Chatbot 101 — From the history to the future of Chatbots

The Complete Beginner’s Guide of Conversational AI

“Hey Alexa, what is the weather like today?” “Ola Siri, What time is it? “Hey Food Genie, can you book a table for me at Olive’s Kitchen at 7 PM today” “Ok, Google, am I your best friend?!”

Oh! Come on, we know all of us have done the last one at least! 😉 But the question here is, who are we talking to? Who is responding to us? Where and how did it come into existence? What is under the hood? And why is everyone talking about it?

Chatbots, virtual assistants, or conversational AI assistants are some of the popular buzzwords today, and every organization/industry is adapting them.

We are about to demystify the jargon and know what this deal is all about! You game? Let’s go!

So, What is a Chatbot?

A chatter robot (chatbot) is a computer program designed to simulate an intelligent conversation with human users in natural language via voice or textual methods.

Chatbots are versatile enough to carry out conversations and even tasks for the users. They can be as simple as programs that answer a simple query with a single-line response or as complex as digital assistants that learn and evolve to deliver increasing levels of personalization.

5 Levels of Conversational AI assistants

How are they categorized?

Chatbots are primarily of two types,

  • Rule-based chatbots (Scripted chatbots) — These types of chatbots can only interact with users by following pre-programmed rules. Instant responses, quick answers, FAQs, complaint resolution, and mostly all the facets of customer support are achievable through these chatbots. This ensures the round-the-clock availability of businesses. These chatbots are less intelligent.

For example, a designer boutique’s customer support chatbot would need to cater to operational questions about the store, like the timings, apparel variety, location, etc., and also handle basic tasks like making an appointment with the designer, scheduling a pickup, and notifying the customer about the order status. All of which will follow a flow and a pattern.

  • AI chatbots (Virtual assistants) are self-trained and powered by machine learning. They bank on artificial intelligence to learn and respond based on interactions with users. These are not hardcoded like the rule-based predecessor. These bots learn from the conversational datasets(conversations with the users) and predict the response.

Retrieval-based model-based chatbots are close-domain, sweep through the database of answers, and provide the most relevant answer with the highest rank. Usually used when conversation scope is limited to a topic.

Generative models-based chatbots are open-domain and generate answers based on the words in the input. It is complex and prone to error. Used when there is no focused scope and generic. Siri and Google assistant are good examples of AI chatbots.

Why Chatbots?

Chatbot dons multiple hats, that of an on-demand help desk representative, a troubleshooter, and a personal assistant, all of it together. It’s a package! Of course, one would love to chat rather than have multiple calls with the one who always listens! 😉

As per a statistical report submitted by HubSpot, “approximately 21% of the customers believe that chatbots are the best and easiest way to initiate a conversation with any business”

  • Handling customer queries with near-immediate response time. Many users can use the chatbot in parallel and get quick responses 24/7 without having to wait for an agent. Bots can redirect it to agents when required. This decreases customer churn.
  • Engaging users is super easy. With faster and most relevant responses from chatbots, users are more glued to the conversation than lose interest.
  • Products/Services are marketed to a wider audience. Using chatbots as an interactive marketing campaign, the users have an active experience, and the availability of chatbots on Facebook makes it easier to grab widespread attention across a huge spectrum of people.
  • Data collection and Lead Generation. It helps in the collection of user data with an interactive way of gathering information. This data can be used for further analysis and recommendations.
  • Money and Time-efficient. Engaging multiple users simultaneously saves time and money on customer service staff. The staff is preserved to solve more complex queries.

From the user’s perspective, chatting with a human-like chatbot seems easy, engaging, and fun!

Before we get to the rise and rise of the Chatbot industry, let us have a look at chatbot history!

What is the history of Chatbots?

Knowing about a new niche technology is interesting, but the history and the story that led to its creation are sure compelling!

History of Chatbots

The timeline from the advent of chatbots to now,

1950 — The Turing Test: This test laid the foundation of a chatbot. Alan Turing challenged scientists to create a program that would be indistinguishable from a human in a natural language conversation. And assured this would revolutionize conversations with machines.

Turing Test
Turing Test

1966 — Eliza: World’s first chatbot mimicked human conversations by responding with scripted word strings with a list of possible responses. User reaction to Eliza chatbot was compelling, with many experts claiming them to be indistinguishable from the human mind against Joseph Weizenbaum’s view that a human mind is unique and cannot be replaced or mimicked by a bot. Turing tests were widely used to disprove Joseph Weizenbaum’s theory.

1972 — Parry: Parry was developed by a psychiatrist to imitate a patient with schizophrenia. Unlike Eliza, responses were assigned weights to verbal inputs. Testing was inconclusive in the ’70s, with a variation of Turing tests not being adequate coupled with weak technology.

