Personalisation has become a cornerstone of digital marketing and user experience, but the landscape is rapidly changing. With increasing privacy regulations, browser restrictions on third-party cookies, and growing consumer awareness about data collection, businesses face a critical question: can effective personalisation exist in a cookieless world?

The traditional approach to personalisation has heavily relied on cookies—small text files stored on users’ devices that track browsing behaviour and preferences. However, with Google Chrome planning to phase out third-party cookies, Apple’s Safari and Mozilla’s Firefox already blocking them by default, and regulations like GDPR and CCPA limiting data collection, businesses must adapt or risk losing their personalisation capabilities.

This article explores how businesses can maintain effective personalisation strategies without relying on traditional cookie-based approaches, examining alternative technologies, first-party data strategies, and contextual targeting methods that are proving successful in the emerging cookieless landscape.

Valuable Introduction for Businesses

For businesses, personalisation isn’t merely a marketing tactic—it’s a fundamental approach to customer engagement that directly impacts revenue. The demise of third-party cookies represents both a challenge and an opportunity to rethink personalisation strategies in ways that better respect user privacy while still delivering tailored experiences.

The stakes are significant. McKinsey shows that companies that excel at personalisation generate 40% more revenue than those that don’t. Even more telling, 71% of consumers expect personalised interactions, and 76% get frustrated when this doesn’t happen.

Businesses that proactively adapt to this new reality will gain competitive advantages through:

• Enhanced trust with consumers who increasingly value privacy
• Reduced dependency on third-party data sources
• More creative, contextual approaches to understanding user needs
• Greater resilience against future privacy regulation changes
• Improved first-party data collection and management capabilities

The transition requires investment in new technologies and strategies, but the alternative—continuing to rely on soon-to-be-obsolete cookie-based approaches—represents a far greater business risk.

Valuable Benefits for Industry

Moving beyond cookies can actually strengthen personalisation efforts across industries, providing several significant benefits:

Enhanced Data Quality

Cookie-based data collection has always suffered from accuracy issues—cookies can be deleted, blocked, or misattributed. Alternative approaches that focus on deterministic identification (like authenticated users) and first-party data provide more reliable information for personalisation.

Improved Customer Trust

Transparent data practices build trust. When businesses clearly communicate how they collect and use data—and give customers control over their information—they create stronger relationships that can translate into greater willingness to share data voluntarily.

Cross-Channel Consistency

Cookie-based approaches have always struggled with cross-device tracking. Modern identity solutions that rely on deterministic matching (like logged-in users across devices) can create more consistent experiences across touchpoints.

Regulatory Compliance

Cookie-free personalisation approaches that prioritise privacy by design are more likely to remain compliant with evolving regulations worldwide, reducing legal risks and compliance costs.

These benefits aren’t merely theoretical. According to McKinsey, companies that successfully implement privacy-conscious personalisation strategies are seeing revenue increases of 10-15% and marketing efficiency improvements of 10-30%.

Actionable Perspective for Industry

To successfully implement personalisation without cookies, businesses across industries need to adopt new technical approaches and strategic mindsets:

First-Party Data Strategy

The foundation of cookieless personalisation is a robust first-party data strategy. This involves:

1. Value Exchange: Clearly articulate the benefits users receive in exchange for sharing their data
2. Progressive Profiling: Gradually collect data as users engage more deeply with your brand
3. Data Unification: Connect data across touchpoints to create unified customer profiles
4. Preference Management: Give users control over how their data is used

Contextual Intelligence

Rather than relying on historical tracking, contextual approaches focus on the current user context:

• Page content and semantics
• Search queries and site navigation patterns
• Time of day, season, and current events
• Device type and technical capabilities

For example, a travel website might personalise offers based on current search parameters and seasonal trends rather than past browsing history tracked through cookies.

Server-Side Processing

Moving data processing from client-side (browser) to server-side environments allows businesses to maintain personalisation capabilities while reducing reliance on browser storage mechanisms like cookies:

This approach is particularly valuable for Jasmine Web Directory and other information-rich platforms that need to deliver personalised results without excessive client-side tracking.

Federated Learning

This privacy-preserving machine learning approach allows algorithms to learn from user data without that data ever leaving the device. Google’s Privacy Sandbox initiatives include federated learning methods that aim to enable interest-based advertising without third-party cookies.

These approaches aren’t mutually exclusive—the most effective cookieless personalisation strategies typically combine multiple methods based on specific business needs and user expectations.

Practical Analysis for Market

Different market segments face unique challenges and opportunities in implementing cookieless personalisation. Here’s how various sectors are adapting:

Market analysis reveals that companies are increasingly exploring hybrid approaches. For instance, research on personalised learning environments shows that combining algorithmic recommendations with human expertise produces better outcomes than either approach alone.

