by Sara Steffen
As a global media conglomerate housing over 37 distinct brands, Condé Nast faced the challenge of delivering targeted consumer experiences across their brands amidst fragmented data silos. To overcome this hurdle and remain competitive, they turned to Databricks — significantly accelerating time-to-insights and decision-making. Moreover, the ability to report consistently on a global scale improved data accuracy and operational efficiency. With Databricks, Condé Nast not only optimized its infrastructure to the tune of $6 million in cost savings, but also achieved greater agility in delivering personalized content experiences to a diverse audience, enhancing consumer engagement and loyalty.
As the media industry evolves, so do consumer expectations. Condé Nast — a powerhouse in the world of media and entertainment with global brands like Vogue, The New Yorker, and GQ — realized the importance of delivering tailored content and experiences to its audience. However, their existing data infrastructure was fragmented, hindering their ability to analyze data efficiently, make informed decisions, and provide personalized content at scale. To remain competitive and relevant in a dynamic media landscape, they needed a solution to centralize their data and accelerate their data-driven capabilities. Condé Nast recognized that centralizing data was the key to unlocking a new level of personalization and efficiency. "We struggled to find ways to break out of our data silos across the organization," said Nana Yaw Essuman, Senior director of data engineering at Condé Nast.
Condé Nast chose the Databricks Data + AI Platform to better execute their vision of providing a unified view of their consumers. "The ability to leverage the exact same data that has been collected through our data pipelines allows for more consistent reporting in a global fashion," said Essuman. The lakehouse architecture offered more than just the democratization of data. It has empowered their data team with a comprehensive suite of tools, including Unity Catalog and Databricks SQL, which enables them to securely govern data access and streamline analysis and decision-making processes across the organization, empowering their teams to move faster and smarter. With this newfound agility, Essuman's team is able to respond more quickly to ever-evolving market trends and deliver content experiences that resonate with their diverse global audience.
Since adopting the Databricks Data + AI Platform, Condé Nast has harnessed the full potential of their data for analytics and AI while reducing annual infrastructure costs by approximately $6 million. This not only bolstered their financial health but also empowered them to reallocate resources for crafting personalized consumer experiences globally. Essuman concluded, "Databricks helps us understand the customer from a single view so we can provide the most compelling consumer experience." With a unified data view and robust analytics and AI tools at their disposal, Condé Nast's data team can now easily create personalized content experiences that enhance consumer offerings, fostering higher engagement and loyalty.
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Condé Nast's data was scattered across silos spanning its more than 37 global brands, which made it difficult to analyze information efficiently, make timely decisions or deliver personalized content at scale. Senior director of data engineering Nana Yaw Essuman noted the team "struggled to find ways to break out of our data silos across the organization." This fragmentation limited the company's ability to remain competitive in a fast-changing media landscape.
The platform's lakehouse architecture lets Condé Nast's data team access the same data collected through its pipelines, enabling consistent global reporting instead of fragmented brand-by-brand views. Tools like Unity Catalog and Databricks SQL allow the team to securely govern data access while streamlining analysis and decision-making. As Essuman put it, "Databricks helps us understand the customer from a single view so we can provide the most compelling consumer experience."
Condé Nast reduced its annual infrastructure costs by approximately $6 million after moving to the Databricks Data + AI Platform. Beyond the direct savings, this reduction freed up resources that the company reallocated toward building personalized consumer experiences across its brands.
With a single, consistent view of consumer data, Condé Nast's team can now craft personalized content experiences across its brands rather than working from disconnected data sets. This unified approach supports higher consumer engagement and loyalty by letting the company respond to audience needs more precisely.
Condé Nast has accelerated time-to-insight and decision-making while improving the accuracy and consistency of its global reporting. The added agility also helps Essuman's team respond more quickly to shifting market trends and deliver content that resonates with a diverse global audience. Readers can find similar outcomes from other organizations in Databricks' customer success stories.
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