Education Website Analytics & Optimization

Traffic Sources Analysis & SEO

To lay the groundwork for understanding user behavior, I begin by segmenting the audience based on their traffic sources and analyzing how each group interacts with the website. Using tools like Google Analytics for traffic breakdowns and SEMrush for keyword research, I assess the performance of different channels. I also benchmark these findings against industry standards and competitors using platforms like SimilarWeb and SEMrush.

For this project, I identified that direct and organic traffic were the primary sources, which aligns with industry norms. A significant volume of direct traffic often raises concerns about tracking discrepancies. However, a deeper analysis of landing pages revealed that the majority of this traffic was from returning users accessing their accounts—an expected and healthy trend.

Referral traffic analysis further uncovered insights about a specific user segment that warranted closer attention. Organic traffic, which showed higher engagement rates, emerged as a key opportunity for optimization. Competitor benchmarking revealed a gap: while none of the main competitors had strong organic strategies, this channel had clear potential to drive growth. By identifying high-potential topics and keywords, I outlined opportunities for SEO improvements that could provide a competitive edge.

To ensure ongoing monitoring and actionable reporting, I usually create custom dashboards using tools like Google Looker Studio or DashThis. For this project, I utilized DashThis to enable key stakeholders to track performance over time, measure the impact of strategic decisions, and adjust tactics as necessary.

User Behavior on Site & User Flows

Understanding how users navigate through a website is essential for identifying friction points and areas for optimization. For this project, I utilized tools like heatmaps, screen recordings, and funnel analysis to gain detailed insights into user behavior. These methods allowed me to observe where users clicked, how they scrolled, and where they dropped off during key processes, such as signing up or exploring content.

By analyzing user flows, I identified patterns and potential obstacles in navigation. For instance, certain pages with critical information were receiving less engagement than expected due to unclear call-to-actions or overly complex pathways. Additionally, drop-offs in the sign-up funnel revealed opportunities to streamline the process and reduce user frustration.

I also analyzed the site’s top-performing pages to understand why they were successful and what this revealed about user interests and behavior. This analysis helped identify the content and layouts that resonated most with users, providing a model for optimizing underperforming pages.

The analysis also revealed that the menu served as the primary navigation tool for most users. However, the site’s vast amount of content and diverse program offerings, coupled with the absence of a site search feature, often made it challenging for users to find what they needed. This highlighted the need for improved navigation and content organization.

Based on these insights, I provided recommendations to optimize the site’s navigation and taxonomy to ensure users could access relevant information more intuitively. Additionally, I suggested introducing a robust site search feature, including exploring AI-powered solutions, to enhance discoverability. Finally, I proposed the development of an interactive program-finding tool to help users quickly locate programs suited to their needs. These suggestions were presented in actionable reports, providing clear guidance for improving the user experience.