#248 Effective Product Management for AI with Marily Nika, Gen AI Product Lead at Google Assistant
DataFramed
Measure the Metrics for Product Prosperity
Effective product management relies heavily on a well-defined set of metrics, primarily categorized under product health. Key indicators include user satisfaction metrics such as NPS and CSAT, which assess how users feel about their experience. Analyzing the acquisition funnel reveals user retention rates and engagement levels, illustrated by actions like sharing stories or making comments. High retention suggests product success, with 'stickiness' referring to the number of users returning daily. Additionally, monetization metrics evaluate revenue generation per user, considering options such as ads or in-app purchases, which contribute to understanding user lifetime value. Referral metrics gauge the effectiveness of user recommendations and incentives for new user acquisition. In the realm of AI, model-specific metrics, particularly accuracy, become crucial to monitor how well the product performs.
