5 Ways to Use Chatbots for Your Business
This in-depth and interesting article looks at 5 ways to use chatbots for your business and explores the misconceptions of them as well as how they work.
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In popular science fiction, a bot would be something that Tony Stark has from the “Ironman” Franchise: J.A.R.V.I.S.
Or at least that is what we expect our smart bots to be.
An AI bot that not only answers your questions but is capable of intelligent decision-making based on what might be best for you, or in J.A.R.V.I.S.’s case, whatever is good for Tony!
But is that what we have today? Are we anywhere close to what J.A.R.V.I.S. can do? I try to answer these questions and try to define chatbots in their current form. Most importantly, how chatbots can be used to drive revenue. For us to understand what a chatbot is or isn’t, we need to first learn how to define it. A little googling would give you the following definition,
“A chatbot is a computer program or a list of instructions that simulates a human conversation via texts or voice”
Though this definition is the right one, in popular culture, the following is what is prevalent (from Wikipedia).
A chatbot (also known as a talkbot, chatterbot, b ot, IM bot, interactive agent, or Artificial Conversational Entity) is a computer program or an artificial intelligence, which conducts a conversation via auditory or textual methods.
Did you notice “artificial intelligence?” Don’t worry, you are not the only one! Most people seem to be obsessed with the word. Considering how cool J.A.R.V.I.S. is, it’s no surprise either, but chatbots, as they stand now, are not artificially intelligent or capable of it, yet!
Before we can go further debunking that myth, we need to understand:
- How chatbot’s work
- Where chatbots come from — history
How Do Chatbot’s Work?
Chatbots, at least all the usable versions, use something the community calls NLP, which is short for Natural Language Processing. This is not to be confused with Neuro-linguistic programming NAL (Natural Language Processing), which deals with the analysis and processing of natural language.
A chatbot whose main objective is to simulate a conversation like its human creators would need to process and understand the common language.
Common language is the mode of communication/language that was developed and used by the populace to talk to each other or get their ideas around.
Some really advanced chatbots have been known to use NLP to process and simulate conversations. Though the fact of the matter is, NLP itself is not yet fully developed, i.e. chatbots to some extent answer a specific set of queries and build a conversation, but they are yet truly intelligent nor can they understand language.
NLP is hard and the progress is slow. It would take sometime before NLP would truly understand natural language (whatever we say). Consequentially, chatbots haven’t reached a state where they can understand human conversation and respond appropriately. Most chatbots can only answer predefined questions and some may even learn from these interactions.
Though the process itself, irrespective of NLP or not remains the same. and goes something like this,
- Record a statement
- Find keywords
- Find answers (from a predefined set)by matching keywords
- Respond with the matched predefined answers.
This what I call a simple linear bot with decision-making confined to predefined keywords and answers.
What Does This Mean? — The Misconceptions
This means chatbots are not as smart as you thought. Chatbots are not J.A.R.V.I.S. yet. By their definition, they are meant to converse with a human as another human would. Current technology is not capable of such a feat. Though that is the end goal.
Another misconception is the fact that a chatbot is something that chats with you over a chat window. On the contrary, chatbots are anything that simulates a conversation with a human. Google home and Amazon Alexa are both chatbots using voice.
From all that we know now, let’s redefine a chatbot:
A chatbot is a program that follows a set of rules and sometimes AI to interact with users like any other human would
Though we inherently assume that chatbots would have AI, it is not always true, and this takes us to the part where we try to differentiate between various types of chatbots.
Types of Chatbots
Chatbots from how they operate can be differentiated into 2 types:
- Linear or sequential
- Machine Learning and AI-driven
If matched, the answer(s) are sent back as a response.
AI-Driven/Machine Learning Chatbot
One of the defining features of these is that they use NLP. Like the linear chatbot above, ML chatbots needs a set of predefined questions and answers along with keywords (also called intent). This initial data is called a learning set, which the chatbot uses to answer user’s initial questions and learns from the answers and responses to eventually be smart enough to answer queries accurately.
How Can You Use a Chatbot for Business?
Though chatbots are the future, they might never be able to replace human intelligence. Not unless true AI’s come into the picture. Having said that, chatbots, like the machines of the industrial revolution, can take over anything that’s repetitive and doesn’t require emotional intelligence and decision-making capabilities.
Some of the areas include:
1. Increasing Productivity of Support Teams
If you ever have been a part of a support team, you should have noticed that more than 30% of your queries are about things already present on the website either on the FAQ page or in support documents. Most of these queries rarely require any action and are limited to sharing predefined answers and links. Chatbots can help the customer by connecting their queries to FAQ’s and support docs and sharing an answer from this predefined set.
Additionally, chatbots can offer to connect the customer with a support agent in case the query couldn’t be found in the predefined set.
