Getting Started with CXone Bot Builder

This page introduces essential Conversational AI concepts and ties them to Bot Builder. The goal is to help you understand the purpose of Bot Builder configurations and what they help you accomplish.

A conversation between a contact and any agent, including bots, has three key elements. The key conversational elements have corresponding configurations in CXone Bot Builder. When you understand these configurations and how they work together, you can approach creating a bot with confidence. They are:

• What the contact says.
• What the contact wants.
• What the agent or bot says and does.

What the contact says and wants are represented in Bot Builder with intents, entities, and slots. What the bot says and does is represented by stories, rules, and bot actions.

What the Contact Says and Wants: Utterances, Intents, Entities, and Slots

The contact communicates with the bot by typing messages in the chat window. The bot receives the messages—also called utterances—and acts on them.

Concept	Definition	Example	What the Bot Does
Utterance	Anything a contact says in an interaction. Sometimes called a message.	"I lost my password." "What is my balance?" "Are you a bot?"	The bot uses Natural Language Understanding (NLU) to analyze each contact utterance to determine its meaning, or intent.
Intent	What the contact wants to communicate or accomplish. Every message the contact sends has an intent.	"I lost my password" has the intent of "reset password". "Hello" has the intent of "greeting".	The bot analyzes a contact's message using NLU This process expands on Natural Language Processing (NLP) to make decisions or take action based on what it understands. to determine the intent. Once it knows that, it can respond with a message of its own. You configure the response you want the bot to use for each intent.
Entity	A defined piece of information in a contact's message.	Person or product name, phone number, account number, location, and so on.	The bot uses NLU to identify entities in a contact's message. Entities help the bot understand what the contact's message means.
Slot	An entity extracted from a contact's message and saved for use in bot responses. Similar to a variable.	Creating a slot for contact name lets the bot use that name in responses during an interaction, making it more personal.	When configured to do so, the bot extracts an entity from a contact message and saves it in a slot. You can have the bot use this information later in the conversation.

What the Bot Says and Does: Stories, Rules, and Bot Actions

Human conversation is unpredictable and varied. Your bot's responses are not. This means your bot must be able to correctly interpret the wide variation in how humans speak, but it doesn't have to "think" about how it will respond. The bot's responses are clearly defined and depend on the intent that's identified.

Concept	Definition	Example	What the Bot Does
Rule	Defines a bot's response to messages that don't change meaning with context.	Single-turn interactions with fixed responses: What are your hours? What is your address? Conversation building blocks: Greetings, good-byes, thank yous and transitions; simple yes/no questions; and acknowledgments. CXone Bot Builder comes with default intents and rules for several of these, including greetings, handover Any contact message that should trigger transfer to a live agent requests, and more. FAQs Insults and classic bot challenges	Rules are one of two ways you can configure how the bot responds to an intent. Rules are useful for certain kinds of intents, but not all intents.
Story	Trains a bot to handle an interaction based on message intent and conversational context.	In an interaction about a forgotten password, the bot would respond to, "How do I do that?" in one way. If the interaction were about creating a new account, the response would be quite different even though in both cases the contact is using the same words with the same intent – to get more information.	Stories are the second of two ways you can configure how the bot responds to an intent. Stories teach the bot how to use the context of the conversation to respond appropriately.
Bot Action	Anything a bot says or does while handling an interaction.	In an interaction about a forgotten password, the bot responds by sending the link to the password reset FAQ on the website. When a contact expresses frustration, such as "I don't understand! It's not working!!!" the bot responds with "I'm sorry. Would you like me to transfer you to a human agent?" When the contact says yes, the bot initiates the transfer.	Actions are the options you have when defining how you want the bot to respond to each intent. They give you the flexibility to configure each response to achieve the outcome that meets the contact's needs.

How the Bot Learns: Training and Testing

Training teaches your bot to correctly predict contacts' intents The meaning or purpose behind what a contact says/types; what the contact wants to communicate or accomplish. It starts with providing your bot plenty of high-quality, real-world examples of each intent. This is called training data. When combined with training dialogues Bot stories and rules in CXone Bot Builder., training data helps your bot learn to recognize what contacts need, and then to respond appropriately.

To test your bot, you must first build a model Version of a bot that has been trained and staged of the data in the bot's configurations. In Bot Builder, the Train and Stage option triggers a new model to be built. The process runs in the background.

A model is built from an analysis of the configured intents, stories, rules, examples, and other training data. The model is the core of what your bot is—a software program that analyzes conversational human speech to determine the closest match from its set of data points, then executes the corresponding action.

You can build a new model as often as you want to. Each model is numbered and there is a historical list of past models.

