Hajime Takeda - Media Mix Modeling:How to Measure the Effectiveness of Advertising
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www.pydata.orgMedia Mix Modeling, also called
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Media Mix Modeling, also called Marketing Mix Modeling (MMM), is a technique that helps advertisers to quantify the impact of several marketing investments on sales.
If a company advertises in multiple media (TV, digital ads, magazines, etc.), how can we measure the effectiveness and make future budget allocation decisions? Traditionally, regression modeling has been used, but obtaining actionable insights with that approach has been challenging.
Recently, many researchers and data scientists have tackled this problem using Bayesian statistical approaches. For example, Google has published multiple papers about this topic.
In this talk, I will show the key concepts of a Bayesian approach to MMM, its implementation using Python, and practical tips.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVi...
Media Mix Modeling, also called Marketing Mix Modeling (MMM), is a technique that helps advertisers to quantify the impact of several marketing investments on sales.
If a company advertises in multiple media (TV, digital ads, magazines, etc.), how can we measure the effectiveness and make future budget allocation decisions? Traditionally, regression modeling has been used, but obtaining actionable insights with that approach has been challenging.
Recently, many researchers and data scientists have tackled this problem using Bayesian statistical approaches. For example, Google has published multiple papers about this topic.
In this talk, I will show the key concepts of a Bayesian approach to MMM, its implementation using Python, and practical tips.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVi...
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در تاریخ 1401/12/08 منتشر شده
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