Before the arrival of chatbot platforms, building a bot was a complicated and tiresome task and required sophisticated sets of tools and advanced programming knowledge.
A chatbot platform is a set of tools that is used to conveniently build, train, implement and manage Artificial Intelligence conversations for your enterprise chatbot.
Cognitive Abstraction: With this function, you can take advantage of any AI service available today and scale for future services. It will not be blocked to a specific supplier or product of AI.
Omni-channel implementation: the platform must be deployable in most of your communication channels.
Easy integration: The solution should be able to easily integrate with business applications and work in conjunction with current legacy systems.
Extensive customization: The bots must be fully customizable according to the organizational and brand needs.
First steps for the development of a enterprise chatbot
- Identify profitable use cases within your company.
- Establish an automation strategy with the bot.
- Perform tests for multiple use cases.
- Experiment with different services and review them in different scenarios.
Factors to consider
Chatbot platforms are better alternatives to a development framework, and allow companies to focus on creating and delivering chatbots that address the specific needs of employees, partners and customers instead of focusing on the technical aspects of developing a chatbot through programming and engineering.
The following are some of the main architectural requirements that companies need to ensure are incorporated into their chatbot platforms.
1. Multiple types of chatbot
Ideally, you have the ability to develop, build and deploy chat bots that target a single function (for example, allow customers to track your shipping requests), as well as create a multi-purpose chatbot that communicates with multiple systems and complete tasks in each of them. (for example, customer support assistant).
2. Multiple tasks
What can the bot do? The platform provides pre-made chatbots that address specific use cases (for example, connect to an api) or the ability to customize chatbots to handle workflows and multi-step processes (for example, accept questions and find answers to frequently asked questions) .
3. Multiple channels
Can users take advantage of chatbots on the channel of their choice? You should look for platforms where you can add the chatbots to your website, messaging and mobile applications.
4. Recognition of natural language and voice
Does the platform have the capacity to recognize natural language and voice? Is the training based exclusively on Machine Learning? Can chatbots maintain precise two-way conversations, rich in content, through text or voice?
Chatbot platforms that combine Natural Language Processing and Machine Learning offer the best results, recognizing the intention and extracting entities to understand the meaning.
5. Configuration and Analytics Panel
Does the platform facilitate the configuration of messages to users, chatbots and internal and external systems using a configuration panel?
Some basic requirements should include the capture and storage of messages sent to and from users, the automatic registration and classification of errors and failures of messages, and the processing of user entries from any channel.
6. Conversation design
What type of tool is used to build bots and conversations? Platforms must include an intuitive, web-based tool to design and create conversations in a consistent manner, while being customized based on use cases, tasks, channels and requirements, along with the option to start the process of development from scratch or reuse it.
Look for the capability to test the build of chatbot throughout the development.
There is a difference between a platform and chatbot development frameworks or standard non-configurable solutions that are passed as a platform.