- Why Should You Read This?
- What is a Deep Learning Chatbot?
- Pros and Cons of an AI Chatbot
- Is It Difficult to Develop a Chatbot Based on AI Technology?
- How Will You and Your Customer Base Benefit from an AI-Based Chatbot?
- Over to You
Chatbots are a whole new universe with their own trends, vocabulary, and rules. Although it is a pretty complicated and complex technology, chatbots are changing the way brands interact with customers, the way customers make their purchases, the way customer service functions, and many other things about e-commerce.
If you searched for this type of article, you probably already got the idea that chatbots are a cool instrument for businesses and that you probably want one as well to attract more customers, speed up customer support, simplify and automate certain processes.
Time to create your first chatbot?.. Well, not so fast. Let's approach this matter gradually and strategically.
First, we suggest learning about how chatbots work, what they are capable of, and where their limits are. A good next step could be to analyze which of your company's problems a chatbot will be able to solve. Then comes the choice of the platform, the design and launch of a new chatbot, and, of course, reaping the benefits.
This article is going to focus on the very first step of this journey. Read this post to learn about popular chatbot software apps and how to choose the one that's right for you.
The chatbot is a computer program designed to have a conversation with a human. Chatbots can be based on different technologies, meaning that they will have different features and capacities. Generally, two types of chatbots are distinguished:
- A rule-based chatbot (can sometimes be called keyword-based, linguistic chatbot, decision-tree chatbot)
- An AI chatbot (aka intelligent chatbot, machine learning chatbot)
Both of them are exciting and useful for certain purposes. Here we are going to focus on AI chatbots, but in case you are interested in the first group as well, check our earlier post.
The use cases of chatbots are not limited to customer service or Facebook chats. It even goes way beyond e-commerce and marketing to many other spheres of human activity. Let's take a look at various examples of how a chatbot can create value and assist people in different things.
NatGeo Genius: a Voice from the Past
In the attempt to promote its new TV show Genius where they talk about the lives of well-known figures like Albert Einstein and Pablo Picasso, National Geographic presented a Facebook bot. The purpose of this bot was to have conversations with users as if they talked to the real Albert Einstein.
The chatbot make sarcastic jokes, talked about matters that Albert Einstein studied, and told stories about his life answering professional and personal questions.
The result? This chatbot generated unbelievable engagement rates. Figures show that the average conversation lasted for 6-8 minutes with 11 turns per conversation. 50% engaged with the chatbot more than once. This is a great chatbot experience from both educational and marketing perspectives.
OneRemission: Chatbots Against Cancer
The first healthcare chatbot was introduced as far back as 1966. Its name was ELIZA and its primary goal was to use pattern matching and response selection to imitate the work of a psychotherapist. However, the knowledge and communication skills of ELIZA were rather limited. Today, healthcare machine learning bots are widespread and their market is growing: according to the statistics, this market is expected to grow to 563 Million USD by 2026 from 148 Million USD in 2019.
Chatbots help patients and doctors solve a wide range of issues: from maintaining mental health to making appointments and interpreting medical test results.
OneRemission developed quite an unusual chatbot: it helps make the lives of cancer survivors easier. This bot is designed to provide more information about cancer and post-cancer healthcare. One Remission is trying to empower cancer patients and survivors by providing comprehensive diets, physical exercises, and other post-cancer practices curated by Integrative Medicine experts so that these people are able to live a more independent life with less reliance on a doctor. OneRemission also offers a possibility for around-the-clock consultation with an online oncologist.
Have you ever thought of such an application of a chatbot?
A Chatbot for Learning: Duolingo
When you learn a foreign language, sometimes words just don't come to your mind at the right moment. Duolingo introduced a chatbot powered by AI. The chatbot is trying to tackle this problem!
This chatbot imitates the conversation with a real native speaker of the language you are learning. Not only is this chatbot interactive and enjoyable, but it also helps people deal with the anxiety and embarrassment related to language learning.
This is a great example of how chatbots help people in their day-to-day struggles.
Let us take a deeper dive into the ins and outs of an AI chatbot.
AI, Machine Learning, Natural Language Processing, and Other Concepts you Need to Know When Dealing with Chatbots
Why is Artificial Intelligence (AI) chatbot called this way?
Such chatbots are based on Artificial Intelligence, which is a branch of computer science that aims to create technologies and software imitating the human brain. AI is an umbrella term that has a lot of sub-divisions some of which are used in machine learning chatbots:
- Natural Language Processing (NLP)
- Machine Learning (ML)
- Deep Learning
- Neural Networks
...and even more. Chatbots are made possible thanks to the first three technologies. So, let's zoom into them.
