Activechat Manual
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What is Activechat?
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Conversational AI
For Customer Service Teams
For Product Managers
For Innovation Teams
For Marketers
For e-commerce
For developers
Help Guides
Setting up your team
Managing conversations
Natural language automation
Building automations visually
Improving your virtual agent
Using live chat AI hints
Customizing automatic website page messages
Tracking website actions
Facebook Ads automation
Lead generation
Zapier integrations
Customizing your project
Pricing guide
Fundamentals
Terminology
Intents and entities
Contexts
Skills and events
Conversation elements
Messaging channels
Intents and bot skills
Conversation insights
Grow tools
Broadcasting
Visual builder reference
Sending messages
Triggering events
Manipulating data
Conditional logic
Timers and delays
E-commerce blocks
Natural Language
System attributes
System events
Integrations
Google services
Shopify
WooCommerce
Dialogflow
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Terminology
This part of the manual will give you some background in conversational AI and customer service automation by defining key concepts and explaining some terms.
There are a few key concepts to understand when it comes to conversational AI.

What is conversational AI?

The use of artificial intelligence technology to create chatbots and other types of virtual assistants that can communicate with humans in natural language is called conversational AI. It's a type of artificial intelligence that enables computers and devices to have natural conversations with people.
Natural Language Processing (NLP) is the ability of a computer to understand human language and respond in a way that is natural for humans. This includes understanding the intent of a user's question, as well as understanding the nuances of human conversation.
Context is also important, as a computer needs to understand the conversation taking place in order to respond in a way that is relevant. Additionally, computers need to be able to learn over time, so that they can better understand the nuances of human conversation.
Each of these objectives can be achieved easily with Activechat, so let's dive into some specific terms first.

Do I need a tech background to build conversational AI systems?

Quick answer: no. Our vision is to enable non-tech teams that do customer communication (service, marketing, sales, etc) with the most up-to-date technology to help them do their job better, and we are devoted to making this process as easy as possible.
Once you get familiar with the basics of Activechat as a platform, you'll be able to build advanced customer service automation scenarios in weeks or even days instead of months, skipping the development learning curve and saving substantial amounts of money on custom development.
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What is conversational AI?
Do I need a tech background to build conversational AI systems?