This type of bot is what we call an FAQ Bot.
2. Generating Qualified Leads
One of the banes of being in marketing is that your website’s visitor to qualified lead conversion is a number so small that even Yoda would have been surprised!
Chatbots have been extensively used to tackle this problem. Companies like Drift, Kommunicate, and Botsify, among others, have built businesses around this.
How would you use this?
Let’s look at an example.
If Shobha developers (a real estate and construction firm) ever tried to put in a bot on their website (And they will! Eventually...), they would replace the live support button with a chat box with a bot in its place. Something like the one below:
The bot would then ask questions depending on where the visitor is on the website. For example, if the visitor is on the pricing page, the bot can offer to explain the pricing plan itself.
Chatbots have been known to add up to 30% more qualified leads to the top of the funnel. Some of them can even be used to complete an entire sales cycle. A very good example is the ticket booking bot.
One of the interesting aspects of a bot is its ability to trigger and change in real time based on the current situation of the visitor or the customer.
This is very similar to event-based email marketing that is being extensively used by most digital marketers including yours truly (bows!).
The chatbot can include the events that the customer goes through and change the way it interacts with the said customer. The major difference from email-based followup is that chatbot is realtime and the entire interaction takes place while the customer is on your website.
This tactic especially works when the customer is at the decision-making stage and needs just a nudge to talk to the sales team or set up a demo.
Combine this with a popular social media platform like Facebook and you are looking at 80% open rates with up to 40% clickthroughs.
Here is a message that I received from Josh Fechter of BAMF media via Facebook messenger:
He even sends his newsletter via Facebook because a chat-based conversation just works so well.
Most companies that I know of use one or another team collaboration and chat tool, some of the most popular ones include Slack and Facebook Workplace among others. A chatbot can be integrated into these tools to automate a bunch of time-consuming though important processes.
I have listed some of these below:
- Automated Team updates and status: A chatbot integrated into Slack or Facebook messenger can be used to gather daily updates from the team, compile a report, and send it to the team lead or manager.
- Internal Notifications: Sales teams keep missing scheduled demos? Use a chatbot to create notifications to be sent to the entire team 15 minutes before the call begins.
- Internal FAQ: Human Resource, finance, tech, etc. follow a certain set of rules and regulations, and in some industries, like healthcare and finance, there are government regulations that need to be followed. Chatbots can help internal teams find the right regulation based on the intent of the question. This not only simplifies the search itself but also makes sure that the team follows the given regulations. And like support team’s case, internal teams won’t have to spend time answering routine questions.
5. Upselling and Abandoned Cart
An abandoned cart is a scenario where a customer adds a product into the cart or clicks on the payment button but doesn’t go through with the purchase.
A chatbot in case of an abandoned cart identifies if the user is back on the site and proposes to complete the transaction for him. Things like an increase in prices and related events can be used via a chatbot to compel the user to complete the transaction.
Though similar things have been tried via emails and notification with significant results, a chatbot-based approach has shown to give 40% better results than any email or notification.
How to Build a Chatbot? — The Platforms to Use
There are more than enough tools and products on the internet that can help you build a decent Sequential Chatbot (see the types of chatbot section above), which is sufficient for most tasks, though if you are looking at making an actual dent in the productivity of your team, you would have to add some kind of Machine Learning, which is also called an intent-driven chatbot, into the mix.
Though not AI, it learns and responds from the customer responses and manual updates. My suggestion is to use Dialogflow. Though the self-learning part of it might be hard to implement, you can add intent to it by yourself. It is then used by the bot to answer queries.
It is easy enough for a non-developer to implement.
You can use any one of the following bot making platforms:
- ChatFuel— Build an AI chatbot on Facebook for free.
- ANACHAT — Open Source chatbot framework for all platforms with drag and drop UI and can be used for agent chat too.
- Pandorabots — An end-to-end chatbot platform. I like it for the fact that I don’t have to look for a separate server or other resources. Free for the most part.
- BotKit — Open Source chatbot framework for all platforms.
- Botsify— One chatbot free indefinitely.
- Drift — Basic Live chat is free. If you can spare the manpower, nothing is better than this in my opinion.
If you are looking at making some advanced bots, check out:
In most of the cases above, you will need a platform to publish the chatbot on to your website or App. You can always build your own publishing unit, but a better way would be to build the bot in any of the above chatbot platforms and integrate it with something like Kommunicate.
Chatbots are the next step in the evolution of customer communication and most of us have just begun to understand their importance or how to make use of them. We also need to understand that the chatbots we have now will need human intervention in most complex cases. Though a true AI chatbot is still in the works, we can still use the ones we have (sequential and intent-based chatbots). Having said that, investment in chatbots will add value in the long run both for you and your business.
Published at DZone with permission of Vigil Viswanathan. See the original article here.
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