Imagine’s ADS ad decision service is used by cable, satellite and telco providers to increase monetization by providing targeted opportunities to advertisers and enhancing customer engagement. The service considers criteria such as the current content being viewed, user preferences, customer data and business rules for multiscreen to determine which advertisement is to be inserted into a program (entertainment content).
ADS is ideally suited for two use cases:
- Ad decisions for ‘linear simulcast OTT streams’ for Imagine’s OTT Monetization solution, ingesting ad pools from scheduling systems such as Imagine’s Novar, Eclipse and Broadcast Master systems.
- Ad decisions for Imagine’s Linear Monetization solution, providing regional targeting and higher revenue for programmers’ primary distribution.
Incorporating spot optimization information from the campaign management system and key data from delivery components, ADS provides a single point of entry and data collection across the dynamic ad insertion workflow — enabling a cohesive ecosystem for sales, execution, and analysis.
- Monetize live and on-demand multiscreen video with relevant advertising products
- Integrate service with your current linear TV, VOD, and online video advertising systems
- Ensure compatibility with open, scalable and standards-based design
- Access integrated verification reporting to reconcile delivery to campaign
- Static ADS – Simple ADS that doesn’t require campaign manager to make ad decision
- CSV-based schedule files for linear, cDVR and VOD
- Schedule files are similar to CCMS (supports personalized ad decision)
- Default campaigns can be used in schedule files for generalized ad decision
- Same schedule file is used for multiple time zones
- Supports add/delete/edit of schedule files
- Focus on time-based ad decision (allows signal-based for demos or simple use cases)
- Support of simple ad pool rotation
- Decision making for alternate content for blackout
- Analytics generation for billing
- SCTE-130 and VAST interfaces
- Clustering to support High Availability and Scaling
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