When building a chatbot you should think about bot’s ability to understand human language and to solve the user’s problems. A smart bot should make a human-like conversation and should not ask repetitive questions. Consequently, a smart bot can be a satisfying conversational partner that your customers will enjoy chatting to.
This guide will provide you with 10 important steps necessary for building a smarter bot that will serve your customers right. Read on to learn how to build a bot that will learn, understand customers’s needs, have the ability to sense the environment, be sharp to think, quick to act, formulate coherent and convincing responses, understand the mood of a user, have a personality, and act as a helper.
As explained in one of our earlier blog posts, the smart bot should keep some knowledge about its users in terms of what identifies them and “who” they are. For the chatbot to recognize patterns in data it receives and has earlier received, it needs to be “constantly learning.” Whether this happens is up to us humans.
Machine learning algorithms that are part of the technology behind the intelligent bot allow its operator to make sense of streams of data, which is afterward inserted in the same bot to help to improve its existing skills. When the bot operator is good at looking at and learning data, the bot can, in turn, perform better in its following interactions with users.
A Bot Should Become Aware of Those Users’ Needs
Users might have particular, and at times, complex needs, so the technology behind chatbots needs to be complex as well to make sense of those needs. As exemplified earlier, human users might ask the bot to fly them somewhere specific at a particular time whereas simultaneously they have limitations on their travel budget or the number of passengers – and they might feed that information to their bot all in one go. How to include and make sense of all of those wishes?
It is argued that the smart bot has the human capability of gaining information efficiently or at least as efficiently as its human operator, as discussed above. To be efficient means that the bot is assisted in understanding the intention of each request it receives and by making connections between them can respond most appropriately to all user needs at once.
Furthermore, considering how users interact, we propose that the technology behind smart bots is in some situations even better than humans at gaining information efficiently since it does not get stressed or forgetful the way humans do. People often have too many factors to care about, which gives bots an advantage. If they are smart enough, they will calculate users’ stress levels and respond carefully.
A Bot Should Have the Ability to Sense the Environment
One could argue that users’ needs have a strong connection to their environment or the context they are situated within. Therefore, understanding this context is extremely important if the bot wants to give people a pleasant experience.
Before the bot can perform a particular task, it needs to integrate with the physical and linguistic environment of the conversation to receive the information required. It is not only the capability of receiving data that matters but rather the importance of understanding what kind of requests and intentions specific environments trigger in users. BotXO’s chatbots are built as environment-sensitive, which means that they are operated to serve their users best depending on the specific time, channel, and behavior.
A Bot Should Be Sharp to Think
A bot whose operator thinks sharp does not just understand the environment the user resides in, but it goes a step further. The smart chatbot makes a decision based on how it interprets the acquired knowledge. According to Maruti Techlabs, this decision is made by leveraging pre-existing knowledge of the user and new knowledge the same user is continuously conveying to the bot. The smart bot achieves a decision by the use of neural networks in machine learning.
A Bot Should Be Quick to Act
Once the bot has taken the environment-sensitive decision(s), it has to react to keep the user engaged in the conversation properly. By that point, the smart or intelligent chatbot should know what to respond to the user. Progress towards the pre-defined goal of the interaction is reachable once the smart bot has gone through this sense-think-act cycle.
Smart chatbots allow the dialogue to jump between contexts that give people the ability to navigate without a defined path. Instead of remaining stuck in scripted decisions, smart bots are open for new input or additional parameters from its users even if it means replacing or adding to some already gained information. In real life, people can change their minds at any time, so the chatbot makes a smart move by respecting this change. It gives the bot users the feeling of more independence and freedom.
The smart bot’s ability to come with appropriate answers enables the conversation to flow more naturally like between two humans. To achieve this, the bot is assisted to learn the language nuances through NLU (Natural Language Understanding). NLU is a technique that powers conversations as it enables the bot to write in its users’ natural language when chatting with them. At BotXO, this function is tailored to individual languages to make things work in English, Danish, Swedish, German, Spanish, and more.
Besides being multilingual, smart bots, like the ones customers can build in the BotXO platform, correct your spelling, and recognize names. They use algorithms that help them to do checks for misspellings, look up names of persons, companies, or places as well as to divide users’ sentences into different substitutes to find a link between them.
As a result of NLU, bots can understand the intent of their users’ sentences. Altogether, this knowledge helps the bot to reach its users in a more efficient way where interactions between the two become similar to interactions between two humans.
What makes smart bots extra cool and intelligent is their ability to understand what mood their users are in! They do that through sentiment analysis as part of Natural Language Understanding, while this feedback, which is provided by users, enables to sensitize the bot’s responses. The smarter the bot, the better it has become at deciding whether its user is dealing with a small issue or a very urgent problem that needs a solution. It relates to understanding the language and the context of the conversation that allows the bot to decide the mood chatbot users are having.
Sentiment analysis also allows measuring of how users feel about the bot, which is beneficial for fitting the bot to people’s mood. According to Jens Dahl Møllerhøj, Lead Data Scientist at BotXO, “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 conversation is rarely limited to achieving just one response or one goal. Humans are social beings, so besides exchanging relevant information, they might try to have a little fun with their bot. Therefore, to have more stimulating conversations, the smart bot should integrate social talk into the conversation. It can give the conversation a lighter and more natural form. Enriching a chatbot with a “personality” (as close to a “person” as it can get) might enable the bot to engage its users better.
A Bot Should Act as a Helper Instead of a Collector
Having all of the above in mind, the biggest takeaway about the difference between dumb and smart chatbots is that the first act as collectors, whereas the second act as helpers. Tech professionals from Maruti Techlabs indicate that “a chatbot acting as a helper is considered to be smarter than the chatbot that serves as a collector.”
It means that the smart AI chatbot lets the user lead the conversation while through its operator, it learns from the user as much as it can. So, the more data it receives, the better! After that, the smart bot can show off its Natural Language Understanding power to assist its users closer to the users’ needs and desired goals.
In the same situation, the dumb bot aims to stick to its script by targeting the user with pre-defined questions that always expect a specific answer. The technology behind dumb bots does not support them to calculate how close a user input is to an intent. The lack of this understanding does not allow dumb bots to help their users in a clever and personal way, as smart bots do.
How can a bot deliver lovable automated conversations?
If we fuel a bot with NLU and a sense for the context of the conversation, this seems to be possible as it helps to deliver more personal experiences.
Any bot’s most prominent role model can only be a human, so for a bot to make sense and become a smart conversation partner, human involvement is needed and crucial to their development and success in any application.
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.