Point-in-time tests vs. always-on incremental measurement
In today’s complex, privacy-conscious marketing environment, accurately measuring the impact of advertising spend is more critical than ever. Two common methodologies—incrementality testing and marketing mix modeling (MMM)—offer marketers distinct approaches to assess performance. However, the depth, sophistication, and actionable insights provided are worlds apart. This article explores the key differences between the two methods, highlighting the advanced capabilities of MMM and inherent limitations of incrementality tests.
Incrementality Testing: A Snapshot in Time
Incrementality testing is a straightforward method for assessing the additional lift or impact a specific channel or campaign has on business outcomes. These tests typically compare the performance of a treatment group (exposed to the campaign) with that of a control group (not exposed to the campaign).
What Incrementality Tests Offer
Incrementality testing provides an enhanced view beyond last-touch attribution or simple matchback tests. It indicates how incremental a particular channel or campaign is. For instance, a test might reveal that Google Ads contributes 70% incremental traffic to a website.
Inherent Limitations of Incrementality Tests
- Channel-Specific Focus: Incrementality tests are typically limited to assessing one or two channels at a time and may not account for interactions among numerous channels. If test results aren’t used carefully, actions taken on the results can be misguided, as marketing ecosystems rarely function in isolation.
- Point in Time: Incrementality tests are point-in-time tests, meaning they’re limited to a particular campaign time frame. Results are delivered post-campaign and become outdated—limiting the actionability window.
- Accounting for Cost Curves: Incrementality tests cannot account for diminishing returns. While it may be useful to know that a channel has strong incremental benefits, this alone doesn’t reveal whether the channel’s budget already exceeds its efficiency threshold, where every additional dollar spent has diminishing return on investment. A channel can be incremental, but not infinitely.
- Holistic Insights: These tests cannot fully consider external factors such as seasonality, economic conditions, or competitor actions. Consequently, marketers are left with a static snapshot rather than comprehensive understanding.
- Actionable Budget Guidance: Although incrementality tests provide evidence of a channel’s effectiveness, they lack the mathematical framework to suggest optimal budget allocation across multiple channels and media partners.
Marketing Mix Modeling (MMM): A Comprehensive Approach
Marketing mix modeling employs econometric techniques to evaluate the contribution of various marketing channels to business outcomes over time. By accounting for factors such as seasonality, market dynamics, and channel interdependencies, MMM offers a more sophisticated, data-driven approach.
What MMM Offers
- Cross-Channel Interplay: MMM excels at measuring the interactions (collinearity) among different marketing channels. For example, it can identify how search ads enhance the effectiveness of display ads, providing actionable, synergistic insights.
- Cost Efficiency: MMM analyzes cost curves, determining the point beyond which additional spend yields diminishing returns. This enables marketers to maximize ROI and avoid waste.
- Incorporation of External Factors: Unlike incrementality tests, MMM incorporates external influences such as seasonality, macroeconomic trends, and competitor actions, offering a robust analysis of marketing performance.
- Strategic Budget Allocation: With its detailed insights into channel performance and interdependencies, MMM guides marketers in optimizing budget allocation, ensuring that every dollar is spent efficiently and effectively.
- Always-On Incremental Measurement: Next-generation SaaS MMM platforms are now available that ingest performance data daily and offer model refreshes weekly. This provides marketers with readily available incremental insights to make quick optimization decisions in the fast-paced landscape of mobile user acquisition.
Real-World Example
Consider a retailer running ads across Google, Facebook, and Apple Search Ads. An incrementality test might show that Facebook Ads are 100% incremental, indicating strong performance. However, an MMM analysis could reveal that despite its high incrementality, Facebook Ads have surpassed their efficiency threshold. The analysis might suggest reallocating a percentage of spend to Apple Search Ads for better returns. Additionally, MMM could uncover how seasonality impacts each channel, enabling more precise planning.
Why MMM Is the Future of Marketing Measurement
Incrementality tests, while useful for quick insights, are akin to examining a single puzzle piece. MMM, on the other hand, assembles the entire puzzle, offering a comprehensive view of marketing performance. The mathematical rigor and computational sophistication underpinning MMM empower marketers to make informed, strategic decisions that drive sustainable growth.
Incrementality tests provide quick and interesting insights but are not intended to offer actionable or comprehensive guidance. Marketing mix modeling stands out as the gold standard for advanced marketers, delivering a nuanced understanding of channel dynamics, cost efficiencies, and external influences. In an era where precision is paramount, MMM is not just a tool—it’s a necessity for navigating today’s complex marketing landscape.
Interested in learning more about MMM? Check out the MMM 101 eBook or get in touch with our team.
