Creating a Strategic Framework for Content Prioritization
As AI began reshaping digital search, optimizing every webpage was no longer practical or necessary. I developed a prioritization framework that helped identify the organization's highest-value content, enabling future optimization efforts to focus on the pages most likely to deliver strategic impact.
The Challenge
Large organizations often manage thousands of webpages, making comprehensive content optimization both time-consuming and resource intensive.
As AI-generated search experiences became increasingly common, I recognized the need to determine which pages should be prioritized for optimization rather than attempting to improve every page equally.
The challenge was not simply analyzing website data.
It was defining what "important" actually meant.
My Approach
While completing an MBA project, I became interested in the RFM (Recency, Frequency, Monetary) framework commonly used to segment customers.
I recognized that the same concept could potentially be adapted to website content.
Because the organization was not a commercial business, the Monetary component was not applicable. After evaluating several alternatives, I replaced it with Engagement, creating a new prioritization framework based on Recency, Frequency, and Engagement (RFE).
I designed the methodology from the ground up, including data preparation, Power Query transformations, scoring logic, Excel dashboards, and executive presentation materials.
Considerable effort was devoted to ensuring the framework produced meaningful results. This included cleaning duplicate URLs, evaluating English and French content fairly, selecting the most appropriate engagement metrics, and validating the methodology before presenting the findings.
The resulting framework later became an important input into broader AI optimization recommendations by identifying the pages that should receive priority attention.
Key Contributions
Designed the RFE prioritization framework
Adapted an existing business model to a new application
Developed data preparation workflows using Power Query
Built dashboards and executive reporting
Identified strategic content optimization priorities
Connected content prioritization with AI strategy
Results
The framework provided leadership with a structured methodology for prioritizing content optimization efforts based on business value rather than intuition alone.
It also became a foundational component of future AI visibility recommendations by identifying the pages most likely to benefit from optimization for AI-generated search experiences.
Lessons Learned
Not every initiative can receive the same level of attention.
Strategic planning often begins by determining where limited resources will create the greatest impact.
This project reinforced the value of adapting proven business concepts to solve new organizational challenges while using data to support prioritization and decision-making.
Skills Demonstrated
Strategic Planning • Prioritization • Innovation • Performance Measurement • Power Query • Data Analysis • Decision Support • Digital Strategy