With Google finally phasing out third-party cookies, marketers are scrambling to develop alternative targeting and measurement approaches. This represents one of the most significant technical changes affecting digital marketing in years.
As the digital marketing landscape evolves in 2025, several alternative targeting methods and strategies are gaining traction in the post-cookie era:
Alternative Targeting Methods
- Contextual Advertising: This approach places ads based on the content or context of a webpage rather than user behavior. For example, a sportswear brand might place ads on fitness blogs or workout videos.
- Universal IDs: Alternative identifiers like The Trade Desk’s UID2 and ID5’s Universal ID are becoming crucial for maintaining a comprehensive consumer view across channels.
- Identity Graphs: Companies are adopting a “graph-of-graph” strategy, combining their own first-party data with licensed identity graphs to enhance personalization.
- AI-Powered Personalization: Leveraging artificial intelligence to analyse customer data and predict behaviours enables hyper-personalized content delivery without relying on cookies.
Building Valuable First-Party Data Collection Systems
- Customer Data Platforms (CDPs): Implement robust CDPs to centralize and analyse data from various touchpoints.
- Progressive Profiling: Gradually collect more information from users over time by offering clear value propositions.
- Zero-Party Data Collection: Encourage users to voluntarily share information through surveys, quizzes, and preference centres.
- First-Party Data Sources: Utilize website interactions, purchase history, email subscriptions, and customer feedback to build comprehensive profiles.
Privacy-Compliant Personalization Techniques
- Contextual Targeting: Align publisher content with relevant ads, ensuring delivery based on content rather than individual identifiers.
- Privacy-Compliant Personalization: Leverage real-time insights, advanced analytics, and machine learning to create tailored user experiences without infringing on privacy.
- Cookie less Personalization: Use machine learning algorithms to suggest behavioural recommendations based on observed activity on a given web page (first-party data).
- Transparent Data Practices: Build trust by clearly communicating how data is collected, stored, and used.
How Leading Brands are Maintaining Performance
- Amnet: Achieved a 3X impression lift across cookie-blocked browsers using privacy-first cookieless targeting.
- Martens: Saw a 9X increase in click-through rate (CTR) by adopting cookie less strategies.
- OMD: Drove 2X more cost-efficient engagement for a luxury auto brand using alternative targeting methods.
- Rush Street Interactive: Gained a 20% lower cost-per-click (CPC) through cookieless advertising approaches.
- Pepsico Mexican Foods: Experienced a 24% lift in video completion rate (VCR) by implementing privacy-compliant targeting strategies.
These examples demonstrate that brands can maintain and even improve performance by adapting to the cookieless era through innovative targeting methods, robust first-party data strategies, and privacy-compliant personalization techniques.
