“Hello! How may I help you?”
“Um…hi! I was wondering if you could tell me more about…you.”
“Yes. I am curious about understanding what exactly a chatbot is and what it does.”
“Ah! Great. Shall I begin from the beginning then?”
A chatbot is a computer program powered by rules or Artificial Intelligence, you see, that users can communicate with, via a chat interface.
Chatbots interact with users, interpret and process their words, and reply to their questions automatically within seconds.
Today, chatbots can be found serving a variety of functions across a range of platforms like FB Messenger, Slack, Telegram, Skype, websites, apps, and more. You might have acquainted yourself with one while buying shoes online? Or while canceling an unused subscription, haven’t you?
For a better illustration, let us look at this example:
A customer finds the food they had ordered lacking taste and quality. Now, instead of ringing up the restaurant or the customer care guys at the delivery service, they can just go back to the app, take up the issue with the bot, and have their order refunded or replaced within minutes.
And since the idea of using human language in communication with machines was first conceived in the early 50s, this technology has come notably far. Today chatbot usage has become almost entrenched in industries spanning healthcare, education, eCommerce, and finance to the point where 1.4 bn people now use them regularly. Experts predict that 90% of the customer interactions in banks will be automated by 2022.
And it’s not just the finance world that’s going big on the technology.
Around 60% of millennials resort to chatbots to purchase essential goods. Today, there is a chatbot to get weather updates, order groceries, know the breaking news of the day, receive personalized stories as per preferences, receive life advice, financial advice, schedule meetings, and so on.
In a way, we can say chatbots are the tools companies today employ to help customers resolve their queries quickly and with little hassle.
But what’s the big deal?
Why do customers love chatbots? And what is the big opportunity that businesses see in them?
People are so excited about using chatbots simply because they like to chat. With friends, with relatives, even with brands. And they prefer to do so over dialing up a business for customer support or having to navigate their websites in search of what they are looking for. As per Facebook research, 56% of people would rather message than call customer care. And 53% of people are more likely to shop with businesses they can message.
The reason being, chatbots are faster and more effective in resolving customer queries. As per Hubspot research, 71% of people want to use messaging apps to get help with their questions primarily because they want their problem solved fast.
…and businesses will naturally build their services where the customers are
Today’s messaging apps attract more global users than traditional social networks — to the point that 63% of consumers think businesses should be on Messenger. Since their evolution from a humble messaging channel into an expansive multimedia hub supporting photos, videos, games, payments, and more, people are logging in more than ever to these chat platforms to connect with brands and discover their merchandise and content rather than just exchange GIFs with their peeps.
The most popular services have hundreds of millions of monthly active users (MAU). And plummeting data prices, cheaper devices, and advancing features are only helping their cause. Since any company will focus on building its services where its customers are, businesses today are readily recognising this coming-of-age of messaging apps and their massive potential as awesome avenues for connecting to their customers. So they are building innovative strategies like leveraging the collaborative intelligence of chatbots to drive user engagement on these messaging apps for lucrative monetisation of their vast fanbase.
Right. But what does a chatbot do? What can it really do for businesses? For the customers?
Okay. Let’s look at the benefits for everyone involved.
1. Provide quick response and prompt customer service
Among customers who use chatbots, a good 37% use them for getting answers in case of an emergency. That’s a massive pain point among customers who agree that companies that have online forms, non-response email addresses, or telephone numbers that are hard to get through regularly put them off with inconveniently long wait periods for responses.
A ‘Customer Lifecycle Survey’ found that around 53% of customers are likely to quit halfway through when faced with sluggish responses. 73% of respondents say that the most important thing companies should immediately latch on is valuing their customers’ time.
AI-powered chatbots offer this speed and convenience of service that customers desire. They give instant replies backed by factual data and can reduce wait periods to less than 2 seconds.
2. Reduce IVR frustration for customers
57% of customers would instead contact companies via digital media than use voice-based customer support, as per Ameyo’s research. Forrester says, nearly 1/3 of customers report sending a mobile/SMS message to the company requesting assistance. Contacting the support arm of a business can feel like a chore to many customers, especially when it comes to having to repeat themselves all over again over a frustrating, robotic, and impersonal IVR call. Around 90% of consumers expect an online portal for customer service, as per Microsoft.
