Data-driven Decision-making for Product Managers

This book is an essential guide for product managers seeking to harness the power of data to drive their product decisions. It is a detailed resource for developing and maintaining data literacy, a core skill for product managers.

Through a structured approach supported by practical insights and illustrative examples, readers will learn to prioritize decisions based on quantitative data rather than intuition, understand core data concepts, and analyze and leverage data effectively.

Product managers will discover how data can transform decision-making processes, enabling evidence-based selection, prioritization, and resource allocation for product features. By using customer feedback, user behavior data, market research, and performance metrics, product managers can foster a culture that leverages data to create successful products.

This introductory primer and reference guide is indispensable for product managers aiming to integrate data-driven methodologies into their practice, ensuring their decisions are informed, strategic, and impactful.

Equips product managers with essential data literacy skills to make informed decisions Provides practical methodologies to improve product feature selection and resource allocation Illustrates effective data-driven decision-making with real-world case studies

Auteur

Gabriel Steinhardt is Blackblot's founder and an international technology product management expert, author, lecturer, and developer of practical tools and methodologies that increase product managers' productivity.

A marketing and information systems MBA with over two decades of experience in product management with technology products, Gabriel has assumed diverse leadership roles with major corporations and start-ups in marketing, product management, and technical undertakings.

Gabriel is the developer of the Blackblot Product Manager's Toolkit® (PMTK) product management methodology, a globally adopted best practice.

Contenu

1. The Data Age.- 2. Data-Driven Decision-Making (DDDM).- 3. Data Information Knowledge.- 4. The DDDM Process.- 5. Peers and Environment.