USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN CHATBOTS

 A Chatbot is a computer program or an Artificial Intelligence software that can simulate a real human conversation with real-time responses to users based on reinforced learning. 

The successful adoption of chatbots by end users has led to the use of more and more bots in advanced artificial intelligence technologies and their usage by a custom software development company. Even there are reports that 80–85% of businesses will be deploying advanced chatbots by 2020.

AI Chatbots either use text messages, voice commands, or both. AI robots use a natural language to communicate with Artificial Intelligence features embedded in them.

Most of the chatbots are a kind of messaging interface where instead of humans answering to your messages bots are responding. The conversation humans have with bots is powered by ML algorithms which breaks down your messages into human understandable natural languages using NLP techniques and responds to your queries similar to what you can expect from any human on the other side .

MACHINE LEARNING CHATBOTS:

The systems are already becoming complex to handle, and in such a situation, you must make the software work all by itself. Automation is the more apt word for it. Automations are helping us out in giving us solutions even in the rapidly changing times. 

•  Solve complicated queries: chatbots develop their answers or responses to the complicated questions. Why? Because they use natural language processes and machine learning. These chatbots learn better when you train and employ them more. The more you train them, the better they will operate with the users.

• Give relevant answers: API integrations are the backbone of AI chatbots. They continuously feed the chatbots with resources that help them in giving more relevant solutions and queries.

• Learning process: As the name implies, machine learning refers to continually learning from the encountered situations and experiences without any interruption by humans. 

• Technology evolution: You can still experiment by giving instructions to the systems, but till the time, it will take those instructions. Technology will change, which further requires new programming.

• Not based on rules: The system learns according to the experience it encounters rather than the feeding process.

• It employs an algorithm: It depicts the instructions based on which computers function. Whenever a chatbot receives an input, it merely analyzes it, forms the context, and gives you accurate results.

Al CHATBOTS:

 Unlike the rule-based chatbots, which creates its foundation on predefined rules and approaches. These rules are not flexible, and chatbots will only provide solutions to the queries which are fed into it, whereas AI chatbots have more potential in comparison to the rule-based chatbots.

See some of its features :

How do AI and machine learning chatbots work :

As discussed above, AI chatbots understand language and not merely commands. Also, they have the ability to learn more and respond accordingly as they encounter new situations. They receive the data, analyze it and determine the appropriate reactions.

Al chatbots work on the basis of two components: machine learning and natural language processing. So, that means machine learning is not a separate form of a chatbot. But it is itself a part of AI Chatbot.

HOW DOES MACHINE LEARNING CHATBOT WORK?

At a glance, a chatbot can look like a normal app. There’s an application layer, a database, and APIs to call external services. The main thing that’s missing is the UI, which in the case of a bot is replaced by the chat interface. While this setup is convenient for users (that’s why chatbots are on the rise, after all), it does add a layer of complexity for the app to handle. Without the benefit of a rich interface that allows a user to input specific, discrete instructions, it falls on the app to figure out what the user wants and how best to deliver that.

Unlike normal app inputs, human language tends to be messy and imprecise. That’s where the NLP engine comes in. Made up of a number of different libraries, the NLP engine does the work of identifying and extracting entities, which are relevant pieces of information provided by the user, using libraries for common NLP tasks like tokenization and named entity recognition. Tokenization breaks sentences down into discrete words, stripping out punctuation, while named entity recognition looks for words in pre-defined categories (for example, place names or addresses). They might also use a library called a normalizer, which catches common spelling errors, expands contractions and abbreviations, and converts UK English to US English.

What if you’re trying to build a bot that’s a more generalized assistant rather than a text-powered version of a simple web app? For that, your bot is going to need to understand context and intent. To establish context and intent, you’ll need some additional NLP tasks that allow the NLP engine to understand the relationships between words. Part-of-speech tagging takes a sentence and identifies nouns, verbs, adjectives, etc. while dependency parsing identifies phrases, subjects, and objects. 

Understanding context and intent allows bots to understand and act upon a much wider array of actions, or even ask the user additional questions until they understand the request. From there, you can add more complex NLP tasks like sentiment analysis, which can identify when a user is becoming frustrated and perhaps escalate the interaction to a human CS rep.

When it comes to building an NLP engine, there are a lot of options out there, depending on the functionality your bot requires and the language you’re using to build it. Python is often celebrated for its robust machine learning libraries, which include NLTK, SpaCy, and Pattern, all of which provide support for basic NLP tasks, as well as some more advanced application
s like deep learning

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HOW THEY PROCESS HUMAN LANGUAGE?
UNDERSTANDING COMPLEX REQUESTS

1.They find the most efficient solutions: AI chatbots simplify and handle the customer's service quite correctly. They can analyze vast amounts of data, finding and giving you the right answer. 

2. It collects and analyses data quickly :

3.It creates a distinct personality: The traditional chatbots would only give responses to a simple question. Even if a customer has asked a question several times, he would only get the same answer every time. But with the evolved technology, AI chatbots give users a feeling as if they are talking to humans. If a customer is asking a query several times, it will respond differently to provide users the ultimate satisfaction until they find the perfect answer.

Let's take an example - Devices such as Alexa and google home are already using machine learning. They gather millions and trillions of data and give output with the assumptions of an accurate answer. Such intent-based algorithms and AI tools are already building after every six months. Currently, machine learning is focusing on gathering insights from the data.

