Observed Signal · Nov 22, 2024 · Educational / Case Study · Source: OnlineMarketing.de · Impact: 2/5 · Sentiment: Positive
Efficient Measurement with Marketing Mix Modelling
Marketing Mix Modelling (MMM) is presented as a statistical method that uses aggregated advertising spend and revenue data to optimally allocate future marketing budgets. A key advantage highlighted is that MMM does not require personal data, sidestepping Third-Party cookies debates. The article provides a practical case study from a fashion manufacturer, analyzing online revenue and online ad spend across Google Ads, Microsoft Ads, Paid Social, and a Brand digital budget, while excluding offline marketing. Data were collected over 22 months and aggregated weekly. The model achieved an R2 of 0.85, indicating a good fit. Notably, Paid Social accounted for 4.4% of costs and 10.5% of revenues; with a permissible budget variance up to 60%, spend could rise to 7% of the budget and be responsible for a 10.3% uplift in revenue. The piece emphasizes the need for substantial, multi-channel data and warns that limited data reduces accuracy, underscoring MMM’s potential to improve budget efficiency.
Educational article detailing Marketing Mix Modelling methodology with a real-case example; relevant to AdTech/MarTech practices.
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Key Takeaways & Evidence Grounding
- MMM is a statistical model using aggregated ad spend and revenue to optimize budget allocation.
- The model does not require personal data; it avoids Third-Party cookies.
- In the case study, data covered 22 months, focusing on online revenue and online ad spend only.
- R2 score achieved was 0.85, indicating a good model fit.
- Paid Social accounted for 4.4% of costs and 10.5% of revenues; with up to 60% budget variance, revenue uplift reached 10.3%.
Connected Companies & Entities
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Recent verified developments and strategic activity across this market segment.
Choosing a Marketing Mix Modeling (MMM) Tool
AdExchanger’s podcast episode discusses how marketers should choose a marketing mix modeling (MMM) solution, weighing the tradeoffs of using open-source, low-cost MMM tools built by Big Tech. The piece notes both Google and Meta have released MMM tooling (Google’s Meridian and Meta’s Robyn) and highlights concerns about conflicts of interest when measurement solutions are tied to companies that also sell performance advertising. The episode references James Hercher’s reporting comparing the two platforms and frames the decision as a balance between accessible measurement and potential platform influence.
Five Lessons from Marketing Mix Modelling for Marketers
An opinion piece by Tobin Thomas (CEO & Founder, Lifesight) published on VideoWeek argues that modern marketing mix modelling (MMM) corrects common measurement biases by capturing brand and cross-media effects that last-click attribution misses. The article lists five core insights: brand effects (TV/video/audio) are measurable via MMM; high ROAS channels can have low incremental value; channels interact as a system rather than acting independently; overspending can reduce marginal returns; and contemporary MMM is sufficiently advanced to support cross-media decision-making across CTV, video, social, retail media, search and offline channels. The author emphasizes acting on model outputs — including defunding beloved channels when models indicate low contribution — rather than simply decorating dashboards.
Microsoft Xbox creates new division for films, series, parks
Microsoft's Xbox gaming division announced the creation of a new business unit dedicated to films, television series, and theme park attractions. The move signals an expansion into entertainment and immersive experiences beyond video games, leveraging Xbox's intellectual property. This strategic diversification is part of Microsoft's broader ambition to grow its media and entertainment footprint, following trends seen across the industry. The new division will focus on developing and producing content based on Xbox franchises, potentially opening new revenue streams for the company. Financial details or a timeline for the division's operations have not been disclosed.
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