After the model is built, you can test your bot. Testing involves having conversations with your bot. This is how you find the places where your bot doesn't understand, or makes poor predictions. You can fix the configurations, build a new model, and test again.

Bot Builder has a built-in chat program you can use to have test conversations with your bot. You can also share your bot with other people who can help you test it. They don't have to report their experiences to you, because every conversation your bot has is saved in Bot Builder. You can review them to find the pain points that need attention.

Reviewing conversation data is important during the development of your bot as well as after it's in production. Ongoing fine-tuning of intents, stories, and rules is needed to ensure your bot continues to perform well.

How to Deal with Trouble

Bot Builder provides two configurations that allow you to deal with potential bot problems:

• Fallback: This teaches your bot what to do when it's not sure how to proceed. There are two kinds of fallback: 
  • NLU fallback: Used when the bot isn't confident its understanding the contact.
  • Action fallback: Used when the bot isn't confident in its ability to predict the next action.
• Safety Net: A safety net allows you to configure what happens when there's another problem with the bot or the systems it connects to. This could include things such as the bot taking longer than normal to respond to the contact.

Fallback and a safety net are preventative options, but not all problems can be prevented. It's important to regularly review conversation data to look for contact pain points.

Monitor and Manage Your Bots

Bot Builder provides many tools you can use to monitor your bot's performance. This is a critical, ongoing part of managing your bots. By regularly monitoring your bot's performance with these tools, you can spot pain points and refine the bot's configurations to ease them.

The following tools allow you to review conversation data: 

• Insights: Provides reporting and real-time, interactive analytics for your bots: 
  • Dashboard: Provides widgets that display real-time data on customer conversations and messages.
  • Journeys: Provides detailed analytics on the flow of intents during your customers conversations.
  • Conversations: Displays all bot conversations for you to review. You can search, tag, or create training data from these real conversations.
• NLU Inbox: Helps you manage your NLU This process expands on Natural Language Processing (NLP) to make decisions or take action based on what it understands. data to improve the quality of your bot. It shows all new messages from contacts.
• Query search: Use the tags to narrow results in the NLU inbox or the Insights section.

The following tools allow you to manage and organize your bot's data:

• Tags: Use tags throughout Bot Builder. You can have them applied automatically by the bot or you can apply them manually.
• Bot skills: Use bot skills to organize training data based on what your bot can do. You can filter training data by skill to limit what's visible to you.

The following tools allow you to view information about your bot: 

• Health Monitor: Displays information about your bot's training, models and configuration changes.
• Import and Export Tools: import or export certain data from your bots. You can use this as a backup option.
• Activity Log: Provides a history of what users are doing when logged in to Bot Builder.

Getting the Most from CXone Bot Builder

As you begin to make plans for how best to work bots into your contact center, consider the following ideas. They can help you get the most from Bot Builder.

• Build multiple bots A software application that handles customer interactions in place of a live human agent. for different use cases, channels, or audiences. You can have them work together with live human agents using digital Any channel, contact, or skill associated with Digital Experience.ACD skills. CXone views your bot as a user entity, so routing works the same way for a bot as for your human agents.

• There are many use cases for bots. For example, you can: 

  • Collect information before handing the contact over to a human agent.

  • Handle triage at the start of interactions to route contacts to a more specific agent.

  • Use bots to handle the most common and simple questions your agents receive, such as checking on order statuses or billing due dates, updating contact information, or questions about store locations and hours.

  • Let bots handle your night shift to provide 24/7 customer service. Create a digital ACD skill for overnight interactions, then set up your script with to send incoming interactions to a bot overnight. The bot can either handle the interaction or route it to an agent for handling the next morning.

  • Use Autopilot Knowledge to deliver answers pulled directly from your CXone Expert knowledge management center.
  • Set up integrations between Bot Builder and other systems via API to increase the usefulness of your bot.
  • Set up scripting integrations to create custom bot actions using JavaScript.

How to Start a New Bot Project

If you're new to Bot Builder, you can follow the tutorial. It walks you through creating a sample bot.

After you are comfortable with the Bot Builder interface and concepts, you can follow the implementation process to begin planning and building your first bot. This process covers all the tasks you need to complete when creating a bot.

After you have a stable working model of your bot, you can begin to slowly introduce it to your customers. Instead of immediately having your bot handle a full load of interactions from the start, you could: 

• Drive a small percentage of traffic to your bot to start out slowly. Raise the percentage over time as the bot gets smarter and more capable of handling more use cases. In your Studio script, use script logic to set conditions to define what traffic should be routed to the bot.

• Use digital skills and script logic to split traffic between two different bots for A/B testing. This helps you validate which bot performs better.