1988 — Jabberwacky: Jabberwacky chatbot was developed to imitate human conversation. Jabberwacky led to technological advancement, which adhered AI concept of “contextual pattern matching.”

1992 — Dr. Sbaitso: Dr. Sbaitso was created to be incorporated in MS-Dos, which was a voice-operated chatbot. The chatbot would converse with the user as a psychologist.

1995 — A.L.I.C.E. (Artificial Linguistic Internet Computer Entity): It uses heuristic pattern matching to carry conversations. ALICE was reprogrammed with XML and Java and later was open-sourced into different programming and foreign languages. ALICE chats as a young girl simulating a real person.

2001 — SmartChild: A precursor to SIRI was developed and used by AOL and MSN messenger to initiate a conversation with people aged 18–24, which was a data exchange to access other services.

Then came all the current AI bots,

2006 — WATSON: IBM came up with WATSON to play at the infamous show ‘Jeopardy!’ with the ability to defeat human champions

2010 — Siri: Apple created a smart, intelligent and powerful assistant that goes to length to perform many tasks for the user through natural language UI.

2012 — Google Now: Launched by Google Inc. to compete with Siri, Google Now was an assistant that could help users search for information and provide recommendations.

2014 — Cortana: Microsoft created her with the ability to perform various tasks like sending texts, chitchat, finding locations, and recommending places by either typing or through voice.

2014 — Alexa: Amazon’s Alexa has become a family member for many. She performs innumerable tasks such as querying, playing music, setting alarms, making a checklist, and even controlling other home devices(IoT).

2017 — Google Assistant: A successor of Google Now, is used in a google search where the information is provided in the simplest format.

How do Chatbots work?

Chatbots or digital assistants use Natural Language Processing to communicate with humans. Known as NLP, this technology focuses on understanding how humans communicate with each other and how we can get a computer to understand and replicate this behavior.

For example, if we say “Hello” to a chatbot, it understands that this is similar to ‘Hi’ or ‘Good morning’ because we taught the machine to understand so. This is a simple example, but sometimes the same word can mean different things. There is a big difference between “I’m fine” and “Pay the fine.” Just like humans, computers need context to learn what you mean. Chatbots are trained to understand the difference with the use of machine learning.

NLP helps in the classification of the intent and entity extraction

How are Chatbots being leveraged across industries?

eCommerce

eCommerce being one of the most booming industries (One good impact of the pandemic), the usage of chatbots is predominant. Be it marketing, sales, or customer service, all of it is taken care of by the chatbot. Hence, many eCom businesses like Sephora and Nike have deployed chatbots on apps like Facebook, WeChat, WhatsApp, and many more.

eCommerce Chatbot

Few uses of chatbots in the eCommerce industry,

  1. 24/7 Support: In a scenario where the shopper in us wakes up at 2 AM and starts shopping online and BAM! there is an issue. Well, a customer agent can be off the clock, but a chatbot comes to the rescue.
  2. Offers and Discounts!: Chatbots can be used to send offers, rewards, and discounts per user using recommendations based on customer interactions.
  3. Recommendations and Re-engagement: Based on the user conversations, the chatbot intelligently provides recommendations, tracks products and notifies product restock, and engages the user in case the cart is abandoned.
  4. Gauge Consumer Base: The bot learns the patterns of consumer conversations and picks up on the trends and repetitive queries. This helps to target the audience with a tasteful strategy and customer engagement.

Banking

Money is what the world revolves around, and the bank keeps our bucks. Chatbots help a great deal in letting us know our account balance, reminding us to pay credit card bills on time, handling transactions in a jiffy, helping us with investments, and helping the bank save huge money. How cool?!

“Chatbots can deliver cost savings of over $8 billion per year by 2022 in the banking and healthcare sectors” — Juniper Research.

Banking Chatbot

Few of the many ways chatbot is used in the banking industry,

  1. Answering all the common basic questions: Like “When is my credit card payment due?”, “What is the credit limit?”, “What is my loan status?”
  2. Simple Transactions: Payment of loans, transferring money, and other non-complex tasks can be carried out by chatbots.
  3. Issue handling: Faster issue resolution is possible with chatbots in place, and they can redirect to an agent when necessary.
  4. Marketing products and offers: Chatbots can notify users of the latest loan schemes, online services, and rewards.
  5. Lead Generation: Through consumer engagement, chatbots can get lead opportunities.
  6. Quick resolutions for fraud: Say you are mugged(God forbid!), you cannot wait around for an agent to block the cards, chatbots can do it at the click of a button.

Insurance

Insurance keeps us at peace, and chatbots just make our life more at peace.

