AI-powered chatbots can collect user information, organize meetings, drive lead generation, reduce overhead costs, and respond to customer inquiries, to achieve operational automation
“The original question, ‘Can machines think?’ I believe it to be too meaningless to deserve discussion.” — Alan Turing
From ELIZA and PARRY to A.L.I.C.E., Jabberwacky, and so many more, chatbots have come a long way since the inception of the text-based conversational interactions by Alan Turing in the 1950s. They are not even limited to textual mediums anymore. Conversational bots that have auditory and even sign-language capabilities to create an utmost personalized experience are becoming common!
Today, chatbots help businesses address various requirements either via a rule-based algorithm or through Artificial Intelligence (AI). These requirements include, but are not limited to, collecting user information, organizing meetings, driving lead generation, reducing overhead costs, and responding to customer inquiries, to achieve operational automation. Be it Facebook Messenger, WhatsApp, Slack, Skype or simple SMS texting – chatbots are everywhere.
The sheer profitability of integrating a chatbot into your existing system can be best explained by segregating their use cases. Chatbots can handle both simple and complex business tasks, thereby reducing the need for manpower, infrastructure, upskilling, and even multiple platforms. These business chatbots can be classified into:
- Menu-based Chatbots: As one of the most basic forms of Generative Conversational AI functioning in today’s market, menu- or option-based chatbots help the users communicate using pre-programmed pointers. These share a very close resemblance to the phone menus and are based on the decision tree hierarchy. Thriving on a series of buttons, this form of chatbots are ideal for handling repetitive customer support questions. The very same capability proves a disadvantage owing to its inability to handle more complex queries and scenarios.
- Keyword Identifying Chatbots: With the ability to identify keywords in the conversations, this chatbot gives relevant answers. Often, this type of chatbot uses a combination of keywords to arrive at the best response. While it seems like a next-gen innovation compared to menu-based chatbots, it is not without disadvantages. When a conversation goes on with several similar questions or having the same keywords, the responses start to repeat. A combination of menu-based and keyword identifying chatbots are often used to provide a better user experience.
- Contextual Chatbots: The most advanced among the three, this conversation-AI powered chatbot uses machine learning (ML) to ensure better context in its conversations. As a result, the dialogues are specific to each user and the bot learns with each conversation to provide a better engagement over time. With a focus on the data, the bot fares very well in engaging users for extended durations, hence helping in clarifying queries, generating leads and converting them.
Before we indulge in the hawk-eye view of the processes that chatbots automate, let’s have a look at how they do it.
The basic functioning of a chatbot
Support chatbots, which are still deployed in abundance, have functions based on a predefined set of rules. They detect keywords and fetch a response with matching keywords or wording patterns from a database. This database must be compiled by a developer beforehand using separate expressions or any other form of string analysis. The chatting capabilities are therefore restricted to the database exclusivity and the user must include at least one keyword in his/her chats to get a response. Their predecessors, the menu/button-based chatbots, had decision tree hierarchies that were presented to the user in the form of buttons.
The advanced versions, like the skills and assistance chatbots, use deep learning and sophisticated Natural Language Processing (NLP) systems to understand interactions and improve over time. These are smart bots capable of recording chat history, processing information, and providing adequate suggestions. They discover patterns in data and apply them to similar problems and questions. The user can ask Attachment Unit Interface (AUI) questions which the bot processes into a structured code via NLP. NLP essentially tackles the “The bot doesn’t understand what I am saying” scenario. The code generated from NLP is then run on the target system to retrieve answers and complete the loop. With this intelligence, skills, and assistance chatbots can perform tasks, solve problems, and manage information without human intervention.
Automating end-to-end processes
With the proliferation of messengers, apps, and virtual assistants that accentuate the need for chatting, the impact that chatbots bring to business has drastically increased. As their popularity increases, chatbots are going to get infused into more and more processes – from increasing customer engagement and supplementing promotional campaigns to offering additional ways of customer service. Here are the 5 types of chatbots that are being deployed by businesses across industries to automate processes.
