Streaming platforms and broadcasters lose millions in unattributed viewership revenue every year – not because audiences are not watching, but because content metadata does not match cleanly across distribution platforms, catalogues, and rights systems.
When an episode fails to map correctly across distribution platforms, those viewing minutes disappear - they do not count toward audience measurement or support monetisation.
Series with multiple seasons, formats, international variants, and distribution deals create metadata mismatches that compound across thousands of titles and device paths.
IP and rights teams negotiate studio deals without accurate viewership evidence - because the data exists but is buried in attribution failures across platforms.
Research and operations teams spend significant time manually reconciling viewership data across platforms, devices, and content catalogue versions.
ContentIQ connects to your content catalogue and distribution platform data on Databricks, runs advanced matching models across series and episode hierarchies, and recovers unmapped viewing minutes.
ContentIQ connects to your content catalogue, distribution platform data, and rights system on Databricks - across all platforms and devices.
Matching models run across series, season, and episode hierarchies to identify and resolve mapping gaps at the most granular level.
Recovered viewing minutes are attributed to the correct content asset and enriched with device, platform, and viewing behaviour context.
Output feeds into audience measurement dashboards, rights reporting, and contract negotiation workflows - giving IP teams verified evidence.
Continuous monitoring maintains match quality as new content is added, new platforms are launched, and catalogue structures evolve.
Attributed viewership data flows into ad inventory, licensing valuation, and content strategy workflows - connecting metadata quality to revenue outcomes.
ContentIQ applies advanced matching models to align content metadata across series hierarchies and episode-level granularity – eliminating unmapped viewer sessions and recovering the viewership data that supports ad revenue and rights negotiations.
Matching models that resolve content identity across complex taxonomies – series hierarchies, episode variants, international formats, and multi-platform distribution paths.
Matching at the most granular level available – episode-specific attribution across all platforms, not series-level approximations.
Recovery of viewer sessions previously lost to metadata gaps – with device, platform, and timing context restored.
Unified content intelligence across CTV, mobile, web, and linear feeds – all normalised into a single attributable view.
Viewership data enriched for rights negotiation – episode-level attribution that supports licensing conversations with evidence, not estimates.
Built on Delta Lake and Unity Catalogue – enterprise data governance for content and viewership data at scale.
When unmapped viewing minutes are recovered and attributed, the downstream benefits extend across ad revenue, rights negotiations, audience measurement credibility, and operational efficiency.
Recovered Viewership Revenue
Unmapped viewing minutes are attributed and counted - directly supporting ad inventory valuation and content licensing negotiations.
Stronger Rights Negotiations
IP and rights teams negotiate with verified viewership evidence instead of estimates - improving licensing terms and deal outcomes.
More Accurate Audience Measurement
Audience measurement improves as previously unmapped viewing is attributed - improving advertiser confidence and premium inventory pricing.
Reduced Manual Reconciliation
Data quality improvements reduce the manual reconciliation work that research and operations teams spend time on every reporting cycle.
Improve audience measurement accuracy by eliminating the attribution gaps that undercount viewership across platforms and devices.
Negotiate content deals with verified viewership evidence - episode-level data that supports licensing terms and protects IP value.
Maintain metadata quality across a growing catalogue, across new platforms, and across evolving distribution arrangements.
Understand which content is actually performing across all distribution paths - and use that data to guide acquisition and renewal decisions.
ContentIQ is built on Databricks Delta Lake and Unity Catalogue and integrates with content catalogue, rights management, and audience measurement systems to connect to your existing content infrastructure.
Explore insights on content metadata management, viewership attribution, and streaming analytics for media and broadcast companies.
ContentIQ handles episodic series, feature films, sports, news, and live content. It is designed for complex taxonomies with multiple seasons, formats, and distribution variants.
No. It works with your existing catalogue format and maps to distribution platform schemas without requiring source system changes.
Accurate viewership attribution means ad inventory tied to specific content has verified audience data – which supports premium pricing and direct sales conversations with advertisers.
Yes. ContentIQ is designed to work alongside third-party measurement data and can incorporate external attribution signals into the matching models.
ContentIQ’s matching models are trained to resolve identity across format variants – different aspect ratios, edit lengths, dubbed versions, and international localisation – without losing attribution accuracy.
