Overview

Simulations are one of Marketrix’s most powerful features - they allow your AI agents to explore and learn your application’s user interface through actual interaction. This hands-on exploration helps agents understand how your product works, making them significantly more effective at helping users.

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What Are Simulations?

A simulation is an automated exploration session where your AI agent interacts with your website or application to learn its interface, workflows, and functionality. Think of it as your agent taking a guided tour of your product to understand how it works.

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How Simulations Work

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Why Simulations Matter

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The Problem with Traditional AI Support

Most AI support platforms rely on:

• Static documentation - Agents only know what’s written in manuals
• Limited context - No understanding of actual user experience
• Generic responses - Can’t provide specific, actionable guidance
• Outdated information - Documentation often lags behind product changes

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How Simulations Solve This

Marketrix simulations enable:

• Real UI understanding - Agents see and interact with your actual interface
• Current knowledge - Agents learn from the live version of your product
• Specific guidance - Agents can provide exact steps based on real exploration
• Dynamic learning - Agents adapt as your product evolves

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What Agents Learn Through Simulations

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Interface Understanding

Visual Elements:

• Button locations and functions
• Form fields and their purposes
• Navigation menus and structure
• Modal dialogs and popups
• Error messages and notifications

User Flows:

• How to create accounts
• How to complete purchases
• How to access features
• How to troubleshoot issues
• How to navigate complex workflows

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Functional Knowledge

Feature Capabilities:

• What each feature does
• How features work together
• What’s possible vs. impossible
• Common user tasks and goals
• Edge cases and limitations

Error Handling:

• What errors look like
• How to resolve common issues
• When to escalate problems
• Recovery procedures
• Alternative approaches

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The Simulation Process

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1. Agent Preparation

Before starting a simulation, your agent:

• Receives instructions about what to explore
• Gets connection details to access your application
• Uses existing knowledge to guide exploration
• Sets exploration goals based on your requirements

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2. Active Exploration

During the simulation, your agent:

• Opens your application using provided credentials
• Navigates through interfaces following your instructions
• Interacts with elements like buttons, forms, and menus
• Records observations about layout, functionality, and workflows
• Asks questions when encountering unfamiliar situations

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3. Learning and Recording

As the agent explores:

• Captures screenshots of important interfaces
• Records interaction sequences for future reference
• Builds mental models of how your application works
• Identifies common user paths and pain points
• Documents feature relationships and dependencies

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4. Knowledge Integration

After exploration:

• Integrates new knowledge with existing information
• Updates understanding of your product
• Prepares for user assistance with real experience
• Builds confidence in providing accurate guidance

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Types of Simulations

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Feature Exploration

Purpose: Understand specific features or workflows Example: “Explore how users create and manage projects” Outcome: Agent learns project creation, editing, and management workflows

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User Journey Mapping

Purpose: Follow complete user experiences Example: “Walk through the entire signup and onboarding process” Outcome: Agent understands the complete user journey from start to finish

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Error Scenario Testing

Purpose: Learn how to handle problems and edge cases Example: “Explore what happens when users encounter errors” Outcome: Agent learns error messages, recovery steps, and troubleshooting

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Integration Testing

Purpose: Understand how different parts work together Example: “Explore how the dashboard connects to other features” Outcome: Agent learns feature relationships and navigation patterns

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Benefits of Simulation Learning

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For Your Agents

Enhanced Accuracy:

• Agents provide specific, tested guidance
• Responses based on actual interface experience
• Reduced guesswork and assumptions
• Higher confidence in recommendations

Better User Experience:

• Agents can guide users through exact steps
• Specific button names and locations
• Accurate workflow descriptions
• Real-time problem solving

Continuous Improvement:

• Agents learn as your product evolves
• New features automatically discovered
• Updated workflows and interfaces
• Always current knowledge

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For Your Users

Precise Guidance:

• Exact steps with specific instructions
• Accurate button and menu references
• Tested workflows that actually work
• Reduced user frustration

Faster Problem Resolution:

• Agents know where to look for issues
• Understand common error scenarios
• Can provide immediate solutions
• Reduce support ticket volume

Better Onboarding:

• Agents can guide new users effectively
• Understand the complete user journey
• Provide context-aware assistance
• Improve user success rates

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What Makes Marketrix Different

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Traditional AI Support Platforms

• Static knowledge from documentation only
• Generic responses not specific to your interface
• Outdated information that doesn’t reflect current state
• Limited context about actual user experience

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Marketrix with Simulations

• Dynamic learning through actual interface exploration
• Specific guidance based on real interaction experience
• Current knowledge from live product exploration
• Deep understanding of user workflows and pain points

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Simulation Best Practices

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Effective Simulation Instructions

Be Specific:

• “Explore the user dashboard and all its features”
• “Walk through the complete checkout process”
• “Test the account settings and profile management”

Focus on User Goals:

• “Learn how users accomplish [specific task]”
• “Understand the [workflow] process from start to finish”
• “Explore common user scenarios and edge cases”

Include Context:

• “As a new user, explore the onboarding process”
• “As an existing user, learn how to manage subscriptions”
• “As an admin, understand the user management features”

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Regular Simulation Updates

Product Updates:

• Run simulations after major feature releases
• Update agent knowledge when interfaces change
• Test new workflows and user paths
• Verify existing guidance still works

User Feedback Integration:

• Run simulations based on common user questions
• Explore areas where users struggle
• Test scenarios reported in support tickets
• Validate solutions to user problems

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Next Steps

Now that you understand simulations, you’re ready to:

1. Create your first simulation - Learn how to set up and run simulations
2. Monitor simulation progress - Watch your agents learn in real-time
3. Review simulation results - Verify what your agents learned
4. Test in the playground - See how simulation learning improves agent performance

Simulations are the key to creating agents that truly understand your product. By letting your agents explore and learn your interface, you’re creating AI assistants that can provide the specific, accurate help your users need.

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Getting Help

If you need assistance with simulations:

• Check the troubleshooting guide for common issues
• Review simulation best practices for effective exploration
• Test different instruction approaches to find what works best
• Contact support for additional help

You’re now ready to create agents that truly understand your product through simulation learning! 🚀