You will analyze website crawlability using tools like Screaming Frog to identify and prioritize technical SEO errors. You’ll interpret Issues reports and determine corrective actions that ensure crawlers can access high-value content.

You will create in-depth content using keyword clusters to target specific search intent while meeting established quality standards. You’ll combine AI drafting with structured SEO practices to produce CMS-ready content.

You will evaluate written content using structured SEO checklists, focusing on EEAT, metadata, schema, and internal linking. You’ll assess content against quality benchmarks to improve authority and performance.

You will create strategic pillar–spoke content clusters designed to secure citations in LLM-generated responses. You’ll structure editorial plans that improve visibility and authority across AI-powered search tools.

You will analyze attribution reports to identify which content generates the most keyword mentions and visibility. You’ll translate performance insights into actionable editorial strategies.

You will apply custom event tracking to make AI referral traffic visible within analytics platforms. You’ll configure and visualize referral sources to better understand AI-driven user behavior.

You will evaluate funnel data to identify where LLM-sourced users drop off in the customer journey. You’ll interpret retention patterns and propose optimization strategies to improve performance.

You will apply GA4 exploration features to segment traffic sources and analyze user behavior metrics. You’ll interpret engagement patterns and identify meaningful audience insights.

You will evaluate a Google Analytics 4 property to detect tagging errors and propose corrective actions. You’ll audit events, confirm data accuracy, and improve reporting reliability.

You will create a KPI dashboard that integrates impressions, citations, and conversions from generative engines. You’ll consolidate data from GA4, Google Search Console, and SGE into a unified reporting framework.

You will evaluate key performance indicators using variance analysis to explain significant changes. You’ll propose corrective actions and automate reporting workflows to support data-driven decision-making

You will analyze datasets to identify and visualize correlations between SEO and business metrics. You’ll interpret patterns in impressions, click-through rates, and conversions to uncover performance drivers.

You will evaluate meta-description A/B test results using statistical analysis to determine the winning version. You’ll apply chi-square testing methods to make confident, data-driven optimization decisions.

In this project, you will evaluate and optimize AI-driven SEO performance using content visibility analysis, traffic flow evaluation, citation assessment, GA4 diagnostics, and KPI framework optimization. Rather than configuring tools or building dashboards, you will interpret existing performance data to understand how AI-optimized content performs across discovery, engagement, and conversion stages. You will identify measurement gaps, diagnose performance issues, and recommend targeted optimization and scaling actions based on evidence from realistic reporting snapshots. The project reflects the responsibilities of a senior SEO or growth analyst and results in a structured, portfolio-ready performance analysis and optimization strategy suitable for executive decision-making.