Written by Marcel Ayres on Planeta Chatbot.
Have you ever heard or had the experience of having a conversation with a conversational chatbot ? They are robots programmed to optimize consumer care via chats, providing quick information, answering questions, helping in decision-making processes, among other functions.
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Chatbots can be developed from rules (condition x action), and are combined with artificial intelligence , learning and personalization of your approach based on the continuous inputs it receives and the data provided by users. Beyond that come questions like: but does this bot replace human attention? The answer is no. However, by using bots, companies manage to optimize time and money in customer service, as it can scale, serving their users 24/7 (24 hours/7 days a week), removing doubts or even guiding the user through the purchase process through the website, application or social media and expanding their conversion results.
Another question is: how can I have a chatbot? Nowadays there are different players operating in this market:
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- Natural language processing platforms or NLP (IBM Watson, Microsoft LUIS, Recast.AI, Wit.AI systems etc.) that can be integrated into chatbots, giving them allows you to better understand the language used by users and connect to other data banks on the Internet.
- The creation of chatbots platforms (Chatfuel, Friendly, Flow, Botsify, Hi-Platform, etc.) that offer tools and services for the creation and maintenance of robots.
- Specialized companies and professionals commercializing work conversation strategically plan, develop and/ or perform continuous maintenance of these robots to increase their accuracy in interactions.
Here are key points presented by StartSE that need to be taken into account before investing in developing a conversational for your business.
It all starts with a “pain point” to be solved. Can you help your customers with your bot? How can you dial the difference in your business and improve or expand some kind of expected result? This is the starting point for the project.
- Themes and premises
What issues or topics should the bot address and need to understand in order to solve the user problem assertively? What will their language look like? What previous user information is important for the development of the conversation? What is the function of the bot, more precisely, within this topic that he will act?
- Simulation of dialogues
Once the topics are defined, I suggest simulating conversations on the topic, in order to assign possible questions that serve as a point (condition) for chatbot actions. This will make it possible to imagine a broader flow or create subflows of the conversation based on user demand.
- Navigation between themes and
In this step, it is important for the bot to understand the topics defined above to respond precisely. In addition to the work of refining points (conditions), you can work here in an allied way with NPL platforms (Microsoft LUIS, IBM Watson, etc.) to improve the reading and understanding of phrases sent by users.
- Conversation trees
With themes, integers and mapped phrases, conversational trees are now mounted (with inputs, responses, and automation flows).
- Information Sources
Here it is important to define where the Bot will look for information to respond to user demands. Will it be integrated with your own database? Will you have only the inputs from the database of the platform used?
- Assign channels
In in the event that there is a change in the quality of information.
Post originally published on the Hackel blog
Original version in Portuguese.