The future of identity management

Data Axle’s panel of B2B & B2C experts unveils the strategies and tools that can empower you to manage your data and drive more precise, personalized, and impactful strategies.

Meet the panel:

Marc Sabatini, SVP Enterprise Solutions, Data Axle
Mark Dye, Co-Founder, B2B Tech Group
Jay Sivasailam, Chief Growth Officer, UCare

You can download Marc’s slides here.

Recap & key takeaways

1. Identity resolution is the foundation of marketing

Identity resolution—accurately linking individuals, households, and businesses across multiple data sources—is critical for both marketing effectiveness and customer insights. It enables personalization, precise targeting, and measurement across channels.

“When you can bring together all these different data points into one identity spine, suddenly you’re not just looking at transactions. You’re looking at behaviors, preferences, and even social factors that impact outcomes.”
(00:53-1:00)

Key actions:

• Consolidate first-party and third-party data into a central identity spine.
• Use AI and machine learning for probabilistic identification when exact matches are not possible.
• Integrate social and environmental determinants in healthcare applications for predictive insights.

2. AI amplifies insights but depends on data quality

AI and large language models can make complex queries human-friendly, letting marketers and healthcare professionals get actionable insights from massive datasets. However, the accuracy of these tools is only as good as the data they’re trained on.

“What’s exciting is you can ask a really human question: something like, ‘Which patients are most likely to benefit from this outreach?’ The AI translates that into a very complex query across millions of records. But it’s only useful if the underlying data is solid.”
(01:23–01:33)

Key actions:

• Prioritize high-quality, vetted data sources.
• Combine AI with first-party and verified third-party data for accurate predictions.
• Continuously monitor and refine datasets to maintain trustworthiness.

3. First-party data strategy: Start now

Brands should treat first-party data as a long-term investment. Building a truth set—understanding and vetting existing data—sets the foundation for future success in a cookieless and AI-driven world.

“You’ve gotta start by really understanding the data in your current systems… separate the quality from the not-so-good data. That’s how you create a truth set you can trust, and then everything else—AI, personalization, measurement—becomes possible.”
( 01:50–01:59)

Best practices:

• Audit all current systems and data sources.
• Remove low-quality data and focus on high-value sources.
• Ensure internal alignment on use cases, terminology, and compliance standards.

4. Preparing for a cookieless future

Even if third-party cookies persist, marketers must plan for a future where first-party and privacy-compliant data is the foundation of targeting and measurement.

“Whether cookies go away or not, you still have to understand the data behind those cookies. Too many brands got hooked on scale and forgot quality. Now is the time to re-center on what data you actually trust.”
(02:48–02:57)

Key actions:

• Build persistent, brand-owned IDs independent of cookies.
• Verify and validate third-party cookie data before use.
• Integrate multiple data sources to maintain measurement accuracy.

5. Differentiating your data strategy

Data Axle’s Audience360 solution differentiates by centralizing all first-party and third-party data to build a persistent enterprise identity spine. This enables privacy-compliant, ROI-driven marketing across multiple platforms.

“It’s about helping the brand stitch together all of that information, manage all those IDs, and then make sure it supports both privacy compliance and the marketing strategies that drive higher ROI. It’s not just about connecting the dots, it’s about making those dots valuable.”
(03:20–03:35)

Key actions:

• Centralize disparate data sources into a unified platform.
• Support multiple marketing point solutions while maintaining a single source of truth.
• Focus on both effectiveness and compliance in identity management.

Commonly asked questions: AI, identity resolution, and data strategy

Do we still need third-party cookies?

Planning for a cookieless future is essential, even if cookies remain. The accuracy of cookie-based data varies, so building first-party, verified identity data is critical.

How should companies prepare their first-party data strategy?

Start by auditing current data, building a truth set, removing low-quality data, and aligning on internal use cases and compliance standards. This sets the foundation for AI-driven insights and long-term marketing success.

How does AI impact identity resolution?

AI can make complex queries easy and predictive, but the results are only as good as the underlying data. High-quality, vetted data is essential for AI to deliver accurate, actionable insights.

How does Data Axle differentiate from other data providers?

Data Axle’s Audience solution centralizes first-party and third-party data into a persistent enterprise identity spine, enabling privacy-compliant marketing, accurate measurement, and integration across multiple point solutions.

What’s the role of probabilistic matching in healthcare?

Probabilistic models allow identification and prediction where exact data is unavailable, incorporating social and environmental determinants for better population and individual insights.