Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
39th (2025)
Session ID : 4D3-OS-33c-05
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Overcoming the Challenges of Outsourced MMM: A Path to In-House Transparency
*Takeshi MATSUMOTOKatsuyuki ARIINatsumi SASAGAWA
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

Outsourcing Marketing Mix Modeling (MMM) presents significant challenges, particularly the lack of transparency in algorithms. Common methods like path analysis and regression often fail to capture the complexity of time-series data, risking reduced accuracy in performance measurement. Additionally, non-disclosure of algorithmic details prevents marketers from explaining discrepancies or requesting improvements when results seem inconsistent. Further issues include long lead times, often taking months, and high costs. This presentation introduces an approach to address these challenges through in-house implementation. By ensuring algorithm transparency, enhancing analytical accuracy, and enabling faster feedback, we demonstrate practical solutions and key considerations with real-world examples.

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© 2025 The Japanese Society for Artificial Intelligence
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