Season 4, Episode 13: Changing attitudes on marketing measurement (with Maor Sadra)
Nov 26, 2024
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Maor Sadra, CEO of INCRMNTAL, dives into the shifting landscape of marketing measurement. He discusses the evolving perception of media mix modeling and its limitations compared to incrementality measurement. The conversation highlights trends in user acquisition budgets, particularly the increasing relevance of web platforms. Sadra also explores the impact of AI on marketing strategies and the challenges advertisers face in adapting their methods, including the integration of new technologies while navigating privacy concerns.
Incrementality measurement offers a real-time method to evaluate marketing effectiveness without relying on traditional user-level data.
Recent shifts in attitudes toward media mix modeling highlight a growing skepticism among app marketers regarding its immediate performance benefits.
The increasing role of AI in marketing measurement emphasizes the need for advertisers to adopt data-driven strategies for improved targeting and campaign adjustments.
Deep dives
Understanding Incrementality Measurement
Incrementality measurement represents a fresh approach to evaluating marketing effectiveness without relying on user-level data or planned experiments. This method, pioneered by Incremental, offers an alternative to traditional metrics that often yield delayed or ambiguous results. Its continuous nature allows marketers to gather insights regarding their campaigns in real time. By focusing on the effectiveness of marketing spend rather than just click data, incrementality can bring a more reliable understanding of advertising impacts.
The Trade-Offs in Measurement Methodologies
The podcast delves into the complexities of three primary measurement methodologies: media mix modeling (MMM), experimentation, and click attribution. Each method has unique strengths and weaknesses regarding granularity, privacy compliance, and predictive capabilities. While MMM is often touted for scenario planning, its correlation-based approach does not inherently demonstrate causation, which can lead to misconceptions about its effectiveness. Understanding these differences and choosing the right method for specific marketing goals is crucial for accurate performance measurement.
Shifts in Attitudes Toward Media Mix Modeling
Recent attitudes towards media mix modeling have seen a noticeable shift, particularly among app marketers. Initially embraced as a solution following significant changes in privacy regulations, many companies have expressed disappointment in its ability to deliver what was promised—particularly in terms of immediate performance metrics. As a calibration process, MMM requires patience and understanding of its long-term benefits, rather than expecting rapid results consistent with other methodologies like click attribution. The misunderstanding around its use has led to skepticism, overshadowing its potential when properly implemented within the right context.
Budget Allocation Trends in Digital Advertising
Current trends indicate that budget allocations primarily favor traditional giants, Google and Meta, despite the exploration of newer platforms like TikTok and CTV. Within the gaming sector, advertisers are increasingly relying on the established major players due to their proven track record. Experimental channels such as CTV show promise but remain a smaller part of overall spend compared to these mainstream options. As marketers assess their budgets, aligning with platforms that demonstrate consistent return on ad spend remains paramount.
The Role of AI in Advertising Measurement
Artificial intelligence is becoming increasingly integral in optimizing advertising strategies by enhancing targeting and measurement capabilities. The application of AI can facilitate smarter decision-making and refine audience targeting based on extensive data analytics, guiding marketers in campaign adjustments. Agility in adopting AI-driven strategies is essential for advertisers seeking to stay competitive within a rapidly evolving landscape. As AI technologies mature, they promise to reshape the way marketing measurement is approached and executed.
In this episode of the Mobile Dev Memo podcast, I speak to returning guest Maor Sadra, the CEO of INCRMNTAL, about changing attitudes toward marketing measurement. The catalyst for this conversation was a set of diagrams that Maor recently published on the INCRMNTAL blog, ranking various marketing measurement methodologies across a number of features.
In this episode, we discuss:
The tradeoffs inherent in the above spiderweb diagram;
Whether and how app advertisers implement experiments in their marketing;
The popularity of media mix modeling in the app advertising ecosystem and whether enthusiasm for it has changed;
Trends in the composition of user acquisition budgets by channel for app advertisers;
Whether budget is shifting meaningfully to the web for app advertisers;
The gaps in measurement that app advertisers struggle to close;
Whether budgets are increasing on Meta and Google as their AI-empowered solutions expand;
How AI plays a role in marketing measurement.
Thanks to the sponsors of this week’s episode of the Mobile Dev Memo podcast:
Vibe. Vibe is the leading Streaming TV ad platform for small and medium-sized businesses looking for actionable advertising campaign performance.
Clarisights. Marketing analytics that makes it easy to get answers, iterate fast, and show the impact of your work. Go to clarisights.com/demo to try it out for free.
INCRMNTAL. True attribution measures incrementality, always on.
Interested in sponsoring the Mobile Dev Memo podcast? Contact Marketecture.