By using friendly and approachable AI-powered chatbots, businesses can ensure that customers can have their unique issues understood and addressed via a simple text request.
3. Empower support employees with real-time critical customer information
Sample this conversation between a customer and an airline support representative:
‘My Frequent Flyer Number is LH1236699999. Can you please link it to my Zurich-Singapore-Zurich itinerary?’
‘Yes, sure. Please give me a few minutes.’
*2 minutes later*
‘Hello! Are you able to link it?’
‘Please bear with me while I locate your booking. Shall I put your call on hold for 2 minutes?’
*Wait-in-line music plays*
*5 minutes, 20 screens, and a dozen of computer programs later*
‘Did you say your number was LH1236699999, Sir?
Customer conversations are often riven with friction because live support agents do not have access to critical information in real-time. Many do not have the right answers owing to a lack of proper training or a lack of an updated knowledge base. Sometimes they resort to outdated information and end up providing incorrect replies.
Often, conversations meander rarely culminating in customer happiness. And this gap in knowledge and disorganization ends up disappointing not only the customer who’s at the receiving end of such interaction but also the agents themselves. Not being able to meet customer expectations erodes their morale and breeds failure in the long haul.
AI chatbots can change all of this. These smart assistants can analyse millions of customer data points in real-time and can help support reps access customer information immediately when required.
They can empower them with intelligent insights into the problems and help them successfully solve complex issues at the first go itself with precision and efficiency. Ensuring the first-contact resolution like that not only makes the customer happy but also motivates the agents to take on greater challenges in the long run.
4. Save customer service hours and increase employee productivity
Towering numbers of routine customer requests and inefficient workflows can often cause employee burnouts. Request overload and stress can diminish their abilities to empathize with the customer. Without the right tools and technology to allay frustration, the reps can find themselves demotivated to carry on or can even end up passing on their stress onto the customer.
AI-powered virtual assistants can single-handedly manage 60–80% of incoming query traffic to keep the support reps free for dedicating themselves to higher value-adding activities. Chatbots are inherently scalable and can emulate human cognition to readily take over the L1 tasks of the customer support staff.
As per research, 64% of agents who use chatbots to answer repetitive FAQs, create tickets and fetch invoices have higher bandwidth for solving challenging problems. And leveraging chatbots will help companies save as much as 2.5 billion customer service hours by the end of 2023.
5. Cut operational costs by up to 30%
Ecommerce statistics show that businesses spend around $1.3 trillion on customer requests every year.
With the assistance of chatbots, this customer service expense could be reduced by 30%. Scaling the customer support team fast enough to keep up with soaring customer demand can be difficult. Recruiting and training agents can be expensive, especially when customer support channels are several and all in need of additional pairs of hands.
On the contrary, a chatbot will be a smarter, one-time investment for development and integration, post which it can help a business scale service and sales interactions indefinitely across multiple touchpoints with a customer.
6. Provide interactive, 24/7 support
AI chatbots can facilitate intelligent two-way conversations between the customer and the brand. The AI, capable of Natural Language Processing and Contextual Understanding, allows users to ask what they will without limiting them to a pre-structured set of questions.
The interactive assistants, available 24/7, can help keep a business connected to its customers and provide consistently high support quality even when an agent might not be available. As such, they amplify the customer’s trust, create loyalty, and increase customer lifetime value.
7. Craft omnichannel experiences
Most businesses lose track of their customer’s journey across the numerous touchpoints that they share with them. As per Microsoft, 66% of consumers have used at least three communication channels to contact customer service. AI-driven chatbots can help keep the support staff up-to-date with the customer’s imprints across channels in real-time to be able to craft genuinely superior omnichannel experiences.
8. Give personalised solutions
AI chatbots are quick to integrate with CRM and extract data concerning the customer lifecycle stage, purchase history, past requests, and more, for support reps to reference in real-time and be able to provide customers with truly personalised and optimal solutions instantly.
