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Identity Resolution – The Brain of Customer Data Platform (CDP)
Wed, 23 April
At the heart of every Customer Data Platform (CDP) is Identity Resolution, the key to creating accurate, unified customer profiles. Organizations need to stitch together fragmented customer data—spanning multiple touchpoints, devices, and interactions—to power Customer 360 personas and drive personalized activations.
This session explores the evolution of Identity Resolution techniques—from rule-based methods to traditional machine learning, deep learning, and now Generative AI (LLMs). We’ll examine how each technique builds upon its predecessor, tackling challenges in data fragmentation, scalability, and precision. Through a real-world case study, attendees will learn how to frame a business problem as a machine learning problem and navigate common pitfalls in building identity resolution systems at scale.
Key Takeaways
- What is Identity Resolution? – Understanding its role in creating unified customer profiles.
- Powering Data Products with Identity Resolution – How accurate customer profiles fuel personalization and marketing automation.
- Identity Resolution Techniques – Comparing rules-based matching, machine learning, deep learning, and LLM-driven approaches.
- Key Challenges & Trade-offs – Exploring precision vs. recall, scalability, and performance considerations.
- Building for Scale & Continuous Improvement – Strategies for optimizing identity resolution for massive datasets.
- Generative AI in Identity Resolution – How LLMs can enhance customer data unification and inference.
Target Audience
- Data Scientists & ML Engineers – Professionals looking to develop AI-driven identity resolution models.
- Data Engineers – Experts working on scalable data pipelines and real-time customer data processing.
- Customer Data & Personalization Teams – Leaders interested in enhancing CDP capabilities through AI.
Identity Resolution is no longer just a data problem—it’s an AI problem. Join us to explore cutting-edge techniques for building intelligent, scalable, and continuously improving identity resolution systems.
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About the speaker
Upendra Singh
Architect – Machine Learning & Generative AI, Twilio
Upendra is an Architect at Twilio with deep expertise in Machine Learning and Generative AI. He works on deploying ML systems for batch and real-time processing, researching advanced ML algorithms, and enhancing performance through custom extensions to ML libraries. His areas of interest include entity resolution, unsupervised learning, deep learning, and Generative AI.
