Cultural AI Media Targeting
Qloo’s cross domain intelligence provides an unprecedented strategic view of your audience’s taste in all areas. This can be deployed to better identify a range of targeting parameters. Qloo studies your audience (or a subset of it) and searches for naturally occurring clusters of taste, hobbies, interests and passion points to identify the things that are exceptionally correlated to them.
These insights uncover additional taste-based targeting options that may not be possible to identify using traditional media targeting approaches. We provide a strategic view of consumer taste that is agnostic to platform and distribution channel and enables more focused and personalized approach to reaching customers based on their preferences in any category of culture.
- Hyper-targeting based on over 150 million factors, resulting in highly granular, actionable, accurate insights about audience taste.
- No PII is required. All predictions are made based on fully anonymized user data
- Qloo’s personalization service is fully GDPR compliant.
How it works
- Qloo’s AI can accept audience definitions based on any combination of cultural entities or factors.
- Results are returned via the API within milliseconds.
- Qloo’s API is able to integrate with all major or proprietary CRM systems, and become an integral part of a broader data pipeline and intelligence. Qloo can also help gap-fill and generate inferences in categories where companies do not have data (overcoming cold start).
Luxury european automaker wanted better media targeting insightsCultural AI solution
A leading luxury Auto brand was struggling to convert sales for a premium sedan. European automaker wanted higher efficacy media buys rather than targeting traditional parameters.
Their media agency had simply advised them to “target luxury”. Based on this approach they deemed their campaigns to be somewhat successful based on engagement, however this engagement was not translating to sales.Cultural AI solution
Client programmatically looped in inputs through Qloo API about known audience segment characteristics and then pulled highly relevant granular correlations, and focused on high relevant but obscure correlations.Results
Focusing on obscure correlation revealed buyable segments that were much less crowded buys, and much higher ROI per dollar spent on programmatic buys. Further to this, they briefed Qloo that the media opportunities they were targeting were also being pursued by their closest competitors and they tasked Qloo with identifying new strategic opportunities to target based on strong empirical evidence.
Using Qloo’s API, they ran data using cultural factors as proxies to define the existing owners of the car model, blended with their known target audience demographics. One example of a buyable segment the data uncovered was an extraordinary correlation to the pursuit of Triathlon. This insight provides the brand with a new, additional metric for taste based niche marketing that was previously unknown to them and led to programmatic media buys with conversion efficacy more than 76% higher than the status quo buys, leading to tremendous cost savings and stronger conversion.
Helping with alternative media for smarter buys
Swarovski wanted to identify highly correlated influencers across different domains of culture and entertainment as well as emerging media properties such as podcasts, apps and games that had high relevance to their target audience. This was part of a broad effort to find alternative buyable media and partnerships to increase the marketing efficacy and relevance to the consumer.