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Blurbs comparison of Measured and Peq
Learn about how these Ad Measurement & Attribution vendors stack up against each other by checking out our blurbs, claims, and case studies.
Measured
"Optimizes marketing budgets with incrementality testing."
Focused on Incrementality and Media Mix Modeling (MMM) .
Measured assists marketers by offering a platform that focuses on incrementality testing to maximize media budget ROI. It helps marketers identify the true impact of every media dollar, find cost-effective spending cuts, and reallocates resources for better efficiency. It avoids reliance on complex models or cookies, prioritizing clarity and actionable insights.
Automated geo experimentation
Measured claims that their platform is the industry's first fully-automated, geo experimentation solution for incrementality measurement.
Revolutionary measurement approach
Measured claims that their approach combines incrementality testing with media mix modeling, a revolutionary way to measure media.
Full-funnel media optimization
Measured claims their comprehensive workflow is designed to optimize the entire media portfolio from beginning to end.
Peq
"Optimize spend by analyzing sales-impacting actions."
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This solution assesses which marketing actions boost sales most effectively, guiding where to allocate your marketing budget efficiently. Utilizing AI, it compares different efforts' impacts, simplifying decision-making across marketing channels like retail media, digital, trade, and brand marketing. The platform is user-friendly, requiring no extensive training, and is accessible via a website login, providing data on demand.
Simplifies budget allocation decisions
Pēq claims that their platform identifies the best marketing activations, removing guesswork from budget allocation.
User-friendly platform access
Pēq claims that their platform requires no downloads and is accessible anytime, anywhere for easy data access.
AI-driven performance comparison
Pēq claims that their platform uses AI to compare retail sales data, enabling precise performance evaluation.