『Data and Marketing Nation』のカバーアート

Data and Marketing Nation

Data and Marketing Nation

著者： Dimitri Visnadi
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 Looking to stay up-to-date on all things data and marketing? Look no further than Data and Marketing Nation! The podcast is hosted by Dimitri Visnadi, data consultant. The podcast features interviews with industry experts who dish on ideas, trends, and insights. From data strategy to email marketing to measurement and everything in between, you’ll be sure to find something helpful and entertaining. So whether you’re a marketing pro or just looking to learn more about the industry, tune in to Data and Marketing Nation.Dimitri Visnadi 経済学
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  • DAMN 13: Designing Geo-experiments at Google with Christoph Best

    DAMN 13: Designing Geo-experiments at Google with Christoph Best
    2023/02/23

    Christoph Best is a Data Scientist at Google who tries to answer the question: Does advertising work? Generally, it's easier to evaluate online advertising performance than offline. In this episode, Christoph talks about his approach how to run geo-experiments, their importance and his overall experience running such experiments. Moreover, he touches upon general marketing terms such as Mix Modeling and Attribution Modeling in order to bring all theses topics into context.
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    39 分
  • DAMN 12: Creating Dashboards People Use with Alex Kolokolov

    DAMN 12: Creating Dashboards People Use with Alex Kolokolov
    2023/01/29

    Alex Kolokolov is an expert on dashboard creation. In fact, he is in the business of selling dashboards. In this episode, he shares his process of creating a dashboard that people use.
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    35 分
  • DAMN 11: Attribution at Spinger Nature with Nina Meinel

    DAMN 11: Attribution at Spinger Nature with Nina Meinel
    2022/12/23

    Nina Meinel is a Senior Data Scientist at Springer Nature and a wonderful person to talk to about Marketing Data Science. She combines many years of research and industry experience with Marketing data. Nina shares how she and her team at Springer Nature tackle the complicated attribution problem.   
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    34 分
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