When you build a bot it’s important to consider the chatbot’s ability to understand human language and solve the user’s problems.
A smart bot should be able to have a human-like conversation and should not ask repetitive questions. Engaging with a smart bot should be something your customers will enjoy.
This guide will provide you with 10 important steps that teach you how to build a chatbot that will serve your customers right.
Read on to learn how to build a bot that will understand your customers needs, their mood, the context of the conversation, and formulate coherent and convincing responses.
Your smart chatbot should collect data from its interactions with users. For the chatbot to recognize patterns in data, it needs to be ‘constantly learning’ from this data.
Think about how to build a chatbot that doesn’t ever get smarter? Your customers would just be having the same conversation again and again!
Machine learning algorithms that are part of the technology behind intelligent chatbots, and these algorithm’s allow the chatbot to make sense of streams of data.
When you consider how to build a chatbot, machine learning is a huge part of what goes into the performance of the bot in terms of its interactions with users, and therefore the continuous improvement of its customer service skills.
Individual users might have particular, and at times, complex needs. As such, the technology you use to build a bot needs to be sufficiently complex to make sense of those needs.
Consider the case of a user requesting travel information – the user might ask for a specific destination and time, but with limitations on travel budget and number of passengers – and they might feed that information to their chatbot all in one go.
How should the chatbot make sense of all of those variables at once?
A smart bot should have the capability to process this information at least as efficiently as a human operator. This means that the bot understands the intention of each request and is able to respond appropriately to all user needs simultaneously.
Furthermore, when you build a bot the technology used should allow the chatbot to be even more efficient than humans at processing data efficiently.
A truly smart bot should be able to take many factors into account and adjust its response carefully, and it is simply not possible to build a bot like this without machine learning.
Users’ needs have a strong connection to their environment or the context they are situated within. Understanding this context is extremely important in providing users with a good experience.
Before the bot can resolve a users request, it needs to understand the context of the conversation.
It is not only understanding a users request that matters, but also what kind of requests and intentions specific environments trigger in users.
After all, why build a bot that exists only in its own world?
Certainly’s platform solves the issue of how to build a chatbot from scratch that is environment-sensitive, meaning the chatbots serve users differently depending on the specific time, channel, and individual user behavior.
Smart chatbots do not just understand the environment, but are able to make decisions based on how they interpret this.
These decisions are made by leveraging pre-existing data about the user as well as new data collected in real-time about that specific user.
The smart bot reaches a decision by use of neutral networks in terms of machine learning algorithms.
Once the bot has taken those environment-sensitive decision(s), it has to react in order to keep the user engaged in the conversation.
By that point, the smart chatbot should know how to respond to the user, and understand how to resolve the interaction through this sense-think-act cycle.
If you build a bot that achieved all the steps mentioned so far, your chatbot should be able to react to your customers instantly. And let’s face it, no one likes waiting…
Smart chatbots can comprehend dialogue that jumps between contexts. This allows users to navigate a conversation without a defined path.
Instead of remaining limited to if/then scripted decisions, smart chatbots are able to comprehend additional input from users, even if it means replacing or adding to previously recorded data.
In real life, people change their minds, and chatbots needs to be able to take this into account. This gives users more independence and freedom throughout the conversation.
The smart bot’s ability to provide appropriate answers enables the conversation to flow more naturally as it would between two humans.
To achieve this, build a bot capable of learning language nuances through NLU (Natural Language Understanding). NLU technology enables chatbots to mimic natural language when dealing with users.
At Certainly, NLU functionality can available in various languages to maximize customer satisfaction – English, Danish, Swedish, German, Spanish, and more.
Besides multilingual functionality, smart bots can identify and account for users’ misspellings when searching for the names of persons, companies, or places in query resolution.
Their learning algorithms allow smart bots to divide users’ query sentences into fragments, and apply substitutes to find a link between them.
If you build a bot that can do this, far fewer of your customers are going to walk away unhappy.
As a result of NLU technology, bots can understand the intent of users’ sentences. When you think about how to build a chatbot, factors such as these make user interaction its most efficient, and the most similar to interactions between two humans.
What makes smart bots extra cool is their ability to understand what mood their users are in!
They do this through sentiment analysis, which allows chatbots to sensitize their own responses based on user feedback through usual interactions.
The smarter the bot, the better it becomes at deciding whether a user is dealing with a small issue or a very urgent problem that needs an immediate solution.
It relates to understanding the language and the context of the conversation that allows the bot to determine the mood of a user.
Sentiment analysis is also capable of measuring users’ perception of the bot itself, which is beneficial in tailoring the bot to people’s mood.
According to Jens Dahl Møllerhøj, former Lead Data Scientist at Certainly, “being able to measure how happy customers are with the bot means we know how to change the bot to move into the right direction.“
Most humans would agree that real conversations is rarely limited to achieving just one goal. Humans are social beings, so besides exchanging relevant information, they might want to converse.
But how to make a bot that accounts for this?
To encourage more stimulating conversations when you build a bot, integrate social talk software. ‘Social talk’ is the act of engaging in lighter and more natural interactions.
Enriching a chatbot with a ‘personality’ therefore enables the bot to engage its users better.
The biggest differentiator of smart chatbots is that they act as helpers, instead of simply collectors of data.
A smart AI chatbot lets users lead the conversation, learning about the user through these initial interactions. Through this, the chatbot develops a better understanding of the users’ needs and desired goals.
In the same situation, a standard chatbot would stick to its script, targeting the user with pre-defined questions, and only able to interpret specific answers.
The technology behind standard chatbots does not support interpretation of user intent, preventing the suggestion of personalized solutions, as smart bots do.
If we fuel a bot with NLU and a sense for the context of the conversation, we can build a bot which delivers more personal experiences.
And what’s the first consideration of how to build a bot that your customers will love?
One that provides exceptional customer service of course!
For a chatbot to become a smart conversation partner, build a bot that acts like a human, as they will develop just like your human employees do!
More personal interactions have the potential to trigger a more significant amount of engagement and excitement, and if you’re a business, a much better customer experience.
Want to learn more? Find out how to leverage AI Chat to create outstanding Customer Experiences in our ebook:
If you are interested in hearing more about how to get started, get a demo of the Certainly Platform here.
Article written by Iliknur Hyusnyueva