OpenText Core Digital Asset Management - Adobe Analytics Integration and Automation

Common Integration Use Cases Between OpenText Core Digital Asset Management and Adobe Analytics

1. Measure asset performance by campaign and channel

Data flow: OpenText Core Digital Asset Management to Adobe Analytics

Publish approved images, videos, and rich media from OpenText Core Digital Asset Management into campaigns and track how each asset performs in Adobe Analytics. Marketing teams can compare engagement, conversions, and revenue contribution by asset version, format, audience segment, and channel. This helps identify which creative assets drive the best business outcomes and which should be retired or refreshed.

2. Link asset metadata to web and campaign reporting

Data flow: Bi-directional

Sync asset metadata such as campaign name, product line, region, language, and usage rights from OpenText Core Digital Asset Management into Adobe Analytics reporting dimensions. This enables analysts to attribute traffic and conversion results to the correct asset groups without manual tagging. In return, performance metrics from Adobe Analytics can be pushed back to asset records to give content teams a clear view of asset effectiveness.

3. Optimize creative variants using performance insights

Data flow: Adobe Analytics to OpenText Core Digital Asset Management

Use Adobe Analytics data to identify which creative variants deliver the highest click-through, engagement, or conversion rates. Feed those insights back into OpenText Core Digital Asset Management so content managers can prioritize the best-performing versions, retire underperforming assets, and guide future creative production. This supports faster iteration and better use of design resources.

4. Govern asset usage based on audience and region performance

Data flow: Adobe Analytics to OpenText Core Digital Asset Management

Analyze performance by geography, device type, or audience segment in Adobe Analytics and use the results to inform asset governance in OpenText Core Digital Asset Management. For example, a video may perform well in one region but underperform in another due to language or format differences. Teams can then update asset recommendations, usage notes, or regional variants to improve relevance and compliance.

5. Improve campaign asset selection before launch

Data flow: Bi-directional

Before a campaign goes live, planners can review historical Adobe Analytics performance data alongside approved assets in OpenText Core Digital Asset Management to choose the most effective creative. After launch, the same integration can feed live performance back into the DAM to support mid-campaign optimization. This creates a closed loop between planning, execution, and measurement.

6. Track asset-level ROI for paid media and email programs

Data flow: OpenText Core Digital Asset Management to Adobe Analytics

Associate each approved asset with paid media, email, or landing page deployments and track downstream ROI in Adobe Analytics. Business teams can calculate which asset types contribute most to lead generation, sales, or subscription growth. This is especially useful for organizations managing large volumes of creative across multiple channels and markets.

7. Support content lifecycle decisions with usage analytics

Data flow: Adobe Analytics to OpenText Core Digital Asset Management

Use Adobe Analytics to identify assets with declining engagement, low conversion impact, or high bounce association and surface those insights in OpenText Core Digital Asset Management. Content owners can then decide whether to archive, update, localize, or replace assets based on actual usage data rather than assumptions. This improves content quality and reduces storage of outdated materials.

8. Enable cross-team reporting for marketing, creative, and analytics teams

Data flow: Bi-directional

Integrate OpenText Core Digital Asset Management and Adobe Analytics to create shared reporting views for creative, marketing, and analytics teams. Creative teams can see how their assets perform in market, while analysts can trace results back to approved source assets and versions. This reduces manual reconciliation, improves accountability, and speeds up decision-making across the content lifecycle.