WHY DOES ORGANIZATION NEED CHATBOTS

1. Scaling Operations

Chatbots are great for scaling operations because they don’t have human limitations. The world may be divided by time zones, but chatbots can engage customers anywhere, anytime. In terms of performance, given enough computing power, chatbots can serve a large customer base at the same time.

2. Task automation

Chatbots are very effective at automating specific tasks. Once they’re programmed to do a specific task, they do it with ease. For example, some customer questions are asked repeatedly, and have the same, specific answers. In this case, using a chatbot to automate answering those specific questions would be simple and helpful.

3. User Engagement

Getting users to a website or an app isn’t the main challenge – it’s keeping them engaged on the website or app. Chatbot greetings can prevent users from leaving your site by engaging them. Short chat invitations let you proactively engage with users.

4. Social Media Integrations

Chatbots can be integrated with social media platforms like Facebook, Telegram, WeChat – anywhere you communicate. They can also be integrated with websites and mobile applications. Integrating a chatbot helps users get quick replies to their questions, and 24/7 hour assistance, which might result in higher sales.

5. Data generation

When interacting with users, chatbots can store data, which can be analyzed and used to improve customer experience.

6. Ability to speak multiple languages

Apart from being able to hold meaningful conversations, chatbots can understand user queries in other languages, not just English. With advancements in Natural Language Processing (NLP) and Neural Machine Translation (NMT), chatbots can give instant replies in the user’s language.

7. Connect with younger customers

Statistics show that millennials prefer to contact brands via social media and live chat, rather than by phone. They’re tech-savvy, and they have big buying power. It’s good to satisfy their needs, and have a solid chatbot.

INDUSTRIES WHERE CHATBOTS CAN HELP

1. Customer Service

If your company needs to scale globally, you need to be able to respond to customers round the clock, in different languages. Chatbots do that efficiently. 

2. Ecommerce

As the number of online stores grows daily, ecommerce brands are faced with the challenge of building a large customer base, gaining customer trust, and retaining them. To successfully achieve these tasks, brands need round-the-clock customer assistance, assist with online purchases, manage payments and also update customers with the latest discounts, create trust and create social engagement. 

It can be burdensome for humans to do all that, but since chatbots lack human fatigue, they can do that and more. 

3. Healthcare

Research has shown that medical practitioners spend one-sixth of their work time on administrative tasks. Chatbots in healthcare is a clear game-changer for healthcare professionals. It reduces workloads by gradually reducing hospital visits, unnecessary medications, and consultation times, especially now that the healthcare industry is really stressed.

For patients, it has reduced commute times to the doctor’s office, provided easy access to the doctor at the push of a button, and more. Also, chatbots contribute to cost savings in healthcare delivery. Experts estimate that cost savings from healthcare chatbots will reach $3.6 billion globally by 2022. 

4. Travel and Tourism

With chatbots, travel agencies can help customers book flights, pay for those flights, and recommend fun locations for vacations and tourism – saving the time of human consultants for more important issues.

5. Banking and Finance 

Banking and finance continue to evolve with technological trends, and chatbots in the industry are inevitable. With chatbots, companies can make data-driven decisions – boost sales and marketing, identify trends, and organize product launches based on data from bots. 

Some banks provide chatbots to assist customers to make transactions, file complaints, and answer questions. Compliance and security are major obstructions to the adoption of new tech in the financial space, but with chatbots, you can build security protocols like two-factor-authentication, token integration, firewalls, 24/7 monitoring, encrypted backends to protect user data, and more.

6. Food Services and Grocery Stores

Waiters sometimes mistake food orders. But most food brands and grocery stores serve their customers online, especially during this post-covid period, so it’s almost impossible to rely on the human agency to serve these customers. Using chatbots here has become necessary. They’re efficient at collecting customer orders correctly and delivering them. Also, by analyzing customer queries, food brands can better under their market. Since chatbots work 24/7, they’re constantly available and respond to customers quickly.

ADVANTAGES OF AI AND MACHINE LEARNING CHATBOTS :

The most prominent benefit of AI chatbots is they are continuously resolving customer complaints and services. They never go out of their duty. Now let's see some other benefits as well :

•  You can quickly achieve any desired goals with it. They are the perfect problem resolvers for customers. It helps you to turn a lead into conversions by automating the required processes. 
• AI can quickly identify the demographic factors of the visitors in a conversation. It can identify a customer's past histories as well, enabling you to reach your desired goal. i.e. conversion goals. The more it encounters a situation or interaction, the better it learns, and the better it opens the pathways to achieve goals.

•  Al chatbot can quickly gather and analyse data while its constant interaction with the customers or leads. Chatbots immediately recollect the past conversation when an old customer revisits the website. AI chatbots can quickly grasp all the likes, interests of such customers and engage them easily till they reach the final destination, i.e. conversion goals.

• Provide 24/7 service

• Decrease response time

• Allow the client self-care

• Increase your team’s productivity

• Increase the level of user satisfaction

• Provide a personalized service

• Expand your customer base

• Increase lead generation

• Reduces cost

AI and customer service continually improve with updated data and machine learning.You can use the collected data in building a good customer base and creating strategies using marketing automation software.

FUTURE OF CHATBOTS

Searching for the marketing trends related to the future is easy if you have all the correct data and when it is in front of you. But these trends are a bit obvious and widespread compared to the complex numbers of the demand and supply fluctuations. With chatbots, we know where things are heading to the future. The job for businesses and brands after a certain point is to take the next leap and move forward. For AI and chatbot, the future is coming one way or another, and that can’t be avoided.