Artificial Intelligence (AI) assistants are the advanced and forthcoming means of support for our product or service. These cutting-edge technologies allow us to provide prompt customer service, ensuring easy access for those in need and guiding them to the right individuals for query resolution and issue-solving satisfactorily and swiftly.
It is evident that deploying a help bot can benefit any organization in numerous ways. Automation of specific support services can result in higher conversion rates, better customer interaction, streamlined and standardized data collection from customers, and decreased operational expenses.
After careful consideration, it has been determined that a service robot would be advantageous for your organization. So what is the next step? Hiring an external resource to construct the bot and integrate it with your website might incur high expenses. Alternatively, an in-house solution can be developed using open-source software that is accessible to all companies.
If you opt to implement this approach in-house, what resources will you require? Firstly, let’s scrutinize what is needed for the launch of a support bot.
Well-defined Objectives
Before initiating the development of a chatbot, it is crucial to determine its objectives. It is advisable to ask questions such as “What is the chatbot’s purpose?”, “What are the typical customer issues?”, and “What functions do we want in the chatbot?” to guide the selection of the platform and design of the bot’s conversational flow. This will result in a successful outcome.
Before embarking on the development of your chatbot, it is critical to have a comprehensive strategy in place. Not defining a clear objective for the chatbot could lead to an unsuccessful outcome. Clarifying the rationale behind why the chatbot is being built, its target audience, and the expected impact it will have on your business and customers is crucial.
Select a Chatbot Service
Several free and open-source chatbot development platforms are available, including Botkit, Botpress, Rasa, Wit.ai, and OpenDialog, when selecting a chatbot development platform. It is important to bear in mind that integrating an open-source solution into your existing website might necessitate the involvement of web professionals.
Numerous commercial chatbot systems offer facile integration with your website; however, they might be pricier and have fewer features than open-source solutions.
Developers
Abiding by the open-source approach necessitates the engagement of developers skilled in one or more prevalent chatbot languages. Currently, Python, Clojure, Ruby, Lisp, and Java are the most commonly used programming languages for chatbots.
Your developers will find it advantageous to be familiar with the frameworks that several open-source chatbots utilize.
Conversing Effectively
It is crucial to take concrete steps at this point. Once the requisite personnel and equipment are assembled, we can proceed to devise the chatbot’s dialogue. At present, no chatbot exists that can initiate a conversation unless a script has been written in advance. This can be achieved by creating triggers, decision nodes, and action blocks.
Typically, an initial exchange with a chatbot is initiated when the user launches the application. The user will then ask a question, which a decision node (e.g., Customer A seeking help with Product X) must answer. Upon reaching a resolution and specifying an action block (e.g., inputting an email or serial number for a product), the process is complete.
Producing such conversations can be a time-consuming process, necessitating the development of several of them to cover all the use cases that the chatbot must cater to.
It’s Time to Educate the Robot
The subsequent step is to train the chatbot in line with the devised conversation flow, but only if your chatbot employs AI. Depending on the complexity of the chatbot’s rules engine, this stage might be discretionary.
This constitutes a critical juncture in the development of an AI-powered chatbot. Throughout the training phase, available data sets (like emails, support tickets, and other conversation threads) or bespoke data sets from an external source can be employed to instruct the bot on how to respond adequately.
For the successful training of the bot, it is crucial to anticipate what its human users might say and deliver a fitting response. Familiarity with utterances, intent, and entities is vital to accomplish this; for instance, an utterance such as “What is today’s weather?” includes the entities “today’s” and “weather,” which help clarify the question’s intent.
During training, it is crucial to verify that:
- Intentions are distinct and encompass a vast array of words.
- Entities serve a specific purpose.
- The chatbot possesses character.
- A conversational robot leverages more than just words to interact.
It’s Time to Test the Bot
It is crucial to set aside ample time for testing the chatbot and to employ a varied test group. This is vital to a successful testing process.
It is recommended that personnel familiar with the project, such as engineers, should not be the ones to conduct bot testing. To ensure a wide range of responses, it is advised to involve personnel from other divisions. A diverse testing team can yield more dependable outcomes and identify how the bot may falter or be used differently by individuals with varying personalities, cultural backgrounds, or levels of expertise.
Conclusion
Support chatbots offer an effective means to streamline initial customer contacts. Additionally, they are a cost-efficient approach to realizing a desired outcome that may not be immediately discernible. The heightened customer engagement and satisfaction translates to a notable boost in profitability.
While deploying a support chatbot may require a certain amount of time, the advantages to your business and clients make the endeavor worthwhile.