Insurance Chatbot

Some of the insurance uses of a chatbot are,

  1. Advising best insurances: Based on the user’s history, advising the apt insurance plan ranging from basic to premium.
  2. Suggesting policies: Chatbots segment and engage consumers by making personalized recommendations of policies and services and then handling the baton to the agent.
  3. Answering the plethora of questions: Chatbot handles all the FAQs posed by consumers with ease.
  4. Filling forms: Chatbots can be designed to capture information to fill a form, the user would respond to each field without having to feel tedious.

Healthcare

One of the gigantic industries that have benefited from the advent of chatbots is Healthcare.

Healthcare Chatbot
  1. Monitoring health: Chatbots can act as authentic assistants by reminding them to sip water, pop a tablet, or provide healthy tips.
  2. Assisting doctors: Doctors too get overwhelmed with the enormous number of names in the medical field. Chatbots can quickly help them with medicine names, dosages, or standards.
  3. Booking appointments: Chatbots help the patients make appointments and follow-ups.
  4. Providing general information: Users can key in the symptoms, and the chatbot can supply information on illnesses, remedies, suggestions from doctors, etc.

To better inform the world about COVID-19, WHO has launched a Facebook Messenger version of its Health Alert platform — offering instant and accurate information about COVID-19– via Facebook’s global reach.

Government

If there is one industry that does get a lot of complaints and queries is undoubtedly the government. The answer to handling the mammoth queries shot towards the government is CHATBOT!

Government Chatbot
  1. Accessing information: Users can get detailed information about their records, public laws, rules, articles, etc.
  2. Answering queries 24/7: Users can get answers to their questions even on public holidays. No need to wait!
  3. Form filling: Processing of government paper submissions, form filling need not be done by waiting in the line, say Hello to chatbot!
  4. Complaint collection: All the complaints and issues can be gathered and segmented.
  5. Periodic surveys: Surveys related to the operation of the government or law can be done and feedback assimilated.

HR

“Oh, when is the next holiday?”, ” I lost my Employee card, how can I get a new one?”, “How many leaves do I have?” — These are common questions directed toward the HRs of every company. Thanks to chatbots, they will do the answering for the mundane, repetitive questions.

HR Chatbot
  1. Functioning of HR: Tasks like onboarding, recruitment, and learning, can be done through chatbots so that the HRs can concentrate on other initiatives.
  2. Policy and Procedure sharing: Company information such as policy changes, procedure updates, and organization structure modifications can be shared through chatbots, and related questions can be answered.
  3. Assisting with tasks: Applying for leave, subscription for office transport, tracking attendance can be done, etc., can be done via a chatbot.
  4. Announcement of events/changes: Notifications can be sent to employees on major events and fire alerts and can also help in employee engagement.

Apart from these industries, retail, food, travel, music, and telecom- are all moving towards inculcating chatbots. Chatbots are here to stay!

What are Chatbot platforms?

The first step is to derive how the conversation should flow and how the chatbot should respond. Once the flow and scope are frozen, comes the question of on what platform the chatbot should be built. Chatbots can be built from scratch, but several frameworks and tools are available that make it super easy!

There are pre-made platforms that can help in the implementation of NLP into chatbots. Some of the popular chatbot platforms are,

What is the Future of Chatbots?

Decades back, it was predicted that chatbots or the conversational AI world would penetrate into all the areas. That day is not too far, where more and more streams are adapting chatbots that are AI-powered and gaining a massive advantage over other peers.

Banks, real estate market, healthcare, hospitality, the internet of things, agriculture, legal, leisure, and entertainment — all the facets of life are going to utilize chatbots soon, and eventually, every human can have a fully functional AI-powered personal assistant right in their pocket, making our world a more efficient and connected place to live and work.

An ecosystem of chatbots

Chatbot’s influence on marketing, customer insights, and predictability of user actions will grow immensely even with the rapid growth of users. NLP and Deep learning possibilities will make chatbots abler and perform near-human operations.

What are the Limitations of Chatbots?

Though chatbots have tons of pros, some cons need to be acknowledged. Apart from keeping the data secure, making the dialogue lively, and trying to understand mixed languages, Chatbots lack emotional intelligence. Though chatbots do a good job of engaging the users, retaining the customer can be a challenge where human intervention is necessary. Chatbots do not have the ability to differentiate between good and bad. Hence decision-making is not their thing!

Wrapping it up, despite the limitations of chatbots, more and more companies are investing in them and reaping the benefits! Our journey through chatbots from history, the breakup, the makeup, the pros and cons, and the sleek feel has led us to a bright horizon where opportunity meets unending human needs! The initial and final goal of a chatbot is the realization of a near-human feel which is still unattained, making the eventual evolution of chatbots exciting!

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