OpenText Core Experience Insights - MediaViz AI Integration and Automation

Common Integration Use Cases Between OpenText Core Experience Insights and MediaViz AI

OpenText Core Experience Insights helps organizations measure how users interact with content and applications, while MediaViz AI is typically used to analyze media assets such as images, video, and rich visual content using AI-driven classification, tagging, and search capabilities. Together, they can create a closed-loop workflow that connects media intelligence with real usage data, helping teams improve content discoverability, engagement, and operational performance.

1. Measure engagement with AI-tagged media libraries

Data flow: MediaViz AI - OpenText Core Experience Insights

MediaViz AI can classify and tag images and video assets, then OpenText Core Experience Insights can track how users search, open, share, and reuse those assets across portals or digital workplaces. This helps content teams identify which tags, categories, and media types drive the most engagement and which assets are underused.

• Improves media library taxonomy based on real user behavior
• Helps content teams prioritize high-value assets
• Reduces time spent searching for relevant media

2. Optimize digital workplace adoption for media-rich content portals

Data flow: OpenText Core Experience Insights - MediaViz AI

OpenText Core Experience Insights can reveal where users struggle in media portals, such as low search success, high abandonment, or poor content reuse. Those insights can be fed into MediaViz AI to improve auto-tagging rules, metadata enrichment, and visual search relevance for the most problematic content areas.

• Improves portal usability and content findability
• Supports continuous improvement of media search experiences
• Helps digital workplace teams reduce support tickets

3. Identify high-performing visual content for marketing and communications

Data flow: Bi-directional

MediaViz AI can analyze visual assets and classify them by theme, subject, or campaign, while OpenText Core Experience Insights measures which assets generate the most clicks, views, shares, or downstream actions. Marketing teams can use this combined view to determine which visual styles, topics, or formats perform best across channels.

• Supports evidence-based content strategy
• Improves campaign asset selection and reuse
• Helps teams retire low-performing media faster

4. Improve compliance and governance for regulated media repositories

Data flow: MediaViz AI - OpenText Core Experience Insights

MediaViz AI can detect and classify sensitive or regulated visual content, such as logos, product labels, people, or restricted imagery. OpenText Core Experience Insights can then monitor how often users access, download, or share those assets, helping compliance teams spot risky usage patterns and enforce governance policies.

• Strengthens oversight of sensitive media assets
• Supports audit readiness and policy enforcement
• Helps reduce accidental misuse of restricted content

5. Prioritize content enrichment based on actual user behavior

Data flow: OpenText Core Experience Insights - MediaViz AI

OpenText Core Experience Insights can identify frequently searched but poorly discovered media assets, as well as content with high bounce rates or low engagement. That usage data can be sent to MediaViz AI to trigger enrichment actions such as improved tagging, object detection, or metadata completion for the most important assets.

• Focuses enrichment effort on content with the highest business impact
• Improves search precision and content reuse
• Reduces manual metadata work for content operations teams

6. Support customer experience teams with visual content performance analytics

Data flow: Bi-directional

Customer experience teams can use MediaViz AI to organize and classify visual content used in self-service portals, knowledge bases, or product support materials. OpenText Core Experience Insights can then measure how customers interact with those assets, showing which visuals help resolve issues faster and which ones create confusion or drop-off.

• Improves self-service effectiveness
• Helps support teams choose clearer visual assets
• Reduces repeat contacts and escalations

7. Track adoption of AI-enhanced media search and recommendation features

Data flow: OpenText Core Experience Insights - MediaViz AI

When MediaViz AI powers visual search or content recommendations, OpenText Core Experience Insights can measure adoption, usage frequency, and user satisfaction with those features. Product and platform teams can use the data to refine recommendation logic, improve search relevance, and validate the business value of AI-enabled media capabilities.

• Measures ROI of AI search and recommendation features
• Helps product teams improve feature adoption
• Provides evidence for future AI investment decisions

8. Create a continuous improvement loop for enterprise content operations

Data flow: Bi-directional

MediaViz AI can enrich and organize media assets, while OpenText Core Experience Insights can continuously measure how those assets perform in real workflows. Together, they create a feedback loop where usage data informs better AI classification, and improved classification drives better user engagement and operational efficiency.

• Enables ongoing optimization of content operations
• Improves collaboration between content, analytics, and IT teams
• Supports scalable governance and experience management