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Feedloop AI

Training

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updated : 19 July 2023

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What is Training?

Trainings allows you to teach and customize your AI agent's responses, ensuring it understands and engages with users like never before. Through the training process, your AI agent learns from example conversations and data, becoming smarter and more accurate in interpreting user intents. Craft personalized interactions, equip your agent with expert product knowledge, and infuse human-like empathy into every conversation

Here's how this cutting-edge feature empowers you:

Enhanced Customization: With the training feature, users can fully customize their AI agent's behavior, personality, and responses. They can shape the AI agent to align seamlessly with their brand identity and business objectives, creating a unique and personalized virtual assistant.

Improved Conversational Experience: By providing precise instructions and examples, users can guide the AI agent's focus during conversations. This ensures that the AI agent engages in goal-oriented interactions, such as assisting sales teams in securing leads, understanding customer pain points, and delivering tailored product solutions.

Human-Like Interaction: With the training feature, users can direct their AI agent's style and tone, ensuring it communicates with users authentically and naturally. The AI agent can use empathy, persuasive techniques, and natural language understanding to build rapport, foster trust, and leave a lasting impression on prospects and customers.

Through the training feature, users can continuously improve and fine-tune the performance of their AI agents. As more training examples are provided, the AI agent becomes more capable of handling a wide range of user interactions and providing accurate and contextually appropriate responses.

Training Guide

Accessing the Training Feature

Navigate to the dashboard or workspace.

Select the project in which you want to train the AI agent.

Locate the desired agent within the project and access its settings or configuration.

Navigating to Training

Once you are in the agent settings, find the Training tab.

Click on the Training tab to access the training feature.

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Training Types

In the Training tab, you will see two training types: "By Example" and "By Rules".

Choose the appropriate training type based on your requirements.

By Example Training:

In this type of training, users provide specific examples of conversations or inputs along with the desired outputs or responses that the AI agent should generate for each input.

These examples act as a guide for the AI agent to learn from and understand how to respond to similar inputs from users.

By example training is useful for teaching the AI agent to handle various user queries and scenarios effectively.

By Rules Training:

By rules training involves defining specific rules or conditions that trigger particular responses from the AI agent.

Users specify the conditions, and the AI agent is trained to follow these rules and produce the desired output when the conditions are met.

By rules training allows for more structured and conditional responses from the AI agent.

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Adding Training by Examples

By Example Training:

Select the "By Example" training type.

Click on the "+ Add Training" button to create a new training example.

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Enter a conversation or specific input example that represents a scenario or context.

Specify the expected output or response that the AI should generate for the provided input.

Click the "Save" button to save the training example.

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Save the training rule by clicking the "Save" button.

To discard a context,click the "Discard" button instead of the "Save" button.

By Example: You can use both English and Bahasa Indonesia as input examples. This training type allows you to provide various conversational scenarios in either English or Bahasa Indonesia to teach the AI agent how to respond accurately.

Adding Training by Rules

By Rules Training:

Select the "By Rules" training type.

Click on the "+ Add Training" button to create a new training rule.

Define a condition or pattern that triggers a specific response.

Specify the desired output or action that the AI should produce when the condition is met.

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Save the training rule by clicking the "Save" button.

To discard a context,click the "Discard" button instead of the "Save" button.

By Rules: This training type supports English input for defining specific conditions and responses. If you prefer to instruct the AI agent with rule-based patterns using English, this is the ideal option for you..

Deleting Training:

If you need to remove a training example or rule, locate the specific training item.

Select the option to delete or discard it.

Managing Multiple Training

You can add multiple training examples to cover various conversation patterns or user intents.

Ensure a diverse range of inputs and desired outputs to train the AI model effectively.

Testing the Training

After saving the training examples or rules, it's essential to test their effectiveness.

Initiate conversations or inputs that match the training examples or rule conditions.

Evaluate the AI agent's responses to verify if they align with the desired outputs.

Repeat the testing process with different inputs to validate the training.

Inspect Training

Click on the "Inspect" option within the chat bubble.

Once you click on "Inspect," The AI Agent will generate a display showing the relevant training used to generate its response

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Best practice

Example

Input Example: "I'm looking for a dress for a special occasion."

Desired Output: "For a special occasion, I recommend our ABC Evening Gown collection. They feature elegant designs and are available in various sizes and colors."

Input Example: "What are the latest fashion trends for summer?"

Desired Output: "This summer, the latest fashion trends include floral prints, pastel colors, and flowy dresses. Check out our Summer Style Guide for more inspiration."

Input Example: "Do you have any discounts or promotions available?"

Desired Output: "Yes, we currently have a promotion running where you can get 20% off on select items. Use the code 'SUMMER20' at checkout to avail the discount."

Input Example: "I need a durable backpack for hiking and outdoor activities."

Desired Output: "For hiking and outdoor activities, I recommend our DEF Adventure Backpack. It is made of water-resistant materials, has multiple compartments, and offers excellent durability."

Input Example: "What is the return policy for online purchases?"

Desired Output: "Our return policy allows you to return products within 30 days of purchase, provided they are in their original condition with all accessories and packaging."

Input Example: "Is there a loyalty program or rewards system for frequent shoppers?"

Desired Output: "Yes, we have a loyalty program called 'Shop & Earn.' You can earn points for every purchase and redeem them for discounts or exclusive offers."

Rules

Condition: When the user expresses interest in a specific product but hesitates to make a purchase.

Instruction: Offer a limited-time discount or a special offer to incentivize the user to make a purchase, emphasizing the value they will gain from the product.

Condition: When the user asks for a comparison between two or more products.

Instruction: Provide a detailed comparison chart highlighting the key features, benefits, and pricing of each product, assisting the user in making an informed decision.

Condition: When the user inquires about the availability of a product that is currently out of stock.

Instruction: Apologize for the inconvenience and offer to notify the user when the product is back in stock. Provide alternative product options that meet the user's requirements.

Condition: When the user asks for a demonstration of how a product works.

Instruction: Offer to schedule a personalized live demo or provide access to a pre-recorded video demonstration showcasing the product's functionality and key features.

Condition: When the user asks for customer testimonials or reviews about a specific product.

Instruction: Share positive customer testimonials, reviews, or case studies that highlight the product's success stories and satisfied customers, building trust and credibility with the user.