

Are you sure your chatbot knows everything! You’re wrong. No matter how sophisticated your chatbot’s AI and machine learning capabilities are or how much attention you’ve paid to design its dialogue flow. There are moments when it can make a mistake. In some cases, these moments aren’t even the chatbot’s fault and are more so related to users not using the chatbot correctly or having false expectations regarding what it offers as a service.

During those critical moments, having a human agent as a backup will help businesses ensure that users are taken care of regardless whose mistake it was.

What Google trends shows about chatbots?

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Chatbots are the future of m-commerce: healthcare, fin-tech & startups

Google trends allows you to see how popular search terms have been overtime on Google along with related demographic information as estimated by Google. So, we used Google trends to find how popular “chatbot” term is — 

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You can see quite clearly that over the past several years especially after 2017 there’s been skyrocketing growth in chatbot searches. You might notice slight dips but for the most part, the search volume for this niche is pretty stable.

Makerobos’s stance on chatbots

In this demanding lifestyle, customers are unable to synchronize with the businesses on time. According to a recent study, fully-engaged customer represents 23% more revenue than average. If you don’t have a , you could be missing opportunities to interact with customers and building a long-lasting relationship with them.

  • "Consumers like chatting, so deploying a best chatbot on website opens up untapped opportunity for businesses to engage, nurture & turn their visitors into loyal customers. Further, people are already acquainted with mobile interface and businesses just need to tap on this. chatbot building platform offers instant chatbot that comes with app-like look and feel, which makes easy for companies to interact with customers anywhere"
  • Robinder Gauba, CEO and Founder of Makerobos Innovation Labs and Former Vice President, CarDekho.com, Girnar Software Pvt. Ltd.

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