Natural Language Processing (NLP)
What is NLP?
NLP is a branch of AI that is concerned with creating computers that are able to understand the text in a way that is very similar to how we, humans, do it.
Where is it used?
Speech and text recognition technologies are not solely parts of a chatbot. They are virtually everywhere you go:
Unexpectedly, spam detection platforms use Natural Language Processing technologies to scan the language of emails for the signs of phishing or spam: overuse of financial terms, poor grammar, etc.
You probably supposed that Google Translate isn't just replacing words of one language with the words of another. Good translations mean capturing the meaning, tone, message behind one's word. That's where the NLP comes into play. The process of translating is in many ways similar to the work of AI chatbots. And, both AI chatbots and machine translation platforms are making progress on that.
Social media Analytics
NLP has recently become an important tool for uncovering hidden data insights from social media. By having these technologies analyze the language used in reviews, comments, posts, and responses, companies can discover what kind of image they create.
How does the software recognize and produce the text?
Human language is extremely ambiguous and very complicated. In fact, scientists don't know much about how the language is produced or why we are able to produce it. On the contrary, computers are very logical, structured, and consistent. So, teaching AI chatbots to understand people and make conversations with them is a complex task with several steps made possible by a certain technology or tool.
Homonyms, homophones, idioms, sarcasm and jokes, metaphors, made-up words, typos, variations in sentence structure – a chatbot has to learn to understand all of these. Let's take a look at the example of how a message chatbot would do this.
Understanding the Written Text
- First, understanding parts of speech. To make sense of what you have typed, a chatbot breaks the sentence into chunks and associates each chunk with a part of speech. Now the sentence is just a sequence of tags. For example, a chatbot will tag "make" as a verb in "How to make cookies?" and as a noun in "What make of car do you have?".
- Second, meaning. A chatbot analyses the possible meanings of each word and chooses the one that is more likely to fit a given context. For example, this process of disambiguation would distinguish "make" in "make progress" (to progress) and in "make a bet" (to place).
- Also, chatbots are capable of recognizing proper nouns. A tool called Named entity recognition can tell that Florida is a state and Ben is a male name.
Interesting fact: To identify if a name belongs to a male or a female as well as to say if, for instance, "a doctor" is she or he, a chatbot crawls the data available on the net or the data of a certain database. So, if the data has more instances of a doctor being a male, a chatbot will pick it up. Even if in the given text, it's a female doctor.
- Then, the most advanced chatbots are able to identify sentiments by analyzing the choice of vocabulary.
- Last, a chatbot makes the text into a code understandable for a computer.
Composing the Best Reply
To make it a "live chat", a chatbot should also be able to produce text. People make conversations with a chatbot for a purpose. To put on music, to call an electrical service company, or to order a pizza.
As a rule, chatbots have a library of intents. Once a chatbot knows what all the worlds mean, it makes sense of the whole phrase by matching it to an intent.
Of course, the capacity of a chatbot is limited. That's why when you ask, let's say, Siri, about something that she isn't designed to recognize, she gets confused.
Producing the Text
This part, though seeming the most mesmerizing, is relatively simple. An AI chatbot uses templates, that's how it provides a suitable answer. If an answer consists of a word that doesn't fit any template, say, a proper noun, a chatbot generates it letter by letter.
This is quite a simple model. Over time, with Machine Learning, chatbots have become even smarter.
Machine Learning (ML)
What is ML?
Machine Learning is a sub-field of AI that gives computers the ability to learn without being explicitly programmed. A machine programs itself through experience and training with the extensive use of data.
What does it have to do with chatbots? Well, a chatbot infused with machine learning is able to:
1) improve its performance over time, as you feed a chatbot with more data
2) see and explain certain trends in interactions between your chatbot and customers. For example, what do customers ask for more often? What queries is the chatbot not able to answer?
Where is it used?
For many large companies, Machine Learning is at the heart of their business models, for example, Netflix, Google search, YouTube, and Facebook. Machine Learning lies behind these companies' recommendation algorithms. They gather data about what we watch, like, share, and where we spend more time, then they show or recommend what we like.
As for chatbots, this technology helps to improve their performance in so many ways. The most obvious and prominent one is customer support chatbots. Such chatbots can learn from the data of past conversations to interact with customers like real human beings.