FAQ Assistance & Site Navigation
By using a chatbot for answering FAQs and helping visitors navigate through the website, you can ensure that customers get answers to simple questions and find the content they are looking for easily. If the search flow is streamlined by eliminating the need for search and filter buttons and time to explore the brand is reduced, the purchase will automatically be quicker.
The FAQ chatbot can also provide a link to relevant questions if customers need or want to explore further and impart info on new features, sales, and seasonal greetings. Furthermore, you can loop in human agents in case of complex questions. This way, a repetitive, low-skill task is taken off your employees’ list and traffic is efficiently tackled.
For successful implementation of such a chatbot, either stand-alone on your website or through a messaging app, you need to feed in more than just the Q&A data and navigational menus. These bots need to be trained with context, follow-up questions, and scenarios to escalate questions to an agent. Beauty and fashion chatbots used by brands like H&M, Sephora, and Victoria’s Secret are a classic example of automation of site navigation and FAQ bot.
Acting as a 24x7 virtual sales agent, chatbots can automate the crucial process of holding conversations with potential customers, disseminating useful information, and regularly engaging with them. A lead generation chatbot can automatically send updates, notifications, and alerts based on a customer’s preferences alluring old customers back to your brand. The prompts and triggers introduced into the purchasing journey positively affect first-time visitors and old customers alike.
They mitigate the age-old customer hopping problems associated with long lead forms, incomplete information, and lack of an immediate touchpoint. Sophisticated versions can also qualify leads based on priority scorings and seamlessly integrate with leading CRM systems for closure. Chatbots deployed by brands like Yes Bank, NASSCOM, and Vodafone, specializes in engaging with prospects and generating leads from ads. Acting as a complete marketing tool, it employs nurturing workflows for the target audience and even offers marketing assistance. It enables you to improve the marketing KPIs by running smart follow-ups, detecting fake leads, and keeping you updated on campaign developments.
By deploying a chatbot for a transactional process, businesses can automate most of their activities. The bot can send you reminders of awaiting shipment, ask for permission before moving stock from the warehouse, compare costs, or sort and filter out orders as per any given criteria. Basically, it can perform simple functions the way a human would have done.
Acting as an advanced version of answering machines, transactional bots are optimized to follow a fixed set of conversation flow and execute specialized processes that replace the need to talk to an expert or use more complicated UIs such as mobile apps or websites. Being trained on structured data and a limited set of operations, these bots focus on finishing one task completely and often fail to understand unrelated queries or provide information when conversation derails.
However, they can simplify the user experience and carry out a function entirely on their own in a quick and convenient manner. Businesses with repeat transactional orders (bank verification, credit card issuance, purchase, procure, stock, distribute, etc.) can easily implement these bots.
A good example is Domino’s use of a transactional bot which allows customers to place their orders. Such chatbots are also used in the banking and insurance (BFSI) industry. Consider the following scenario: a person logs into a utility provider’s portal to pay the power bill. A virtual assistant present on the portal not only calculates and displays the outstanding payment amount but also asks “Can I help you pay your bill?”. This is why these chatbots have superior functioning and API/communication capabilities with conjugated platforms. It can improve the day’s sales outstanding (DSO) by means of conversations.
One of the best examples for this is the RBL Cares bot built by Senseforth.ai for RBL bank. This Generative Conversational AI solution displays exceptional financial transaction capabilities with one-time passwords to validate fund transfers.
This is a domain where businesses aim to utilize cognitive conversations to not only automate but enhance experiences. Chatbots make workplaces more collaborative and virtually connected transcending limitations like geographical boundaries, time differences, and departmental silos. Furthermore, employees that engage with chatbots tend to be more aware of business context which further benefits the organization.
Conversational platforms with advanced cognitive technologies are fostering the development of precise and customized automated dialogues efficiently catering to numerous employee-related processes. Tasks and experience delivery are streamlined by delegating activities to chatbots.
