Nitin emphasizes the critical role of first-party data in improving the accuracy and personalization of models. While third-party data is costly and often consists of stratified samples, collecting first-party data ensures direct relevance to end consumers. A continuous feedback loop is necessary to assess its value and refine recommendations. Leadership must recognize the trade-off between personalization and cost, as more customized data leads to better consumer insights and more precise models. The decision to invest in first-party data ultimately impacts the effectiveness of AI-driven recommendations.
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