EPISODE · Nov 7, 2025 · 27 MIN
Will Parker: Marketing Mix Modeling, AI in Modeling and Data, & Why MMMs are Important
from The ForeCast · host Rain the Growth Agency
In this episode of The Forecast, host Morgan Willis speaks with @Will Parker, Chief Strategy Officer of @Leavened, about the intricacies of marketing measurement, particularly focusing on Marketing Mix Modeling (MMM). They discuss the differences between MMM and deterministic attribution, the challenges of real-time MMM, and the importance of integrating various measurement strategies. Will emphasizes the need for brands to hold all media accountable and the critical role of AI in enhancing marketing measurement. The conversation also touches on the importance of marketing expertise and the future of marketing measurement in a rapidly changing landscape.The ForeCast is a podcast by Rain the Growth Agency, hosted by Morgan Willis. In each episode, we speak with industry experts about advertising, media, and the latest marketing trends, and sometimes we have a bit of fun, too! We close out each episode with our guest’s forecast for the future of their area of expertise.Timestamps:00:00 Intro00:48 Understanding Marketing Mix Models (MMM)03:34 Real-Time Marketing Mix Modeling Challenges07:45 Integrating MMM with Deterministic Attribution10:55 The Importance of Marketing During Economic Downturns14:08 The Role of Upper Funnel Media17:12 Leveraging AI in Marketing Measurement19:59 The Need for Marketing Expertise23:18 Will’s ForecastPlease follow our podcast and leave a review!Our website: https://www.rainforgrowth.com/Follow us on social media!LinkedIn: https://www.linkedin.com/company/rainthegrowthagency/?viewAsMember=trueFacebook: https://www.facebook.com/RainTheGrowthAgencyInstagram: https://www.instagram.com/rainthegrowthagency/X: https://x.com/rainforgrowthYouTube: https://www.youtube.com/channel/UC7LlxqQWvCl5nPIJctIuiswTikTok: https://www.tiktok.com/@rainthegrowthagency
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Will Parker: Marketing Mix Modeling, AI in Modeling and Data, & Why MMMs are Important
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