L’hybridation des données chez Moët Hennessy

Data Hybridization at Moët Hennessy - Interview with Sandrine Martin

June 26, 2024

On April 23 and 24, Saas Advisor, in partnership with Audiense, hosted "Hybrid," the first Social Media event in France dedicated to data hybridization. The event, held both online and in person, featured many high-profile guests and was as engaging as it was enriching.

On this occasion, Sandrine Martin, Head of Social Intelligence, answered our social media questions.

How does data hybridization manifest at Moët Hennessy?

"Data hybridization is manifested through dashboards that incorporate various data sets to address specific questions. These dashboards are designed with precise storytelling so that each dataset finds its place within the insights and can address these business questions."

What has impressed you most about the evolution of consumer data in recent years?

"Artificial intelligence! And the ease of access to data. This has truly impressed me. In just a few months, there have been many advancements that have greatly facilitated data interpretation."

What will be your main Social Media challenges in 2024 at Moët Hennessy?

"Insight. It's about giving meaning to this data and data hybridization, answering more strategic questions, and ensuring that we not only look at KPIs but also interpret the data and make sure it provides insights for the business."

What role does artificial intelligence play in your Social Media strategy?

"My department focuses on insights, so it will be about data interpretation: explaining what is happening on specific charts and reducing the time spent explaining graphs. Ideally, a regular user could access the platform and understand the dashboards with the help of artificial intelligence or even ask questions to receive AI-generated answers."

What are the main advantages and limitations of data hybridization for marketing professionals, in your opinion?

"The main advantage is having clearer, more granular responses. The limitation is having too much data and not knowing which data to use to answer our questions."

 

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The Saas Advisor Team


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