What are chatbots?
Why are they such a big possibility? How do they operate? How can I create one? How can I meet other people engrossed in chatbots?
These are the issues we’re going to answer for you right now.
Ready? Let’s do this.
What Is A Chatbot?
A chatbot is an assistance, powered by dominions and seldom artificial aptitude, that you communicate with via a chat interface. The service could be any quantity of things, reaching from functional to fun, and it could live in any significant chat product (Facebook Messenger, Slack, Telegram, Text Messages, etc.).
We may also define them as, Chatbots are software applications that use artificial intelligence & natural language processing to understand what a human wants, and guides them to their desired outcome with as little work for the end user as possible. Like a virtual assistant for your customer experience touchpoints.
A well planned & built chatbot will:
- Use existing communication data (if available) to surmise the type of questions people ask.
- Investigate correct answers to those questions through a ‘training’ period.
- Use machine knowledge & NLP to learn context, and constantly get better at answering those questions in the future.
The confirmation of chatbots was accelerated in 2016 when Facebook opened up its developer platform and showed the world what is reasonable with chatbots through their Messenger app. Google also got in the game soon after with Google Assistant. Since then there have been a tremendous amount of chatbot apps built on websites, in applications, on social media, for customer support, and countless other examples.
If you wanted to buy shoes from Nordstrom online, you would go to their website, look around until you find the shoes you wanted, and then you would purchase them.
How Do Chatbots Operate?
One of the most interesting parts of the chatbot space is the variety of ways you can build a chatbot. The underlying technology can vary quite a bit, but it really all comes down to what your goals are. At the highest level, there are three types of chatbots most consumers see today:
a. Regulation-Based Chatbots – These chatbots follow pre-designed rules, often built using a graphical user interface where a bot builder will design paths using a decision tree.
. AI Chatbots – AI chatbots will automatically learn after an initial training period by a bot developer.
What Are The Advantages of Chatbots?
Today’s purchasing & sales teams are under a lot of pressure to not only show results but to continually be enhancing the client experience. It’s a big task. Not to mention the ever-increasing expectations of todays consumers (aka, the Amazon effect).
Today, we expect answers immediately and we expect that they will be accurate. This can be done with human beings up to a certain tipping point, then technology has to be the answer. This is why forward-thinking brands have adopted chatbots to help them:
- Increase their website translation rate – Marketers put a lot of work in to drive traffic to their website, to only have that traffic convert anywhere between 0.25%-1.0%.
- Generate more suited leads – It would be nice if we could talk to every lead and ensure they’re a good fit before we schedule a meeting. In reality, that’s impossible for most organizations to do at scale. Bots can help use advanced qualification logic to do lead qualification and improve sales acceleration.
- Combat Client Churn – Bot are a perfect answer to high-volume support inquries, especially where customers become frustrated with standard knowledge bases that are hard to sift through.
How to Create A Chatbot
Getting started with chatbots can feel a bit threatening at first. The strategy, the tools, the technology, the method, the recording – the list goes on.
There are two different tasks at the core of a chatbot:
1) User request analysis
2) Returning the response
As you can see in this graphic, a chatbot returns a response based on input from a user. This process may look simple; in practice, things are quite complex.
1) User request analysis: this is the first task that a chatbot performs. It analyzes the user’s request to identify the user intent and to extract relevant entities.
Example of user request analysis.
The ability to identify the user’s intent and extract data and relevant entities contained in the user’s request is the first condition and the most relevant step at the core of a chatbot: If you are not able to correctly understand the user’s request, you won’t be able to provide the correct answer.
2) Returning the response: once the user’s intent has been identified, the chatbot must provide the most appropriate response for the user’s request. The answer may be:
• a generic and predefined text
• a text retrieved from a knowledge base that contains different answers
• a contextualized piece of information based on data the user has provided
• data stored in enterprise systems
• the result of an action that the chatbot performed by interacting with one or more backend application
• a disambiguating question that helps the chatbot to correctly understand the user’s request
The Value Chatbots Bring to Businesses and Customers
Chatbots boost operational efficiency and bring cost savings to businesses while offering convenience and added services for customers. They allow companies to easily resolve many types of customer queries and issues while reducing the need for human interaction.
With chatbots, a business can scale, personalize, and be proactive all at the same time—which is an important differentiator. For example, when relying solely on human power, a business can serve a limited number of people at one time. To be cost-effective, human-powered businesses are forced to focus on standardized models and are limited in their proactive and personalized outreach capabilities.
By contrast, chatbots allow businesses to engage with an unlimited number of customers in a personal way and can be scaled up or down according to demand and business needs. By using chatbots, a business can provide humanlike, personalized, proactive service to millions of people at the same time.
Consumer research is showing that messaging apps are increasingly becoming the preferred method for connecting with businesses for certain types of transactions. Delivered through messaging platforms, chatbots enable a level of service and convenience that in many cases exceeds what humans can provide. For example, banking chatbots save an average of four minutes per inquiry compared to traditional call centers. The same capabilities that help businesses achieve greater efficiency and cost reductions also deliver benefits to customers in the form of an improved customer experience. It’s a win/win proposition
How Chatbots Have Evolved
The origin of the chatbot arguably lies with Alan Turing’s 1950s vision of intelligent machines. Artificial intelligence, the foundation for chatbots, has progressed since that time to include superintelligent supercomputers such as IBM Watson.
The original chatbot was the phone tree, which led phone-in customers on an often cumbersome and frustrating path of selecting one option after another to wind their way through an automated customer service model. Enhancements in technology and the growing sophistication of AI, ML, and NLP evolved this model into pop-up, live, onscreen chats. And the evolutionary journey has continued.
With today’s digital assistants, businesses can scale AI to provide much more convenient and effective interactions between companies and customers—directly from customers’ digital devices.
Are Chatbots Bad?
There are some misconceptions about the term chatbot. Although the terms chatbot and bot are sometimes used interchangeably, a bot is simply an automated program that can be used either for legitimate or malicious purposes. The negative connotation around the word bot is attributable to a history of hackers using automated programs to infiltrate, usurp, and generally cause havoc in the digital ecosystem.
Bots and chatbots, therefore, should not be confused. Generally speaking, chatbots do not have a history of being used for hacking purposes. Chatbots are conversational tools that perform routine tasks efficiently. People like them because they help them get through those tasks quickly so they can focus their attention on high-level, strategic, and engaging activities that require human capabilities that cannot be replicated by machines.