What is Deep Learning?
Over time, Machine Learning developed into a more advanced technology – Deep Leaning. In many ways, it works in a similar way to Machine Learning. Machine Learning makes informed decisions based on data and algorithms, but if it makes a mistake, it's a programmer's job is to change the algorithm or use different data. Deep Learning is also able to assess if the decision is right or wrong, which means these programs need almost no assistance.
Where is it used?
Deep Learning is not so widespread as Machine Learning, and the technology is still getting polished. Nevertheless, these are quite some use cases:
- Self-driving cars. Thanks to Deep Learning, these cars are able to detect objects on the road and "see" pedestrians.
- A deep learning chatbot. These chatbots basically do the same as all the other chatbots, but they are capable of interactions of much better quality and need less human supervision. One of such chatbots was developed at Zendesk.
- Electronics. Many home assistance devices can respond to your voice or learn your preferences because they are powered by Deep Learning.
This scheme will help you clearly see how all these AI concepts are related.
As stated in the research done by Invesp, 67% of global consumers interacted with a chatbot over the last year. This and many other statistics indicate a rapid growth of the chatbot industry. Your business might also try to implement a chatbot to engage more customers, automate processes or any other reason. In order to perform well in any task, you need to know well what you are dealing with. By learning about AI, you:
- will understand the limitation of chatbots
- will get the idea of what problems might be solved with chatbots
- will know the strong points of chatbots
- will better navigate in the market of chatbot platforms
- in case you decide to hire a developer, it will be simpler to explain to him the kind of chatbot you want.
- will be up-to-date with the latest technologies.
AI chatbots have their advantages just like they have shortcomings and limitations. So far in this blog, we've talked about how great AI chatbots are, but we highly recommend assessing your company's needs and thinking thoroughly about what problems you are planning to solve with the chatbot before you get a chatbot. To make it a bit simpler, we laid out the advantages and disadvantages of chatbots powered by AI.
Automation. This is one of the coolest chatbot features. A chatbot allows automating certain repetitive actions: sending a newsletter, offering certain sales discounts to groups of customers, etc.
Also, since chatbots can be programmed to complete simple automated tasks, your team can pay more attention to complex and creative tasks!
Limited capacity. Although chatbots are quite efficient in communication, it is not possible to replace human-to-human conversations. For instance, only the most advanced state-of-art chatbots are able to understand emotions and no chatbot is so far able to grasp implicit ideas or ambiguous hints. As a result, chatbots might cause customer frustration and a bad brand experience.
However, it doesn't mean that it will. When you design your chatbot in alignment with the issues you are trying to solve, when you take into account its limitations and focus on its strengths, there will be minimum frustration.
|Multipurpose. It is possible to create a chatbot to serve a number of different purposes: email collection, customer support, placing orders, etc.||
Expensive price tag. While this is not true for all the bot software, a well-designed, tailor-made chatbot will cost you immoderate sums of money. There are options that are rather available, but these types of software, like for example, ManyChat, Facebook Messenger bot, come with limitations.
|Fast customer service. A chatbot offers an immediate response to customer queries. This leads to a better customer experience and more engagement with your brand.||Data Security. When you collect data from your customers, it's up to you to keep this data safe. Do your best to ensure the security of data transfers from chatbots to a CRM. Otherwise, you will lose the trust of your customers and even have legal problems.|
Data collection. Chatbots can be programmed to collect all kinds of data about your customers: name, email, preferences, opinions, and much more.
This data is a great way to learn what your customers prefer, or what can be improved about your business.
|Availability around the clock. A chatbot doesn't have coffee breaks, is never tired or sick. This significantly increases the brand experience.|
The answer to this question depends on how you are planning to build a chatbot, how many features you need, and whether you want to have AI in place.
There are two major paths you can take to build a chatbot:
- Buy access to a chatbot building platform
- Build your own custom chatbot from the ground up
Let's take a quick look at both of these ways. To read more about a step-by-step process of using a chatbot building platform, read our earlier post Step-by-Step Process to Build a Web App with or without Coding Skills.
Coding Your Own Custom Chatbot
What will you need?
Let's say you already have some coding skills. Of course, the more, the better. Then, here is your approximate game-plan:
- Pick a coding language, for example, Python.
- Get some code samples from GitHub (an open-source platform to share codes).
- Make training samples for necessary intents.
- Write your code.
- Take time to test and improve a chatbot
What if you don't have the necessary skills? Hire someone who does! A skilled experienced developed might require a lot of financial resources, but you will get a highly customized chatbot with almost any function that you want this chatbot to have.