But the question that pops up now is, how do chatbots do all of this?
How do the bots work?
Like regular applications, a chatbot has an application layer, a database, APIs, and Conversational User Interface (CUI). This…uh-oh wait.
First — there are two types of chatbots, each with their own set of benefits and limitations: Click-based and AI-based.
The thing about click chatbots is:
- They function on pre-programmed keywords or U/X features or suggested responses to take the conversation forward. They cannot understand language and are incapable of natural, human-like conversation.
- They can only automate particular situations that they have been trained for, such as tracking order status, looking up refund status, or referencing, and presenting something product or services catalog.
- While they can be extremely convenient and time-saving for millions of users, they lack critical understanding and flexibility and are not very useful when unfamiliar situations arise, which they do very often.
On the contrary, AI chatbots are the real thing:
- They understand language. They allow the user to communicate naturally in free form as they would to another human.
- They are unlikely to trap the customer in a useless or even endless conversation loop precisely because they do not employ any keyword-powered buttons to drive the conversation forward. Everything they respond with is based on their understanding of context and user intent.
- They thrive in new scenarios. In fact, that’s where they learn the most. Every conversation with them is unique and helps them hone their own capabilities of providing successful answers in uncustomary situations. Since they are so flexible, adaptive, and perpetually self-improving, they are the best when it comes to resolving an assortment of customer issues from the dreariest to the most unusual.
Since AI chatbots can understand people, how do they process human languages?
They use something called Natural Language Processing (NLP).
Natural Language Processing is the ability of a computer program to convert unstructured human text or speech into structured data, match it with the right response in the knowledge database, and select a fitting reply.
AI chatbots do this all the time. They analyze customer text using NLP and respond appropriately in their language itself. This makes the interaction between the user and the chatbot seem natural and free-flowing, like between two people.
- The process of converting human text into structured data for a machine to understand is called Natural Language Understanding (NLU).
- The process of converting structured data back into the human text for a user to understand is called Natural Language Generation (NLG).
NLP employs both these processes regularly to enable a chatbot to interact with a human successfully.
To understand this better, imagine, a user asks a chatbot, ‘What is my bank account balance?’
In response, a chatbot first breaks down the sentence into Intents and Entities.
An ‘intent’ is something the user wants to be done, like an action they want to be performed or a request they want to be fulfilled or some information they want to be received. The goal, basically.
An ‘entity’ is a detail that describes the intent and defines it more clearly. It makes it easier for the chatbot to identify the goal.
In the above example, the intent would be “balance.” The entity would be “customer’s bank account.”
Having recognised the correct intent and entities, the chatbot provides the customer with their bank account balance.
Now, there are steps to an NLP mechanism. The primary ones being:
1. Tokenization — Splitting a sentence into different parts, words or “tokens”
2. Part of speech tagging — Determining which words are nouns, verbs, and adjectives
3. Stemming — Trimming down a word to its basic form
4. Named entity recognition — Finding out entities in the user’s text
5. Sentiment Analysis — The ability to gauge how a user is feeling at any point in time. Like what’s their mood like? What’s the recognisable emotion? Is the user happy?
This is extremely important to ensure that chatbot-aided interactions are not a failure. Real-time sentiment analysis and conversational analytics help a chatbot redirect the chat to a support agent in case the user does not seem satisfied with the bot’s response.
This significantly reduces the churn rate as it ensures that the customer doesn’t tune out mid-interaction or switch loyalties along the journey.
All this is a good briefing about a chatbot’s backend but…
What does an AI-powered chatbot look like to a customer?
We spoke earlier about CUI, didn’t we? Conversational User Interface. It’s what chatbots have instead of regular UX.
And it is what enables a user to have a text or voice interaction with technology in an understandable human language.
A right CUI makes interaction effortless for the customer and uplifts the brand personality. Courtesy a good Conversational UI, communicating with the business can seem to anyone as natural as talking to a friend.
More on CUI and chatbots in the next post, but analysing your current sentiment, we’re content this will do for now. 😉