Engagement on each piece of content — views, learners reached, and content metadata. Use when you need to know which content is actually working.
The Content Engagement Report breaks down engagement on each piece of content for the time range you specify. Use this when you're auditing content performance, deciding what to retire, or building a case for which content needs more investment.
For the strategic frame on which report fits which question, see Reporting: Which Report Should I Use?. For the mechanics of running reports, see Admin Reports in Continu.
When to Use This Report
Content audits. Identify content that's not getting views (dead weight in the library) and content that's getting high views without high engagement (titles that promise more than the content delivers).
Justifying content investment. When a stakeholder asks whether a content investment paid off, this report shows the engagement on the resulting content. Pair with feedback ratings for a fuller picture.
Identifying outdated content for refresh or retirement. Content that used to perform well and now doesn't is often a content-update opportunity. Trending views over time reveals which pieces are aging out.
Column Reference
Content ID — Unique ID for the content. Useful for API workflows or matching to other systems.
Content Title — Title of the content piece.
Content Type — Article, File, Video, Workshop, Track, SCORM, or Imported.
Content Tags — Tags applied to the content.
On Explore — YES/NO depending on Explore visibility settings.
Published — YES/NO depending on whether the content is live for learners.
Archived — YES/NO depending on whether the content has been archived.
Containing Track — YES/NO if the content is part of a Learning Track.
Plus view and engagement columns — total views, unique viewers, and other engagement metrics in the date range.
How to Use This Report Effectively
Look at views per audience, not raw views. A piece of content seen by 100 learners in an audience of 200 is performing differently than the same view count from an audience of 10,000. Always contextualize against the segmentation.
Filter by Content Type for cleaner comparisons. Articles, Videos, and Workshops have different baseline engagement patterns. Comparing across types can mislead.
Use tags to find content clusters worth analyzing together. A tag filter on "compliance" or "sales onboarding" gives you a focused view of program-specific content.
Pair with Content Completion for the full picture. Engagement (views) alone hides whether learners are actually finishing. Pair this report with Content Completion to distinguish "people looked at this" from "people learned this."
Configuration Pitfalls
Comparing Content Across Time Without Adjusting for Audience. A piece of content's engagement in 2024 vs 2025 isn't directly comparable if the audience size changed, the assignment cadence changed, or the segmentation changed.
Retiring Content Based on Low Views Without Checking Why. Low views can mean low quality, but it can also mean limited audience, poor surfacing on Explore, or no assignments pointing at it. Investigate before retiring.
Treating All Views Equally. Some content (deep training) deserves a few high-quality views; some content (reference docs) is supposed to be visited briefly and often. Set the baseline based on content type before evaluating.
Forgetting Archived Content Stops Accumulating. An archived content piece keeps historical view data but stops accumulating. Don't compare archived vs active content's views without accounting for that.
Where This Fits
You're here because you need engagement data on specific content. For per-learner engagement, see User Engagement Report. For completion data specifically, see Content Completion Report.
See Also
- Reporting: Which Report Should I Use? — the strategic anchor.
- Admin Reports in Continu — running and filtering reports.
- User Engagement Report — per-learner engagement.
- Content Completion Report — completion-focused view.
- View Content Ratings — pair with quality signal from ratings.
Filter to specific content types or tags for clean comparisons. Pair engagement (views) with completion data for the full picture. Investigate low views before retiring content.