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"Which channel is actually effective?"
As a marketer, you've probably asked yourself this question at least once. With third-party cookies disappearing and privacy regulations becoming stricter, accurately measuring marketing effectiveness is becoming increasingly challenging. With each channel having its own performance metrics, even consolidating data for analysis has become a major challenge.
Moreover, every Monday is spent exhausting ourselves compiling reports from each channel, leaving little time to discover important insights. In today's complex lead funnel, simply looking at ROAS and ROI metrics isn't enough to answer practical business questions like 'Should we invest more in this channel?' or 'Is this campaign really effective?'
A. The Seismic Shift in Marketing Measurement, 2025
Marketing is a fierce battle between input costs and conversion performance. That's why it's crucial to analyze how we approach consumers through different channels and understand the regression analysis of consumer behavior and conversions from those channels. In today's dark funnel era, where new advertising platforms emerge daily and customer purchase journeys can't be accurately tracked, last-click or multi-touch attribution are no longer reliable measurement metrics. (People have begun to question whether judging results based on just one or two ad clicks, while ignoring factors like brand awareness, word-of-mouth, and offline media campaigns that influence purchase decisions, actually helps improve advertising.)
That's why many global companies are seeking new alternatives to traditional marketing measurement models, with changes occurring in two main directions:
1. The Shift to Incrementality Measurement
The first is the transition to incrementality measurement. While 'incrementality measurement' might sound like a complex methodology, it simply answers the question, "What would have happened if we hadn't run this ad?" Here's an example:
This method allows for accurate measurement of advertising effectiveness. For instance, a global sports brand A used Google's Ads Data Hub to create similar cities for testing incremental ROI. By comparing test and control group performance in real-time, they accurately identified each channel's actual contribution. However, there are drawbacks. Currently, only Meta and Google offer extensive and detailed incremental measurement capabilities. Additionally, testing often involves significant costs.
2. The Revival of MMM (Media Mix Modeling)
According to EMARKETER's 2024 research, 61% of marketers plan to improve their measurement strategy through MMM. While previously considered outdated after the rise of attribution, MMM has made a comeback. This revival is driven by the introduction of app tracking transparency policies for user privacy protection, which has made it more difficult to collect user-level data for attribution measurement, making it more practical to look at overall marketing effectiveness.
Particularly, while traditional MMM required enormous resources for preprocessing vast amounts of data, recent developments like Google's Meridian and Meta's Robyn open-source MMM tools have made MMM accessible even to non-enterprise companies.
The advancement of AI and big data technology has modernized MMM, accelerating its revival. What previously took months to analyze can now be done through real-time data integration analysis. Technological progress has enabled automation of marketing data collection that was previously done manually:
Recent machine learning technology enables automatic learning of vast datasets and quick analysis and prediction based on algorithms. This has led many global companies to seek integrated performance metrics beyond simple ROAS. New measurement metrics have emerged with the growth of e-commerce. Most notably, 'ACOS' (Advertising Cost of Sales). ACOS, which originated from Amazon, looks at the proportion of advertising costs in total sales rather than just advertising returns.
Companies like Home Depot have gone further, using 'ROMO' (Return on Marketing Objectives). This looks beyond total sales metrics to include brand awareness and in-store market share.
2025's New Performance Metrics
B. But There's a Hidden Challenge
To properly utilize these new measurement methods, there's one prerequisite: 'data integration'.No matter how good an analysis methodology is, proper analysis is impossible if data is scattered across different locations. We need a system that can integrate and analyze data from Facebook, Google, Naver, and other platforms in real-time.
How Do We Start Data Integration?
To achieve effective data integration, we need to focus on three key elements.
First is building a real-time data integration system. The key is automatically collecting and integrating data from different platforms like Facebook, Google, and Naver. This allows comparing performance across all channels using unified metrics. Particularly, real-time monitoring enables immediate detection and action when advertising budgets are being wasted.
Second is cross-channel analysis automation. Since channels don't operate independently but create synergy and influence each other, understanding channel interactions is important. Through automated systems, you can calculate cross-channel incremental effects and receive AI-based optimal budget allocation recommendations. This goes beyond simply looking at individual channel ROAS to optimize marketing performance from an integrated perspective.
Finally, customized dashboard construction is necessary. No matter how good your data is, its value is diminished if you can't effectively visualize and share it. A dashboard that allows real-time monitoring of key KPIs and easy sharing of insights with team members is now essential, not optional. Especially for agencies, automating client report creation can dramatically reduce time spent on report preparation.
C. Conclusion
In 2025, marketing measurement technology is evolving rapidly. With AI technology advancements, data integration is becoming easier, and incrementality measurement and MMM are becoming more accurate.
The most notable point is that now small businesses and startups can perform this sophisticated analysis. You no longer need to hire data scientists – accurate marketing effect measurement is possible through automated systems.
Stop wasting time on data compilation and report creation. Start advanced marketing measurement through real-time data integration. Let systems handle the tedious work while we focus on what really matters - strategy development and creative campaign planning.
