New in MMM: Capturing Delayed Advertising Effects
Gabriel Mohanna
Founder and CEO of the Most Innovative Marketing Mix Modeling Company | Data Science, AI, ML
In advertising, customers rarely see an ad and immediately make a purchase. While some may convert within minutes, others might take weeks or even months. This lag becomes more pronounced as the purchase price increases - a phenomenon particularly evident in industries like automotive. In this article, we explore how modern Marketing Mix Modeling (MMM) incorporates this delayed effect using a transformative approach called the Weibull transformation, revolutionizing the way advertisers measure the delayed and long-lasting impacts of their campaigns.
Traditional MMM
Before diving into the Weibull transformation, let’s revisit how traditional MMM captures advertising effects. Traditional models often rely on the geometric adstock transformation, which assumes an immediate impact followed by a consistent decline. While effective for simple scenarios, this approach doesn’t account for delayed or intricate advertising dynamics, such as the long-term influence of upper-funnel campaigns like TV ads.
We covered this geometric adstock model in a previous article. But for simplicity, it assumes that advertising effects fade predictably and immediately—a limitation for campaigns where delayed response plays a critical role.
Moving Towards Modered MMM with Weibull Adstock
A newer and more advanced solution to this challenge is the Weibull transformation. Unlike the geometric model, the Weibull transformation introduces flexibility by capturing both the delayed effect and gradual decay of advertising impact. This makes it an ideal choice for real-world applications, where campaign responses often unfold over time.
Key Parameters of the Weibull Transformation:
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This dynamic structure enables marketers to tailor MMM to match campaign behavior, whether for short-term promotions or prolonged brand-building activities.
Business Impact
For marketing teams, using the Weibull transformation means:
Example in Action
Consider a luxury automotive brand running a TV campaign to build awareness for a new model. Traditional adstock models may underestimate the delayed sales impact, leading to suboptimal budget allocation. By applying the Weibull transformation, the brand can:
Take the Next Step with MMM Labs
At MMM Labs, we are at the forefront of modernizing Marketing Mix Modeling. By integrating advanced transformations like the Weibull into our platform, we’re building tools that make it easier for businesses to measure, optimize, and plan their advertising strategies. Our mission is to bring these innovations to market, making MMM more accessible, actionable, and impactful for advertisers everywhere. Book a demo today to learn how MMM Labs can transform your marketing strategy.
This article was written in collaboration with Romzy Safadi and edited by Gabriel Mohanna. See the full code on our GitHub page.
Marketing & Media Leader || mMBA Marketing & Brand Management | Exited Founder
2 个月Can you help me understand why the delay in impact after ad exposure? What is theory and science here? And is the delay in impact different per channel?
Group Media Manager @Stena Line
2 个月It's a verry interesting way of looking at a challenge that all incrementallity solutions has. How long will the model attribute sales for upper funnel channels - at some point the exposure is not relevant any more? Also since we have challenges getting compeditor spends for online channels, the longer delay effect you accept the higher risk of compeditor activites challenging the modell. Maybe Fredrik Hallberg you have experience in these challenges?
?? Senior Marketer Making Strategies Work ★ P&L Hitter ? SO…GET IN TOUCH NOW!
2 个月Insightful
We bring scientific evidence to business decisions
2 个月An advertising exposure typically has a half-life of three to four weeks. And advertisers counter this decay by being always-on with the maximum weekly reach the budget allows.??
Growth & Marketing - Realeyes Vision AI, Advertising, Attention Measurement
2 个月Where is the creative input in your model?