MARKETING ANALYTICS CASE STUDY
Paid Publisher Benchmark Framework
Turning four years of paid publisher campaign data into meaningful performance benchmarks to help teams better understand results, improve reporting, and make smarter marketing decisions.
Project Overview
Turning campaign data into meaningful benchmarks.
The Literacy team had four years of paid publisher campaign data, but no consistent way to compare performance across publishers, newsletters, and content types. I developed a benchmarking framework to organize that data, identify meaningful performance trends, and make future campaign evaluations more consistent.
Why It Matters
Better benchmarks lead to better decisions.
Campaign results don't tell the whole story on their own. By creating clearer performance benchmarks, I helped give the team a more reliable way to evaluate channel performance, identify opportunities, and make informed decisions about future publisher placements and marketing investments.
Key Highlights
Analyzed four years of paid publisher campaign data to uncover performance patterns and create a clearer picture of historical channel results.
Historical Performance Analysis
Built a structured framework to compare performance across publishers, newsletters, and content types, making campaign reporting more consistent and actionable.
Performance Benchmarking
Data-Driven Insights
Turned campaign performance trends into practical insights to support reporting, optimization, publisher strategy, and future media planning.
EXPLORE THE FULL PROJECT
See the framework in action.
Curious how four years of campaign data became a more useful reporting tool? Explore the full case study to see my approach to performance benchmarking, the insights uncovered, and how the framework helped support better campaign decisions.
Anonymized portfolio case study. No proprietary campaign tables, customer data, publisher-level results, or confidential internal materials are displayed.