Why is it important to train your company’s chatbot? Who does it?
Before getting into the specific topic of this article, training chatbots, it is worth revisiting a few points that people tend to forget.
The first thing to remember: What is a chatbot?
The word “chatbot” is made up of the words “chat” and “bot” (short for robot). So, a chatbot is simply a robot that chats, in order to interact with people. Although it sounds like new technology, chatbots have been around for quite some time and can be found, for example, in the telephone-based services of phone companies and banks. You know those messages from your cell phone company asking you to press a number to reach the right operator? Chatbots follow the same logic and principles, but they do so with a bit more sophistication, and using a text message interface.
The second thing: How does a chatbot work?
Chatbots use specific programming, in which certain words are identified and associated with user requests. For example, the customer might ask “when will the product be delivered?” The bot will search the words it has been taught, their relevance within the information recorded in the system, and offer possible answers to the user.
Now that we have revisited what a chatbot is and how it works, we can talk about training chatbots and why it matters.
Training a chatbot is a key part of ensuring the technology preforms well. Let’s get to some tips on how to conduct this training.
1. What does it mean to “train a chatbot?”
When we talk about “training a chatbot,” we are referring to the task of providing inputs that are relevant to the bot’s purpose, so it learns by example the meaning of certain questions.
In order to ensure that training is appropriate and ideal, we absolutely must understand the intention of the user’s request and what entities (people, places, concepts, objects, products, etc.) they are talking about.
Because it is impossible to simply program a bot to understand every possible request, we need to train the bot, giving it enough data and content to recognize, at minimum, the most frequent information.
2. Why is it important to train chatbots?
The training phase is what makes the chatbot more accurate. This is when we teach the bot how to “behave,” and evaluate the types of mistakes it makes in understanding or answering questions.
The idea is to increase the bot’s knowledge base (intentions, entities, and diverse sample sentences), and set up its content, so that it is prepared to deal appropriately with future questions, committing the fewest possible communications errors.
This way, each time the bot receives a new request, its algorithm will calculate correlations between the data it has received and the information it already has, offering the most appropriate response.
3. Where to get data to train a chatbot?
You can collect data in many ways, including:
Data that is available online: the simplest way to train your bot is to use data that is available online. You can find free databases of information specifically for chatbots online, for a wide variety of purposes.
Collecting data within your company: the closer the data used to train your chatbot are to reality, the better your chatbot will perform. So, if your company’s call center has a database of customer interactions, you may have an excellent opportunity to build a system using data that are extremely relevant to the task your chatbot must perform.
Collecting interaction data from the chatbot itself: after you have completed testing, adjusted your chatbot, and brought it online, ensuring the quality of its software is an ongoing effort. This is why you should include a method for users to evaluate the performance of the chatbot. This will allow you to continue optimizing the application, maintaining a level of excellence in customer service, and winning more customers using this channel.
And what is chatbot training comprised of?
We can facilitate chatbot training by including certain additional options within the system’s cognitive motor:
· Intention: effective communication is rich in empathy and intuition. These skills strengthen relationships and allow us to quickly identify what someone wants.
· Entities: once the chatbot has worked and understood the expected outcome, it needs to extract the relevant information. Just like you do, for example, when a mechanic overloads you with details about car trouble, and you detect the details and listen to the “entities,” such as when the repair can be done and how much it will cost.
· Correct and practice: like any new employee, the chatbot needs to learn about its tasks. Fortunately, you do not need to invest in new training materials. Reference data can come from existing communications assets, as discussed above, such as written transcripts of of voice conversations conducted by customer service representatives.
Once these assets have been uploaded, your chatbot will technically be in its trial period. The next phase, just like with human employees, is to correct its mistakes. This is an interactive process. But, over time, the chatbot will get better at representing your company.
But, who actually trains the chatbot?
It is time to end the myth that “they learn on their own.” We teach chatbots to converse, using a process of continuous learning, using the interaction history of real users over time.
And to ensure this learning progresses appropriately, the most qualified person is a communications professional, who can ensure the chatbot responds correctly, maintaining the quality of customer service.
Ultimately, it works like a kind of curatorship. Natural Language Processing (NLP) is built up through constant practice, using the detection of patterns in data that can be used to make sense of information given by users, providing ongoing improvement in quality, enabling immediate results.
In other words, the trainer looks at the behavior of the user and creates or changes the chatbot’s response for future occurrences, making the chatbot as accurate as possible in its interactions. The chatbot’s algorithms receive words and phrases for each new input intention, in order to provide answers that are correlated with the questions asked.
A communications professional can monitor the questions and answers using the chatbot’s database, in order to adjust the chatbot’s ability to combine content with the correct answers. This allows for continuous improvements, increasing the precision of the chatbot.
Many types of professionals can take on the work of continuously improving and personalizing your chatbot. A UX Writer is ideal (because they are well-rounded professionals, with experience in language and user experience), but others are possible, including linguists, advertising agents, marketing analysts, and content analysts. Ultimately, it depends greatly on what the company doing the hiring expects of the person assigned to the project.
To conclude, if you invest time in correctly training your chatbot, it will yield fruit for you and your brand. Chatbots will never replace interactions between people, but if we can make them pleasantly simulate human conversation, they will be able to help us have meaningful relationships with our customers.