The greatest advantage of these chatbots is that you are not limited by the capacity and features of a chatbot-building platform. While you are unlikely to outdo giants like Facebook or Amazon, you are more likely to get a more authentic, smarter AI chatbot.
How long does it take?
Creating an intelligent chatbot infused with AI (Machine Learning and Natural Language Processing) takes on average 120-192 hours, according to Chatbot Magazine. Remember about thorough testing and bug fixing before your chatbot gets released.
Using a Chatbot Building Platform
What will you need?
There are hundreds of chatbot platforms out there, and your task is to find the best one for your needs. They are similar in many ways, but at the same time, they offer unique details. The good news is that almost any chatbot platform offers a free trial that you can take advantage of before making a final decision.
To learn more about the most popular chatbot platforms and what to look at when browsing through chatbots, check out our earlier post Top Chatbot Apps for All Tastes.
There are lots of advantages to a chatbot building platform for a small business:
- Such a chatbot is a cost-effective solution.
- These chatbots require no coding skills. Instead, they have a drag-and-drop interface.
- You can create as many chatbots as you need for different purposes.
- These chatbot platforms usually offer tools to analyze the data collected.
- These chatbots require little manpower. There is no need for a large team of developers since a chatbot can be built by just a couple of people.
How long does it take?
A ready-made chatbot solution is the least time-consuming option. You may even choose a chatbot from a template and deploy it immediately.
So, answering the question about the difficulty, we can say that it varies a great deal. But whichever pathway you choose, you will need to learn about how chatbots work. We hope that you will get a good grip on chatbots and AI after reading this article.
Whether you code your chatbot from scratch or use a chatbot building app, there will be multiple benefits for your business and for your customers:
Chatbots are available 24/7.
As it was mentioned before, chatbots know no breaks, no sick leaves, no holidays. This is a great way to improve the quality of customer support and a great way to expand the business internationally.
Waiting for days for a customer support email is the worst customer experience. A chatbot helps you to turn it into the best customer experience by offering instant answers to customer queries.
Consistent quality of answers.
Though sometimes chatbots sound too mechanical, they will never be rude or disrespectful to your customers. Chatbots are designed to maintain a highly polite, respectful, and customer-oriented approach in a conversation.
Many chatbot building software companies, including TruVISIBILITY, offer to deploy chatbots on multiple platforms: Instagram, Facebook, Twitter, Telegram, your website, etc. This gives customers a chance to communicate with the brand using the platform they prefer.
Chatbots ensure personalization.
A Chatbot powered with AI provides an opportunity to send personalized promotions to your customers and gather information about their preferences. More advanced chatbots are able to successfully engage in one-on-one conversations by maintaining a natural tone.
Chatbots give your team more creative freedom.
Chatbots are great at automation. They can take care of all the repetitive tasks leaving all the cool and creative work to your team. There is a widespread stereotype that chatbots are replacing humans. But in fact, they are dealing with dumb and boring tasks so that we can devote more time to what really matters: delivering value to customers.
As said before, all chatbot web applications come with analyzing and monitoring tools. With these tools, you will be able to see how well your chatbot is performing and identify the areas of improvement. You can get even more inside data: what your customers prefer, what difficulties they face, what language they use to interact with your chatbot.
Here is an example of the TruVISIBILITY Chat Dashboard.
Chatbots open the door to conversational marketing.
Conversational marketing is a way to do marketing by talking with customers via chatbots, voice assistants, and other forms of conversational AI. It is a great trend because conversational marketing isn't focused on hard selling and bombarding customers with ads, but rather on getting to know the customer and establishing a deep connection between the customer and the brand. Getting a chatbot is a great first step towards this kind of marketing.
Hopefully, this blog has shed some light on concepts related to chatbots and AI.
The next step is to make decisions about your business. Do you really need a chatbot? Which issues are you planning to solve with a chatbot? Is there a chatbot app that will help you solve them? Or do you need to program your own chatbot from scratch? Does a chatbot fit into your marketing strategy or do you need to adapt it to the logic of chatbots? Will you have enough time and resources to get a chatbot? These are extremely important questions to ask yourself and your team.
With TruVISIBILITY, you will have a smooth chatbot-building experience: intuitive interface, guidance to build your chatbots, multiple channels, and caring customer service.
Want to receive more articles?
Sign-up for our weekly newsletter to receive info that will help your business grow