Content AI 

Content Recommendation Overview

AI-Powered Content Recommendations enable you to deliver dynamic, personalized content experiences tailored to each lead based on artificial intelligence. By analyzing user behavior, industry trends, and account history, this feature enhances engagement by displaying relevant content that wasn't explicitly added to your board but is intelligently recommended from your content center.
It supports key use cases like resource centers and demand generation, ensuring visitors always see content that's most relevant to them.

Elevate Engagement: Unleashing the Power of AI-Driven Content Recommendations

The AI-powered recommendation engine transforms your boards into dynamic, personalized experiences by intelligently presenting content tailored to each lead.

• Dynamic Personalization
  Content is adapted in real time based on a combination of the lead’s behavior, account activity, and industry trends. This ensures that every visitor—whether a first-time viewer or a returning lead—sees the most relevant materials.
• Content Center Integration
  Recommended items can include assets from the Content Center that weren’t manually added to the board. This expands discovery without requiring extra setup, making each board smarter and more comprehensive.
• Smarter Journeys Through Interaction
  As leads engage with recommended content, the AI engine learns and improves future recommendations—enhancing the personalization loop over time.
• Versatile Display Options
  Recommendations can be presented in multiple formats, such as navigation arrows or floating content containers, and can be embedded within any content section. These options support a variety of use cases, from resource centers to demand generation hubs.
• Seamless Analytics Integration
  All interactions with recommended content—whether explicitly added to the board or sourced via AI—are tracked and attributed accurately. Performance data flows into analytics tools like Pulse, Report Center, and the Account Dashboard, giving you full visibility into impact and engagement.

Content Summaries: The Foundation for AI Recommendations

To deliver accurate and relevant recommendations, the AI engine relies on Summaries—concise descriptions that help determine the context and intent behind each content item.

Summaries are a prerequisite for any item to be eligible for AI-driven recommendations. Without a summary, the recommendation engine cannot assess the content's relevance or include it in personalized suggestions.

How Summaries Support Recommendations

• Automatic Creation: When a new item is added to the Content Center, a summary is automatically generated at the item level using AI to streamline the recommendation process. This automatic generation typically takes around 24 hours to complete.
• On-Demand Generation: If you don't want to wait for the automatic process, you can generate summaries "on demand" through the item settings.
• Eligibility Criteria: Only items with a generated summary can be marked as Available for Recommendation. This two-step process is crucial because the AI recommendation engine exclusively selects from items that have been explicitly marked as "Available for Recommendation." No matter how relevant an item might be, if it hasn't been given this designation, the recommendation engine will not include it in personalized suggestions. This gives you complete control over which content can be recommended while ensuring the AI engine only works with well-understood content.
• Manual Control: Users can manually edit, refine, or regenerate summaries to improve recommendation quality. If you update an item significantly, you may want to regenerate its summary to ensure recommendations remain accurate.
• Privacy Considerations: Summaries are not generated for private items, as these are not intended for broader recommendation.

*For bulk update of existing content items, please contact your CSM. 

How It Works

Recommendation Engine

The AI recommendation engine intelligently analyzes and recommends content by looking at various signals and patterns. The system takes into account what content has resonated with your leads, what's trending in their industry, and what's relevant to their organization as a whole. This comprehensive approach ensures that each lead receives a personalized content experience that's both engaging and relevant to their needs and interests.

When a lead lands on a board, the system automatically selects the most relevant content. If needed, the system has fallback mechanisms to ensure leads always see appropriate recommendations, even if they're new to your content.

The system also avoids repeatedly recommending content that leads have already engaged with extensively, ensuring a fresh content experience each time.

Content Section Settings

You can configure recommendations at several levels and combine settings for maximum flexibility:

Source Settings (What leads see when they first land on the board):

• Curated: Content comes only from items explicitly added to that section
• AI: Content can include items from the content center not explicitly added to the board

Note: Source AI is available only in Promoted Content and Single Item sections.

Journey Logic (What leads see as recommendations when viewing individual items):

• Curated: Recommendations are based on items selected within that section
• AI: Recommendations include items from outside the board/section from the content center

You can select any combination of Curated and AI options for both Source and Journey settings to customize your content delivery strategy.

Recommendation Navigation UI:

• Arrows: Navigate through recommendations with previous/next arrows. "Previous" shows items the lead has already viewed, while "Next" shows new recommendations based on your selected settings (Curated or AI).
• Bottom: Display 3 recommended items based on your selected settings (Curated or AI) as suggestions that appear at the bottom of the screen for what to view next.

Reports and Analytics 

All interactions with recommended content are tracked to provide valuable insights:

Key Metrics Tracked

• Views and Time Spent: Tracked at the board and item levels
• Attribution: Content items, whether manually added or recommended by AI, are attributed to the board where they are viewed. Even though recommended items originate from the Content Center, once they appear on a board as recommendations, all analytics for these items are fully attributed to that specific board. This ensures consistent reporting and accurate measurement of board performance regardless of content source.

Reporting and Dashboards

Data from recommended content will be reflected in the following:

• Pulse: Tracks visitor engagement and activity. Will show indication in 'item viewed' that it came as recommended
• Report Center: All content interaction data is aggregated for further analysis. Content Engagement Report will show the source of the content (curated or AI) and if this item is available for recommendation

Setting Up AI Recommendations

Prerequisites

Before you can use AI recommendations, three essential requirements must be met:

1. Organization-level activation: The AI feature must be enabled for your entire organization by an administrator. This global setting makes the AI functionality available across all boards.
2. Content summaries: Each content item needs a summary generated for it. These summaries are crucial as they help the AI understand your content and make accurate, relevant recommendations based on the content's substance. Once the AI feature is enabled at the organization level, any new item created will have a summary automatically generated for it by default.
3. "Available for recommendation" marking: Individual content items must be specifically marked as available for the recommendation engine to consider them. By default, all items are created with 'Available for recommendation' turned OFF, so you'll need to explicitly enable this for items you want included. This gives you control over exactly which content can appear in recommendations.

Configuration Steps

After meeting the prerequisites, you'll need to configure recommendations at three different levels in this hierarchical approach:

1. Item Level:

• • For any content item to be eligible for AI recommendations:
    • It must first have a summary generated
    • Then it must be marked as "Available for recommendation"
  • Only items that complete both steps will be included in the recommendation pool

2. Designer Level:

• • Within each board, you can configure AI settings for specific content sections
  • This is where you select Source and Journey settings (Curated vs. AI)
  • Different sections within the same board can have different AI recommendation strategies

3. Board Level:

• • Each individual board has its own AI toggle (ON/OFF)
  • By default, this toggle is ON, but you can turn if OFF if needed
  • This allows you to selectively implement AI recommendations on specific boards while keeping others traditional

This multi-level configuration approach gives you precise control over how AI recommendations work across your entire content ecosystem, from organization-wide settings down to individual content items.

Not Supported file types:

1. Images of all types - png, jpeg, etc.
2. Google drive files which are private and permissions protected by the company
3. Videos from private source - Wistia, Vimeo, Brightcove, Vidyard