Datazoom Advertising Tracking And Monetization
With real time bidding, big budget ad buys, quickly evolving user interests, erratic content schedule changes and a competitive content acquisition environment, content publishers focused on driving ROI of their service need real time access to flexible, granular, end to end data delivered to the data analysis and visualization tools they prefer.
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When the Datazoom DaaS Platform is used to capture data about ads in streaming media, broadcasters, OTT publishers, digital publishers, and audio publishers, the results have been proven to increase CPM and engagement
How Datazoom Can Help Companies Overcome Challenges in Optimizing Video Advertising ROI
Datazoom’s Data-as-a-Service (DaaS) platform can help companies with ad-supported business models overcome many of the challenges faced in optimizing ad ROI.
Ad Tolerance Levels
Determine optimal ad pod sizes and durations by analyzing user and revenue impact.
Monetization Transparency
Price and optimize available inventory based on how different elements contribute to revenue growth and ROI.
Content Performance
Balance content costs with revenue generated based on content and user characteristics, engagement and revenue.
Ad Engagement and Viewability
Optimize ad campaigns by understanding revenue based on user attention toward and engagement with ads and determining ad viewability.
Merchandizing Ad Sports
Integrate content and user data with the ad systems to drive ad spot value by facilitating advertiser targeting across premium and real time bidding campaigns.
Acquire Higher Value Cohorts
Allocate user acquisition marketing budgets toward user types based on revenue expectations.
Ad Error Management
Track and resolve ad errors promptly to identify and address issues causing lost revenue opportunities.
Inventory Forecasting
Predict ad inventory and revenue based on historical data to align strategies to meet revenue targets.
Quality of Experience (QoE) and Quality of Service (QoS)
Ensure a seamless, cost effective viewer experience with data correlated through the entire video delivery stack.
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With a fully-unified stack and precise analytics, anyone delivering ads within streaming media can take better control of their operations, inventory, and engagement using the Datazoom DaaS Platform.
Datazoom Facilitates Advertising Monetization
Fully Unified Stack
Datazoom’s standardized data collection spans the entire video delivery stack, correlating quality metrics, user behavior, and revenue-related data. By delivering a holistic view of content and user performance, Datazoom empowers publishers to harmonize their efforts and maximize revenue.
Precise Analytics
Datazoom empowers publishers to monetize their content with precision. By integrating content and user data with ad systems, publishers can optimize ad spot value in light of user engagement, characteristics, attention, and ad viewability for effective real-time bidding and premium campaign targeting.
Outsized Performance
Content, user engagement, and ad performance are interconnected. Datazoom allows you to forecast and price ad inventory based on historical data, track and resolve revenue impacting ad errors promptly and fine-tune your service for ROI and viewer satisfaction.
How It Works
Common Use Cases
There are many advertising tracking and monetization use cases to which Datazoom can be applied:
- Precise revenue tracking (video and display)
- Ad engagement analysis
- Inventory forecasting
- Maximize revenue opportunities
- Track KPIs by ad_id
- Track KPIs by advertiser or agency
- Intermediating 3P measurement SDKs
- Build targetable (addressable) audience cohorts
- Track marketing conversions
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There are many use cases within streaming media advertising where the Datazoom DaaS Platform can improve operational effectiveness and improve revenue.
Use Case Highlight: Tracking Ad Tolerance Levels
One way to use Datazoom for advertising tracking and monetization is to understand how ad tolerance impacts user engagement.
Ad Pod Size Tolerance
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Datapoints
Sum all unique ViewIDs (AdStarts / sumAdBreaks)
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Suggested Filters
title, referrerURL, playbackDurationContent, userID, user cohort, churn rate, device type, geolocation, time of day, adPosition, adPartner and adSystem
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Actions
Adjust ad count per pod based on engagement numbers
Ad Pod Duration Tolerance
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Datapoints
adBreakEnd/adBreakStart, adDuration
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Suggested Filters
title, referrerURL, playbackDurationContent, userID, user cohort, churn rate, device type, geolocation, time of day, adPosition, adPartner and adSystem
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Actions
Adjust ad duration per pod based on engagement numbers
