How Mutiny AI Works: Features, Usage, and Best Practices

Campaigns is available to customers with the ABM Package. If you are not on this plan and would like to learn more, please reach out to your Mutiny Rep for assistance.  If you are unsure who your rep is, our support team can help you out by submitted a ticket at the bottom of the page!

Overview

Mutiny AI is designed to empower marketers to create personalized, account-specific experiences at scale by leveraging advanced AI-driven content generation, dynamic page structuring, and intelligent account insights. This guide breaks down how Mutiny AI works, where it’s applied, and how to use it effectively for your campaigns.

What This Guide Covers:

• How Mutiny AI powers personalization
• Key AI-driven features and their use cases
• Best practices for writing prompts and leveraging account data
• Technical Specifications

Core Mutiny AI Features

Mutiny AI is structured around four main features designed to help you create personalized, scalable microsite experiences:

1. Theme Extraction

Purpose: Quickly apply brand guidelines across microsites by automatically pulling key design elements from your website.

How It Works:

• Mutiny uses a web scraper powered by GPT-4 to analyze your website’s HTML and extract essential design elements, such as:
  • Colors
  • Fonts
  • Button styles
  • Page layouts
• Once extracted, these elements create a cohesive theme applied across your microsite templates.

Best Use: Run this feature once for each brand or design refresh to save time applying consistent styling.

2. Base Page Generation

Purpose: Quickly build a microsite structure based on an existing webpage’s layout and content.

How It Works:

• Mutiny scrapes your target webpage to identify key elements like text blocks, images, CTAs, and sections.
• The AI then organizes the scraped content into corresponding Mutiny blocks.
• The output provides a close approximation of your webpage structure, which can then be refined in the editor.

Best Use: Kickstart page creation for new campaigns without manually building from scratch.

3. Account Priorities

Purpose: Highlight key business initiatives for each target account to guide personalized messaging.

How It Works:

• Mutiny pulls data from public filings (like SEC documents) or news sources.
• AI filters priorities relevant to your offerings based on account context.
• Provides sales and marketing teams with actionable insights tailored to each account.

Best Use: Leverage this feature to inform personalized messaging for high-value accounts.

4. LLM-Driven Content Generation

Purpose: Create dynamic, AI-generated copy that scales across target accounts.

How It Works:

• You input prompts that guide the AI on what kind of content to generate.
• The AI uses account-specific data (such as use-case, industry, and priorities) to create personalized messaging for each account.
• Mutiny supports prompt previews so you can refine outputs before applying them broadly.

Best Use: Generate personalized messaging at scale for ABM campaigns.

Best Practices for Using Mutiny AI

1. Provide Clear and Specific Context

The more context Mutiny has, the better the AI can personalize the experience. Upload sales notes, product information, and relevant documents into the AI context box.

2. Craft Specific and Clear Prompts

• Provide clear instructions for the AI to follow.
• Be explicit about tone, structure, and desired outcome.
• Example: Instead of "Rewrite this section," try "Rewrite this headline to emphasize cost savings for {{industry}} clients."

3. Incorporate Account-Specific Variables

• Always use dynamic variables like {{account_name}}, {{industry}}, or {{use_case}} to ensure personalized outputs.
• Example Prompt: "Rewrite this paragraph to highlight {{account_name}}'s focus on {{use_case}}."

4. Leverage AI Context for Deeper Personalization

• Upload relevant context documents (e.g., pitch decks, sales call notes) to guide the AI.
• The AI will use this context for more relevant and insightful outputs.

5. Use Iterative Testing for Refinement

• Start simple and refine.
• Use previews to gauge effectiveness.
• Update your prompts with additional instructions if the output isn’t precise.

6. Remember AI Generations Campaign-Specific

• AI context is applied at the campaign level.
• Update your context for each campaign to ensure the AI uses the most relevant data.

Technical Specifications

If you need to understand how Mutiny AI works under the hood, here are the key technical details:

AI Models and Infrastructure

• Language Models: Mutiny AI leverages state-of-the-art large language models (LLMs), including OpenAI's GPT-4 and Anthropic’s Claude for content generation.
• Web Scraping: When generating themes or base pages, Mutiny uses a proprietary web scraper to extract HTML data and identify brand elements (colors, fonts, layout structures).

How AI Processes Data

• Theme Extraction: AI analyzes website HTML and visual elements to capture brand colors, typography, and layout structure.
• Base Page Generation: Scrapes and interprets page content, mapping sections into Mutiny’s modular block system for a near-match template.
• Account Priorities: Utilizes public data sources like SEC filings and news aggregators (via services like Perplexity AI) to identify relevant account priorities and filter them for relevance.
• Content Personalization: Generates unique content using account data, custom prompts, and AI context files (PDFs, text files) provided by users.

Data Usage and Security

• Data Input: User-uploaded data is used strictly for generating personalized content and is not stored or used for training AI models.
• Security Compliance: Mutiny AI adheres to industry-standard data privacy and security protocols, ensuring sensitive customer information is protected.

Performance Considerations

• Mutiny AI is optimized for lists up to 500 accounts for fast performance. Larger lists may take longer to process but will still complete asynchronously.
• AI-driven personalization uses a credit-based system where applying changes across all accounts consumes one credit per account per element.

AI Context Guidelines

• Supports text and PDF file uploads.
• Ideal documents include pitch decks, product one-pagers, brand guidelines, or account-specific notes.
• Contextual data is campaign-specific, but global context functionality is on the roadmap.

Final Thoughts

Mutiny AI empowers you to scale personalization efforts with precision and ease. By understanding how to leverage features like theme extraction, base page generation, account priorities, and LLM-driven content, you can create highly customized experiences that drive meaningful engagement with target accounts.

Need Help?

If you have questions or need help, the Mutiny Support team is here for you!  You can submit a support ticket at the bottom of this page or reach us at support@mutinyhq.com.