Test and Learn for optimised OOH Ad design
Simple machine-driven analysis and actionable insights for reviewing and improving OOH ad design. In seconds
better designed posters have a 40% higher likelihood of holding attention
CLEAR CHANNEL, 2023
71.7% of creatives agree that AI tools will help them to improve their work
THE IMPACT OF AI ON THE CREATIVE INDUSTRY,
ENGINE CREATIVE, 2023
A self service platform
- that uses machine learning models to analyse OOH creative
- and surface valuable data
- that can be matched against proven OOH advertising principles
- to present actionable insights
- in order to optimise the design of OOH creative
- and improve campaign effectiveness.
Within seconds and at low cost.
Super Optimal helps ensure your OOH ad design is format fit via a 5 stage process.
1
Machine-driven analysis across a minimum 20 attributes (for a typical ad)
2
Standardised assessment of the analytics data vs proven OOH design principles
3
Consolidation of output into 3 core metrics - Format Fit / Clarity / Attention
4
An overall compliance score
5
Guidance for optimisation of any underperforming elements
Super Optimal helps teams make informed design decisions that recognise OOH’s unique engagement characteristics.
Super Optimal validates out-of-home (OOH) advertising designs using a combination of machine learning and AI analysis.
The platform identifies and scrutinises key design components that make up an OOH ad and assesses the analysis data against evidence-based guidelines for OOH effectiveness.
Super Optimal delivers a standardised assessment across key design elements and provides actionable insights to promote optimisation of the OOH ad.
Pre-campaign you can use Super Optimal to test and review artwork and to optimise the design for OOH’s specific characteristics.
Post-campaign you can review the artwork, assess its effectiveness in OOH environments and use the lessons learnt to optimise for your next campaign.
Super Optimal won the coveted Innovation Award at the 2024 UK Dev Awards.
The judges commented: “A great example of machine learning applicability in a commercial environment. It was a very ambitious project and it was great to see these types of developments taking shape in the market.”
Get in touch
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