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What are Chatbots & Will They Change How We Interact with Computers?

It’s 7 am and your phone chimes. This is Slackbot, sending a notification about how your schedule looks like today.

Lark alerts you on calorie intake at breakfast and Hello Hipmunk sends you a notification that flight tickets for your next business trip are booked.

Bots are everywhere and they are changing the way we interact with businesses!

What are Chatbots?

Chatbots are a type of conversational AI solution designed to help humans interact with machines using natural language. They are essentially a piece of software that can engage in a text-based conversation.

It isn’t only in our personal life that we notice the pervasive presence of bots. They are also impacting the way businesses communicate with their customers.

There was a time when businesses hired a room full of people to provide customer service. Today, many of them rely on Facebook messenger bot, WhatsApp bots, and WeChat to reach out to their customers. Chatbots are blurring the line between human and computer-led interaction and are creating a personalized experience for every user.

With the evolution of chatbots, the need for human intervention has drastically reduced. To have a fair understanding of this current scenario, let’s have a look at how human-machine interaction has evolved over the past few years.

Evolution of Chatbots

1920

The two components of the word chatbot – ‘chat’ & ‘bot’, capture the conversational nature of these tools and represent the digital subsection of our concept of ‘robots’. In 1920, Karel Čapek in his science-fiction play first introduced the word ‘robot’ and showed the first-ever form of human-computer interaction.

1950

Alan Turing wrote a paper starting with a question “Can machines think?” To find an answer, he conducted a thought experiment and asked if a machine can successfully play a game. He dubbed it ‘the Imitation Game’. Through this experiment, Turing concluded that by understanding language and interacting like a human, machines can be perceived as intelligent things.

1956

The Dartmouth Summer Research Project on Artificial Intelligence spearheaded by John McCarthy laid the groundwork for future research and exploration in the field of machine-human communication. This was an attempt to find out if machines can use language to form abstractions and concepts and solve problems. This conjecture took the concept of ‘chatting’ beyond purely human communication into a foundational fabric, for the future of machine intelligence.

1964

Joseph Weizenbaum’s ELIZA is considered by some as the world’s first chatbot! By using Natural Language Processing (NLP) it parsed typed user inputs, interpreted those inputs, & responded accordingly. This nascent chatbot had a rule-based scripted response and did relatively little ‘intelligent’ computation in the background.

1988

Fast-forwarding to 1988, we find Rollo Carpenter’s humorous chatterbot, Jabberwacky. Its capability to simulate natural human chat, interestingly and humorously, makes it an interesting road marker in our evolution chart. Unlike Eliza’s simple script-based conversation model, Jabberwacky’s working-memory-based model leveraged a well-understood trick of human psychology.

2001

SmarterChild was a step forward in the trajectory of machine intelligence & human-computer interaction. Instead of exhibiting basic intelligence by carrying out a trivial conversation, it enabled users to access real-time news and information. Chatbots were no longer a novelty, but could now help us with practical, day-to-day tasks via IM on AIM, MSN Messenger, and Yahoo messenger.

2006

Watson marks a significant advancement in machine intelligence & Natural Language Processing. It showed the world, combining multiple elements within sentences, it can respond appropriately. Today, its underlying technology is deployed in various domains, helping businesses to grow.

Present Day

From creating bots for research and novelty in the ’90s to building them today for utility - this trajectory shows how chatbots have evolved. Amazon’s Alexa, Apple’s Siri, Google Assistant, and Microsoft’s Cortana - have transformed the current landscape of chatbots. They can imitate human conversations, help customers have their queries answered in real-time, crack jokes, and even play songs for us!

By leveraging NLU, LSTM (Long short-term memory) and DM (Dialogue Management), chatbots today are built thoughtfully and designed to address requirements for specific domains. Advanced conversational AI platforms are making them more intelligent and functional, keeping the user needs & goals in mind. Imbibed with the ability to ‘understand’ the mood of the user, chatbots have brought down the expenditure on maintaining a large base of customer service representatives and have also improved workforce efficiency.

Hence, the demand for chatbots is increasing at a tremendous pace across verticals. In a recent survey, Gartner predicted that 85% of our engagement with businesses will be done without interacting with another human by 2020. Instead, we’ll be using self-service options and chatbots.

Chatbots are being adopted to automate processes like sales, marketing, lead generation, and customer service. During this survey, 42% of participants responded that automation technologies in these areas will improve the customer experience. 48% said that they already use automation technology for various business functions, and the other 40% said they are planning to implement some form of automated technology by 2020.

Let’s have a look at the following use cases to understand how chatbots are changing the way we interact:

Chatbots in Healthcare

AI-powered chatbots in Healthcare aim to make medical diagnosis faster, easier, and more transparent by personalizing medical care and sending reminders for appointments and medications. Be it, patients or physicians, healthcare chatbots provide accurate responses to the ever-growing range of medical questions of users.

