Topic: marketing mix modeling
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3 PPC Myths That Could Cost You in 2026
Successful PPC in 2026 will prioritize disciplined execution and business fundamentals over chasing platform narratives, as over-reliance on automation in 2025 often increased budgets without improving efficiency. AI targeting is not universally superior; its effectiveness depends on high-quality...
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Top MMM Tools Compared: Meridian vs. Robyn vs. Orbit vs. Prophet
The marketing mix modeling landscape now includes powerful open-source tools like Google's Meridian and Meta's Robyn, which are comprehensive, production-ready systems that automate complex analysis to directly output budget recommendations. Robyn is noted for its accessibility, using automation ...
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5 Essential Marketing Measurement Strategies for 2026
Marketing teams must move beyond fragmented reports to build a unified measurement framework that connects data, adds context, and integrates with business planning to drive confident decisions. Effective measurement requires incorporating real-world context—like competitor moves and consumer sen...
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Marketing Mix Modeling's Real Issue: Adoption, Not Tech
The primary obstacle for marketing mix modeling (MMM) is not technical but organizational, as companies often fail to act on insights due to outdated processes and a lack of continuous, integrated strategy. Effective MMM requires cross-functional ownership, transparent data practices, and faster ...
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Ditch Click Attribution for Smarter Executive Dashboards
Relying solely on click-based attribution creates strategic blind spots, as it fails to capture the full multi-channel customer journey and can lead to misallocated budgets and undervalued brand-building efforts. Over-dependence on clicks skews investment toward short-term, lower-funnel tactics, ...
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Avoid These Marketing Mix Modeling Mistakes That Hurt ROI
Marketing mix modeling (MMM) is essential for measuring campaign effectiveness across channels, especially with increasing privacy restrictions limiting user-level tracking. Common implementation errors include using inconsistent data, misinterpreting correlations as causation, and applying MMM f...
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Marketers' Trust in Measurement Stagnates
Marketers' confidence in performance measurement tools has stalled, with many reporting no improvement or a decline in trust, and internal skepticism often leads colleagues to question the validity of reported metrics. Key obstacles to precise measurement include siloed and incomplete data, chall...
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MMM: Why It Scares Marketers & Why You Need It
Marketing mix modeling (MMM) is a contentious tool in marketing, with enthusiasts seeing it as a solution to attribution issues and skeptics recalling flawed implementations due to conflicts of interest. MMM is regaining relevance due to privacy regulations and tracking restrictions, as it doesn'...
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