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Graham McNicoll is a highly accomplished product leader, widely recognized for his pivotal role as the former Head of Product for The New York Times Cooking. During his tenure, he was instrumental in transforming NYT Cooking into a leading digital subscription service and a beloved platform for millions of users, significantly contributing to its growth and user engagement. His expertise encompasses digital product strategy, subscription models, user experience (UX) design, mobile app development, and leading cross-functional teams to build innovative and user-centric products. Graham is known for his deep understanding of how to blend content, community, and technology to create compelling digital experiences, particularly within the media and lifestyle sectors. He is passionate about building products that solve real user problems and drive business impact.
Graham McNicoll's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Led the product strategy and execution that significantly grew NYT Cooking's subscriber base and revenue, establishing it as a major success story in digital media subscriptions and a benchmark for food-related digital products.
Under his product leadership, NYT Cooking received numerous accolades, including multiple Webby Awards, for its exceptional design, user experience, and innovative features in the Food & Drink category.
Championed the development of key features such as personalized recipe recommendations, user recipe boxes, and community engagement tools that greatly enhanced the value and stickiness of the NYT Cooking platform.
Recognized as a thought leader in product management, often speaking at industry conferences and sharing insights on building successful digital products, particularly in the media and subscription space.
Carnegie Mellon University - Year 1996
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GrowthBook is an open-source feature flagging and A/B testing platform designed for modern data stacks. It enables companies to deploy code more confidently, iterate faster on product features, and make data-driven decisions by running experiments and analyzing their impact using their existing data warehouse and BI tools. It aims to democratize experimentation and feature management for businesses of all sizes.
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