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Updated 3 Days Ago
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Audigent uses first-party data to optimize media strategies without relying on cookies. By harnessing partnerships with major publishers and data curation, Audigent enhances programmatic advertising efficiency. Its tools enable advertisers to target accurately and navigate the changing digital privacy landscape effectively.
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Audigent's Website Claims...
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privacy-safe identity solution
Audigent claims that its Hadron IDβ’ offers a future-proof, privacy-safe identity solution, ensuring interoperability without cookies.
optimized data curation
Audigent claims that its SmartPMPβ’, ContextualPMPβ’, and CognitivePMP products optimize consumer-safe data with premium inventory at scale.
unique supply-demand alignment
Audigent claims that its platform aligns supply- and demand-side technologies uniquely, optimizing media performance for digital campaigns.
BlurbSTAR Case Study
Audigent & Havas & Proper Twelve Whiskey
Enhanced targeting improves brand engagement and market presence.
30%
Enhancement in ROI efficiency
45%
Increase in engagement rates
1.
Situation
Reaching Niche Audience Challenge
β
Need to reach niche audiences
β
Traditional ads inadequate for specific demographic
β
Aimed for targeted brand engagement
Proper Twelve Whiskey faced the challenge of connecting with a niche audience composed of whiskey enthusiasts and Conor McGregor fans while ensuring sufficient scale. Traditional mass-market strategies were ineffective due to the specific tastes and interests of this target demographic. This necessitated a highly targeted advertising approach to efficiently reach the intended audience while maximizing brand engagement and conversation.
2.
Task
Develop Robust Data Strategy
β
Utilize first-party data intelligently
β
Focus on contextual consumer content
β
Ensure strategy is effective and scalable
The task was to create a robust advertisement strategy that leverages precise data targeting capabilities. Audigent and Havas needed to utilize first-party data collected through trusted publisher partners. The objective was to develop a custom contextual approach that would allow Proper Twelve Whiskey to reach and engage with specific content consumers interested in whiskey and Conor McGregor content. This data-driven strategy needed to be effective, scalable, and maintain user engagement throughout the campaign.
3.
Action
Implement SmartPMPs Techniques Effectively
β
Implement SmartPMPβ’ for better targeting
β
Use first-party data from publishers
β
Align ads with engaging content
Audigent employed their SmartPMPβ’ technology to optimize the campaign through the use of exclusive first-party data from major publishers like Conde Nast and Menβs Journal. They collaborated with Havas to design a custom strategy that took full advantage of contextual targeting. By aligning advertising with engaging content that potential consumers were already interacting with, they maximized the relevance and effectiveness of ad placements, resulting in improved audience reach and engagement while maintaining campaign scalability.
4.
Result
Impressive Campaign Performance Results
β
Outperformed all other partner campaigns
β
Delivered precise audience targeting
β
Improved ROI and engagement metrics
The implementation of Audigent's SmartPMPs resulted in outperforming all other partners by delivering precise audience targeting and improved engagement metrics for Proper Twelve Whiskey. This strategic execution led to a higher return on investment for the ad spend by ensuring that advertising efforts reached the intended audience effectively. The enhancements not only elevated brand conversations but also strengthened the overall brand presence within the niche market, setting a new benchmark for future advertising ventures.
Keywords
AUDIGENT
SMARTPMP
FIRST-PARTY DATA
HAVAS
PROPER TWELVE WHISKEY
ADVERTISING STRATEGY
CONTEXTUAL TARGETING
NICHE AUDIENCE ENGAGEMENT
DATA-DRIVEN MARKETING
BRAND CONVERSATION
Audience Data & Enhancement Q & A
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1.
What types of audience data do you provide (behavioral, transactional, location-based, intent, psychographic, etc.)?
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2.
How do you collect and enrich audience data, and is it sourced from first-party, second-party, or third-party data?
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3.
Can your platform integrate with our existing MarTech stack (CDP, DMP, CRM, ad platforms, etc.)?
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4.
Do you offer real-time audience insights, and how frequently is your data refreshed?
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5.
How does your platform enhance first-party data and help with identity resolution?
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6.
Do you provide predictive analytics, AI modeling, or lookalike audience generation?
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7.
How does your data support media activation (programmatic, CTV, social, retail media, etc.)?
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8.
How do you measure audience quality and performance (uplift studies, match rates, incrementality testing, etc.)?
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9.
Can your platform provide closed-loop measurement to track how enriched audiences impact conversions and sales?
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10.
What is your pricing model (subscription, data usage-based, CPM-based, or custom enterprise pricing)?
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