Personalization at scale takes data - and a lot of it. In this episode we explore types of data that can can be “home grown” to help create ever more powerful and personalized experiences. In particular we dive into the concepts of synthetic and augmented data and their implications for technology and human experience.

Resources

AWS’ Guide To Data Augmentation - https://aws.amazon.com/what-is/data-augmentation/

Synthetic Data Generation using LLM: Crash Course for Beginners - https://youtu.be/hMjtdECXlYo?si=AHLaad4fj13VlG2N

Synthetic Data and the Future of AI - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4722162

Personalization Done Right (Spotify Case Study) - https://hbr.org/2024/11/personalization-done-right

Takeaways

Synthetic data mimics statistical properties of real data.

Augmented data enriches existing data sets for better insights.

Context is crucial when utilizing data for decision-making.

Collaboration with data scientists enhances data utilization.

Synthetic data allows for scaling and running simulations.

Augmented data can personalize experiences across various industries.

Data limitations can hinder effective personalization efforts.

Elasticity testing can benefit from larger synthetic data sets.

Understanding different data types is essential for professionals.

The implications of data types extend to healthcare and user experience.

Chapters

00:00 - Introduction to Synthetic and Augmented Data

03:18 - Understanding Augmented Data

06:35 - Exploring Synthetic Data

09:18 - Applications of Augmented Data

12:08 - The Intersection of Data and Personalization

15:15 - Conclusion and Future Implications