Market leaders are also exploring partnerships with specialised data providers and technology platforms that can enhance personalisation capabilities without relying on cookies. For example, contextual intelligence providers can analyse page content in real-time to determine user intent without tracking individual users across sites.

Actionable Case Study for Operations

The operational implementation required significant cross-functional collaboration:

• Technology Team: Developed server-side personalisation infrastructure and API-based data exchange
• Marketing: Redesigned customer journeys to incorporate explicit data collection points
• Legal/Compliance: Ensured all approaches met regulatory requirements
• Customer Service: Trained to explain the value exchange of personalisation to customers

A similar approach could benefit businesses across sectors, including enterprise software providers who need to balance personalised user interfaces with privacy considerations.

The case study demonstrates that with thoughtful implementation, cookieless personalisation can actually outperform traditional approaches by building stronger trust relationships with customers.

Strategic Facts for Industry

To develop effective cookieless personalisation strategies, businesses need to understand the current landscape and emerging trends:

The Current State of Cookie Deprecation

• Chrome (with ~65% market share) is phasing out third-party cookies, with complete removal expected by 2025
• Safari and Firefox have already blocked third-party cookies by default
• Mobile app environments never relied on cookies and instead use app-specific identifiers, which are also facing increasing privacy restrictions

Alternative Identification Approaches

Several technologies are emerging as potential alternatives to third-party cookies:

• Universal ID Solutions: Industry initiatives like Unified ID 2.0 that use hashed email addresses
• Data Clean Rooms: Secure environments where first-party data can be matched without direct sharing
• Browser APIs: New privacy-preserving APIs like Google’s Topics API that categorise users’ interests
• Probabilistic Matching: Statistical approaches that connect user touchpoints without persistent identifiers

Regulatory Considerations

Privacy regulations continue to evolve globally, with implications for personalisation:

• GDPR in Europe requires explicit consent for personal data processing
• CCPA/CPRA in California establishes consumer rights to opt out of data sharing
• Many other jurisdictions are implementing similar regulations

The trend is clear: regulations increasingly favour transparent, consent-based approaches to data collection and personalisation.

Consumer Attitudes

Understanding changing consumer perspectives is crucial:

• 71% of consumers expect personalisation, according to McKinsey
• 76% get frustrated when this doesn’t happen
• However, 87% are concerned about how their data is collected and used
• The key insight: consumers want personalisation but with transparency and control

This apparent contradiction represents the central challenge and opportunity of cookieless personalisation—delivering tailored experiences while respecting privacy preferences.

Effectiveness Comparison

Early evidence suggests that well-implemented cookieless approaches can match or exceed cookie-based personalisation:

• Contextual targeting is showing 85-95% of the effectiveness of behavioural targeting in many scenarios
• First-party data strategies often deliver higher ROI due to increased data quality and consumer trust
• Hybrid approaches that combine multiple signals typically outperform single-method approaches

Businesses that view cookie deprecation as an opportunity to improve their personalisation strategies—rather than merely a technical challenge to overcome—are seeing the strongest results.

Strategic Conclusion

The evidence is clear: personalisation can not only survive but thrive in a cookieless world. The transition requires investment, strategic thinking, and technological adaptation, but the potential rewards extend beyond merely maintaining the status quo.

Successful cookieless personalisation strategies share several key characteristics:

1. Privacy by Design: Building personalisation systems with privacy considerations integrated from the beginning
2. Value Exchange: Creating clear benefits for users who share their data
3. Technical Flexibility: Implementing solutions that can adapt to changing regulations and browser policies
4. Data Minimisation: Collecting only what’s necessary for the intended personalisation use case
5. Transparency: Clearly communicating how data is used for personalisation

As online platforms evolve, businesses must continually adapt their personalisation approaches. Those that embrace this change as an opportunity to build stronger, more transparent relationships with their customers will gain competitive advantages.

This shift represents a fundamental evolution in how businesses approach personalisation, moving from implicit tracking to explicit value exchange. It’s a change that aligns business interests with consumer preferences for privacy and control.

For organisations looking to navigate this transition, resources like personalised learning plans can provide frameworks for developing the necessary skills and knowledge within teams.

The most successful businesses will be those that view cookieless personalisation not as a technical challenge but as a strategic opportunity to differentiate through more thoughtful, transparent, and effective customer experiences.

By embracing these principles, businesses can deliver personalisation that respects privacy, builds trust, and drives results—proving definitively that personalisation can not only work without cookies but potentially work better than before.