  • For patients, some chatbots function as care managers, helping deliver crucial information to patients about conditions, illnesses, upcoming procedures or scheduling appointments. They provide 24/7 assistance for patients to check an existing prescription, answer follow-up questions and reduce the number of repetitive support calls to hospital staff. By accessing medical databases and patient history, chatbots can provide the required information securely, in full compliance with standard healthcare regulations.
  • The Cancer bot, for instance, supports patients going through chemotherapy with medications. It also advises the friends and family of patients on how to provide emotional support.
  • For the hospitals, clinics and health care organizations, chatbots cover the entire workflow of patient care, leading to a well-managed healthcare system. They ensure internal resources can be free of repetitive tasks and have time to focus on critical cases. Healthcare chatbots also help doctors by providing them with timely updates on patient health and work as a connector between the patient and the doctor.
  • Let’s take the example of SafedrugBot, a chatbot messaging service that offers readily accessible drug information guides to doctors. It acts as an assistant for health professionals and shows the active ingredients within medications, as well as recommends alternatives to drugs.

Chatbots in Retail

The retail industry has always relied on customer service to build brand value. The more consistent the service is, the faster the brand can gain trust and expand its customer base. While businesses strive to excel in customer engagement and personalization, providing 24/7 call support comes at a significant cost. Customer support chatbots provide superior customer service online, anytime, anywhere without requiring human intervention and reducing burn-out.

  • Retail chatbots can make shopping a simple and more enjoyable experience for customers. By simulating the experience of shopping in a physical store or by providing after-sales support, they engage customers on a personal level. By referring to past transactions and buying patterns of customers, they can make product recommendations and lend support at the point of sales.
  • Tacobot, a chatbot for Taco Bell, helps customers optimize their time by navigating them through the food menu. It engages customers with sharp and witty responses and answers questions, organizes group orders, and facilitate transactions.
  • In eCommerce retail, chatbots help customers browse through the huge inventory and provide shoppers what they have been looking for. Apart from recommending products, they can also upsell and cross-sell by suggesting a pair of sneakers with the black jeans that the customer has added to the cart.
  • Sephora’s chatbot deployed on the messaging platform Kik drives sales by leveraging the one-to-one experience and replicating in-store conversations. It helps customers to find products by recommending tailored beauty solutions based on their skin type and tone.
  • By leveraging behavioral economics, chatbots are helping retailers to track customer satisfaction. Mood tracking technologies are helping chatbots to understand customer preferences - their likes and dislikes. This helps retailers to have a better understanding of their customers’ choices and adjust their inventories accordingly.
  • Retailers are also adopting chatbots to provide not only online but also in-store assistance. Chatbots can be used as an alternative to traditional checkout counters and speed up the payment process, especially during festivals and weekends. As virtual counters, chatbots can solve check out issues and enhance the customer experience.

Chatbots in Banking

Banking chatbots cater to a wide range of customer requirements. Starting with credit report updates and bill payments to financial advice, chatbots provide one-stop assistance for customers to seamlessly access all the information they need.

  • Chatbots are integrated into banking websites and every time a customer visits the webpage, they initiate a conversation to gauge the intent. This helps generate ‘leads’ and is a much more effective way of communicating with customers in real-time instead of traditional emails and cold calls. They simplify banking processes for customers and either give them direct solutions or redirect them to the right person.

When it comes to financial services, customers approach banks with a lot of apprehensions. Chatbots offer answers to specific queries without overwhelming customers with information.

For instance, HDFC’s Eva understands user queries and fetches the requested information from thousands of possible sources, in a matter of milliseconds.

  • Banking chatbots support internal teams by guiding new members through initial processes and training. They can also help with back end tasks and optimize employee’s time.
  • For instance, JP Morgan Chase’s COIN helps the team to analyze commercial-loan agreements. It has effectively brought 360,000 man-hours down to seconds and is less error-prone and faster than human lawyers.

The versatility of chatbots and their use cases in the plethora of industries clearly show how far conversational AI has come from Turing’s thought experiment in the 90s. The innovations at play have created a plethora of applications for chatbots in multiple functions across verticals. No matter the complexity of the processes at hand, a chatbot can be built to simplify the issue and deliver the required results.

Powered by Conversational AI platforms, chatbots are becoming more smarter and more human-like in engaging customers with smooth, conversational messages. Conversational interfaces are not limited to chatbots. With the rapid developments in technology, businesses can build bots that can engage in voice-based conversations.

Senseforth’s A.Ware, a proprietary conversational AI platform, allows businesses to build industry and function-specific bots with both chat and voice interfaces. We follow an omnichannel approach wherein our bots can be applied across different enterprise use cases and across a broader selection of engagement channels, including WhatsApp, Slack and Facebook Messenger and mobile apps, among others.

Our ready to deploy bots require no coding and cater to diverse industry use cases. Powered by A.Ware, we create bots on a foundation that can scale with enterprise requirements. These are exciting times for the future of conversational interfaces, and businesses have a chance to deliver exceptional omnichannel customer experience through bots. After all, a happy customer is more likely to spend time and money on a brand than a disengaged one!