Turning Audience Data into Meaningful Insights

American publishing icon Condé Nast embarked on a mission to use deep analysis of customer behavioral data to drive user engagement and improve subscription rates. 

To achieve this, it needed a database that could process a large volume of user data quickly and in real-time and achieve high performance at scale without breaking the bank. 

Diginomica Exclusive: Condé Nast on the pursuit of customer experience at web-scale, with DataStax Enterprise

Conde Nast
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"We noticed DataStax was, of course, on top of Cassandra. I wanted to do the benchmark using Cassandra or DynamoDB. That started the story. We saw that for our volume of traffic, DynamoDB was more convenient for lower traffic, but for the volume of traffic we are aiming to, Cassandra was much more convenient. So after a certain point, the DataStax solution was not only more effective in terms of performance, but also cheaper in terms of cost."

Antonino Rau

Director Data Engineering & Intelligence, Condé Nast

The Opportunity

An American mass media company with more than 164 million consumers across 19 brands, including WiredVogueGQ, andVanity Fair, Condé Nast saw a chance to improve audience engagement using the vast array of user behavior flowing into its databases.

To learn how to better engage its customers, Condé Nast launched a multivariate testing initiative with the goal of fully understanding its user base and the types of content, web layouts, and visual displays that appeal to each target segment.

Condé Nast also wanted to leverage the data gathered in its multivariate testing initiative to provide personalized content and recommendations to web visitors, which they hoped would translate to a more engaging experience and increased online subscribers.

The Solution

The Results


Improvement in digital click-through rate


Milliseconds response time for 7,800 requests per minute


Faster data reprocessing time for the new Feature Store