The speaker discusses challenges in data usage across different industries, emphasizing the impact of legal and compliance restrictions. In manufacturing (e.g., General Electric), data science models often face rejection due to strict compliance regulations, preventing them from reaching production regardless of investment.
In financial services, personalization is crucial—customers expect tailored offers and experiences. However, strict privacy regulations require companies to anonymize data to avoid heavy penalties. The speaker advocates for a balanced approach, favoring zero-party (user-consented) and first-party data over third-party data to maintain trust and compliance while enabling personalization. By obtaining direct user consent, companies can offer personalized experiences without legal risks.
Interested in hearing more from our webinar, AI-Powered Personalization vs. Data Privacy: Can You Have Both? Find the full webinar here: https://snowplow.io/events/ai-powered-personalization-vs-data-privacy-can-you-have-both