From onboarding and training to documentation/orientation reminders, addressing company-related doubts, policy changes, and even exit formalities – chatbots can be used to automate all HR processes. This way, the HR professionals do not need to deal with the never-ending, redundant queries of employees all the while tackling several administrative tasks. Employee enablement chatbots are not only people-friendly but also employee-centric and continuously evolve with them. It is like having a smart personal work-life assistant that gives relevant, contextual human-like answers to employee queries!
Chatbots deployed for customer care ensure that the customers and prospects alike get the information and experiences they seek when and where it suits them. Such chatbots are different from navigational, FAQ bots since they provide an end-to-end engagement to customers assisting in different activities in mature ways like reservations, purchasing, and purchase recommendations. They reduce the need for call centers and customer/technical support operators. They are, therefore, key elements in an organization’s digital journey to deliver next-generation intelligent customer service.
Mitsuku, available on Facebook Messenger, Kik, Telegram, Skype, and Twitch is a three-time winner of the Loebner Prize. This bot is designed to be a partner in interesting leisurely conversations - tell jokes, ask questions, discuss philosophy, and answer random questions (as per the training data). Another customer service chatbot is deployed by Amazon Look that helps the buying decision from start till the end – it “looks” at the visitor, matches clothes from the store, and even simulates how the final look would be like.
Healthcare also has numerous ways in which these bots can be integrated for superior yet inexpensive medical support. By the use of biometric wearables (Fitbit, ECG monitor, sensor) and chatting with medical aid chatbots, patients can get easy, on-the-go diagnosis and prescriptions for their ailments.
Lloyds Banking Group, Royal Bank of Scotland (RBS), Renault, and Citroën are also making use of chatbots instead of call centers to provide the first point of contact. RBS’s ‘Luvo’ chatbot is designed to free up time for advisors and resolve simple customer problems. Its functionality is planned to be expanded in the future with more detailed training data that covers the past queries of website and offline visitors. Such bots are avidly used in online music stores where a “May I help you?” is always at your service.
HDFC bank has been using chatbots effectively for years now. The bank’s EVA bot, built by Senseforth.ai. is trained on information on the website and other relevant knowledge bases. EVA is NLP-driven and responds based on intent, making it possible for it to handle complex issues. EVA processes over 300,000 queries each day. Similarly, SBI Cards’ ILA helps in answering static queries and clarifies transactional queries for users, such as account summary, apply for a card, credit limit inquiry and fund transfers, etc.. ILA also plays a pivotal role in lead generation and product recommendation, making it an important channel for revenue generation.
Move ahead with caution and pre-training
A chatbot project should be undertaken with your strategic and operational goals in mind to ensure the bot not only resolves the immediate issues but also improves the company’s productivity goals. But, how do you ensure that the time of deploying a chatbot into your traditional system is minimum, yet deliver optimum results?? How do you reduce the cost of deployment all the while training your chatbot with maximum user intents and possible scenarios? What can be done to guarantee the success of this business venture? The answer is simple - pre-trained customizable chatbots!
It is integral to conceptualize and make sure your bot performs perfectly in what it is designed to do even before you start building it. A pre-trained bot is a single package solution with pre-built features and industrial intelligence that especially assists you in doing so. It is architected to make your life easier by reducing the training time and effort, integrating seamlessly into the system, communicating with existing platforms, and allowing you to give the final touches of look and feel and company-centric persona.
With our unique blend of industry experience and expertise, Senseforth.ai offers you the best of solutions to become a ‘Conversational Enterprise’. Our bot store comprises a wide range of pre-trained bots for industries like BFSI, healthcare, retail, telecom, real estate and many more. You can plug-and-play them for functions like - loan advisory, EMI calculation, bill payments, filing an insurance claim & checking status, customer support, sales analytics, order tracking, invoice download, visa inquiry, ticket booking, etc. It’s time to unlock the untapped potential of your business by leveraging existing data and transforming customer experience.