← Attention Tech
Predictive omnichannel media-quality score (AU)
Adelaide
🇺🇸Adelaide developed the AU metric, a 0-to-100 score representing the probability of a media opportunity to generate Attention and impact. The solution measures media quality across channels and supports planning, buying and optimisation decisions.
How it works
- 1Collection of media-quality signals
- 2Analysis of factors such as position, clutter, coverage and time in view
- 3Incorporation of eye-tracking data and campaign outcomes
- 4Application of machine-learning models
- 5AU Score generation
- 6Use of the Score in planning, buying and evaluation
Main applications
Media planning
Placement-quality assessment
Cross-channel comparison
Programmatic optimisation
Quality-based Private Marketplaces
Custom bidding
Analysis of the link between media quality and outcomes
Inventory benchmarking
Advantages
- Simple metric on a 0-to-100 scale
- Omnichannel approach
- Specific orientation to media quality
- Fits into planning and buying processes
- Uses outcome data to improve the Score
- Ecosystem of programmatic integrations
Limitations to consider
- AU is a modelled, predictive metric — not direct gaze observation
- Teams need to understand the Score's methodology
- Operational use depends on integrations with DSPs, SSPs or platforms
- Access to certain levels of detail depends on the commercial model
- Focus on media quality, not creative evaluation
Ideal profile
Trading desks, agencies and advertisers that buy programmatically and want a single cross-media metric.
